Risk Assessment Method Research Articles

Voltage over-limit risk assessment of wind power and photovoltaic access distribution system based on day-night segmentation and Gaussian mixture model

The access of distributed power sources such as wind power and photovoltaic (PV) with randomness and uncertainty makes the operation of distribution system more complicated. It is particularly necessary to comprehensively and efficiently evaluate the risk of voltage over-limit in distribution systems with wind power and photovoltaic. Firstly, aiming at the problem of centralized sampling of Monte Carlo method in risk assessment of distribution system, a day-night segmented Monte Carlo (MC) sampling method is proposed to generate a large number of day-night sampling scenarios. Secondly, the Gaussian mixture model is used to fit the probability density of the voltage obtained from probabilistic power flow calculations, concurrently, the utility preference exponential function characterizes the severity of the over-limit, and a comprehensive evaluation model of voltage over-limit risk is constructed. Finally, the effectiveness and accuracy of the proposed method are verified by taking the improved IEEE 33-bus distribution system as an example. These results offer actionable insights for future risk assessments of new energy grid connections.

An review of research on liquid hydrogen leakage: regarding China’s hydrogen refueling stations

Hydrogen is regarded as the premier energy source for future sustainability and renewability. However, its distinct physicochemical properties render it prone to explosions in the event of a leak. Therefore, there is a need for more comprehensive research dealing with hydrogen leakage, explosion scenarios, and risk assessment. This paper provides an overview of the current hydrogen policies adopted in China. It reviews the processes of hydrogen refueling station construction and the thermophysical mechanisms of liquid hydrogen leakage. In this regard, the effects of various factors, including leakage rate, leakage time, leakage hole size, wind direction and speed, and building location, on the hydrogen leakage rate are analyzed and evaluated. Additionally, the impacts of different factors on hydrogen explosion overpressure are reported, including hydrogen concentration, wind speed, obstacles, and ignition position, in addition to the current applications of quantitative risk assessment methods in hydrogen refueling stations. Finally, the limitations of current research on liquid hydrogen leakage and explosion accidents are highlighted, along with the shortcomings of current risk assessment methods for liquid hydrogen refueling stations.

Preliminary Evaluation of New Wearable Sensors to Study Incongruous Postures Held by Employees in Viticulture.

Musculoskeletal Disorders (MSDs) stand as a prominent cause of injuries in modern agriculture. Scientific research has highlighted a causal link between MSDs and awkward working postures. Several methods for the evaluation of working postures, and related risks, have been developed such as the Rapid Upper Limb Assessment (RULA). Nevertheless, these methods are generally applied with manual measurements on pictures or videos. As a consequence, their applicability could be scarce, and their effectiveness could be limited. The use of wearable sensors to collect kinetic data could facilitate the use of these methods for risk assessment. Nevertheless, the existing system may not be usable in the agricultural and vine sectors because of its cost, robustness and versatility to the various anthropometric characteristics of workers. The aim of this study was to develop a technology capable of collecting accurate data about uncomfortable postures and repetitive movements typical of vine workers. Specific objectives of the project were the development of a low-cost, robust, and wearable device, which could measure data about wrist angles and workers' hand positions during possible viticultural operations. Furthermore, the project was meant to test its use to evaluate incongruous postures and repetitive movements of workers' hand positions during pruning operations in vineyard. The developed sensor had 3-axis accelerometers and a gyroscope, and it could monitor the positions of the hand-wrist-forearm musculoskeletal system when moving. When such a sensor was applied to the study of a real case, such as the pruning of a vines, it permitted the evaluation of a simulated sequence of pruning and the quantification of the levels of risk induced by this type of agricultural activity.

