Optimizing Railroad Transportation Safety Improvement Strategies

ILLINOIS - RAILROAD ENGINEERING

Optimizing Railroad Transportation Safety Improvement Strategiesy p g

Rapik Saat, Ph.D., Chris Barkan, Ph.D.p , , ,Rail Transportation and Engineering Center (RailTEC)

University of Illinois at Urbana-Champaign

14 November 2011INFORMS Meeting


Outline

• Mainline derailment cause analysis• Mainline derailment cause analysis

• Risk reduction strategies

• Railroad infrastructure/track class upgrade• Railroad infrastructure/track class upgrade

• Integrated optimization model

Rail transportation safety and risk analysis questions and• Rail transportation safety and risk analysis questions and challenges


U.S. Class I railroad mainline derailments by accident cause group: 2000 2009accident cause group: 2000-2009

Signals 0.5%

Misc.(12%)

Track(38%)

Human Factors(15%)

Equipment(35%)

Notes:1. FRA Railroad Accident/Incident Reporting System (RAIRS) database, 2000-20092. Total of 3,995 train derailments involving Class I trains derailed on Class I railroad mainline track, track classes 1 to 53. Includes BNSF, UP, CSX, NS, KCS, CP (SOO) and CN (GTW)4. Excludes derailments due to train collisions and highway-rail crossing collisions


Mainline derailments due to track-related causes

562 (37%)*

0 100 200 300 400 500 600

Broken Rails or Welds

Number of Class I Mainline Derailments, 2000-2009

( )

277 (18%)

134 (9%)

120 (8%)

Track Geometry (excl. Wide Gauge)

Wide Gauge

B ckled Track 120 (8%)

92 (6%)

66 (4%)

Buckled Track

Turnout Defects - Switches

Misc. Track and Structure Defects

64 (4%)

59 (4%)

45 (3%)

Joint Bar Defects

Roadbed Defects

Other Rail and Joint Defects

40 (3%)

37 (2%)

10 (1%)

Rail Defects at Bolted Joint

Non-Traffic, Weather Causes

Turnout Defects - FrogsNote: 1. Indicates percentage of all track-related derailments, e.g. broken rails or welds caused 37%2. 1,506 total track-related derailments from 2000-2009, involving Class I trains derailed on Class I mainline track, track classes 1 to 53. Includes BNSF, UP, CSX, NS, KCS, CP (SOO) and CN (GTW)4. Excludes derailments due to train collisions and highway-rail crossing collisions

10 (1%)Turnout Defects Frogs


Derailments due to equipment-related causes

252 (18%)*

214 (15%)

0 50 100 150 200 250 300

Bearing Failure (Car)Broken Wheels (Car)

Number of Class I Mainline Derailments, 2000-2009

( %)

128 (9%)

124 (9%)116 (8%)

113 (8%)

( )Other Wheel Defects (Car)

Other Axle/Journal Defects (Car)Coupler Defects (Car)

Sidebearing, Suspension Defects (Car)89 (6%)

51 (4%)

51 (4%)

44 (3%)

43 (3%)

Centerplate/Carbody Defects (Car)Loco Trucks /Bearings /Wheels

Stiff Truck (Car)All Other Car Defects

Track/Train Interaction (Hunting) (Car) 43 (3%)

40 (3%)

37 (3%)

31 (2%)

17 (1%)

Track/Train Interaction (Hunting) (Car)Other Brake Defect (Car)

Truck Structure Defects (Car)Brake Rigging Defect (Car)

Air Hose Defect (Car)15 (1%)

13 (1%)

6 (0.4%)

2 (0.1%)

1 (0 1%)

All Other Locomotive DefectsLoco Electrical and Fires

UDE (Car or Loco)TOFC/COFC Defects

Handbrake Defects (Car)Note: 1. Indicates percentage of all equipment-related derailments, e.g. bearing failure caused 18%2. 1,387 total equipment-related derailments from 2000-2009, involving Class I trains derailed on Class I mainline track, track classes 1 to 53. Includes BNSF, UP, CSX, NS, KCS, CP (SOO) and CN (GTW)4. Excludes derailments due to train collisions and highway-rail crossing collisions

1 (0.1%)Handbrake Defects (Car)


Distribution of cars derailed for different accident causes

Broken Rails Bearing Defectg


Frequency-severity graph of track- and equipment-related Class I mainline derailments 2000-2009related Class I mainline derailments, 2000 2009

25

d

Ave. = 90.4

20

Joint Bar Defects

Other Rail and Joint Defects

Rail Defects at Bolted Joint

ars

Der

aile

d

10

15 Broken Rails or Welds

Wide Gauge

Buckled Track

Num

ber o

f Ca

A 9 2

5

10

Track Geometry Defects (other than wide gauge)

Bearing Failure (Car)

Broken Wheels (Car)

Aver

age

N Ave. = 9.2

00 100 200 300 400 500 600

Number of DerailmentsNote: 1. Total of 2,893 track- and equipment-related derailments from 2000-2009, involving Class I trains derailed on Class I mainline track2. Includes BNSF, UP, CSX, NS, KCS, CP (SOO) and CN (GTW)3. Excludes derailments due to train collisions and highway-rail crossing collisions


Potential risk reduction strategiesInfrastructure Operational

Railcar/Container

Track class upgradeReduce accident occurrence

Speed reductionReduce accident severity

RoutingRailcar/Container Routing

Tank car safety designReduce incidence and

severity of releases

Alternative routingsReduce impact of releases


Example risk reduction strategy optimization:Example risk reduction strategy optimization: Railroad infrastructure/track class upgrade

Kawprasert, A (2010). Quantitative Analysis of Options to Reduce Risk of Hazardous Materials Transportation by Railroad. PhD Dissertation, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL.


