Vulnerability Assessment Research Articles

Vulnerability assessment of buildings adjacent to natural gas pipelines under explosion accident

ABSTRACT Natural gas pipeline leak may lead to explosion accidents, which may threaten the safety of the adjacent buildings. This paper conducts a vulnerability assessment of buildings adjacent to natural gas pipeline under explosion, which is implemented by Copula Bayesian network (CBN) model. The incident escalations and evolution nodes were identified based on the accident reports. The correlation between nodes is calculated using the Kendall correlation coefficient to develop a CBN model of natural gas pipeline accidents. The weaknesses in the buildings adjacent to pipelines are identified using spider diagrams. The vulnerability of building adjacent to pipelines is characterized by the damage degree. The model is verified by a case study. The results indicate that the occurrence probability of the explosion accident reaches 85%. The identified weaknesses are ignition sources and confined spaces. The occurrence probability of a delayed ignition within buildings is 0.23, and the explosion overpressure is estimated to be 84.25 kPa. The vulnerability degree of building 1 is higher than building 2. These findings can help to understand the system weaknesses and support the safety improvement of buildings in the case of natural gas pipeline explosion.

Safety barriers under changing operating conditions–An analysis of impact parameters in Germany

Vehicle restraint systems and especially the impact of a collision on such are subject to various influencing variables. These systems are tested and approved through vehicle impact tests to ensure that safety standards are met as well as to ensure comparability amongst the systems. However, differences in the objectives of the standard DIN EN 1317 and the behaviour in practice have become apparent.There is the standard DIN EN 1317 which defines the impact tests on testing grounds. Nevertheless, there are a number of influencing parameters such as developments in the vehicle fleet over the last years, available safety barriers, including their construction types and the impact itself. Previous research indicates that there could be a gap between these parameters.This research uses an empirical analysis based on chiefly quantitative data sources to evaluate the differences between these parameters. It leads to a partial divergence between static requirements of the standard and the actual road traffic conditions. Additionaly, the differences are developed within a vulnerability analysis and for the purpose of comparison, the advantages as well as the disadvantages of the standardized impact tests are discussed in this paper.As a result, a parameter based suggestion for a reevaluation of impact tests for safety barriers, according to the standard DIN EN 1317, is advisable due to the changing road traffic on the current stock and new barrier systems to be built. This research strives to illuminate the trend for new investigation methods such as the finite element method (FEM) simulation. It gives an outlook to further research needs in safety barriers, principally in the observation of the future development of the impact parameters. At the same time, impulses and potential for improvement can be identified for the future documentation of vehicle impacts on these barriers.

Vulnerability indicators of seawater intrusion in offshore aquifers

This study represents the first attempt to define vulnerability indicators for offshore fresh groundwater, extending prior analyses of the key threats to onshore coastal aquifers. The method applies an existing steady-state sharp-interface coastal aquifer model with semi-confined offshore extension to characterise the sensitivities of the tip and toe locations (top and bottom of the freshwater–seawater interface, respectively) and the freshwater and seawater volumes to environmental changes that threaten offshore freshwater resources. Sensitivity analysis applied to seven case studies quantifies their vulnerability to seawater intrusion from sea level rise, recharge change and a regional change in the onshore groundwater heads. The analysis demonstrates that the tip-to-toe distance in offshore aquifers is constant for different fresh groundwater discharge rates (under certain conditions). Otherwise, the interface is usually longer (flatter slope) in offshore aquifers than in onshore aquifers, except where the offshore limit of the aquifer is reached. The offshore extension of the aquifer leads to more seaward toe positions, increases the interface length and reduces the onshore seawater volume. As the freshwater discharge increases, the offshore freshwater volume becomes more vulnerable to impacts from changes in the freshwater discharge until the tip reaches the offshore limit or the toe crosses the coastline. For high values of freshwater discharge, the volume of freshwater stored offshore is more vulnerable to losses from changes in the freshwater discharge rate than is the onshore freshwater storage. For lower values of freshwater discharge, however, offshore freshwater storage is generally less vulnerable than onshore freshwater storage. Contrasts in the behaviour of onshore and offshore freshwater require that both need to be considered in coastal aquifer vulnerability assessments.

