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Journal articles on the topic 'Accident Causation/ Accident Patterns'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Young, Stephen L., and Lobat Hashemi. "Fatigue and Trucking Accidents: Two Modes of Accident Causation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 18 (October 1996): 952–56. http://dx.doi.org/10.1177/154193129604001819.

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The U.S. National Transportation Safety Board investigated 113 heavy-truck accidents to determine “the role of specific factors, such as drivers' patterns of duty and sleep, in fatigue-related heavy truck accidents” (NTSB, 1995a). For a number of reasons, we believed that a re-analysis of this data, with a different set of variables, might yield a more complete picture regarding the nature of fatigue-related accidents and their causes. Specifically, principal components analysis was employed to determine the underlying factors that contributed to accidents where fatigue was determined to be the primary cause. In this analysis, two principal components were extracted that dealt with (1) the nature of the driver's sleep periods and level of experience, and (2) aspects of the driver's work periods. Subsequent cluster analysis demonstrated that the cases could be divided into two distinct accident modes or types: those with and those without regular sleep/work patterns. Drivers with generally regular sleep/work patterns appeared to develop fatigue while on the job, while those with irregular sleep/work patterns appeared to arrive at the job already fatigued. In conclusion, the variables which contributed to fatigue in the NTSB report were found to contribute to fatigue in the present analysis, but not to the same extent in all cases. Some of the variables that influenced driver fatigue in one of the clusters (or accident modes) had no effect on the other. These different accident modes should be considered when examining the effect of a given variable on fatigue.

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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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3

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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4

Link, Bruce G. "Epidemiological Sociology and the Social Shaping of Population Health." Journal of Health and Social Behavior 49, no. 4 (December 2008): 367–84. http://dx.doi.org/10.1177/002214650804900401.

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When biomedical knowledge and technology create the capacity for humans to avoid disease and circumvent early death, sociological factors become more, not less important for population health. The transformation of disease causation from cruel fate, accident, and bad luck to circumstances that are under some degree of human control facilitates a powerful social shaping of disease and death. When humans have control, it is their policies, their knowledge, and their behaviors that shape the consequences of biomedical accomplishments, and thereby extant patterns of disease and death. I propose a “social shaping approach” that can frame our understanding of these processes and allow us to take action to optimize population health. Support for this approach is garnered from evidence of dramatic improvements in population health and in the uneven distribution of those improvements across persons, places, and times. Health improvements suggest that humans have gained control of disease whereas the uneven and very slow spread of such improvements underscores the critical importance of social factors. But the evidence presented represents a stick figure at best, one that needs to be filled in by a well-supported “epidemiological sociology” that uses a wide range of sociological concepts and theories to elucidate the social shaping of disease and death. Absent a robust societal investment in epidemiological sociology, population health will reside below its optimal level and the maldistribution of health-enhancing innovations will continue to create health disparities.

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5

Elvik, Rune. "Laws of accident causation." Accident Analysis & Prevention 38, no. 4 (July 2006): 742–47. http://dx.doi.org/10.1016/j.aap.2006.01.005.

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6

Acharya, Sumnima, Awadesh Tiwari, and Raju Prasad Shakya. "Clinico-radiological Profile of Stroke in Western Nepal." Journal of Lumbini Medical College 4, no. 2 (December 30, 2016): 60. http://dx.doi.org/10.22502/jlmc.v4i2.91.

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Introduction: Stroke is a major public health burden worldwide and is responsible for a large proportion of disability. It ranks third in the causation of morbidity and mortality. This study was carried out to establish the pattern of various types of cerebrovascular accident (CVA) in western Nepal, to correlate the clinical data and radiological findings in cases of stroke, and to identify the common risk factors associated with stroke. Methods: A total of 200 patients presented at the department of Radiodiagnosis from emergency or ward within six months of study period from 18th of September 2015 to 17th of March 2016 with clinical diagnosis of stroke. Brain CT scan was done within 14 days of onset. Results: There were 200 patients with stroke (124 males and 76 females), aged 19 to 92 years in which infarction was more common than hemorrhage (57% Vs 41.5%) clinically. Hypertension was the commonest risk factor noted in 59% cases followed by Diabetes Mellitus in 39%. Middle cerebral artery (MCA) territory infarction was the most common site of infarction. Clinical and CT localization of hemorrhage and infarct was correct in 153 cases (75%) which was statistically significant. Conclusion: Infarction is more common than hemorrhage as the type of stroke. Hypertension is the commonest risk factor followed by diabetes mellitus.

