Resilience Assessment Framework Research Articles

TSoSRA: A task-oriented resilience assessment framework for system-of-systems

System-of-systems (SoS) are inevitably subject to disturbances during task execution, and resilience is a key factor for SoS damage and recovery. System-of-systems resilience (SoSR) assessment holds significant value in optimizing SoS architecture and completing tasks. However, identifying the most resilient SoS among different ones for the same task is a basic but challenging question. This paper proposes a task-oriented SoSR assessment framework (TSoSRA) to identify the most resilient SoS. First, we use a heterogeneous information network and meta-path to describe a SoS network architecture composed of different subsystems and the SoS performance model is developed, based on node and link quality. Based on this model, a system-of-system resilience metric (SoSRM) is proposed to describe the ability of the SoS to recover quickly dealing with disruption. Then, we extend further this metric to consider the impact of mitigation measures that exist in practical scenarios. Finally, we demonstrate the feasibility and effectiveness of TSoSRA through a case study, offering valuable insights to enhance network security, improve SoS reliability and design a more resilient SoS.

A probabilistic framework to evaluate seismic resilience of substations based on three-stage uncertainty

Electrical substation systems exhibit vulnerability after an earthquake. It results in significant economic losses because of the uncertainty of the functional state and recovery process. To quantitatively assess the uncertainty of substations, this paper proposes a probability-based seismic resilience assessment framework. This framework considers uncertainty in three stages: functional state, functional recovery, and resource constraints. Based on the functional characteristics of substation systems, a directed acyclic graph was constructed, and the Monte Carlo algorithm was used to obtain the functional state matrix, thereby establishing a probability-based functional state model. Moreover, a dynamic post-earthquake functional recovery analysis framework was built based on recovery efficiency metrics, and functional recovery paths were obtained through iterative simulations. A stepped functional recovery curve was developed based on resource constraints. Three-stage uncertainty parameters were transformed into resilience features for quantitative assessment. By analysing seismic resilience of a typical 220 kV step-down substation, probability distributions of functional recovery curves and confidence intervals for seismic resilience metrics were obtained. Notably, mutual constraint relationships among resource conditions were identified.

A novel framework for urban flood resilience assessment at the urban agglomeration scale

With global climate change and continuous urbanization exacerbating floods, urban flood resilience (UFR) has become a key to cope with floods. However, few studies target frameworks of UFR assessment at the urban agglomeration scale over a longer time span. This study, taking the Yangtze River Delta urban agglomeration as a case study, developed an evaluation framework to detail the building of a final evaluation index system of UFR, to analyze UFR's driving factors and spatiotemporal features based on the SSA-PP-KL-TOPSIS (projection pursuit based on sparrow search algorithm-Kullback-Leibler-technique for order of preference by similarity to ideal solution) model. From the perspectives of comparing numerical values and spatial distribution results, the evaluation indicators and method proposed in this article perform better. The case results showed that UFR displayed an overall growth trend and significant spatial heterogeneities. The economic, social, and infrastructure resilience showed a similar growth trend, while the environmental resilience demonstrated a decreasing trend. Environmental resilience has become a weak link in improving resilience. Higher resilience levels were concentrated in the central metropolis, provincial capitals, and industrial cities. The findings could be of use to researchers and practitioners, and the framework presented would be of reference to other flood-stricken areas.

A coupled PSR-based framework for holistic modeling and flood resilience assessment: A case study of the 2022 flood events in five southern provinces of China

