Encrypted D3.4 SYNER-G Fragility functions for gas and oil ...

D 3.4

DELIVERABLE

PROJECT INFORMATION

Project Title: Systemic Seismic Vulnerability and Risk Analysis for

Buildings, Lifeline Networks and Infrastructures Safety Gain

Acronym: SYNER-G

Project N°: 244061

Call N°: FP7-ENV-2009-1

Project start: 01 November 2009

Duration: 36 months

DELIVERABLE INFORMATION

Deliverable Title: D3.4 – Fragility functions for gas and oil system networks

Date of issue: 31 October 2010

Work Package: WP3 – Fragility functions of elements at risk

Deliverable/Task Leader: Bureau de Recherches Geologiques et Minieres (BRGM)

Reviewer: University of Rome La Sapienza (UROMA)

REVISION: Final

Project Coordinator:

Institution:

e-mail:

fax:

telephone:

Prof. Kyriazis Pitilakis

Aristotle University of Thessaloniki

[email protected]

+ 30 2310 995619

+ 30 2310 995693

i

Abstract

In the frame of SYNER-G Work Package 3 – Fragility functions of elements at risk –

and Task 3.2 (Fragility functions for utility system networks), the present deliverable

aims at presenting fragility curves for components of gas and oil system networks

(Sub-Task 3.2.2). These fragility functions need to be applicable to the specific

European context and they are intended to be integrated to the general evaluation of

the systemic vulnerability. The following network components are considered: buried

pipelines, storage tanks and processing facilities (including compression stations,

pumping stations). Based on a literature review, it is found that the available fragility

functions are mostly empirical and should be applied to the European context, given

the current lack of data needed to validate potential analytical methods of

vulnerability assessment. For buried pipelines, fragility relations from (ALA, 2001)

are selected, with respect to both wave propagation and ground failure. The curves

from the HAZUS methodology (NIBS, 2004) may be used for storage tanks and

compression stations, as these facilities are decomposed into a fault-tree analysis.

Gas network, Oil network, Fragility curves, Empirical relations

iii

Acknowledgments

The research leading to these results has received funding from the European

Community's Seventh Framework Programme [FP7/2007-2013] under grant

agreement n° 244061

v

Deliverable Contributors

BRGM Pierre Gehl

Arnaud Reveillere

Nicolas Desramaut

Hormoz Modaressi

AUTH Kalliopi Kakderi

Sotiris Argyroudis

Kyriazis Pitilakis

Maria Alexoudi

vii

Table of Contents

1 Introduction........................................................................................................................................ 1

2 Oil and gas systems in Europe .......................................................................................................... 1

2.1 NATURAL GAS SYSTEM............................................................................................ 1

2.1.1 Production Facilities and Extra European supply sources............................... 2

2.1.2 Tank Farms...................................................................................................... 2

2.1.3 Natural Gas Pipelines ...................................................................................... 3

2.1.4 Stations............................................................................................................ 4

2.2 OIL SYSTEM ............................................................................................................... 4

2.2.1 Refineries......................................................................................................... 4

2.2.2 Oil Pipelines..................................................................................................... 5

2.2.3 Pumping Plants................................................................................................ 5

2.2.4 Tank Farms...................................................................................................... 5

3 Past ear thquake damages on system elements ................................................................................ 7

3.1 PHYSICAL DAMAGES / MAIN CAUSES OF DAMAGE.............................................. 7

3.1.1 Buried pipelines damages ............................................................................... 7

3.1.2 Storage tanks damages................................................................................... 8

3.1.3 Processing facilities damages ......................................................................... 9

3.2 CLASSIFICATION OF FAILURE MODES / DIRECT LOSSES ................................. 10

3.2.1 Pipeline failure modes ................................................................................... 10

3.2.2 Tanks failure modes ...................................................................................... 11

3.2.3 Support facilities failure modes...................................................................... 13

4 Methodology for the vulnerability assessment of system elements ............................................. 15

4.1 IDENTIFICATION OF THE MAIN TYPOLOGIES ...................................................... 15

4.1.1 Pipelines ........................................................................................................ 15

4.1.2 Tank farms..................................................................................................... 17

4.1.3 Stations.......................................................................................................... 17

4.2 GENERAL DESCRIPTION OF EXISTING METHODOLOGIES................................ 20

4.2.1 Empirical relations ......................................................................................... 20

4.2.2 Bayesian approach ........................................................................................ 21

4.2.3 Analytical approach ....................................................................................... 21

4.2.4 Fault-tree analysis (for support facilities) ....................................................... 22

viii

4.3 DAMAGE STATES .................................................................................................... 24

4.3.1 Pipeline components ..................................................................................... 24

4.3.2 Storage tanks................................................................................................. 25

4.3.3 Processing facilities (pumping / compressor stations) ................................... 28

4.4 INTENSITY INDEXES ............................................................................................... 30


4.4.2 Storage tanks................................................................................................. 33

4.4.3 Processing facilities ....................................................................................... 33

5 Fragility functions for system elements ......................................................................................... 35

5.1 STATE-OF-THE-ART FRAGILITY CURVES PER COMPONENT ............................ 35


5.1.2 Storage tanks................................................................................................. 47


5.2 VALIDATION / ADAPTATION / IMPROVEMENT...................................................... 57


5.2.2 Storage tanks................................................................................................. 58


5.3 FINAL PROPOSAL .................................................................................................... 58


5.3.2 Storage tanks................................................................................................. 63


6 Analytical expressions of fragility functions.................................................................................. 69

6.1 PIPELINE COMPONENTS ........................................................................................ 69

6.1.1 Wave propagation.......................................................................................... 69

6.1.2 Permanent ground deformation ..................................................................... 70

6.2 STORAGE TANKS .................................................................................................... 71

6.3 PROCESSING FACILITIES....................................................................................... 72

6.3.1 Pumping / compressor stations ..................................................................... 72

6.3.2 Re.Mi cabins .................................................................................................. 73

6.3.3 GRF reduction groups ................................................................................... 73

ix

List of Figures

Figure 1 Schema of a gas system. ........................................................................................ 1

Figure 2: Overview. Gas in Europe (Nies, 2008). ................................................................... 2

Figure 3 Pipeline damage in (a) perpendicular and (b) parallel crossings of a lateral spread

(Rauch, 1997)...................................................................................................... 8

Figure 4 Continuous steel pipeline (source: FULCRUM DYNAMICS, LLC) ........................ 10

Figure 5 Segmented concrete pipeline and rubber gasket joint (Kim et al., 2010) .............. 11

Figure 6 Common failure modes for steel tanks (a) sloshing damage to the upper shell (b)

pipe connection failure (c) elephant's foot buckling (Berahman & Behnamfar,

2007) ................................................................................................................. 12

Figure 7 RE.MI cabin in the L'Aquila area: outside view (courtesy of Enel Rete Gas) ........ 19

Figure 8 RE.MI cabin in the L'Aquila area: inside view (courtesy of Enel rete Gas) ............ 19

Figure 9 View of a reduction group as used in the L'Aquila area (courtesy of Enel Rete Gas)

........................................................................................................................... 20

Figure 10 Decomposition of a compressor station into a fault-tree...................................... 23

Figure 11 Example of a fault-tree for an anchored steel tank failure modes (ALA, 2001) ... 27

Figure 12 Empirical correlation between PGS (strain) anf maximum horizontal PGV

(Paolucci & Pitilakis, 2007) ................................................................................ 31

Figure 13 Strain vs Repair rate correlation, for both wave propagation and permanent

ground displacement (O’Rourke & Deyoe, 2004).............................................. 32

Figure 14 Pipeline fragility data of Katayama et al. (1975) as presented by O'Rourke & Liu

(1999) ................................................................................................................ 37

Figure 15 Bilinear pipeline fragility relations by (Eguchi, 1991) ........................................... 38

Figure 16 Fragility relations of Barenberg (1988) and O'Rourke & Ayala (1993)................. 39

Figure 17 Fragility function by Eidinger et al. (1995, 1998), for all data............................... 40

Figure 18 Fragility relations by Isoyama et al. (2000), for both PGA (a) and PGV (b)

parameters, without corrective factors............................................................... 42

Figure 19 "Backbone curve" proposed by ALA (2001), representing the median repair rate

of all data points, and the corresponding 16th and 84th quantiles. ..................... 43

Figure 20 Fragility relations proposed by (Eguchi, 1983) for fault ruptures ......................... 46

Figure 21 Fragility curves of Berahman & Behnamfar (2007), for DS2................................ 49



x

Figure 24 Fitted surface for fragility median µ...................................................................... 51

Figure 25 Fitted surface for fragility standard deviation く .................................................... 52

Figure 26 Fault-tree analysis proposed by HAZUS (NIBS, 2004) to assess the vulnerabiltiy

of tank farms...................................................................................................... 53

Figure 27 Fragility curves for gas pumping / compression stations (anchored components)

proposed by Risk-UE (Alexoudi & Pitilakis, 2003)............................................. 56

Figure 28 Fragility curves for gas pumping / compression stations (unanchored

components) proposed by Risk-UE (Alexoudi & Pitilakis, 2003) ....................... 57

Figure 29 Comparison of the pipeline fragility relations for PGV. Arrows refer to the range of

applicability of a given relation, approximated from knowledge of the dataset

from which it wa derived (Tromans, 2004) ........................................................ 59

Figure 30 Proposed fragility curves for the most common gas & oil pipeline typologies (ALA,

2001), for wave propagation.............................................................................. 61

Figure 31 Comparison of three fragility curves, with respect to PGD .................................. 62

Figure 32 Proposed fragility curves for the most common gas & oil pipeline typologies (ALA,

2001), for permanent ground deformation......................................................... 63

Figure 33 Fragility curves for steel tank farms (NIBS, 2004) ............................................... 64

Figure 34 Fragility curves for Greek pumping / compressor plants (SRMLIFE, 2003-2007) 65

Figure 35 Fragility curves for generic pumping / compressor plants (NIBS, 2004).............. 66

Figure 36 Fault-tree analysis of a Re.Mi cabin according to (Esposito et al., 2011) ............ 67

Figure 37 Fault-tree analysis of a Reduction Group (GR / GRM) according to (Esposito et

al., 2011)............................................................................................................ 68

xi

List of Tables

Table 1 Two main types of sollicitations ................................................................................. 7

Table 2 Main features of the studied pipeline networks........................................................ 16

Table 3 Proposed damage states for pipeline components.................................................. 25

Table 4 Damage states defined in HAZUS (NIBS, 2004) and (O’Roure & So, 2000).......... 25

Table 5 Correlation between damage modes and repair costs (ALA, 2001) ....................... 26

Table 6 Damage states adapted from (ALA, 2001) ............................................................. 27

Table 7 Damage states defined by (Kappos et al., 2006) for buildings ............................... 28

Table 8 Damage scale proposed by (LESSLOSS, 2007) and (SRMLIFE, 2003 - 2007) for

pumping / compressor stations.......................................................................... 28

Table 9 Description of damage states and functionality indicators for gas stations

(SRMLIFE, 2003-2007) ..................................................................................... 29

Table 10 Maximum longitudinal strains induced by seismic waves propagation along a

pipeline (St John & Zahrah, 1987)..................................................................... 30

Table 11 Summary of the fragility functions from the literature............................................ 35

Table 12 Values of corrective factor K1, according to Eidinger et al. (1995, 1998).............. 40

Table 13 Values of corrective factors according to (Isoyama et al., 2000). Bracketed values

are less reliable due to small sample size. ........................................................ 41

Table 14 Values of corrective factor K1, according to (ALA, 2001) ..................................... 44

Table 15 Summary of the past studies on fragility of pipeline components subjected to

permanent ground deformation ......................................................................... 45

Table 16 Values of the corrective factor K2 according to (ALA, 2001) ................................. 46

Table 17 Proposed vulnerability indices by Ballantyne, for various pipe materials and joint

types (B&S: bell and spigot, RG: rubber gasket, R: restrained, UR: unrestrained)

........................................................................................................................... 47

Table 18 Median and standard deviation parameters for the fragility curves proposed by

O'Rourke & So (2000) ....................................................................................... 48

Table 19 Median and standard deviation parameters for the fragility curves proposed by

ALA (2001) ........................................................................................................ 49

Table 20 Fragility curves of components (anchored or unanchored) of tank farms

components, according to HAZUS (NIBS, 2004) .............................................. 53

Table 21 Fragility parameters (lognormal distribution) for steel tank farms, according to

HAZUS (NIBS, 2004)......................................................................................... 54

Table 22 Median and standard deviation parameters of the fragility curves for pumping

plants (LESSLOSS, 2007)................................................................................. 54

xii

Table 23 Parameters of fragility curves for stations components taken from (NIBS, 2004). 55

Table 24 Median and standard deviation parameters of the fragility curves (lognormal

distribution) for pumping plants (SRMLIFE, 2003-2007) ................................... 55


distribution) for pumping plants, proposed by the HAZUS methodology (NIBS,

2004) ................................................................................................................. 56

Table 26 Pipe material and pipe diameter categories included in the dataset for the (ALA,

2001) fragility relation, according to (Tromans, 2004) ....................................... 59

Table 27 Fragility parameters for steel tank farms, according to HAZUS (NIBS, 2004) ...... 64

Table 28 Fragility parameters for Greek pumping plants, according to (SRM-LIFE, 2003-

2007) ................................................................................................................. 65

Table 29 Fragility parameters of the fragility curves for pumping plants, proposed by the

HAZUS methodology (NIBS, 2004) ................................................................... 66

Table 30 Damage states for the Re.Mi cabin....................................................................... 67

Table 31 Damage states of the Reduction Group (GR / GRM) ........................................... 68

Table 32 Values of corrective factor K1 (ALA, 2001)............................................................ 69

Table 33 Values of corrective factor K2 (ALA, 2001)............................................................ 70

Table 34 Fragility parameters for steel tank farms (HAZUS, 2004) ..................................... 71

Table 35 Damage states definitions for tank farms (HAZUS, 2004) .................................... 71

Table 36 Fragility parameters for pumping / compressor stations (HAZUS, 2004) and

(SRMLIFE, 2003-2007) ..................................................................................... 72

Table 37 Damage states definitions for pumping / compressor stations (HAZUS, 2004) and

(SRMLIFE, 2003-2007) ..................................................................................... 73

SYNER-G – D3.4 – Fragility functions for gas and oil system networks

1

1 Introduction

The SYNER-G project intends to quantify the impact of the disruption of various urban

systems (building areas, health-care centers, transportation networks, utilities) after an

earthquake event. Among the studied utility systems, the gas & oil network has proven to be

prone to some damages during past earthquakes, often with significant consequences:

pollution of waterways, triggering of fires, disruption of gas services.

In the frame of Work Package 3 – Fragility functions of elements at risk – and Task 3.2

(Fragility functions for utility system networks), the present deliverable aims at presenting

fragility curves for components of gas and oil system networks. These fragility functions

need to be applicable to the specific European context and they are intended to be

integrated into the general evaluation of the systemic vulnerability.

The present report reviews at first the different damages that occurred to gas and oil network

components in the past seismic events, along with the most common damage mechanisms.