SEISMIC VULNERABILITY ASSESSMENT OF AN HISTORICAL UNREINFORCED MASONRY BUILDING OF THE XIXTH CENTURY: EL FETH HIGH SCHOOL IN BLIDA, ALGERIA

Schools In Algeria, built in the XIXth and XXth centuries, are not only places of education and learning, but make up a rich cultural heritage of architectural techniques and traditional know-how. However, their seismic vulnerability risks the safety of their occupants. They were built of masonry before seismic regulations were put into place, which increases their sensitivity to seismic hazard. Algeria is situated in a well-known zone of high seismic activity and the risk to these buildings challenges their structural behaviour. This study focuses on an assessment of seismic vulnerability on a specimen built entirely in hollow brick which wonderfully represents this architectural heritage leading to a better understanding of the potential risks for these buildings, at a structural level. Macro element models, using the Tremuri software, are subjected to a non-linear “Pushover” analysis in order to determine the degree of vulnerability and locate the weak sections of the structure which could collapse during seismic action. This study aims to highlight the seismic risks of these types of structures and also offer appropriate guidelines and recommendations that could be of use during a possible rehabilitation or conservation program of this built heritage site.

Abstract C028: Challenging PDAC adaptability: Uncovering therapeutic vulnerabilities in APE1 DNA repair mechanisms

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a therapeutically challenging malignancy notorious for its resilience to therapeutic strategies and ability to thrive under extreme conditions. The cancer's inherent ability to adaptively resist treatments underscores the need for novel and combinatorial therapeutic approaches. Our research focuses on elucidating the role of Apurinic-apyrimidinic endonuclease/Redox effector factor 1 (APE1/Ref-1), a critical multifunctional protein in PDAC pathobiology. APE1 serves two essential functions: as the principal endonuclease in the base excision repair (BER) pathway for DNA repair and as a redox regulator of transcription factors essential for cancer cell proliferation. While the therapeutic targeting of APE1’s redox function has been effective and continues to yield significant advances, the development of treatments aimed at its DNA repair function has proven more challenging with comparatively limited progress. Since standard PDAC treatment regimens involve DNA damaging agents potentially repaired via BER and APE1, we engineered three mutant cell lines with knock-in mutations resulting in a reduction of APE1’s BER activity while maintaining full redox activity. Biochemical evaluations confirmed the effects of the mutation, revealing a 30-fold reduction in DNA repair capacity. Surprisingly, with respect to growth and proliferation, the mutant and wild-type cell lines behaved similarly. Analyses of cytotoxic vulnerabilities revealed similar findings with the mutant lines exhibiting minimal phenotypic differences in sensitivity when challenged with cytotoxic and DNA damaging agents in proliferation-based assays. These findings led us to posit that the mutant cell lines were relying on compensatory DNA repair pathways which were providing sufficient compensation for the decrease in APE1 activity. We further hypothesized that the cell lines may still have hidden, long-term deficiencies in DNA damage processing which are not apparent during the initial stress response. Subsequent colony formation assays revealed that the mutant cell lines do exhibit poor long-term survival even after only short-term exposure to DNA damage. In vivo orthotopic mouse model experiments further corroborated these findings, showing a significant reduction in tumor size and decreased metastasis to the lungs and liver in mutant cell lines compared to wild-type controls. While APE1 is the primary endonuclease in the BER pathway, studies have demonstrated APE1-independent BER in rare, specific contexts. We are probing the hypothesis that these APE1-independent BER pathways function as the compensatory mechanism safeguarding these cells in short-term stress situations. Identifying and characterizing these backup pathways will not only offer a better understanding of APE1’s DNA repair capabilities within PDAC but will also provide a better understanding of how DNA repair mechanisms can be therapeutically targeted for novel therapeutic options or combinations. This opens the path to enhance standard of care treatments such as FOLFIRINOX. Citation Format: Eyram K Kpenu, Randall Wireman, Mahmut Mijiti, Silpa Gampala, Melissa L Fishel, Mark R Kelley. Challenging PDAC adaptability: Uncovering therapeutic vulnerabilities in APE1 DNA repair mechanisms [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C028.

