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9780780360174

Probablistic Risk Assessment and Management for Engineers and Scientists

by ;
  • ISBN13:

    9780780360174

  • ISBN10:

    0780360176

  • Edition: 2nd
  • Format: Paperback
  • Copyright: 2000-04-18
  • Publisher: Wiley-IEEE Press

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Summary

Electrical Engineering Probabilistic Risk Assessment and Management for Engineers and Scientists Second Edition "State of the art in risk analysis...[this book] projects the technology into the next decade. Congratulations to the authors on a virtuoso performance." -Charles Donaghey, University of Houston "A very useful reference to the academic and government communities, and junior engineering staff within nuclear, chemical, transportation, aerospace, and other industries." -Yovan Lukic, Arizona Public Service Company As the demands of government agencies and insurance companies escalate, societal risk assessment and management become increasingly critical to the development and use of engineered systems in the full range of industrial installations. Packed with real-world examples and practical mathematical and statistical methods for large, complex systems, this definitive text and sourcebook gives you the guidance you need for thorough and conclusive study. You'll find new and updated coverage of all the key topics related to risk analysis: * Probabilistic nature of risk * Qualitative and quantitative risk assessments * System decomposition * Legal and regulatory risks * And much more! The authors also provide end-of-chapter problems and a course outline. Complete with a new, automated, fault tree synthesis method using semantic networks. Probabilistic Risk Assessment and Management for Engineers and Scientists, Second Edition will be of value to anyone working with engineered systems. Also of Interest from IEEE Press... Successful Patents and Patenting for Engineers and Scientists edited by Michael A. Lechter, Esq. 1995 Softcover 432 pp IEEE Order No. PP4478 ISBN 0-7803-1086-1 Metric Units and Conversion Charts A Metrication Handbook for Engineers, Technologists, and Scientists Second Edition Theodore Wildi 1995 Softcover 144 pp IEEE Order No. PP4044 ISBN 0-7803-1050-0 The Probability Tutoring Book An Intuitive Course for Engineers and Scientists (And Everyone Else!) Carol Ash 1993 Softcover 480 pp IEEE Order No. PP2881 ISBN 0-7803-1051-9

Author Biography

Professor Hiromitsu Kumamoto is a Professor in the Graduate School of Informatics at Kyoto University. His research interests include Human Roles in Systems, Human-Machine Systems, Intelligent Transport Systems, and System Reliability and Safety Assessment. Ernest J. Henley is the author of Probablistic Risk Assessment and Management for Engineers and Scientists, 2nd Edition, published by Wiley.

