Safety Risk Analysis Research Articles

Brief Analysis of Safety Risks and Emergency System Construction of Electric Power Production under the New Situation

Brief Analysis of Safety Risks and Emergency System Construction of Electric Power Production under the New Situation

Bayesian network safety risk analysis for the dam–foundation system using Monte Carlo simulation

Gravity dams are mostly located in alpine and gorge regions with complex terrain and geological conditions, facing challenges of large peak flows, developed weak structural planes, high-stress levels, etc. The determination of failure risks of different failure modes in gravity dams is closely related to structural characteristics, materials properties, and loading conditions. However, the failure risks in the traditional risk analysis methods are usually calculated based on the expert evaluation methods and statistical data, ignoring the uniqueness of dam characteristics, and leading to an unreasonable risk assessment. Therefore, an improved probabilistic risk analysis method for the dam–foundation system using Bayesian network (BN) and Monte Carlo simulation is proposed in this study, which considers the combined action of overtopping, foundation stability, and structural failure. Based on the Monte-Carlo method, the risk analysis of overtopping is proposed by considering the influences of peak flows and maximum wind speeds, and the dam–foundation system is developed by establishing response surface equations of performance functions. Then, the BN safety risk analysis method for gravity dams is formed. This improved method is applied in the GD gravity dam project and finds that the system risk is 2.10 × 10−3. The most critical failure factor is the foundation instability, and the importance and sensitivity analysis also proved it, implying the validity and reasonability of the proposed method. Thus, the BN safety risk analysis method for gravity dams enables an improved and more reliable estimate of dam risk.

A Case Study on Condition Assessment of Fire-Damaged RC Members of Turbo-Generator

Many researchers across the globe have carried out fire safety risk analysis to gather evidence and pertinent data for different Reinforced Cement Concrete (RCC) members exposed to fire. Assessment of fire-damaged structures furnishes the minute details of the effect of fire on the properties of concrete.The study indicates the condition assessment of the turbo-generator (TG) unit, comprises of concrete bearing pedestals, deck and supporting columns. The research was conducted using Non-Destructive Testing (NDT) techniques using Rebound hammer test, Ultrasonic Pulse Velocity (UPV) test, Concrete Cover measurement, Carbonation and Crack depth measurements followed by microstructural studies using an X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), Optical Microscope (OM), and Mercury Intrusion Porosimetry (MIP). The samples were taken from a fire-damaged concrete bearing pedestal B2 and a non-fire-damaged concrete bearing pedestal B4 of the TG unit. The approach enabled us to find the extent of damage to the RCC members exposed to fire. The above mentioned test witnessed that the concrete bearing pedestal B2 was the moderately distressed member, expressed doubtful quality of concrete, higher porosity, reduced residual compressive strength and reduction in yield strength of steel. However minor distress in form of crushing at the top grout portion was observed in concrete bearing pedestal B4, and no apparent distress was observed in supporting columns of TG unit. Based on the distress identified, repair and remedial measures were proposed to concrete bearing pedestals in order to improve the performance of the TG unit.

Work Safety Risk Analysis Using Hirarc Method In Iron Production Area PT. Java Rakindo

<p><em>HIRARC (Hazard Identification, Risk Assessment and Risk Control) is a series of processes to identify hazards that can occur in routine or non-routine activities in the company, then carry out a risk assessment of these hazards and then create a hazard control program so that the risk level can be minimized to a lower level. with the aim of preventing accidents. The implementation of K3 begins with good planning including, identification of hazards, assessment and risk control which are part of risk management. HIRARC is what determines the direction of K3 implementation in the company. This study aims to determine the risk analysis of occupational safety and health in the work production section of PT. Java Rakindo This type of research is a quantitative study using a descriptive approach. The population in this study were all workers in the work environment at PT. Java Rakindo with a total sampling technique that is as many as 25 respondents who are in the iron production section. The data were analyzed using univariate to describe the respondent's characteristics and to analyze each variable. K3 risk analysis using the HIRARC method obtained an assessment that the most dominant K3 hazard is substitution hazard of 72% (high). K3 risk assessment with a moderate level of risk category (Medium) of 84%. Administrative control of 92% and control of PPE by 100% so that it can be said that it has not been fully implemented (50%-90%).</em></p><p><em> </em></p>

Multifactor Logistic Analysis to Explore the Risk Factors of Safety Risks in the Transport of Critically Ill Patients with ICU and the Improvement of Nursing Strategies.