The following components are proposed to be studied in the scope of SYNER-G:

- pipeline components, which can be damaged by both wave propagation and

permanent ground deformation;

- atmospheric storage tanks;

- processing facilities (e.g. gas pumping / compressor stations);

Then, the second part deals with the description of the European typologies of each of the

gas and oil network components, with an emphasis on the elements located in the selected

case studies of Thessaloniki, Vienna and the L’Aquila area. A review of existing

methodologies (empirical relations, numerical models, fault-tree analyses…) is followed by

the definition, for each component, of some key parameters:

- a damage scale;

- an intensity index (e.g. the selected intensity measure);

- performance indicators that can help to specify what is the link between the damage

state of the component and its serviceability / functionality;

Finally, based on a review of state-of-the-art fragility curves for each component, we

examine whether there is a need for further development or not. For those elements that

have already suitable fragility curves, a discussion is needed to select the most appropriate

fragility function.

At last, the report ends with a short section that specifies the following points, needed for the

coding of the fragility curves into the software tool:

- typology classification of each component;

- damage scale definition;

- intensity index used;

- fragility curve parameters, for each damage state and each typology.


1

2 Oil and gas systems in Europe

2.1 NATURAL GAS SYSTEM

Natural Gas System transfers gas. Gas is composed mainly of methane (CH4) and other

gases in smaller percentages. Five different types of Natural Gas exist: Dry, Liquefied

Natural Gas (LNG), Sour, Sweet and Wet.

Gas system consists of Figure 1:

- Production wells, offshore platforms and gathering facilities

- Terminals

- Compressor station or pressure reduction station

- Storage tanks

- Transmission and distribution pipelines

- Communication and control facilities

- Isolation valves

- Maintenance support facilities (these include maintenance centres and facilities for the

storage of the spare equipment and parts)

Figure 1 Schema of a gas system.

Natural Gas System

2

2.1.1 Production Facilities and Extra European supply sources

Production Facilities serve as the source of the gas supply and consist either of onshore

facilities (production field) or offshore platforms.

Gas supply in Europe essentially comes from four sources outside of domestic production;

production within the EU accounts for around a third, and imports come from the following

four countries: Russia (46% of imports), Norway (27%), and Algeria (20%), and to a lesser

extent Nigeria (less than 8%). Proportions of supply sources vary from member state to

member state for obvious geographic reasons. The dominance of Algerian gas in the mix of

Mediterranean states (Italy, France, and also Portugal) contrasts with Russia’s dominance in

Central Europe, notably in the new member states and Germany. The rest comes from

internal production, which rose to 33% in 2005 (Figure 2).

Figure 2: Overview. Gas in Europe (Nies, 2008).

2.1.2 Tank Farms

Tank farms are facilities that store fuel products (it is suitable for oil system). They include

tanks, pipes and electric components. There are two types of storage facilities: Underground

storage facilities and Storage Tanks.

Underground Storage Facilities

The use of sub-surface facilities for storing gas usually is used to balance seasonal

variations in demand. They may be classified as:


3

- seasonal supply reservoirs, designed to be filled during the 214 day non-heating season

(mostly gas/oil fields and aquifers);

- high-deliverability sites for 151-day heating season (mostly salt cavern reservoirs).

These facilities are located hundred meters below the surface. They are usually natural

geological reservoirs, such as depleted oil or gas fields or water-bearing sands on the top

and impermeable cap rock.

Above ground Storage Tank

LNG tanks are used to store Liquefied Natural Gas. They differ from Water/ Wastewater

tanks as they are designed to minimise any heat ingress. The insulation of the tanks will not

keep the temperature of LNG cold by itself. LNG will stay at near constant temperature if

kept at constant pressure. As long as the steam (LNG vapour boil off) is allowed to leave the

tank, in a safe and controlled manner, the temperature will remain constant. This

vaporisation loss is collected from the tank and either reabsorbed as a liquid, sent to the gas

output line connecting to the national gas grid, or used as fuel on the site. The LNG tanks

would be of a full containment design. In a full containment system two tanks are employed,

an inner tank which contains the stored liquid, and an outer tank which provides security in

the event of any loss of containment or leak from the inner tank. Sophisticated automatic

protection systems are employed to monitor the tank levels, pressures, temperatures and

any potential leakage from the inner tank.

2.1.3 Natural Gas Pipelines

Natural gas networks are operating at different pressures: supra-regional transmission

pipelines operate at very high pressures. These pipelines have a maximum diameter of

1.40 m and are operating at pressure higher than 100 bars. Such gas pipelines can cover

distances of up to 6 000 km (e.g. from west Siberia to Europe).

Supra-regional transmission pipelines are then separated to several branches of high-

pressure pipelines (<70 bars). The high-pressure pipelines distribute natural gas to several

regions. Distribution pipelines then are used to serve the needs of communities. The

pressure for these regional networks range between from 1 to 70 bars, while local

distribution systems are usually operates in the medium (0.1 - 4 bars) or low-pressure

(<0.1 bas) range.

Offshore pipelines have smaller diameters (maximum 1.05 m) although they are designed

for much higher pressures (up to 200 bar).

Natural Gas System

4

2.1.4 Stations

Compressor Stations

Compressor station is a facility, which supplies gas with energy to move in transmission

lines. Otherwise compressor stations are operated at underground storage facilities to raise

the pressure of the gas injected into storage or to compress the natural gas as it leaves

storage to be fed into the pipeline.

The distance between compressor stations along a transmission trunk line is usually

between 100 and 250 km. Each station contains one or more centrifugal or reciprocating

compressor units, and auxiliary equipment for purposes such as generating electricity,

cooling discharge gas and SCADA system that controls the station with all the equipments.

Metering/ Pressure Reduction or compression Stations

Metering stations are used for controlling the flow of gas and its quality in the pipelines

network.

Pressure reduction or compression stations are used in order to set the gas pressure at the

required level for its industrial or commercial use. In each station is using SCADA systems.

LNG Terminal Stations

The terminal stations include moorings for tankers, used for the transportation of liquefied

natural gas, storage tanks for the liquefied gas and re-liquefaction installations. Piping

system in the station or in terminal stations should be designed in order to prevent rupture

during the worst case earthquake. No specific guide exists.

2.2 OIL SYSTEM

An oil system typically consists of refineries, pumping plants, tank farms, and pipelines.

2.2.1 Refineries

Refineries are an important part of an oil system. They are used for processing crude oil

before it can be used. Although supply of water is critical to the functioning of refinery, it is

assumed in the methodology that an uninterrupted supply of water is available to the

refinery.


5

2.2.2 Oil Pipelines

Oil pipelines are used for the transportation of oil over long distances. A large segment of

industry and millions of people could be severely affected by disruption of crude oil supplies.

Rupture of crude oil pipelines could lead to pollution of land and rivers. Pipelines are typically

made of mild steel with submerged arc welded joints, although older gas welded steel pipe

may be present in some systems.

2.2.3 Pumping Plants

Pumping plants serve to maintain the flow of oil in cross-country pipelines. Pumping plants

usually use two or more pumps. Pumps can be of either centrifugal or reciprocating type.

However, no differentiation is made between these two types of pumps in the analysis of oil

systems. Pumping plants are classified as having either anchored or unanchored

subcomponents.

2.2.4 Tank Farms

Tank farms are facilities that store fuel products. They include tanks, pipes and electric

components. Tank farms are classified as having either anchored or unanchored

subcomponents.


7

3 Past earthquake damages on system

elements

3.1 PHYSICAL DAMAGES / MAIN CAUSES OF DAMAGE

3.1.1 Buried pipelines damages

Like many other underground components, buried pipelines are very sensitive to permanent

ground deformation (resulting from various ground failures), in addition to transient ground

deformation due to seismic wave propagation: the characteristics of these physical

phenomena are summed up in Table 1.

Table 1 Two main types of sollicitations

Ground failure Transient ground

deformation

Hazard surface faulting, liquefaction,

landslides

R-waves, S-waves

Usual descriptor PGD PGV, PGA, strain

Spatial impact local and very site-specific large and distributed

The first sign of damages to buried pipelines is the 1906 San Francisco earthquake, which

resulted in significant fires through the city, due to the rupture of water lines needed by fire-

hydrants. Regarding the causes of damage, according to O’Rourke & Liu (1999), the zones

of lateral spreading accounted for only 5% of the built-up area affected by strong ground

shaking, yet approximately 50% of all pipeline breaks occurred within one city block of these

zones: this fact demonstrate the high impact of ground failure on pipelines damage.

Indeed, according to Eguchi (1987), past earthquakes have caused significant damages to

underground pipelines throughout the world: yet inertia forces are not the main issue for

buried components, whereas faulting, landslides or liquefaction pose the most problems

(Hall, 1987).

(O’Rourke & Ayala, 1990) report that a few earthquakes have induced damages to pipelines

only by the effect of seismic wave propagation:

- 1985 Michoacan earthquake, which damaged a large corrosion-free modern

continuous steel pipeline;

- 1964 Puget Sound, 1969 Santa Rosa, 1983 Coalinga and 1989 Loma Prieta

earthquakes;

Yet, in most cases, it appears that seismic wave propagation damaged mainly pipelines that

were previously weakened either by corrosion or welds of poor quality (EERI, 1986).


8

On the contrary, there are numerous examples of damages induced by permanent ground

deformation: 1906 San Francisco, 1952 Kern County, 1964 Niigata, 1964 Alaska, 1971 San

Fernando, 1978 Miyagi-ken-oki and 1983 Nihonkai-Chuba earthquakes. During the 1971

San Fernando earthquake, the steel pipeline system withstood significant ground shaking,

yet it was damaged by abrupt vertical or lateral dislocations or ground ruptures: lateral

spreading (Figure 3) induced severe damages during that earthquake (EERI, 1986,

O’Rourke & Trautmann, 1981, O’Rourke, 1988), and one of the most severe damage was

observed in a in pipeline that was deformed by a differential lateral movement up to 1.7 m.

Regarding liquefaction, a good example is the 1964 Niigata earthquake, where the average

failure ratio for a pipeline system was as high as 0.97 per km, with all kinds of failure types

(pipe body breaks, weld breaks, joint separations).

Figure 3 Pipeline damage in (a) perpendicular and (b) parallel crossings of a lateral

spread (Rauch, 1997)

More recent events, like the 1994 Northridge, 1995 Kobe, 1999 Kocaeli or 1999 Chi-Chi

earthquakes, confirmed the relative vulnerability of piping systems to strong ground motions

and the somewhat good performance of welded-steel pipes with respect to seismic wave

propagation.

As a result, the emphasis is put on the ductility of pipes and the quality of welds, when

building earthquake resistant piping systems: still, pipe welds or joints seem to be the most

vulnerable parts of this component. Also, corrosion is an aggravating factor of the pipeline

vulnerability (Young & Pardon, 1983, Ogawa, 1983).

3.1.2 Storage tanks damages

According to (EERI, 1986), damage to tanks is quite common throughout past earthquakes:

- 1952 Kern County earthquake: damage occurred near the top, due to sloshing oil,

with more severe damages on floating roof tanks (ASCE, 1987);

- 1964 Niigata earthquake: oil leaked from ruptured tanks and caught fire, damaging

two refineries (ASCE, 1984);

- 1971 San Fernando earthquake: many incidents with storage tanks were reported,

most of them were half-full to full;


9

- 1975 Imperial Valley earthquake: out of six unanchored full tanks in the area, the

largest one was damaged and the failure of the fixed roof allowed for the sloshing oil

to spill (EERI, 1986);

- 1978 Miyagi-ken-oki earthquake: a large oil refinery with 90 tanks had three of them

failed and three others damaged without failure. Tank failure induced oil spillage and

pollution of waterways (ASCE, 1984);

- 1985 Chile earthquake: a refinery with 120 storage tanks had 12 full or nearly full

tanks damaged, with elephant’s foot buckling, roof damage, base plate failure, or

damage to the exiting piping (due to rocking of the tanks and differential settlement)

(EERI, 1986);

- 1989 Loma Prieta earthquake: tank damages could be observed up to 120 km from

the epicentre location. Unanchored tanks underwent an uplift of the walls (up to 200

mm displacement between the foundation and the shell), which resulted in elephant’s

foot buckling, vertical splits in tank walls, ruptures of elephant’s foot buckles,

puncture of tanks by restrained pipes, and damage to restrained pipes anchored to

both tank and foundation (EERI, 1990).

As a result, most tanks show a significant vulnerability to ground shaking, and due to the

potential gravity of indirect damages (fire risk, liquid spillage and pollution…), the seismic

vulnerability assessment of such component should be looked at thoroughly, in the scope of

a systemic vulnerability analysis.

All these damage reports from past earthquakes seem to indicate that unanchored tanks

seemed the most vulnerable, along with vertical cylinders tanks with a large height-to-

diameter ratio (EERI, 1990). Finally, the amount of liquid stored within the tank has a

significant impact, as full tanks are subject to larger lateral forces and overturning moments

due to liquid sloshing, which can also damage the tank roof. Other damage mechanisms

include elephant’s foot buckling (generated by compressive forces against the tank wall) and

leakage or breakage of pipe connections (due to tank rocking and sliding).

3.1.3 Processing facilities damages

Reports from past earthquakes show a little information on above ground facilities, yet the

small number of incidents associated to these components tends to indicate a good

behaviour of these support facilities during an earthquake:

- 1971 San Fernando earthquake: underground facilities buried in vaults or manholes

did not suffer from any structural damage (ASCE, 1974);

- 1985 Chile earthquake: some industrial facilities endured minor damage, yet they

were still functional and there was no shut-down (EERI, 1986);

- 1987 Ecuador earthquake: a pumping station was damaged, with a jammed control

valve and the outage of electrical power and back-up generators (Crespo et al.,

1987);

- 1989 Loma Prieta earthquake: no serious damage was reported for industrial

facilities

Thus, this limited experience shows that modern facilities (compressor stations, pumping

stations, control stations) that are built according to seismic codes with anchored equipment


10

exhibit good resistance to ground shaking. (Bettinger, 1980). The anchorage of

subcomponents is especially a crucial point, as unanchored equipment can lead to the

rupture of electrical connections (Nyman, 1987) or the tipping and sliding of mechanical

parts.

3.2 CLASSIFICATION OF FAILURE MODES / DIRECT LOSSES

3.2.1 Pipeline failure modes

Continuous pipelines (e.g. welded-steel pipes, Figure 4) are built with rigid joints (welds) and

they have a tendency to show good performance during past earthquakes. They usually fail

due to compression strains, that induce buckling of the pipe body (like a beam), or warping

and wrinkling of the pipe wall (ALA, 2001). This deformation may not generate leakage, yet

the modification of the pipe shape may produce disruption of the gas / oil flow. A crucial

factor for the resistance of continuous pipelines is the quality of the welds, as past studies

have shown that pipes constructed before the 1930s with poor quality welds experienced

damages mostly at the joint locations.

Figure 4 Continuous steel pipeline (source: FULCRUM DYNAMICS, LLC)

Segmented or jointed pipelines usually consist of rigid pipe segments (e.g. cast-iron or

concrete, Figure 5) connected through loose or flexible joints. Three main failure modes

have been identified for this typology (ALA, 2001): tensile and bending deformations of the

pipe barrel, excessive rotation of a joint, and pullout of a joint (Singhal, 1984). This pipeline

type is much less frequent in oil / gas piping networks.