Table of Contents

Preface xv
Basic Risk Concepts
1(54)
Introduction
1(1)
Formal Definition of Risk
1(17)
Outcomes and Likelihoods
1(3)
Uncertainty and Meta-Uncertainty
4(2)
Risk Assessment and Management
6(2)
Alternatives and Controllability of Risk
8(4)
Outcome Significance
12(2)
Causal Scenario
14(1)
Population Affected
15(1)
Population Versus Individual Risk
15(3)
Summary
18(1)
Source of Debates
18(8)
Different Viewpoints Toward Risk
18(1)
Differences in Risk Assessment
19(3)
Differences in Risk Management
22(4)
Summary
26(1)
Risk-Aversion Mechanisms
26(9)
Risk Aversion
27(1)
Three Attitudes Toward Monetary Outcome
27(3)
Significance of Fatality Outcome
30(1)
Mechanisms for Risk Aversion
31(1)
Bayesian Explanation of Severity Overestimation
31(1)
Bayesian Explanation of Likelihood Overestimation
32(3)
PRAM Credibility Problem
35(1)
Summary
35(1)
Safety Goals
35(20)
Availability, Reliability, Risk, and Safety
35(1)
Hierarchical Goals for PRAM
36(1)
Upper and Lower Bound Goals
37(5)
Goals for Normal Activities
42(1)
Goals for Catastrophic Accidents
43(5)
Idealistic Versus Pragmatic Goals
48(4)
Summary
52(1)
References
53(1)
Problems
54(1)
Accident Mechanisms and Risk Management
55(40)
Introduction
55(1)
Accident-Causing Mechanisms
55(20)
Common Features of Plants with Risks
55(2)
Negative Interactions Between Humans and the Plant
57(1)
A Taxonomy of Negative Interactions
58(4)
Chronological Distribution of Failures
62(2)
Safety System and Its Malfunctions
64(3)
Event Layer and Likelihood Layer
67(5)
Dependent Failures and Management Deficiencies
72(3)
Summary
75(1)
Risk Management
75(10)
Risk-Management Principles
75(3)
Accident Prevention and Consequence Mitigation
78(1)
Failure Prevention
78(3)
Propagation Prevention
81(3)
Consequence Mitigation
84(1)
Summary
85(1)
Preproduction Quality Assurance Program
85(10)
Motivation
86(1)
Preproduction Design Process
86(1)
Design Review for PQA
87(5)
Management and Organizational Matters
92(1)
Summary
93(1)
References
93(1)
Problems
94(1)
Probabilistic Risk Assessment
95(70)
Introduction to Probabilistic Risk Assessment
95(9)
Initiating-Event and Risk Profiles
95(1)
Plants without Hazardous Materials
96(1)
Plants with Hazardous Materials
97(1)
Nuclear Power Plant PRA: WASH-1400
98(4)
WASH-1400 Update: NUREG-1150
102(2)
Summary
104(1)
Initiating-Event Search
104(13)
Searching for Initiating Events
104(1)
Checklists
105(1)
Preliminary Hazard Analysis
106(2)
Failure Mode and Effects Analysis
108(2)
FMECA
110(3)
Hazard and Operability Study
113(2)
Master Logic Diagram
115(1)
Summary
115(2)
The Three PRA Levels
117(11)
Level 1 PRA---Accident Frequency
117(9)
Level 2 PRA---Accident Progression and Source Term
126(1)
Level 3 PRA---Offside Consequence
127(1)
Summary
127(1)
Risk Calculations
128(4)
The Level 3 PRA Risk Profile
128(2)
The Level 2 PRA Risk Profile
130(1)
The Level 1 PRA Risk Profile
130(1)
Uncertainty of Risk Profiles
131(1)
Summary
131(1)
Example of a Level 3 PRA
132(1)
Benefits, Detriments, and Successes of PRA
132(6)
Tangible Benefits in Design and Operation
132(1)
Intangible Benefits
133(1)
PRA Negatives
134(1)
Success Factors of PRA Program
134(2)
Summary
136(1)
References
136(2)
Chapter Three Appendices
138(1)
Conditional and Unconditional Probabilities
138(5)
Definition of Conditional Probabilities
138(1)
Chain Rule
139(1)
Alternative Expression of Conditional Probabilities
140(1)
Independence
140(1)
Bridge Rule
141(1)
Bayes Theorem for Discrete Variables
142(1)
Bayes Theorem for Continuous Variables
143(1)
Venn Diagrams and Boolean Operations
143(5)
Introduction
143(1)
Event Manipulations via Venn Diagrams
144(1)
Probability and Venn Diagrams
145(1)
Boolean Variables and Venn Diagrams
146(1)
Rules for Boolean Manipulations
147(1)
A Level for 3 PRA---Station Blackout
148(17)
Plant Description
148(2)
Event Tree for Station Blackout
150(2)
Accident Sequences
152(1)
Fault Trees
152(1)
Accident-Sequence Cut Sets
153(2)
Accident-Sequence Quantification
155(1)
Accident-Sequence Group
156(1)
Uncertainty Analysis
156(1)
Accident-Progression Analysis
156(7)
Summary
163(1)
Problems
163(2)
Fault-Tree Construction
165(62)
Introduction
165(1)
Fault Trees
166(1)
Fault-Tree Building Blocks
166(9)
Gate Symbols
166(6)
Event Symbols
172(2)
Summary
174(1)
Finding Top Events
175(4)
Forward and Backward Approaches
175(1)
Component Interrelations and System Topography