Objective Multivariate logistic analysis was employed to explore the risk factors of safety risks in the transport of critically ill patients with ICU and the improvement of nursing strategies. Methods Two hundred critical transport patients with ICU treated in our hospital from January 2019 to April 2021 were enrolled. According to the occurrence of unsafe events in transit, the patients were assigned to the control group (165 cases without unsafe events, n = 165) and the study group (35 cases with safety incidents, n = 35). Multivariate logistic analysis was employed to explore the risk factors of safety risks in the transport of critically ill patients with ICU and to enhance nursing strategies. Results (1) General data of the subjects: among the 200 critically ill patients with ICU who needed in-hospital transport, the age ranged from 18 to 85 years with an average age of 52.48 ± 3.31, including 89 males and 111 females. There were 35 cases of gastrointestinal bleeding, 16 cases of respiratory failure, 23 cases of heart failure, 43 cases of myocardial infarction, 26 cases of cerebrovascular accident, 14 cases of ectopic pregnancy, 25 cases of severe injury, and 18 cases of mechanical ventilation. There were 35 cases in the study group with accidents and 45 cases in group B without accidents. (2) Among the 200 patients, 35 patients had complications during the transit process in the intermediate people's court, with an incidence rate of 17.5%. It included blood pressure fluctuation (n = 6), artificial airway obstruction (n = 6), decrease in blood oxygen saturation (n = 10), dyspnea (n = 5), fall pain (n = 3), elevated intracranial pressure (n = 2), and other factors (n = 3). There exhibited no significant difference in blood oxygen saturation at each time point during transport (P > 0.05). There exhibited no significant difference in SpO2 before transport. The comparison of 5 min and 10 min blood oxygen saturation during transit in the study group was lower compared to the control group (P < 0.05). (3) In a univariate analysis of safety risks for critically ill ICU patients, home escorts did not show significant differences in hospital transport for critically ill ICU patients (P > 0.05). There were significant differences in terms of age, patient's condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline (P < 0.05). The results of multivariate logistic regression analysis indicated that age, patient's condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline were the risk factors affecting the safe transport of critically ill patients (P < 0.05). Conclusion Age, patient's condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline are the independent risk factors that affect the safe transport of emergency or ICU critically ill patients. Therefore, in order to reduce the risk of transshipment, we must enhance the safety awareness of escorts, strengthen the management and training of escorts, promote rules and regulations, and formulate dangerous plans, so as to eliminate the occurrence of unsafe factors.

Improved LS-SVM Method for Flight Data Fitting of Civil Aircraft Flying at High Plateau

High-plateau flight safety is an important research hotspot in the field of civil aviation transportation safety science. Complete and accurate high-plateau flight data are beneficial for effectively assessing and improving the flight status of civil aviation aircrafts, and can play an important role in carrying out high-plateau operation safety risk analysis. Due to various reasons, such as low temperature and low pressure in the harsh environment of high-plateau flights, the abnormality or loss of the quick access recorder (QAR) data affects the flight data processing and analysis results to a certain extent. In order to effectively solve this problem, an improved least squares support vector machines method is proposed. Firstly, the entropy weight method is used to obtain the index weights. Secondly, the principal component analysis method is used for dimensionality reduction. Finally, the data are fitted and repaired by selecting appropriate eigenvalues through multiple tests based on the LS-SVM. In order to verify the effectiveness of this method, the QAR data related to multiple real plateau flights are used for testing and comparing with the improved method for verification. The fitting results show that the error measurement index mean absolute error of the average error accuracy is more than 90%, and the error index value equal coefficient reaches a high fit degree of 0.99, which proves that the improved least squares support vector machines machine learning model can fit and supplement the missing QAR data in the plateau area through historical flight data to effectively meet application needs.

