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Objective Resilience : Policies and Strategies.

MOP 146examines policies and strategies related to community and asset resilience and provides infrastructure stakeholders with a comprehensive set of practices.

Bibliographic Details
Main Author: Ettouney, Mohammed M.
Corporate Author: Knovel (Firm)
Format: eBook
Language:English
Published: : American Society of Civil Engineers, 2022.
Edition:1st ed.
Series:Manuals and Reports on Engineering Practice Ser.
Subjects:
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Intro
  • Book_5107_C000
  • Half Title
  • Title Page
  • Copyright Page
  • Contents
  • Blue Ribbon Panel (In Alphabetical Order)
  • Authors (In Alphabetical Order)
  • Preface
  • Introduction
  • Book_5107_C001
  • Chapter 1 : On the Definition of Resilience
  • 1.1 Introduction
  • 1.2 Key Observations for the Definition of Resilience
  • 1.2.1 Assessment of Resilience
  • 1.2.2 Acceptance of the Assessment
  • 1.2.3 Resilience Improvement
  • 1.2.4 Resilience Monitoring
  • 1.2.5 Communication
  • 1.3 The Term "Resilience" and a Historical Perspective of the Appearance of the General Concept of Resilience
  • Etymology
  • 1.4 General Key Definitions of Resilience
  • 1.4.1 Definitions from the Literature
  • 1.4.2 Definitions from Agencies
  • 1.5 Key Properties and Common Components of Resilience: Universal Resilience Definition
  • 1.6 Resilience versus Risk
  • 1.7 Needed Attributes for Objectivity and Theory of Resilience Definition
  • 1.7.1 Needed Attributes for Objectivity
  • 1.7.2 Theory of Resilience Definition
  • 1.7.2.1 Proof of Theory of Resilience Definition . Assumptions: We make the following assumptions for the TRD to be valid: (1) We first assume that for any desired resilience-related objective process, S and H are modeled adequately by the set
  • 1.7.2.2 Implications of Theory of Resilience Definition. The TRD has some important implications for any objective resilience processes, and these are as follows: (1) If the resilience objective model under consideration is comprehensive and integr
  • 1.8 Summary and Conclusions
  • 1.9 Recommended Practices
  • References
  • Book_5107_C002
  • Chapter 2 : Objective Resilience of Infrastructure Systems
  • 2.1 Introduction
  • 2.2 Hazards, Threats, and Disruptive or Extreme Events
  • 2.3 Infrastructure Systems.
  • 2.4 Safety and Reliability of Infrastructure Elements
  • 2.5 Safety and Reliability of Infrastructure Systems
  • 2.6 Safety and Reliability of a Set of Interconnected and Interdependent Infrastructure Systems
  • 2.7 Concept of Resilience
  • 2.8 Evaluating and Measuring Resilience
  • 2.8.1 Screening and Prioritization
  • 2.8.2 Scenarios-Case Studies
  • 2.9 Resilience Management
  • 2.10 Strategies for Providing and Enhancing Resilience
  • 2.11 Conclusion
  • 2.12 Recommendations
  • References
  • Book_5107_C003
  • Chapter 3 : Achieving Operational Resilience through Codes, Standards, Metrics, and Benchmarks
  • 3.1 Introduction
  • 3.1.1 Definitions
  • 3.1.2 Scale
  • 3.2 Community Resilience
  • 3.2.1 Codes and Standards
  • 3.2.2 Continuum of Guidance
  • 3.2.3 Expanding Scope
  • 3.2.4 Evolving Risks and Uncertainties
  • 3.2.5 Metrics and Benchmarking
  • 3.3 Recommendations
  • 3.4 Conclusion
  • Bibliography
  • References
  • Book_5107_C004
  • Chapter 4 : Resilience Management of Effects of Hazard Events
  • 4.1 Overview
  • 4.2 Creation of FEMA and Enactment of the Stafford Act
  • 4.3 Key Mitigation Program
  • 4.3.1 FEMA Hazard Mitigation Assistance
  • 4.3.2 National Flood Insurance Program
  • 4.4 The Cost of Mitigation
  • 4.4.1 Disaster Relief Fund
  • 4.4.2 Amendments to the Stafford Act
  • 4.4.3 NFIP Losses
  • 4.5 Mitigation and Resilience
  • 4.6 FEMA ' s New Strategy toward Resilience
  • 4.6.1 2019 FEMA National Response Frameworks
  • 4.6.2 FEMA Economic Sectors and Resilience
  • 4.6.3 Modernizing the Delivery of FEMA Grants
  • 4.6.4 NFIP Trajectory and New Resilience Initiatives
  • 4.7 Recommended Practices
  • BIBLIOGRAPHY
  • References
  • Book_5107_C005
  • Chapter 5 : Asset and System Modeling Considerations for Assessment of Civil Infrastructure Resilience.
