Global 2013 Presentation

7/27/2019 Global 2013 Presentation

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APPROACH TO PROLIFERATION RISK ASSESSMENT

BASED ON MULTIPLE OBJECTIVE ANALYSIS FRAMEWORK

SOLUTION OF RESOURCE ALLOCATION PROBLEM FOR IDENTIFICATION OF

COST-EFFECTIVE MEASURES TO REDUCE NUCLEAR PROLIFERATION RISKS

Andrianov A., Kuptsov I.

Obninsk Institute for Nuclear Power Engineering of NRNU MEPhI

GLOBAL 2013: International Nuclear Fuel Cycle Conference, September 30 October 3, 2013

ADVANCED TOOLS DEVELOPMENT AND APPLICATION FOR

PROLIFERATION RISK AND RESISTANCE STUDIES IN INPE


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CONTENTS

Introduction

1. Framework for proliferation risk and resistance assessment studies

2. Current status and trends in quantitative proliferation risk assessment

3. MCDM methods for proliferation risk and resistance assessment

studies4. Evaluating the attractiveness of HEU production scenarios at a

clandestine enrichment facility using centrifuge enrichment technology

5. Solution of resource allocation problem for identification of cost-

effective measures to reduce nuclear proliferation risks6. Additional examples of tools application

Conclusion


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INTRODUCTION

At the present time it is deeply recognized that there is no absolutely proliferation-free

technical, institutional solutions and measures from all possible nuclear and

radiological threats. The possible additional measures to increase proliferation resistancetowards one of the potential threats will all accompany reducing the proliferation resistance

to other threats. This leads to the fact that in each case it is necessary to take into account

the specific features of the nuclear infrastructure, possible proliferator scenario

(motivations, intentions, capabilities) and an appropriate decision should be based on a

reasonable compromise. There is a growing understanding that the problem of proliferation risk and resistance

assessment and optimizing resources allocations is multi-criteria. The criteria

characterizing different aspects of proliferation scenarios are conflicting by nature. This

means that improving the value of one criterion leads to a decrease in the values of other

criteria. The development and application of state-of-the art multiple criteria decision making

(MCDM) for the proliferation risk and resistance assessments and optimization of resource

allocations in multi-objective formulation is urgently necessary. Based on this techniques

decision support tools intend to highlight conflicts and find compromises in the decision

making process related to the proliferation risk and resistance assessments.


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FRAMEWORK FOR PROLIFERATION RISK ANDRESISTANCE ASSESSMENT STUDIES


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PROLIFERATION RISK AND RESISTANCE

ASSESSMENT STUDIES IN INPE & NNRU MEPHI

APPLICATIONS:

Materials, facility, NFC, nuclear

power system levels

Local, national, region, globallevels

SOFTWARE DEVELOPMENT:

DeTRAS

RANSE Risk Assessment-VM Nuclear Fuel Cycle Calculators

Simple MCDM toolbox

Uncertainty Calculator

METHODOLOGY DEVELOPMENT:

Taxonomy of proliferation resistance and risk

assessments Approaches based on multi-objective

analysis framework

Probability risk analysis approaches

Integrated approaches (jointing scenarios

based and multi-attributive based)

Materials flows analysis for PR studies

Optimization of resource allocation

EDUCATIONAL RESOURCES:

Textbooks

Monographs

Training materials Lecture courses


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The main

assessment

framework

standpoints:

multicriteriality,

uncertainty,

dynamics &evolution

Proliferation aspects

should be consideredtaking account others

problem areas:

resources,

economics, waste

management

THE MAIN POINTS IN THE ASSESSMENTS

MULTICRITERIALITY

UNCERTAINTYDYNAMICS &EVOLUTION

Different levels for considerations and

assessments:

materials level, the facility level, the

NFC level, the nuclear power level.

