Dynamic Vulnerability Assessment Research Articles

A novel methodology for dynamic vulnerability assessment of storage tank exposed to technological hazards

Storage tanks are vulnerable to catastrophic technological hazards such as fires or explosions. Although many attempts have been made to assess the tank vulnerability exposed to a certain fire or explosion, little attention has been paid to the uncertainties of diverse accident scenarios and time-dependent damage effects. In this paper, a novel methodology is developed to dynamically estimate the vulnerability of chemical storage tank, while the static and dynamic factors related to tank vulnerability are studied in a unified framework. The uncertainties in the evolution of technological hazard are discretized and assessed using the dynamic event tree, in which the dynamic possibility of ignition and potential scenario transition are taken into account. Furthermore, a detailed study of the dynamic consequence and time-dependent damage behavior of physical effects is conducted, supporting a more accurate assessment of tank vulnerability. The case study demonstrates that the developed methodology could simulate the stochastic process of spatio-temporal evolution of technological hazards and enable a comprehensive analysis of damage patterns over time. Besides, the protection and mitigation effects of different safety barriers are evaluated and discussed, the results are valuable for reducing the risks of tank farms.

Dynamic vulnerability assessment framework for urban flood disasters considering real-time population changes

ABSTRACT Flood vulnerability assessment is an important means to cope with urban flood disasters. However, urban population mobility and land-use changes bring significant uncertainty to vulnerability assessments. In order to respond to the refined and dynamic needs of urban flood disaster prevention and control, a multi-scale and multi-categorized urban flood dynamic vulnerability assessment framework that considers real-time population changes was proposed in this study. The framework used the comprehensive function of exposure, sensitivity, and coping ability under population dynamic changes to characterize urban flood dynamic vulnerability, and constructed urban flood disaster vulnerability assessment models at both grid and regional scales. The results show that population mobility has a significant impact on the vulnerability of urban flood disasters. The vulnerability of flood disasters in Zhengzhou City is highest at 8:00 and 18:00, and high-vulnerability areas are mainly concentrated in residential areas in the central part of the city and main transportation channels. From 10:00 to 15:00, the high-vulnerability areas migrate to public service areas in the eastern part of Zhengzhou City. In the evening, the vulnerability degree of flood disasters is relatively low. The research results can provide a theoretical basis for urban flood managers to prevent and control flood disasters.

Assessment of risk intensity in the triffa plain aquifer: Integration of hazard quantification, land use analysis, dynamic vulnerability GCITF, and DRASTIC method

This study aims to assess the level of groundwater pollution risk in the Triffa Plain, stemming from various pollution sources, with a specific focus on agricultural intensification and excessive pesticide use. Data were collected from ABHM (the Moulouya Hydraulic Basin Agency) and ORMVAM (Regional Office of Moulouya Agricultural Development), and a field visit was conducted in July 2023. The study utilized two main methodologies for mapping risk intensity: the COST 620 action and overlaying vulnerability maps with the land use (LU) factor. Vulnerability maps were generated using the original DRASTIC method and the new dynamic vulnerability assessment method, GCITF.The research approach involved comparing the COST 620 risk index (Ri) and the land use risk index (LU) to identify the most suitable method for the study area. Due to challenges in inventorying various point sources of pollution, the study focused on mapping the primary sources of pollution (diffuse, point, and linear). The key findings indicate that the predominant pollution intensity in the region is high, covering 60.66% of the total surface area. These results closely align with those obtained using the European COST 620 approach and the spatial distribution of nitrates. The study demonstrates the reliability of integrating the GCITF method in assessing groundwater contamination risk, highlighting the significant negative impacts of agricultural activities on the Triffa Plain aquifer, primarily due to uncontrolled pesticide and fertilizer use and point sources of pollution.This study suggests that implementing targeted technical solutions for specific pollution sources is crucial for reducing contamination in the Triffa Plain. These pollution risk intensity maps can assist planners and decision-makers in understanding the origin of pollution and identifying necessary actions to minimize contamination risk, contributing to better groundwater management and protection in the region.