175(1)
Plant Boundary Conditions
176(1)
Example of Preliminary Forward Analysis
176(3)
Summary
179(1)
Procedure for Fault-Tree Construction
179(17)
Fault-Tree Example
180(4)
Heuristic Guidelines
184(4)
Conditions Induces by OR and AND Gates
188(6)
Summary
194(2)
Automated Fault-Tree Synthesis
196(31)
Introduction
196(1)
System Representation by Semantic Networks
197(7)
Event Development Rules
204(2)
Recursive Three-Value Procedure for FT Generation
206(4)
Examples
210(10)
Summary
220(2)
References
222(1)
Problems
223(4)
Qualitative Aspects of System Analysis
227(36)
Introduction
227(1)
Cut Sets and Path Sets
227(13)
Cut Sets
227(1)
Path Sets (Tie Sets)
227(2)
Minimal Cut Sets
229(1)
Minimal Path Sets
229(1)
Minimal Cut Generation (Top-Down)
229(2)
Minimal Cut Generation (Bottom-Up)
231(1)
Minimal Path Generation (Top-Down)
232(1)
Minimal Path Generation (Bottom-Up)
233(1)
Copying with Large Fault Trees
234(6)
Common-Cause Failure Analysis
240(6)
Common-Cause Cut Sets
240(1)
Common-Causes and Basic Events
241(1)
Obtaining Common-Cause Cut Sets
242(4)
Fault-Tree Linking Along an Accident Sequence
246(5)
Simple Example
246(2)
A More Realistic Example
248(3)
Noncoherent Fault Trees
251(12)
Introduction
251(1)
Minimal Cut Sets for a Binary Fault Tree
252(5)
Minimal Cut Sets for a Multistate Fault Tree
257(1)
References
258(1)
Problems
259(4)
Quantification of Basic Events
263(76)
Introduction
263(1)
Probabilistic Parameters
264(21)
A Repair-to-Failure Process
265(6)
A Repair-Failure-Repair Process
271(3)
Parameters of Repair-to-Failure Process
274(4)
Parameters of Failure-to-Repair Process
278(2)
Probabilistic Combined-Process Parameters
280(5)
Fundamental Relations Among Probabilistic Parameters
285(12)
Repair-to-Failure Parameters
285(4)
Failure-to-Repair Parameters
289(1)
Combined-Process Parameters
290(7)
Constant-Failure Rate and Repair-Rate Model
297(7)
Repair-to-Failure Process
297(2)
Failure-to-Repair Process
299(1)
Laplace Transform Analysis
299(4)
Markov Analysis
303(1)
Statistical Distributions
304(1)
General Failure and Repair Rates
304(5)
Estimating Distribution Parameters
309(13)
Parameter Estimation for Repair-to-Failure Process
309(9)
Parameter Estimation for Failure-to-Repair Process
318(4)
Components with Multiple Failure Models
322(3)
Environmental Inputs
325(1)
Command Failures
325(1)
Secondary Failures
325(1)
Human Error
326(1)
System-Dependent Basic Event
326(1)
References
327(1)
Chapter Six Appendices
327(1)
Distributions
327(5)
Mean
328(1)
Median
328(1)
Mode
328(1)
Variance and Standard Deviation
328(1)
Exponential Distribution
329(1)
Normal Distribution
330(1)
Log-Normal Distribution
330(1)
Weibull Distribution
330(1)
Binomial Distribution
331(1)
Poisson Distribution
331(1)
Gamma Distribution
332(1)
Other Distributions
332(1)
A Constant-Failure-Rate Property
332(1)
Derivation of Unavailability Formula
333(1)
Computational Procedure for Incomplete Test Data
334(1)
Median-Rank Plotting Position
334(1)
Failure and Repair Basic Definitions
335(4)
Problems
335(4)
Confidence Intervals
339(24)
Classical Confidence Limits
339(12)
Introduction
339(1)
General Principles
340(6)
Types of Life-Tests
346(1)
Confidence Limits for Mean Time to Failure
346(3)
Confidence Limits for Binomial Distributions
349(2)
Bayesian Reliability and Confidence Limits
351(3)
Discrete Bayes Theorem
351(1)
Continuous Bayes Theorem
352(1)
Confidence Limits
353(1)
References
354(1)
Chapter Seven Appendix
354(1)
The χ2, Student's t, and F Distributions
354(9)
χ2 Distribution Application Modes
355(1)
Student's t Distribution Application Models
356(1)
F Distribution Application Models
357(2)
Problems
359(4)
Quantitative Aspects of System Analysis
363(62)
Introduction
363(2)
Simple Systems
365(9)
Independent Basic Events
365(1)
AND Gate
366(1)
OR Gate
366(1)
Voting Gate
367(4)
Reliability Block Diagrams
371(3)
Truth-Table Approach
374(5)
AND Gate
374(1)
OR Gate
374(5)
Structure-Function Approach
379(4)
Structure Functions
379(1)
System Representation
379(1)
Unavailability Calculations
380(3)
Approaches Based on Minimal Cuts or Minimal Paths
383(6)
Minimal Cut Representations
383(1)
Minimal Path Representations
384(2)
Partial Pivotal Decomposition
386(1)
Inclusion-Exclusion Formula
387(2)
Lower and Upper Bounds for System Unavailability
389(2)
Inclusion-Exclusion Bounds
389(1)
Esary and Proschan Bounds
