Atjaunināt sīkdatņu piekrišanu

Risk Management in Civil Infrastructure [Hardback]

(Weidlinger Associates Inc., New York, USA),
  • Formāts: Hardback, 528 pages, height x width: 254x178 mm, weight: 1133 g, 461 Tables, black and white; 291 Line drawings, black and white; 48 Halftones, black and white; 339 Illustrations, black and white
  • Sērija : Civil Infrastructure Health and Sustainability
  • Izdošanas datums: 01-Dec-2016
  • Izdevniecība: CRC Press Inc
  • ISBN-10: 148220844X
  • ISBN-13: 9781482208443
Citas grāmatas par šo tēmu:
  • Hardback
  • Cena: 217,27 €
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Bibliotēkām
Risk Management in Civil InfrastructurePalielināt
  • Formāts: Hardback, 528 pages, height x width: 254x178 mm, weight: 1133 g, 461 Tables, black and white; 291 Line drawings, black and white; 48 Halftones, black and white; 339 Illustrations, black and white
  • Sērija : Civil Infrastructure Health and Sustainability
  • Izdošanas datums: 01-Dec-2016
  • Izdevniecība: CRC Press Inc
  • ISBN-10: 148220844X
  • ISBN-13: 9781482208443
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781482208443.html
Keywords:

This book presents several original theories for risk, including Theory of Risk Monitoring, and Theory of Risk Acceptance, in addition to several analytical models for computing relative and absolute risk. The book discusses risk limit, states of risk, and the emerging concept of risk monitoring. The interrelationships between risk and resilience are also highlighted in an objective manner. The book includes several practical case studies showing how risk management and its components can be used to enhance performance of infrastructures at reasonable costs.

Recenzijas

"The book Risk Management in Civil Infrastructure is a tour de force that provides fresh insight to the topic of risk management. With civil infrastructure owners increasingly aware of the importance of risk management, the book is very timely and fills a critical need given the absence of such comprehensive books on the topic. The book very effectively provides a new framework for risk management by decomposing risk into topics ranging from assessment to monitoring. Especially noteworthy about the book is the embracing of graph theory as a basic concept necessary for risk management." Jerome Lynch, University of Michigan, USA

"This book fills a big gap in engineering literature as it presents a very thorough and objective study of risk management in civil infrastructure. This includes an extensive review of what is already available but it is the first time this topic has been approached in such a unified, objective and complete manner. The chapters which include risk acceptance, risk treatment, risk monitoring, risk communication and risk management applications deal with issues that are of extreme importance for all stakeholders of civil infrastructure. So far engineers have been thinking about design/analysis and this book connects this process to one more level including consequences and costs in an objective manner. One might reasonably argue this is the future of structural engineering." Simos Gerasimidis, University of Massachusetts, Amherst, USA

Preface xix
Acknowledgments xxi
Authors xxiii
Chapter 1 Introduction 1(38)
1.1 Overview
1(4)
1.1.1 Risk Management Landscape
1(1)
