Proposed Risk Assessment Method Research Articles

Network Attack Path Selection and Evaluation Based on Q-Learning

As the coupling relationship between information systems and physical power grids is getting closer, various types of cyber attacks have increased the operational risks of a power cyber-physical System (CPS). In order to effectively evaluate this risk, this paper proposed a method of cross-domain propagation analysis of a power CPS risk based on reinforcement learning. First, the Fuzzy Petri Net (FPN) was used to establish an attack model, and Q-Learning was improved through FPN. The attack gain was defined from the attacker’s point of view to obtain the best attack path. On this basis, a quantitative indicator of information-physical cross-domain spreading risk was put forward to analyze the impact of cyber attacks on the real-time operation of the power grid. Finally, the simulation based on Institute of Electrical and Electronics Engineers (IEEE) 14 power distribution system verifies the effectiveness of the proposed risk assessment method.

Water environmental nexus-based quality and safety risk assessment for fish (Carassius auratus) in aquaculture

Abstract Freshwater aquaculture is the main form of aquaculture in inland areas, and pollution is a significant challenge. The aim of this work was to propose an effective risk assessment method for aquaculture to predict pollutant bioaccumulation in fish tissue based on water environment variables. This method was designed to assess the risk of pollutant levels in fish tissue that exceed China’s food safety standards. Firstly, field observation and investigation were conducted to analyze the migration mechanisms of the main pollutants between fish tissue and the water environment. Secondly, a classification and regression tree (CART) and generalized additive model (GAM) nexus method was used to analyze the environmental variables related to pollutants in the water environment and establish prediction models. Finally, models of the bio-reaction kinetics were established to predict the pollutant bioaccumulation in fish tissue. The experimental results indicate that the GAM models could explain 73.7%, 84.4%, and 84.5% of the deviations for the three predicted pollutants. For 90% of the sample data, the accuracy of the bioaccumulation prediction was 93.44% for volatile phenol bioaccumulation, and 90.16% for Cu and coliform bioaccumulation. The proposed risk assessment method could be extended for aquaculture applications that require monitoring of additional parameters to safeguard aquaculture quality and facilitate effective safety risk management.

Assessing risk: Characterizing language performance in pediatric patients with intractable epilepsy pre- and post-surgical resection

Neuropsychologists play an important role in assessing risk for post-surgical cognitive decline in pediatric patients with medically refractory epilepsy. Families, neurologists, and neurosurgeons are particularly concerned about the possibility for language decline for patients with a dominant, most often left, hemisphere epileptic focus and planned surgical resection. This study aims to describe language functioning in pediatric epilepsy patients following resection and evaluate the accuracy of a clinical approach of assessing risk. This study proposes a risk assessment method that considers a patient’s pattern of lateralized dysfunction across cognitive domains, suspected neuroanatomical reorganization of language functions, and planned site of resection. Pediatric patients (N = 47) were dichotomized as being at minimal risk or at greater risk for post-surgical language decline based on the proposed risk assessment method. Retrospective chart review was utilized to obtain neuropsychological (Boston Naming Test and Weschler Vocabulary subtest) and clinical variables of interest. Patients in the minimal risk group demonstrated significantly improved BNT scores at post-surgery. Most patients remained stable in their Vocabulary knowledge. The proposed risk assessment method correctly classified patients 77% of the time based on BNT performance. Cluster analysis examining the individual components of the proposed method revealed three distinct patient subgroups. Clinical implications are discussed.

Risk assessment of chemical process considering dynamic probability of near misses based on Bayesian theory and event tree analysis

With the development of modern automatic control systems, chemical accidents are of low frequency in most chemical plants, but once an accident happens, it often causes serious consequences. Near-misses are the precursor of accidents. As the process progresses, near misses caused by abnormal fluctuation of process variables may eventually lead to accidents. However, variables that may lead to serious consequences in the production process cannot update the risk in the life cycle of the process by traditional risk assessment methods, which do not pay enough attention to the near misses. Therefore, this paper proposed a new method based on Bayesian theory to dynamically update the probability of key variables associated with process failure risk and obtain the risk change of the near-misses. This article outlines the proposed approach and uses a chemical process of styrene production to demonstrate the application. In this chemical process, the key variables include flow rate, liquid level, pressure and temperature. In order to study the dynamic risk of the chemical process with consideration of near misses, according to the accumulated data of process variables, firstly the abnormal probability of the variables and the failure rate of safety systems associated with the variables were updated with time based on Bayesian theory. On the basis of the dynamic probability of key process variables, an event tree of possible consequences caused by variable anomalies was established. From the logical relationship of the event tree, the probability of different consequences can be obtained. The results show that the proposed risk assessment method based on Bayesian theory can overcome the shortcomings of traditional analysis methods. It shows the dynamic characteristics of the probability of different near misses, and achieves the dynamic risk analysis of chemical process accidents.