Analysis of Husband-Wife Interaction, Financial Vulnerability, and Objective Well-Being in Sandwich Generation Families

In sandwich-generation families, there are individuals who simultaneously support the financial needs of children and the elderly. This is a quantitative study with a cross-sectional design using an online survey as a data collection tool. The study was conducted in Indonesia with a research population including sandwich families living in one house consisting of three generations: husband and wife, children, and elderly. The research sample consisted of working wives from the sandwich generation. Of the 223 respondents who participated, 106 met the criteria for further analyses. The results show that spousal education and income play important roles in reducing financial vulnerability and improving family welfare. Harmonious interactions between husbands and wives can reduce financial vulnerability and improve family welfare. Conversely, high financial vulnerability can disrupt a family's objective welfare if not properly managed. The conclusion is the need to improve financial literacy, create a good financial management strategy, and maintain open and harmonious communication between husband and wife to reduce financial vulnerability and improve the welfare of sandwich-generation families.

The association between social vulnerability and geriatric assessment impairments among older adults with gastrointestinal cancers-The CARE Registry.

Older adults comprise the majority of patients with gastrointestinal (GI) cancer. Geriatric assessments (GAs) are recommended for older adults with cancer in part to detect aging-related impairments (e.g., frailty) associated with early mortality. Social factors like social vulnerability may also influence aging-related impairments. However, the association between social vulnerability and aging outcomes among older adults with cancer is understudied. The authors included 908 older adults aged 60 years and older who were recently diagnosed with GI cancer undergoing GA at their first prechemotherapy visit to the University of Alabama at Birmingham oncology clinic. The primary exposure of interest was the social vulnerability index (SVI). Outcomes were frailty (frail vs. robust/prefrail) and total number of GA impairments (range, 0-13). The authors examined the association between SVI and outcomes using Poisson regression with robust variance estimation and generalized estimating equations. The median age at GA was 69 years (interquartile range, 64-75 years), 58.2% of patients were male, 22.6% were non-Hispanic Black, 29.1% had colorectal cancer, 28.2% had pancreatic cancer, and 70.3% had stage III/IV disease. Adjusting for age, sex, cancer type, and disease stage, each decile increase in the SVI was associated with an 8% higher prevalence of frailty (prevalence ratio, 1.08; 95% confidence interval, 1.05-1.11) and a 4% higher average count of total GA impairments (risk ratio, 1.04; 95% confidence interval, 1.02-1.06). The results were attenuated after further adjustment for race and education. Greater social vulnerability was associated with a higher prevalence of frailty and an increasing average number of GA impairments among older adults with GI cancers before systemic treatment. Intervening on social vulnerability may be a target for improving the risk of frailty and GA impairments, but associations of race and education should be further evaluated.

Risk and vulnerability analysis of road network in landslide prone areas in Munnar region, India