Progress and prospects of safety assessment methods of medicinal and food homologous substances

Food and medicinal substances(FAMS) with both edible and medicinal uses have a long history in China, being an important part of China's excellent traditional culture and traditional Chinese medicine(TCM). The legal management of FAMS is in the form of catalogue, which has a history of nearly 40 years. More than 100 substances have been included in the China's FAMS catalogue. According to the Regulation of Food and Medicinal Substances Catalogue, safety assessment is a basis for substances to be included in the catalogue. The safety assessment of FAMS should follow the principles and requirements of food safety risk assessment. However, FAMS is a complex mixture, and the nature and data adequacy of the assessed substance should be comprehensively considered. Different eva-luation models and methods should be selected according to the principle of case analysis. With the development of next-generation technologies such as big data, artificial intelligence, high-throughput and high-content in vitro testing, and computational toxicology and the trend of increasing edible substances with medicinal effects applying for the inclusion in the China's FAMS catalogue, the methods of risk assessment are applied in the management of FAMS, novel food products, and local characteristic food products, playing a scientific role. This paper systematically reviews the methods, challenges, and prospects of safety assessment of FAMS.

A spatiotemporal data mining method for advanced prediction and assessment of large combined excavation-induced wall deformations and risks

A holistic and precise assessment of retaining wall deformations is critical for on-site risk management of large combined deep excavation projects, where the risk-related points are highly dispersed, evolving, and interacting. Despite extensive exploration of this topic in previous studies, the omission of intricate spatiotemporal characteristics of wall deformations has resulted in diminished prediction accuracy and stability. To mitigate this deficiency, a spatiotemporal characteristics matrix for all data points and time series was first generated for a deep excavation scenario and used as input for a new hybrid model that combines convolutional neural network (CNN) and long short-term memory (LSTM) with incorporated attention mechanism (CNN-LSTM-Att), which enables the cross-learning mechanism and improves interpretability. In addition, by leveraging the attention weight, a new risk assessment index for retaining wall deformations across various scenarios was formulated. Then the proposed method was applied in a large combined deep excavation in Shanghai, China. The results show that: (1) The incorporation of fed-in characteristic data and the attention mechanism enables the proposed method to produce satisfactory prediction results for the holistic spatiotemporal distribution of a large combined excavation; (2) Compared with other published models, the proposed model shows much better prediction accuracy, interpretability, and stability, especially in medium- and long-term predictions; and (3) The new risk assessment index serves as a reliable decision-making tool for assessing the risk evolution of retaining wall deformations and provides valuable guidance for effective risk management in multi-scenario excavation projects.

Risk Assessment Method for Forecasting Time-Dependent Aging Effects on Corrosion Rate: Preemptive Bridge Assets Management

Risk Assessment Method for Forecasting Time-Dependent Aging Effects on Corrosion Rate: Preemptive Bridge Assets Management

Modern Instrumental Methods of Diagnostics and Risk Assessment of Developing Antitumor Therapy Cardiovasculotoxicity.

The most important component of cardio-oncology is the assessment of the risk of development and diagnosis of cardiovascular toxicity of the antitumor therapy, the detection of which is largely based on visualization of the cardiovascular system. The article addresses up-to-date methods of non-invasive visualization of the heart and blood vessels, according to the 2022 European Society of Cardiology Clinical Guidelines on cardio-oncology. Also, the article discusses promising cardiovascular imaging techniques that are not yet included in the guidelines: assessment of coronary calcium using multislice computed tomography and positron emission computed tomography with 18F-labeled 2-deoxy-2-fluoro-d-glucose.