1.1.2 What Is Risk?
1(1)
1.1.3 History of Design Paradigms and Risk
2(2)
1.1.4 Convenient Definition for Risk
4(1)
1.2 Risk Basic Components
5(3)
1.2.1 Overview
5(1)
1.2.2 Threat/Hazard/Demand
5(1)
1.2.3 Vulnerability/Capacity
5(1)
1.2.4 Consequences
6(1)
1.2.5 Basic Risk Equation
7(1)
1.2.6 Risk Analogy Principle
7(1)
1.3 Reliability, Exposure, Likelihood, Resilience, and Sustainability
8(14)
1.3.1 Overview
8(1)
1.3.2 Reliability
9(2)
1.3.3 Exposure
11(1)
1.3.3.1 Exposure Application: Bridge Inspection
11(1)
1.3.4 Likelihood
12(1)
1.3.5 Resilience
13(5)
1.3.5.1 Overview
13(1)
1.3.5.2 Resilience and Its Components
14(2)
1.3.5.3 Resilience Management
16(1)
1.3.5.4 Asset Resilience vs. Community (Network) Resilience
16(2)
1.3.6 Risk Relationships
18(4)
1.3.6.1 Risk Relationship with Resilience
19(3)
1.4 Components of Risk Management
22(7)
1.4.1 Overview
22(1)
1.4.2 Risk Assessment
22(2)
1.4.3 Risk Acceptance
24(1)
1.4.4 Risk Treatment/Improvement
25(2)
1.4.5 Risk Monitoring
27(2)
1.4.6 Risk Communications
29(1)
1.5 Miscellaneous Issues Related to Risk Management
29(6)
1.5.1 Overview
29(1)
1.5.2 Uncertainty
30(1)
1.5.3 Intersections/Links/Networks
31(1)
1.5.4 Multihazards Considerations
31(1)
1.5.5 Snapshot vs. Time Marching
31(1)
1.5.6 Subjective vs. Objective Risk
31(1)
1.5.7 Cascading Effects
32(2)
1.5.8 Unintended Consequences
34(1)
References
35(4)
Chapter 2 Graph Networks 39(40)
2.1 Introduction
39(1)
2.1.1 Overview
39(1)
2.1.2 Contents of This
Chapter
39(1)
2.2 Formal Modeling of Graph Networks
40(4)
2.2.1 Overview
40(1)
2.2.2 Components of Graph Networks
41(2)
2.2.2.1 Nodes
41(1)
2.2.2.2 Links
42(1)
2.2.2.3 Layers
42(1)
2.2.3 Tree vs. Network
43(1)
2.2.4 Cyclic vs. Acyclic Networks
43(1)
2.2.5 Observations (Evidence)
44(1)
2.2.5.1 Soft Evidence vs. Hard Evidence
44(1)
2.3 Bayesian Networks
44(8)
2.3.1 Bayesian Theory
44(1)
2.3.2 Definition of Bayesian Networks
45(1)
2.3.3 Templates of BN Examples
45(1)
2.3.4 Case Study 2.1: Absolute Risk vs. Relative Risk
46(3)
2.3.4.1 Overview
46(1)
2.3.4.2 Model
46(1)
2.3.4.3 Conditional Probabilities Tables
47(1)
2.3.4.4 Results
48(1)
2.3.4.5 Concluding Remarks
49(1)
2.3.5 Case Study 2.2: Infrastructure Security
49(3)
2.3.5.1 Overview
49(1)
2.3.5.2 Model
49(1)
2.3.5.3 Conditional Probabilities Tables
49(1)
2.3.5.4 Results
50(2)
2.3.6 Bayesian Network: Closing Remarks
52(1)
2.4 Markov Networks
52(7)
2.4.1 Case Study 2.3: Traffic and Functional Class
53(1)
2.4.1.1 Overview
53(1)
2.4.1.2 Potentials
54(1)
2.4.1.3 Results
54(1)
2.4.2 Case Study 2.4: Architectural Vulnerability
54(3)
2.4.2.1 Overview
54(1)
2.4.2.2 Model
54(1)
2.4.2.3 Conditional Probabilities Tables
55(1)
2.4.2.4 Results
55(2)
2.4.3 Case Study 2.3 Revisited: Traffic and Functional Class
57(2)
2.4.4 Concluding Remarks
59(1)
2.5 Chain Graphs: Combining Bayesian and Markov Networks
59(4)
2.5.1 Overview
59(1)
2.5.2 Case Study 2.5: Risk and Its Components
59(4)
2.5.2.1 Overview
59(1)
2.5.2.2 Model
59(1)
2.5.2.3 CPTs and Potentials
59(2)