11

Figure 5 Segmented concrete pipeline and rubber gasket joint (Kim et al., 2010)

Aside from these usual failure modes, a piping system is more vulnerable at discontinuities

like pipe elbows, tees, in-lines valves or connections to adjacent structures (storage tanks,

racks, facilities…): high stresses are especially concentrating at these anchor points and

rigid locations (ALA, 2001). Also, corrosion has a strong influence on the pipes vulnerability,

as it decreases the wall thickness and creates heterogeneous zones that may lead to stress

concentrations.

It is very difficult to translate the described damage mechanisms in terms of direct losses

(intensity of leakage, breakage): indeed, damages such as joint failure or pipe buckling may

result in various outcomes, from the slight leakage to the complete spillage of the content.

Empirical data on pipeline failures from past earthquakes has been developed based on a

simple indicator: the number of repairs per unit length performed by the exploiting company.

Thus, no distinction is made between the types of repairs: those can include the complete

fracture of the pipe, a leak in the pipe, or damage to an appurtenance of the pipe (ALA,

2001). All this collected data is unfortunately not differentiated and these different types of

repairs have of course various impacts at the scale of the piping system evaluation. The

more recent post-earthquake review of damages carried out after the L’Aquila event also

makes no distinction between the different failure types.

3.2.2 Tanks failure modes

According to NZNSEE (1986), Kennedy & Kassawara (1989) and ALA (2001), the following

classification of failure modes is proposed:

- shell buckling: it is one of the most common forms of damage in steel tanks, and it is

expressed via an outward buckling of the bottom shell courses (“elephant foot”,

Figure 6c), that can sometimes occur over the full circumference of the tank. This

phenomenon may lead to the loss of the content due to weld or piping fractures, and

less frequently to the total collapse of the tank.

- roof damage (e.g. Figure 6a) : ground shaking may induce oil sloshing inside the

tank. When tanks are full or nearly full, this sloshing motion generates an upward

pressure distribution against the tank roof. This may cause a rupture of the joints

between the wail and the roof, leading to a spillage of tank contents over the tank

walls. Observations from past earthquakes show that floating roofs have generally


12

endured more severe damage than fixed steel roofs. It is yet important to note that

roof damage, although expensive to repair, usually does not lead to more than a third

of total content loss (ALA, 2001).

- anchorage failure: many tanks are anchored with steel braces or bolts, but it is still

possible that these anchors may be pulled out or stretched by the seismic load.

However, the failure of anchoring components does not necessary imply the loss of

the tank contents.

- tank support system failure: this failure mode is specific for above-grade tanks,

elevated by steel columns or frames. Even if the failure of the supporting system

often leads to complete loss of contents, this issue is of lesser concern to large oil

storage tanks, which are usually built at grade.

- foundation failure: this phenomenon can be common in the case of poor foundation

conditions prone to liquefaction, resulting in base rotation and important settlements.

In the case of unanchored tanks, tensile stress can also generate uplift displacement

of the tank base, separating it from the baseplate.

- hydrodynamic pressure failure: ground shaking generates pressures between the

fluid and the tank walls, thus resulting in tensile hoop stresses. The induced loads

may then lead to splitting of the wall and leakage, especially in the case of steel

tanks with riveted joints.

- connecting pipe failure (e.g. Figure 6b): this is one the most common failure modes

that can induce a total loss of the tank contents. The fracture of the pipes at the

connections to the tank results from differential displacement between the piping and

the tank (uplift displacements, foundation failure).

- manhole failure: because of significant stresses against the manhole cover, the latter

can fail which results in loss of content through the opening.

Figure 6 Common failure modes for steel tanks (a) sloshing damage to the upper

shell (b) pipe connection failure (c) elephant's foot buckling (Berahman & Behnamfar,

2007)

The variety of failure mechanisms makes it very difficult to assess the direct losses. One

approach is to convert everything in terms of economic losses, based of the replacement

value of the damaged tank or the cost of repairs. Yet, these direct economic losses are not

well correlated to the functionality of a tank: for example, elephant’s foot buckling might

deform the tank wall (inducing heavy repair cost) without generating any loss of contents,

( a )

( b )( c )


13

whereas a pipe connection failure (which represents a small fraction of the tank value) can

result in the total spillage of contents and the loss of the tank function.

3.2.3 Support facilities failure modes

Because of the little information available on support facilities damages, which is a

consequence of their good behaviour in past earthquakes, main failure modes are not well

identified. However, a fault-tree analysis of a gas compressor station or a pumping station

can help identifying the following key components:

- building: the collapse of the structure sheltering the facility may damage the

equipment with falling debris;

- pump / compressor: this key element is connected to the piping system and its

failure, due to sliding or rocking if unanchored, can generate leakage or breakage of

the pipe;

- electrical / mechanical components: these miscellaneous components, necessary for

the compressor to operate, can also be damaged if not anchored;

- electric power supply: external power can be shut down because of the electric

power network disruption, or the connection failure between the power lines and the

facility building. However, most facilities are equipped with backup power generators.

Again, these different causes of damage are very disparate in terms of direct economic

losses, but the smallest component failure can have the same impact as the building

collapse, in terms of the facility functionality.

Regarding in-line valves, many types are found along the piping network (gate valves,

butterfly valves, check valves, ball valves…) and they can be either buried with the pipeline

or located in underground concrete vaults. Following the recommendations of (ALA, 2001), it

is proposed to treat pipeline valves in the same framework as pipe components. In other

words, they are affected only if the pipe segment they are fixed to is affected. It has to be

noted that this is different from not considering the components at all, as they require the

functionality of other networks (e.g. power supply and communication links) to assume their

role in the system. Also, their functionality is related to the connection with the pipeline: if the

pipe-valve joint fails, the flow continuity id not ensured (break).

Finally, SCADA equipment includes many components (instrumentation, power supply,

communication components, vaults). For hardware located in metal cabinets, the main

observed damages comprise batteries falling over, circuit boards dislodging and gross

movement of the cabinet enclosure (ALA, 2001). Regarding pressure / flow measuring

instruments, ground shaking is likely to induce air bubbles that can provoke false reading.


15

4 Methodology for the vulnerability assessment

of system elements

4.1 IDENTIFICATION OF THE MAIN TYPOLOGIES

4.1.1 Pipelines

Natural gas networks are operating at various pressures, depending on their scale:

- supra-regional transmission pipelines: these pipelines operate at very high pressures

(~100 bar) and present large diameters (up to 1.40 m). Such pipelines can cover large

area (e.g. from west Siberia to Europe, from Norway to France…);

- regional transmission/distribution pipelines: these pipes still operate at high pressure

(from 1 to 70 bar) and are used to connect local distribution systems;

- local distribution pipelines: these smaller pipelines usually operate in the medium (0.1

– 4 bar) or low-pressure (< 0.1 bar) range;

In addition to this classification, the pipeline typologies mainly rely on the following

parameters:

- material type;

- material strength;

- diameter;

- wall thickness;

- smoothness of coating;

- type of connection;

- design flow;

Focusing mainly on the typologies inherent to the three cases studies (Thessaloniki, Vienna

and L’Aquila), pipeline components from Greece present the following characteristics:

- transmission pipelines (19 bar): welded-steel, diameters ranging between 100 –

250 mm and wall thickness from 4.37 mm to 5.56 mm;

- distribution pipelines (4 bar): made of PVC (with electro-fusion connections), with

diameters between 125 and 160 mm and wall thickness ranging from 11.4 mm to 14.6

mm;

These natural gas pipelines are located at a conventional depth, 1.10 m + pipeline diameter

+ 0.15 m.

In Austria, there are several long distance transmission pipelines going through (TAG,

WAG, HAG…). They consist of welded-steel and have diameters ranging from 200 to 1,400

mm. They are operated at 84 bar and are buried at an average depth of 1 m.


16

The regional transmission/distribution pipelines operate at a pressure of about 16 bar, and

get down to 1 bar locally: these pipelines are made of PVC.

In L’Aquila, the transmission network (operated by SNAM at a national level) is made of

welded –steel pipes, with an internal diameter of 103.9 mm and wall thickness of 5 mm. The

transmission and delivery pressure for the L’Aquila area is 64 bar. Locally, the gas is

distributed via a 621 km pipeline network: 234 km of pipes operating at medium pressure

(2.5 – 3 bar), and the remaining 387 km with gas flowing at low pressure (0.025 – 0.035 bar):

these pipelines are either made of steel or HDPE (High Density Polyethylene). HDPE pipes

have a nominal diameter ranging from 32 to 400 mm, whereas diameter of steel pipes is

usually between 25 and 300 mm.

As a result, it is reasonable to find the pipelines typologies based on the following known

features:

- material type: welded-steel, PVC or HDPE;

- operating pressure;

- pipe diameter;

- connection type (if known);

On Table 2, the main characteristics of the studied pipelines for each area are summed up.

Table 2 Main features of the studied pipeline networks

Type Pressure Material Diameter (mm) Thickness (mm)

transmission 19 bar welded-steel 100 – 250 4.37 – 5.56 Greece

distribution 4 bar PVC 125 – 160 11.4 – 14.6

supra-

regional

transmission

84 bar welded-steel 200 – 1,400 -

transmission 16 bar PVC - -

Austria

distribution 1 bar PVC - -

transmission 64 bar welded-steel 103.9 -

distribution 2.5 – 3 bar

L’Aquila

distribution

(local)

0.025 –

0.035 bar

welded-steel

/ HDPE

25 – 300 /

32 – 400

3.2 – 5.6 /

2.3 – 36.4

Regarding oil pipelines, these components are less frequent in the studied areas and they

may present features similar to supra-regional gas transmission pipelines: indeed, most oil

pipelines crossing Europe are made of welded-steel with arc-welded joints, with large

diameters (250 – 1,000 mm), and operate at high pressure/flow.


17

4.1.2 Tank farms

Natural gas

Aside from underground storage facilities, natural gas is usually stored while in its liquefied

state (LNG) in specific LNG tanks: these facilities are designed to insulate the gas from any

heat ingress, using “auto-refrigeration” techniques (Vaporization of part of the stored

liquefied gas counteracts the unavoidable heat flow coming from the outside, keeping the

two phases system at the equilibrium, which implies a constant temperature for a given

pressure). This technique requires an inner tank (which contains the stored liquid) and an

outer tank (which provides security in the event of any loss of containment from the inner

tank).

Inner shells are usually made of a nickel-steel alloy, whereas the outer shell is a pre-

stressed concrete construction. The LNG tanks are usually vertical cylinders and can

represent huge facilities, which make them too specific to study in the scope of this project.

Oil and fuel

Liquid products (oil and fuel) are stored in atmospheric storage facilities, which include tanks

(vertical cylinders), pipes and electric components. The tank typologies are usually classified

according to the following characteristics:

- material: steel or reinforced-concrete;

- construction type: at-grade or elevated;

- anchored or unanchored;

- roof type;

- capacity;

- shape factor: height vs diameter ratio;

- amount of content in the tank: empty, half-full, full;

There is a wide variety of storage tanks in Europe, and main typologies should be extracted,

mainly based on the material and construction types, and whether components are anchored

or not.

4.1.3 Stations

Compressor stations

This type of station is a facility which supplies gas with energy to move along the

transmission lines. Compressor stations are also used in storage facilities to compress the

gas when it is fed into the pipeline. The distance between compressor stations along a

transmission trunk line is usually between 100 and 250 km. Each station contains one or

more centrifugal or reciprocating compressor units, and auxiliary equipment for purposes


18

such as generating electricity or cooling discharge gas and SCADA system that controls the

station with all the equipments. Two or more compressors at a station can be used either in

parallel or in series (FEMA 233, 1992): however, no differentiation is made between these

two types of compressors in the analysis of natural gas systems.

In Greece, it seems that most compressor stations are housed in RC low-rise buildings, with

anchored components. Those we propose to consider the following typologies for

compressor stations:

- with anchored or unanchored components;

- within low-rise buildings, made of masonry or RC;

We also propose to include oil pumping stations in this category of stations, as they are very

similar to compressor stations (presence of a pump instead of a compressor).

Metering / Pressure reduction stations (M/R stations)

These stations are used to reduce the gas pressure for industrial or pressure use. In each

station, there is a SCADA system that controls the equipment. The natural gas system of

Thessaloniki comprises two central M/R stations. In the L’Aquila area, the medium-pressure

network is connected to the high-pressure transmission lines through three M/R stations

(referred to as RE.MI “REgolazione e MIsura” in Italian). RE.MI stations are one-story

masonry buildings with steel roofs (Figure 7).

Inside the M/R stations (Figure 8) the gas undergoes the following operations and

processes:

- gas preheating;

- gas-pressure reduction and regulation;

- gas odorizing;

- gas-pressure measure;

- data transmission through SCADA system (no SCADA for the Re.Mi cabins in the

L’Aquila area);

The specificities of the operations performed within these stations prevent them from being

included in the compressor stations typologies.


19

Figure 7 RE.MI cabin in the L'Aquila area: outside view (courtesy of Enel Rete Gas)

Figure 8 RE.MI cabin in the L'Aquila area: inside view (courtesy of Enel rete Gas)

Reduction groups

In L’Aquila, about 300 Final Reduction Groups (referred to as GRF “Gruppi di Riduzione

Finale” in Italian, Figure 9) allow for the transformation of the medium distribution pressure

into the low distribution pressure. These facilities can be either buried, sheltered in a kiosk or

housed within a building.


20

Figure 9 View of a reduction group as used in the L'Aquila area (courtesy of Enel Rete

Gas)

4.2 GENERAL DESCRIPTION OF EXISTING METHODOLOGIES

4.2.1 Empirical relations

The most used and straightforward approach is based on empirical data collected

throughout past earthquakes.

In the case of pipeline components, the usual practice is to evaluate the repair rate per unit

length of pipe, with respect to a parameter representative of ground shaking (e.g. PGV or

PGA) or ground failure (e.g. permanent ground deformation, PGD). Empirical data is

collected from gas / oil companies operating the pipelines and consists of the following:

length of pipes subjected to a given level of ground shaking, and the number of repairs

carried out for that segment. This means that this data is very generic and no distinction is

made between the different kinds of repairs: complete fracture of the pipe, leak in the pipe or

damage to an appurtenance of the pipe (ALA, 2001).

Usually, some adjustments to the raw data are performed: for instance, in the ALA (2001)

methodology, only the damage to the main pipe is used to assess the relative vulnerability of

different pipe materials. Also, data points assumed to contain permanent ground

displacement effects can be eliminated when studying only the effects of ground shaking.

Then, based on the data points, a correlation procedure is performed in order to fit a

predefined functional form with the empirical data. For example, ALA (2001) explored a

linear model (RR = a.IM) and a power model (RR = b.IMc). Depending on the consistency of

the available data, it is possible to build specific models based on various factor such as pipe

material, pipe diameter or pipe connections. Many empirical studies have been carried out,

like the ones from HAZUS (NIBS, 2004), Eguchi et al. (1983), Eidinger (1998), Isoyamaet al.

(2000) or Toprak (1998).

Regarding storage tanks, empirical relations are also quite common, such as (O’Rourke &

So, 2000), HAZUS (NIBS, 2004), (ALA, 2001) or (Fabbrocino et al., 2005). During

earthquakes, at each refinery or storage facility subjected to a given level of ground shaking,


21

the proportion of damaged tanks is evaluated. Observations may give some details about

the type of failure (roof damage, pipe connection failure, elephant’s foot buckling…), which is

then translated into a damage state (whose definition changes depending on the study). The

occurrence of a damage state is then fitted into a probability function, taking the form of a

lognormal distribution with two parameters (median and standard deviation).