Dynamic vulnerability assessment of hybrid system considering wind power uncertainty

The stochastic volatility of wind power introduces numerous uncertainties to the security and stability of the hybrid system, which in turn affects the overall vulnerability level of the system. In this study, a wind power output model incorporating the effects of wind abandonment and uncertainty factors is established. Additionally, a hybrid optimal power flow (OPF) method considering economic dispatch, stochastic trip, and islanding strategies is developed to simulate the power flow dispatch during cascading failures. Furthermore, a set of indexes describing the global dynamic vulnerability of the hybrid system is proposed to reveal the effects of changes in wind power uncertainty and penetration levels on the hybrid system in the short term. Simulations were conducted on an adapted IEEE118 system, and the results demonstrate that an increase in wind power uncertainty and penetration will exacerbate the system’s vulnerability. This severity is particularly pronounced during peak and valley load periods, making the hybrid system more susceptible to large-scale outages. When the wind power uncertainty level grows to 4, the overall vulnerability level of the hybrid system increases by 102.3% compared to the initial uncertainty case. When the wind penetration level reaches 46%, the overall vulnerability level rises by 75.9% compared to the initial system. These findings emphasize the sensitivity of the hybrid system to different levels of wind power uncertainties and penetrations, providing evidence-based support for the prevention of system cascade failures.

Integrated SEAWAT model and GALDIT method for dynamic vulnerability assessment of coastal aquifer to seawater intrusion

Seawater intrusion (SI) has become a global issue exacerbated by intense anthropogenic activities and climate change. It is imperative to seek a synergistic strategy to reconcile environmental and economic benefits in the coastal regions. However, the intricate SI process and data scarcity present formidable challenges in dynamically assessing the coastal groundwater vulnerability. To address the challenge, this study proposed a novel framework that integrates the existing vulnerability assessment method (GALDIT) and variable-density groundwater model (SEAWAT). The future scenarios from 2019 to 2050 were investigated monthly under climate change (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5) and human activities (80 % and 50 % of current groundwater abstraction) in Longkou city, China, a typical coastal region subject to extensive SI, compared with the status quo in 2018. Results indicated that by 2050, the high vulnerability area, is in a narrow buffer within 1.2 km from the shoreline and exhibits minor changes while the salt concentration here increased by about 2700 mg/L compared with the current situation. The moderate vulnerability zone expands by about 30 km2, and the low vulnerable area decreases proportionally. The groundwater over-abstraction is identified as a more critical factor compared to the regional precipitation under climate change. When groundwater abstraction is reduced to 80 % of the current scale, the expansion rate of the moderate-vulnerable area slows down significantly, with an expansion area of only 18 km2 by 2050. Further reducing groundwater abstraction to 50 % of the current scale shifts the evolution trend of the medium-vulnerable area from expansion to contraction, with the area shrinking by about 11 km2 by 2050. The integrated vulnerability assessment framework can be applied not only in the similar coastal regions but also provides insights into other natural hazards.

Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory

The increasing factors of uncertainty faced by the system are due to the deep coupling of the electric power cyber network and the physical network. Consequently, ensuring the efficient, secure, and stable operation of the cyber–physical power system (CPPS) has become a key concern. To achieve this, vulnerability assessment plays a crucial role, as it identifies and protects the vulnerable points of the system. The application of complex network theory to assess the vulnerability of CPPSs has garnered significant attention from scholars. This paper delves into the research connotation of vulnerability assessment for CPPSs, starting with the origin, definition, and classification of vulnerability. Subsequently, the assessment framework of vulnerability based on complex network theory is presented, and the status of current domestic and international research in this field is summarized. Furthermore, the interrelationship between system vulnerability and cascading failures is analyzed from the perspective of complex network theory. In conclusion, the ideas of CPPS coupling modeling in vulnerability assessment are summarized, the concept of situation awareness is introduced, and a prospective approach for dynamic vulnerability assessment is proposed. This approach is based on situation awareness combined with complex network theory. Security protection and optimal operation of CPPSs based on vulnerability assessment are also discussed, along with the assessment of vulnerability within integrated energy cyber–physical systems (IECPSs).