2.5.2.4 Results
61(2)
2.6 Decision under Uncertainty: Influence Diagrams
63(6)
2.6.1 Overview
63(1)
2.6.2 Decision Trees and Utility
63(4)
2.6.2.1 Overview
63(1)
2.6.2.2 Utility vs. Risk
63(1)
2.6.2.3 Case Study 2.6: Structure Inspection and Monitoring Methods Using Decision Tree
64(3)
2.6.3 Influence Diagrams
67(2)
2.6.3.1 Overview
67(1)
2.6.3.2 Case Study 2.7: Structure Inspection and Monitoring Methods Using ID
67(2)
2.7 Dynamic Graph Networks
69(7)
2.7.1 Overview
69(3)
2.7.2 Time Marching in DGN
72(1)
2.7.3 Case Study 2.8: Observed vs. Actual Infrastructure Condition Rating
72(4)
2.8 Sources of CPTs
76(1)
2.9 Concluding Remarks
76(1)
References
77(2)
Chapter 3 Risk Assessment 79(112)
3.1 Introduction
79(7)
3.1.1 Overview
79(1)
3.1.2 Risk Assessment in Civil Infrastructures
79(7)
3.1.2.1 Natural Hazards
79(1)
3.1.2.2 Man-made Hazards
80(1)
3.1.2.3 Flood and Scour Hazards
81(1)
3.1.2.4 Geotechnical Engineering
81(1)
3.1.2.5 Offshore Platforms and Coastal Engineering
82(1)
3.1.2.6 Bridge Engineering
83(1)
3.1.2.7 Construction Engineering
83(1)
3.1.2.8 Environmental Risk
84(1)
3.1.2.9 Urban Risks
85(1)
3.1.3 This
Chapter
86(1)
3.2 Risk Assessment Methods and Related Issues
86(6)
3.2.1 Essential Ingredient of Risk Assessment
86(1)
3.2.2 Risk Assessment Methods (Risk as a Function of Random Variables)
87(1)
3.2.2.1 Weighted Averages
88(1)
3.2.2.2 Probabilistic Tree Construct Methods: FTA and ETA
88(1)
3.2.2.3 Graph Networks
88(1)
3.2.3 Combination of Risks
88(1)
3.2.3.1 Overview
88(1)
3.2.3.2 Analytical Methods
89(1)
3.2.3.3 GN-Based Methods
89(1)
3.2.4 Limit States and Risk Assessment
89(3)
3.2.4.1 Objective Limit States
90(1)
3.2.4.2 Subjective Limit States
90(1)
3.2.4.3 Exposure Limit States
90(2)
3.2.4.4 Consequence Limit States
92(1)
3.2.4.5 Risk Limit States
92(1)
3.3 Weighted Averages
92(8)
3.3.1 Overview
92(1)
3.3.2 Case Study 3.1: Mass Transit Stations
93(1)
3.3.3 Case Study 3.2: Tunnels
93(6)
3.3.4 Limitations
99(1)
3.4 Probabilistic GN
100(14)
3.4.1 Overview
100(1)
3.4.2 Case Study 3.3: Earthquake Risk
101(1)
3.4.2.1 Overview
101(1)
3.4.2.2 Model Description
101(1)
3.4.2.3 Conditional Probabilities Tables
101(1)
3.4.2.4 Results
101(1)
3.4.3 Case Study 3.4: Blast Risk
102(5)
3.4.3.1 Overview
102(1)
3.4.3.2 Model Description
102(4)
3.4.3.3 Conditional Probabilities Tables
106(1)
3.4.3.4 Results
106(1)
3.4.4 Case Study 3.5: Building Security
107(4)
3.4.4.1 Overview
107(1)
3.4.4.2 Model Description
108(1)
3.4.4.3 Conditional Probabilities Tables
108(2)
3.4.4.4 Results
110(1)
3.4.4.5 Concluding Remarks
110(1)
3.4.5 Case Study 3.6: Absolute Risk
111(3)
3.4.5.1 Overview
111(1)
3.4.5.2 Model
112(1)
3.4.5.3 Conditional Probabilities Tables
112(1)
3.4.5.4 Results
112(2)
3.5 Civil Infrastructures Networks
114(13)
3.5.1 Overview
114(1)
3.5.2 Case Study 3.7: BN Risk Assessment of Bridge Network
115(8)
3.5.2.1 Overview
115(4)
3.5.2.2 Model
119(1)
3.5.2.3 Conditional Probabilities Tables
119(1)
3.5.2.4 Results
120(3)
