Probability Of Accidents Research Articles

A MODEL FOR ASSESSING SHIPPING SAFETY WITHIN PROJECT-ORIENTATED RISK MANAGEMENT BASED ON HUMAN ELEMENT

Safety risk management in shipping projects is an extremely important aspect aimed at ensuring the success of the project and the safety of all participants in the maritime transportation process. This paper presents an approach to assessing safety risks that considers multiple factors including equipment condition, external circumstances, and human factors. The risk assessment utilizes the probability of accidents and their consequences, as well as the weighting factors of each factor. The results of the assessment are interpreted using a scale that defines the hazard level. The proposed methodology can effectively identify, analyse and manage safety risks, which can contribute to the success and safety of shipping projects. The study also discusses the importance of dividing the crew into functional groups based on the operations performed, which helps to better identify the safety risk for each group. Safety risk assessment is conducted for each operation individually as well as for the entire project or multiple operations to provide a comprehensive safety assessment. The results of the study have shown the feasibility of the proposed method for assessing the safety risks of shipping projects and its suitability to the initial data “safety” taking into account its separate sides, features, as well as the constituent aspects of the concept, systematization of the ship's safety structure in order to develop solutions to improve integral safety and optimize decision-making in emergency situations. Achievement of the general purpose of shipping safety thus means realization of ways of reduction of influence of the human factor on the number of accidents, and an estimation of the degree of influence of a set of factors on a ship during operation.

Comprehensive analysis of the mining accident forecasting and risk assessment methodologies: Case study – Stanterg Mine

Purpose. This research aims to outline a methodology for accident forecasting and risk assessment in mining operations using the Stanterg Mine as a case study. It emphasises the crucial role of reliable mining accident reporting and accurate data processing in forecasting accidents and effectively managing risks during mining operations. Methods. The research paper analyzes various methodologies for forecasting mining accidents using Excel and Simple Linear Regression Method (SLRM) to analyse data selected from the Stanterg Mine accidents. Findings. The forecast indicates that on average there are about 3 accidents per month at the Stanterg Mine. The analysis, based on a one-month study of 42 reported accidents, and assuming a steady production rate, suggests an increased risk of accidents. This is supported by a thorough assessment using a 3×3 risk assessment matrix tailored to the Stanterg Mine. Stope mining is highlighted as the most hazardous area, associated with risks ranging from moderate to extreme levels. Originality. Mining accident analysis at the Stanterg Mine involves an examination of the incidents, including factors leading to accidents, encountered hazards and their consequences. Accident forecasting entails studying historical data, identifying patterns, and using predictive modelling to anticipate future incidents. This proactive approach enables mining companies to proactively address risks and take preventative measures, reducing the probability of accidents. Practical implications. The systematic processing and analysis of mining accidents has revealed valuable insights into the practical application of risk assessment in mining operations. The examination of accidents at the Stanterg Mine provides researchers with crucial knowledge for effective risk assessment and management in the mining sector.

Analysis of the Relationship between Speed Consistency and Traffic Accident Probability (on the Mojokerto-Surabaya Toll Road)

Vehicle speed consistency plays a crucial role in maintaining traffic safety, with speed limits set to reduce accident fatalities. While the direct impact of speed limits on vehicle speed is minimal, their implementation significantly influences driver behavior, with about 85% of drivers complying with speed limits. However, variables such as traffic volume, weather conditions, and travel urgency often cause drivers to be inconsistent in adhering to these limits, increasing accident risk. On the Mojokerto-Surabaya toll road, data from IRSMS Korlantas Polri and Jasa Marga recorded 193 accidents with 101 fatalities from 2018 to August 2023, mostly caused by driver behavior such as excessive speed. This study analyzes the relationship between speed consistency and accident probability on this road, highlighting accident issues due to speed violations and inconsistency at ramp off/on locations. Results show the importance of toll road infrastructure considering vehicle volume, identifying accident blackspots, and implementing urgent speed management as key factors in improving safety on the Surabaya-Mojokerto toll road. The findings emphasize the need for better traffic management and speed regulation to reduce fatal accident risks.