Oil-based drilling cutting pyrolysis residues-recycled fine powder sintered ceramsite: Basic properties, microsintering mechanism, lightweight concrete application and heavy metals solidification

Oil-based Drilling Cutting Pyrolysis Residue (ODPR) is a waste produced during oilfield drilling using oil-based mud. Recycled Fine Powder (RFP) consists of particles less than 0.16 mm, crushed and sieved from waste concrete. China's solid waste is characterized by high production, low utilization rates, and high pollution levels. This study explores the feasibility of preparing ceramsite from ODPR and RFP. By examining the effects of varying temperatures and proportions on the macroscopic and microscopic properties of ODPR-RFP ceramsite (ORC), the optimal process was determined: ODPR: RFP = 7:3, 2 % borax flux, 10 minutes ball milling, 1200℃ sintering temperature, and 30 minutes insulation. The resulting ORC, with a bulk density of 1120 kg/m³, cylinder compression strength of 10.50 MPa, and water absorption rate of 7.8 %, meets the "Lightweight aggregates and its test methods (GT/B17431.2)" standard. Batch production of ORC products of various sizes was conducted to evaluate their practical application in LC30 lightweight aggregate concrete. Replacing the aggregate in lightweight concrete with ORC yielded a concrete with excellent mixing performance, reaching a maximum strength of 31.2 MPa after 7d and 44.8 MPa after 28d. The damage pattern of ORC lightweight concrete is characterized by longitudinal splitting, with varied crack initiation and expansion paths. In the interfacial transition zone of ORC concrete, the ORC form a strong bond with the cement mortar, enhancing the strength of the lightweight concrete. Additionally, the leaching of heavy metals (HMs) from the ORC was examined to assess potential environmental pollution. The results indicated that preparing ORC from these two types of solid waste can effectively immobilize HMs, with a solidification rate of up to 92.10 %. Pb with high content is mainly solidified in the form of solid solution to form (Ba, Pb) SO4. The ecological risk assessment method for HMs shows that using this solid waste and process to prepare ORC does not pose HMs risks and is an environmentally friendly building material.

Estimating the burden of atrial fibrillation and atrial flutter with projection to 2050 in Iran

Atrial fibrillation (AF)/atrial flutter (AFL) is the most common cardiac tachyarrhythmia, with an increasing trend in its burden in recent years. However, the burden of AF/AFL in Iran remains unclear. This study aimed to estimate the burden of AF/AFL and its attributable risk factors from 1990 to 2019 at national and subnational levels. Using the comparative risk assessment method of the Global Burden of Disease (GBD) Study 2019, we extracted data on AF/AFL incidence, prevalence, deaths, disability-adjusted life years (DALYs), and their age-standardized rates from 1990 to 2019 and analyzed them based on by age, sex, and socio-demographic index (SDI). The percentage contribution of AF/AFL major risk factors was calculated. Moreover, the AF/AFL burden in 2050 was projected using the United Nations world population prospect data. In 2019, there were 339.1 (259.4–433.7) thousand AF/AFL patients in Iran, with 30.2 (23.2–38.5) thousand new cases, 1.7 (1.5–2) thousand deaths and 48 (37.7–60.5) thousand DALYs. Females and 50–69-year-old patients recorded a higher burden for AF/AFL; however, the increasing trend was more pronounced in males and more than 85-year-old patients. High systolic blood pressure and elevated body mass index (BMI) were the predominant attributable risk factors for AF/AFL-related deaths and DALYs. It is estimated that in 2050, the number of AF/AFL patients will increase to 1.1 million people, the incidence of AF/AFL will increase to 91 thousand patients, and the number of AF/AFL-related deaths and DALYs will surge to 7.2 and 170.8 thousand, respectively. Despite advancements in prevention and treatment, AF/AFL remains a major public health problem in Iran. Given its largely preventable and treatable nature, more cost-effective strategies are required to target modifiable risk factors, especially within susceptible age and sex groups.