Safety Risk Analysis of a New Design of Basalt Fiber Gabion Slope Based on Improved 3D Discrete Element Method and Monitoring Data.

Gabion has been extensively used in retaining walls and slope protection. This study carries out a safety risk analysis of a new structure combining basalt fiber reinforcement (BFR) and the traditional gabion structure. The micro-parameters of BFR and soil were calibrated by using the 3D discrete element method after the tensile test of BFR was completed. The mechanical property of the gabion unit was investigated by using a refined model and a numerical test of uniaxial compression. This work developed a simplified method to simulate the seepage effect. The stress condition and sliding displacement between gabions were also investigated. Deformation, stress, and porosity were all used to evaluate the stability of the new type of gabion slope. According to this study, BFR has a tensile strength of 68.22 MPa, and the safety factor increased by 25.68% after using these BFR gabions. The damage is mainly manifested by bending the BFRs and the dislocation of the gabion units, as the slope does not slip. It is indicated this novel gabion structure has a lower safety risk compared to traditional ones, and thus can be popularized and used in retaining walls and slope protection.

Analysis of Occupational Safety and Health Risk Using the HAZOPS Method and ergonomics Approach (RULA and REBA) at UD. Sekar Surabaya

UD. Sekar Surabaya is a small and medium enterprise, which produces uyel crackers. In the development of cracker production activities, of course there is a production process that is dangerous (hazard). If not controlled this potential hazard can cause various problems, such as fatigue, musculoskeletal complaints, the risk of injury, and the most serious work accidents. The purpose of this research is to help UD. Sekar Surabaya identifies hazards in the production process to control and prevent potential hazards in the work area. To find out the ergonomic hazards, the HAZOPS method was used for identification, then followed by the NMB questionnaire to determine the part of the worker's body that felt pain. Then use the RULA and REBA methods to calculate body posture, where the results of these calculations will be used as suggestions for improvement to reduce the risk of work accidents. From the results of the hazard analysis, it can be seen that the hazards that can cause work accidents are attitudes and the physical work environment. In addition, there are ergonomic risks in the cracker production process. The risks experienced by workers are musculoskeletal complaints and pain in the neck, shoulders, arms, back, hands and feet. The recommended stations for improvement are the process of taking flour from the warehouse, the process of inserting the rack into the oven, the process of lifting the ducks to the drying station, and the process of frying crackers.

Fuzzy FMEA for the safety risk analysis of underground coal mining (a case study in Iran)

ABSTRACT Hazards in underground coal mines create an unsafe working environment for workers and equipment. This paper aims to analyze the safety risk in underground coal mining using an improved Failure Mode and Effect Analysis (FMEA) method. To achieve this, the causes of the main events that threaten the safety of the working environment were identified and discussed in a case study; Parvadeh Tabas coal mine, Iran. The Analytical Hierarchy Process (AHP) was applied to calculate the importance degree of each hazard. Then, the FMEA approach under the fuzzy environment was used for the safety risk analysis. Regarding the results of this study, the outburst-related hazards, failure to provide sufficient compressed air, and the electrical locomotive-related hazards have the highest level of safety risk. In this concept, it is possible to identify the leading causes of accidents and propose practical solutions to improve the safety conditions of the mine working places.

Safety Measures and Risk Analysis for Outdoor Recreation Technicians and Practitioners: A Systematic Review