  • 5.1 Definition of Resilience
  • 5.2 Resilience Factors for Constructed Facilities
  • 5.2.1 Constructed Facilities as Assets-Impact on System Resilience
  • 5.2.2 Asset Functionality within a Civil Engineering System
  • 5.2.3 Critical and Valuable Facility Assets
  • 5.2.4 Critical Asset Components and Characteristics
  • 5.3 Performance Measures for Constructed Facility Resilience
  • 5.3.1 Limit States, Damage Indices, and Loss Functions
  • 5.3.2 Risk Factors and Resilience Indices
  • 5.3.3 Nonstructural Response, Human or Social Factors
  • 5.3.4 Response, Repair, Restoration, Recovery
  • 5.4 Simulation Tools for Asset and System Resilience Assessment
  • 5.4.1 Finite Elements
  • 5.4.2 Geospatial Analysis
  • 5.4.3 Artificial Intelligence
  • 5.5 Asset Resilience-The Role of Simulation
  • 5.5.1 Multihazard Asset Simulation
  • 5.5.2 Multihazard System Performance Simulation
  • 5.5.3 Case Studies
  • 5.5.3.1 Case Study 1-Resilience of Bridges in North Mississippi. and#x200B; Hurricane Katrina severely impacted the built environment in a number of ways through its devastating combination of high winds and unprecedented surge. A number of highway bridges ke
  • 5.5.3.2 Case Study 2-Resilience of Buildings on the UM Main Campus. The influence of a major earthquake on buildings in north MS has also been a major concern. A number of select facilities were identified for detailed FE simulation prior to Katrin
  • 5.6 Best Practices
  • References
  • Book_5107_C006
  • Chapter 6 : Resilience Management
  • 6.1 Introduction
  • 6.1.1 Definitions
  • 6.1.1.1 The 4Rs. Infrastructure resilience has been defined in numerous ways, and a popular definition was introduced by NIAC (2009) , which states.
  • 6.1.1.2 PPD-8 and PPD-21. Another popular resilience definition, PPD-8, was introduced by NSC (2011) . It was then updated as PPD-21 by the Office of the Press Secretary (2013) . As in almost all popular resilience definitions, its basic contents
  • 6.1.1.3 Resilience, Risk, and Sustainability. Before we end our discussion of resilience definitions, it is of interest to clarify the differences and relationships between resilience and another two important paradigms in civil infrastructure: ri
  • 6.1.2 Asset Resilience versus Community Resilience
  • 6.1.3 Essentiality of Network Considerations for an Objective Resilience Management
  • 6.1.4 Objective versus Subjective Resilience Scales
  • 6.1.5 Multidimensionality of Resilience
  • 6.2 Objective Processes
  • 6.2.1 Overview
  • 6.2.2 Resilience Metrics
  • 6.2.3 Popular Objective Methods
  • 6.2.3.1 Analytical Methods. Evaluating risk, or resilience, using analytical methods is enticing because it can utilize simple formulas that are amenable to mathematical manipulations and can produce finite expressions for resilience
  • see Vose (200
  • 6.2.3.2 Weighted Averages Method. The weighted averages approach has been extensively used for evaluating the resilience of different types of infrastructure
  • see Kennett and others (2011a , b ). They offered a resilience assessment procedure for bui
  • 6.2.3.3 This Section. In the remainder of this section, we briefly discuss four types of objective and semiobjective processes that we will be using in the different examples throughout the chapter. Because of space limitation, we present only the
  • 6.2.4 Networks and Their General Components
  • 6.2.5 Graph Networks
  • 6.2.6 Some Important Graph Networks Properties
  • 6.2.7 Probabilistic Graph Networks.
  • 6.2.7.1 Bayesian Networks. The nodal variables in BNs are all random variables. These random variables can be discrete or continuous. Moreover, the interrelationships among the variables are described by using CPTs. For a detailed description of BNs
  • 6.2.7.2 Markov Networks. Similar to BNs, the variables in MNs (sometimes referred to as Markov random fields) are also random variables. The main difference between BNs and MNs lies in the fact that the links between a subset of variables are nondi
  • 6.2.7.3 Chain Graph. In many practical situations, a need may arise to use a mix of directional and nondirectional links among the variables of a PGN. The resulting PGN is called a chain graph (CG). The name CG derives from the fact that the model
  • 6.2.7.4 Influence Diagrams and Decision-Making. Influence diagrams are a special kind of PGN that supports decision-making. To provide this capability, IDs include two additional types of variables, in addition to random variables. A decision varia
  • 6.2.7.5 Decision-Making, Policy, and Strategy. Any discussion of decision-making should lead us to the subject of policy and strategy. Unfortunately, there is some confusion in using the terms policy and strategy (see Koller and Friedman 2009, P
  • 6.2.8 Dynamic Probabilistic Graph Network
  • 6.2.9 Game Theory
  • 6.2.9.1 Overview. Game theory is a branch of mathematics and economics that has been successfully used in solving many problems in many applications
  • see Fudenberg (1991) , Gibbons (1992) , or Prisner (2014) . We will briefly discuss the basic co
  • 6.2.9.2 Components of Games. Each game will have these components:
  • 6.2.9.3 Plethora of Games and How Games are Solved. Several classes of games are available, see Prisner (2014) . These include, but are not limited to,.