390(1)
Partial Minimal Cut Sets and Path Sets
390(1)
System Quantification by KITT
391(25)
Overview of KITT
392(5)
Minimal Cut Set Parameters
397(5)
System Unavailability Qs(t)
402(2)
System Parameter Ws(t)
404(5)
Other System Parameters
409(1)
Short-Cut Calculation Methods
410(4)
The Inhibit Gate
414(1)
Remarks on Quantification Methods
415(1)
Alarm Function and Two Types of Failure
416(9)
Definition of Alarm Function
416(1)
Failed-Safe and Failed-Dangerous Failures
416(3)
Probabilistic Parameters
419(1)
References
420(1)
Problems
421(4)
System Quantification for Dependent Events
425(46)
Dependent Failures
425(2)
Functional and Common-Unit Dependency
425(1)
Common-Cause Failure
426(1)
Subtle Dependency
426(1)
System-Quantification Process
426(1)
Markov Model for Standby Redundancy
427(19)
Hot, Cold, and Warm Standby
427(1)
Inclusion-Exclusion Formula
427(1)
Time-Dependent Unavailability
428(11)
Steady-State Unavailability
439(3)
Failures per Unit Time
442(2)
Reliability and Repairability
444(2)
Common-Cause Failure Analysis
446(25)
Subcomponent-Level Analysis
446(3)
Beta-Factor Model
449(7)
Basic-Parameter Model
456(5)
Multiple Greek Letter Model
461(3)
Binomial Failure-Rate Model
464(3)
Markov Model
467(2)
References
469(1)
Problems
469(2)
Human Reliability
471(64)
Introduction
471(1)
Classifying Human Errors for PRA
472(2)
Before an Initiating Event
472(1)
During an Accident
472(2)
Human and Computer Hardware System
474(7)
The Human Computer
474(3)
Brain Bottlenecks
477(1)
Human Performance Variations
478(3)
Performance-Shaping Factors
481(8)
Internal PSFs
481(3)
External PSFs
484(3)
Types of Mental Processes
487(2)
Human-Performance Quantification by PSFs
489(5)
Human-Error Rates and Stress Levels
489(2)
Error Types, Screening Values
491(1)
Response Time
492(1)
Integration of PSFs by Experts
492(2)
Recovery Actions
494(1)
Examples of Human Error
494(4)
Errors in Thought Processes
494(3)
Lapse/Slip Errors
497(1)
SHARP: General Framework
498(1)
THERP: Routine and Procedure-Following Errors
499(7)
Introduction
499(3)
General Therp Procedure
502(4)
HCR: Nonresponse Probability
506(3)
Wrong Actions due to Misdiagnosis
509(4)
Initiating-Event Confusion
509(1)
Procedure Confusion
510(1)
Wrong Actions due to Confusion
510(1)
References
511(2)
Chapter Ten Appendices
513(1)
Therp for Errors During a Plant Upset
513(12)
HCR for Two Optional Procedures
525(5)
Human-Error Probability Tables from Handbook
530(5)
Problems
533(2)
Uncertainty Quantification
535(38)
Introduction
535(1)
Risk-Curve Uncertainty
535(1)
Parametric Uncertainty and Modeling Uncertainty
536(1)
Propagation of Parametric Uncertainty
536(1)
Parametric Uncertainty
536(3)
Statistical Uncertainty
536(1)
Data Evaluation Uncertainty
537(1)
Expert-Evaluated Uncertainty
538(1)
Plant-Specific Data
539(2)
Incorporating Expert Evaluation as a Prior
539(1)
Incorporating Generic Plant Data as a Prior
539(2)
Log-Normal Distribution
541(8)
Introduction
541(1)
Distribution Characteristics
541(1)
Log-Normal Determination
542(1)
Human-Error-Rate Confidence Intervals
543(2)
Product of Log-Normal Variables
545(2)
Bias and Dependence
547(2)
Uncertainty Propagation
549(1)
Monte Carlo Propagation
550(5)
Unavailability
550(2)
Distribution Parameters
552(1)
Latin Hypercube Sampling
553(2)
Analytical Moment Propagation
555(9)
And Gate
555(1)
Or Gate
556(1)
And and Or Gates
557(1)
Minimal Cut Sets
558(2)
Taylor Series Expansion
560(1)
Orthogonal Expansion
561(3)
Discrete Probability Algebra
564(2)
Summary
566(1)
References
566(1)
Chapter Eleven Appendices
567(1)
Maximum-Likelihood Estimator
567(2)
Cut Set Covariance Formula
569(1)
Mean and Variance by Orthogonal Expansion
569(4)
Problems
571(2)
Legal and Regulatory Risks
573(16)
Introduction
573(1)
Losses Arising From Legal Actions
574(6)
Nonproduct Liability Civil Lawsuits
575(1)
Product Liability Lawsuits
575(1)
Lawsuits by Government Agencies
576(1)
Worker's Compensation
577(1)
Lawsuit-Risk Mitigation
578(1)
Regulatory Agency Fines: Risk Reduction Strategies
579(1)
The Effect of Government Regulations on Safety and Quality
580(3)
Stifling of Initiative and Abrogation of Responsibility
581(1)
Overregulation
582(1)
Labor and the Safe Workplace
583(4)
Shaping the Company's Safety Culture
584(1)
The Hiring Process
584(3)
Epilogue
587(2)
Index 589

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