In the context of global climate change, the increasing frequency of extreme weather events has led to increasingly severe disaster situations. Traditional disaster management approaches are inadequate for addressing these challenges; thus, the concept of resilience has gradually been integrated into disaster management strategies. This study addresses this gap by developing a semi-quantitative evaluation framework for flood resilience on a large, regional scale. This framework combines the Pressure-State-Response (PSR) model with a dynamic representation of flood resilience processes, incorporating pre-disaster resistance, during-disaster absorption, and post-disaster recovery. A comprehensive regional flood resilience index system (RFRI) is constructed to provide a holistic assessment of flood resilience throughout the disaster cycle. This study quantified flood resilience and utilized Geographic Information System spatial analysis to evaluate the spatial patterns of flood resilience at the municipal level. The evaluation framework was applied to a real flood disaster that affected five southern provinces of China in 2022. The results indicate that: (1) The overall flood resilience levels in the five southern provinces were relatively low, with only 6% of the units having a Flood Resilience Index (FRI) exceeding 0.6; and (2) in terms of pre-disaster resistance, 74% of municipalities in the five southern provinces of China exhibited a moderate or higher level of resilience. However, the overall performance of these provinces is relatively poor in terms of absorption during disasters and post-disaster recovery; (3) The development of flood resilience systems in the five provinces was severely imbalanced, with only two municipal-level cities having an FRI above 0.8, both of which are located in Guangdong Province. The evaluation framework established in this study enables rapid and accurate quantitative assessment of flood resilience at the municipal level. It aids in identifying deficiencies in the flood resilience systems of various regions, thereby strengthening efforts to build flood resilience.

Dynamic evolution of urban resilience and its coupling mechanism with EF3D-driven natural capital utilization: Case study in three typical urban agglomerations of China

Improving urban resilience (UR) and natural capital utilization are critical for supporting regional sustainable development. However, most of the previous studies have separately assessed them, and their coupling mechanism is still unclear. This study develops a cloud model-based urban resilience (UR) assessment framework to explore the dynamic evolution of UR in the three typical urban agglomerations of the Yangtze River Economic Belt (YREB). Natural capital utilization is analyzed by an improved ecological footprint (EF3D) model. Coupling Coordination Degree (CCD) and Environmental Kuznets Theory (EKC) are integrated for revealing the relationship between UR and natural capital utilization. Results show that UR in the YREB shows an increasing trend with an average annual rate of 1.33%, and there is a significant difference in the sub-dimensions of UR. Water system resilience generally has a positive impact on UR in the early periods, but its impact later becomes negative, with over 45% of all cities' UR being negatively affected by water system resilience. The spatial distribution of EF3D shows a decentralized trend in the YREB. The consumption of resource stocks represented by ecological footprint depth increases during the period from 2000 to 2015, with increase rates of 1.09%, 4.73%, and 3.42% for the upstream, midstream, and downstream urban agglomerations, respectively. The CCD between UR and natural capital utilization increases from an intermediate coordination stage to a well-coordinated stage. The EKC analysis discloses that UR and natural capital utilization present inverted U-shaped curves in three urban agglomerations with spatial differences. The inflection point of UR in the upstream is earlier (in 2008) than that in the midstream (in 2014) and downstream (in 2015) urban agglomerations. Findings can help quantify the development space for each city to enter into coordinated development in the future.

Analysis of multi-modal public transportation system performance under metro disruptions: A dynamic resilience assessment framework

The well-functioning multi-modal public transportation systems play crucial roles in reducing traffic congestion, alleviating environmental pollution, and improving mobility. There are variants of disruptions that may impede the smooth functioning of public transportation systems and challenge their normal operations. It is essential to develop resilient multi-modal public transportation systems, and a reasonable resilience assessment framework serves as the foundation for developing such systems. In this paper, we propose a resilience assessment framework based on performance-based measurement metrics. We develop a dynamic simulation procedure that considers the impacts of disruptions on passenger choices of path and departure time. By incorporating these features into the simulation procedure, we can effectively model the variations of passenger flow under disruptions. Finally, to demonstrate the proposed resilience assessment framework and dynamic simulation procedure, the multi-modal public transportation system in Beijing is considered as a case study. The results reveal that the system exhibits good resistance and recovery capabilities, but it lacks robustness. Additionally, we discuss the effects of downtime, bus frequency, bus bridging services, and proportions of commuters on resilience, which lead to several valuable policy implications.