Effectiveness of countermeasure options for chemical facilities against the discharge of chemical substances into rivers caused by a large earthquake: case study of the Yodo river system in Osaka prefecture, Japan

Technological accidents triggered by natural hazards, which are commonly referred to as Natech events, are rare occurrences yet carry the potential for significant damage. Specifically, the release of hazardous chemicals into the aquatic environment and community water systems poses a grave threat to human health and society. Accordingly, we must conduct assessments that consider the potential consequences of these accidents. In this study, we examined the criteria for implementing spill protection measures to mitigate river spills of chemical substances using information on the amount of chemical substances and their toxicity. The countermeasure options readily available to employees at industrial plants and chemical storage sites where a chemical spill might originate included emergency shut-off valves, bunds and related spill containment structures, and other spill prevention measures. In this case study, a combination of countermeasure options was evaluated to examine the effectiveness of spill mitigation in the Yodo River located in the Kyoto Prefecture of Japan. Results of the case study showed that bunds were emerged as the most useful countermeasure option, reducing the probability of accidents occurring and impact of accidents. We also defined a methodology for calculating the chemical storage volumes appropriate for different countermeasures to ensure that the concentration of chemicals that could reach the water intake does not exceed the standard values. We believe that these methodologies can help chemical-handling companies make decisions when countermeasure options for responding to a chemical spill into a river. Chemical-handling companies can estimate the risk to downstream water treatment plants in the chemical spill, which can also help them consider mitigation measures.

Analysis of the impact of building shape on safety accidents

Preventing various types of safety accidents on construction sites with safety control efforts centered around site engineers has limitations. To resolve this issue, efforts have been made for the last decade to identify safety risk elements that arise during construction and have them reflected in the Design for Safety (DfS). Taking two buildings with the same total floor area for example, the building with a more complex shape or higher floors is expected to have a higher probability of safety accidents in DfS terms. However, little research is available that has used safety accident data from real construction to analyze the impact of building shape on safety accidents. One of the reasons is that many construction companies do not disclose safety accident data. The purpose of this study is to analyze the impact of building shape on safety accidents. For this research, actual project data collection including safety accidents and analysis on their correlation with each risk element were performed in series. As a result, it was demonstrated that R2 was 0.947 for the correlation between shape factor and safety accidents and R2 was 0.881 for the correlation between the number of building floors and safety accidents, showing that safety accidents are closely related to both elements. It is recommended according to the research findings that designers should take into account of building shape in order to perform more effective DfS and developers and constructors should add more safety facilities and manpower depending on building shape for the same total floor area.

Safety Evaluation and Influential Factor Analysis of Urban Expressway Diversion Areas Based on Non-Stationary Conflict Extremes

To evaluate the safety conditions of expressway exit areas with different exit forms, a safety analysis method based on the conflict extreme model is proposed. Based on video data from four typical urban expressway diversion areas, longitudinal conflicts and lateral conflicts were identified using time to collision and cross time to collision methods, respectively, and traffic parameters such as traffic flow were extracted. A Bayesian hierarchical conflict extreme model for joint conflict types was constructed by integrating the peak over threshold and Bayesian hierarchical approach. The threshold for conflicts was determined using the mean residual life plot and the threshold stability plot. Subsequently, a logarithmic link function for the scale parameter was established by combining different covariates. Then, the model parameters were estimated using the Markov chain Monte Carlo simulation method. Finally, based on the fitted distribution, a comprehensive safety evaluation and influential factor analysis were conducted for each diversion area. The results show that an increase in traffic flow and the ratio of large vehicles leads to a higher probability of traffic accidents. However, an increase in the average speed reduces the probability of traffic accidents. The construction form of the diversion area and the number of off-ramp lanes do not demonstrate an explicit relationship with the probability of traffic accidents. The research conclusion indicates that the Bayesian hierarchical extreme model can effectively utilize short-term observed conflicts for long-term crash estimation, and it has the potential to be applied in the field of safety evaluation.