Dynamic vulnerability assessment of maize under low temperature and drought concurrent stress in Songliao Plain

With global climate change, most parts of the world face more than one natural disaster. Field crops must cope with a combination of two or more stresses. System vulnerability has changed, and quantitative vulnerability analysis is imminent and challenging. Based on the crop water surplus deficit index (CWSDI) and low-temperature index (LTC), this study used the copula method to establish a dynamic assessment model of maize vulnerability under different low temperature and drought concurrent stress intensities, finally showed it in two forms of three-dimensional surface and spatial distribution, which was more vivid and comprehensive. The main conclusions are as follows: the peak number of individual events and concurrent events of low temperature and drought is significantly different, the time trend of the number of concurrent events in each growth period is not the same, and the interannual difference is significant; low-temperature severity and maize yield loss rate, low-temperature severity, and drought severity had significant correlation. Based on this, a 3 C-vine-copula model was established and passed the test. The interaction between the joint probability of concurrent event intensity and the loss rate leads to complex changes in vulnerability. When low temperature and drought are concurrent, the vulnerability analysis cannot be simply superimposed by low temperature and drought intensity. The vulnerability distribution of maize at different growth stages in Songliao Plain shows noticeable regional differences. The central and southern parts of the study area are the most vulnerable areas under low-temperature and drought stress. This study’s results can help managers adjust agricultural resources and adopt more effective irrigation policies under combined stress conditions.

Dynamic vulnerability assessment and damage prediction of RC columns subjected to severe impulsive loading

Reinforced concrete (RC) columns are crucial in building structures and they are of higher vulnerability to terrorist threat than any other structural elements. Thus it is of great interest and necessity to achieve a comprehensive understanding of the possible responses of RC columns when exposed to high intensive blast loads. The primary objective of this study is to derive analytical formulas to assess vulnerability of RC columns using an advanced numerical modelling approach. This investigation is necessary as the effect of blast loads would be minimal to the RC structure if the explosive charge is located at the safe standoff distance from the main columns in the building and therefore minimizes the chance of disastrous collapse of the RC columns. In the current research, finite element model is developed for RC columns using LS-DYNA program that includes a comprehensive discussion of the material models, element formulation, boundary condition and loading methods. Numerical model is validated to aid in the study of RC column testing against the explosion field test results. Residual capacity of RC column is selected as damage criteria. Intensive investigations using Arbitrary Lagrangian Eulerian (ALE) methodology are then implemented to evaluate the influence of scaled distance, column dimension, concrete and steel reinforcement properties and axial load index on the vulnerability of RC columns. The generated empirical formulae can be used by the designers to predict a damage degree of new column design when consider explosive loads. With an extensive knowledge on the vulnerability assessment of RC structures under blast explosion, advancement to the convention design of structural elements can be achieved to improve the column survivability, while reducing the lethality of explosive attack and in turn providing a safer environment for the public.

The simulation of wildland-urban interface fire evacuation: The WUI-NITY platform

Wildfires are a significant safety risk to populations adjacent to wildland areas, known as the wildland-urban interface (WUI). This paper introduces a modelling platform called WUI-NITY. The platform is built on the Unity3D game engine and simulates and visualises human behaviour and wildfire spread during an evacuation of WUI communities. The purpose of this platform is to enhance the situational awareness of responders and residents during evacuation scenarios by providing information on the dynamic evolution of the emergency. WUI-NITY represents current and predicted conditions by coupling the three key modelling layers of wildfire evacuation, namely the fire, pedestrian, and traffic movement. This allows predictions of evacuation behaviour over time. The current version of WUI-NITY demonstrates the feasibility and advantages of coupling the modelling layers. Its wildfire modelling layer is based on FARSITE, the pedestrian layer implements a dedicated pedestrian response and movement model, and the traffic layer includes a traffic evacuation model based on the Lighthill-Whitham-Richards model. The platform also includes a sub-model called PERIL that designs the spatial location of trigger buffers. The main contribution of this work is in the development of a modular and model-agnostic (i.e., not linked to a specific model) platform with consistent levels of granularity (allowing a comparable modelling resolution in the representation of each layer) in all three modelling layers. WUI-NITY is a powerful tool to protect against wildfires; it can enable education and training of communities, forensic studies of past evacuations and dynamic vulnerability assessment of ongoing emergencies.

