This document summarizes a presentation on risk analysis and management. It discusses identifying potential threats and consequences, reducing vulnerabilities, and mitigating consequences through an integrated approach. It also outlines key elements of risk management like risk identification, mitigation, response and reconstruction. Graphs and diagrams show frameworks for analyzing risk, defining risk zones, and the relationship between risk and available resources/options.

1. AIChE Annual Meeting 2013
November 7, 2013
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

2. Lawrence Livermore National Laboratory
2
LLNL-PRES-xxxxxx

3. Risk Analysis
Potential
Events/Failures
Likelihood/Probability
Reduce
Threats &
Vulnerabilities
Potential
Consequences
Mitigate/
Reduce
Consequences
Response Management
Security and Protection
Emergency Response/
Consequence Management
Risk Reduction: Safety & Security
Lawrence Livermore National Laboratory
3
LLNL-PRES-xxxxxx

4. Integrated Approach
Pr
o
Pr tec
ev tio
en n/
tio
n
Threat
Critical Asset
n/
tio se
ga
iti pon
M s
Re
Lawrence Livermore National Laboratory
Consequence
4
LLNL-PRES-xxxxxx

5. KEY ELEMENTS OF RISK MANAGEMENT
Planning and Preparation
Risk
Identification
Mitigation
Risk Transfer
Response and
Reconstruction
Preparedness
Emergency
Response
Rehabilitation
and
Reconstruction
Hazard assessment
(frequency,
magnitude and
location)
Physical/structural
mitigation works
Insurance/ reinsurance 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.
5
Lawrence Livermore National Laboratory
LLNL-PRES-xxxxxx

6. § 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!
Lawrence Livermore National Laboratory
6
LLNL-PRES-xxxxxx

7. Unacceptable Risk
Resources
Options
Technologies
Potential Losses
Operations
Performance
Minimum Risk
Lawrence Livermore National Laboratory
7
LLNL-PRES-xxxxxx

8. C
Threats
Consequences
Resources
Options
Technologies
C
C
F
Losses
Operations
Performance
Barriers for Safety and Security
Develop protective concepts and management strategies
Lawrence Livermore National Laboratory
8
LLNL-PRES-xxxxxx

9. § 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!
Lawrence Livermore National Laboratory
9
LLNL-PRES-xxxxxx

10. Risk Zone Process
Plant Boundary
Plant Boundary
Road Network
+
Plant Boundary + Road Network
Transmission Lines
+
Plant Boundary + Road Network + Transmission Lines
+
Plant Boundary + Road Network + Transmission Lines + Visibility
+
Plant Boundary + Road Network + Transmission Lines + Visibility + Slope
Visibility
Slope
Lawrence Livermore National Laboratory
10
LLNL-PRES-xxxxxx

11. RISK ZONE AREAS
Lawrence Livermore National Laboratory
11
LLNL-PRES-xxxxxx

12. Frequency of Fatalities Due to Man-Caused Events

13. Framework for hazard detection and
judgment of evidence

14. 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

15. § 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
Lawrence Livermore National Laboratory
15
LLNL-PRES-xxxxxx