Analysis of the Effect of Outdoor Thermal Comfort on Construction Accidents by Subcontractor Types

The impact of climate on construction site safety varies significantly depending on subcontractor types due to the diverse nature of workplaces and work methods. This study introduces a novel approach by categorizing construction work according to subcontractor types and assessing accident risk probabilistically through the Physiologically Equivalent Temperature (PET), an outdoor thermal comfort index. Additionally, a Hidden Markov Model (HMM)-based clustering methodology was proposed to classify new groups using PET and accident probability. This study proceeded in the following sequence: (i) collection and classification of data, (ii) PET calculation, (iii) calculation of accident probability, and (iv) clustering and Pearson correlation coefficient analysis. As a result of clustering, each group was classified according to the workplace. Groups 2 and 3 demonstrated a strong positive correlation between accident probability and PET, with correlation coefficients of 0.837 and 0.772, while Group 1 exhibited a moderately positive correlation of 0.474. This study quantitatively evaluated the impact of climate on workers for each subcontractor type using PET, an outdoor thermal comfort index for construction work, and accident probability, resulting in the identification of new groups. The findings of this study may serve as novel benchmarks for safety management in construction worker safety based on PET.

Predicting black ice-related accidents with probabilistic modeling using GIS-based Monte Carlo simulation.

Black ice, a phenomenon that occurs abruptly owing to freezing rain, is difficult for drivers to identify because it mirrors the color of the road. Effectively managing the occurrence of unforeseen accidents caused by black ice requires predicting their probability using spatial, weather, and traffic factors and formulating appropriate countermeasures. Among these factors, weather and traffic exhibit the highest levels of uncertainty. To address these uncertainties, a study was conducted using a Monte Carlo simulation based on random values to predict the probability of black ice accidents at individual road points and analyze their trigger factors. We numerically modeled black ice accidents and visualized the simulation results in a geographical information system (GIS) by employing a sensitivity analysis, another feature of Monte Carlo simulations, to analyze the factors that trigger black ice accidents. The Monte Carlo simulation allowed us to map black ice accident occurrences at each road point on the GIS. The average black ice accident probability was found to be 0.0058, with a standard deviation of 0.001. Sensitivity analysis using Monte Carlo simulations identified wind speed, air temperature, and angle as significant triggers of black ice accidents, with sensitivities of 0.354, 0.270, and 0.203, respectively. We predicted the probability of black ice accidents per road section and analyzed the primary triggers of black ice accidents. The scientific contribution of this study lies in the development of a method beyond simple road temperature predictions for evaluating the risk of black ice occurrences and subsequent accidents. By employing Monte Carlo simulations, the probability of black ice accidents can be predicted more accurately through decoupling meteorological and traffic factors over time. The results can serve as a reference for government agencies, including road traffic authorities, to identify accident-prone spots and devise strategies focused on the primary triggers of black ice accidents.

Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship

The arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and the model structure is developed using Bayesian Networks. To this end, an extensive literature survey is conducted, enhanced with the domain knowledge elicited from the experts and improved by the experimental data obtained during representative MASS model trials carried out in an inland river. Conditional Probability Tables are generated using a new function employing expert feedback regarding Interval Type 2 Fuzzy Sets. The developed Bayesian model yields the expected utilities results representing an accident’s probability and consequence, with the results visualized on a dedicated diagram. Finally, the developed risk assessment model is validated by conducting three axiom tests, extreme scenarios analysis, and sensitivity analysis. Navigational environment, natural environment, traffic complexity, and shore-ship collaboration performance are critical from the probability and consequence perspective for inland navigational accidents to a remotely controlled MASS. Lastly, important nodes to Shore-Ship collaboration performance include autonomy of target ships, cyber risk, and transition from other remote control centers.

Evolutionary Tripartite Game Model in the Coal Mine Risk-Hazard Double Pre-Control and Management in China