3.5.3 Case Study 3.8: Chain Graph Risk Assessment of Bridge Network
123(4)
3.5.3.1 Overview
123(1)
3.5.3.2 Model
124(1)
3.5.3.3 Conditional Probabilities Tables
125(1)
3.5.3.4 Results
126(1)
3.6 Resilience Assessment
127(13)
3.6.1 Introduction
127(1)
3.6.2 Case Study 3.9: Flood (Scour) Resilience of Bridges, A 4-R Model
128(6)
3.6.2.1 Overview
128(2)
3.6.2.2 Model Description
130(2)
3.6.2.3 Conditional Probabilities Tables
132(1)
3.6.2.4 Marginal Probabilities
132(2)
3.6.3 Case Study 3.10: Time-Continued Operations: Hazard Independent Building Resilience Model
134(57)
3.6.3.1 Overview
134(1)
3.6.3.2 Model Description
135(1)
3.6.3.3 Conditional Probabilities Tables
135(1)
3.6.3.4 Results
136(4)
Appendix 3.I: Definitions of Network Nodal Variables
140(4)
Appendix 3.II: CPTs for Case Study 3.3
144(4)
Appendix 3.III: CPTs for Case Study 3.4
148(4)
Appendix 3.IV: CPTs and Potentials for Case Study 3.5
152(10)
Appendix 3.V: CPTs for Case Study 3.6
162(2)
Appendix 3.VI: CPTs for Case Study 3.7
164(7)
Appendix 3.VII: CPTs and Potentials for Case Study 3.8
171(8)
Appendix 3.VIII: CPTs for Case Study 3.9
179(4)
Appendix 3.IX: CPTs for Case Study 3.10
183(4)
References
187(4)
Chapter 4 Risk Acceptance 191(70)
4.1 Introduction
191(3)
4.1.1 Overview
191(1)
4.1.2 Historical Background
191(2)
4.1.3 Definitions
193(1)
4.1.4 This
Chapter
194(1)
4.2 Overview of Risk Acceptance Methods
194(1)
4.3 Subjective Risk Acceptance Methods
195(4)
4.3.1 Overview
195(1)
4.3.2 Existing Methods
195(1)
4.3.3 Components Based Risk Acceptance
196(1)
4.3.3.1 Multicomponent Acceptance
196(1)
4.3.3.2 Reliability-Based Acceptance
197(1)
4.3.3.3 Exposure-Based Acceptance
197(1)
4.3.3.4 Three-Component Acceptance
197(1)
4.3.4 Risk vs. Opportunity or Reward (Cost-Benefit) Acceptance Methods
197(2)
4.4 Semi-Subjective Risk Acceptance Methods
199(4)
4.4.1 Overview
199(1)
4.4.2 Utility Theory
199(2)
4.4.2.1 Overview
199(1)
4.4.2.2 Theory of Utility
199(1)
4.4.2.3 Types of Utility
200(1)
4.4.2.4 Use of Utility in Risk Acceptance
201(1)
4.4.3 Value at Risk
201(1)
4.4.4 Available Budget Method
202(1)
4.4.5 Target Risk Method
202(1)
4.5 Lower Limit States: Deterioration of Infrastructures
203(11)
4.5.1 Overview
203(1)
4.5.2 Case Study 4.1: Deterioration of Single Asset
204(6)
4.5.2.1 Overview
204(1)
4.5.2.2 Model
204(1)
4.5.2.3 Conditional Probabilities Tables
205(1)
4.5.2.4 Results
206(2)
4.5.2.5 Summary
208(2)
4.5.3 Case Study 4.2: Deterioration of Multiple Connected Assets: Infrastructures Networks
210(4)
4.5.3.1 Overview
210(1)
4.5.3.2 Model
210(1)
4.5.3.3 Conditional Probabilities Tables
211(1)
4.5.3.4 Results
211(3)
4.6 Case Study 4.3: Higher (Ductile) Limit States
214(8)
4.6.1 Overview
214(2)
4.6.2 Model
216(2)
4.6.3 Conditional Probabilities Tables
218(1)
4.6.4 Results
218(4)
4.7 Case Study 4.4: Brittle Limit States: Risk/Reward of Proof Tests
222(5)
4.7.1 Overview
222(1)
4.7.2 Model
223(1)
4.7.3 Conditional Probabilities Tables
224(1)
4.7.4 Results
225(2)
4.8 Acceptance Using Decision Methods
227(10)