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7

Williamson, Ann M., Anne-Marie Feyer, and David R. Cairns. "Industry differences in accident causation." Safety Science 24, no. 1 (October 1996): 1–12. http://dx.doi.org/10.1016/s0925-7535(96)00025-2.

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8

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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9

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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10

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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11

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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12

WAGENAAR, WILLEM A., and JAMES T. REASON. "Types and tokens in road accident causation." Ergonomics 33, no. 10-11 (October 1990): 1365–75. http://dx.doi.org/10.1080/00140139008925338.

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13

Kwon, Hyuckmyun, Hyungjoon Yoon, and Il Moon. "INDUSTRIAL APPLICATIONS OF ACCIDENT CAUSATION MANAGEMENT SYSTEM." Chemical Engineering Communications 193, no. 8 (August 2006): 1024–37. http://dx.doi.org/10.1080/00986440500352089.

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14

Hudson, Patrick. "Accident causation models, management and the law." Journal of Risk Research 17, no. 6 (March 6, 2014): 749–64. http://dx.doi.org/10.1080/13669877.2014.889202.

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15

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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16

Griffin, T. G. C., M. S. Young, and N. A. Stanton. "Investigating accident causation through information network modelling." Ergonomics 53, no. 2 (January 22, 2010): 198–210. http://dx.doi.org/10.1080/00140130903125165.

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17

Lozada-Larsen, Susana R., and Kenneth R. Laughery. "Do Identical Circumstances Preceed Minor and Major Injuries?" Proceedings of the Human Factors Society Annual Meeting 31, no. 2 (September 1987): 200–204. http://dx.doi.org/10.1177/154193128703100214.

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The identical causation hypothesis contends that identical causes or circumstances preceed minor and major injuries in accidents. Tests of the identical causation hypothesis were carried out by examining frequencies of prior activities, accident events and injury events across minor and major injuries, including a breakdown by job family. Also, combinations of variables (scenerios) for minor and major injuries were examined. For the individual accident variables, the data clearly support a similar causation hypothesis. However, for the combinations of accident variables, differences were discerned between minor and major injuries. Overall, the present test of the identical causation hypothesis suggests that similar preceeding circumstances may underly both minor and major injuries.

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18

Salmon, PM, N. Goode, MG Lenné, C. Finch, and E. Cassell. "Understanding accident causation in led outdoor activities: development of an accident analysis framework." Injury Prevention 18, Suppl 1 (October 2012): A240.1—A240. http://dx.doi.org/10.1136/injuryprev-2012-040590w.53.

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19

Meng, Xiang Yun, Ri Hui Chen, and Shi Bin Wang. "The Gray Relation Analysis of Non-Coal Mine Accidents Causation." Advanced Materials Research 989-994 (July 2014): 2306–9. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2306.

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The Gray Relation Analysis is applied to the casualty analysis of non-coal mine accident in four certain years in China to export grey relational order to determine the main related factors in the non-coal mine accident, obtaining quantitative analysis results of the relationship between non-coal mine accident and multiple factors, introducing the concept of mine accident risk correlation degree.

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20

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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21

Grant, Eryn, Paul M. Salmon, Nicholas J. Stevens, Natassia Goode, and Gemma J. Read. "Back to the future: What do accident causation models tell us about accident prediction?" Safety Science 104 (April 2018): 99–109. http://dx.doi.org/10.1016/j.ssci.2017.12.018.