The accuracy of empirical relations is heavily relying on the quality and quantity of available

data: for example, the distinction of vulnerability into different typologies is limited to what

has been observed and recorded in a statistically reliable way. Also, most of these empirical

studies have been based on non-European earthquakes and damages that occurred on

fairly ancient components (e.g. pipelines built in the early 30s). However, it has to be

stressed that these empirical studies have come a long way, from the first relation (Eguchi et

al., 1983) to the work by O’Rourke & Deyoe (2004), which introduced the ground strain

(based on wave velocity) as an intensity measure. In this scope, the 1944 Northridge

earthquake constituted an important breakthrough, as it allowed for the collection of valuable

damage data on fairly modern infrastructures.

4.2.2 Bayesian approach

In the case of storage tanks, one study (Berahman & Behnamfar, 2007) proposes to use a

Bayesian approach to improve the empirical procedure. The authors use field observations

of unanchored on-grade steel tanks, previously reported by ALA (2001), and they aim at

accounting for both aleatory and epistemic (model bias, small data sample, measurement

errors …) uncertainties. Fragility models are developed using a probabilistic limit state

function and a reliability integral, solved with Monte-Carlo simulation. It was found that the

fragility curves were less conservative than purely empirical models from ALA (2001) or

NIBS (2004), suggesting a better tank performance than expected. Also, one important

result is that commonly used lognormal distributions do not seem to be the best fit to the

available empirical data.

However, this study was only conducted for a specific typology of tanks (unanchored on-

grade steel tanks) and other sets of fragility curves should be built to cover all typologies.

Finally, the proposed fragility curves are based on an integral formulation and are not

associated with an analytical function (like the lognormal distribution, which can be easily

described with two parameters).

4.2.3 Analytical approach

In the case of buried pipelines, there are not many examples of analytical studies. Terzi et al.

(2007) developed fragility curves for the case of segmented pipelines subjected to

permanent ground deformation, using a FEM model and accounting for pipe-soil interaction.

The results were confronted with the case of a PVC pipe that suffered damage from the

2003 Lefkas earthquake.

Regarding storage tanks, a study by Iervolino et al. (2004) performs numeric analyses on

dynamic models of unanchored steel tanks. Using a limit state function (e.g. axial stress,

governing the failure by elephant’s foot buckling), the authors propose a decomposition of

the random structural variable into those affecting the capacity (e.g. mechanical or material

properties) and those affecting the demand (set of parameters defining the structure, shape,

dimensions…). A design of experiments is set up, with two axis (fluid level-over-radius ratio,


22

and friction coefficient between the baseplate and the unanchored tank), and for each of the

studied structure, a reliability analysis is performed in order to obtain a fragility curve. Then,

through a second order polynomial model, it is possible to obtain the response surface of the

fragility parameters (median and standard deviation of the lognormal distribution). As

expected, a low friction coefficient and a nearly full tank were found to have the highest

probability of failure. This method is interesting, as it allows for the vulnerability assessment

of all structures belonging to the “tank” typology. Yet, this study was only applied to one

specific damage state (failure by elephant’s foot buckling), and other sets of response

surfaces should be needed for an exhaustive evaluation of the vulnerability of storage tanks.

4.2.4 Fault-tree analysis (for support facilities)

In-line components or processing facilities such as gas compressor stations include many

subcomponents, which make a quantitative vulnerability assessment quite difficult.

In the configuration where support equipment (e.g. pumps, compressor, electric cabinets…)

are sheltered within a building, a solution is to treat these facilities as a common building.

Thus, one can use the fragility curves for low-rise RC or masonry structures to assess the

vulnerability of the compressor or pumping stations. (Kappos et al., 2006) proposed such

fragility curves for pumping plants in low-rise RC buildings, with anchored components.

Another approach is to consider these facilities as systems and to aggregate the fragility of

each component into a global systemic vulnerability. Such a work has been carried out in the

SRMLIFE project (Greek project, 2003 – 2007, where a gas compressor stations is

decomposed into the following components:

- building;

- electrical / mechanical equipment;

- pump;

- commercial power;

- power backup;

Then, using the HAZUS (NIBS, 2004) fragility curves for these individual components and

the curves from Kappos et al. (2006) for the building, it is possible to compute the global

fragility curve of the plant, based one the following fault-tree (this fault-tree represents the

global functionality analysis of the station, particular damage states may be represented with

a different logic):


23

Figure 10 Decomposition of a compressor station into a fault-tree

The fault-tree decomposition follows a logic structure, with AND / OR operators that indicate

how to aggregate the fragilities of two connected components. For two components A and B

assembled in series (e.g. AND operator), like a pump and the building where it is stored into,

the probability of failure of the system A-B is given by ( Equation 1

)()()( BPAPABP fff ©?

( Equation 1 )

On the other hand, when components A and B are mounted in parallel (e.g. OR operator),

like commercial power connection and backup power, the probability of failure is expressed

as ( Equation 2:

] _ ] _)(1)(11)( BPAPABP fff /©//? ( Equation 2 )

Using these basic rules, it is indeed possible to build up the global probability of failure of the

compressor stations and to account for the fragility of both the building and the components

within.


24

4.3 DAMAGE STATES

4.3.1 Pipeline components

Damage states definition

As stated before, empirical relations for the fragility of pipelines are based on the recorded

number of repairs during past earthquakes, and no distinction is really made between leaks

and breaks of the pipes. As a result, all fragility relations for pipelines are given for a single

“damage state”, e.g. the repair rate per unit length of pipe. However, according to HAZUS

(NIBS, 2004), the type of repair or damage depends on the type of hazard: a damaged pipe

because of ground failure is likely to present a break (it is assumed 80% breaks and 20%

leaks), whereas ground shaking may induce more leak related damages (e.g. 20% breaks

and 80% leaks). These percentages are accepted in the reviewed publications that are

interested in making such distinction even if these values do not result from a specific

argumentation. However, they provide a rare link between what can be seen as the repair

cost (almost directly linked to the number or repairs, which is the recorded data) and the

functionality (whether a pipe is leaking and assumed to continue being operational, or

broken and unable to assume its function, as discussed further in 3.5.1).

Then, using a Poisson probability distribution and the repair rate RR, one can assess the

probability of having n pipe breaks / leaks in a pipe segment of length L ぇlうそたg! ぉて gとぬiかて

ヾとてえそiにjさな kさな gちglてとうな hiちくとえしさせi.):

* + * +!n

LRRenNP

n

LRR ©©?? ©/

( Equation 3 )

Finally, assuming that a pipe segment fails (flow rupture) when it has a least one break along

its length, the probability of failure is given by ( Equation 4:

* + LRR

f eNPP©//??/? 101 ( Equation 4 )

Finally, using the HAZUS assumption and considering the type of hazard, it is possible to

assess the probability to have a pipe break or a pipe leak along the length of the segment.

Performance indicators

The performance indicators of a pipeline in terms of serviceability or functionality may take

various definitions, depending on the point of view. For the end-user, it can be for example

the availability of the desired amount of product (at the requested flow / pressure / quality);

for the operating companies, this can be measured at the network level by the ratio of

satisfied demand on the total demand, or the total loss of contents; also, for environment

agencies, it can represent the amount of spilled contents in the nature.


25

Table 3 Proposed damage states for pipeline components

Damage state Damage description

DS0 no damage no break / leak

DS1 leakage at least one leak along the pipe length

DS2 failure at least one break along the pipe length

Regarding the pipelines, as two damage states are considered, it is possible to propose the

following correspondence between pipe damage and serviceability/ functionality (Table 3):

- DS1: leakage – we assume that the pipe may still be functional, yet with a reduced

flow (a given % of the flow is assumed to go out of the system);

- DS2: failure – the flow is disrupted, and we can consider the pipe segment as

disconnected from the rest of the network;

4.3.2 Storage tanks


Fragility curves from the literature, whether they are empirical or analytical, usually propose

the same number of damage states (e.g. 5, including “no damage”), and very similar

definitions (O’Rourke & So, 2000), (ALA, 2001), (NIBS, 2004), (Berahman & Behnamfar,

2007):

- DS1: no damage

- DS2: slight / minor

- DS3: moderate

- DS4: extensive

- DS5: complete / collapse

Table 4 Damage states defined in HAZUS (NIBS, 2004) and (O’Roure & So, 2000)

Damage state Damage definition

DS1 None No damage to tank or I/O pipes

DS2 Slight / minor Damage to roof, minor loss of contents, minor damage to piping,

but no elephant’s foot buckling

DS3 Moderate Elephant’s foot buckling with minor loss of content

DS4 Extensive Elephant’s foot buckling with major loss of content, severe damage

DS5 Complete Total failure, tank collapse


26

The detailed damage states used by HAZUS (NIBS, 2004) and O’Rourke & So (2000) are

given in Table 4. HAZUS damage states were initially developed for building-type structure

for which it is reasonable to relate increasing direct damage and decreasing functionality.

This has been adopted for tanks, whereas there is no direct correlation between repair cost

and functionality for tanks. Damage states are consequently based on the physical damage

of the tank (direct economic losses) and their classification does originate from the

serviceability but from the repair cost (expressed as a percentage of the whole tank

replacement cost).


The authors of ALA (2001) identified the need of relating serviceability to a given aggression

level. They propose the following Table 5 to relate a damage state (which corresponds to a

repair cost) to a level of functionality.

Table 5 Correlation between damage modes and repair costs (ALA, 2001)

The damage states definitions from ALA (2001) are very similar to the table 4 as it has been

built in order to closely match the fragility curves used in HAZUS. In addition, they were

modified to account for the potential large loss of functionality due to inexpensive damages.

For instance, a tank with “broken I/O pipes” is classified in DS4 (cf. Table 6).

Most common damage modes Repair costs (% of

the replacement

cost)

Functionality as

percentage of

content lost

immediately

after the

earthquake

Rupture of drain pipe 1% to 2% 50% to 100%

Rupture of overflow pipe 1% to 2% 0% to 2%

Rupture of Inlet/Outlet pipe 1% to 5% 100%

Rupture of bottom plate from bottom course 2% to 20% 100%

Roof system partial damage 2% to 20% 0% to 10%

Roof system collapse 5% to 30% 0% to 20%

Upper shell buckling 10% to 40% 0% to 20%

Elephant’s foot buckling with no leak 30% to 80% 0%

Elephant’s foot buckling with leak 40% to 100% 100%


27

Table 6 Damage states adapted from (ALA, 2001)

Damage

state

Damage definition Functionality as the

content lost immediately

after the earthquake

DS1 None No damage to tank or I/O pipes 0%

DS2 Slight /

minor

Damage to roof other than buckling,

minor damage to piping

1% to 20%

DS3 Moderate Elephant’s foot buckling with minor loss

of content

20% to 40%

DS4 Extensive Elephant’s foot buckling with major loss

of content, severe damage, broken I/O

pipes

40% to 100%

DS5 Complete Total failure, tank collapse 100%

The authors are still careful with the construction of the corresponding fragility curves:

“Because of incomplete descriptions of the actual damage to some tanks, the definition of

damage state between DS = 2, DS = 3 and DS = 4 is sometimes left to judgment”.

One approach for obtaining the probability of occurrence of these damage states is to

decompose each state into a fault-tree, down to the basic failure modes of the tank (Figure

11).

Figure 11 Example of a fault-tree for an anchored steel tank failure modes (ALA, 2001)


28

4.3.3 Processing facilities (pumping / compressor stations)


Following the approach by (Kappos et al., 2006) a pumping / compressor stations may have

the same damage states as a usual building, the loss index being defined by the percentage

of failed structural elements (criterion also used in HAZUS methodology, Table 7):

Table 7 Damage states defined by (Kappos et al., 2006) for buildings

Damage state Loss index

DS0 None 0%

DS1 Slight 0 – 1%

DS2 Moderate 1 – 10%

DS3 Substantial to heavy 10 – 30%

DS4 Very heavy 30 – 60%

DS5 Collapse 60 – 100%

In the case of a fault-tree analysis of the compressor station, the global damage state is

based on the individual damage state of its components. For example, a slight / minor

damage (e.g. short-time malfunction of the plant) to the station may be induced by the loss

of electrical power and backup generators, or a slight damage to the building. Such an

approach was used in the LESSLOSS (2007) and SRMLIFE (2003-2007) projects, which

resulted in the damage scale presented in Table 8.

Table 8 Damage scale proposed by (LESSLOSS, 2007) and (SRMLIFE, 2003 - 2007) for

pumping / compressor stations

Damage state

DS0 None

DS1 Slight / minor

DS2 Moderate

DS3 Extensive

DS4 Complete

The damage states above are not directly related to physical damage (percentage of loss),

and they integrate also functional aspects: therefore a straightforward description is not

available. A more detailed analysis of this case is presented is the next sections

(performance indicators).


29

Finally, regarding in-line valves or SCADA equipment, as it was explained before, no

quantitative study of their vulnerability is available, and there is no point in defining damage

states for now.


Performance indicators associated with processing facilities such as pumping / compressor

stations may include measures of loss of contents or percentage of decrease of output

pressure / flow.

The damage states defined for pumping / compression stations (see Table 8) in projects

LESSLOSS (2003-2007) and SRMLIFE (2003-2007) can be considered as performance

indicators, as they already account for the functionality loss (aside from the physical

damage). The belowTable 9 proposes indeed a correlation between the damage states

(repair costs in % of the replacement value) and some functionality / serviceability indicators:

Table 9 Description of damage states and functionality indicators for gas stations

(SRMLIFE, 2003-2007)

Serviceability/ Functionality Repair

cost (%)Damage state

75 – 100Complete

damage Building collapsed

Full loss of

function

(un repairable

damage) 50 – 75 Extensive

Damage

Building being

extensively damaged,

or the pumps badly

damaged beyond

repair.

Disability of

boosting gas in

compression

station

Malfunction.

(Full function

after repairs)

30 – 50 Moderate

Damage

Considerable damage

to mechanical and

electrical equipment

or considerable

damage to building or

loss of electric power

and of backup for 7

days.

Several stops and

reduced flow of gas

in the transmission

gas pipelines

10 – 30

1 - 10

Slight/Minor

Damage

Slight damage to

building or full loss of

commercial power

and backup power for

few days (< 3 days)

Normal function

Full function

- No -


30

4.4 INTENSITY INDEXES


Wave propagation

Among the numerous studies proposing empirical relations for pipelines subjected to

transient ground deformation, several intensity measure parameters have been proposed:

- Macro-seismic intensity: (Eguchi, 1983), (Eguchi, 1991);

- PGA: (Katayama et al., 1975), (Isoyama & Katayama, 1982), (Hamada, 1991),

(Isoyama et al., 2000), (O’Rourke et al., 1998);

- PGV: (Barenberg, 1988), (O’Rourke & Ayala, 1993), (Eidinger et al., 1995), (Eidinger,

1998), (Isoyama, 1998), (O’Rourke et al., 1998), (Toprak, 1998), (Eidinger & Avila,

1999), (O’Rourke & Jeon, 1999), (ALA, 2001), (Pineda & Ordaz, 2003), (HAZUS,

2004), (O’Rourke et Deyoe, 2004);

- PGV²/PGA: (Pineda & Ordaz, 2007);

- PGS (transient strain): (O’Rourke & Deyoe, 2004), (Paolucci & Pitilakis, 2007);

We can notice that PGV is by far the most used intensity-measure parameter, from the first

empirical relations to the more recent ones. However, the seismic response of buried pipes

is mostly controlled by the amplitude of transient strain, induced in the ground by the wave

propagation. The peak horizontal ground strain can indeed be related to the peak horizontal

velocity V (PGV), by the following equation ( Equation 5 ):

C

V?g ( Equation 5 )

where C is the wave propagation velocity in the surrounding soil, relative to the ground

surface. In the case of body waves, S-waves only are considered, since they tend to

generate larger ground motion that P-waves. Concerning surface waves, the most significant

motions are those caused by Rayleigh waves. According to LESSLOSS (2007), longitudinal

strains are the most damaging factor, compared to shear strains: Therefore it is possible to

determine the incident angle of the waves that can generate maximum longitudinal strains

(St John & Zahrah, 1987). Their results are summed up in Table 10.