The classification, investigation, and management of the safety risk (namely, risk-hazard double pre-control management mechanism) in coal mines were introduced into a behavioral evolution game to assess the decision-making processes of coal mine workers, regulators, and supervisors. A tripartite game tree and a revenue perception matrix were constructed, and the evolutionary stability strategy (ESS) achieved by the evolutionary system under different conditions was obtained according to the replication dynamic equation (RD). The numerical simulation of the evolution game was conducted in MATLAB, which verified the influence of various parameters on the behaviors adopted by all parties. The results show: (1) When the safety, regulatory, and supervisory costs are high, the average expected value of mine workers, regulators, and supervisors to choose safety behaviors is low, so they adopt an unsafe behavior. By contrast, reducing costs can encourage the adoption of safety behaviors. (2) When the punishment for accident losses caused by unsafe behavior and the lack of regulations and supervision is higher than 50% of the initial state, the actors in the tripartite game are more inclined to avoid risks when facing cost losses in the short term, which can lead them to choose a safety behavior. (3) When the actors in the tripartite game face different accident probabilities and accident loss, with the severity of the accident increasing to 80% of the initial state, mine workers and regulators gradually adopt safety and regulation behaviors, and supervisors quickly adopt supervision methods.

Interaction of CsOH with structural steel 316L and simulated products of the steel-cladding reaction under assumed conditions relevant for the accident at the Fukushima Dai-Ichi Unit 2 and 3

A high radiation dose rate under the shield plugs of the Units 2 and 3 reactors at the Fukushima Dai-Ichi Nuclear Power Station (1F), raised an important question on volatile radioactive Cs migration, adsorption and retention on various structural materials during the accident. The high dose rate interferes with decommissioning work. The purpose of this study is to present basic knowledge on contamination mechanisms of a BWR reactor structural materials and post-accident debris by Cs compounds to help decommissioning companies consider the ways of decontamination and debris handling during 1F debris retrieval. Having this goal, a series of tests on CsOH contamination mechanism under assumed accident conditions for Units 2 and 3 was performed. The results may improve the accuracy of estimating the situation inside the reactor from the perspectives of accident analysis and materials’ properties. The test temperature and compounds were chosen based on the probable accident scenario. In particular, Cs adsorption was checked using preoxidized 316L stainless steel, a product of control blade degradation (steel-B4C eutectic) and a product of steel-channel box and cladding interaction (Zr-Fe based multiphase material). Penetration ability of Cs into the oxidized and metallic layers of materials was evaluated. CsOH most probable adsorption temperature range and new Cs containing phases’ formation temperature range were followed.

Development of a simplified one-dimensional CDA bubble model

Sodium-cooled fast reactors (SFRs) have high safety with an extremely low probability of a core disruptive accident (CDA). However, from a defense-in-depth perspective, the CDA sequence is still worth studying. Severe accidents in SFRs, such as unprotected loss of flow, might lead to a CDA during which fuel and some fission products could be instantly released from a large CDA bubble through potential leak paths in the top shield structure. Therefore, a reasonable prediction of dynamic behavior of a large-scale bubble within the sodium pool is vital for accurately evaluating the migration of source terms. In this study, we propose a simplified one-dimensional CDA bubble model that can handle heat and mass transfer in two-phase multicomponent materials in different computational domains during the rising of bubbles through the sodium pool toward the cover-gas region. In this model, an entrainment model based on the Rayleigh–Taylor instability and Kelvin–Helmholtz instability was used to explain the coolant entrainment through the gas/liquid boundary and jet fragmentation. The model also addresses the mitigation effect of non-condensable gases on the condensation of fuel, steel and sodium vapor at bubble interface. We evaluated the model using a past experiment on the expansion of a two-phase, large bubble with high pressure in a stagnant liquid pool conducted by Purdue University in the late 1970 s using a 1/7-scale model of Clinch River Breeder Reactor. Good agreement with the experimental data demonstrates that the developed model can reasonably represent the essential characteristics of dynamic behavior of a large, high-pressure bubble with heat and mass transfer in two-phase multicomponent materials. This is valuable for evaluating the migration of the source terms, which will be carried out in future studies.

A Possibility Evaluation Model for Road Transportation of Hazardous Chemicals Based on Bow-tie Theory and Bayesian Model

This paper collected 1115 road transportation accidents of hazardous chemicals in China from 2013 to 2021, and constructed a total of 120 accident chains, among which the most common accident chain was "impact → rear-end collision → fuel tank damage → leakage", with a total of 195 times. Based on the analysis of historical accident data, the occurrence mechanism of road transportation accidents of hazardous chemicals was discussed. Based on the bow-tie theory, the bow-tie diagram was established to realize the construction of qualitative reasoning bow-tie diagram for multi-disaster coupling accidents in road transportation of hazardous chemicals. The mapping rules between Bow-tie model and Bayesian network were established, and the structure of Bayesian network for road transportation of hazardous chemicals was constructed. The prior probability and conditional probability of Bayesian network nodes are determined by multi-source data, and the real-time accident probability evaluation is realized by combining quantitative and qualitative methods. Finally, a real time evaluation of the possibility of multi-disaster coupling accidents is realized every 30 seconds through a numerical example, which reflects the influence law of multi-disaster coupling scenarios on risks.

