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ASCE Manuals and Reports on Engineering Practice 146 - Objective Resilience: Policies and Strategies, 2022

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ASCE Manuals and Reports on Engineering Practice 146 - Objective Resilience: Policies and Strategies, 2022

Book_5107_C000 [Go to Page]
Half Title
Title Page
Copyright Page
Contents
Blue Ribbon Panel (In Alphabetical Order)
Authors (In Alphabetical Order)
Preface
Introduction
Book_5107_C001 [Go to Page]
Chapter 1: On the Definition of Resilience [Go to Page]
1.1 Introduction
1.2 Key Observations for the Definition of Resilience [Go to Page]
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 [Go to Page]
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 [Go to Page]
1.7.1 Needed Attributes for Objectivity
1.7.2 Theory of Resilience Definition [Go to Page]
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 [Go to Page]
Chapter 2: Objective Resilience of Infrastructure Systems [Go to Page]
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 [Go to Page]
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 [Go to Page]
Chapter 3: Achieving Operational Resilience through Codes, Standards, Metrics, and Benchmarks [Go to Page]
3.1 Introduction [Go to Page]
3.1.1 Definitions
3.1.2 Scale
3.2 Community Resilience [Go to Page]
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 [Go to Page]
Chapter 4: Resilience Management of Effects of Hazard Events [Go to Page]
4.1 Overview
4.2 �Creation of FEMA and Enactment of the Stafford Act
4.3 Key Mitigation Program [Go to Page]
4.3.1 FEMA Hazard Mitigation Assistance
4.3.2 National Flood Insurance Program
4.4 The Cost of Mitigation [Go to Page]
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 [Go to Page]
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 [Go to Page]
Chapter 5: Asset and System Modeling Considerations for Assessment of Civil Infrastructure Resilience [Go to Page]
5.1 Definition of Resilience
5.2 Resilience Factors for Constructed Facilities [Go to Page]
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 [Go to Page]
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 [Go to Page]
5.4.1 Finite Elements
5.4.2 Geospatial Analysis
5.4.3 Artificial Intelligence
5.5 Asset Resilience—The Role of Simulation [Go to Page]
5.5.1 Multihazard Asset Simulation
5.5.2 Multihazard System Performance Simulation
5.5.3 Case Studies [Go to Page]
5.5.3.1 Case Study 1—Resilience of Bridges in North Mississippi. 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 [Go to Page]
Chapter 6: Resilience Management [Go to Page]
6.1 Introduction [Go to Page]
6.1.1 Definitions [Go to Page]
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 [Go to Page]
6.2.1 Overview
6.2.2 Resilience Metrics
6.2.3 Popular Objective Methods [Go to Page]
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 et al. (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 [Go to Page]
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 [Go to Page]
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,
6.2.9.4 Public Indifference Game and Its Solution Methods. The game of public indifference: Investigating resilience (or risk) issues that relate to assets and communities will invariably involve the public as one of the players. The term “public
6.2.10 The Ostrich Paradox [Go to Page]
6.2.10.1 Overview. A study by the Multihazard Mitigation Council (MMC 2005) showed that a savings of $4.0 is incurred for every $1.0 spent on the mitigation of/preparedness for natural hazards. However, Meyer and Kunreuther (2017) observed that
6.2.10.2 The Biases against Preparedness. Figure 6-9 illustrates the six PIBs and their subimpedances. We can summarize them as follows:
6.2.10.3 Concluding Remarks. The Ostrich Paradox promises to be the basis for many objective studies and developments in the fields of resilience, risk, and climate change. With appropriate objective modeling, including those in this chapter (Secti
6.3 Components of Resilience Management [Go to Page]
6.3.1 Overview
6.3.2 Resilience Assessment [Go to Page]
6.3.2.1 Modeling of Aging. The effects of aging of systems are often missed during assessments. Note that aging will affect all of the 4Rs because each of the 4Rs includes, to a different degree, physical components that are susceptible to aging a
6.3.2.2 Assessing Unintended Consequences. One of the most desired goals of adequate resilience management is to try to avoid unintended consequences. Some of the concerns that can produce unintended consequences are the following: ignoring interac
6.3.2.3 Assessing Civil Infrastructure as the Center of a Global Network of Risks. Section 1.2.1 argued that successful considerations of objective resilience need to account for the nature of network of its controlling variables. Network considera
6.3.2.4 Preparedness: An Ostrich Objective Viewpoint
6.3.3 Resilience Acceptance [Go to Page]
6.3.3.1 Subjective Acceptance: Resilience Itself. Subjective acceptance thresholds will use descriptive expressions such as {High} or {Medium}. Equation (6-17) is then applied using one of two possible scenarios, depending on the assessment me
6.3.3.2 Objective Acceptance. Objective acceptance still uses Equation (6-17) for the acceptance processes. In this case, both sides of the inequality are objective. There are several possibilities in applying the inequality, and these are as fol