Catastrophes like landslides have the potential to impair critical transportation infrastructure, particularly road networks. The hilly regions in the state of Kerala in India are particularly prone to hazards and changing climate conditions. During the monsoon season, landslides are common in the Western Ghats, and the intensity of adverse impacts is more severe due to its densely populated regions. The study area of this research is in Idukki district of Kerala, where over 60 % of the land is prone to landslides. The monsoon rains bring with them a slew of disastrous landslides in the region. Most of the roadways in the study area are often disrupted due to landslides. Landslide risk assessment (LRA) is a crucial component of research on adverse impacts of landslide. The use of Geographical information System (GIS) and Multi Criteria Decision Analysis (MCDA) using Analytical Hierarchical Process (AHP) for susceptibility mapping and hazard risk assessment assists in the identification of disaster-prone areas. The data collected by field surveys were used to confirm the study results and the high-risk zones of the region were identified and the risk maps are prepared for the region as well as for the road network in the region. The risk of landslides may be described as the possibility of negative repercussions on road network thereby adversely impacting the inhabitants of the region. The landslide risk assessment of the road network in a hilly region is carried out which gives important insights for risk management and for future planning of resilient development in the region. This study enhances the knowledge for management of road network risk and vulnerabilities in intricate hilly region settings by developing a thorough vulnerability analysis framework. The research advances by giving transportation engineers a useful quantitative tool for identifying the risk and vulnerabilities of road network and directing design strategies and mitigation measures to lessen the possible negative effects of disruptive events like landslides on road infrastructure. The research findings could be an input for policy makers to plan for alternative resilient strategies for landslide risk management in road networks. The rational methodology adopted here could be replicated for carrying out risk and vulnerability assessment in other landslide prone areas.

Hybrid nonlinear probabilistic model using Monte Carlo simulation and hybrid support vector regression for evaporation predictions

This study presents a hybrid model combining Support Vector Regression (SVR) with the Gray Wolf Optimizer (GWO) for evaluating evaporation dynamics. The model was tested using 50 years of meteorological data from Zabol and Chabahar stations in Iran, and compared against standard SVR. Results show that the SVR-GWO significantly outperforms SVR, reducing predictive errors by over 41% on average. For Zabol, the SVR-GWO markedly improved performance, particularly in July where R2 increased from 0.867 to 0.973. The model more closely matched observed statistics, especially for mean and standard deviation, though challenges remain in reproducing higher-order statistics. Interestingly, 5,000 functions evaluation proved nearly as effective as 500,000 suggesting computational efficiency. This integrated approach, incorporating Monte Carlo simulations and kernel density estimation, provides valuable probabilistic insights into evaporation dynamics, offering a promising tool for drought vulnerability assessment and water resources planning in regions with complex climatic patterns.

Efficient finite element reliability analysis employing sequentially-updated surrogate model for fragility curve derivation

As the threat of natural disasters to structures intensifies, risk assessment of infrastructure has gained much importance. Fragility curves are essential tools in predicting disaster-related losses and making disaster mitigation decisions. In this paper, we propose a new method to efficiently derive accurate fragility curves for structures with high levels of nonlinearity or complexity, addressing the computational challenges of conventional finite element reliability analysis (FERA). To reduce the computational cost for calculating probability of failure in FERA, the proposed method utilizes the first-order reliability method (FORM). However, even with this approach, the computational cost of deriving the fragility curve may remain high; therefore, a surrogate model is used to further reduce costs. By training the surrogate model using the initial structural damage probabilities for a few hazard intensities, an optimal starting point can be calculated for the subsequent FORM analysis. During the fragility analysis, the surrogate model can be updated sequentially to increase the efficiency of FORM analysis continuously. In particular, the training process of the surrogate model requires no separate or additional finite element analysis because it is constructed using previous FERA results. The accuracy and efficiency of the proposed method are tested using conventional FERA and Monte Carlo simulations through a hypothetical short-column example. In addition, fragility curves are derived through a bridge flood fragility assessment considering the scour and seismic vulnerability assessment of a buried gas pipeline considering soil-structure interactions. The derived fragility curves closely match those derived using the conventional FERA, and the computational costs are reduced by 36.54 % and 52.38 %, respectively, compared with the conventional FERA, confirming its cost-effectiveness.