RT Based Railway Gates Automation Using NI myRIO

Railway safety at level crossings remains a paramount concern due to the recurring incidence of train accidents. This study proposes an innovative solution to enhance safety by introducing an automatic gate system at unmanned crossings, replacing manual operation. The system utilizes strategically positioned proximity detectors to detect approaching trains, automating gate management. This reduces gate closure duration compared to manual operation, minimizing disruptions to road traffic. Additionally, the system reduces reliance on human labor, offering a more efficient and reliable solution. It is particularly suitable for unmanned crossings prone to higher accident probabilities, where dependable operation is crucial. By integrating infrared sensors and servo motors, the system ensures prompt gate closure upon train detection, reducing potential accidents caused by negligence. This study enhances prior research by utilizing two infrared sensors on each side of the track, improving train position tracking accuracy. The sensors are programmed using the LabVIEW platform, facilitating integration with myRIO controllers. Overall, this study presents a comprehensive approach to enhancing railway safety through innovative automation technology at unmanned level crossings. Keywords— NI myRIO, IR sensors, Servomotor, Labview.

Risk of road traffic injury in Norway 1970–2022

This paper describes changes in the risk of road traffic injury in Norway during the period from 1970 to 2022. During this period, the risk of fatal and personal injury declined by more than 70 % for most groups of road users. There are five main potential explanations of a decline in the risk of injury: (1) a reduced probability of accidents that have the potential for causing injury; (2) an improved protection against injury given that an accident has occurred; (3) improved medical care increasing the survival rate, given an injury (this would reduce the number of fatalities, but not the number of injuries); (4) a tendency for the reporting of injuries in official accident statistics to decline over time; (5) uncertain or erroneous estimates of the exposure to the risk of injury. The decline in the risk of road traffic injuries in Norway after 1970 can probably be attributed to a combination of reduced reporting of injuries in official statistics, improved protection against injury in accidents, and (for fatal injuries) improved medical care. Insurance data, available from 1992, do not indicate a reduction in the risk of accidents leading to insurance claims. Incomplete and possibly erroneous data for mopeds and motorcycles make it impossible to identify sources of changes in injury risk over time for these modes of transport.

Temperature control for the synthesis of n-butylmagnesium bromide Grignard reagent based on n-octadecane/polystyrene microPCMs

Thermal runaway accounts for a high proportion of chemical safety accidents and poses a serious threat to the operational safety of personnel. Phase change materials (PCMs) have a high enthalpy of melting, if the latent heat energy of their phase change can be stored and used to absorb the heat released during thermal runaway, this phenomenon can provide a new approach for the control of reaction thermal runaway. In this work, microencapsulated phase change materials (microPCMs) were prepared by the suspension polymerization method using n-octadecane as the core material and polystyrene (PS) as the shell material. The prepared microPCMs had regular spherical morphologies with smooth surfaces, and the average particle size was 7.54 μm, the thermal conductivity was 0.05964 W/m∙K. The melting enthalpy of the microPCMs was 142.2 J/g, and the encapsulation percentage of the PCMs was 62.15%. The synthesis of the n-butylmagnesium bromide Grignard reagent occurred via a strong exothermic reaction, which was very likely to lead to overpressure venting once control was lost. The prepared microPCMs were applied as inhibitors in this reaction to investigate the temperature control effect under different operating conditions. The results showed that the amount of microPCMs added, and the timing of the addition affected the control effect. The addition of microPCMs could effectively reduce the reaction temperature and slow the rate of temperature increase. Even in the event of an emergency situation, such as a control failure, time could be gained for other emergency measures, effectively reducing the probability of thermal runaway accidents.