Dynamic vulnerability assessment of process plants with respect to vapor cloud explosions

Vapor cloud explosion (VCE) accidents in recent years such as the Buncefield accident in 2005 indicate that VCEs in process plants may lead to unpredicted overpressures, resulting in catastrophic disasters. Although a lot of attempts have been done to assess VCEs in process plants, little attention has been paid to the spatial-temporal evolution of VCEs. This study, therefore, aims to develop a dynamic methodology based on discrete dynamic event tree to assess the likelihood of VCEs and the vulnerability of installations. The developed methodology consists of six steps: (i) identification of hazardous installations and potential loss of containment (LOC), (ii) analysis of vapor cloud dispersion, (iii) identification and characterization of ignition sources, (iv) explosion frequency and delayed time assessment using the dynamic event tree, (v) overpressure calculation by the Multi-Energy method and (vi) damage assessment based on probit models. This methodology considers the time dependencies in vapor cloud dispersion and in the uncertainty of delayed ignitions. Application of the methodology to a case study shows that the methodology can reflect the characteristics of large VCEs and avoid underestimating the consequences. Besides, this study indicates that ignition control may be regarded as a delay measure, effective emergency actions are needed for preventing VCEs.

Integrating safety and security resources to protect chemical industrial parks from man-made domino effects: A dynamic graph approach

Chemical industrial parks, being critical infrastructures, are susceptible to domino effects triggered by intentional attacks. Previous research on security risk management has mainly focused on using security measures to prevent intentional attacks, neglecting the effects of safety barriers. Safety barriers are able to reduce the potential consequences and decrease the attractiveness of chemical industrial parks to terrorists who aim to maximize the damage. From a systematic perspective, the potential consequence of intentional attacks is defined as the expected loss which is the sum-product of damage probability and consequence of installations. A consequence-based method including a Dynamic Vulnerability Assessment Graph (DVAG) model is proposed to integrate safety and security resources for reducing the risk of intentional attacks. The DVAG model is developed based on dynamic graphs, considering the effects of security measures, safety barriers, and emergency response. This method can assess the consequences and damage probabilities of possible intentional attacks so as to mitigate the risk via evaluation and allocation of security measures and safety barriers with fast computation speed.

An Integrative Vulnerability Evaluation Model to Urban Road Complex Network

In order to analyze topological properties and vulnerable elements of urban road complex network, 98 lines and 128 nodes are selected by taking Shiyan city in China as an example. Firstly, the definitions of the urban road network’s running state vulnerability and structural vulnerability are proposed in this paper, and the assessment indexes are given respectively. From the perspective of the urban road network topology’s structural characteristics and the traffic demand characteristics, the internal relationship of the running state vulnerability and the structural vulnerability is introduced in order to show the necessity and reasonableness of the urban road network vulnerability assessment. Secondly, the concepts of the urban road network element’s structural-running state parameters are proposed to identify the source of network vulnerability. The Original Method is used to acquire the topology of the urban road network. Finally, with static vulnerability assessment principle, the structural vulnerability index is calculated on the premise that the cascading failure is not considered. With dynamic vulnerability assessment principle, the running state vulnerability index is calculated on the premise that the propagation effects of traffic congestion are considered. The results show that the vulnerability of road network is influenced by two factors: network topology structure and network running state.

Optimal PMU placement for pessimistic dynamic vulnerability assessment

This study proposes a novel optimal phasor measurement unit (PMU) placement method for dynamic vulnerability assessment with minimum number of PMUs. PMU measurements should reflect the change of power system status as earlier as possible when a contingency occurs. Therefore, those buses which are sensitive to the change of power system status have to be equipped with PMUs to monitor the fragile areas of power systems. First, a large power system is partitioned into several coherent clusters. Next, a probabilistic vulnerability index defined as the objective function and a binary quadratic programming model are proposed for this purpose. Finally, the proposed method is tested on IEEE 9-, 39-, and 145-bus systems. Results show that this method results in a PMU configuration with minimum number of devices and high vulnerability index. Such a PMU placement is able to estimate the vulnerability of power systems.

Home Health Care vulnerability assessment using graph theory and matrix methods

The accumulation of factors like climate variability, epidemics and the increasing mobility of people around the world have increased the devastator impact of disasters. Furthermore, people have become more aware and exigent especially in terms of healthcare. Hence, a lot of pressure has been exercised on the healthcare system. Home Health Care (HHC), as a vital component of the healthcare system is facing manifolds crisis that can undermine its activities. This paper addresses the question of HHC vulnerability assessment. We use digraph presentation and matrix operations in order to synthetize indexes that infer the severity of crisis situations that a HHC facility could face, based on the predefined criteria. We introduce dynamic vulnerability assessment that takes into account cascading events over time. Vulnerability Priority Index (VPI) has been proposed to support decision-making related to the design of countermeasures and mitigation policies.

