| S.No. | Paper Name | Summary | Key topics | Relevence (out of 10) | Look again, if yes, when? |
| 1 | Resilience-based network component importance measures | Important metric to evaluate recovery, time component, Two measures defined for a network based resilience - adverse impact and positive impact, algorithm to perform stochastic ordering of network, time component included | Network resilience
Component importance measure
Vulnerability
Recoverability | 8 | Metric definition |
| 2 | Reliability evaluation of linear multi-state consecutively-connected systems constrained by m consecutive and n total gaps | Extends the linear multi-state consecutively-connected system, can we used for fluid transportation systems, wireless communication systems, sensor systems and logistics systems. | Linear multi-state consecutive-connected
system
Multi-state connection elements
Non-uniform deployment
Universal generating function
Two different types of failures
Genetic algorithm | 5 | Only if network modeling is required, and the evaluation is based on distance between the nodes. |
| 3 | An approach to design interface topologies across interdependent urban infrastructure systems | Approach to design or retrofit interface topologies to minimize cascading failures across urban infrastructure systems. Four types of interface design strategies are formulated based on maximum network component degree, maximum component betweenness, minimum
Euclidean distance across components and component reliability rankings. To compute and compare strategy effectiveness under multiple hazard types, this paper introduces a global annual cascading failure effect (GACFE) metric as well as a GACFE-based cost improvement (GACI) metric. | Interface topologies
Interdependent lifeline systems
Design strategies
Cascading failure effect
Random hazards
Hurricane hazards
Complex networks | 7 | When working on the cascading effect and modeling piece |
| 4 | Optimal probabilistic planning of passive harmonic filters in distribution networks with high penetration of photovoltaic generation | Approach based on Genetic Algorithm (GA) and Monte-Carlo Simulation (MCS) for the optimal planning of single-tuned passbe harmonic filter (PHFs) in a distribution network. The objective function minimizes the installation cost and energy losses. |
Harmonic mitigation
High photovoltaic penetration
Passive harmonic filter
Probabilistic planning | 4 | Can be looked only for methodology for minimizing the objective function |
| 5 | Stochastic measures of resilience and their application to container terminals | Modeling paradigm for quantifying system resilience, primarily as a function of vulnerability and recoverability. To account for uncertainty, stochastic measures of resilience are introduced, including Time to Total System
Restoration, Time to Full System Service Resilience, and Time to alpha%-resilience. | Resilience
Infrastructure systems
Vulnerability
Recoverability | 8 | Metric definition |
| 6 | Resilience improvement planning of power-water distribution systems with multiple microgrids against hurricanes using clean strategies | Stochastic programming aims to minimize the investment cost of resilience improvement strategies and the expected inaccessibility values of loads to power and water under hurricanes. | Microgrids
Resilience improvement planning
Stochastic linear programming
Power network
Water network | 3 | Look for uncertanity parameters |
| 7 | Framework for analytical quantification of disaster resilience | The recovery process usually depends on available technical and human resources, societal preparedness, public policies and may take different forms, which can be estimated using simplified recovery functions or using more complex organizational and socio-political models. | Disaster resilience
Fragility
Functionality
Hospital
Losses
Recovery
Resilience | 7 | Dimension of resilience, loss function for disaster based scenarios |
| 8 | Multi-dimensional hurricane resilience assessment of electric power systems | The paper introduces a probabilistic modeling
approach for quantifying the hurricane resilience of contemporary electric power systems. This approach
includes a hurricane hazard model, component fragility models, a power system performance model, and
a system restoration model. These coupled four models enable quantifying hurricane resilience and
estimating economic losses. | Electric power systems
Resilience
Hurricane hazards
Component fragility
Robustness
Restoration
Networks
Probabilistic Resilience Model | 7 | Resilience assessment |
| 9 | Economic resilience to transportation failure: a computable general equilibrium analysis | This study develops and applies a multimodal computable general equilibrium
(CGE) framework to investigate the role of resilience in the economic consequences of
transportation system failures. Vulnerability and economic resilience of different modes of
