Journal articles: 'Reason's model of accident causation'

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Ma, Xiaoli, Yingying Xing, and Jian Lu. "Causation Analysis of Hazardous Material Road Transportation Accidents by Bayesian Network Using Genie." Journal of Advanced Transportation 2018 (August 5, 2018): 1–12. http://dx.doi.org/10.1155/2018/6248105.

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With the increase of hazardous materials (Hazmat) demand and transportation, frequent Hazmat road transportation accidents had arisen the widespread concern in the community. Thus, it is necessary to analyze the risk factors’ implications, which would make the safety of Hazmat transportation evolve from “passive type” to “active type”. In order to explore the influence of risk factors resulting in accidents and predict the occurrence of accidents under the combination of risk factors, 839 accidents that have occurred for the period 2015–2016 were collected and examined. The Bayesian network structure was established by experts’ knowledge using Dempster-Shafer evidence theory. Parameter learning was conducted by the Expectation-Maximization (EM) algorithm in Genie 2.0. The two main results could be likely to obtain the following. (1) The Bayesian network model can explore the most probable factor or combination leading to the accident, which calculated the posterior probability of each risk factor. For example, the importance of three or more vehicles in an accident leading to the severe accident is higher than less vehicles, and in the absence of other evidences, the most probable reasons for “explosion accident” are vehicles carrying flammable liquids, larger quantity Hazmat, vehicle failure, and transporting in autumn. (2) The model can predict the occurrence of accident by setting the influence degrees of specific factor. Such that the probability of rear-end accidents caused by “speeding” is 0.42, and the probability could reach up to 0.97 when the driver is speeding at the low-class roads. Moreover, the complex logical relationship in Hazmat road transportation accidents could be obtained, and the uncertain relation among various risk factors could be expressed. These findings could provide theoretical support for transportation corporations and government department on taking effective measures to reduce the risk of Hazmat road transportation.

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Elliott, Malcolm, Karen Page, and Linda Worrall-Carter. "Reason’s accident causation model: Application to adverse events in acute care." Contemporary Nurse 43, no. 1 (December 2012): 22–28. http://dx.doi.org/10.5172/conu.2012.43.1.22.

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Zou, Xin, and Wen Long Yue. "A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica." Journal of Advanced Transportation 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/2525481.

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Based on an overall consideration of factors affecting road safety evaluations, the Bayesian network theory based on probability risk analysis was applied to the causation analysis of road accidents. By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts’ knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. Then Netica was used to carry out posterior probability reasoning, the most probable explanation, and inferential analysis. The results showed that the Bayesian network model could effectively explore the complex logical relation in road accidents and express the uncertain relation among related variables. The model not only can quantitatively predict the probability of an accident in certain road traffic condition but also can find the key reasons and the most unfavorable state combination which leads to the occurrence of an accident. The results of the study can provide theoretical support for urban road management authorities to thoroughly analyse the induction factors of road accidents and then establish basis in improving the safety performance of the urban road traffic system.

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Fu, Gui, Ziqi Zhao, Chuanbo Hao, and Qiang Wu. "The Accident Path of Coal Mine Gas Explosion Based on 24Model: A Case Study of the Ruizhiyuan Gas Explosion Accident." Processes 7, no. 2 (February 2, 2019): 73. http://dx.doi.org/10.3390/pr7020073.

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In order to effectively prevent coal mine accidents, we selected the most serious type of accident in coal mines—gas explosions—as the research object. Based on the accident causation model (24Model), we propose an action path and analysis steps of accidents caused by different employees in the organization. A gas explosion coal mine accident was analyzed using the 24Model and the proposed action path, and 12 unsafe actions, 3 unsafe states, 4 habitual behaviors, 10 safety management systems, and 10 safety cultures were obtained. Case analysis results show that by using the 24Model and path analysis the proposed effect can help employees to clearly identify the cause of the accident, to better understand the logical relationship with the causes of the accident, improve the effectiveness of training, and effectively prevent similar accidents. The 24Model and the proposed path can be used to comprehensively analyze the reasons for and help to effectively prevent coal mine gas explosion accidents.

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Cookson, Simon. "Zagreb and Tenerife." Australian Review of Applied Linguistics 32, no. 3 (January 1, 2009): 22.1–22.14. http://dx.doi.org/10.2104/aral0922.

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The International Civil Aviation Organization (ICAO) is currently implementing a program to improve the language proficiency of pilots and air traffic controllers worldwide. In justifying the program, ICAO has cited a number of airline accidents that were at least partly caused by language factors. Two accidents cited by ICAO are analysed in this paper: the mid-air collision above Zagreb in 1976, and the runway collision at Tenerife in 1977. The paper examines the linguistic factors involved in each accident, such as code switching and L1 interference, and uses the ‘Swiss cheese’ model of accident causation developed by Reason (1990) and adapted by Wiegmann and Shappell (2003) to put these factors into a broader aviation context. It is shown that, while linguistic factors were in each case significant, both accidents occurred as the result of multiple causal factors, many of which were non-linguistic. Furthermore, stress and fatigue played a decisive role in exacerbating the linguistic factors in each accident. Finally, the paper suggests lessons that may be drawn from the analysis for the training of pilots and air traffic controllers, both nativespeaker and non native-speaker.

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Cookson, Simon. "Zagreb and Tenerife." Australian Review of Applied Linguistics 32, no. 3 (2009): 22.1–22.14. http://dx.doi.org/10.1075/aral.32.3.02coo.

