Modeling of countermeasures for large-scale disasters using High-level Petri Nets

KIT – University of the State of Baden-Württemberg and
National Laboratory of the Helmholtz Association
Helmholtz Centre Potsdam
GFZ German Research Centre for Geosciences
CENTER FOR DISASTER MANAGEMENT AND RISK REDUCTION TECHNOLOGY
Modeling of countermeasures for large-scale disasters using
High-level Petri Nets
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Research context
Modeling requirements
Petri Nets
Modeling of countermeasures
Application of the model
Possible modeling extensions
Summary & future prospects
Outline
Stella Moehrle, Institute for Nuclear and Energy Technologies, KIT
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Context of research I
How can disaster management be supported by IT to handle events
for which no underlying models exist to anticipate all possible event
developments and therefore no pre-defined management
strategies are prepared?
Objectives
Use knowledge of previous disasters.
Address different kinds of disasters.
Recommend countermeasures in a coherent manner.
Account for uncertain incoming information.
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Context of research II
Case-based reasoning
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Retrieve
Similar Cases
Reuse
Revise
Confirmed solution
Learned case
New Case
Retain
Generic case base
Event description
Sequence of
countermeasures
Petri Nets
Merging Petri Nets
The CBR cycle illustrated is based on Aamodt, A. and Plaza, E. (1994) Case-Based Reasoning: Foundational Issues,
Methodological Variations, and System Approaches, AI Communications 7,1, 39-59.

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Consideration of the sequence of countermeasures
implemented
Applicability to different kinds of events
Description of model components in a general manner
Representation in a graphical manner
Integration of factors influencing the decisions on
countermeasures
Easy extensibility
Modeling requirements
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A Petri Net is a triple N=(P,T,F) where
P and T are non-empty finite sets of places and transitions
P ∩ T = ∅
F⊆ (P  T) ∪ (T  P) is a binary relation over P ∪ T.
Petri Nets I
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Can be used for modeling and analysis, simulation and
good graphical representation
Allow for modeling of sequential, parallel, alternative, and
iterative actions
Applied successfully in various fields such as emergency
and disaster management and accident modeling
Petri Nets II
Advantages
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Different types of nets: Low- and High-level Nets
Low-level Nets: tokens are indistinguishable
High-level Nets: tokens are distinguishable, each place, transition
and arc is defined with respect to different token types
Modeling countermeasures, sub-events, influencing
factors, endangered objects... leads to increasing
complexity
High-level Petri Nets allow for a more compact description
Petri Nets III
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Characteristics
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Decisions on countermeasures depend on (sub-)events
and the resulting endangered objects
Two types of transitions, (sub-)events and
countermeasures
Events create engangerment and endangered objects
Countermeasures reduce endangerment
Tokens contain information about the endangered object
and the degree of endangerment
Predefined range of transition labels and endangered
objects

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Example
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x=chemical
park
y=1
x=chemical
park
y=0.7
overflow of dike
dike protection flooding
A×[0,1]
a1
p0 p3
p1
p2
x=city
y=1
evacuationa1|y=1, a2|y=1
a1≠ a2
a2
A×[0,1]a1|y=0.7 a1
A = {chemical park, city}
a1, a2 = (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
Endangered object and degree
of endangerment