Seismic Vulnerability Assessment of Masonry and RC Building Stocks: A Simplified Methodology

Assessing the seismic vulnerability of existing buildings at the territorial scale is a crucial aspect for seismic-prone regions to properly plan effective strategies for disaster risk management. This paper presents a simplified methodology for the seismic vulnerability assessment of existing masonry and reinforced concrete buildings. The main purpose is to provide a tool able to evaluate the vulnerability of large building stocks, with the aim of defining priorities for further investigations or interventions. The procedure, inspired by methods in the literature devoted to the large-scale evaluation of structural vulnerability, allows defining the collapse peak ground acceleration (PGAc) through the evaluation of the resisting shear force, the latter being estimated by mechanical considerations and by taking expert judgment into account to consider the real structural complexities involved. A classification is proposed, which aims to categorize buildings within homogenous groups characterized by a level of seismic vulnerability belonging to given intervals. The method was calibrated with reference to several case studies in order to reach a sufficient level of reliability in the vulnerability estimate and was then applied to a significant number of school buildings in the province of Ravenna, Italy. For some of them, the simplified methodology was validated through comparisons with results obtained by means of vulnerability assessment procedures based on finite element analyses.

A Review of Methods to Assess Groundwater Vulnerability to Pollution

Groundwater resources that are increasingly being cherished for most socioeconomic development are exposed to varied pollutant sources. Studies have shown that they are vulnerable to various impacts such as climatic change, human impacts and also pollution from seawater intrusion in coastal areas. The susceptibility of a groundwater body to pollution indicates extent to which its quality is at risk of being compromised by contaminants. Assessments of this vulnerability are classified based on scale (site, local, regional) or objective (such as risk management or protection zoning) and also distinguish between source and resource vulnerability maps, as well as specific and intrinsic vulnerability maps. Groundwater vulnerability assessment methods differ based on several factors, including the availability and spatial distribution of quantitative and qualitative data, the objectives and scale of the mapping, the costs of model development, and the particular hydrogeological characteristics of the aquifer under investigation. The National Research Council has classified these methods into three primary categories: process-based methods, statistical methods, and overlay/index methods. Among these, the overlay/index method is widely employed for conducting large-scale assessments of aquifer sensitivity and groundwater vulnerability. It is especially advantageous in developing countries due to the easily accessible data required for its implementation.

A Bayesian network-based probabilistic framework for seismic vulnerability assessment of road networks

After an earthquake, roadside debris from collapsed buildings, structural damage to bridges, and large-scale emergency evacuations are major obstructions to the connectivity of road networks (RNs). However, few studies have comprehensively examined the impact of all these obstructions on the seismic vulnerability of RNs while considering uncertainties. In this paper, a novel probabilistic framework is proposed for seismic vulnerability assessment of RNs based on Bayesian networks (BNs). Herein, the vulnerability of RNs is defined as a combination of the failure probability of a road link and its conditional consequences in terms of network dis-connectivity. The framework can be used to assess the effects of debris distributions, the functionality losses of bridges, and evacuation flows on the failure probabilities of road links and the seismic vulnerability of RNs. Uncertainties in the post-earthquake damage states of buildings and bridges, building collapse types, building-to-road distances, and travel costs are explicitly considered and propagated in the framework using Monte Carlo (MC) simulations. The MC results are used to establish prior probabilities, and based on bidirectional inference with BNs, it is possible to assess the seismic vulnerability of RNs and identify critical roads. The proposed methodology is verified through a real-world RN in China.

VOLCANBOX: a software platform for Volcanic Hazard Assessment

Volcanic eruptions have an intrinsic multi-hazard nature, in which a variety of volcanic products (lava flows, fallout, lahars, and pyroclastic flows) and associated hazards (seismic shocks, landslides, tsunamis, or floods) may interact and impact sequentially. Volcanic hazard assessment relies on probabilistic approaches based on the past eruptive history, from which scientists identify eruptive scenarios and their expected recurrence. However, not enough attempts have yet been made to address volcanic hazard assessment in a systematic way, based on principles that may be equally applicable to different volcanoes and volcanic zones regardless of their particular nature. Hence, we present VOLCANBOX, a new multiplatform (GNU/Linux, MacOS, Windows) system designed to conduct long-and short-term volcanic hazard assessment and risk analysis in a systematic and rational manner, aimed at reducing volcanic risk by anticipating future eruptions. VOLCANBOX includes several sets of software tools designed to evaluate long and short-term volcanic hazards, to conduct vulnerability analysis, and to assist decision-makers during the management of a volcanic crisis. VOLCANBOX can be implemented before an emergency, in order to identify optimum mitigating actions and how these may have to be adapted as new information is obtained. VOLCANBOX is aimed at experts in volcanic hazard and risk assessment and management and is designed to facilitate the interaction and cooperation between scientists, policy makers and civil protection agencies to anticipate volcanic disasters in a timely manner, by quantifying volcanic hazards, understanding volcanic unrest, forecasting volcanic eruptions, and identifying the most probable scenarios in a simple and clear manner.