There is no expectation to suppress all accidents in the outdoor recreation sector; nevertheless, it is expected that all possible safety measures are taken in order to minimize the risk of accidents. The objective of this study was to systematize the knowledge regarding recommended and used safety measures and risk assessments for technicians and outdoor recreation practitioners. We conducted a systematic review on PubMed, BVS, SciELO, Science Direct, ABI/INFORM, Spinger, Web of Knowledge, and Esmerald full text databases, up to February 2021. The eligible criteria followed the PICOS strategy; the included risk assessment studies on outdoor recreation (according to its definition) had methodological quality, were indexed, and peer reviewed. Ten studies, from ten countries, fulfilled these specifications, which focused on different approaches. Five studies focused on risk perception, four studies focused on safety practices, injuries, and risk assessment; three studies addressed safe behaviors; two studies addressed equipment- and risk matrix-related themes. We concluded that there was a concern for this topic, and the 28 mentioned measures could provide important information regarding health and prevention. These measures could be used to develop safety strategies and risk reduction, aimed at reducing accidents in outdoor recreation activities. In order to evaluate the pertinence and importance of the mentioned measures, namely risk perception, safe practices, sport injuries, risk analysis, safe behaviors, as well as equipment and risk assessment matrices, further investigation is needed using experimental or observational designs. These strategies and procedures can contribute to enhanced interventions by technicians with higher security and quality, and therefore, improved well-being and satisfaction of practitioners.

STRATEGI PENINGKATAN EKSPOR PRODUK KELAUTAN DAN PERIKANAN KE PASAR EROPA

Fishery resources produced amounted to 12.5 million tons/year with an economic value of $2.04 billion USD. From 2016 - 2020 Indonesia's fisheries export sector continues to experience a positive trend by continuing rises with an increase of 5.72% and in 2020 the value was reached of $5.205 billion USD. The export sector who dominates is with fishery products have code 0303, and fishery commodities types shrimp, tuna, skipjack, seaweed, squid-octopus, crabs, etc. There are several obstacles i.e strict on standards of trade rules in the EU, the absence of Indonesia's free trade agreement with the EU, producers that tend to change frequently and the low quality of fishermen's human resources and not yet in accordance with the quality standards of fishery products produced. In increasing exports of Indonesia's fisheries and marine sector, several strategies are needed, i.e;1) Optimization of the potential of fish resources to increase export activities; 2) Enhance cooperation with other countries and with international institutions related to the production and quality supervision of fishery products; 3) Improved WPP-based national fisheries management; 4) Empowerment and optimization of catches of small fishermen by applying international quality standards; 5) Coaching on handling export standard fishery products; 6) Improvement of infrastructure, facilities, especially to carry out C3Q. 7) Optimization of SLIN system; 8) Increased role of government in maintaining food safety and ecolabelling; 9) Promote the principle of sustainable fisheries management; 10) Establish a special institution to coordinate the implementation of fishery product safety research and risk analysis of fishery products as a basis in determining food safety goals; 11) Synergize between government as a regulator and employers as a executor.

System Dynamics Analysis of Construction Safety Risk considering Existing Railway Lines.

Existing railway line (ERL) construction safety has received significant attention during the past decades due to the high accident rate and the difficulty of progress development under the limited synthesis construction time schedule (SCTS). However, the previous literature is dominated by the construction safety of new railway lines, while research on construction safety of ERLs is limited. This paper analyzed the interactions and causal relationships between construction safety risk (CSR) and multiple factors and classified feedback loops. Hence, a system dynamics model was developed, and a series of tests were conducted to simulate the evolution of CSR under different group environments. The results indicated that (1) the CSR considering ERLs is significantly relevant to the implementation degree of SCTS. For situations where there are more delays and more schedule pressure, construction safety accidents tend to have a higher level. (2) Work efficiency is negatively related to construction safety accidents probability. The increase of work intensity could reduce schedule pressure in the short term but could increase construction safety risk in a long time. Applying both appropriate work efficiency and work intensity may achieve an acceptable result. This paper adds to the knowledge of construction safety risk management in terms of implementation and offers lessons and references for future construction safety management considering ERLs.