Visualising the Complexity of Drought: A Network Analysis Based on the Water Resilience Assessment Framework and the Actor-Relational Approach

Visualising the Complexity of Drought: A Network Analysis Based on the Water Resilience Assessment Framework and the Actor-Relational Approach

Impact of the Russia–Ukraine Conflict on Global Marine Network Based on Massive Vessel Trajectories

Maritime transportation plays a vital role in global trade, and studying the resilience of the global maritime network is crucial for ensuring its sustainable development. Currently, the ongoing conflict between Russia and Ukraine has garnered significant global attention. However, there is a lack of specific research on the impact of the conflict on maritime shipping, particularly the resilience of the global maritime network. This paper proposes a resilience assessment framework under the influence of significant events by combining complex network metrics and network performance indicators from the resilience triangle model. It quantitatively evaluates the resilience changes in the global maritime network before and after the outbreak of the Russia–Ukraine conflict. The experiment utilizes real automatic identification system (AIS) maritime trajectory data to quantify and visualize the changes in global maritime traffic during a 20-day period before and after the conflict, constructing the global maritime network for resilience calculations. The research findings indicate the following changes occurred after the Russia–Ukraine conflict. Firstly, the global maritime industry experienced overall growth, with increased ship transportation between ports. Transportation in certain regions was negatively affected, with a significant decrease in ship activities in the Black Sea and Adriatic Sea areas. The positions of Russia and Ukraine in the world maritime industry noticeably declined. Secondly, the network connectivity, network size, and network density of the global maritime network significantly increased, indicating an enhanced network resilience. According to our quantitative results, from a topological perspective, we observed the following changes: network connectivity increased by 27.2%, network scale increased by 36.6%, network density increased by 32.4%, and network resilience increased by 18.6%. Thirdly, the global maritime network is characterized by a high degree of heterogeneity, and the impact of conflicts on the heterogeneity of the shipping network is not significant. Finally, the network exhibited a slower performance decline under random attacks, while deliberate attacks led to a sharp decline. Due to the adaptive nature of the maritime network, the resilience of the network improves in terms of its topology following the outbreak of conflicts. After conflict incidents, the rate of performance decline during simulated attacks is lower compared to the pre-conflict period.

Heat stress resilience assessment of urban form from physical space dimension: A case study of Guangdong-Hong Kong-Macao Greater Bay Area

Improving urban resilience is crucial to counteract rising high-temperature disasters. This study constructed a framework for a process-based heat stress resilience (HSR_phy) assessment from the urban physical space dimension. Based on the universal thermal climate index (UTCI), the Weather Research and Forecasting (WRF) model, and the Local Climate Zone (LCZ) map generated through WUDAPT, an HSR_phy evaluation method with high spatiotemporal accuracy is proposed. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was studied for heat stress resilience patterns in July 2021. Boosted regression tree (BRT) models analyzed LCZ landscape patterns' impacts on HSR_phy. The results indicated that HSR_phy during the daytime was significantly lower than that at night. The HSR_phy of GBA showed the characteristics of low inland and high periphery. Significant differences in HSR_phy existed among most LCZs. LCZA, LCZC, and LCZ9 showed strong HSR_phy, whereas LCZ2, LCZ8, and LCZ7 were opposite. At the 1500 m scale, the Percentage of Landscape (PLAND), Landscape Shape Index (LSI), and Shannon's Diversity Index (SHDI) of LCZ4, LCZ5, and LCZ6 were the key factors affecting HSR_phy. Our research demonstrates how to quantify heat stress resilience and impact factors of urban physical spaces to provide a basis for developing climate-sensitive urban design strategies.

Enhancing infrastructural dynamic responses to critical residents’ needs for urban resilience through machine learning and hypernetwork analysis

The increasing frequency of extreme weather events poses ever greater challenges to urban resilience and residents’ quality of life. Despite a growing trend advocating for an anthropocentric approach to urban resilience, there remains an inadequate understanding of the evolving hierarchical needs of residents during post-disaster periods, especially considering the interplay with infrastructure service restoration. This study aims to address the gap by elucidating how emergency governance and urban infrastructure repairs can effectively address critical residents’ needs, providing empirical insights for improved resource allocation in infrastructure rush-repair scenarios. First, we categorize residents’ needs into three layers (safety and health, social livelihood and civic engagement) using Latent Dirichlet Allocation topic modeling. Subsequently, we present an urban resilience assessment framework that traces the recovery of residents’ needs alongside dynamic infrastructural functionality restoration, benchmarking against pre-disaster levels. Additionally, hypernetwork analyses are adopted to identify critical and evolving patterns of residents’ post-disaster needs over time. The robustness of our proposed framework is validated through its application to a dataset comprising 220,567 records from residents’ appeals during three recurrent rainfall events in Beijing. Theoretically, this study models the dynamic interactions between residents’ needs and infrastructure response during urban post-disaster recovery. Practically, the pinpointed critical needs guide efficient infrastructure rush-repairs and proactive disaster prevention in infrastructure maintenance.

