Transcript Risk Model

Derailment Risk Model
Frequency analysis and scenario development
Gavin Astin
29 September 2011
Agenda
1. Background
2. Frequency
Assessment
3. Consequence /
Impact Assessment
4. Summary
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Risk Model Structure
Basic causes
Intermediate
causes
Hazard/
What -if
Fault Tree Analysis
Developing
consequences
Fully developed
consequences
Event Tree Analysis
Mitigation 2
Yes
Mitigation 1
Yes
Hazard
Outcome
1
No
2
Yes
3
No
4
No
Primary controls
Secondary controls
= Key risk reduction measures
 Traditional bow-tie approach.
 Hazard = derailment.
 Freight train risk reduction measures shown as controls in the bow-tie structure.
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Background to Risk Model Data
 Previous freight train derailment accident reports:
- 201 accident reports collected by DNV from various sources.
- The Agency provided access to accident summaries used for their previous work. After
elimination of duplicates, those which were not derailments etc. the usable Agency data was
355 accident summaries from a range of European countries.
- The total volume of information used was 556 accident reports / summaries.
 Undertook research to establish other freight train derailment causes, not
necessarily occurring in the accident data. (Although if not occurring in 500+
accidents then we can conclude that such causes are very low contributors.)
 These data populate frequency (“fault tree”) and scenario (event tree) models.
 Observations:
- Not many accident reports identify root causes. This makes analysis difficult. Hot axle box
may have caused a derailment, but what caused the HAB?
- Systematic analysis of accident data on an annual basis may identify national differences,
good practice and trends (not just limited to freight train derailment accidents).
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Agenda
1. Background
2. Frequency
Assessment
3. Consequence /
Impact Assessment
4. Summary
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Fault Tree Extract
Operational failures
leading directly to, or
which are the primary
cause of a freight train
derailment
Page 1
OPS_DRL
Freight train
composition failure
Improper loading of
wagons
Failure to perform
brake check /
inspection
Incorrect setting of
points/turnouts leading to, or
primary cause of derailment
(mainly yards with no
interlocking)
Mishandling of train
en-route
Items left under
train
Other operational
failures l
O_1_DRL
O_2_DRL
O_3_DRL
O_4_DRL
O_5_DRL
O_6_DRL
O_7_DRL
Page 4
Unfavourable train
composition formation
(empties before loaded
wagons)
Other train
composition failure
O_1A
O_1B
Speed not set
Brakes not properly Brakes not set with
according to brake checked or tested
respect to load or
performance
speed of brake
application
O_3A
O_3B
O_3C
Wrong setting in
relation to
movement
authority
Point moved whilst
occupied by train
Driver
overspeeding
Other mishandling
of train
0_4A
0_4B
O_5A
O_5B
Excessive speed
through turnout in
deviated position
Excessive speed
elsewhere
O_5A1
O_5A2
 This is part of a set of fault trees, although they were used to quantify the analysis.
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Alternative Frequency Analysis Approach
Cause 1 leads to
high or low speed
derailment?
% contribution cause 1
% contribution cause 1
Infrastructure
.
.
% contribution cause n
Cause n leads to
high or low speed
derailment?
Rolling Stock
Hazard: Freight Train Derailment
Operations
Calculation flow
 Annual number of significant derailments per year = 500 (from Eurostat and Agency data)
 A severe derailment is one which has the potential for loss of containment. A
significant derailment is one which has the potential to become severe.
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Some Statistics for Accidents with Single or Dominant
Cause
Accident Causes Breakdown
45%
41%
40%
35%
33%
30%
24%
25%
20%
15%
10%
5%
1%
0%
Infrastructure
Rolling stock
Operational failure
Others
(environment etc)
 About 75% of derailments have single or dominant cause:
- > 65% Inf derailments result from track geometry defects (track width dominant from single
causes, although when combinational causes included track twist becomes dominant).
- > 70% RS derailments result from wheel / wheel set failures (HAB dominant).
- ~ 25% Ops derailments result from loading errors (although dominant single cause is brake
checking errors including handbrake left on)
 Example: HAB = 75% * 41% * 38% = about 12% (60 in number) of all derailments.
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Some Statistics for Accidents with Several Causes
 Track geometry defects appear in about 50% of accidents where more than one
cause is present, with track twist the most significant appearing in about 30%.