Exploration on Wireless Network-Based Monitoring and Early Warning Algorithms for Power Grounding Faults

Electricity is an indispensable resource in daily life. While it brings great convenience to people, it also brings some safety hazards, especially in the event of power failure, which may cause significant harm. Therefore, monitoring and warning of power faults are very important. Traditional power grounding fault monitoring and warning systems have problems such as untimely monitoring, inaccurate warning, and high error rates in fault location. In order to solve the above problems, this paper uses wireless networks to construct a power grounding fault monitoring and early warning system. The wireless network collected fault data based on the complexity of power grounding fault data, and used threshold monitoring method to analyze the collected data. The wireless network was used to construct a prediction model to monitor grounding faults. Through experiments, it can be found that the accuracy of the wireless network-based power fault monitoring system for predicting grounding faults was over 92.57%, and the average warning accuracy of 20 experiments was 93.856%. This paper studied a wireless network-based algorithm for monitoring and warning of power grounding faults, which can effectively improve the monitoring and warning capabilities of power systems, and reduce the risk of power equipment faults and the probability of power accidents.

Does accident awareness affect people's risk perception of hydrogen infrastructure and information-seeking behaviour?

With increasing concerns about recent hydrogen-related accidents in leading countries applying hydrogen energy, maintaining public trust in hydrogen infrastructure is crucial for advancing energy transitions. This study investigates how individuals aware and unaware of hydrogen-related accidents perceive the risk of hydrogen refuelling facilities in Japan. The comparative analysis reveals that accident awareness significantly increases public apprehension by amplifying perceived accident probabilities and consequences. Specifically, accident-aware individuals value their subjective understanding of hydrogen knowledge more than objective knowledge when it comes to trusting hydrogen technologies. The direct impact of positive affect on alleviating risk perceptions is found to be counteracted by accident awareness. In terms of behavioural outcomes, this study confirms individuals' inclination to seek information based on their perceived risk. People are more eager to acquire risk preparedness information when they perceive the potential consequences of undesired events as significant. In contrast, the perceived likelihood of risk accidents does not exhibit such a significant relationship. The findings offer valuable insights for recognising circumstances in which the communication of risk preparedness initiatives becomes crucial in the aftermath of accidents.

Risk assessment of man‐machine systems under safety‐critical multitasking situations

AbstractMultitasking is increasingly common in highly complex and safety‐critical systems, especially under abnormal situations. Mental overload (MOL) may occur and result in forgetting/mistaking tasks uncertainly. Such probabilistic errors could have catastrophic consequences and contribute greatly to the multitasking risk of man‐machine systems. In this paper, to better identify the risks of safety‐critical multitasking situations, MOL mechanism is investigated and a risk analysis method considering MOL is proposed. MOL occurs when the demand for resources estimated by Multiple Resources Model exceeds an operator's ability. Then, the operator's performance degrades, and s/he tends to mistake or abandon parts of tasks. Based on the MOL mechanism, a MOL‐performance dependency (MOL‐PDEP) gate is proposed to incorporate MOL into risk analysis. Its inputs are concurrent tasks, and it triggers the related hazardous human behavior events with certain probabilities if MOL occurs. Through this gate, the dependence among these events and their nondeterministic cause relationships to MOL are added to traditional fault tree (FT), which presents a challenge issue to FT analysis. An implicit method is proposed to analyze the FT with MOL‐PDEP gate and calculate the accident probability. A case study on a helicopter crash accident demonstrates the effectiveness of the proposed method.

Diminishing Safety Margins of Telescoping-Boom Aerial Lifts

Abstract As the height of telescoping-boom aerial lifts increase, the severity of tip-over accidents obviously increases. To reduce the probability of tip-over accidents, manufacturers use countermeasures such as outriggers and wheel axels that expand in width to provide a more stable base, counterweights to offset the moments generated by the telescoping boom, and controllers that limit the machine configurations to within stable envelopes. The size of stability margins is determined by industry standards that set the approved load capacity of the machine to less than the load that would induce tip-over. This paper investigates the effectiveness of such load-based safety margins for very tall aerial lifts with telescoping-booms. The results indicate that the industry standards result in both inconsistent and often low safety margins.