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The International Civil Aviation Organization (ICAO) is currently implementing a program to improve the language proficiency of pilots and air traffic controllers worldwide. In justifying the program, ICAO has cited a number of airline accidents that were at least partly caused by language factors. Two accidents cited by ICAO are analysed in this paper: the mid-air collision above Zagreb in 1976, and the runway collision at Tenerife in 1977. The paper examines the linguistic factors involved in each accident, such as code switching and L1 interference, and uses the ‘Swiss cheese’ model of accident causation developed by Reason (1990) and adapted by Wiegmann and Shappell (2003) to put these factors into a broader aviation context. It is shown that, while linguistic factors were in each case significant, both accidents occurred as the result of multiple causal factors, many of which were non-linguistic. Furthermore, stress and fatigue played a decisive role in exacerbating the linguistic factors in each accident. Finally, the paper suggests lessons that may be drawn from the analysis for the training of pilots and air traffic controllers, both nativespeaker and non native-speaker.

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Jiang, Chengyue, Zhiyong Yin, Lihai Ren, Yuanzhi Hu, Xi Liu, and Hongxu Zhu. "Coupling Simulation of an Impact-Induced Rollover Accident and Evaluation of Curtain Airbag Effectiveness." International Journal of Computational Methods 17, no. 08 (June 26, 2019): 1950041. http://dx.doi.org/10.1142/s0219876219500415.

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The causes of fatal and serious injuries in rollover accidents have yet to be fully identified. This study aimed to reconstruct a complex accident, based on both video analysis and vehicle coupling simulation. Besides, the major fatal injury causation and curtain airbag’s effectiveness were analyzed. The coupling model, including finite element tire and multi-body vehicle body, was developed to estimate the vehicle trajectory. A validated curtain airbag (CAB) module, was introduced for occupant protection effectiveness evaluation. The vehicle trajectory from the simulation correlated well with that from video recordings and simulation result indicated that passenger’s head contact with road (maximum contact force 9834.9[Formula: see text]N) was assumed to be the main reason of the victim death. After introducing the CAB, the maximum head acceleration was reduced from 129.1[Formula: see text]g to 24.9[Formula: see text]g, and the neck Fz was reduced by 80.0% as well. The coupling simulation method turned out to be efficient to reconstruct certain complex accident case. Such study is beneficial for further similar accident reconstruction and restraint system evaluation.

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Joe-Asare, T., N. Amegbey, and E. Stemn. "Human Factor Analysis Framework for Ghana’s Mining Industry." Ghana Mining Journal 20, no. 2 (December 31, 2020): 60–76. http://dx.doi.org/10.4314/gm.v20i2.8.

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In an attempt to incorporate human factors into technical failures as accident causal factors, researchers have promoted the concept of human factor analysis. Human factor analysis models seek to identify latent conditions within the system that influence the operator’s action to trigger an accident. For an effective application of human factor analysis models, a domain-specific model is recommended. Most existing models are developed with category/subcategory peculiar to a particular domain. This presents challenges and hinders effective application outside the domain developed for. This paper sought to propose a human factor analysis framework for Ghana’s mining industry. A comparative study was carried out between three dominated accident causation models and investigation methods in literature; AcciMap, HFACS, and STAMP. The comparative assessment showed that HFACS is suitable for incident data analysis based on the following reason; ease of learning and use, suitability for multiple incident analysis and statistical quantification of trends and patterns, and high inter and intra-coder reliability. A thorough study was done on HFACS and its derivative. Based on recommendations and research findings on HFACS from literature, Human Factor Analysis, and Classification System – Ghana Mining Industry (HFACS-GMI) was proposed. The HFACS-GMI has 4 tiers, namely; External influence/factor, Organisational factor, Local Workplace/Individual Condition and, Unsafe Act. A partial list of causal factors under each tier was generated to serve as a guide during incident coding and investigation. The HFACS-GMI consists of 18 subcategories and these have been discussed. The HFACS-GMI is specific to the Ghanaian Mines and could potentially help in identifying causal and contributing factors of an accident during an incident investigation and data analysis. Keywords: Human Factor Analysis, Causal Factor, Causation Model, Mining Industry

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Dolzhenko Nadezhda Aleksandrovna, Maylyanova Ekaterina Nikolaevna,, Toluev Y.,, and Assilbekova I.,. "INFLUENCE OF SYSTEM ERRORS IN METEOROLOGICAL SUPPORT ON FLIGHTS SAFETY." NEWS of National Academy of Sciences of the Republic of Kazakhstan 5, no. 443 (October 15, 2020): 81–88. http://dx.doi.org/10.32014/2020.2518-170x.107.

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There are many different systems of interaction in practical aviation activities. In particular, in a system consisting of an operator and a machine there are quite often failures due to errors of designers, operators, manufacturers, maintenance, etc. Errors are usually unintentional: a person performs erroneous actions, considering them as correct or most suitable due to insufficient information, neglect of rules and standards and even due to lack of such. The specialists of the American corporation Boeing calculated the share of aviation accidents related to incorrect decision-making. It turned out that of all aviation accidents, such incidents account for 75%. Back in 1990, Professor Reason developed a model describing the causation of an air accident. One of the main elements of this manufacturing system consists of decision-makers, another key element is decision-executors. For top-level decisions and line management actions to be implemented into effective and productive activities carried out directly by pilots and instructors, certain preconditions must be met. The Rison model explains how people contribute to the disruption of complex, interacting and well-protected systems (such as aviation), resulting in an aviation incident. This model reveals to us causal relationships that do not directly lead to an accident, but shows that, although there are lots of protection levels between risks and accidents, there are drawbacks in each layer of protection that, in the case of systemic “flaring-out”, can trigger an accident [3]. The drawbacks of one level of protection do not allow realizing the risk, since there are other protections to prevent a single point of failure, but with systemic accumulation of risks, catastrophic consequences are inevitable. This effect is sometimes called the "aggregate action effect." In our work, we tried to investigate the system of unprotected risks that led to disaster.