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Approach is used to model solutions of cases in the CBR
system. How to reuse the nets?
Idea: merge nets
Aim: identify new sequences of countermeasures without
losing orginal firing sequences
Possible: influencing factors on the decision are known
Merging of two nets is based on a common event
generating the endangerment and at least one common
countermeasure
Additional runs after merging depend on endangerment
generated and the effect of the countermeasures on the
endangerment
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Scenario: nuclear reactor accident in summer with an
atmospheric release of 137Cs and a wet deposition due to
rain. The release is over and the contaminated plume has
passed. The population has not been evacuated. The area
surrounding the incident has been contaminated.
Three cases are retrieved. Characteristics of solutions
differ:
Scenario 1: Soil/grass areas are surfaces that contribute most to
external dose. In particular, the focus is on playgrounds.
Scenario 2: The focus is on a strategy to decontaminate city
gardens.
Scenario 3: The area contaminated are mostly inhabited by elderly
who refuse to leave the area. There is need to protect the people
and clean the area (in particular city gardens).
Example I
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www.cedim.deStella Moehrle, Institute for Nuclear and Energy Technologies, KIT
ISCRAM 2013
x=sensitive
area
y=1A×[0,1]
a1
start p1
x= people
y=1
relocationa2
end
A = {sensitive area, people}
a1, a2 = (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
x= city
garden
y=1
topsoil removal
rotovating
A×[0,1]
a1
p1‘
A = {city garden, people}
a1, a2 = (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
a1|y=1, a2|y=1
a1≠ a2
endstart
x= people
y=1
a2a1|y=1, a2|y=1
a1≠ a2
relocation
Example II
Scenario 1
Scenario 2
atmospheric
release
atmospheric
release

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x= city
garden
y=1
A×[0,1]
a2
P1‘‘
x= people
y=1
relocation
a1
endstart
rotovating
A = {city garden, people, sensitive area}
a1, a2 ,a3 = (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
a1|y=1, a2|y=1 ∨ a1|y=1, a3|y=1
a1 = people, a2 ≠ a3
x= sensitive
area
y=1
topsoil removal
x= city
garden
y=1A×[0,1]
a1
P1‘‘‘
x=elderly
y=1
shelteringa2
a1|y=1, a2|y=1
a1≠ a2
end
start
A = {city garden, elderly}
a1, a2 = (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
rotovating
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a3
Example III
Scenario 1 + 2
Scenario 3
atmospheric
release
atmospheric
release

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x= city
garden
y=1
A×[0,1]
a2
P1*
x= people
y=1
relocation
a1
endstart
rotovating
A = {city garden, people, sensitive area, elderly}
a1, a2 ,a3, a4= (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
a1|y=1, a2|y=1 ∨
a1|y=1, a3|y=1 ∨
a3|y=1, a4|y=1
a1 = people
a2 = sensitive area
a3 = city garden
a4 = elderly
x= sensitive
area
y=1
topsoil removal
x= elderly
y=1
sheltering
a3
a4
Example IV
Scenario 1+2+3
atmospheric
release
city garden, people, sensitive area
Net has to be adapted to
the current situation by
comparing possible
endangered objects.

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x= city
garden
y=1
A×[0,1]
a2
P1*
x= people
y=1
relocation
a1
endstart
rotovating
A = {city garden,people, sensitive area , elderly}
a1, a2 ,a3, a4= (x,y): A × [0,1]
M0(p0) =
M0(p1) = M0(p2) = M0(p3) = ∅
a1|y=1, a2|y=1 ∨
a1|y=1, a3|y=1 ∨
a3|y=1, a4|y=1
a1 = people
a2 = sensitive area
a3 = city garden
a4 = elderly
x= sensitive
area
y=1
topsoil removal
x= elderly
y=1
sheltering
a3
a4
Possible modeling extensions
atmospheric
release
Additional types
Additional
characteristics
Refinement of
degree of
endangerment
Time and probabilities
Allow countermeasure
transitions to cause
endangerment
Modeling of 'forbidden‘
transitions

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Case-based recommendation of sequences of
countermeasures by reusing the most similar cases and
their solutions from the past
Sequences are modeled by High-level Petri Nets
Factors influencing the decisions are integrated
Generic and can be extended
Reuse past solutions by merging the nets
Preserve orginal sequences of countermeasures
Propose new combinations of countermeasures
Future work: analyze feasability of countermeasures, the
composition of basic patterns, different abstractation levels
and characteristics after merging, evaluation of strategies
Summary & future prospects
ISCRAM 2013

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Thank you for your kind attention!
ISCRAM 2013

Modeling of countermeasures for large-scale disasters using High-level Petri Nets

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Modeling of countermeasures for large-scale disasters using High-level Petri Nets