PROLIFERATION

RISK AND

RESISTANCE

ASSESSMENT


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BASIC TOOLS FOR RISK ASSESSMENT

SIMPLE MCDA TOOLBOX

Technology

To perform calculation based on the proposed concept

systematic implementation of MCDM and uncertainty analysis

techniques the specialized software was developed

UNCERTANTY CALCULATOR

DIALOG SYSTEM OF STOCHASTIC

MULTIOBJECTIVE OPTIMIZATION

INTERACTIVE SYSTEM FOR VISUAL

ANALYSIS OF FEASIBLE SET

BORDERS


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CURRENT STATUS AND TRENDS IN QUANTITATIVEPROLIFERATION RISK ASSESSMENT


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CURRENT STATUS AND TRENDS IN QUANTITATIVE

PROLIFERATION RISK ASSESSMENT

Current status

no concept of proliferation risk and methodology for its assessment, in the general

case decision-making procedure is not formalized

variety of attributive and scenario approaches for proliferation risk assessment

most of models are oriented on the analysis of situations where the proliferator is

a State

Some trends

accounting multiple proliferator goals, the dynamics of event development and

uncertainty of initial data

consideration of situations where proliferator is non-State actors development of proliferation act models to identify the relationship between model

parameters and risk indicators

increasing practical use (recommendations for improving nuclear security

measures, cost optimization, etc.)


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Scenario based

approaches

Probabilistic risk analysis (M.Golay , G. Rochau , J. Hill, D.

Sentell and others)

Markovian Method (R. Bari , A.

Rumyantsev and others)

Graph-analytical and

probabilistic methods(vulnerability assessment

software - ASSESS, EASI,

SAVI, VEGA, SAPE)

Attributive based

approaches

MAUA (I. Papazoglou ,

C. Heising, P. Silvennoinen,

S. Ahmed, R. Krakowski,W. Charlton, and others)

Barriers to proliferation

(Proliferation Vulnerability Red

Team, TOPS, PRPP GIF

working group, SAPRA)

Evaluation of the materialsfrom the disposition of excess

weapons materials

Cost estimates (inspection

cost estimate, overcoming

barriers cost estimates)

Game theory based

approaches

Study of the nuclear

deterrence mechanism

Identification of the most

effective inspection strategy

Identification of the adversaryinterception strategies

PROLIFERATION RISK AND RESISTANCE

ASSESSMENT APPROACHES


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COMPARATIVE ANALYSIS OF SCENARIO- AND

ATTRIBUTIVE-BASED APPROACHES

Probabilistic risk analysis Multi-attributive approaches

Main concept Probability of event Utility function

Authors G. Rochau, A.Rumyantsev, M.Bunn, and

others

V.Charlton, P.Silvennoinen, R.Krakovski,

R.Brogli, and others

Advantage Ability to construct a chain of events and

accounting different system level factors

Accounting the relationship with

technological featuresDisadvantage Low sensitivity to technological

attributes

Need to assess and aggregate different

characteristics of a system in a common

set of units

No single model or approach is sufficient to cover the entire landscape of adversary scenarios andsupport the decisions to be made by decision makers.

Development of integrated approach based on the combination of PRA and multi-attributive models is

important and it may be done based on multiple-objective analysis framework.

Such integrated approach allows to overcome the limitations of PRA and multi-attributive models, thus

extend the range of their application.


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MCDM METHODS FOR PROLIFERATION RISK ANDRESISTANCE ASSESSMENT STUDIES


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MODM: base methods

Combinatorial optimization

problems JMetal GA framework

NSGA-II, MOCHC algorithms

Fuzzy hybrid algorithm FMOCHC

Neural Net joined with GA

optimization

etc

THE MAIN COMPONENTS OF MCDM TECHNIQUES

MCDA: base methods

MAVT (aggregation)

AHP (pairwise comparison) TOPSIS (distance to ideal point)

PROMETHEE (pairwise comparison based on

preference functions)

MAUT (uncertain criterion values)

Fuzzy MAVT (MAVT joined with fuzzy theory)

ProMAA (distributed criterion values and weights) etc

Multiple criteria decision making (MCDM) techniques are a tool aimed at

supporting decision makers faced with making numerous and conflicting

assessments. MCDM techniques intend to highlight conflicts and find compromises in

the decision making process. Multi-Criteria Decision Analysis (MCDA) and Multi-Objective Decision Making (MODM) are the main components of MCDM.

