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LLNL-PRES-XXXXXX This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC AIChE Annual Meeting 2013 November 7, 2013

(NuClean) Risk and Response Management

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Ed Jones of Lawrence Livermore National Laboratory (LLNL) presents on risk and response management both in general and with regards to nuclear waste. The NuClean Kick-Off workshop was held on Nov. 7, 2013 at the Handlery Union Square Hotel in San Francisco, CA, co-located with the AIChE 2013 Annual Meeting. For more information on NuClean, visit: http://www.aiche.org/cei/conferences/nuclean-workshop/2013. For more information on AIChE's Center for Energy Initiatives (CEI), visit: http://www.aiche.org/cei.

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Page 1: (NuClean) Risk and Response Management

LLNL-PRES-XXXXXX This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC

AIChE Annual Meeting 2013 November 7, 2013

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Lawrence Livermore National Laboratory LLNL-PRES-xxxxxx 2

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Lawrence Livermore National Laboratory LLNL-PRES-xxxxxx 3

Potential Events/Failures

Potential Consequences

Response Management

Security and Protection Emergency Response/ Consequence Management

Risk Reduction: Safety & Security

Reduce Threats &

Vulnerabilities

Mitigate/ Reduce

Consequences

Risk Analysis

Likelihood/Probability

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Lawrence Livermore National Laboratory LLNL-PRES-xxxxxx 4

Critical Asset

Threat

Consequence

Protection/Prevention

Mitigation/

Response

Integrated Approach

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Lawrence Livermore National Laboratory LLNL-PRES-xxxxxx 5

KEY ELEMENTS OF RISK MANAGEMENT Planning and Preparation Response and

Reconstruction Risk

Identification Mitigation Risk Transfer Preparedness Emergency

Response Rehabilitation

and Reconstruction

Hazard assessment (frequency, magnitude and location)

Physical/structural mitigation works

Insurance/ re-insurance of public infrastructure and private assets

Early warning systems. Communication systems

Humanitarian assistance

Rehabilitation/ reconstruction of damaged critical infrastructure

Vulnerability assessment (population and assets exposed)

Land-use planning and building codes

Financial market instruments (catastrophe bonds, weather-indexed hedge funds)

Contingency planning (utility companies/ public services)

Clean-up, temporary repairs and restoration services

Macroeconomic and budget management (stabilization, protection of social expenditures)

Risk assessment (a function of hazard and vulnerability)

Economic incentives for pro-mitigation behavior

Privatization of public services with safety regulation (energy, water, transportation, etc.)

Networks of emergency responders (local/national)

Damage assessment Revitalization for affected sectors (exports, tourism, agriculture, etc.)

Hazard monitoring and forecasting (GIS, mapping, and scenario building)

Education, training and awareness about risks and prevention

Calamity Funds (national or local level)

Shelter facilities Evacuation plans

Mobilization of recovery resources (public/ multilateral/ insurance)

Incorporation of disaster mitigation components in reconstruction activities

Building and Strengthening National Systems for Disaster Prevention and Response: These systems are an integrated, cross-sectoral network of institutions addressing all the above phases of risk reduction and disaster recovery. Activities that need support are policy and planning, reform of legal and regulatory framework coordination mechanisms, strengthening of participating institutions, national action plans for mitigation policies and institutional development.

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§  Multiple hazards!•  Natural disasters!•  Technological failures!•  Human malevolence!

§  Multiple assets/targets!•  Facilities!•  Extended infrastructures!•  Urban-scapes!

§  Multiple consequences!•  Safety and security!•  Economics!•  Societal integrity!

§  Risk management objectives!•  Save lives and property!•  Effective resource allocations!•  Strategies for protection and response!

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Unacceptable Risk

Minimum Risk

Potential Losses Operations Performance

Resources Options Technologies

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Lawrence Livermore National Laboratory LLNL-PRES-xxxxxx 8

C

Threats Resources Options Technologies

Consequences Losses Operations Performance

Barriers for Safety and Security

F

C

C

Develop protective concepts and management strategies

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§  Establish problem domain, major goals, and organizational space !

§  Take an inventory of existing capabilities, resources, and management options !

§  Decision framework: logical relationships of general management objectives to technical risk!

§  Define management objectives, values and preferences!

§  Determine the risk ʻlandscapeʼ!

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Plant Boundary

Road Network

Transmission Lines

Visibility

Slope

+

+

+

+

Plant Boundary

Plant Boundary + Road Network

Plant Boundary + Road Network + Transmission Lines

Plant Boundary + Road Network + Transmission Lines + Visibility

Plant Boundary + Road Network + Transmission Lines + Visibility + Slope

Risk Zone Process

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RISK ZONE AREAS

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Frequency of Fatalities Due to Man-Caused Events

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Framework for hazard detection and judgment of evidence

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Quantitative dominance of PPV and NPV by low frequency of hazard occurrence

Insensitive to false positive or false negative rates, the number of false positives will overwhelm the false negatives

as the frequency of hazard decreases

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§  For low frequency hazards, a large number of false positives can lead to ʻcomplacencyʼ!

§  For low frequency hazards, false negatives may be rare and difficult to detect, but consequences can be extremely severe!

§  When false positives or negatives are found, structured tests need to be performed to determine their causes!

§  Dominance of false positives over false negatives argues that trying to get to ʻzero riskʼ is destabilizing: rather, risk tradeoffs are inevitable!

§  False positive and false negative rates, and frequency of hazard are initially uncertain: there must be constant iteration and feedback among the data and these factors!

These issues entail the importance of the interplay and feedbacks among data and models to manage

uncertainty

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