Unveiling economic resilience: exploring the impact of financial vulnerabilities on economic volatility through the economic vulnerability index

While earlier studies have explored the relationship between economic vulnerability and economic resilience, they have repeatedly overlooked the significance of financial vulnerabilities within the economic vulnerability index, and the effects of financial and economic vulnerabilities on economic volatility. An attempt is made in this study to close this research gap by conducting a detailed analysis of the relationship between financial vulnerabilities, economic vulnerability and economic volatility, stressing the significance of tweaking prevailing vulnerability indices to fully encapsulate its multidimensional nature in developing countries. Employing panel data for 142 countries over the 2002 to 2022 period and a robust econometric approach like the Driscoll and Kraay fixed effect method, the study reveals that financial vulnerabilities yield significant coefficients to influence economic volatility, thereby accentuating their significance in the Economic Vulnerability Index. Sub-group analyses reinforce the need for incorporating financial variables in vulnerability investigations. Moreover, the causality tests reveal that all the variables and indices meant to capture the economic and financial vulnerabilities Granger causes economic volatility across the sample. In essence, this study fills a critical gap in existing research by demonstrating, that financial vulnerabilities significantly influence economic volatility, underscoring the imperative of integrating financial variables into vulnerability assessments for policymakers and scholars focusing on sustainable development. This study contributes to a broader understanding of economic vulnerability by highlighting the crucial role of financial vulnerabilities in driving economic volatility, suggesting a fundamental reconsideration of existing vulnerability assessment frameworks for policymakers and researchers focused on sustainable development frameworks. By uncovering the causal relationship between financial vulnerabilities and economic volatility across a diverse set of countries, the findings underscore the imperative of integrating financial factors into vulnerability investigations to enhance resilience and stability in developing economies.

Comparison and theoretical conceptualization analysis of statistical methods used to develop heat vulnerability indices in urban areas

In view of the impact of extreme temperatures on physical and psychological health, particularly in urban areas, several studies have focused on assessing social vulnerability using quantitative indexing approaches with the aim of creating a heat vulnerability index (HVI). In this context, this study employs three statistical methodologies frequently used to construct HVIs on the territory of the Toulouse Métropole, France, at the census block (IRIS) scale to assess the efficiency of this type of approach for evaluating social vulnerability in urban environments considering the current theoretical conceptualization. The three HVIs show the same general trends, with a spatial configuration in which high levels of vulnerability are concentrated in the downtown and suburbs of the Toulouse municipality. Vulnerability gradually decreases away from the urban core, becoming moderate in the inner suburbs and low on the outskirts. However, a spatial analysis of the clusters reveals variability in the boundaries of the vulnerability hotspots. Value class matching indicates that a significant number of census blocks are classified differently according to the method considered. These results raise questions concerning the ability of HVIs to provide reliable vulnerability assessments, given their geostatistical and conceptual limitations. Indexing approaches therefore appear to contradict current theoretical conceptualizations promoting the concept of vulnerability as being complex and multifactorial.