A large number of MCDA techniques have been developed to deal with different

kinds of problems (MAVT, AHP, TOPSIS, PROMETHEE, etc.). At the same time each

technique has pros and cons and can be more or less useful depending on the

situation.

The methods of MODM for multi-objective optimization problem solving are various: a priori methods; a

posteriori methods; adaptive methods; methods based on the preliminary construction of the Pareto set

approximation.


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MULTIPLE CRITERIA DECISION MAKING (MCDM)

Criteria identification

Problem formulation, goals, formalization

Formation of alternatives

Criteria assessment

Summary tables

DM/Exp/St-H preferences

Weighting Scoring

Aggregation

Uncertainty analysis

Final Recommendations

E

E

Experts, Stakeholders,

Decision Support Tools

(DST)

Experts,

Stakeholders,

KBModels, Expert-

Stakeholders judgments

DST

Expert Judgments,

DST

DST, Expert Judgments

Decision Maker, Experts,

Stakeholders

DST, Models

Experts-Stakeholders for

Decision Maker

BASIS FOR PROPOSED APPROACH


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BASIS FOR PROPOSED APPROACH

In contrast to approaches to the selection of optimal solution based on one of a criteria set

(or a convolution of a number of them) in the proposed approach the methods are

implemented of the vector formulation of a problem based on the principle of compromise,

which provides for an acceptable set of values of all factors.

At the same time this approach offers no unique solution, but only the region of

reasonable (rational, compromise) solutions. Finding out a unique solution remains the

prerogative of an expert.

This approach is the foundation of most state-of-the-art methods of multiple criteria

decision-making theory, where the basic concept is the notion of a set of nondominated

(efficient, Pareto, Pareto-optimal) solutions - the Pareto set.

Informally, the Pareto set is defined as a set

where the value of any particular criteriacan be improved only at the expense of

another criteria. Thus, any solution from the

Pareto set can not be optimized

simultaneously on all individual criteria.


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EXAMPLE OF RISK INDICATORS

Risk indicators Proliferator goals Counteraction goals

Proliferation time (PT) minimize maximizeProliferation cost (PC) minimize maximize

Proliferation technical difficulty (PTD) minimize maximize

Material type quality (MTQ) maximize minimize

Detection probability (DP) minimize maximizeCounteraction resource (CR) maximize minimize

A set of risk indicators have to be defined by experts

taking into account their potential application fordifferent elements of nuclear infrastructure.

Specific form of risk indicator may be defined based

on multi-attributive analysis or proliferation act model


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The described method of analysis has the following features: account of the relationship between variables and the influence of this dependence on the value of integrated indicators;

construction of various realizations of the proliferation act;

meaningfulness of the process of scenario development and modeling that allows an expert to get an idea of proliferation act and the

possibilities of its implementation, identify critical elements, as well as possible barriers.

The disadvantages of the approach are:

the need to construct a model of proliferation act and identify relationships between variables;

the need for significant qualitative study of the model (to create multiple models corresponding to each scenario, selection and

analysis; uncertainty boundaries of scenarios);

limited number of possible combinations of variables (the number of scenarios to be considered in detail and the number of variables

GENERAL DESCRIPTION OF APPROACH


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EVALUATING THE ATTRACTIVENESS OF HEUPRODUCTION SCENARIOS AT A CLANDESTINE

ENRICHMENT FACILITY USING CENTRIFUGE

ENRICHMENT TECHNOLOGY

PROBLEM STATEMENT


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PROBLEM STATEMENT

To evaluate the attractiveness of different scenarios of HEU clandestine

production in quantities of 1 SQ using centrifuge enrichment technology taking

into account that proliferator has already a cascade of enrichment and it ispossible to add new centrifuges to this cascade on daily basis.