Data learning and expert judgment in a Bayesian belief network for aiding human reliability assessment in offshore decommissioning risk assessment

Decommissioning of offshore facilities involve changing risk profiles at different decommissioning phases. Bayesian Belief Networks (BBN) are used as part of the proposed risk assessment method to capture the multiple interactions of a decommissioning activity. The BBN is structured from the data learning of an accident database and a modification of the BBN nodes to incorporate human reliability and barrier performance modelling. The analysis covers one case study of one area of decommissioning operations by extrapolating well workover data to well plugging and abandonment. Initial analysis from well workover data, of a 5-node BBN provided insights on two different levels of severity of an accident, the ’Accident’ and ’Incident’ level, and on its respective profiles of the initiating events and the investigation-reported human causes. The initial results demonstrate that the data learnt from the database can be used to structure the BBN, give insights on how human reliability pertaining to well activities can be modelled, and that the relative frequencies from the count analysis can act as initial data input for the proposed nodes. It is also proposed that the integrated treatment of various sources of information (database and expert judgement) through a BBN model can support the risk assessment of a dynamic situation such as offshore decommissioning.

Risk assessment of the UPIoT construction in China using combined dynamic weighting method under IFGDM environment

Large-scale integration of renewable energy systems poses challenges to the ubiquitous power Internet of things (UPIoT) construction in China. This paper aims to study beyond these challenges from a risk assessment perspective, using the combined dynamic weighting evidence fusion (CDWEF) method under the intuitionistic fuzzy group decision-making (IFGDM) environment. The UPIoT construction risk is identified and characterized by a 17-indicator system which is scored by intuitionistic fuzzy relations (IFRs) from experts. The IFRs are corrected by the dynamic expert weight determined from both the intuitionistic fuzzy entropy and conflicts among IFRs. The IF-AHP-DEMATEL method is adopted to determine the combined indicator weight for correcting the risk mass functions, which are obtained from the IFRs with the evidence fusion theory. The proposed risk assessment method is validated in a case study, indicating that the UPIoT construction risk in China is high in communication networks and business innovation.

Health risk assessment of heavy metals, BTEX and polycyclic aromatic hydrocarbons (PAHs) in the workplace in a secondary oil re-refining factory

The present study aimed to evaluate the health risk of heavy metals (iron, zinc, cadmium, arsenic, nickel, lead, and mercury), benzene, toluene, ethylbenzene and xylene (BTEX), and polycyclic aromatic hydrocarbons (PAHs) in the workplace in a secondary oil re-refining factory. In this descriptive, cross-sectional study, samples were collected and analyzed using the NIOSH 1501 method at eight sampling points with determined concentrations of BTEX, 16Ʃ PAHs, and heavy metals. The concentration of each pollutant was evaluated based on the type of workers (packaging/filtration). The risk assessment of the contaminants was carried out using the RAIS software, and the risk of non-carcinogenic compounds was estimated based on the reference respiratory concentration (mg/m3). The results showed that the lifetime cancer risk index (LCR) cumulative risk of the heavy metals was within the definitive risk range at all the sampling points. The highest carcinogenic risk of LCR belonged to arsenic at sampling point H (filtration chamber), and the highest cumulative carcinogenic risk of the total contaminants in the environmental sampling points belonged to sampling point H. At all the sampling points, the LCR carcinogenic risk accumulation for the hydrocarbon compounds was within the definitive range. The maximum cumulative lifetime cancer risk for the hydrocarbon compounds was evaluated in filtration (point B), and the most hazardous carcinogens were arsenic, benzo(a)pyrene, and naphthalene. The proposed risk assessment method was observed to be comprehensive, and its results could be used for corrective and controlling measures and the prioritization of risk reduction resources.