4.8.1 Overview of Decision Methods
227(1)
4.8.2 Case Study 4.5: Deterioration (Exposure)-Based Acceptance and Decision (01.03.02A)
227(4)
4.8.2.1 Overview
227(1)
4.8.2.2 Model
228(2)
4.8.2.3 Conditional Probabilities Tables
230(1)
4.8.2.4 Results
230(1)
4.8.2.5 Summary
231(1)
4.8.3 Case Study 4.6: Deterioration (Exposure) and Consequences Based Acceptance and Decision
231(6)
4.8.3.1 Overview
231(1)
4.8.3.2 Model
232(1)
4.8.3.3 Conditional Probabilities Tables
233(1)
4.8.3.4 Results
233(4)
4.8.3.5 Summary
237(1)
4.9 Grandfathering: The Hidden Risk Acceptance Practice
237(9)
4.9.1 Process
238(1)
4.9.2 Case Study 4.7: Objective Grandfathering Process Using Weighted Averages
238(3)
4.9.3 Case Study 4.8: Objective Grandfathering Process Using ID
241(4)
4.9.3.1 Overview
241(1)
4.9.3.2 Model
241(2)
4.9.3.3 Conditional Probabilities Tables
243(1)
4.9.3.4 Results
243(2)
4.9.4 Summary
245(1)
Appendix 4.I: Definitions of Network Nodal Variables
246(1)
Appendix 4.II: CPTs for Case Study 4.1
247(2)
Appendix 4.III: CPTs for Case Study 4.2
249(4)
Appendix 4.IV: CPTs for Case Study 4.3
253(2)
Appendix 4.V: CPTs for Case Study 4.4
255(1)
Appendix 4.VI: CPTs for Case Study 4.5
255(1)
Appendix 4.VII: CPTs for Case Study 4.6
256(1)
Appendix 4.VIII: CPTs for Case Study 4.8
257(2)
References
259(2)
Chapter 5 Risk Treatment 261(76)
5.1 Introduction
261(3)
5.1.1 Overview
261(2)
5.1.2 Objectives of Risk Treatment
263(1)
5.1.3 This
Chapter
264(1)
5.2 Phases of Risk Treatment
264(3)
5.2.1 Overview
264(1)
5.2.2 Phase I: Choose Strategy
264(3)
5.2.2.1 Risk Transfer (or Sharing)
265(1)
5.2.2.2 Risk Mitigation (Modification)
265(1)
5.2.2.3 Accept/Tolerate Risk
266(1)
5.2.2.4 Remove/Circumvent/Avoid Risk
266(1)
5.2.3 Phase II: Project Plans and Prioritization
267(1)
5.2.4 Phase III: Execute Strategy
267(1)
5.3 Need for Objective Approach when Choosing Risk Treatment Strategy
267(8)
5.3.1 Overview
267(1)
5.3.2 Modeling Processes
267(3)
5.3.3 Case Study 5.1: Simple Risk Treatment Model: Interaction between Exposure and Consequences
270(4)
5.3.3.1 Overview
270(1)
5.3.3.2 Bayesian Network Model
270(1)
5.3.3.3 Conditional Probabilities Tables
271(1)
5.3.3.4 Results
271(2)
5.3.3.5 Optimal Decision/Strategy for Risk Treatment
273(1)
5.3.4 Revisiting the C—L Diagram Method
274(1)
5.4 Risk vs. Reliability Treatment
275(1)
5.5 Project Prioritization Strategies
275(2)
5.5.1 Overview
275(1)
5.5.2 The Dilemma of Project Prioritization
276(1)
5.5.2.1 CapEx as a Prioritization Metric
276(1)
5.5.2.2 Cost/Benefit as a Prioritization Metric
276(1)
5.5.2.3 LCC and LCA as a Prioritization Metric
277(1)
5.5.3 The Case for Risk as Prioritization Metric
277(1)
5.6 Risk Treatment: Multiphase Decision Process
277(9)
5.6.1 Overview
277(1)
5.6.2 Case Study 5.2: Multiphase Risk Treatment Decisions for a Single Asset
278(2)
5.6.2.1 Model
278(1)
5.6.2.2 Conditional Probabilities Tables
279(1)
5.6.2.3 Results
280(1)
5.6.2.4 Optimal Decisions
280(1)
5.6.3 Case Study 5.3: Multiphase Risk Treatment Decisions for Asset Networks