.

ACCOUNTING OF PROLIFERATORS INTENTIONS


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ACCOUNTING OF PROLIFERATORS INTENTIONS

min max

min max

min max

...

i

i

i

PT PT PT

PC PC PC

CR CR CR

1

min( ) min( ) min( ) max( ) min( ) min( )

PT PC PTD MTQ DP CRk k k k k k

i i i i i i

i

PT PC PTD MTQ DP CRR

PT PC PTD MTQ DP CR

"Aggressive" strategy - proliferator seeks to achieve his goals in the shortest possible time without stinton resources.

"Hidden" strategy - proliferator seeks the lowest cost to achieve his goal by making his actions the most

inconspicuous.

"Moderate" strategy - proliferator seeks to moderate risk of detection, cost and reasonable time to achieve

his goal.

Ways of defining a set of scenarios, taking into account probable proliferators

strategy:1) Formation of criterion restriction

2) Construction of aggregate indicator

RISK INDICATORS AND INFRASTRUCTURAL


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RISK INDICATORS AND INFRASTRUCTURAL

RESTRICTION FOR HEU PRODUCTION SCENARIOS

0( , , , , , )c c c

heu te in d PT PT x x x N C N

.

0( , , )c c

dPC PC N N PT

( )

c

PTD PTD C

( )heuFMT FMT x

RISK INDICATORS

INFRASTRUCTURAL RESTRICTIONS

0)x(f

...

0)x(f

0)x(f

N

2

1

Amounts and type of available source materials

Type of centrifuge and their total number

etc.

- time needed to produce 1 SQ of HEU

- total number of centrifuge involved in the program

- centrifuge capacity

- HEU enrichment

TRADEOFFS BETWEEN RISK INDICATORS FOR


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TRADEOFFS BETWEEN RISK INDICATORS FOR

ACQUISITION OF LEU FOR HEU PRODUCTION

IMPACT OF PROLIFERATOR CAPABILITIES ON


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IMPACT OF PROLIFERATOR CAPABILITIES ONPT AND PC RISK INDICATORS


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INTERACTIVE DECISION MAP VISUALIZING


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INTERACTIVE DECISION MAP VISUALIZING

FEASIBLE PROLIFERATION SCENARIO SET

The calculations are made on the assumption that the goal is to produce 1 SQ of HEU with 90%

enrichment. The non-colored area is principally not achievable for proliferator. Ultimately, scenarios from

marginal feasible proliferation scenarios may be ranked with accounting technological capabilities and

proliferator strategy. This procedure may be realized based on formulated a posteriori aggregated risk

indicator risk function or by a set of criteria constrains unique for each proliferator groups andcircumstances.

CATEGORIZING SCENARIOS WITH ACCOUNTING


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CATEGORIZING SCENARIOS WITH ACCOUNTING

PROLIFERATORS STRATEGY

Initial number of

centrifuge, centr.

Number of daily

running centrifuge,

centr./day

Centrifuge capacity,

kgSWU/yr

Feed

enrichment, %

Tails assay,

%

HEU

enrichment,

%

766 964 7 5,9 3,9 0,6 90

648 6 0 1,7 1,6 0,6 90

44 46 0 1,1 1,0 0,390

404 11 2 1,6 1,8 0,6 90

587 14 1 1,4 1,2 0,5 90

Proliferation time (PT),

day

Proliferation cost

(PC), centr.