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Grey, E., and P. Wilkinson. "APPLYING WHAT WE KNOW ABOUT HUMAN ERROR: FROM THEORY INTO PRACTICE." APPEA Journal 44, no. 1 (2004): 885. http://dx.doi.org/10.1071/aj03050.

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Human error is often said to be at the heart of the majority of incidents and the developing discipline of human factors a way of understanding how these errors occur. There is little debate about this. But do we practise what we preach and are we reaping the benefits of applying the insights? Anecdotal evidence suggests not. Human error is too often interpreted as people being reckless, careless or just ignorant in discharging their duties. This so-called careless worker approach was the unstated assumption behind early moves to improve health and safety. It could be argued in the petroleum industry that we have adopted a more sophisticated approach, emphasising the importance of the engineering integrity of process systems and the role of formal management systems. However, there remains a need to better integrate what we know about human and organisational error. Reason’s (1997) organisational accident model has had a profound effect on how accidents are viewed and how we can learn from them. The clarity with which the model is presented does not, however, necessarily translate directly into ease of application. The model is a description of accident causation, but does not provide a method for making assessments about organisational resilience in its own right. As such, individuals wanting to use the model need to be well trained if benefits are to be realised. This paper describes a practical and applied approach to human error training based on principles of adult learning that is designed to tap into trainees’ existing knowledge and experiences.

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Watson, Barbara, Alan Salmoni, and Aleksandra Zecevic. "Case Analysis of Factors Contributing to Patient Falls." Clinical Nursing Research 28, no. 8 (January 30, 2018): 911–30. http://dx.doi.org/10.1177/1054773818754450.

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Falls are a constant risk for patients in acute-care hospitals, which can lead to serious consequences. The purpose of this study was to examine hospital fall case studies and to learn the contributing factors for patient falls. This was achieved by conducting a secondary analysis of 11 fall case studies obtained from two previous studies. The fall cases used the Senior Falls Investigative Methodology (SFIM) approach, which provided detailed analysis of the circumstances surrounding the falls. A total of 549 contributing factors were identified in the 11 case studies, where major categories were classified according to the four different layers of defenses using Reason’s Swiss Cheese Model of Accident Causation (organizational factors, supervision, preconditions, and unsafe acts). Hospital policies, reduced supervision, disease processes, the environment, and patients transferring without assistance dominated the reasons for increased risk. Additional strategies were recommended for all layers of defense to reduce patient falls.

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Tarik, Bakeli, and Hafidi Alaoui Adil. "Occupational health and safety in the Moroccan construction sites: preliminary diagnosis." International Journal of Metrology and Quality Engineering 9 (2018): 6. http://dx.doi.org/10.1051/ijmqe/2018005.

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Managing occupational health and safety on Moroccan construction sector represents the first step for projects' success. In fact, by avoiding accidents, all the related direct and indirect costs and delays can be prevented. That leads to an important question always asked by any project manager: what are the factors responsible for accidents? How can they be avoided? Through this research, the aim is to go through these questions, to contribute in occupational health and safety principles understanding, to identify construction accidentology and risk management opportunities and to approach the case of Moroccan construction sites by an accurate diagnosis. The approach is to make researchers, managers, stakeholders and deciders aware about the criticality of construction sites health and safety situation. And, to do the first step for a scientific research project in relation with health and safety in the Moroccan construction sector. For this, the paper will study the related state of art namely about construction sites accidents causation, and will focus on Reason's ‘Swiss cheese’ model and its utilization for Moroccan construction sites health and safety diagnosis. The research will end with an estimation of an accidents fatality rate in the Moroccan construction sector and a benchmarking with the international rates. Finally, conclusions will be presented about the necessity of Occupational Health and Safety Management System (OHSMS) implementation, which shall cover all risk levels, and insure, at the same time, that the necessary defenses against accidents are on place.

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Puaar, Seetal Jheeta, and Bryony Dean Franklin. "Impact of an inpatient electronic prescribing system on prescribing error causation: a qualitative evaluation in an English hospital." BMJ Quality & Safety 27, no. 7 (October 10, 2017): 529–38. http://dx.doi.org/10.1136/bmjqs-2017-006631.

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BackgroundFew studies have applied a systems approach to understanding the causes of specific prescribing errors in the context of hospital electronic prescribing (EP). A comprehensive understanding of underlying causes is essential for developing effective interventions to improve prescribing safety. Our objectives were to explore prescribers’ perspectives of the causes of errors occurring with EP and to make recommendations to maximise benefits and minimise risks.MethodsWe studied a large hospital using inpatient EP. From April to June 2016, semistructured interviews were conducted with purposively sampled prescribers involved with a prescribing error. Interviews explored prescribers’ perceived causes of the error and views about EP; they were audio-recorded and transcribed verbatim. Data were thematically analysed against a framework based on Reason’s accident causation model, with a focus on identifying latent conditions.ResultsTwenty-five interviews explored causes of 32 errors. Slips and rule-based mistakes were the most common active failures. Error causation was multifactorial; environmental, individual, team, task and technology error-producing conditions were all influenced by EP. There were three broad groups of latent conditions: the EP system’s functionality and design; the organisation’s decisions around EP implementation and use; and prescribing behaviours in the context of EP.ConclusionsErrors were associated with the design of EP itself and its integration within the healthcare environment. Findings suggest that EP vendors should focus on revolutionising interface design and usability issues, bearing in mind the wider healthcare context in which such software is used. Healthcare organisations should draw upon human factors principles when implementing EP. Consideration of work environment, infrastructure, training, prescribing responsibilities and behaviours should be considered to address local issues identified.