280(6)
5.6.3.1 Overview
280(4)
5.6.3.2 Model
284(1)
5.6.3.3 Conditional Probabilities Tables
285(1)
5.6.3.4 Results
285(1)
5.6.3.5 Optimal Decisions
285(1)
5.7 Case Study 5.4: Prioritization Methods in Risk Treatment
286(29)
5.7.1 Overview
286(1)
5.7.2 Risk Variables
287(8)
5.7.3 Weighted Averages
295(4)
5.7.3.1 Overview
295(1)
5.7.3.2 Results
296(3)
5.7.4 Probabilistic Graph Network
299(13)
5.7.4.1 Overview
299(1)
5.7.4.2 Model
299(2)
5.7.4.3 Subnetworks
301(2)
5.7.4.4 Nodes and Their States
303(1)
5.7.4.5 Sources and Description of Potentials and CPTs
304(1)
5.7.4.6 Prior (Initial Results)
304(2)
5.7.4.7 Evidence (Observation) Introductions
306(6)
5.7.5 Concluding Remarks
312(3)
Appendix 5.I: Definitions of Network Nodal Variables
315(2)
Appendix 5.II: CPTs for Case Study 5.1
317(1)
Appendix 5.III: CPTs for Case Study 5.2
318(2)
Appendix 5.IV: CPTs for Case Study 5.3
320(2)
Appendix 5.V: Marginal Probability for Decision Scenarios of Case Study 5.3
322(9)
Appendix 5.VI: CPTs and Potentials for Case Study 5.4
331(3)
References
334(3)
Chapter 6 Risk Monitoring 337(42)
6.1 Introduction
337(3)
6.1.1 Overview
337(2)
6.1.2 Objectives of Risk Monitoring
339(1)
6.1.2.1 Monitoring Risk Components
339(1)
6.1.2.2 Monitoring Temporal Behavior of Risk: Trending and Forecasting
339(1)
6.1.2.3 Other Risk Monitoring Objectives
340(1)
6.1.3 This
Chapter
340(1)
6.2 Components of Risk Monitoring
340(8)
6.2.1 Overview
340(2)
6.2.2 Hazards/Demand Monitoring
342(2)
6.2.3 Capacity Monitoring
344(1)
6.2.4 Exposure (Reliability) Monitoring
344(1)
6.2.4.1 Exposure Monitoring at Lower Limit States
345(1)
6.2.5 Consequences Monitoring
345(3)
6.2.5.1 Overview
345(3)
6.2.6 Putting It All Together: Risk Monitoring
348(1)
6.3 Case Study 6.1: Risk-Based vs. Exposure (or Reliability)-Based Monitoring
348(2)
6.3.1 Overview
348(1)
6.3.2 Model
348(1)
6.3.3 CPTs and Potentials
349(1)
6.3.4 Results
349(1)
6.4 Case Study 6.2: Inference in Risk Monitoring
350(4)
6.4.1 Overview
350(1)
6.4.2 Model
351(1)
6.4.3 Conditional Probabilities Tables
351(2)
6.4.4 Results
353(1)
6.5 Case Study 6.3: Forecasting Future Risk of Deterioration and Condition Ratings
354(17)
6.5.1 Overview
354(6)
6.5.1.1 Sources of Deterioration
355(1)
6.5.1.2 Modeling Deterioration
355(3)
6.5.1.3 Markov Model
358(1)
6.5.1.4 Probability Distributions
359(1)
6.5.1.5 Reliability Index Model
359(1)
6.5.1.6 Concluding Remarks
360(1)
6.5.2 CGN Process in Forecasting
360(1)
6.5.3 Model
361(3)
6.5.4 Conditional Probabilities Tables
364(1)
6.5.5 Prior (Initial) Marginal Probabilities (Initial Time Slice)
365(1)
6.5.6 Filtering (First Time Slice)
366(2)
6.5.7 Forecasting (Prediction) at Future Time Slice
368(3)
Appendix 6.I: Definitions of Network Nodal Variables
371(1)
Appendix 6.II: CPTs and Potentials for Case Study 6.1
372(1)
Appendix 6.III: CPTs for Case Study 6.2
373(3)
Appendix 6.IV: CPTs for Case Study 6.3
376(1)
References
377(2)
Chapter 7 Risk Communication 379(26)
7.1 Overview
379(2)