Proliferation technical

difficulty (PTD),

kgSWU/yr

Fissile material

type (FMT), %

Proliferator

strategy

766 0,2 966,2 5,9 90 Aggressive

648 182,5 9,3 1,7 90 Hidden

44 71,7 58,0 1,1 90

Moderate404 32,0 72,3 1,6 90

587 55,8 62,8 1,4 90

RISK INDICATORS VALUES

ADVERSARY PARAMETERS

SUMMARY OF EVALUATING THE ATTRACTIVENESS


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SUMMARY OF EVALUATING THE ATTRACTIVENESS

OF HEU PRODUCTION SCENARIOS The results of evaluation of different types of attractiveness of initial nuclear

materials, as starting points for developing nuclear weapons, quantitatively confirm

the question posed in a number of studies, thesis that existed for a long time and thewidespread opinion of a greater risk associated with the HEU and plutonium: the risk

of LEU proliferation is considerably higher than in the case with other types of

nuclear materials, mainly due to its availability and low detectability of use as

compared with other materials.

It should be noted that the risk of NED creation from HEU, if HEU and LEU equally

available to the proliferator, will be much higher. However, in assessing risks

consideration must be also given to possible ways of acquisition of nuclear materials

and further handling. As a result of implementation of some measures focused on

direct use materials, the risk associated with LEU is increased, which is todayconsiderably higher than in the case of HEU, despite the technical difficulties

associated with the need to further enrichment of LEU. This requires the introduction

of stronger measures at sites with LEU realization to ensure physical protection, the

quantitative characteristics of which can be identified through calculations and

experts activities with risk assessment models.


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SOLUTION OF RESOURCE ALLOCATION PROBLEMFOR IDENTIFICATION OF COST-EFFECTIVE

MEASURES TO REDUCE NUCLEAR

PROLIFERATION RISKS


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SOFTWARE RANSE RISK ASSESSMENT VM


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The developed software package (Dr. A. Rumyantsev, NRC KI) based on extended

scenario model realizing the controlled finite Markov chain approach, is a flexible

environment that enables experts to specify with any degree of detail the sequence of

threat and counteraction events leading to the resulting event.

The software is actually a constructor like Lego that allows from the individual elements

to construct a detailed chain of events taking into account time factor, uncertainty and

capability for multifactor processing of scenarios indicators.

SCENARIOS

RESULTING EVENT

CHARACTERISTICS

THREAT

CHARACTERISTICS

COUNTERACTION

CHARACTERISTICS

risk

(c.u.)

rate risk

(c.u./ year)

duration event

(days)

event

probability (%)

threat cost

(c.u.)

threat probability

(%)

counteraction

costs (c.u.)

counteraction

probability (%)

NED creation * * * * * * * *

RDD, RED creation * * * * * * * *

sabotage * * * * * * * *

SOFTWARE RANSE_RISK_ASSESSMENT-VM

Here and below are presented the calculation results for adversary scenarios for hypothetical

nuclear infrastructure taken from a scenarios library realized in the software.

THE STRUCTURE OF RESULTS OF RISK ASSESSMENTS OF ADVERSARY SCENARIOS FORHYPOTHETICAL NUCLEAR INFRASTRUCTURE

RESOURCES ALLOCATION PROBLEM TO IMPROVE


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Resources allocation problem to improve the effectiveness of counteraction system involves the following

optimization problem:HOW TO ALLOCATE THE LIMITED RESOURCES SO THAT THE EFFECT MEASURED BY THE PROBABILITY OF

RESULTING EVENTS IS DECREASED AS MUCH AS POSSIBLE?

0 01

1N

t c

i i

i

p p p

01

1 ( )N

c t

i i

i

p p p c

1

Nt

i

i

c C

.

The formulated problem is nonlinear. As a multipurpose method for solving the problem stochastic

optimization methods can be proposed (random search, low-discrepancy sequences, and genetic

algorithms).