Measuring community resilience inequality to inland flooding using location aware big data

Understanding community resilience is critical for effective resource allocation and planning. However, classical resilience measures often fall short in capturing the diverse characteristics of each stage: preparation, resistance, recovery, and adaptability. We propose a multi-stage resilience assessment framework integrating morphological indicators to measure community resilience. Applying this framework to evaluate disparities in community resilience after the inland flooding in Changsha, we find that morphological indicators provide a more accurate description of resilience priority and ability compared to speed indicators. The analysis reveals stronger complementarity and lower redundancy among resilience indicators. Moreover, we establish a strong connection between resilience, driving factors, and government actions. Neighborhoods with high flood risk and socioeconomic status encounter the severest impact and highest recovery priority, leading to substantial government engineering measures. Conversely, vulnerable communities facing high flood risk and low socioeconomic status display the lowest resistance and recovery ability, emphasizing the necessity for tailored initiatives like increasing green infrastructure and constructing flood buffer zones. Additionally, low river flood risk communities with high socioeconomic status experience minimal flood impact, underscoring the significance of prioritizing low-lying regions susceptible to surface water flooding. The study informs government decision-making, emphasizing differentiated strategies for enhancing community resilience across regions and stages.

Fragility Analysis and Resilience Assessment of the Single-Column Pier Steel-Concrete Composite Bridge Subjected to Seismic Loads

Abstract With the advantages of a small footprint, wide under-bridge view, and beautiful appearance, single-column pier bridges are widely used in urban bridge networks. However, single-column pier bridges are prone to damage during earthquakes or heavy vehicle use, which can seriously affect normal operations and postdisaster recoveries. Therefore, there is an urgent need to carry out seismic resilience assessments of single-column pier bridges and formulate disaster prevention and mitigation measures from the aspects of design, maintenance, and postearthquake recovery. This paper first establishes a resilience assessment framework for the single-column pier bridge and optimizes a functionality recovery model after an earthquake. Then, a numerical model of a sample bridge is built for resilience fragility analysis. Nonlinear dynamic time history analysis is performed to build a probabilistic seismic demand model, and moment–curvature analysis is performed to build a probabilistic seismic capacity model. Finally, a seismic resilience assessment of the single-column pier bridge is obtained based on the seismic fragility, and a sensitivity analysis is carried out for the pier height, pier section dimension, span and vehicle load level to improve the resilience of the single-column pier bridge.

Urban resilience assessment from the perspective of cross-media carbon metabolism

With the accelerating pace of globalization, uncertainty and unknown risks within open and complex urban systems increase with the occurrence of problems such as the conflict between humans and natural land use, water scarcity, and the continuing loss of biodiversity. Thus, the improvement of urban resilience has emerged as an important issue in the context of global urbanization. However, a knowledge gap remains in its evaluation from the perspective of systematic resource/element metabolic processes. To understand the urban resilience response mechanism better and depict metabolic processes systematically, an urban resilience assessment framework of “robustness-adaptability-restorability-coordination” based on the cross-media carbon metabolism network model was established. Principles of material flow analysis and ecological network analysis were applied to examine the urban resilience of Guangzhou, China, from 2010 to 2020. Results showed the urban resilience level decreased from a carbon metabolism perspective during the study period. This was reflected in an overall decline in system robustness and restorability, relatively unchanged adaptability, and a non-beneficial coordination relationship. Recommendations such as regulating key sectors (e.g., agriculture and construction) were proposed to improve urban resilience. This research will bring a new insight into future urban resilience assessment and contribute the urban sustainable development.