Screening Patients with Type 2 Diabetes at High Risk of Obstructive Sleep Apnea: A Single Tertiary Center Experience

Objective: Current guidelines suggest screening patients with type 2 diabetes (T2D) for obstructive sleep apnea (OSA). However, there is no consensus regarding the optimal method for OSA risk assessment. We aimed to identify those with diabetes who are at high risk for OSA and investigate the concordance among questionnaires utilized in assessing high OSA risk. Method: STOP, STOP-BANG, and Berlin questionnaires for the assessment of the risk of OSA and the Epworth Sleepiness Scale (ESS) for an investigation of daytime sleepiness were utilized. Results: We included 108 patients, with a median HbA1c of 7.5%, a BMI of 30.7 kg/m², and waist and neck circumferences measuring 104.3 cm and 38.9 cm, respectively. On ESS, 10.2% of patients had excessive daytime sleepiness. According to Berlin (38.9%), the number of patients at high risk of OSA was found to be lower than that of in STOP (53.7%) and STOP-BANG (68.5%) questionnaires. For patients with a BMI

Dynamic risk assessment of Uncertain Random System considering operator's simple emergency-stop action in short time window

Human-machine systems can be considered as typical Uncertain Random Systems (URS). In human-machine systems, operator's simple emergency-stop actions act as a vital soft barrier. Conventional Human Reliability Analyses face challenges in evaluating operator's simple emergency-stop action due to their static characteristics, incompatibility with short time windows, and problems posed by small samples. This paper provides a novel solution to risk assessment of human-machine systems involving operator's simple emergency-stop mechanism. Specifically, an evaluation method of operator's simple emergency-stop action is established, where human cognition is decomposed according to its temporal and logical dimensions, key indicators of human sub-cognition are evaluated, and uncertainty theory is used to integrate these indicators. The output of proposed method is uncertainty of operator's behavior (UOB), which can offer more information than traditional Human Error Probability (HEP) and can be readily converted into uncertainty of human error. Further, a precise simulation method for dynamic risk assessment of Uncertain Random Systems is developed, in which the integration of the UOB is achieved. A case study demonstrates the effectiveness of the proposed methods, and its results show that the proposed methods can clearly reflect the differences in system risk under short time window conditions that have minor distinctions.

Теоретичні засади розвитку системи управління ризиками на підприємствах лісопромислового комплексу

In the article, a comprehensive study of the theoretical foundations of developing the risk management system at the enterprises of the forestry complex is carried out. The essence and classification of the main risks inherent in this industry are revealed, including environmental (climate change, fires, forest degradation), economic (wood price fluctuations, globalization), and technological and social factors. Modern scientific approaches to risk management, in particular international standards (COSO, ISO 31000), and applied risk assessment methods, both quantitative and qualitative, are analyzed. The specificity of environmental risks is particularly emphasized due to their importance for the forestry sector. The proposed systemic approach to risk management includes integrating innovative technologies such as geographic information systems (GIS), drone surveillance, and artificial intelligence for more effective forest monitoring and risk prediction. This allows enterprises to be flexible in responding to threats and reduce their vulnerability to external influences. It also stressed the urgency of improving management processes through the adaptation of international experience, particularly in the forestry sector. This global collaboration in risk management is crucial for a sustainable development strategy that balances the economic interests of enterprises and the preservation of environmental safety. An innovative approach to risk management based on the introduction of digital technologies allows for increased effectiveness in risk assessment and management, which becomes an important tool for ensuring the long-term stability and competitiveness of enterprises in the forestry complex in the context of global changes. Keywords: risk management, forest industry complex, environmental and economic risks, innovative technologies, sustainable development, system approach, monitoring.

Protocol of health screening related to occupational diseases in 100 000 workers in critical sectors: a cross-sectional study with worksite risk assessment

BackgroundOccupational diseases are one of the most important health problems related to employment However, in Malaysia, there are few epidemiological studies discussing these issues, especially among workers in the industry....

A Robust Method for Simultaneous Determination and Risk Assessment of Multiresidual Pesticides in Fishery Products.

