Project Participants:

Queensland University of Technology (QUT)Central Queensland University (CQU)Monash University (MU)University of Wollongong (UOW)

Industrial Partners:

V/LineDepartment of Transport VictoriaRio TintoARTC & KiwiRail

Outline of the Presentation

• An overview

• Common weaknesses of existing BMS in Australia

• Maintenance optimisation process – summary

• Framework of the proposed BMS

• Classification (or Categorisation) of network of bridges

• Prediction of Remaining Service Potential (RSP)

• Durability Assessment of Steel Bridges: Failure Due to Corrosion and

Cracking

• Criticality and Vulnerability Analysis

• Synthetics Rating

• Maintenance optimisation

There are over 9,480 bridges in the major Australian Rail Networks:

– 3,710 in Queensland Rail (including QRN);

– 3,230 in ARTC;

– 1,200 in RailCorp;

– 990 in V/Line;

– 350 in TasRail and

– 40 in Rio Tinto

• Over 30% of these bridges are over 80 years old

• Replacement of 3000 bridges nationally at a cost of $4.5 Billion over 20 years

An Overview

Common weaknesses of existing BMS in Australia

Syndromes and symptoms

• Bridge classification (or categorisation) is generic

• Inspection records are not detail enough for maintenance optimisation at network

level

• Deterioration models are not in use and remaining service potential cannot be

predicted

• Maintenance intervention points cannot be identified

• Maintenance strategies cannot be compared (eg. Repair work, Strengthening)

• Subjective maintenance work based on human judgements

• Item vice cost cannot be identified and maintenance cost cannot be optimised

Maintenance Optimisation Process - Summary

Future conditions of the components (UOW and

MU)

Rating based on structural Criticality and Vulnerability

analysis (QUT)

Rate Bridges based on current and future conditions (Synthetic rating)

Remaining life + Intervention frequencies

Current conditions of the components from inspection

Alternative management strategies

MR&R optimisation

Work orders

QUT

UOW+MU+QUT

CQU

CQU

Phase 1Phase 1

Framework of the Proposed BMS

Inspection module

Synthetic rating module

Bridge Inventory Data

Environmental classification

Deterioration modelling

Bridge Classification

Loading

QUT UOW+MU

Future Condition Assessment (Prediction)

Current Condition Assessment

Intervention frequencies

Mai

nten

ance

His

tory

QUT+ UOW+MU

QUT

Future condition of components

Remaining Service Potential (RSP) of components

Rating based Criticality and Vulnerability

Flood, Wind, EarthquakeVehicle collision,

Environmental effects

Phase 2 Phase 2

Framework of the proposed BMS (cont)

Maintenance quality or political decisions

UnacceptableBudget limits

Project level optimization

Network level optimization(Network level criticality)

Component interaction

Analysis period, analysis scenarios and base case

Define alternative bridge management strategies(Preventative maintenance, Repair work, Strengthening, Replacement, Do Nothing)

Calculate Net Present Value

Minor works or Regular repair

Estimate costs· Agency & routine maintenance· User, work related, other· Vulnerability cost

Modify management strategies

MR&R optimization module

Assignment of projects to work groups

Prepare work bids and plains

Select preferred strategy

Record maintenance history

Maintenance implementation

Per

form

ance

rev

iew

CQU

Classification (or Categorisation) of network of bridges

Prediction of Remaining Service Potential (UOW)

• Contributing factors :

Rail-traffic volume (Tonnage ) Number of tracks, Material type, Functional class,

Nature of the defect Structure type Environmental categories, etc.

Markov chain based stochastic deterioration models were selected

Regression-based nonlinear optimization techniques were use to estimate the Transition Probability Matrixes (TPM) .

Deterioration curves were developed for classified element groups based on their; Structural role Maintenance requirements Costing or inspection procedures Environmental category Traffic volume

(a) Network level Analysis Results By using one TPM

A typical example for a TPM of a primary beam (Average Performance Index vs Age)

(b) Network level Analysis By using multiple TPMs (c) Application of Markov approach for approximate service life prediction of single components

Highlights

• Expected performance index curves and transition probability derived for entire life of a subcomponent can be used to comparison purpose and network level bridge management decisions.