Risk assessment of seismic landslides based on analysis of historical earthquake disaster characteristics

Risk assessment of seismic landslides in potential earthquake zones is important for construction in mountainous areas. To present a new method for conducting risk assessment of landslides, data of 720 landslides caused by the Ludian Ms6.5 earthquake, which occurred in 2014, are taken as a sample, and five impact factors are selected as risk assessment indexes; these factors include the slope, slope direction, elevation, strata lithology, and peak ground acceleration. Fractal theory and the result of the landslide distribution analysis of the Ludian earthquake are adopted to calculate the weight of each impact factor. The proposed risk assessment method is established by calculating the landslide distribution density. Under an assumed earthquake, the method is used for conducting risk assessment in the Dayong Expressway region; the topography and geology of this region are very similar to those of the Ludian County. The landslide risk zoning in the region can be obtained using the K-means cluster method to classify the risk level after the assignment of the landslide risk index. The result shows that a 2.25-km route of the Dayong Expressway has the highest risk of geological disasters with an occurrence probability of 1.1% considering the influence of the Chenghai fault. The assessment results can provide a scientific basis for disaster prevention in the Dayong Expressway area.

Traction Power-Supply System Risk Assessment for High-Speed Railways Considering Train Timetable Effects

A traction power-supply system (TPSS) is the only power source for electric locomotives; therefore, its safe and consistent operation is of critical importance to reliable, high-speed operation. Electrical faults can disrupt train scheduling and jeopardize the safety and security of high-speed railways. Thus, it is essential to quantitatively evaluate possible risk factors in TPSSs. To do so, based on 24-h train timetable, this paper defines indices to describe the failure risk to traction power-supply equipment, and a separate set of indices present the risk from various power-quality problems. Combining both the equipment and power-quality risks yields a comprehensive risk-assessment for the TPSS, by means of a weighted evaluation. The proposed risk assessment method can ensure informed personnel by communicating the system's risk state in real-time to identify high-risk operation, thereby avoiding the potential for severe accidents and informing maintenance and operational plans.

WAREHOUSE RISK ASSESSMENT USING INTERVAL VALUED INTUITIONISTIC FUZZY AHP

Warehouses are essential components of a supply chain management system. Any malfunction in warehouses may have an important effect on the subsequent operations of a firm. For example, an accident that occurs in a warehouse can damage the operations of the company as well as the health of the employees. In this paper, critical operations at a warehouse are considered in terms of occupational health and safety. The originality of the paper is that the proposed approach provides a new perspective on warehouse risk assessment. It is the first time a method involving interval valued intuitionistic fuzzy Analytical Hierarchy Process (IVIF-AHP) and a new risk assessment table is utilized to evaluate and categorize the risks in warehouses. As a result of the proposed risk assessment method, hazards in warehouses are categorized as insignificant, marginal, or catastrophic.

Mechanism and risk assessment of overall-instability-induced rockbursts in deep island longwall panels

An increasing number of mines in China are being subjected to overall-instability-induced (OII) rockbursts in extracting deep remnant island longwall panels, causing severe damage at far larger scale and intensity compared with common local rockbursts. Using the island longwall panel LW1305 at Zhaolou Coal Mine as a case example, this paper investigates the mechanism of the newly defined OII rockburst by means of stress and microseismic monitoring, and then proposes a straightforward risk assessment method for OII rockbursts based on the actual bearing index in an attempt to provide guidelines for making engineering judgement. The proposed risk assessment method was successfully applied to LW1305, and the assessment result is supported by the occurrence of an OII rockburst in LW1305, and further verified by numerical modeling and microseismic monitoring.

Assessment of structural risks using the fuzzy weighted Euclidean FMEA and block diagram analysis

