Risk Assessment of Hazardous
Materials Transportation Routes
Ashrafur Rahman
PhD Candidate
Nicholas E. Lownes, Ph.D., P.E.
Associate Professor
Department of Civil and Environmental Engineering
University of Connecticut
WTS-ITE Mini Series 2013
Introduction
2
An incident involving a vehicle carrying hazardous materials (Hazmat) cargo can
produce undesirable short and long term consequences to human health and the
environment, including severe illness, death, irreversible pollution, and in the worst case
may require evacuation.
1
Hazmat Risk
Health
Safety
Property
(1PHMSA 2008)
Hazmat Incident
3

Hazmat incident is a ‘Low Probability High Consequence’ event
East Lyme, CT

Plainfield, CT
Hazmat Incident Maps http://hazmat.globalincidentmap.com/map.php
Hazmat Shipment
4
1,400,000
1,200,000
1,202,825
Tons (thousands)
1,159,514
1,000,000
800,000
661,390
600,000
628,905
400,000
200,000
109,369 129,743
228,197
149,794
0
TRUCK
RAIL
WATER
Mode
PIPELINE
2002
2007
Objectives
5
1. To formulate an improved measure of link risk
2. To Formulate and solve a hazardous materials flow
model in robust and stochastic framework
3. To obtain a prohibition strategy support system by
Network Vulnerability Analysis
Risk Assessment
6
= Risk on link (i,j)
= Accident / Release Probability
Traditional Risk measure:
= Consequence / Population
Risk Assessment Approach
Identification of an
appropriate spatial threshold
for the risk associated with a
hazmat release
Accommodating
spatial variability in
risk measurement
Selecting
appropriate
measure of risk
Spatial Threshold of Risk
7
TABLE Impact Area by Hazmat Class2
Census blocks
Explosives
Flammable Gas
Poison Gas
Impact Area
(mile)
1.0
0.5
5.0
Farmable/Combustible Liquid
0.5
Hazmat Class
Impact area
i
Link
FIGURE Circular impact area of a vehicle and the resulting
fixed bandwidth impact area around a link. 1
=0.5 mile to 5 miles
Flammable Solid;
Spontaneously Combustible;
Dangerous when wet
Oxidizer/Organic Peroxide
Poisonous, not gas
Corrosive Material
0.5
0.5
5.0
0.5
(1Batta and Chiu 1988)
(2US DOT 1996)
Spatial Variability of Risk
8
% Risk Exposure
Decay Functions
100
90
80
70
60
50
40
30
20
10
0
Where
= distance of block centroid b to link
= selected impact area (buffer) size
0
0.1
No decay
0.2
0.3
0.4
0.5
0.6
Distance
Linear
Exp (dis)
Circular
0.7
Risk Measure
9
Link Risk :
Where,
= release accident rate on the link
= travel time on the link (min)
= length of each link (mile)
= census blocks inside the impact area
= decay value of each block, b
= population in block,
Census blocks
Impact area
Link
i
Application of the Risk Measure
10
Risk assessment for hazardous materials transportation routes
Current Route
Proposed Route
Bi-Objective Hazmat Flow Model
11
Data
Travel time,
Decision Variable
Hazmat flow on arc
Bi-Objective Model
and Risk,
(or
)
for each O-D pair:
P1
Regulator
P2
Carrier
s.t.
Preliminary Research: Static Bi-Objective
Routing Problem
12
O,D: 2,18
8
3
4
6
7
35
11
9
13 23
10 31
9
25
33
12
36
15
5
26
32
34 40
6
12
16
21
48
10
29
51 49
30
14
42 71
44
72
23
13
74
39
24
46 67
69 65 68
75
21
58
61
63
62
14
12
10
A1
A2
8
18 54
B2
10
B3
B4
6
600
B5
200
300
400
500
Shortest Path Cost (min)
O,D: 3,18
16
56 60
16
14
12
C1
10
C2
C3
C4
D1
14
12
10
8
D2
D3
D4
C5
6
600
O,D: 3,22
20
FIGURE Sioux-Falls Network.
12
8
200
300
400
500
Shortest Path Cost (min)
Destination
8
64
14
A3
6
18
52
Destination
59
7
50
19
45
22
66
55
57
15
70
73 76
16
20
17
28 43
41
38
17
22 47
53
37
19
8
24
27
11
14
Maximum Link Risk
Origin
4
B1
16
Maximum Link Risk
Origin
1
5
2
16
Maximum Link Risk
2
Maximum Link Risk
3
1
O,D: 2,22
200
300
400
500
Shortest Path Cost (min)
600
D5
D6
6
200
300 400
500
Shortest Path Cost (min)
600
FIGURE Pareto-Efficient Routes.
Ongoing Reseach: Stochastic, Time-Varying
Bi-Objective Hazmat Flow Problem
13

1Motivation
:
Multi-criteria: multiple stakeholders
Hazmat
Transportation
Time Varying: network attributes
Uncertainty: network attributes are unknown
(1Chang, Nozick, and Turnquist 2005)
Thanks !
14
Question?
[email protected]
Reference
15

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
Boyles, Stephen D, and S Travis Waller. 2010. A mean-variance model for the minimum cost flow problem with stochastic arc costs. Networks. Wiley Online Library.
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Carotenuto, Pasquale, Stefano Giordani, and Salvatore Ricciardelli. 2007. Finding minimum and equitable risk routes for hazmat shipments. Computers \& Operations
Research. Elsevier.
Chang, Tsung-Sheng, Linda K Nozick, and Mark A Turnquist. 2005. Multiobjective path finding in stochastic dynamic networks, with application to routing hazardous
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