Multi-Indicator Fused Resilience Assessment of Power Grids Considering Wind-Photovoltaic Output Uncertainty during Typhoon Disasters

Extreme weather events such as typhoons pose a serious threat to the safe operation of power grids. In the field of power system resilience assessment during typhoon disasters, a parametric typhoon wind field model combined with actual historical meteorological data has not been well adopted, and the conventional renewable energy uncertainty modeling methods are not suitable for typhoon disaster periods. In this paper, a multi-indicator fused resilience assessment strategy considering wind-photovoltaic uncertainty and component failure during typhoon disasters is proposed. Firstly, based on the actual historical meteorological data of typhoons, an uncertainty model of typhoon wind speed is established by a rolling non-parametric Dirichlet process Gaussian mixture model. Then, a spatial–temporal contingency set is constructed by considering the best-fit wind field model and stress–strength interference model for failure probability of transmission lines. On this basis, a holistic resilience assessment framework is established from the perspectives of priority, robustness, rapidity, and sustainability, and the entropy weight method combined with the technology for order preference by similarity to an ideal solution is leveraged to obtain the comprehensive resilience indicator. Finally, numerical studies are performed on the IEEE-30 bus test system to identify vulnerable lines and improve system resilience during typhoon disasters.

The safety climate, hierarchical levels and resilience assessment in transport and mining companies

ABSTRACT Transport and mining companies are vulnerable to a variety of hazards, and this paper offers a novel conceptual framework for organisational resilience assessment at different organisational levels. It is based on a safety climate and performances assessment in companies in the transport and mining sector. The framework contains factor and reliability analysis and continues by applying the SMART method from the perspective of resilience corners: anticipate, monitor, react and learn. The highest resilience coefficients at all organisational levels are obtained regarding safety awareness, safety training and safety communication areas, while the lowest values are observed for risk assessment and the organisational environment. The obtained results indicate that the ‘monitor’ resilience corner must be improved at all organisational levels, employees trained and procedures changed, since employees do not sufficiently use experience from previous events. The very high values at all organisational levels of the coefficients regarding the ‘anticipate’ and ‘learn’ resilience corners indicate organisational adaptation to changes through corrective activities, rather than planned preventive ones. All hierarchical levels have good resilience indicators, except for middle management, which expressed an adequate resilience index, due to the lower ratings of the safety training, organisational commitment, risk assessment and management support areas.

Leverage rule-based Bayesian network on assessing straits/canals resilience performance on a risk coupling analysis perspective

ABSTRACT The maritime transportation system is comprised of several crucial nodes, including straits and canals, which are becoming increasingly susceptible to external emergencies and disturbances. The intricate interactive relationships and non-linear influences among the risk factors pose significant challenges in assessing the resilience performance of these straits and canals. To address these challenges, a four-stage resilience assessment framework was developed to analyze the resilience performance of the straits and canals under uncertain risk coupling scenarios. The framework leverages the advantages of fuzzy logic and Bayesian network, enabling the construction of conditional probability tables and reducing expert judgement inconsistencies. The findings indicate that the Strait of Malacca exhibits higher resilience performance under multi-dimensional risk coupling scenarios. This framework has significant potential in providing valuable insights for risk and resilience management and can be extended to similar industries.

Probabilistic seismic hazard assessment framework for Uganda: a stochastic event-based modelling approach

Uganda lies between the eastern and western arms of the East African Rift System, the largest seismically active rift above sea level. With increasing population, urbanisation and rapid construction, seismic risk in the country is escalating fast and is compounded by the high vulnerability of the building stock and inadequate disaster prevention and mitigation strategies. Hence, there is an urgent need to assess Uganda’s resilience against seismic risks. This paper presents a Monte-Carlo based probabilistic seismic hazard model for Uganda, as the first step towards the development of a seismic risk and resilience assessment framework for the country. In addition to fault segment data, earthquake catalogues are compiled for the period between 1900 and 2022 to estimate recurrence parameters for source zones in the area of interest. Area source zones incorporating focal mechanisms are used to stochastically model a national hazard framework for Uganda. A logic tree approach is applied to implement four ground motion prediction equations for both stable continental and active shallow crust geologies. Mean hazard curves, uniform hazard spectra, earthquake disaggregation and spectral pseudo-accelerations for major Ugandan cities are derived in addition to hazard maps for the country. The findings are largely consistent with previous regional studies and confirm that western Uganda is exposed to the highest level of seismicity. The model presented herein can be used to kick-start the update and continuous improvement of Uganda Seismic Design Code and the National Policy for Disaster Preparedness and Management.