Comparative Vulnerability Analysis of Thai and Non-Thai Mobile Banking Applications

The rapid adoption of mobile banking applications has raised significant concerns about their security vulnerabilities. This study presents a comparative vulnerability analysis of mobile banking applications from Thai and non-Thai banks, utilising the OWASP Mobile Top 10 framework. Nine mobile banking applications (five Thai and four non-Thai) were assessed using three vulnerability detection tools: AndroBugs, MobSF, and QARK. The results showed that both Thai and non-Thai mobile banking applications had vulnerabilities across multiple OWASP Mobile Top 10 categories, with reverse engineering, code tampering, and insufficient cryptography being the most common. Statistical analysis revealed that Thai banking applications exhibited significantly more vulnerabilities compared to non-Thai banking applications. In the context of vulnerability detection tools, AndroBugs and QARK proved more effective in detecting vulnerabilities compared to MobSF. Additionally, the study highlights critical security challenges in mobile banking applications, particularly for Thai banks, and emphasises the need for enhanced security measures. The findings also show the importance of using multiple assessment tools for comprehensive security evaluation and suggest potential areas for improvement in mobile banking applications.

Integrated Environmental Vulnerability Assessment and Adaptation Strategies for Coastal Areas under Sustainable Development

Integrated Environmental Vulnerability Assessment and Adaptation Strategies for Coastal Areas under Sustainable Development

Identification and Evaluation of Vulnerable Links in a Distribution Network with Renewable Energy Source Based on Minimum Discriminant Information

With the increase in the proportion of photovoltaic and wind power access, the scale and form of distribution networks are becoming more and more complex. The traditional single distribution network vulnerability assessment method is difficult to use to identify the vulnerable links in the distribution network. Therefore, this paper proposes a method for identifying and evaluating vulnerable links in distribution networks based on minimum discriminant information. First, considering the influence of distributed grid connection, an improved probabilistic power flow calculation method is proposed, which improves the calculation efficiency and accuracy. Second, considering the correlation degree, transmission capacity, and voltage stability of branches in the distribution network, the identification index of vulnerable lines is defined. Based on power quality and operating state, the identification index of vulnerable nodes in a distribution network is defined. Finally, based on the indicators of vulnerable nodes and vulnerable lines, the vulnerable links in the distribution network are comprehensively evaluated based on the principle of minimum discriminant information, and the vulnerable links of the entire distribution network are evaluated according to different degrees of vulnerability. The rationality and effectiveness of the proposed method are verified via an example analysis of actual power grid data.

Vulnerability assessment and evolution analysis of Beijing's Urban Rail Transit Network

With the development of urban rail transit system, the complexity of the network intensifies, and its vulnerability shifts correspondingly. Understanding the characteristics and evolution of network vulnerability, as well as identifying developmental patterns, enables more scientific network planning. Current researches on network vulnerability predominantly focus on the static vulnerability assessment of existing networks, with limited studies on vulnerability evolution. This paper divides the topological evolution of the Beijing Urban Rail Transit Network (BURTN) from 2000 to 2020 into Formation and Improvement stages using the K-means++ method. By constructing a multidimensional vulnerability assessment model that considers node degree uniformity, network efficiency, and connectivity, the vulnerability evolution characteristics and patterns of BURTN are explored in cases of both Single-station failures and Multi-station consecutive failures (including random and intentional failures). Furthermore, the evolutionary relationship between network vulnerability and network structure is explored using the Ridge regression model. Calculations reveal that in the case of Single-station failures, during the Formation stage, the proportion of highly vulnerable stations (HVS) and the impact of each station failure on network performance decrease significantly, by 69.36 % and 67.67 %, respectively. During the Improvement stage, the proportion of HVS decreases significantly, while the impact of each station failure on network performance decreases slightly, by 79.10 % and 37.04 %, respectively. In the case of Multi-station consecutive failures, during the Formation stage, the network’s ability to cope with both random and intentional failures decreases, with the percentage of network nodes removed at the collapse state decreasing by 24.95 % and 11.12 %, respectively. During the Improvement stage, the network’s ability to cope with random failures remains stable, while its ability to cope with intentional failures decreases. This study helps to understand vulnerability from an evolutionary perspective and provides practical strategies for reducing vulnerability.