A novel machine learning model for safety risk analysis in flywheel-battery hybrid energy storage system

Flywheel energy storage system (FESS) has been regarded as the most promising hybrid storage technique to manage the battery charging process of electric vehicles. Thanks to properly regulating with the FESS, the battery life can be significantly prolonged. In order to ensure the safety of the hybrid storage system, it is imperative to monitor the mechanical operation condition of the FESS. Because the rolling bearing is a critical mechanical component in the FESS, the performance degradation monitoring and remaining useful life (RUL) prediction of the rolling bearing must be performed. This paper proposes a new machine learning method for the construction of a health indicator to quantitatively evaluate the bearing health status. In this new method, the original feature set is firstly selected through three feature evaluation indicators and the principle component analysis (PCA) is employed to fuse the original feature set as a new health indicator. Then the primary trend of the health indicator is extracted by the empirical mode decomposition (EMD); and the Kriging model-based prediction method is proposed to predict the bearing RUL. The feasibility and superiority of the proposed method is verified through experimental test and analysis result shows that the root mean square error (RMSE) of the prediction is as small as 0.0425.

Occupational Health and Safety Risk Analysis in Construction Projects: A Systematic Literature Review

The construction service business world always wants the best results in every project activities carried out. One of the best desired outcomes is the timely completion of a construction project, but this is often not achieved for several reasons, one of which is occupational health and safety incidents that occurs in a construction project. Based on the background of the problem and the results of a literature review sourced from 40 journals from 2011-2021, the journals collected and reviewed discussed occupational health and safety in construction projects. Therefore, it is very necessary to implement an OHS (Occupational Health and Safety) management system during construction work. Occupational health and safety aims to create conditions that support work comfort for workers, so as to improve risk management. Using sources based on previous research, the following will identify the types of occupational safety and health risk factors that most often occur in construction work. The types of risks that will be discussed here will be divided into three types based on internal risk, external risk, and project risk. Types of risk are divided into two types, namely technical and non-technical risks. Based on data from a total of 40 studies that have been reviewed, there are 22 studies that have Project Risk as the risk that causes 76% of risk in a building construction project.

Assessment of operation safety risk for South-to-North Water Diversion Project: a fuzzy VIKOR-FMEA approach

Abstract The South-to-North Water Diversion Project (SNWDP) is a cross-basin large-scale water infrastructure, whose operational management faces many complex risks. This study constructs an operational safety risk analysis model based on fuzzy VIKOR-FMEA. First, the expert team used linguistic variables to evaluate the severity of each failure mode (S), frequency of occurrence (O), and difficulty of detection (D) in the failure mode and effects analysis (FMEA). Then, the fuzzy analytic hierarchy process (AHP) and the maximal deviation approach were integrated to carry out risk factor weights. The risk factor weight analysis matrix integrates the subjective and objective weights to obtain the comprehensive weights of the risk factors. Secondly, VIKOR is introduced to improve the traditional FMEA model and is used to calculate the risk priority number. The case study shows that untimely flood protection, irregular maintenance, and untimely emergency response are in the top order. Finally, it is compared with the traditional FMEA method, which verifies the feasibility and effectiveness of the proposed method, and provides a reference algorithm for risk analysis of operation management for the water diversion project.

Novel Iapso-Lstm Neural Network for Risk Analysis and Early Warning of Food Safety

Novel Iapso-Lstm Neural Network for Risk Analysis and Early Warning of Food Safety

SELECTION OF THE SAFETY RISK ANALYSIS TECHNIQUE MOST COMPATIBLE WITH NATURE, REQUIREMENTS AND RESOURCES OF MINING PROJECTS USING AN INTEGRATED FOLCHI-AHP METHOD

There are numerous safety risk analysis techniques. Moreover, no ideal method exists for all companies; hence, the selection of the method most congruous with nature of the intended project, as well as the needs and resources of a mining company is of particular significance. To address the issue, a mathematical model has been developed with the aid of the Folchi-AHP method, whereby safety experts can opt for the best technique after multiplying an impacting factors matrix by a correlation matrix. The former is created by the safety team in the decision-making time, and includes 15 evaluation criteria, while the latter is comprised of the relative weight of each criterion to each technique. To find these weights, 22 methods were compared to each other in terms of 15 criteria by 10 safety experts using the analytic hierarchy process (AHP). To ease computations, an Excel program was developed and investigated in four mining projects.