6.3.3.3 Resilience Acceptance: A Closer Look. The just-discussed methods for setting an acceptance threshold have one thing in common: the process of setting the thresholds themselves is rather arbitrary. This is true for both subjective and object
6.3.3.4 Two Lemmas of Resilience Acceptance. Discussions of Sections 3.3.1 and 3.3.3 lead us to the following two essential lemmas of resilience acceptance:
6.3.3.5 Case Study: Asset Acceptance Thresholds
6.3.3.6 Case Study: Community Acceptance Thresholds
6.3.4 Resilience Improvement/Treatment [Go to Page]
6.3.4.1 Many Dimensions of Treatment/Mitigation. Because there are several dimensions of resilience, as discussed in Section 1.4, it is reasonable to expect that resilience treatment/improvements will also possess several dimensions. We note that
6.3.5 Resilience Monitoring [Go to Page]
6.3.5.1 Overview. As in every aspect of life, the resilience of assets and communities degrades with the passage of time. This degradation affects all the 4Rs; see Section 3.1. For example, the physical deterioration of facilities is well documented
6.3.5.2 Case Study: Resilience Monitoring of Bridge Subjected to Scour
6.3.5.3 Case Study: Resilience Monitoring of Bridge Subjected to scour as a function of Time
6.3.6 Resilience Communication [Go to Page]
6.3.6.1 Avoiding Ostrich Paradox Preparedness Impedance Biases
6.4 �Resilience and Its Multidisciplinary Underpinnings [Go to Page]
6.4.1 Overview
6.4.2 Objective Multidisciplinary Effectiveness
6.4.3 Emergency Management is a Multidisciplinary Effort
6.5 The Multifaceted Multihazard Considerations [Go to Page]
6.5.1 Overview
6.5.2 Objective Evaluations of Multihazard Effects
6.5.3 Multihazard Effects Using Graph Networks [Go to Page]
6.5.3.1 Overview. Given a GN operations model for a given organization, we can define some multihazard interaction properties as follows:
6.5.3.2 Example: Operational Multihazard Considerations in an Rapid Transit Systems. As an example, we develop an operational GN for an RTS that is based on the operational RTS description given by Hughes (2022). The GN nodes and their descriptio
6.6 The Cascading Events [Go to Page]
6.6.1 In-Parallel versus In-Series Considerations
6.6.2 The Three Modes of Cascading Events [Go to Page]
6.6.2.1 Cascading Hazards. A cascading hazard event occurs when a particular hazard would affect the whole system in such a manner that another totally different hazard occurs. The second hazard will damage the system further. The threat of addition
6.6.2.2 Cascading Effects. Cascading effects occur when a hazard impacts a particular system and degrades its properties. Then for a completely unrelated reason, another hazard occurs, and then both hazards combine to create major damage that would
6.6.2.3 Cascading Failures. Cascading failures of an infrastructure, or a system of infrastructure, usually involve a single hazard, usually referred to as an initiating event. In such a case, the initiating event would cause a local failure in the
6.6.3 Modeling of Cascading Events
6.6.4 Closing Remarks
6.7 Preparedness [Go to Page]
6.7.1 Overview
6.7.2 �Using Resilience Management Components to Address Preparedness Biases
6.7.3 Utilizing Risk Management to Promote Preparedness [Go to Page]
6.7.3.1 Behavioral Risk Auditing. We explored back in Section 6.2.7 the Ostrich Paradox, see Meyer and Kunreuther (2017), which addressed the PIBs. We then offered BN models that aimed at estimating preparedness as a result of PIBs, Section 6.3
6.7.3.2 Modeling Risk Management and Behavioral Risk Auditing
6.7.4 Community Policies to Promote Preparedness [Go to Page]
6.7.4.1 Overview. The BRA approach that was developed by Meyer and Kunreuther (2017), which we reframed in a risk management model in Section 6.7.3, was meant to be applied for short-term hazards such as floods. Meyer and Kunreuther (2017) obs
6.7.4.2 Dominant Equilibrium Strategy. Assume that the payoff table for this game is as in Table 6-30 and Figure 6-37. Looking for maxima of the community administrators for each of the four public sentiments, we find them to be 80, 65, 85, and
6.7.4.3 Nash’s Equilibrium Mixed Strategy. Let us assume that after readjusting its preparedness promotional efforts, the community administrators researched and obtained new payoff values as in Table 6-31 and Figure 6-38. Looking for maxim
6.7.4.4 Concluding Remarks. The examples in Sections 6.3.6.1.2, 6.3.6.1.3, 6.7.4.2, and 6.7.4.3 address public sentiment and how to mix the strategies (policies in Decision Theory terminology) so as to optimize it. There were no considerati
6.7.5 �Combining Ostrich Paradox, Lundgren and McMakin Constraints Model, and Laswell Communication Models [Go to Page]
6.7.5.1 The Model. A GN with directed links that simulate Laswell communication flow is shown in Figure 6-39. The links among the nodes in the model will have impedances (weights) that will represent the strength of the constraints of the LMCM. To
6.8 Return on Investment [Go to Page]
6.8.1 Returns on Investment for Assessment Projects
6.8.2 Return on Investments for Resilience Acceptance Projects
6.8.3 Return on Investments for Resilience Improvement Projects
6.8.4 Return on Investments for Resilience Monitoring Projects
6.9 Summary and Conclusions
6.10 Recommended Practices
Notations
References
Book_5107_IDX [Go to Page]

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