Table 10 Maximum longitudinal strains induced by seismic waves propagation along

a pipeline (St John & Zahrah, 1987)

Maximum strain Ground motion direction

Incident angle Value

R waves Horizontal component parallel to

the wave direction

0°

R

R

C

PGV?g

S waves Perpendicular to the wave

propagation direction

45°

S

S

C

PGV

2?g


31

O’Rourke & Deyoe (2004) proposed a relation between peak ground strain and repair rate of

pipes, obtaining very promising results. Also, they introduced a distinction between

earthquakes depending on which type of wave is responsible for the damage: the authors

assumed that surface R waves are dominant for a shallow distant earthquake (ratio of

epicentral distance to focal depth > 5), whereas body waves S-waves control for deep and

close earthquakes. This study resulted in two statistically reliable expressions between PGV

and repair rate, based on the type of waves.

Also, Paolucci & Pitilakis (2007) established an empirical relation between PGV and PGS

(strain), based on a selection of a few earthquake records (see Figure 12). It was

established( Equation 6 ):

] _1300

/ smPGVPGS ? ( Equation 6 )

Figure 12 Empirical correlation between PGS (strain) anf maximum horizontal PGV

(Paolucci & Pitilakis, 2007)

Although this approach of empirical relations using transient ground strain as an intensity-

measure parameter seems really powerful, the studies carried out so far do not develop

fragility functions for the typology directly concerned with gas pipelines: these are usually

made of ductile materials, whereas the results of (O’Rourke & Deyoe, 2004) are mainly

relying on brittle segmented pipes, like cast-iron. Therefore we propose to adopt PGV as the

intensity-measure parameter: this choice allows us to benefit indeed from a large number of

empirical relations, based on a wide range of pipe typologies.

We may notice that all the presented empirical fragility curves do not consider the direction

of the pipe whereas it is acknowledged that the longitudinal strain is responsible for the

failures. This is justified because once used on the distribution network of a study case,

these relations are applied to a large number of pipelines that can assume to be randomly


32

oriented. Consequently, the additional effort of considering the angle between the pipe and

the direction of the transient displacement does not seem particularly interesting as long as

we are looking at the large number of pipes and failures.

Ground failure

Concerning ground failure, all studies found in the literature rely on the permanent ground

displacement (PGD) to describe the fragility of buried pipes: therefore this parameter is

selected as the intensity-measure index for pipeline damage due to ground failure.

However, it is worth noticing that the study by O’Rourke & Deyoe (2004) has established a

good correlation between ground strain and repair rate (Figure 13): this relationship is valid

for both transient and permanent ground deformations, thus such an intensity index could

also be used for ground failure.

Figure 13 Strain vs Repair rate correlation, for both wave propagation and permanent

ground displacement (O’Rourke & Deyoe, 2004)


33

4.4.2 Storage tanks

Past studies on the vulnerability of storage tanks usually propose PGA as the earthquake

descriptor used to define the fragility curves. This seems to be a good choice as this

acceleration-driven parameter is appropriate to account for the inertia forces inherent to

these large and usually tall structures and the liquid contents within.

4.4.3 Processing facilities

As we consider here mostly facilities sheltered in a building, a classic parameter is PGA, as

it is widely used to describe the fragility of RC or masonry buildings. Also, the behaviour of

anchored or unanchored components within the facility seems acceleration-driven and its

fragility is indeed with respect to PGA in HAZUS (NIBS, 2004).


35

5 Fragility functions for system elements

5.1 STATE-OF-THE-ART FRAGILITY CURVES PER COMPONENT


Ground shaking

The literature review has resulted in a total of 20 empirical studies (the list, in Table 11, may

not be exhaustive) that addressed the issue of fragility relations for pipeline components

subjected to transient ground shaking. We display these studies in the table below, along

with the earthquake descriptor used, the typology of pipes, and the quality of the empirical

data (i.e. number of earthquakes used):

Table 11 Summary of the fragility functions from the literature

Study Typology Intensity index Nb of earthquakes

studied

Katayama et al.,

1975

- mainly cast-iron pipes

- poor, average or good

conditions

PGA 6

Isoyama &

Katayama, 1982

- mainly cast-iron pipes PGA 1

Eguchi, 1983 - WSGWJ (welded-steel

gas-welded joints),

WSAWJ (welded-steel

arc-welded joints), AC

(asbestos cement),

WSCJ (welded-steel

caulked joints), CI (cast

iron)

MMI 4

Barenberg, 1988 - mainly cast-iron pipes PGV 3

Eguchi, 1991 - WSGWJ (welded-steel

gas-welded joints),

WSAWJ (welded-steel

arc-welded joints), AC

(asbestos cement),

WSCJ (welded-steel

caulked joints), CI (cast

iron), DI (ductile iron),

PVC, PE (polyethylene)

MMI 4


36

Study Typology Intensity index Nb of earthquakes

studied

O’Rourke et al.,

1991

- MMI 7

Hamada, 1991 - PGA 2

O’Rourke & Ayala,

1993

HAZUS (NIBS,

2004)

- brittle or flexible pipes PGV 6

Eidinger et al., 1995

Eidinger, 1998

- material type

- joint type

- diameter

- soil type

PGV 7

O’Rourke et al.,

1998

- mainly cast-iron pipes PGV, PGA, MMI 4

Isoyama, 1998 - material type

- diameter

PGV 1

Toprak, 1998 - no distinction PGV 1

O’Rourke & Jeon,

1999

- mainly cast-iron pipes

- diameter

PGV 1

Eidinger et Avila,

1999

- material type

- joint type

- diameter

- soil type

PGV -

Isoyama et al., 2000 - DI, CI, PVC, steel, AC

- diameter

- soil type

PGA, PGV 1

ALA, 2001 - material

- joint type

- soil type

- diameter

PGV 18

Pineda & Ordaz,

2003

- mainly brittle pipes (CI,

AC)

PGV 1

O’Rourke & Deyoe,

2004

- mainly cast-iron pipes PGV, PGS 5

Pineda & Ordaz,

2007

- mainly brittle pipes (CI,

AC)

PGV²/PGA 1


37

The work of Tromans (2004) resulted in a very thorough review of existing pipeline

vulnerability studies. The following subsections propose a summary of some of the most

consistent empirical relations.

Katayama et al., 1975

This is one of the very first studies trying to establish a correlation between observe seismic

damage and a strong-motion parameter (Figure 14). It is based on pipe failure rates

obtained for six earthquakes (4 of them Japanese): 1923 Kanto, 1948 Fukui, 1964 Niigata,

1968 Tokachi-oki, 1971 San Fernando and 1972 Managua earthquakes. A large scatter in

the data is observed, probably due to larger damage rates induced in certain cases by

permanent ground deformation. Most of the data used concerns cast-iron pipes, although

the 1968 Tokachi-oki earthquake includes also damage to asbestos-cement pipes. No

distinction is made on pipe diameter, joint types or pipe material. However the authors

introduce a parameter b ( Equation 7), which depends on several factors like soil condition or

pipe age. Depending on the “poor”, “average” or “good” conditions, this constant can take

the respective values of 4.75, 3.65 or 2.0 (Ayala & O’Rourke, 1989).

PGAbRR

log39.610 -? ( Equation 7 )

Figure 14 Pipeline fragility data of Katayama et al. (1975) as presented by O'Rourke &

Liu (1999)


38

Eguchi, 1991

This study is an update of the earlier work of Eguchi (1983), based on damage date from

four earthquakes: 1969 Santa Rosa, 1971 San Fernando, 1972 Managua and 1979 Imperial

Valley earthquakes. This study explicitly separates wave propagation damages from those

induced by permanent ground deformation, and a distinction is made between different pipe

materials and joint types. Bilinear relations with respect to macroseismic intensity (Modified

Mercalli Intensity) are proposed for each of the pipe types.

Figure 15 Bilinear pipeline fragility relations by (Eguchi, 1991)

O’Rourke & Ayala, 1993

This study uses the original data from Barenberg (1988), plus three additional earthquakes:

1983 Coalinga, 1985 Michoacan and 1989 Tlahuac earthquakes. A total of 11 data points

are used to plot the trend line with respect to PGV (Figure 16), as it was found earlier by

Katayama et al. (1975) and Barenberg (1988) that PGA is not the best earthquake descriptor

for pipeline damage. The fragility equation is given by( Equation 8:

25.20001.0 PGVRR ? ( Equation 8 )

It appears to be only valid for brittle pipes, as the damage data is based on asbestos-

cement, concrete and cast-iron pipes: for more ductile pipe material, it is recommended to

multiply the repair rate by a corrective factor of 0.3.


39

Figure 16 Fragility relations of Barenberg (1988) and O'Rourke & Ayala (1993)

Eidinger et al, 1995, 1998

The work of Eidinger et al. (1995) and Eidinger (1998) is based on the same data as

O’Rourke & Ayala (1993), plus the 1989 Loma Prieta earthquake (i.e. seven US and

Mexican earthquakes in total). Detailed pipeline data have allowed the authors to estimate

different fragility relations based on various factors such as pipe material, diameter, joint type

or soil corrosion. The “best-fit” relation (in this case regression with all data) is defined by the

equation below ( Equation 9 ) and displayed on Figure 17:

98.1

1 0001658.0 PGVKRR ? ( Equation 9 )

Without any distinction on the pipe features, K1=1. Otherwise, the values of this corrective

factor are given inTable 12, for different pipe configurations.


40

Figure 17 Fragility function by Eidinger et al. (1995, 1998), for all data

Table 12 Values of corrective factor K1, according to Eidinger et al. (1995, 1998)

pipe material joint type soil Diameter K1 quality index

cement unknown Small 0.8 B

cement corrosive Small 1.1 C

cement non corrosive Small 0.5 B

CI

rubber gasket unknown Small 0.5 D

arc welded unknown Small 0.5 C

arc welded corrosive Small 0.8 D

arc welded non corrosive Small 0.3 B

arc welded all Large 0.15 B

WS

rubber gasket unknown Small 0.7 D

rubber gasket all Small 0.5 C

cement all Small 1.0 B

AC

cement all Large 2.0 D

welded all Large 1.0 D C

cement all Large 2.0 D

PVC rubber gasket all Small 0.5 C

DI rubber gasket non corrosive All 0.3 C


41

Each of these K1 values is linked to a quality index that gives the degree of confidence in the

empirical data used:

- B: “there is a reasonable amount of background empirical data and study”;

- C: “limited empirical data and study”;

- D: “based largely on extrapolation and judgment, with very limited empirical data”;

Isoyama et al., 2000

The work by Isoyama et al. (2000) is based on earlier studies of the 1995 Kobe earthquake.

The damage data is concentrated on distribution pipes located in Kobe and two others cities

nearby. The following functional forms ( Equation 10 )and( Equation 11 ) is adopted to

represent the pipeline repair rate:

0( ) ( )p d g L

RR IM B B B B R IM? ( Equation 10 )

* +0 min( )b

R IM a IM IM? / ( Equation 11 )

The intensity measure parameter, IM, is either PGA or PGV. R0 represents the “standard”

repair rate, for cast-iron pipes with medium diameter located in alluvial soil (Figure 18). The

authors account for various typologies (pipe material, diameter, ground topography,

liquefaction) by introducing corrective factors Bp, Bd, Bg and BL (see Table 13).

Table 13 Values of corrective factors according to (Isoyama et al., 2000). Bracketed

values are less reliable due to small sample size.

pipe material, Bp pipe diameter (mm),

Bd

ground topography,

Bg

liquefaction, BL

DI 0.3 75 1.6 disturbed hill 1.1 no liquefaction 1.0

CI 1.0 100-150 1.0 Terrace 1.5 partial

liquefaction

2.0

PVC 1.0 200-400 0.8 narrow valley 3.2 total

liquefaction

2.4

Steel (0.3) > 500 (0.5) Alluvial 1.0

AC (1.2) stiff alluvial 0.4

For PGA, 19 data points were used and a relation was established with a=2.88x10-6 and

b=1.97. In the case of PGV, the values a=3.11-3 and b=1.6 were found to best fit the 16 data

points. The corresponding lines are displayed in the figure below:


42

Figure 18 Fragility relations by Isoyama et al. (2000), for both PGA (a) and PGV (b)

parameters, without corrective factors

ALA, 2001

The work carried out in (ALA, 2001) is a compilation of several past studies, including a total

of 18 earthquakes:

- Eidinger et al., 1995;

- Katayama et al., 1975;

- O’Rourke & Ayala, 1993;

- Shirozu et al., 1996;

- Toprak, 1998;

The study consists mainly in a homogenization of all available data and some data cleaning

(some points were excluded due to an excessive influence of permanent ground deformation

effects). This compilation gathers also a good sample of different material types, including

ductile ones. A total of 81 data points are extracted and used to build a “backbone” curve,

based on a single linear model, defining the median slope of all data points:


43

Figure 19 "Backbone curve" proposed by ALA (2001), representing the median repair

rate of all data points, and the corresponding 16th and 84th quantiles.

The median curve is given by the following equation (with K1=1):

PGVKRR 002416.01? ( Equation 12 )

Like the work of Eidinger et al. (1995, 1998), a corrective factor K1 is introduced in order to

account for various configurations such as pipe material, diameter, joint type, soil corrosion.

The different values of this factor are given in the table below:


44

Table 14 Values of corrective factor K1, according to (ALA, 2001)

pipe material joint type soil diameter K1

cement unknown small 1.0

cement corrosive small 1.4

cement non corrosive small 0.7

CI

rubber gasket unknown small 0.8

arc welded unknown small 0.6

arc welded corrosive small 0.9

arc welded non corrosive small 0.3

arc welded all large 0.15


screwed all small 1.3

WS

riveted all small 1.3

rubber gasket all small 0.5 AC

cement all small 1.0

welded all large 0.7

cement all large 1.0

C

rubber gasket all large 0.8

PVC rubber gasket all small 0.5

DI rubber gasket all small 0.5

O’Rourke & Deyoe, 2004

The work of (O’Rourke & Deyoe, 2004) includes data from three US and two Mexican

events: 1965 Puget Sound, 1971 San Fernando, 1983 Coalinga, 1985 Michoacan and 1994

Northridge earthquakes. They introduce a criterion to select only statistically reliable data (

Equation 13 )where n is the minimum number of km of pipe data for a given repair rate):

RR

RRn

/…

136.15 ( Equation 13 )

This led to the selection of 14 data points. Then, using the PGV value, the authors back-

calculate the transient ground strain (based on the apparent wave propagation velocity, see

equations in Table 10). A distinction is made between earthquakes generating surface

waves (“shallow” earthquake and “distant“ basin) and events where body S-waves are

dominant: the velocity of R-waves is assumed to be CR=500 m/s, whereas CS=3000 m/s.