Simplifying the Complex: Pool Stage-Frequency Analysis of USACE’s Largest Reservoir

Lake Sakakawea in North Dakota, U.S.A., was formed following the closure of Garrison Dam in 1953 and is the largest U.S. Army Corps of Engineers (USACE) reservoir. It is the second of six mainstem reservoirs located in series on the Missouri River operated as a system by USACE. Critical for dam safety risk analysis, a pool stage-frequency curve, extending to water levels above the top of dam, was developed for an Issue Evaluation Study using a combination of tools, including Monte Carlo simulation with the recently released USACE reservoir frequency analysis software, RMCRFA. This paper describes the hydrologic tools leveraged to expedite the pool stage-frequency analysis and discusses the challenges overcome during the study. The methods used to reduce a complex reservoir system to a simplified single reservoir model are presented, and statistical challenges associated with mixed population rain/snow floods, paleofloods, and regulated basin data are discussed. The simplified approach was capable of incorporating a variety of hydrology inputs, while providing a reasonable approximation for the complex reservoir operations. The results were transparent and easily understood by decision makers tasked with making portfolio-wide investment decisions.

Span-based model for overlapping entity recognition and multi-relations classification in the food domain

&lt;abstract&gt;&lt;p&gt;Information extraction (IE) is an important part of the entire knowledge graph lifecycle. In the food domain, extracting information such as ingredient and cooking method from Chinese recipes is crucial to safety risk analysis and identification of ingredient. In comparison with English, due to the complex structure, the richness of information in word combination, and lack of tense, Chinese IE is much more challenging. This dilemma is particularly prominent in the food domain with high-density knowledge, imprecise syntactic structure. However, existing IE methods focus only on the features of entities in a sentence, such as context and position, and ignore features of the entity itself and the influence of self attributes on prediction of inter entity relationship. To solve the problems of overlapping entity recognition and multi-relations classification in the food domain, we propose a span-based model known as SpIE for IE. The SpIE uses the span representation for each possible candidate entity to capture span-level features, which transforms named entity recognition (NER) into a classification mission. Besides, SpIE feeds extra information about the entity into the relation classification (RC) model by considering the effect of entity's attributes (both the entity mention and entity type) on the relationship between entity pairs. We apply SpIE on two datasets and observe that SpIE significantly outperforms the previous neural approaches due to capture the feature of overlapping entity and entity attributes, and it remains very competitive in general IE.&lt;/p&gt;&lt;/abstract&gt;

A novel risk analysis approach for occupational safety using Bayesian Network and interval type-2 fuzzy sets: the case of underground mining

Occupational safety problems are no longer acceptable for any industrial environment. Lack of comprehensive and reliable evaluations for occupational safety causes many undesired events and harm to employees during the industrial process. In this study, it is aimed to develop an applicable risk analysis methodology for evaluating the undesired occupational events that occurred in the multi-process system where no historical accident records. The difficulty in obtaining and analyzing the data required for the determination of the occupational safety risks especially in the manually executed processes has been overcome with the Bayesian Network and interval type-2 fuzzy sets by using the expert judgments. While BN enables to development of a comprehensive reasoning approach about the occurrence of the events, interval type-2 fuzzy sets better represent the ambiguity in the judgments by covering the uncertainty in a wider mathematical range with less computational effort according to other fuzzy sets. During multi-processes in industrial activity, various occupational undesired events may occur, including rare events with very serious consequences or frequent events with very low severity consequences. To able to consider all kinds of events occurring in an industrial environment from a holistic risk perspective, a novel fuzzy scale for specifying the probability and consequence of the events are proposed by the interval type-2 fuzzy numbers. Therefore, all undesired events regardless the probability and consequence which may occur during the multi-processes in a system and the main root causes of these events can be observed within the proposed methodology. A case study is used to emphasize the effect of the proposed methodology for risk analysis of occupational safety in underground mining. The results have indicated that occupational safety education is the most contributing factor to occurring the undesired occupational events in underground mining. We believe that this study could help evaluate the safety risk of the multi-process systems comprehensively and holistically and proposing strategic planning for mitigating the occupational safety risks.