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Johnson, C. W., and R. M. Botting. "Using Reason's Model of Organisational Accidents in Formalising Accident Reports." Cognition, Technology & Work 1, no. 2 (September 1, 1999): 107–18. http://dx.doi.org/10.1007/s101110050037.

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Mitropoulos, Panagiotis, Tariq S. Abdelhamid, and Gregory A. Howell. "Systems Model of Construction Accident Causation." Journal of Construction Engineering and Management 131, no. 7 (July 2005): 816–25. http://dx.doi.org/10.1061/(asce)0733-9364(2005)131:7(816).

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Lewis, Penny J., Elizabeth Seston, and Mary P. Tully. "Foundation year one and year two doctors’ prescribing errors: a comparison of their causes." Postgraduate Medical Journal 94, no. 1117 (November 2018): 634–40. http://dx.doi.org/10.1136/postgradmedj-2018-135816.

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ObjectiveJunior doctors have the highest rates of prescribing errors, yet no study has set out to understand the differences between completely novice prescribers (Foundation year one (FY1) doctors) and those who have gained some experience (Foundation year two (FY2) doctors). The objective of this study was to uncover the causes of prescribing errors made by FY2 doctors and compare them with previously collected data of the causes of errors made by FY1 doctors.DesignQualitative interviews, using the critical incident technique, conducted with 19 FY2 doctors on the causes of their prescribing errors and compared with interviews previously conducted with 30 FY1 doctors. Data were analysed using a constant comparison approach after categorisation of the data using Reason’s model of accident causation and the London protocol.ResultsCommon contributory factors in both FY1 and FY2 doctors’ prescribing errors included working on call, tiredness and complex patients. Yet, important differences were revealed in terms of application of prescribing knowledge, with FY1 doctors lacking knowledge and FY2 misplacing their knowledge. Due to the rotation of foundation doctors, both groups are faced with novel prescribing contexts, yet the previous experience that FY2 doctors gained led to misplaced confidence when caution would have been expedient.ConclusionsDifferences in the contributory factors of prescribing errors should be taken into account when designing interventions to improve the prescribing of foundation doctors. Furthermore, careful consideration should be taken when inferring expertise in FY2 doctors, who are likely to prescribe in contexts in which their experience is little different to an FY1 doctor.

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DeJoy, David M. "Human Factors Model of Workplace Accident Causation." Proceedings of the Human Factors Society Annual Meeting 32, no. 15 (October 1988): 958–62. http://dx.doi.org/10.1518/107118188786761910.

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This paper proposes a human factors model of workplace accident causation. Particular attention is given to merging traditional human factors considerations with those related to self-protective behavior. The model focuses on human error, and three categories of diagnostic factors are proposed for analyzing the determinants of error. The diagnostic factors include: person-machine communication, environment, and decision-making. These factors are then linked to three general types of interventions: those involving system modification, organizational modification, and self-protection.

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Li, Qian, Zhe Zhang, and Fei Peng. "Causality-Network-Based Critical Hazard Identification for Railway Accident Prevention: Complex Network-Based Model Development and Comparison." Entropy 23, no. 7 (July 6, 2021): 864. http://dx.doi.org/10.3390/e23070864.

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This study investigates a critical hazard identification method for railway accident prevention. A new accident causation network is proposed to model the interaction between hazards and accidents. To realize consistency between the most likely and shortest causation paths in terms of hazards to accidents, a method for measuring the length between adjacent nodes is proposed, and the most-likely causation path problem is first transformed to the shortest causation path problem. To identify critical hazard factors that should be alleviated for accident prevention, a novel critical hazard identification model is proposed based on a controllability analysis of hazards. Five critical hazard identification methods are proposed to select critical hazard nodes in an accident causality network. A comparison of results shows that the combination of an integer programming-based critical hazard identification method and the proposed weighted direction accident causality network considering length has the best performance in terms of accident prevention.

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Suraji, Akhmad, A. Roy Duff, and Stephen J. Peckitt. "Development of Causal Model of Construction Accident Causation." Journal of Construction Engineering and Management 127, no. 4 (August 2001): 337–44. http://dx.doi.org/10.1061/(asce)0733-9364(2001)127:4(337).

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Luo, Ziyan, Keping Li, Xin Ma, and Jin Zhou. "A New Accident Analysis Method Based on Complex Network and Cascading Failure." Discrete Dynamics in Nature and Society 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/437428.

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A new accident causation model is proposed for accident analysis based on the complex network theory. By employing the cascading failure scheme, a new accident investigation method is performed on the associated new model, by which we can reveal key causation factors and key causation factor chains that lead to the final accident. The efficiency of a network is introduced for evaluating the severity of the damage of the whole network and hence the severity of the accident if it happens. All these can provide the government or associations with recommendations for accident prediction and prevention.

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Liu, Jin-Tao, and Ke-Ping Li. "A cascading failure model for analyzing railway accident causation." International Journal of Modern Physics B 32, no. 01 (January 8, 2018): 1750265. http://dx.doi.org/10.1142/s0217979217502654.