7.1.1 What Is Risk Communications?
379(1)
7.1.2 Lasswell Model
379(1)
7.1.3 Objectives of Risk Communications
380(1)
7.1.4 This
Chapter
380(1)
7.2 Issues of Importance in Communicating Risk
381(2)
7.2.1 Centrality of Risk Communications within Risk Management
381(1)
7.2.2 Theories of Risk Communications
381(1)
7.2.3 Planning Risk Communications
382(1)
7.3 Sources of Risk Communications
383(3)
7.4 Communication Message: How to Communicate Risk
386(2)
7.4.1 Overview
386(1)
7.4.2 Reliability Communications vs. Risk Communication Messages
386(1)
7.4.3 Communication Messages with the Public
387(1)
7.4.4 Obstacles to Efficient Communication Messages
387(1)
7.5 Mediums (Channels) of Communications
388(2)
7.5.1 Overview
388(1)
7.5.2 Visual Mediums
388(1)
7.5.3 Statistical/Analytical Mediums
389(1)
7.5.4 Qualitative Mediums
389(1)
7.5.5 Others Communication Mediums
390(1)
7.6 Receivers of Risk Communications
390(1)
7.7 Case Study 7.1: Effects of Communications: Quantification of Lasswell Model
390(4)
7.7.1 Overview
390(1)
7.7.2 Model
391(1)
7.7.3 Conditional Probabilities Tables
392(1)
7.7.4 Results
392(1)
7.7.5 Remarks
393(1)
7.8 Communicating Basic Risk Components
394(4)
7.8.1 Overview
394(1)
7.8.2 Communicating Hazards
395(1)
7.8.2.1 Type of Hazards
395(1)
7.8.2.2 Phases of Catastrophic Hazards
396(1)
7.8.3 Communicating Vulnerability, Capacity, Reliability, and Exposure
396(1)
7.8.4 Communicating Consequences
397(1)
7.9 Communicating Risk Management Components
398(3)
7.9.1 Overview
398(1)
7.9.2 Assessment
398(1)
7.9.3 Acceptance
399(1)
7.9.4 Treatment
399(1)
7.9.5 Monitoring
399(2)
Appendix 7.I: Definitions of Nodal Variables
401(1)
Appendix 7.II: CPTs for Case Study 7.1 (Objective Lasswell Model)
401(2)
References
403(2)
Chapter 8 Risk Management Applications 405(88)
8.1 Introduction
405(3)
8.1.1 Overview
405(2)
8.1.2 This
Chapter
407(1)