Failure mode and effects analysis (FMEA) is a risk assessment method in products, processes, or systems for appropriate corrective actions. Although FMEA techniques are used in various industries, it has been criticized for several shortcomings. First, conventional FMEA entirely depends on qualitative evaluation. Second, traditional FMEA does not consider the functional influence between components of a system, meaning that it cannot be applied to systems-complicated influence relationships. Third, risk priority number (RPN) in traditional FMEA, which is evaluated in crisp values of severity (S), occurrence rate (O), and the probability of not detecting the failure (D), can lead to a RPN distortion problem in which contradictory interpretations of RPN result from, respectively, reasonable risk factors. In order to overcome these shortcomings, this paper proposes a new risk assessment method using importance risk priority number (IRPN). The IRPN, which is composed of structural and relational importance, is attained by taking a three-dimensional geometric approach to fuzzy weighted Euclidean (FWE) FMEA and risk block diagram analysis. The proposed risk assessment method is applied in the numerical example and empirical example of the thin film transistor liquid crystal display (TFT-LCD) products. Comparison results with previous FMEA methods show that the proposed method not only overcomes the shortcomings of previous FMEA methods, such as the RPN distortion, but is also useful for assessing the structural risks that involve functional influence between risks. In addition, a three-dimensional approach based on fuzzy logic is more analytical and applicable than previous methods.

Construction safety risk assessment with introduced control levels

It is of great importance to facilitate the risk assessment process in construction projects because risk assessment is a requirement in most legislation and safety standards. A great majority of construction SMEs (Small and Medium Enterprises) are not familiar with risk assessment concepts and methods. In particular, SMEs are very likely to have difficulty finding the qualified personnel or time to carry out a proper risk assessment. The method introduced in this paper has some distinct features. The method introduces a new method of risk assessment, replacing the traditional definition of probabilities with control levels because they are easier to implement and yield more accurate risk scores. The method was practically applied on 22 construction SMEs. From the practical application, it was observed that the method was found to be user friendly and the SMEs found it easy to update their risk strategies during various construction stages in their projects. The proposed risk assessment method introduces a powerful and practical control level strategy which would develop a safer, healthier and more competitive workplace for construction SMEs.

Microgrid Risk Analysis Considering the Impact of Cyber Attacks on Solar PV and ESS Control Systems

This paper presents a risk assessment method for evaluating the microgrid cybersecurity while considering the role of solar photovoltaic (PV) and energy storage system (ESS) control systems. This paper studies the impact of cyber attacks that interact with microgrid control systems, and presents Markov-based state transition rules to simulate microgrid responses. This paper utilizes a sample of practical microgrid products to illustrate the behavior of PV and ESS control systems when their parameters are intentionally modified. The Monte-Carlo simulation is applied to calculate the monitory risk index of microgrid, which assesses the microgrid risks when solar PV and ESS control systems are hacked by attackers. The effectiveness of the proposed risk assessment method is demonstrated using the microgrid at Illinois Institute of Technology.

A predictive model for risk assessment on imminent bird strikes on airport areas

Wildlife hazard assessment (WHA) is a compulsory procedure on every significant international airport. With the appearance and integration of avian radar systems, the estimation of future bird tracks is possible, therefore the probability and severity of a bird strike can be assessed several minutes before that occurrence happens. Taking that into account, some mitigation procedures and actions could be implemented on airports in order to reduce the risk of the hazard. This work proposes a methodology for real-time evaluation of the risk assessment based on avian radar and aircraft data. This risk evaluation can trigger actions or procedures, within enough time, to significantly reduce the risk of a bird strike during critical flight phases. The risk estimation model combines the track of a bird and an aircraft (based on speed, altitude and heading), the proximity of the future crossing paths, the bird speed and mass, and the angle of impact. Simulation scenarios have been established to confirm if the mitigation actions could be implemented considering time of reaction, aircraft capabilities, and avian radar coverage. The proposed Risk Assessment method and mitigation actions to reduce the probability of a bird strike on aircrafts are a systematic and scientific approach to enhance flight safety on airports. This approach could be the basis for future mitigation protocols using more sophisticated actions in accordance with present and future technology.

INTRODUCING A METHOD OF URBAN SOIL RISK EVALUATION – A CASE STUDY ON URBAN RECREATIONAL AREAS IN CLUJ NAPOCA

Assessing risks related to urban soil contamination represents a key part of pollution management. The current research proposes a quantitative method that defines and highlights unacceptable risks. The applicability of the method is presented in a case study on several urban recreational areas from the city of Cluj-Napoca, Romania. Concentrations of As, Cu, Cd, Zn, Pb, Hg, Co, Ni and Mg were identified in a number of 48 soil samples from 12 intensively used recreational areas in Cluj-Napoca. The proposed risk assessment method is applied, and potential risks are calculated for all locations.