These assumptions are used to develop the following fragility relations Equations 14, 15 and

16, based on both transient ground strain and PGV:


45

92.0724g?RR (for all cases) ( Equation 14 )

92.0064.0 PGVRRR ? (if Rayleigh waves are dominant) ( Equation 15 )

92.00035.0 PGVRRS ? (if shear waves are dominant) ( Equation 16 )

This analysis has been performed mainly on segmented cast-iron pipelines.

Ground failure

For the damages related to permanent ground deformation effects, the literature review

resulted in 7 studies, which are presented in the table below:

Table 15 Summary of the past studies on fragility of pipeline components subjected

to permanent ground deformation

Study Typology Proposed relation

Eguchi, 1983 - WSGWJ (welded-steel gas-

welded joints), WSAWJ

(welded-steel arc-welded

joints), AC (asbestos

cement), WSCJ (welded-

steel caulked joints), CI (cast

iron)

see Figure 20

Honegger & Eguchi, 1992

HAZUS (NIBS, 2004)

- ductile (steel, DI, PVC) or

brittle (AC, concrete, CI)

56.0821.7 PGDKRR ?

K=0.3 for flexible pipes

Ballantyne & Heubach, 1996 - material : WS, old steel and

CI, locked converse, AC, CI

relative vulnerability (see

ぇlうそたg! ぉて gとぬiかて

ヾとてえそiにjさな kさな gちglてとうな

hiちくとえしさせi.)

Eidinger & Avila, 1999 - ductile of brittle pipes 53.0

2 674.23 PGDKRR ?

K2=0.5 for flexible pipes

ALA, 2001 - material

- joint type

319.0

2 223.11 PGDKRR ?

See Table 16for K2 values

Terzi et al., 2006, 2007 - segmented pipes (PVC) 4103.02103.3 PGDRR ?

The empirical fragility curves proposed by Eguchi (1983) are shown in the figure below. The

author has focused his work on localised abrupt PGD induced by fault ruptures or landslides.

These hazards are indeed likely to induce high strains, as opposed to spatially distributed

deformations induced by ground shaking.


46

Figure 20 Fragility relations proposed by (Eguchi, 1983) for fault ruptures

The study by ALA (2001) is based on empirical judgement, along with engineering

judgement. Like for the wave propagation related damage, the proposed “backbone curve”

can be modified by a corrective factor K2 according to the pipe’s material and joint type. The

different values of the factor K2 are presented in the table below:

Table 16 Values of the corrective factor K2 according to (ALA, 2001)

Pipe material Joint type K2

Unknown Unknown 1.0

cement 1.0

rubber gasket 0.8

CI

mechanical restrained 0.7

arc-welded, lap welds 0.15 WS

rubber gasket 0.7

rubber gasket 0.8 AC

cement 1.0

welded 0.6

cement 1.0

Concrete

rubber gasket 0.7

PVC rubber gasket 0.8

DI rubber gasket 0.5


47

A study by Ballantyne & Heubach (1996) proposes also to rate various pipe typologies:

ruggedness (strength and ductility of the pipe barrel), resistance to bending failure, joint

flexibility, and joint restraint. A grade from 1 to 5 is attributed to each of these criteria and a

global evaluation of the relative vulnerability of each typology is established (Table 17).

Table 17 Proposed vulnerability indices by Ballantyne, for various pipe materials and

joint types (B&S: bell and spigot, RG: rubber gasket, R: restrained, UR: unrestrained)

material joint type

rug

ge

d

ne

ss

be

nd

ing

join

t

fle

xib

ilit

y

join

t

res

tra

int Total

HDPE Fusion 4 5 5 5 19

Steel Arc-welded 5 5 4 5 19

Steel Riveted 5 5 4 4 18

Steel B&S, RG, R 5 5 4 4 18

DI B&S, RG, R 5 5 4 4 18

Steel B&S, RG, UR 5 5 4 1 15

DI B&S, RG, UR 5 5 4 1 15

Concrete B&S, R 3 4 4 3 14

PVC B&S, R 3 3 4 3 13

Concrete B&S, UR 3 - 4 1 12

AC (>8” d.) Coupled 2 4 5 1 12

CI (>8” d.) B&S, RG 2 4 4 1 11

PVC B&S, UR 3 3 4 1 11

Steel Gas welded 3 3 1 2 9

AC (<8” d.) Coupled 2 1 5 1 9

CI (<8” d.) B&S, RG 2 1 4 1 8

CI B&S, rigid 2 2 1 1 6

5.1.2 Storage tanks

We propose here a brief description of each of the fragility curves found in the literature

review for storage tanks.

O’Rourke & So, 2000

This study is based on the investigation of the fragility of on-grade steel tanks: more than

400 tanks damages are selected from 9 earthquake events: 1933 Long Beach, 1952 Kern

County, 1964 Alaska, 1971 San Fernando, 1979 Imperial Valley, 1983 Coalinga, 1989 Loma


48

Prieta, 1992 Landers and 1994 Northridge earthquakes. The size of the available data

allowed the authors to investigate the effects of two parameters:

- the tank’s height to diameter ratio, H/D;

- the relative amount of stored contents, % Full;

No distinction is made between anchored and unanchored tanks, as this condition was only

specified for 40% of the data: however, for the tanks, where the anchorage is known, it is

found that a vast majority of them were unanchored. The damage states are described in

Table 4, and were chosen very similar to the ones of the HAZUS methodology.

Using a logistic regression to fit the data, the authors convert it into the following functional

form (lognormal distribution shown in ( Equation 17 )):

* + ÙÚ

×ÈÉ

ÇÕÕÖ

ÔÄÄÅ

Ã?

µ

xxdsP ln

1

dh ( Equation 17 )

The parameters µ and く are specified in the table below, for each tank configuration:

Table 18 Median and standard deviation parameters for the fragility curves proposed

by O'Rourke & So (2000)

All tanks H/D < 0.70 H/D > 0.70 % Full < 50% % Full > 50%

µ(g) く µ(g) く µ(g) く µ(g) く µ(g) く

DS2 0.70 0.48 0.67 0.50 0.45 0.47 0.64 0.41 0.49 0.55

DS3 1.10 0.35 1.18 0.34 0.69 0.32 - - 0.86 0.39

DS4 1.29 0.28 1.56 0.35 0.89 0.21 - - 0.99 0.27

DS5 1.35 0.22 1.79 0.29 1..07 0.15- - - 1.17 0.21

In the case of tanks that are less than 50% full, only the fragility curve of DS2 is defined: this

is due to the lack of consistent data for higher damages.

ALA, 2001

The ALA study is based on a damage inventory of 424 on-grade steel tanks carried out by

Cooper (1997), plus additional data from other earthquake events. During the 1989 Loma

Prieta earthquake, around 1670 tanks were exposed to relatively low levels of ground motion

(between 0.03 and 0.1g): hardly any of these tanks suffered some damage, therefore they

were not included in the analysis. As a result, 532 tanks, which experienced strong ground

motions of 0.1g or higher, were used to develop empirical fragility curves. For each data

point, the damage description in Table 6 is used to set the corresponding damage state.

A typology distinction is made depending on the percentage of stored contents and the

anchorage of the tank to the baseplate. The parameters µ and く (of a lognormal distribution,

( Equation 17 )) of the corresponding fragility curves are given in Table 19.


49

Table 19 Median and standard deviation parameters for the fragility curves proposed

by ALA (2001)

µ(g) く µ(g) く µ(g) く µ(g) く

DS2 0.56 0.80 0.18 0.80 0.71 0.80 0.15 0.12

DS3 >2.00 0.40 0.73 0.80 2.36 0.80 0.62 0.80

DS4 - - 1.14 0.80 3.72 0.80 1.06 0.80

DS5 - - 1.16 0.80 4.26 0.80 1.13 0.10

% Full < 50%

All

N=95

% Full > 50%

All

N=251

% Full > 50%

Anchored

N=46

% Full > 50%

Unanchored

N=201

Like O’Rourke et So (2000), the ALA study concludes that the tanks that are less than half-

full did not experience enough damage to compute fragility curves for DS4 and DS5. Thus,

only the tanks with a fill percentage higher than 50% were considered to estimate additional

curves, based on the anchorage of tanks.

Berahman & Behnamfar, 2007

This study has already been introduced in sub-section 3.2.2: the authors develop fragility

curves for unanchored on-grade steel tanks, using a Bayesian approach. Using the same

damage states definitions and the same tanks database as ALA (2001), fragility curves for

DS2, DS3 and DS4 are developed: no functional form is available, and the curves are

displayed in the figures below. Due to a too small amount of data for DS5, this curve has not

been developed by the authors.

Figure 21 Fragility curves of Berahman & Behnamfar (2007), for DS2

(g)


50



The “predictive” fragility curve is the one to consider, as it accounts for epistemic

uncertainties (model parameters are then treated as random variables, in the same manner

as aleatory variables). Also, the authors discuss on whether to exclude the 1994 Northridge

earthquake data: indeed, this earthquake generated very few damages given the ground

motion level, and it is found that the data without Northridge provides a better fit. However, in

order to be coherent with other studies like O’Rourke & So (2000) or ALA (2001), the curves

presented above finally include the Northridge earthquake.

(g)

(g)


51

Iervolino et al., 2004

This analytical approach, already presented in sub-section 3.2.3, focuses on unanchored

steel tanks failure by elephant’s foot buckling. The results (µ and く parameters of the

lognormal distribution) are displayed as a response surface, accounting for two effects:

- fluid height-over-radius ratio;

- friction coefficient between the tank and the baseplate;

It is of course found that the tank’s vulnerability increases with the level of stored liquid. The

response surfaces for both µ and く are presented below (respectively Figure 24 and Figure

25).

Figure 24 Fitted surface for fragility median µ


52

Figure 25 Fitted surface for fragility standard deviation く

HAZUS, 2004

The HAZUS methodology proposes fragility curves for “tanks farms”, accounting also for the

fragility of the equipment needed for the tank facilities to function properly:

- electric power (commercial or backup generator);

- tank;

- elevated pipes;

- electrical/mechanical components;

These components are then assembled in the logic fault-tree below (Figure 26):


53

Figure 26 Fault-tree analysis proposed by HAZUS (NIBS, 2004) to assess the

vulnerabiltiy of tank farms

The fragility curves of each component are defined by the median and standard deviation

parameters (lognormal distribution) in Table 20:

Table 20 Fragility curves of components (anchored or unanchored) of tank farms

components, according to HAZUS (NIBS, 2004)

Anchored Unanchored Components Damage

state µ(g) く µ(g) く

Electric Power (Backup) minor

moderate

0.80

1.00

0.60

0.80

0.20

0.40

0.60

0.80

Loss of commercial Power minor

moderate

0.15

0.30

0.40

0.40

0.15

0.30

0.40

0.40

Electrical/ Mechanical Equipment moderate 1.00 0.60 0.60 0.60

Steel tank minor

moderate

extensive

complete

0.30

0.70

1.25

1.60

0.60

0.60

0.65

0.60

0.15

0.35

0.68

0.95

0.70

0.75

0.75

0.70

Elevated pipes extensive

complete

0.53

1.00

0.60

0.60

0.53

1.00

0.60

0.60

Finally, using the fault-tree analysis and the fragility parameters of the sub-components, it is

possible to propose fragility curves for steel tank farms, with anchored or unanchored

components. Table 21 shows the parameters of the corresponding lognormal distributions:


54

Table 21 Fragility parameters (lognormal distribution) for steel tank farms, according

to HAZUS (NIBS, 2004)

Typology Damage state µ(g) く

slight / minor 0.29 0.55

moderate

extensive 0.50 0.55

Tank farm with

anchored

components

complete 0.87 0.50


moderate 0.23 0.55

extensive 0.41 0.55

Tank farm with

unanchored

components

complete 0.68 0.55


LESSLOSS, 2007

Concerning pumping / compressor stations, a study by LESSLOSS (2007) and Kappos et al.

(2006) has proposed an hybrid approach (building fragility curve and Boolean logic tree for

the components) to develop fragility curves for these facilities (in R.C. low rise buildings,

anchored components). The parameters of the lognormal distribution are given in the table

below:

Table 22 Median and standard deviation parameters of the fragility curves for

pumping plants (LESSLOSS, 2007)



moderate 0.15 0.55

extensive 0.30 0.70

Pumping plants with anchored

subcomponents and RC1.1.X.X building

(1-3 floors, with low level seismic codes)

complete 0.40 0.75


moderate 0.30 0.35

extensive 1.10 0.55

Pumping plants with anchored

subcomponents and RC1.1.X.Y building

(1-3 floors, with advanced seismic codes)

complete 2.10 0.70


55

SRMLIFE, 2003-2007

More recently, the SRMLIFE (2003-2007) Greek project resulted in a new set of fragility

curves: also based on a fault-tree analysis of various components (commercial power,

backup generators, pump, electrical/mechanical equipment…), the fragility curves have been

developed for pumping / compressor stations (RC low-rise building, anchored components).

The fragility parameters (median and standard deviation) of the components have been

taken from the HAZUS methodology, as shown in the table below:

Table 23 Parameters of fragility curves for stations components taken from (NIBS,

2004)

Components Damage State µ(g) く

Electric Power (Backup) minor

moderate

0.80

1.00

0.60

0.80

Loss of commercial Power minor

moderate

0.15

0.30

0.40

0.40

Vertical/

Horiz. Pump

extensive 1.25/1.60 0.60

Electrical/ Mechanical Equipment moderate 1.00 0.60

Building (ぁぇ1.1.ゅ.ゃ) minor

moderate

extensive

complete

0.28

0.72

1.66

2.17

0.733

0.733

0.733

0.733

Then, using the fragility functions of all these components and the fault-tree analysis

described in section 3.2.4 (Figure 10), it is possible to establish global fragility curves for the

gas station (Table 24):


distribution) for pumping plants (SRMLIFE, 2003-2007)


minor 0.30 0.70

moderate 0.55 0.45

extensive 0.80 0.50

Anchored

components, RC

low-rise building

(advanced code)

complete 2.20 0.70


56

Risk-UE and HAZUS, 2004

Finally, the Risk-UE project (Alexoudi & Pitilakis, 2003) has used vulnerability models for the

components from the HAZUS methodology (NIBS, 2004), (parameters given in Table 20),

resulting in the following fragility curves parameters values for pumping plants with anchored

or unanchored components (Table 25), based on a fault-tree analysis of the structure of the

facility.


distribution) for pumping plants, proposed by the HAZUS methodology (NIBS, 2004)


Minor 0.15 0.75

Moderate 0.34 0.65

Extensive 0.77 0.65

Anchored

components

Complete 1.50 0.80

Minor 0.12 0.60

Moderate 0.24 0.60

Extensive 0.77 0.65

Unanchored

components

Complete 1.50 0.80

The Risk-UE fragility curves (taken from NIBS, 2004) are represented below, for both

anchored and unanchored components:

Figure 27 Fragility curves for gas pumping / compression stations (anchored

components) proposed by Risk-UE (Alexoudi & Pitilakis, 2003)


57

Figure 28 Fragility curves for gas pumping / compression stations (unanchored

components) proposed by Risk-UE (Alexoudi & Pitilakis, 2003)

Other components

Regarding pressure reduction groups, in-line valves and SCADA systems, no quantitative

fragility curves are available at present.