Optimal Placement of Phasor Measurement Unit based on Power System Loss Index

This paper aims to present the simplest scheme for dynamic vulnerability assessment(DVA) based on Power System Loss(PSL) index. Even though a lot of methods are available for vulnerability assessment, DVA based on PSL index is a very simple to explore the region of vulnerability. The probabilistic nature of network dynamics is obtained by Monte Carlo Simulation to evaluate the system performance iteratively for probable input parameter variations such as load variation, generation variation and list of credible contingencies for finding the vulnerability index of the system. Newton Raphson load flow is performed for each contingency and the losses in power system at various parts of the networks are observed. The vulnerability index is calculated based on PSL. Based on the index, the vulnerable regions in the network are identified and clustered with the help of data clustering algorithm. Phasor Measurement Units (PMU) have to be placed in the most vulnerable regions to prevent the system from blackouts and to implement corrective actions. This proposed approach is tested on IEEE-5, IEEE-14, and Indian utility 62 Bus test systems. Results show that PSL index is effective in identifying the vulnerable regions for optimal PMU placement. The findings of the PMU location are compared with earlier works.

Web from preprocessor for crawling

Usually organizations deploy web applications into the production environment with vulnerabilities. To avoid it, organizations need to run a web application vulnerability assessment. The most prevalent kind of vulnerability assessment is when the tester uses a vulnerability scanner. This assessment can be divided into two phases: crawling and testing. The purpose of the first phase is to gather all the access points of the application. In the second phase the tester sends some malformed values to the application, and then analyze the response looking for known vulnerability patterns. The crawling phase is critical because if the tester cannot reach the applications content, he or she couldn't test that content to find vulnerabilities. One of the main challenges of crawling web applications are to fill out web forms with correct values. To face this challenge, web vulnerability scanners used to include a generic list of field value pairs. These scanners also let the tester to add new pairs. This paper presents a novel method for searching candidate web form field values. The challenge is to map more applications content than using the field value pairs included by default. Our method will try to get form fields values executing the client side code and looking for candidate values in an external data source.We have test the proposed method and the experiments show that it can improve the crawling phase of dynamic vulnerability assessment.

Fuzzy Partitioning of a Real Power System for Dynamic Vulnerability Assessment

Recently, the authors proposed a clustering approach based on the fuzzy C-medoid algorithm (FCMdd), for segregating large power systems into coherent electric areas centered around a representative so-called medoid-bus. This bus was shown to be a natural location for PMU in the context of wide-area measurement system (WAMS) configuration for of dynamic vulnerability assessment (DVA). The method was demonstrated on two test systems. The goal of this companion paper is to extend the approach to an actual grid (Hydro-Quebec) with more realistic characteristics in terms of geography and system dynamics. We start by developing a formulation of the coherency matrix that is recursive in time to enable online grid partitioning. The FCMdd is then implemented and compared with other statistical learning techniques. It is observed that only FCMdd is able to provide an intuitively appealing 7-clusters solution for 429-bus system. It is further demonstrated that medoids-based system-wise indices can forecast the contingencies severity under varying network configurations and loadings.

Automatic Segmentation of Large Power Systems Into Fuzzy Coherent Areas for Dynamic Vulnerability Assessment

This paper proposes a technique for partitioning a large power system into a number of coherent electric areas for possible application to dynamic vulnerability assessment. The coherency concept and a fuzzy clustering algorithm grouping of buses are combined to achieve this goal. The clusters are obtained by selecting representative buses from the data set in such a way that the total fuzzy dissimilarity within each cluster is minimized. The initialization problem of the conventional fuzzy c-means algorithm, which usually leads to multiple solutions, is suitably tackled by incorporating the maximum-dissimilarity based sequential phasor measurement unit (PMU) placement technique. Results of bus grouping for two test systems of three and nine areas demonstrate the potential of the approach. It is observed that such an approach to bus grouping results in a PMU configuration with minimum number of devices and fast data aggregation for a wide-area measurement system.