Ecological network resilience evaluation and ecological strategic space identification based on complex network theory: A case study of Nanjing city

Constructing a resilient ecological network (EN) and identifying critical strategic nodes and corridors within the EN, stands as a pivotal approach toward achieving a harmonious equilibrium between regional development and ecological conservation. It is imperative to expand the perspective to encompass the holistic resilience of the EN, thus identifying and safeguarding ecologically strategic nodes and corridors that play pivotal roles throughout the entire network. Therefore, this study takes Nanjing City as a case study and establishes a comprehensive EN resilience assessment framework based on resilience theory and complex network theory, grounded in a foundation of multidimensional indicators. Building upon this, the research develops the ‘regional network simulation - ecological spatial analysis - strategic spatial identification’ investigative framework. The results show that a core EN structure centered around green spaces, rivers, lakes, and similar features has taken shape, encompassing a total of 39 ecological nodes and 69 ecological corridors. Examining from six perspectives, connectivity, integration, complexity, centrality, efficiency, and substitutability, and their integrated assessment, this study analyzed the impact of single and sequential failures in different EN component spaces on the overall resilience of the EN. The study aimed to identify the component space that significantly contributes to the network's resilience. As a result, the strategic space of the EN was divided into three levels. The ecological source areas 1, 2, 7, and 34, along with ecological corridors 1–34, 1–4, 4–11, 19–34, 18–19, and 27–39, emerge as the primary strategic spaces within the study region. Previous research primarily emphasized the individual characteristics of ecological spaces. However, this study adopts a systemic perspective rooted in resilience theory and complex network theory to meticulously explore the pivotal impact of specific ecological spaces on the overall resilience of the ecological system network. Moreover, it amalgamates considerations of both the significance and scale of ecological spaces, conducting a comprehensive assessment of their combined influence on the overall EN resilience. This approach not only aids in identifying and preserving strategic ecological nodes and corridors but also contributes to evaluating, planning, and restoring regional EN resilience. This progression plays a crucial role in establishing an equilibrium between regional advancement and ecological conservation.

Seismic Resilience Evolution of Shield Tunnel with Structure Degradation

The structural performance of shield tunnel structures is highly susceptible to degradation under complex environmental loads, with the most common manifestation being bolt preload loss. In this study, a shield tunnel numerical simulation model was established to analyze the seismic response of shield tunnels with varying degrees of bolt preload loss. Firstly, the deformation patterns of shield tunnel structures under seismic loads were analyzed. Subsequently, ellipticity and joint opening were selected as seismic resilience assessment indicators based on the mechanical response. A seismic resilience assessment model was then established, including three states: normal state, affected state, and recovered state. The results show a direct relationship between the recovery capacity of tunnel structures and the initial performance of the lining structure, as well as the magnitude of the load. The lower the degree of structure degradation, the greater the structural recovery capacity. Additionally, there is a positive correlation between residual deformation and the initial performance loss of shield tunnel structures, as well as the intensity of seismic loads. This study contributes to enriching the theoretical framework for the seismic resilience assessment of shield tunnels, which have significant implications and provide valuable references for engineering safety.

Assessing fire resilience of historic districts: An approach combining space structure and tourists’ behavior

The fire risk of historical districts is a huge challenge faced by all countries in the world when protecting historical and cultural heritage. As the historic districts are transformed into commercial districts nowadays, increasing tourists and businessmen start to visit and move into these districts, it is more urgent to deal with the fire risks with the growing demand of fire and electricity. Accurate assessment of the fire resilience and targeted implementation of resilience improvement actions are considered to be an effective way to solve this problem. However, the existing research has not fully considered the complex effects of space structure, tourists' behavior and the interaction between them on fire resilience. Therefore, this study constructed a fire resilience assessment framework combining space structure and tourists' behavior, and considering the spatial-behavior interaction. The results revealed that the space structure of commercial historical districts and the behavior of tourists show different characteristics and regulars in our study area, such as the categories of shops using open fires, the location of open fires and the periodicity of tourists ' behavior over time. By taking an experimental verification in Ciqikou Historic district, Chongqing, China, this assessment framework showed a flexible scale of application with strong operability and versatility, which also evidenced that space structure and tourists’ behavior must be taken into account simultaneously to improve the fire resilience of historical districts. At last, we proposed targeted strategies to improve the fire resilience from the aspects of space structure and tourists' behavior, respectively.