Application of human factors evaluation in engineering design and safe operation of dense phase ethylene treaters

Ethylene treaters are widely used in the petrochemical industry to remove impurities from ethylene feedstock imported from pipeline networks or storage caverns. The safety concerns of dense phase ethylene treaters due to the reactive and highly flammable nature of ethylene are well known and studied. Under certain conditions, ethylene may self-polymerize and decompose violently with heat release. Under other conditions, ethylene will auto-refrigerate, generating cold liquids that may cause potential brittle fracture hazards. Therefore, dense phase ethylene treaters present design challenges with the unique combination of high temperature decomposition and cold temperature brittle fracture hazards.Due to these safety concerns, it is important to select the appropriate engineering design options for dense phase ethylene treaters and the associated regeneration facilities. Totally automated treater regeneration systems add complexity and instrument maintenance requirements while manually operated systems rely heavily on operator training and procedures. Unfortunately, little or no information or design guidance is available from published research findings in the literature on the evaluation and risk assessment of current industrial design options and practices for dense phase ethylene treaters.This paper presents a systematic risk assessment method to evaluate the engineering design and safe operation options for dense phase ethylene treaters. The proposed risk assessment method integrates human factors task analysis into the traditional HAZOP, LOPA and fault tree analysis to allow evaluation of automated, manual and hybrid approaches with a goal of selecting and optimizing design options to ensure plant safety. This approach provides a realistic assessment of the operational risk and allows identification of fit-for-purpose risk reduction. Applying this systematic risk assessment approach, a simpler and more cost effective design solution can be justified, thereby avoiding the need for a high integrity protective system.

GIS-Based Risk Assessment of Hail Disasters Affecting Cotton and Its Spatiotemporal Evolution in China

Understanding the spatiotemporal distribution pattern of hail disaster risk for cotton is crucial in mitigating hail disaster and promoting the sustainability of cotton farming. Based on such indexes as hail disaster frequency, spatiotemporal exposure, and vulnerability of cotton, we assess hail disaster risk for cotton, and analyze its spatiotemporal pattern and evolution in Mainland China from 1950 to 2009, supported by geographic information system (GIS). The following conclusions are drawn: (1) The proposed risk assessment method reveals the spatiotemporal difference of hail disaster risk for cotton at the county level. (2) Hail disaster risk for cotton is low in China, except for north of the North China Plain and the cotton-planting areas in Xinjiang Uygur Autonomous Region. From 1950 to 2009, hail disaster risk for cotton gradually increased. (3) The descending orders of hail disaster risk levels for cotton are bud stage, seedling stage, sowing and seeding stage, boll stage, and boll opening stage. The growth period with the highest risk varies across the cotton-planting areas. (4) The results of this paper are important for developing hail disaster prevention and reduction measures.

Cascading Failure Risk Assessment Considering Protection System Hidden Failures

Cascading failure plays an important role in blackouts. Complex network theory, with the disadvantage of ignoring some of physical features of the power systems, is often utilized to model the cascading failure evolution processes. In this paper, a new risk assessment method based on evolution procedure and dynamic fault trees (DFTs), is proposed to model cascading failures in power systems. DFTs, which extend standard fault tree by allowing the modeling of complex system components’ behaviors and interactions, are introduced to describe the cascading failure mathematical model. The power grid topologies affected by protective relays, circuit breakers and transmission lines are taken into consideration to overcome the disadvantages of complex network theory. The evolution of cascading failures of power system, which is modeled based on the DFT, is significantly closer to the actual physical system behavior. The effectiveness of the proposed risk assessment method is discussed using two test cases.

Power System Risk Assessment in Cyber Attacks Considering the Role of Protection Systems

This paper presents a risk assessment method for evaluating the cyber security of power systems considering the role of protection systems. This paper considers the impact of bus and transmission line protection systems located in substations on the cyber-physical performance of power systems. The proposed method simulates the physical response of power systems to malicious attacks on protection system settings and parameters. The relationship among settings of protection devices, protection logics, and circuit breaker logics is analyzed. The expected load curtailment (ELC) index is used in this paper to quantify potential system losses due to cyber attacks. The Monte Carlo simulation is applied to calculate ELC for assessing attackers’ capabilities as bus arrangements are altered. The effectiveness of the proposed risk assessment method is demonstrated using a 9-bus system and the IEEE 68-bus system.