In this study, we developed and validated a multiresidue analytical method for the simultaneous detection of 24 pesticides in fishery products. Using the EN15662 extraction method and C18 as the adsorbent for purification, the validation results complied with Codex guidelines, achieving recovery rates between 70% and 120% and relative standard deviation values (%RSD) within 20%, indicating excellent performance. The limit of detection ranged from 0.25 to 0.8 ng/kg, and the limit of quantification was between 3 and 10 ng/g, providing sufficient sensitivity to comply with future regulatory standards. The calibration curves for all 24 pesticides exhibited great linearity (R2 > 0.98), also satisfying the Codex requirements. The matrix effect was less than 30% for some pesticides-within ±20%-indicating minimal interference from impurities. An analysis of 300 fishery samples from nine regions across South Korea detected lufenuron at 10 ng/g in eels; however, the risk assessment was below 0.19%, posing no significant hazard to public health. This newly developed analytical method proved effective for the multi-analysis of pesticide residues in fishery products, offering rapid and reliable monitoring of the import and export safety of fishery products.

A detailed methodology for estimating health-related hazards of workplace exposure to indoor formaldehyde vapours

A comprehensive risk assessment method was applied to examine the risks associated with airborne formaldehyde occupational exposure among hospital laboratory staff. The method assessed exposure levels and health impacts by integrating area and personal air sampling, biological monitoring, and self-reported health data. Samples were collected from 74 workplaces across various departments using NIOSH method 3500 and were analyzed via UV-vis spectrophotometry. The data showed significant differences in exposure levels between departments (p≤0.05) and confirmed the efficacy of the method in identifying risk differences. Despite average personal exposure levels being measured lower than occupational limits, individual assessments indicated that some participants surpassed these limits, emphasizing the necessity of personal monitoring for workers with higher risks. The high prevalence of respiratory symptoms, such as cough and wheezing among staff, indicated the need for further investigation and targeted interventions. Although estimated cancer and non-cancer risks were within safe thresholds, the study emphasized the importance of continuous exposure monitoring and the implementation of effective control measures in hospital laboratory departments with formaldehyde emission. This integrated method improved the reliability and generalizability of formaldehyde exposure risk assessments and aided in the development of safe occupational health practices.•The method integrated personal and area sampling with advanced calibration for precise occupational exposure evaluation in laboratories.•The method used of biomarkers to assess formaldehyde absorption in the body estimating both cancerous and non-cancerous health risks associated with occupational exposure.•Addressed traditional method limitations and integrated risk components to improve data reliability for workplace safety and health risk management.

Ocean windspeeds forecast by Gaidai multivariate risk assessment method, utilizing deconvolution scheme

The current work presents spatiotemporal analysis of areal windspeeds, using state-of-the-art Gaidai multivariate hazards evaluation approach. Environmental dynamic systems being challenging to forecast using existing reliability methods due to their high dimensionality and intricate nonlinear cross-correlations between different environmental system essential dimensions or components. Developing novel multivariate reliability methods for dynamic environmental systems may assist contemporary research on the global climate change effects. Multivariate Gaidai risks evaluation approach is especially well-suited for multi-dimensional structural and environmental dynamic systems, that have been monitored physically or numerically simulated across a representative time-lapse. The current study made use of raw in-situ windspeed data, collected by NOAA (i.e., National Oceanic and Atmospheric Administration) buoys near the Hawaiian Islands in the North Pacific. Resilient island communities/infrastructure can be designed, using advocated multivariate risk/hazard assessment methodology, particularly those that are close to the ocean and hence subject to extreme weather.As was demonstrated in this study, even given limited underlying dataset, it is feasible to conservatively estimate environmental system’s hazard risks. Novel non-parametric deconvolution extrapolation scheme has been utilized to accurately assess hazard risks.