5.2 VALIDATION / ADAPTATION / IMPROVEMENT


According to the available typologies for gas & oil pipelines in Europe (mostly welded-steel,

PVC and HDPE continuous ductile pipes), it seems that the empirical relations found in the

literature should be satisfying in the scope of the SYNER-G project.

With the criterion of ductile pipes and the use of PGV and PGD as respective intensity

indexes for ground shaking and ground failures, the following relations constitute good

candidates for the final proposal:

- For wave propagation:

o O’Rourke & Ayala, 1993 (HAZUS);

o Eidinger et al., 1995, 1998;

o Isoyama et al., 2000;

o ALA, 2001;

- For permanent ground deformation:

o Eguchi, 1983;


58

o Honegger & Eguchi, 1992 (HAZUS);

o Eidinger & Avila, 1999;

o ALA, 2001;

Some of these relations have been tested and confronted to a European case study (2003

Lefkas earthquake), however only for water distribution pipelines: therefore these results

may not apply to the specific case of gas & oil pipelines.

5.2.2 Storage tanks

The typology of European atmospheric storage tanks may be mostly on-grade steel tanks

with anchored or unanchored components. This type should be well covered by the existing

fragility curves. Thus, we will consider the following studies, which apply to the specific

typologies and propose relevant damage states:

- O’Rourke & So, 2000;

- ALA, 2001;

- HAZUS (NIBS, 2004);


For pumping / compressor stations, the SRMLIFE (2003-2007) study covers well the Greek

typology of gas stations. Yet, some possible typologies seem to be missing, like the pumping

plants in masonry buildings, and the case of unanchored components (for both RC and

masonry buildings). Thus, we need to develop these additional curves, based on the similar

fault-tree analysis and the use of HAZUS (NIBS, 2004) fragility parameters for the station’s

components.

Also, the Re.Mi cabins and the GRF reduction groups located in the L’Aquila area appear to

be very specific and an on-going project between AMRA and ENEL gas network may

provide for the adequate fragility curves.

5.3 FINAL PROPOSAL


Ground shaking

The ALA (2001) study is the most recent one, as the HAZUS curves are still based on the

O’Rourke & Ayala (1993) study. Thus, the ALA (2001) are based on the largest set of

empirical data, including the 1994 Northridge earthquake: 18 events are used, as opposed to

6 in the O’Rourke & Ayala (1993) study. Moreover, the data from ALA (2001) comprises the

study from O’Rourke & Ayala (1993) and is enriched with other datasets.

In the ALA (2001) study, a balanced sample of U.S., Central American and Japanese

earthquake is used, accounting for the variability of pipeline codes among various countries.

Also, the consequent amount of data points (81, as opposed to 11 in O’Rourke & Ayala


59

(1993)) allows for a more balanced distribution of pipeline typologies, as shown in the table

below:

Table 26 Pipe material and pipe diameter categories included in the dataset for the

(ALA, 2001) fragility relation, according to (Tromans, 2004)

Pipeline

characteristic

Category Description % of total

database

AC asbestos-cement 12.3

CI cast-iron 46.9

CP concrete 2.5

DI ductile iron 11.1

MX mixed (CI & DI) 11.1

Material type

S steel 16.0

DS distribution system (small diameter) 70.3

LG large diameter (> 30.48 cm) 9.9

Diameter

SM small diameter (< 30.48 cm) 19.8

Moreover, the study by Tromans (2004) offers to compare some of the existing empirical

relations: these curves are plotted on the same figure below, by assuming a corrective factor

K=1 (use of the “backbone curves”).

Figure 29 Comparison of the pipeline fragility relations for PGV. Arrows refer to the

range of applicability of a given relation, approximated from knowledge of the dataset

from which it wa derived (Tromans, 2004)

As stated by O’Rourke (1999), the fragility relation by O’Rourke & Ayala (1993) seems to be

over-conservative, with pipeline repair rates being unduly affected by the long durations of


60

ground shaking experienced during the 1985 Michoacan earthquake (Tromans, 2004). The

relations by ALA (2001) and Isoyama et al. (2000) offer the longest applicability range, as

opposed to the O’Rourke & Ayala (1993) and Eidinger et al. (1995) relations, which should

not be extrapolated to large values of PGV.

The use of ALA (2001) and Isoyama et al. (1998, 2000) is also advocated by some validation

studies carried out on the 1999 Düzce and 2003 Lefkas earthquakes: “Based on these

validations it was found that the ALA (2001a,b) relationships for water/waste-water system

and Isoyama et al. (1998) for gas system are most suitable for the European distinctive

features.” (Pitilakis et al., 2006).

To conclude, we propose to sum up some comments from Tromans (2004) on the relevance

of existing fragility curves:

- the relation of O’Rourke et al. (1998) are to be used specifically in the U.S., as data

from other locations have not been included: moreover, this relation should only be

applied to cast-iron pipes;

- the Isoyama et al. (1998, 2000) relations are suggested for Japan. Yet, application to

other locations is difficult, due to the specific topographic classification scheme, which

is not normally used outside of Japan (see Table 13);

- for general application, the relation of ALA (2001) is recommended, as it is derived

from a global database;

The study of Tromans (2004) includes also an estimation of the correlation coefficient r² for

each empirical relation: it appears that r² is very low for the ALA (2001) curve, stressing a

huge scatter. However, such a scatter in the data can be expected, as the data points are

selected from various configurations: the proposed relation allows then many of the

contributors of this scatter to be accounted for, using various corrective factors (see Table

16).

Based on this discussion, we finally propose to adopt the following fragility curve from ALA

(2001):

10.002416RR K PGV? ( Equation 18 )

Where RR is the repair rate per km, and PGV is given in cm/s.

The following figure represents the adequate fragility curves to be used for each pipe

typology considered in the scope of SYNER-G (see Table 2):

- Greek transmission lines: welded-steel, small diameter => K1=0.6;

- Greek distribution lines, Austrian transmission and distribution lines, L’Aquila

distribution lines: PVC, small diameter => K1=0.5;

- Austrian supra-regional lines: welded-steel, large diameter => K1=0.15;


61

Figure 30 Proposed fragility curves for the most common gas & oil pipeline

typologies (ALA, 2001), for wave propagation

It is important to note that L’Aquila distribution lines are made of HDPE: this material is not

well studied in the current literature and we make the assumption that these pipelines can be

associated with the PVC fragility curves, although some reports show that HPDE pipes tend

to behave better than PVC.

Ground failure

Like for wave propagation-related damage, the relation of ALA (2001) is the most recent

one, as the one proposed by the HAZUS methodology is taken from Honegger & Eguchi

(1992). The dataset from ALA (2001) comprises 41 data points from 4 earthquakes (one

Japanese and three U.S.), with liquefaction as the main failure mechanism.

Thus, the ALA (2001) curve is based on the most complete empirical data and we propose

to compare some fragility curves (use of the “backbone curve”, without any corrective

factors), in the figure below:


62

Figure 31 Comparison of three fragility curves, with respect to PGD

The figure above shows important discrepancies between the different studies: the curve of

ALA (2001) lies in between the relations from Honegger & Eguchi (1992) and Eidinger &

Avila (1999). Based on this discussion and in order to be coherent with the fragility curve

selected for transient ground motion, we finally propose to adopt the following fragility curve

from ALA (2001):

0.319

211.2238RR K PGD? ( Equation 19 )

Where RR is the repair rate per km, and PGD is given in m.

The following figure represents the adequate fragility curves to be used for each pipe

typology considered in the scope of SYNER-G (see Table 2):

- Greek transmission lines, L’Aquila transmission and distribution lines: welded-steel,

small diameter => K2=0.7;

- Greek distribution lines, Austrian transmission and distribution lines, L’Aquila

distribution lines: PVC, small diameter => K2=0.8;

- Austrian supra-regional lines: welded-steel, large diameter => K2=0.15;


63

Figure 32 Proposed fragility curves for the most common gas & oil pipeline

typologies (ALA, 2001), for permanent ground deformation

5.3.2 Storage tanks

The studies by O’Rourke & So (2000) and ALA (2001) are the most thorough, as they allow

for distinction between many characteristics such as:

- % of contents stored;

- anchored or unanchored components;

- height-over-radius ratio;

However, some of the proposed fragility curves are based on really scarce empirical data,

and this may raise issues on the reliability of the data. Also, the damage states proposed by

these two studies are mostly defined by physical damage mechanisms that prove difficult to

link to any loss of functionality.

Besides, oil storage tanks are located in very complex facilities (e.g. refineries, storage

facilities…) and consider only the damage to the tank body seems to be a quite simplistic

and rather unconservative approach: indeed, the whole system of the “tank farm” should be

accounted for, including elevated pipes, power sources, mechanical equipment…

We propose then to adopt the fragility curves for “tank farms” developed in the HAZUS

methodology (NIBS, 2004) (Table 27 and Figure 33). These curves can be applied to on-

grade steel tank, with a distinction on whether components are anchored or not.


64

Table 27 Fragility parameters for steel tank farms, according to HAZUS (NIBS, 2004)



moderate

extensive 0.50 0.55

Tank farm with

anchored

components

complete 0.87 0.50


moderate 0.23 0.55

extensive 0.41 0.55

Tank farm with

unanchored

components

complete 0.68 0.55

The parameters µ and く are respectively the median and standard deviation of the

lognormal distribution of probability, with respect to PGA.

Figure 33 Fragility curves for steel tank farms (NIBS, 2004)


65


Greek pumping /compressor plants

The project SRMLIFE (2003-2007) has developed fragility curves specifically applicable to

Greek gas stations, which consist of low-rise masonry buildings with anchored components

(Figure 34 and Table 28).

Table 28 Fragility parameters for Greek pumping plants, according to (SRM-LIFE,

2003-2007)


minor 0.30 0.70

moderate 0.55 0.45

extensive 0.80 0.50

Anchored

components, RC

low-rise building

(advanced code)

complete 2.20 0.70



Figure 34 Fragility curves for Greek pumping / compressor plants (SRMLIFE, 2003-

2007)


66

Generic pumping / compressor plants

Apart from the Greek context, the typology of European gas stations is not well known, and

one solution could be to use the generic fragility curves of the HAZUS methodology (NIBS,

2004), which are based only on the distinction between anchored and unanchored

components (Table 29 and Figure 35).

Table 29 Fragility parameters of the fragility curves for pumping plants, proposed by

the HAZUS methodology (NIBS, 2004)


Minor 0.15 0.75

Moderate 0.34 0.65

Extensive 0.77 0.65

Anchored

components

Complete 1.50 0.80

Minor 0.12 0.60

Moderate 0.24 0.60

Extensive 0.77 0.65

Unanchored

components

Complete 1.50 0.80



Figure 35 Fragility curves for generic pumping / compressor plants (NIBS, 2004)


67

Re.Mi cabins (L’Aquila)

For this specific component, we can use preliminary results from the ongoing project

between AMRA and Enel Rete Gas on the l’Aquila gas system.

The fault-tree decomposition has been applied to Re.Mi cabins in order to identify which sub-

component is critical with respect to seismic fragility. All sub-components are considered to

be not anchored and simply supported on the ground (with the exception of bowls located in

a seperated area that are ceiling-mounted). The Re.Mi station is decomposed into the

following sub-components:

- Building;

- Regulators;

- Mechanical equipment (heat exchangers, boilers and bowls);

To compute the global fragility curve of the whole plant, the following faut-tree may be

formulated:

Figure 36 Fault-tree analysis of a Re.Mi cabin according to (Esposito et al., 2011)

Since gas supply has to be maintained at all times, two installations are mounted in parallel

where each installation is characterized by a regulator and a monitor. The monitor is a safety

device that has to be able to prevent the outlet pressure from exceeding safe thresholds in

the case of complete failure of the regulator, taking over the function of the primary, normally

active regulator. During normal operation the monitor is fully open and if the pressure

becomes equal to the setpoint of the monitor, the monitor will close to constrain the

pressure.

According to experts’ experience, two damage states have been identified: complete and

extensive which correspond to a complete loss of functionality of the system (no gas supply).

The following table (Table 30) summarizes the damage states and their description.

Table 30 Damage states for the Re.Mi cabin

Damage state Description

Complete Building collapse

Extensive Extensively damaged building, or both

regulators damaged, or badly damaged

boilers/heat alimentation


68

In particular, when boilers break down the gas flow is not ensured, since the freezing stops

the system.

GRF Reductions groups (L’Aquila)

Reduction groups are decomposed in the following sub-components:

- Regulators;

- Masonry housing (when it is present, otherwise within a kiosk);

To compute the global fragility curve of the whole plant, the following fault-tree has been

formulated:

Figure 37 Fault-tree analysis of a Reduction Group (GR / GRM) according to (Esposito

et al., 2011)

In most cases the safety device is ensured by the presence of shut-off valves that are able to

block the gas flow. When the pressure exceeds a maximum value, the valves close.

Also in this case two damage states have been identified and are summarized in the

following table:

Table 31 Damage states of the Reduction Group (GR / GRM)


Complete Building collapse (mansory housing)

Extensive Extensively damaged housing, or both

regulators damaged.

However, some Reduction Groups do not have the second regulator and this characteristic

implies a higher vulnerability.


69

6 Analytical expressions of fragility functions

6.1 PIPELINE COMPONENTS

6.1.1 Wave propagation

Intensity index: PGV

Fragility curve (ALA, 2001):

10.002416RR K PGV? ( Equation 20 )

Where RR is the repair rate per km, and PGV is given in cm/s.

Table 32 Values of corrective factor K1 (ALA, 2001)

pipe material joint type soil diameter K1

cement unknown small (<30cm) 1.0

cement corrosive small 1.4

cement non corrosive small 0.7

CI

cast-iron


arc welded unknown small 0.6

arc welded corrosive small 0.9

arc welded non corrosive small 0.3

arc welded all large (>30cm) 0.15


screwed all small 1.3

WS

welded-steel

riveted all small 1.3

rubber gasket all small 0.5 AC

asbestos-

cement cement all small 1.0

welded all large 0.7

cement all large 1.0

C

concrete

rubber gasket all large 0.8

PVC rubber gasket all small 0.5

DI

ductile iron

rubber gasket all small 0.5


70

6.1.2 Permanent ground deformation

Intensity index: PGD

Fragility curve (ALA, 2001):

0.319

2 2.5831RR K PGD? ( Equation 21 )

Where RR is the repair rate per km, and PGD is given in cm.