 Wheel profile defects appear in about 20% of accidents where more than one cause
is present.
 Wagon wrongly loaded appears in about 10% of accidents where more than one
cause is present.
 Train mishandling appears in 10% of accidents where more than one cause is
present.
 Our assumption is that removal of a one of these causes will prevent the derailment.
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Derailment Frequency Assessment Results
Derail numbers.docx
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Agenda
1. Background
2. Frequency
Assessment
3. Consequence /
Impact Assessment
4. Summary
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Derailment Event Tree Considerations and Some Data
 Factors include:
- Derailment location.
- Immediate consequences:
- Severe (e.g. overturn, mechanical impact causes loss of containment)
- Not immediately severe:
- Is derailment detected?
- Is train brought to a safe stop?
 About 70% of low speed derailments occur in or around stations.
 About 25% of low speed derailments are immediately severe (potential for loss of
containment).
 About 30% of high speed derailments occur in or around stations.
 About 50% of high speed derailments are immediately severe.
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Partial Event Tree (preceding branches are speed & location)
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Derailment Outcomes (about 170 in total, but simplify to…)
Consequence Description
SD1
Severe derailment occurring immediately, contents spilling, fouling adjacent line and affecting passenger train
on adjacent line
SD2
Severe derailment occurring immediately, contents spilling, fouling adjacent line and affecting freight train on
adjacent line
SD3
Severe derailment occurring immediately, contents spilling, fouling adjacent line but no affect on adjacent line
SD4
Severe derailment occurring immediately, contents spilling but no affect on adjacent line
SD5
Severe derailment occurring immediately , fouling adjacent line and affecting passenger train on adjacent line
SD6
Severe derailment occurring immediately , fouling adjacent line and affecting freight train on adjacent line
SD7
Severe derailment occurring immediately , fouling adjacent line but no affect on adjacent line
SD8
Severe derailment occurring immediately but no contents spill or no affect on adjacent line
SD9
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), contents spilling, fouling adjacent line and affecting passenger train on adjacent line
SD10
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), contents spilling, fouling adjacent line and affecting freight train on adjacent line
SD11
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), contents spilling, fouling adjacent line but no affect on adjacent line
SD12
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), contents spilling, but no affect on adjacent line
SD13
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), no contents spilling, fouling adjacent line and affecting passenger train on adjacent line
SD14
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), no contents spilling, fouling adjacent line and affecting freight train on adjacent line
SD15
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected), no contents spilling, fouling adjacent line but no affect on adjacent line
SD16
Occurring some time after initial derailment (detected by driver/others but unable to apply safe
stop/undetected) but no contents spill or affect on adjacent line
NSD1
Number of non severe derailments per year. Must be without contents spill and no affect on adjacent line
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Derailment Event Tree Statistics
Imm Sev DG
19
3.7%
Non Immed Sev DG
11
2.2%
Immed Sev Normal
165
33.1%
Non Immed Sev Normal
93
18.6%
Detected and safe
204
40.7%
 Each outcome has an impact in terms of:
-
Potential loss of life.
Operational disruption.
Track damage.
Wagon damage.
Environmental events (contamination).
 We estimate:
-
About 4 fatalities per year (almost exclusively from DG incidents).
About 17,000 hours operational disruption per year.
About 720 km track damage per year.
About 2,400 damaged wagons per year.
About 65 contamination events per year.
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Detected not safe stop
8
1.7%
Agenda
1. Background
2. Frequency
Assessment
3. Consequence /
Impact Assessment
4. Summary
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Summing Up
 Risk model predicts impacts.
Basic causes
 Benefits of identified
measures are determined in
terms of avoided derailments /
reduced impacts.
Intermediate
causes
Hazard/
What -if
Fault Tree Analysis
Developing
consequences
Fully developed
consequences
Event Tree Analysis
Mitigation 2
Yes
Mitigation 1
Yes
Hazard
Outcome
1
No
2
Yes
3
No
4
No
 Potential costs of new
Primary controls
measures are defined by the Secondary controls
application scope, measure
cost and maintenance
parameters and effectiveness
of each measure
= Key risk reduction measures
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End of Session - Any Questions
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Safeguarding life, property
and the environment
www.dnv.com
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