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In this paper, a new cascading failure model is proposed for quantitatively analyzing the railway accident causation. In the model, the loads of nodes are redistributed according to the strength of the causal relationships between the nodes. By analyzing the actual situation of the existing prevention measures, a critical threshold of the load parameter in the model is obtained. To verify the effectiveness of the proposed cascading model, simulation experiments of a train collision accident are performed. The results show that the cascading failure model can describe the cascading process of the railway accident more accurately than the previous models, and can quantitatively analyze the sensitivities and the influence of the causes. In conclusion, this model can assist us to reveal the latent rules of accident causation to reduce the occurrence of railway accidents.

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Li, Keping, and Shanshan Wang. "A network accident causation model for monitoring railway safety." Safety Science 109 (November 2018): 398–402. http://dx.doi.org/10.1016/j.ssci.2018.06.008.

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Chira-Chavala, T., B. Coifman, C. Porter, and M. Hansen. "Light Rail Accident Involvement and Severity." Transportation Research Record: Journal of the Transportation Research Board 1521, no. 1 (January 1996): 147–55. http://dx.doi.org/10.1177/0361198196152100119.

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Accident causation and accident severity analyses for a light rail transit system are presented, with a view to providing input for the identification and development of accident and severity countermeasures. Accident reports of the Santa Clara County Transit Authority were used in both analyses. In the accident causation analysis, patterns of critical events for various types of light rail accident involvement were determined. The accident severity model is a binary logit model expressing the probability of injury accident as a function of speeds before collision of both the light rail vehicle and the motor vehicle, movement of the motor vehicle before collision, and peak and off-peak period.

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Fu, Gui, Xuecai Xie, Qingsong Jia, Zonghan Li, Ping Chen, and Ying Ge. "The development history of accident causation models in the past 100 years: 24Model, a more modern accident causation model." Process Safety and Environmental Protection 134 (February 2020): 47–82. http://dx.doi.org/10.1016/j.psep.2019.11.027.

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Wu, Ya Rong, Jing Shun Duanmu, Ji Hui Xu, and Xiao Hong Ren. "Aviation Human Factors Accident Causation Model Based on Structure Entropy." Applied Mechanics and Materials 488-489 (January 2014): 1354–57. http://dx.doi.org/10.4028/www.scientific.net/amm.488-489.1354.

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In order to study the traditional accident causation theories and models about human factors in flight accident. A new aviation accident causation model based on the improved HFACS is constructed. Through using system aging, quality and Structure Entropy formula the degree of order of model 1 and model 2 are evaluated, and by selecting aging entropy, maximum timeliness entropy, timeliness, quality entropy and maximum quality entropy the structure of the degree of order is calculated to verify structure in the right to re-bias stability under the conditions. It is shown that the model 2's structure entropy are lower, aging and model quality are also larger, so the improved model is better structural model.

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Xie, Hong Tao. "Research on the Interaction Relation of the Causations of Tunnel Collapse Accident." Advanced Materials Research 838-841 (November 2013): 1414–19. http://dx.doi.org/10.4028/www.scientific.net/amr.838-841.1414.

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The purpose of this study is to find the key factors influencing the tunnel collapse accident, and explore the causal relationships between the causations of the tunnel collapse accident. Based on document surveys and Delphi Method, a system of the causation indicators of the collapse accident is established. In order to make sure that the hierarchy structure of the causation index system of the tunnel collapse accident is illustrative and reasonable, a new method of system structure analysis is proposed based on the integration of Decision making trial and evaluation laboratory (DEMATEL) and Interpretive structure model (ISM). Applying this method, the center degree and the reasoning degree of the causation are obtained firstly, and then the system hierarchy structure of the causation index system of the tunnel collapse accident is actualized. The results showed that the main causes of the tunnel collapse accident are derived from management. This research reveals the interaction relations of the causations of tunnel collapse accident, based on which this research also provides strong theory and methods to support dynamic decision and quantitative risk assessment in tunnel construction.

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Zhou, Jin, Weixiang Xu, Xin Guo, and Xin Ma. "Railway faults spreading model based on dynamics of complex network." International Journal of Modern Physics B 29, no. 06 (March 2, 2015): 1550038. http://dx.doi.org/10.1142/s0217979215500381.

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In this paper, we propose a railway faults spreading model which improved the SIR model and made it suitable for analyzing the dynamic process of faults spreading. To apply our model into a real network, the accident causation network of "7.23" China Yongwen high-speed railway accident is employed. This network is improved into a directed network, which more clearly reflects the causation relationships among the accident factors and provides help for our studies. Simulation results quantitatively show that the influence of failures can be diminished via choosing the appropriate initial recovery factors, reducing the time of the failure detected, decreasing the transmission rate of faults and increasing the propagating rate of corrected information. The model is useful to simulate the railway faults spreading and quantitatively analyze the influence of failures.

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Liang, Kaiwu, Jikun Liu, and Cuixia Wang. "The Coal Mine Accident Causation Model Based on the Hazard Theory." Procedia Engineering 26 (2011): 2199–205. http://dx.doi.org/10.1016/j.proeng.2011.11.2425.

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Gang, Longhui, Xiaolin Song, Mingheng Zhang, Baozhen Yao, and Liping Zhou. "Analysis of driver fatigue causations based on the Bayesian network model." SIMULATION 93, no. 7 (September 7, 2016): 553–65. http://dx.doi.org/10.1177/0037549716665712.

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Driver fatigue is the major reason for severe traffic accidents. At present, the driver’s driving state evaluation, based on multi-source information fusion, has become a hotspot in the research field of vehicle safety assistant driving. The purpose of this paper is to build a Bayesian network model for driver fatigue causation analysis considering several visual cues, such as Percentage of Eyelid Closure over the Pupil over Time, Average Eye Closure Speed, etc. The proposed method was divided into three stages, that is, variables analysis, model structure design, and model parameter determination. Finally, the presented model and algorithm were illustrated with a simulation experiment and conclusions were inferred from the experiment data analysis.