Assessing spatiotemporal heterogeneity of coastal organic nonpoint source pollution via soil erosion in Yellow River Delta, China

China has been facing severe organic pollution and the nonpoint source export from surface soil is usually overlooked in coastal areas. In this paper, from the perspective of catchment and attenuation, we have constructed a risk assessment method for coastal nonpoint source pollution (NSP) by applying the revised universal soil loss equation (RUSLE) and geostatistical analysis. Combined with the soil and water monitoring data, we have simulated regional NSP risks originating from surface soil organic matter (SOM) in the Yellow River Delta (YRD). Field surveys have verified the significant positive correlations between watershed SOM exporting risks and estuarine chemical oxygen demand (COD) fluxes during the rainy season. There present obvious logarithmic relations between the COD fluxes and the rainfall quantities, and the surface organic NSP risks. Larger NSP contributing sources are mainly located in the areas with higher soil exposure and stronger land-sea interactions. It should focus on the agricultural areas and improve relevant fertilizing and tillage methods to reduce source-exporting risks. Additionally, the summer rainfall concentrating periods need to be controlled emphatically, and vegetation-improving strategies need to be supplemented with the spatiotemporal-specific managements. This study provides a new insight for getting early terrestrial warning information for offshore organic water pollution, and presents research references for similar regional NSP issues.

Risk Assessment Method for Distributed Power Distribution Networks Considering Network Dynamic Reconstruction

A new safety assessment framework has been proposed to address the operational risks of the integration of wind power and photovoltaic grid, which integrates the characteristics of distributed power sources with the dynamic reconfiguration requirements of the distribution grid. The framework comprehensively considers the impacts of wind power and photovoltaic output uncertainties, as well as load fluctuations, on the stability of the distribution grid. It also evaluates the safety under different operational states of the distribution grid. Using Halton sequence sampling technology to accurately simulate the output of distributed power sources and the status of system components, combined with CPLEX optimisation for solving, a dynamic reconfiguration model is constructed to address potential faults in the distribution grid. Introducing the combined weighting method, a comprehensive risk assessment system for voltage violations, power flow violations, and load shedding has been constructed. The effectiveness of this method has been validated through simulations on the IEEE33 bus and IEEE118 bus systems, providing new insights to improve the safety and reliability of distribution grids.

Risk Assessment of Bird Collisions with a Wind Turbine Based on Flight Parameters

The study addresses the challenge of bird collisions with wind turbines by developing an autonomous risk assessment method. The research uses data from the stereoscopic Bird Protection System (BPS) to anticipate potential collision threats by analysing flight parameters and distance from turbines. The danger factor depends on the flight characteristics of the identified bird species and the parameters of the wind turbine control system. The paper proposes an online quantitative risk assessment model that operates in real time, with the aim of minimising unnecessary turbine shutdowns while improving bird conservation. The model is validated through field data from bird flights. The findings suggest that adaptive management of turbine operations based on real-time bird flight data can significantly reduce collision risks without compromising energy production efficiency. The research underscores the balance between ecological considerations and the economic viability of wind energy, proposing an adaptive strategy that reduces unnecessary turbine stoppages while ensuring the safety of avian species.

Research on Construction Risk Assessment of Long-Span Cantilever Casting Concrete Arch Bridges Based on Triangular Fuzzy Theory and Bayesian Networks

Considering the complex construction processes involved, there are significant risks during the construction of long-span cantilever casting arch bridges. In this study, a risk assessment method for the construction process of cantilever casting concrete arch bridges was developed. The compositional elements and characteristics of safety risks in the construction of cantilever casting concrete arch bridges were clarified, and a safety risk source list that includes seven major risk sources and thirty-three minor risk sources was formed. Then, a Bayesian model for the risk analysis of cantilever casting concrete arch bridge construction was established, and a method was proposed to determine the prior and posterior probabilities of the Bayesian network using triangular fuzzy numbers. This method fully utilizes the experience of experts while avoiding the subjectivity of expert opinions. A cantilever casting concrete open spandrel arch bridge (Bridge A) with a total span length of 287 m was taken as an example, and a safety risk assessment was conducted during its construction process. The calculation results show that the construction safety risk level of Bridge A was level III. This engineering application verified the feasibility of determining key node parameters of the Bayesian network using triangular fuzzy numbers.