transportation infrastructure, including air, road, rail, water and local transit, are assessed
using a CGE model that incorporates various resilience tactics including modal substitution, trip conservation, excess capacity, relocation/rerouting, and service recapture. The
linkages between accessibility, vulnerability, and resilience are analyzed. | Transportation
System failure
Economic resilience
Accessibility
Computable general equilibrium (CGE) modeling Hurricane Katrina | 8 | Economic modeling |
| 10 | Optimizing power system investments and resilience against attacks | The planner–attacker–defender model is adopted to develop decisions that minimize investment and operating costs, and functionality loss after attacks. The mixed-integer optimization is solved by decomposition via two-layer cutting plane algorithm. | Electric power network protection
System resilience
Transmission switching
Attacks
Trilevel optimization | 6 | optimal investment planning |
| 11 | Analyzing driving forces behind changes in energy vulnerability of Spanish electricity generation through a Divisia index-based method | Following logarithmic mean Divisia indexes approach, a new method that enables a complete decomposition of changes in electricity vulnerability into contributions from several drivers | Electricity generation
Energy fossil-fuel dependence
Vulnerability
Decomposition analysis
Spain
Divisia index | 7 | electricity decomposition methods, and time series normalization |
| 12 | Impacts and implications of climatic extremes for resilience planning of transportation energy: A case study of New York city | Featuring a multi-stage mathematical program to simulate the dependency of travel behavior on fuel availability when the infrastructure of transportation energy is stressed or under attack. | Climate change
Transportation energy
Critical infrastructure
Fuel supply chain
Resilience
Adaptation-mitigation nexus | 5 | Effect of climate |
| 13 | A holistic framework for building critical infrastructure resilience | This research describes a practical and holistic resilience framework for improving the resilience of CIs taking into account the external agents. The framework is composed of three elements: a set of resilience policies; an influence table that assesses the influence of policies on prevention, absorption and recovery stages; and an implementation methodology that defines the temporal order in which the
policies should be implemented. | Crisis management
Critical Infrastructures
Resilience
Resilience policies
Delphi process
Case studies | 8 | Resilience policy relations |
| 14 | Availability-based engineering resilience metric and its corresponding evaluation methodology | This study proposes a new availability-based engineering resilience metric from the perspective of reliability engineering. Dynamic-Bayesian-network-based evaluation methodology is developed on the basis of the proposed resilience metric. | Resilience
Availability
Metric
Engineering system | 7 | Resilience metric |
| 15 | Embodied energy use in China’s industrial sectors | - A hybrid IO-LCA model was employed to analyze China’s energy use at sectoral level.
- A case study on China’s sectoral energy consumption is done.
- Construction and service sectors are actually energy intensive from the supply chain perspectives.
- Upstream and downstream ectoral collaboration along the whole supply chain is necessary.
- Energy conservation policies should be based upon a comprehensive analysis on sectoral energy use. | Energy consumption
EIO model
Production and consumption | 9 | Almost similar first half of the research done. |
| 16 | Resilience of Energy Infrastructure and Services: Modeling, Data Analytics, and Metrics | The focus is on identifying fundamental
challenges and advanced approaches for quantifying resilience. In particular, the first aspect of this problem is how to model large-scale failures, recoveries, and impacts, involving the infrastructure, service providers, customers, and weather. The second aspect is how to identify generic vulnerability in the infrastructure and services through large-scale data analytics. The third aspect is to understand what resilience metrics are needed and how to develop them. | Data analytics
failure
nonstationary
spatiotemporal models
power distribution infrastructure
recovery
resilience metrics
services to customers | 8 | Metric and for lit review |
| 17 | Resilience analytics with disruption of preferences and lifecycle cost analysis for energy microgrids | | Infrastructure resilience
Scenario analysis
Robust decisions
Energy systems
Strategic planning
Systems engineering |
| 18 | Metrics for energy resilience |
| 19 | Sustainability of integrated energy systems: A performance-based resilience assessment methodology |
| 20 | Resilience of Critical Infrastructures: Review and Analysis of Current Approaches |
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