Table 33 Values of corrective factor K2 (ALA, 2001)

pipe material joint type K2

Unknown Unknown 1.0

cement 1.0

rubber gasket 0.8

CI

mechanical restrained 0.7

arc-welded, lap welds 0.15 WS

rubber gasket 0.7

rubber gasket 0.8 AC

cement 1.0

welded 0.6

cement 1.0

Concrete

rubber gasket 0.7

PVC rubber gasket 0.8

DI rubber gasket 0.5


71

6.2 STORAGE TANKS

Intensity index: PGA

Fragility curve (HAZUS, 2004):

* + 1 ln ln1

2 2k

PGA µP D DS erf

d

Ç ×Ã Ô/‡ ? -È ÙÄ Õ

È ÙÅ ÖÉ Ú ( Equation 22 )

Table 34 Fragility parameters for steel tank farms (HAZUS, 2004)



moderate

extensive 0.50 0.55

Tank farm with

anchored

components

complete 0.87 0.50


moderate 0.23 0.55

extensive 0.41 0.55

Tank farm with

unanchored

components

complete 0.68 0.55

Table 35 Damage states definitions for tank farms (HAZUS, 2004)


DS1 none Fully functional

DS2 slight / minor Malfunction of tank farm for a short time (less than thee days)

due to loss of backup power or light damage to tanks

DS3 moderate Malfunction of tank farm for a week or so due to loss of

backup power, extensive damage to various equipment , or

considerable damage to tanks

DS4 extensive Extensive damage to tanks or elevated pipes

DS5 complete Complete failure of all elevated pipes, or collapse of tanks


72

6.3 PROCESSING FACILITIES

6.3.1 Pumping / compressor stations

Intensity index: PGA

Fragility curve (HAZUS, 2004) and (SRMLIFE, 2003-2007):

* + 1 ln ln1

2 2k

PGA µP D DS erf

d

Ç ×Ã Ô/‡ ? -È ÙÄ Õ

È ÙÅ ÖÉ Ú ( Equation 23 )

Table 36 Fragility parameters for pumping / compressor stations (HAZUS, 2004) and

(SRMLIFE, 2003-2007)


minor 0.30 0.70

moderate 0.55 0.45

extensive 0.80 0.50

Greek typology:

Anchored

components, RC

low-rise building

(advanced code) complete 2.20 0.70

Minor 0.15 0.75

Moderate 0.34 0.65

Extensive 0.77 0.65

“Generic stations”,

Anchored

components

Complete 1.50 0.80

Minor 0.12 0.60

Moderate 0.24 0.60

Extensive 0.77 0.65

“Generic stations”,

Unanchored

components

Complete 1.50 0.80


73

Table 37 Damage states definitions for pumping / compressor stations (HAZUS, 2004)

and (SRMLIFE, 2003-2007)

Damage state

Repair cost

(%)

Serviceability/

Functionality

D1 No - -

1 - 10

Normal

function D2

Slight/Minor

Slight damage to building

or full loss of commercial

power and backup power

for few days (< 3 days) 10 – 30

Several

stops and

reduced flow

of gas in the

transmission

gas

pipelines

Full function

D3

Moderate

Considerable damage to

mechanical and electrical

equipment or

considerable damage to

building or loss of electric

power and of backup for

7 days.

30 – 50

Malfunction.

(Full

function

after

repairs)

D4

Extensive

Building being

extensively damaged, or

the pumps badly

damaged beyond repair.

50 – 75

D5 Complete

damage Building collapsed 75 – 100

Disability of

boosting gas

in

compression

station Full loss of

function

(un

repairable

damage)

6.3.2 Re.Mi cabins

As a first approximation, we are compelled to use the fragility curves from HAZUS (NIBS,

2004) for pumping / compressor stations (“Generic stations” in Table 39), as the fragility of

those specific subcomponents (e.g. regulators) is not well known.

6.3.3 GRF reduction groups

As a first approximation, we are compelled to use the fragility curves from HAZUS (NIBS,

2004) for pumping / compressor stations (“Generic stations” in Table 39), as the fragility of

those specific subcomponents (e.g. regulators) is not well known.


75

References

Adachi, T. 2007. Impact of cascading failures on performance assessment of civil

infrastructure systems. PhD Thesis, School of Civil and Environmental Engineering,

Georgia Institute of Technology.

ALA. 2001. Seismic fragility formulations for water systems. American Lifeline Alliance,

ASCE.

Alexoudi, M., and K. Pitilakis. 2003. Vulnerability assessment of lifelines and essential

facilities (WP06): methodological handbook – Appendix 7: gas utility system. Risk-UE

Report n° GTR-RSK 0101-152av7.

ASCE. 1984. Guidelines for the seismic design of oil and gas pipeline systems. Technical

Council on Lifeline Earthquake Engineering, prepared by the Committee on Gas and

Liquid Fuel Lines, ASCE, 473 pp.

ASCE. 1987. The effects of earthquakes on power and industrial facilities and implications

for nuclear power plant design. Committee on Dynamic Analysis of the Committee on

Nuclear Structures and materials of the Structural Division, ASCE.

Ayala, G., and M. J. O'Rourke. 1989. Effects of the 1985 Michoacan Earthquake on Water

Systems in Mexico. Technical Report NCEER-89-0009, National Center for Earthquake

Engineering Research, State University of New York at Buffalo, Buffalo, NY.

Ballantyne, D. B., and W; Heubach. 1996. Earthquake loss estimation for the city of Everett,

Washington, lifelines. K/J/C 906014.00, Federal Way, Washington.

Barenberg, M.E. 1988. Correlation of pipe damage with ground motion. Journal of

Geotechnical Engineering 114(6): 706-711.

Berahman, F., and F. Behnamfar. 2007. Seismic fragility curves for unanchored on-grade

steel storage tanks: bayesian approach. Journal of Earthquake Engineering 11(2): 1-31.

Bettinger, R.V. 1980. Economic and seismic mitigation for gas and electric utility. In

Conference on Social and Economic Impact of Earthquakes on Utility Lifelines. Edited by

J. Isenberg, ASCE, pp. 98-106.

Cooper, T. W. 1997. A study of the performance of petroleum storage tanks during

earthquakes, 1933-1995. Prepared for the National Institute of Standards and

Technology, Gaithersburg, MD.

Crespo, E., K. J. Nyman, T. D. O’Rourke. 1987. Ecuador earthquakes of March 5, 1987. Earthquake Engineering Research Institute, EERI Newsletter 21(7):1-4.

EERI. 1986. Reducing earthquake hazards: lessons learned from earthquakes. Publication n°86-02, Earthquake Engineering Research Institute, El Cerrito, CA.

EERI. 1990. Loma Prieta earthquake reconnaissance report. Supplement to vol. 6, Technical

Editor, Lee Benuska, Earthquake Spectra, Journal of the Earthquake Engineering

Research Institute.

Eguchi, R. T., M. R. Legg, C. E. Taylor, L. L. Philipson, J. H. Wiggins. 1983. Earthquake

Performance of Water and Natural Gas Supply System. J. H. Wiggins Company, NSF

Grant PFR-8005083, Report 83-1396-5.

Eguchi, R. T. 1987. Seismic risk to natural gas and oil systems. FEMA 139, Earthquake

Hazard Reduction Series 30, pp. 15-33.

Eguchi, R. T. 1991. Early post-earthquake damage detection for underground lifelines. Final


76

Report to the national Science Foundation, Dames and Moore PC, Los Angeles, CA.

Eidinger J., B. Maison, D; Lee, B. B. Lau. 1995. East Bay municipality utility district water

distribution damage in 1989 Loma Prieta earthquake. In Fourth US Conference on

Lifeline Earthquake Engineering, Monograph 6, ASCE, pp. 240-247.

Eidinger, J. 1998. Lifelines, Water Distribution System. in The Loma Prieta, California,

Earthquake of October 17, 1989, Performance of the Built Environment –Lifelines. US

Geological Survey Professional Paper 1552-A, pp A63-A80, A. Schiff Ed.

Eidinger, J., and E. Avila. 1999. Guidelines for the seismic upgrade of water transmission

facilities. ASCE, TCLEE, Monograph 15.

Esposito, S., S. Giovinazzi, I. Iervolino. 2011. Assessing the post-earthquake residual

functionality of gas networks and planning for restoration. In 2011 Pacific Conference on

Earthquake Engineering,14-16 April, New Zealand.

Fabroccino, G., I. Iervolino, F. Orlando, E. Salzano. 2005. Quantitave risk analysis of oil

storage facilities in seismic areas. Journal of Hazardous Materials 23: 61-69.

Hall, W. J. 1987. Earthquake engineering research needs concerning gas and liquid fuel

lifelines. FEMA 139, Earthquake Hazard Reduction Series 30, pp. 35-49.

Hamada, M. 1991. Estimation of earthquake damage to lifeline systems in Japan. In Third

Japan-US Workshop on earthquake resistant design of lifeline facilities and

countermeasures for soil liquefaction, San Francisco, CA.

Honegger, D. G., and R. T. Eguchi. 1992. Determination of the relative vulnerabilities to

seismic damage for San Diego County Water Authority: water transmission pipelines.

Iervolino, I., G. Fabbrocino, G. Manfredi. 2004. Fragility of standard industrial structures by a

response surface based method. Journal of Earthquake Engineering 8(6): 927-945.

Isoyama, R., and T. Katayama. 1982. Reliability evaluation of water supply systems during

earthquake. Report of the Institute of Industrial Science, University of Tokyo, vol. 30(1).

Isoyama, R., E. Ishida, K. Yune, T. Shirozu. 2000. Seismic damage estimation procedure for

water supply pipelines. In Twelfth World Conference on Earthquake Engineering, CD-

ROM paper n°1762, 8 pp.

Kappos, A., G. Panagopoulos, Ch. Panagiotopoulos, Gr. Penelis. 2006. A hybrid method for

the vulnerability assessment of RC and URM buildings. Bulletin of Earthquake

Engineering 44: 391-413.

Katayama, T., K. Kubo, N. Sato. 1975. Earthquake damage to water and gas distribution

systems. In US National Conference on Earthquake Engineering, Oakland, CA, EERI,

pp. 396-405.

Kennedy, R. P., and R. P. Kassawara. 1989. Seismic evaluation of large flat-bottomed tanks.

In Second Symposium on Current Issues Related to Nuclear Power Plant Structures,

Equipment, and Piping with Emphasis on Resolution of Seismic Issues in Low-Seismicity

Regions, EPRI NP-6437-D.

Kim, J., S. O’Connor, S. Nadukuru, J. P. Lynch, R. Michalowski, R. A. Green, M. P. Ghaz,

W. J. Weiss, A. Bradshaw. 2010. Behavior of full-scale concrete segmented pipelines

under permanent ground displacements. In Conference on Health Monitoring of

Structural and Biological Systems, San Diego, CA.

LESSLOSS. 2007. Damage scenarios for selected urban areas (for water and gas systems,

sewage mains, tunnels and waterfront structures: Thessaloniki, Istanbul (European side),

Düzce. LESSLOSS Project Deliverable n°117.

NIBS. 2004. Earthquake Loss Estimation Methodology HAZUS. National Institute of Building

Sciences, FEMA, Washington D.C.H

NZNSEE. 1986. Seismic design of storage tanks. Recommendations of a Study Group of the

New Zealand National Society for Earthquake Engineering.


77

Ogawa, N. 1983. A vibration test of earthquake induced hydraulic transients of liquid-filled

pipelines. In Symposium on Lifeline Engineering, Earthquake Behavior and Safety of Oil

and Gas Storage Facilities, Buried Pipelines and Equipment. PVP 77, ASME.

O’Rourke, M. J. 1988. Mitigation of seismic effects on water systems. In Seismic Design and

Construction of Complex Civil Engineering Systems. Symposium sponsored by

TCLEE/ASCE, National Convention, St Louis, MO, pp. 65-78.

O’Rourke, M. J., and G. Ayala. 1990. Seismic damage to pipeline: case study. Journal of

Transportation Engineering 116(2): 123-134.

O’Rourke, M. J., and G. Ayala. 1993. Pipeline damage due to wave propagation. Journal of

Geotechnical Engineering 119(9):1490-1498.

O'Rourke, M. J., and X. Liu. 1999. Response of Buried Pipelines Subject to Earthquake

Effects. MCEER Monograph No. 3.

O’Rourke, M. J. 1999. Estimation of post-earthquake water system serviceability. In Seventh

Japan-US Workshop on Earthquake Resistant Design of Lifeline Facilities and

Countermeasures for Soil Liquefaction, MCEER, State University of New York at Buffalo,

Buffalo, NY, 391-403.

O’Rourke, M. J., and P. So. 2000. Seismic fragility curves for on-grade steel tanks.

Earthquake Spectra 16(4).

O’Rourke, M. J., and E. Deyoe. 2004. Seismic damage to segment buried pipe. Earthquake

Spectra 20(4): 1167 – 1183.

O’Rourke, T. D., and C. H. Trautmann. 1981. Earthquake ground rupture effects on jointed

pipe. In Second Specialty Conference of the Technical Council on Lifeline Earthquake

Engineering. D. J. Smith, Editor, pp. 65-80.

O’Rourke, T. D., S. Toprak, Y. Sano. 1998. Factors affecting water supply damage caused

by the Northridge earthquake. In Sixth US national Conference on Earthquake

Engineering.

O’Rourke, T. D., and S. S. Jeon. 1999. Factors affecting water supply damage caused by

the Northridge earthquake. In Fifth US Conference of Lifeline Earthquake Engineering,

Seattle, WA.

Paolucci, R., and K. Pitilakis. 2007. Seismic risk assessment of underground structures

under transient ground deformations . In Fourth International Conference on Earthquake

Geotechnical Engineering, Thessaloniki, Greece.

Pineda, O., and M. Ordaz. 2003. Seismic vulnerability function for high diameter buried

pipelines: Mexico City’s primary water system case. In International Conference on

Pipeline Engineering Construction, vol. 2, pp. 1145-1154.

Pineda, O., and M. Ordaz. 2007. A new seismic parameter to estimate damage in buried

pipelines due to seismic wave propagation. Journal of Earthquake Engineering 11(5):

773-786.

Pitilakis, K., M. Alexoudi, S. Argyroudis, O. Monge, C. Martin. 2006. Earthquake risk

assessment of lifelines. Bulletin of Earthquake Engineering 4: 365-390.

Rauch, A. F. 1997. EPOLLS: An empirical method for predicting surface displacements due

to liquefaction-induced lateral spreading in earthquakes. PhD Thesis, Virginia

Polytechnic Institute and State Univ., Blacksburg, VA.

Singhal, A. C. 1984. Nonlinear behavior of ductile iron pipeline joints. Journal of Technical

Topics in Civil Engineering 110(1).

SRMLIFE. 2003-2007. Development of a global methodology for the vulnerability

assessment and risk management of lifelines, infrastructures and critical facilities.

Application to the metropolitan area of Thessaloniki. Research Project, General

Secretariat for Research and Technology, Greece.


78

St John, C. M., and T. F. Zahrah. 1987. Aseismic design of underground structures. TUST

2(2): 165-197.

Terzi, V. G., M. N. Alexoudi, T. N. Hatzigogos. 2007. Numerical assessment of damage state

of segmented pipelines due to permanent ground deformation. In Tenth International

Conference on Applications of Statistics and Probability in Civil Engineering, Tokyo,

Japan, Paper n°202.

Toprak, S. 1998. Earthquake effects on buried lifeline systems. PhD Thesis, Cornell

University, Ithaca, NY.

Tromans, I. 2004. Behaviour of buried water supply pipelines in earthquake zones. PhD

Thesis, Imperial College of Science, Technology and Medicine, University of London.

Young, F. M., and J. M. Pardon. 1983. Hydraulic transients in liquid-filled piping networks

due to seismic excitation. In Symposium on Lifeline Engineering, Earthquake Behavior

and Safety of Oil and Gas Storage Facilities, Buried Pipelines and Equipment. PVP 77,

ASME.

Encrypted D3.4 SYNER-G Fragility functions for gas and oil ...

Documents

Transcript of Encrypted D3.4 SYNER-G Fragility functions for gas and oil ...