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Wang, Jianhao, and Mingwei Yan. "Application of an Improved Model for Accident Analysis: A Case Study." International Journal of Environmental Research and Public Health 16, no. 15 (August 2, 2019): 2756. http://dx.doi.org/10.3390/ijerph16152756.

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An improved accident causation model which demonstrates the relationships among different causal factors was proposed in this study. It provides a pathway for accident analysis from the individual level to the organizational level. Unsafe acts and conditions determined by individuals’ poor safety knowledge, low safety awareness, bad safety habits, etc. are the immediate causes of an accident. Deficiencies in safety management systems and safety culture remain the root causes, which can cause consequences at the individual level. Moreover, the weaknesses of an organization’s safety culture can have a great impact on the formation of a good safety climate and can further lead to poor decision-making and implementation of procedures in the safety management system. In order to contribute to a better perception and understanding of the accident causation model, one typical case in the process industry, the oil leak and explosion of the Sinopec Donghuang pipelines, was selected for this study. The causality from immediate causes to root causes is demonstrated in sequence and can be shown in this model explicitly and logically. Several important lessons are summarized from the results and targeted measures can be taken to avoid similar mistakes in the future. This model provides a clear and resourceful method for the safety and risk practitioner’s toolkit in accident investigation and analysis, and the organization can use it as a tool to conduct staff trainings and thus to keep accidents under control.

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K, Ajaya Kumar, Tamil Selvan R, Nehal Siddiqui A, and Ashutosh Gautam. "Scope for Developing Accident Causation Model of Road Transportation of Hazardous Materials." IARJSET 2, no. 10 (October 20, 2015): 57–63. http://dx.doi.org/10.17148/iarjset.2015.21012.

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Chen, Yuanjiang, Wei Feng, Zhiqiang Jiang, Lingling Duan, and Shuangyi Cheng. "An accident causation model based on safety information cognition and its application." Reliability Engineering & System Safety 207 (March 2021): 107363. http://dx.doi.org/10.1016/j.ress.2020.107363.

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Akuh, Raymond, and Charles Atombo. "Road Transport Accident Analysis from A System-Based Accident Analysis Approach Using Swiss Cheese Model." International Journal of Engineering Education 1, no. 2 (December 15, 2019): 99–105. http://dx.doi.org/10.14710/ijee.1.2.99-105.

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Road safety has become a major concern to both developed and developing countries due to its negative economic impacts. Although, numerous approaches of accident analysis have been conducted, there seem to be an increase in road crashes every year. The main aim of this study is to analyse a driving school accident using a system-based accident analysis approach. The data for the study was collected using an interview. A Swiss Cheese Accident Causation Model was used to identify the factors that contributed to the accident. The study identified four weaknesses in the system defences of the driving school that created a possible accident trajectory. It is concluded that adopting system-based accident analysis approach in analysing road transport accidents, could lead to a greater understanding of latent conditions and road user error, which in turn could inform the development of intervention strategies within a road transport domain as suggested by other studies. Finally, the short falls of using only person approach of accident analysis in road transport domain are also highlighted.

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Kim, Dong San, and Wan Chul Yoon. "An accident causation model for the railway industry: Application of the model to 80 rail accident investigation reports from the UK." Safety Science 60 (December 2013): 57–68. http://dx.doi.org/10.1016/j.ssci.2013.06.010.

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Grant, Eryn, Paul M. Salmon, and Nicholas J. Stevens. "The usual suspects? A novel extension to AcciMap using accident causation model tenets." Theoretical Issues in Ergonomics Science 20, no. 4 (November 15, 2018): 397–418. http://dx.doi.org/10.1080/1463922x.2018.1510061.

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Behm, Michael, and Arthur Schneller. "Application of the Loughborough Construction Accident Causation model: a framework for organizational learning." Construction Management and Economics 31, no. 6 (June 2013): 580–95. http://dx.doi.org/10.1080/01446193.2012.690884.

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Sagir, Zeynep, and Ertugrul Tacgin. "The evaluation of common contemporary occupational accident models using two accident investigations." International Journal of Business Ecosystem & Strategy (2687-2293) 2, no. 4 (March 27, 2021): 24–35. http://dx.doi.org/10.36096/ijbes.v2i4.229.

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The purpose of this paper is to compare three contemporary accident causation models, namely the Swiss Cheese, HFACS, and Fu (2018) Model-based on two accidents existing in the literature. The accidents reviewed are a mine explosion accident and an electrical plant accident. In this way, the validity of the models can be evaluated and weaknesses and strengths revealed. This study discussed the advantages and possible limitations of these models, and according to this discussion, all these models include human and organizational factors and have been found scientific and systematic. According to the results, Fu (2018) and HFACS are more modern, since they were developed based on Swiss Cheese. The product of this research will be a recommendation for safety investigators and accident inspectors which way to turn when choosing the most applicable accident analysis method

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Carthey, Jane. "Understanding safety in healthcare: the system evolution, erosion and enhancement model." Journal of Public Health Research 2, no. 3 (December 1, 2013): 25. http://dx.doi.org/10.4081/jphr.2013.e25.

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The paper summarises previous theories of accident causation, human error, foresight, resilience and system migration. Five lessons from these theories are used as the foundation for a new model which describes how patient safety emerges in complex systems like healthcare: the System Evolution Erosion and Enhancement model. It is concluded that to improve patient safety, healthcare organisations need to understand how system evolution both enhances and erodes patient safety.