8.2 Case Study 8.1: Critical Findings Practice: Is It a Complete Risk-Management Process?
408(8)
8.2.1 Overview
408(2)
8.2.1.1 Critical Findings Practice
408(2)
8.2.1.2 Critical Findings Process (Flagging) as a Risk Management Process
410(1)
8.2.2 Model
410(4)
8.2.2.1 ID Model of Flag Situations
412(1)
8.2.2.2 Utility of Different Decisions
413(1)
8.2.3 CPTs
414(1)
8.2.4 Results
414(2)
8.2.5 Concluding Remarks
416(1)
8.3 Case Study 8.2: Essentiality of Risk-Based Management for Progressive Collapse Considerations of Bridges
416(10)
8.3.1 Overview
416(1)
8.3.2 Historical Overview of PCB
417(1)
8.3.3 Fracture Critical Condition and the Susceptibility to PC
418(1)
8.3.4 Bridge-Specific Generalized Definition of PC
419(1)
8.3.5 PC: Buildings vs. Bridges
419(1)
8.3.6 Assessment of PC Potential in Bridges
419(2)
8.3.7 Risk Management of PCB Potential
421(2)
8.3.7.1 General
421(1)
8.3.7.2 Essential Components of Dealing with Potential of PCBs
421(1)
8.3.7.3 Risk-Based PCB Treatment
421(2)
8.3.8 PCB Risk Assessment Using BN
423(3)
8.3.8.1 Overview
423(1)
8.3.8.2 Model
423(1)
8.3.8.3 Conditional Probabilities Tables
423(1)
8.3.8.4 Results
424(1)
8.3.8.5 Summary
425(1)
8.4 Case Studies 8.3 and 8.4: Super Storms: Cascading Effects (CE) and Resilience (Re)
426(12)
8.4.1 Overview
426(3)
8.4.2 Metrics and Methodologies of CE
429(2)
8.4.3 Assessment and Mitigation
431(1)
8.4.4 State of the Art
432(1)
8.4.5 Case Study 8.3: Community Resilience and Cascading Effects
432(2)
8.4.5.1 Overview
432(1)
8.4.5.2 Model Description
433(1)
8.4.5.3 CPTs and Potentials
433(1)
8.4.5.4 Results
434(1)
8.4.6 Case Study 8.4: Effects of Redundancy
434(4)
8.4.6.1 Overview
434(1)
8.4.6.2 Model
435(2)
8.4.6.3 CPTs and Potentials
437(1)
8.4.6.4 Results
437(1)
8.5 Case Study 8.5: Risk-Based Structural Deficiency of Bridges
438(7)
8.5.1 Overview
438(1)
8.5.2 Model
439(2)
8.5.2.1 Model Topology
439(2)
8.5.2.2 Transfer Matrices
441(1)
8.5.3 Conditional Probabilities Tables
441(1)
8.5.4 Results
441(4)
8.5.5 Concluding Remarks
445(1)
8.6 Case Study 8.6: Risk-Based Functional Deficiency
445(5)
8.6.1 Overview
445(1)
8.6.2 Model
446(2)
8.6.2.1 Model Topology
446(1)
8.6.2.2 Transfer Matrices
446(2)
8.6.3 Conditional Probabilities Tables
448(1)
8.6.4 Results
448(1)
8.6.5 Remarks
449(1)
8.7 Case Study 8.7: Suspension Bridge Security
450(15)
8.7.1 Elements of Suspension Bridge Security
450(2)
8.7.1.1 Overview
450(1)
8.7.1.2 Assessment
451(1)
8.7.2 Security Risk Model
452(13)
8.7.2.1 Model
452(3)
8.7.2.2 Conditional Probabilities Tables
455(1)
8.7.2.3 Results
455(10)
Appendix 8.I: Definitions of Network Nodal Variables
465(2)
Appendix 8.II: CPTs for Case Study 8.1
467(5)
Appendix 8.III: CPTs for Case Study 8.2
472(4)
Appendix 8.IV: CPTs and Potentials for Case Study 8.3
476(2)
Appendix 8.V: CPTs for Case Study 8.4
478(1)
Appendix 8.VI: CPTs for Case Study 8.5
478(3)
Appendix 8.VII: CPTs for Case Study 8.6
481(5)
Appendix 8.VIII: CPTs for Case Study 8.7
486(3)
References
489(4)
Appendix A: Truncated Normal Distributions 493(2)
Appendix B: Statistics of Histograms 495(2)
Index 497
Mohammed M. Ettouney, Sreenivas Alampalli