RESOURCES ALLOCATION PROBLEM TO IMPROVE

THE COUNTERACTION SYSTEM EFFECTIVENESS

limitation on the total amount of resources

probability of the resulting event before upgrading the

counteraction system

probability of the resulting event after upgrading the

counteraction system

( )c ti ip crelative increase in probability of counteraction event

from additional cost

THE RELATIVE INCREASE IN COUNTERACTION


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0.1 1 10 100 1 103

0

0.2

0.4

0.6

0.8

additional cost

specificcountermeasuresprob

abilityincrement

THE RELATIVE INCREASE IN COUNTERACTION

EVENT PROBABILITIES FROM RESOURCES

To solve the resources allocation problem to improve the effectiveness of counteraction system it is first

of all required by experts to assess the relationship between costs and probabilities of different

countermeasures. These relations in general case are nonlinear.

Functions varies from 0 to 1 and has a typical form shown in Fig. This type of function is determined by the

following fact:

zero investment will not increase the effectiveness of the counteraction system

infinite investment will reduce the probability of the resulting event to zero.

( )c ti i

p c

REDUCING RESULTING EVENT PROBABILITY AND


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Model problem for four different countermeasures shows that

ultra-large additional costs may not result in a corresponding

effect, and therefore further increasing additional costs beyonda certain level makes no sense.

Different volumes of resources are allocated differently

between countermeasures. It should be noted that unlimited

improving efficiency of one element of the counteraction

system without improving it in other elements may not have

the desired effect in the efficiency of the counteraction system

as a whole.

Level of Investment

Totalcost.Nationa

lcurrencyunits

REDUCING RESULTING EVENT PROBABILITY AND

DISTRIBUTION OF COSTS

Counter measures 1

Counter measures 2

Counter measures 3

Counter measures 4

SUMMARY ON SOLUTION OF RESOURCE


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SUMMARY ON SOLUTION OF RESOURCE

ALLOCATION PROBLEM

Proposed methodology of selection of cost-effective measures can be

applied for systematic design of cost-effective system to reduce nuclearproliferation risks associated with a national nuclear infrastructure. The

methodology enables the expert to select the cost-effective measures

depending on availability of resources.

The performed analysis with different number of possible measuresconfirm the conclusions that the implementation of extra-large costs may

not produce the required effect, and the increase in resources above a

certain level does not look sensible.

Diversification in improving the effectiveness of other measures seems

more rational and efficient for the whole system than the unlimited

improvement of the effectiveness of only one measure.


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ADDITIONAL EXAMPLES OF TOOLS APPLICATION performing NFC material flows analysis for

proliferation risk assessment studies

obtaining cost-effective measures of risk reduction

considering whole scenarios set for the entire nuclear

infrastructure

PROLIFERATION POTENTIAL OF


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PROLIFERATION POTENTIAL OF

GLOBAL NUCLEAR POWER SYSTEMS

DEVELOPING NUCLEAR POWER STRUCTURES


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DEVELOPING NUCLEAR POWER STRUCTURESConsidered nuclear power structures:

once-through uranium NFC with no restrictions on uranium resources (I);

closed U-Pu NFC with and without restrictions on the locations of FR and the limitations on the amount of

available natural uranium (II, III);

closed U-Pu-Th NFC with restrictions on the location of FR and the amount of available natural uranium

(IV).

PROLIFERATION RISK INDICATORS


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Indicators characterizing the proliferation potential of scenarios:

Potential productivity of fissile materials, SQ/year

Total amount of fissile materials in NFC - Amounts of direct- and indirect-use nuclear materials, SQ

Different structures of developing nuclear power systems are comparable by indicators "total

amount of fissile materials in NFC" and "potential productivity of fissionable materials".

The improvement of one indicator is achieved by worsening another. It is impossible to make

definitive judgments about the prospect of a nuclear power structure and the NFC type from thenon-proliferation viewpoint based on material flow assessment, without a detailed analysis of

the proliferation scenarios and specification of acting national and international systems of

nonproliferation regime management.