Route-specific risk analysis

f “ ”• Identify high-risk “hot spots”

• Risk is due to accident rate and population exposure

Hi h i k h h i id• Highest risk areas are where these coincide


Risk along a route is highly concentrated

23% of route96% of risk

sk

77% of route

Ris

4% of risk

• Small portion of track segments account for majority of risk

• Enables efficient prioritization of risk reduction strategies


Graphical representation of optimal track class upgrade decisions

Upgrade class‐3 segments anywherepg

0 6

0.7

0.8

0.9

0.01

0.1

1

skisk

Upgrade consecutive‐like class‐3 segments

0 6

0.7

0.8

0.9

0.01

0.1

1

sksk

0.1

0.2

0.3

0.4

0.5

0.6

0.0000001

0.000001

0.00001

0.0001

0.001

Cum

ulat

ive

Ris

Segm

ent R

i

0.1

0.2

0.3

0.4

0.5

0.6

0.0000001

0.000001

0.00001

0.0001

0.001

Cum

ulat

ive

Ris

Segm

ent R

is

0.8

0.9

0.1

11.0

d)

0.01E-080 250 500 750 1,000 1,250 1,500

Distance from Origin (miles)

0.01E-080 250 500 750 1,000 1,250 1,500

Distance from Origin (miles)

Upgrade class‐4 segments or lower anywhere

0.3

0.4

0.5

0.6

0.7

0 000001

0.00001

0.0001

0.001

0.01

Cum

ulat

ive

Ris

k

Segm

ent R

isk

0.6

0.8

Pers

ons A

ffec

ted

0.0

0.1

0.2

1E-08

0.0000001

0.000001

0 250 500 750 1,000 1,250 1,500Distance from Origin (miles)0.2

0.4

Ann

ual R

isk (P

Optimal Solutionfor $30 Million

0.00 30 60 90 120 150

Investment Level(million $)


Integrated optimization model to manage the risk of transporting hazardous materials on railroad networks

Capacity

Accident Rate Maintenance N

Optimal Set of DecisionsRoute &Infrastructure

Track Class

Tank CarConditional

Probability of Release

Cost

Transportation Cost

Netw

ork Assignm

Speed Reduction

Product Hazard Consequence

Release Cost

Risk Cost Shipment Routes

ment M

odel

Container Design

Demand

Routes

Lai, Y.C., Kawprasert, A, Lin, C.Y., Saat, M.R., Liang, C.H. and C.P.L. Barkan (2011). Integrated Optimization Model to Manage the Risk of Transporting Hazardous Materials on Railroad Networks. Transportation Research Record, in-press.


Example integrated optimization model

Lai, Y.C., Kawprasert, A, Lin, C.Y., Saat, M.R., Liang, C.H. and C.P.L. Barkan (2011). Integrated Optimization Model to Manage the Risk of Transporting Hazardous Materials on Railroad Networks. Transportation Research Record, in-press.


Railway Safety and Capacity Researchy y p y

1. A Multivariate Analysis of Railroad Toxic-Inhalation-Hazard (TIH) Transportation Release Rate (Xiang Liu)p ( g )

2. Effects of Highway-Rail Grade Crossings on Hazardous Materials Release Rates (Samantha Chadwick)

3 Measuring the Capacity Impact of Higher Speed Passenger Trains3. Measuring the Capacity Impact of Higher Speed Passenger Trains (Samuel Sogin)


Rail transportation safety and risk analysis ti d h llquestions and challenges

• Development of quantitative causal relationships between various accident prevention options, safety performance and cost

• Optimized integration of different risk reduction strategies– How to decide among different strategies, within and between major areas:

infrastructure, operations, routing, package & shipper operating practices– How to account for interactive effects, e.g. reducing accident rate reduces

the benefit of improving the package, and vice versa• Use of risk profile or F/N curves versus single-point estimates of risk in p g p

decision-making– How to select among risk management decisions regarding prevention of

incidents of differing frequency and magnitude– Hazardous materials risk reduction measures generally affect probability

rather than severity• Evaluation of emerging safety issues and risk with shared freight and

( )passenger rail corridors (www.sharedcorridors.org)


Any questions?y q

Christopher P.L. Barkan, Ph.D.M. Rapik Saat, Ph.D. p ,Professor

Director - Rail Transportation & Engineering CenterDepartment of Civil and Environmental Engineering

University of Illinois at Urbana-Champaign1245 Newmark Civil Engineering Laboratory, MC-250

p ,Research Assistant Professor

Rail Transportation & Engineering CenterDepartment of Civil and Environmental Engineering

University of Illinois at Urbana-Champaign1243 Newmark Civil Engineering Laboratory, MC-250

205 North Mathews AvenueUrbana, Illinois 61801

Tel: (217) 244-6338Email: [email protected]

Website: http://ict illinois edu/railroad

205 North Mathews AvenueUrbana, Illinois 61801

Tel: (217) 333-6974Email: [email protected]

Website: http://ict illinois edu/railroad Website: http://ict.illinois.edu/railroadWebsite: http://ict.illinois.edu/railroad

Thank you!Thank you!

Optimizing Railroad Transportation Safety Improvement Strategies

Documents

Transcript of Optimizing Railroad Transportation Safety Improvement Strategies