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Yang, Zhengguo, Yuto Lim, and Yasuo Tan. "An Accident Model with Considering Physical Processes for Indoor Environment Safety." Applied Sciences 9, no. 22 (November 6, 2019): 4732. http://dx.doi.org/10.3390/app9224732.

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Accident models provide a conceptual representation of accident causation. They have been applied to environments that have been exposed to poisonous or dangerous substances that are hazardous in nature. The home environment refers to the indoor space with respect to the physical processes the of indoor climate, e.g., temperature change, which are not hazardous in general. However, it can be hazardous when the physical process is in some states, e.g., a state of temperature that can cause heat stroke. If directly applying accident models in such a case, the physical processes are missing. To overcome this problem, this paper proposes an accident model by extending the state-of-the-art accident model, i.e., Systems-Theoretic Accident Model and Process (STAMP) with considering physical processes. Then, to identify causes of abnormal system behaviors that result in physical process anomalies, a hazard analysis technique called System-Theoretic Process Analysis (STPA) is tailored and applied to a smart home system for indoor temperature adjustment. The analytical results are documented by a proposed landscape genealogical layout documentation. A comparison with results by applying the original STPA was made, which demonstrates the effectiveness of the tailored STPA to apply in identifying causes in our case.

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Wu, Chao, and Lang Huang. "A new accident causation model based on information flow and its application in Tianjin Port fire and explosion accident." Reliability Engineering & System Safety 182 (February 2019): 73–85. http://dx.doi.org/10.1016/j.ress.2018.10.009.

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Saxena, Dr Neeta. "Analysis of Road Traffic Accident using Causation Theory with Traffic Safety Model and Measures." International Journal for Research in Applied Science and Engineering Technology V, no. VIII (August 30, 2017): 1263–69. http://dx.doi.org/10.22214/ijraset.2017.8179.

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Miles, Margaret Shandor, and Alice Sterner Demi. "A Comparison of Guilt in Bereaved Parents whose Children Died by Suicide, Accident, or Chronic Disease." OMEGA - Journal of Death and Dying 24, no. 3 (May 1992): 203–15. http://dx.doi.org/10.2190/g41e-rktf-p0xd-ljlk.

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Based on a model of bereavement guilt developed by the investigators, this study assessed the frequency of guilt feelings, explored their sources, and compared the guilt experiences of parents whose children died by different modes–suicide, accident, and chronic disease. Of the 132 parents who participated in the study: sixty-two experienced a child's death by suicide; thirty-two by an accident; and thirty-eight by a chronic disease. Data from open-ended questions were analyzed using content analysis methods. Guilt feelings were reported by 92 percent of suicide bereaved parents, 78 percent of accident bereaved parents, and 71 percent of chronic disease bereaved parents. Furthermore, 34 percent of the suicide bereaved parents reported that guilt was the most distressing aspect of their grief, while none of the accident bereaved or chronic disease bereaved parents reported guilt as the most distressing aspect of their grief. Using the previously developed topology of guilt sources, findings supported the existence of six sources: Death Causation, Illness-related, Childrearing, Moral, Survival, and Grief Guilt. Sources differed by type of death. Death Causation and Childrearing Guilt were more prevalent among suicide and accident bereaved parents than among chronic disease bereaved parents. As expected, Illness-related Guilt was more prevalent in parents of children who died of chronic disease. Few parents reported Grief, Moral, or Survival Guilt. Implications of the findings for clinical practice with bereaved parents are discussed.

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Li, Wen-Chin, and Don Harris. "From Latent Failure to Active Failure: The Investigation of Human Errors in Aviation Operation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 20 (October 2007): 1425–29. http://dx.doi.org/10.1177/154193120705102011.

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The Human Factors Analysis and Classification System (HFACS, Wiegmann & Shappell, 2003) was developed as an analytical framework for the investigation of the role of human factors in aviation accidents. HFACS is based upon Reason's model (1990) of human error in which active failures are associated with the performance of front -line operators in complex systems and latent failures are characterized as inadequacies which lie dormant within a system for a long time, and are only trigge red when combined with other factors to breach the system's defenses. In this research HFACS was used to analyze accidents occurring in civil aviation aircraft in the Republic of China (ROC). Forty-one accident reports from the Aviation Safety Council (A SC) were analyzed. Relationships in the HFACS framework were identified linking fallible decisions at higher (organizational) levels with supervisory practices, thereby creating the preconditions for unsafe acts and hence indirectly impairing the performance of pilots.

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Kim, Dong-San, Dong-Hyun Baek, and Wan-Chul Yoon. "A Proposition of Accident Causation Model for the Analysis of Human Error Accidents in Railway Operations." Journal of the Ergonomics Society of Korea 29, no. 2 (April 30, 2010): 241–48. http://dx.doi.org/10.5143/jesk.2010.29.2.241.

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Hu, Shenping, Zhuang Li, Yongtao Xi, Xunyu Gu, and Xinxin Zhang. "Path Analysis of Causal Factors Influencing Marine Traffic Accident via Structural Equation Numerical Modeling." Journal of Marine Science and Engineering 7, no. 4 (April 4, 2019): 96. http://dx.doi.org/10.3390/jmse7040096.