PROLIFERATION RISK INDICATORS

Scenarios Total amount of fissile materialsin NFC, 106SQ

Potential productivity offissionable materials, 106SQ/yr

I 4.1 6.2 33 362

II 2.2 4.3 455 664

III 3.0 5.1 302 370

IV 1.9 4.0 420 480

COST-EFFECTIVE PLUTONIUM MANAGEMENT


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COST-EFFECTIVE PLUTONIUM MANAGEMENT

STRATEGIES

0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.60.9

1.0

1.1

1.2

1.3

Pu multirecycling and forming of balance of

Pu production and consumption

Preventing the accumulation of separated Pu

Consumption of

different accumulated

Pu forms

Increasing nuclear proliferation risk importanceThe

relative

increase

int

otalc

osts

The relative increase of scale of nuclear proliferation risks

Relative attractiveness of

plutonium on different NFC stages

Cost-effective strategy for plutonium management and related technological options may be

obtained by means of trade-off strategies calculation on criteria minimizations of the total

discounted costs and the plutonium risk exposure. Trade-off curve identifies additional costrelated to implementation of measures for reduction proliferation risks associated with plutonium.

DETRAS - DECISION TREES RISK ASSESSMENT


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DETRAS - DECISION TREES RISK ASSESSMENT

SOFTWARE

Limitations. Omitting a key node may

render the tree useless, while adding a

few nodes to a decision tree can explode

the tree's size. It can also be difficult to

obtain or elicit probability estimates,

especially where human reliability isconcerned.

Advantages. The above trees can focus analysis upon

scenarios that have chosen outcomes and can provide a

graph that depicts a system. Other risk analysis

techniques (e.g., probabilistic risk analysis) also use

these trees.

Fig. Missile fire

DeTRAS 1.0 is the software for simple risk assessment based on decision trees

methodology. Expanded functionality of the software (graphics, reporting, uncertainty

evaluation, cost optimization) is available in the extended version of the software.The software was developed by the team of the Department of General and Special

Physics of Institute of Nuclear Power Engineering (Obninsk, Russia).

- Decision nodes - represented

by square

- Event nodes -

represented by circle- Final nodes - represented

by triangle

WHOLE THREAT SCENARIO SET


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WHOLE THREAT SCENARIO SETA variety of nuclear and radiological threats and the risks related to the possible adversary action

modifications requires simultaneous consideration of all possible scenarios for the whole nuclear

infrastructure.

A common way of quantifying the risks is to assign a numeric value to them by multiplying eventprobabilities and consequences together. However, a problem with this is that high-

probability/low-impact risks get the same score as high-impact/low-probability risks, about which

experts may well have very different view.

Probability and impact matrix is a well-known tool for assigning category risk from high to low

levels by comparing two parameters: event probabilities and consequences.

The areas of concept usage:

identify the most dangerous scenarios, or the

best way of organizing the counteraction system;

ranking, sorting and classification of thescenarios, which allows dividing scenarios on

predefined homogenous groups ("unacceptable",

"acceptable", "partially acceptable");

screening/filtering aimed at identifying a

smaller set of scenarios for further analysis.


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CONCLUSION

Assessment of proliferation scenarios based on multiple objective analysis framework

may be used as one of tools in the proliferation risk and resistance assessment toolbox.

This technique can be integrated into different approaches of risk assessment, thus

extending the field of their possible application. Using integrated approach meets state-

of-the-art requirements to the problem of assessing adversary scenarios allowing to

manage with the available methodological difficulties.

Lack of general methodologies for decision-making in multi-criteria formulation in the

area of proliferation risk and resistance assessments, complicates the procedure of

formulating a coordinated vision of a preferable technological and institutional solutions

and measures, balanced on different benefits and losses.

MCDM techniques application allow searching for compromises between the conflicting

factors that determine the proliferation risk and resistance and calculating corresponding

trade-off rates; carrying out multifactor analysis of alternatives and choosing, ranking,

sorting corresponding options.


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Thank you

for attention

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Global 2013 Presentation