• Markov approach can be used to predict the average remaining service life estimation of individual components after considering non-homogeneity of the deterioration process, by considering separate Transition Probability for different time zones .

• Inspection intervals need to be predicted by rating each important element of these components.

• Accuracy of the service life estimation is depend on the reliability of the data. Transition Probability matrixes should be updated when new data available in the future.

Remaining Service Potential of Steel Bridges (MU): (Failure Due to Corrosion and Cracking)

The engineering assessment of the durability requires a knowledge of both the operational usage and the environment (rate of corrosion).

Monitoring Corrosion on Bridge 44

Material behavior from 7 microns upwards can be represented as:

REPOS measured for Three Classes of Trains

Criticality and Vulnerability Analysis (QUT)

Scope: Setup of Criticality and Vulnerability Rating Criteria:

• The factors related to the Structural Condition are taken into account.• Bridges will be rated based on Synthetic Rating Method.

Critical factors: • Live Load • Environment factors such as corrosion and temperature• Extreme events such as Flood, Wind, Earthquake & Collusion

The vulnerability may refer to the vulnerability of whole structure or vulnerability of the critical elements of the structure.

The degree of the criticality of the structural elements is identified by weighting factors• Criticality of the elements due to different structural configuration• Criticality of the factors according to the environmental condition

Synthetics Rating (QUT)Components Current Future

Foundation 1 2

Abutments 4 5

Back wall 3 4

Wing walls 1 2

Piers 5 5

Columns 4 5

Primary Beams

4 5

Secondary Beams

2 3

Deck 3 4

Joints 2 3

Current Future

58.8 66.08

61.6 72.8

56.28 64.68

47.25 53.1

109.2 109.2

92.4 109.2

84.7 100.1

59 67

75.04 86.24

35.4 40.2

(1) Condition rating (Inspection+ RSP)

(2) Criticality and Vulnerability analysisCurrent condition of the bridge: 679.67

Future condition of the bridge: 775.14

Factor Current Future

Flood 241.3 265.2

Wind 0.6 0.8

Earthquake 1.1 2.2

Collision 0.0 0.0

Environment 532.1 625.2

(3) Vulnerability rating of each bridge

(4) Synthetic rating of each bridge

Maintenance optimisation (CQU)

Managing Risks with Bridge ManagementR

isk

Miti

gatio

nR

isk

Man

agem

ent

Ris

k A

naly

sis

Haz

ards

Inputs: Inventory, Condition monitoring, SHM, Load ratings, Environmental, Economic, Repair knowledge bank, Future requirements.

Deterioration Mechanisms

(Age, chloride, carbonation, corrosion, etc.)

Unexpected events(Floods, fire, derailments,

cyclone, collision, etc.)

Overloading(Train overloading)

Current bridge condition

Deterioration model

Future bridge condition

Frequency of failure

(Flood 1:30years

Fire 1:10 years)

Consequences(injury, economic, etc.)

Failure modes

Multi objective optimisation(risk, costs, reliability, condition, etc.)

Bridge criticalityEconomic and

repair costs

Schedule maintenance

Reduce bridge load capacity Reduce train speedCondition

monitoring

Priority Order

Element Criticality

Defect Severity

Network Criticality

1 4 5 Use

Highest%

first

2 4 43 3 54 3 45 2 56 2 47 1 58 1 49 4 3

10 3 311 2 312 1 3

Maintenance optimisation... Priority ranking

Risk Priority Number

Probability of Failure Consequences of Failure Consequences of Failure

Safety EnvironmentFunctionality Sustainability

Element criticality Network criticality Inspection cost (to reduce the risk)

Maintenance/ repair cost

Bridge element criticality ratingCriticality

RatingDescription

1 Non-structural2 Structural with redundancy3 Protective4 Structural without redundancy

Network Criticality

Repair priority ranking

Proposed Software Platform

AcknowledgementTo our Industrial partners including V/Line, Rio Tinto and ARTC for their generous support.

V/line– North East corridor