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Many causal factors to marine traffic accidents (MTAs) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to accident mechanisms, the complex structural chains on causes to MTA systems were analyzed by combining the human failure analysis and classification system (HFACS) with theoretical structural equation modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of a MTA, and the constituent elements of the causes of the accident were conducted. Second, a hypothetical model of human factors classification was proposed by applying the practice of the structural model. Third, with the data resources from ship accident cases, this hypothetical model was discussed and simulated, and as a result, the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behavior. Application examples show that relationships in the HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

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Jeong, Jung Sik, Gyei-Kark Park, and Kwang Il Kim. "Risk Assessment Model of Maritime Traffic in Time-Variant CPA Environments in Waterway." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 7 (November 20, 2012): 866–73. http://dx.doi.org/10.20965/jaciii.2012.p0866.

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This paper proposes a quantitative model for assessing collision risk for maritime traffic in waterways. The proposed method reflects recent maritime traffic characteristics under in time-variant CPA environments in waterways and models a dynamic causation factor as a risk indicator. To eliminate an uncertainty by human factors causing maritime accidents, the proposed model combines maritime accident statistics and weather records with spatial and temporal distribution determined on the basis of recent and real data for ship movements. Because our method reflects the characteristics of recent ship movements in the water area, it can be complementarily used with the conventional model using Bayesian Belief Network (BBN).

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Ouyang, Yanfeng, Venky Shankar, and Toshiyuki Yamamoto. "Modeling the Simultaneity in Injury Causation in Multivehicle Collisions." Transportation Research Record: Journal of the Transportation Research Board 1784, no. 1 (January 2002): 143–52. http://dx.doi.org/10.3141/1784-18.

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Constrained by the single-equation specification, traditional logit or probit models for traffic accident severities can only model one severity at a time. Single-equation models fail to account for the simultaneity of injury severity outcomes in multivehicle collisions. An attempt to account for this simultaneity is made by presenting a simultaneous logit model of endogenous interrelationships among injury severities in multivehicle collisions. Car-truck collision data in Washington State between 1990 and 1996 are used for a simultaneous binary logit model to determine the effects of various exogenous factors in the presence of injury simultaneity, and empirical comparisons with traditional single-equation logit models are also provided. The methodology presented provides for significant efficiency gain when correlation between injury severities is high and can easily be extended to multiple severity categories in multiple-vehicle collisions. Empirically, it is also found that parameter estimates for key roadway design variables may vary greatly between a simultaneous logit and its single-equation counterparts. Another finding from this methodology is that preventive measures for head-on collisions, or enforcement of drunk-driving regulations among truck drivers, as well as limiting the occurrence of high-speed curve designs on truck routes, appear to be the most likely factors for significant potential savings in social costs from car-truck collisions.

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Wu, Bing, Huibin Tian, Xinping Yan, and C. Guedes Soares. "A probabilistic consequence estimation model for collision accidents in the downstream of Yangtze River using Bayesian Networks." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 2 (February 22, 2019): 422–36. http://dx.doi.org/10.1177/1748006x19825706.

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Collision is a major type of accident in maritime transportation, which in the downstream of Yangtze River is even more pronounced due to specific features that have significant impact on the collision consequence, including a special lane for small-sized ships, traffic intensity variation with the tide period, many restricted areas, and emergency resources spread along the river. This article models the collision consequences in the downstream of Yangtze River using Bayesian Networks, considering the causation factors and including a novel approach for the emergency management of maritime accidents. The graphical structure lies on domain experts and on previous works, while the conditional probability tables are developed from historical data. Both the graphical structure and parameters are validated using the well-known methods, which reflects that the developed model is reasonable. The merits of the proposed consequence estimation model that considers emergency management includes (1) a detailed description of the collision accident development and (2) consequence estimation result with good accuracy.

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Li, Keping, Xin Ma, and Fubo Shao. "An improved network model for railway traffic." International Journal of Modern Physics C 28, no. 03 (March 2017): 1750037. http://dx.doi.org/10.1142/s0129183117500371.

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In railway traffic, safety analysis is a key issue for controlling train operation. Here, the identification and order of key factors are very important. In this paper, a new network model is constructed for analyzing the railway safety, in which nodes are regarded as causation factors and links represent possible relationships among those factors. Our aim is to give all these nodes an importance order, and to find the in-depth relationship among these nodes including how failures spread among them. Based on the constructed network model, we propose a control method to ensure the safe state by setting each node a threshold. As the results, by protecting the Hub node of the constructed network, the spreading of railway accident can be controlled well. The efficiency of such a method is further tested with the help of numerical example.

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Gharaie, Ehsan, Helen Lingard, and Tracy Cooke. "Causes of Fatal Accidents Involving Cranes in the Australian Construction Industry." Construction Economics and Building 15, no. 2 (May 30, 2015): 1–12. http://dx.doi.org/10.5130/ajceb.v15i2.4244.

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In ten years from 2004 to 2013, 359 workers died in the Australian construction industry because of work related causes. This paper investigates crane-related fatalities in order to find the upstream causation of such accidents. The National Coroners’ Information System (NCIS) database was searched to identify fatal accidents in the construction industry involving the use of a crane. The narrative description of the cases provided in the coroners’ findings and associated documents were content analysed to identify the contributing causal factors within the context of each case. The findings show that the most frequent crane-related accident types were those that were struck by load, and electrocution. The most prevalent immediate circumstance causes were layout of the site and restricted space. The two most commonly identified shaping factors were physical site constraints and design of construction process. Inadequate risk management system was identified as the main originating influence on the accidents. This paper demonstrates that a systemic causation model can provide considerable insight into how originating influences, shaping factors, and immediate circumstances combine to produce accidents. This information is extremely useful in informing the development of prevention strategies, particularly in the case of commonly occurring accident types.

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Journal articles on the topic 'Reason's model of accident causation'

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