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22

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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23

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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24

Hasle, Peter, Pete Kines, and Lars Peter Andersen. "Small enterprise owners’ accident causation attribution and prevention." Safety Science 47, no. 1 (January 2009): 9–19. http://dx.doi.org/10.1016/j.ssci.2007.12.005.

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25

Usami, Davide Shingo, Gabriele Giustiniani, Luca Persia, and Roberto Gigli. "Aggregated analysis of in-depth accident causation data." International Journal of Injury Control and Safety Promotion 24, no. 2 (September 24, 2015): 165–73. http://dx.doi.org/10.1080/17457300.2015.1088037.

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26

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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27

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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Katsakiori, Panagiota, George Sakellaropoulos, and Emmanuel Manatakis. "Towards an evaluation of accident investigation methods in terms of their alignment with accident causation models." Safety Science 47, no. 7 (August 2009): 1007–15. http://dx.doi.org/10.1016/j.ssci.2008.11.002.

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29

Pillay, Mani. "Improving Organisational Health and Safety Performance: Theoretical Framework and Contemporary Approaches." International Journal of Management Excellence 7, no. 3 (October 31, 2016): 855–66. http://dx.doi.org/10.17722/ijme.v7i3.860.

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This paper is reviews accident causation, prevention and occupational health and safety (OHS) management as an opportunity for improving organisational performance. A theoretical framework based on a periodization scheme is introduced first. This is then used to examine theoretical and practical developments in two inter-twined areas of research; accident causation and OHS management. The key premises, limitations and implications for practice are integrated into this review. The paper concludes with some identified gaps in research and opportunities for progressing organisational OHS performance.

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Amorim, Ana Gabriella, and Claudio M. N. A. Pereira. "Improvisation at Workplace and Accident Causation - An Exploratory Study." Procedia Manufacturing 3 (2015): 1804–11. http://dx.doi.org/10.1016/j.promfg.2015.07.219.

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31

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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32

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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Cabral, Lenz Alberto Alves, Zaida Aurora Sperli Geraldes Soler, and José Carlos Lopes. ""Dual causation accident": a third type of work-related accident and its importance for occupational health surveillance." Ciência & Saúde Coletiva 19, no. 12 (December 2014): 4699–708. http://dx.doi.org/10.1590/1413-812320141912.07722013.

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The scope of this study is to contribute to the improvement of Occupational Health Surveillance in the Unified Health System (UHS), through the recognition and inclusion of a third type of work-related accident in the current Brazilian legislation classification: the dual causation accident. This classification aims at facilitating the establishment of a causal connection, thus broadening the understanding of the relationship between work process and the production of diseases. It also aims at improving legal rules to protect the health of workers. This approach, besides enabling the identification of sentinel events (starting point of surveillance activities), might contribute not only to a decrease in underreporting of work-related accidents, but also to the uniformity of concepts and the implementation of integrated actions of the National Social Security Institute (NISS), the UHS, the Ministry of Labor (MLE) and the Judiciary for the protection of workers. To propose a third type of occupational accident, a study of occupational accidents and causes of underreporting was conducted, with reference to the Brazilian labor legislation in the context of the National Policy on Occupational Health and the UHS.

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Arif, Mariam, and Syed Hamad Rasool. "PHYSICAL INJURIES;." Professional Medical Journal 24, no. 11 (November 3, 2017): 1727–32. http://dx.doi.org/10.29309/tpmj/2017.24.11.660.

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Introduction: Injury is one of the leading causes of mortality and morbidityworldwide. Objectives: The aim of the study was to determine the pattern of physical injuriesin medicolegal cases presented to Services hospital, Lahore. Study Design: Descriptive study.Setting: Accident and emergency department of Services hospital, Lahore. Period: 1stJanuary2014 and 31stDecember 2014. Method: All cases presenting for medico legal examination withphysical injuries were included. Data was collected regarding age, gender, types of injuries,body area involved, causative weapon and whether certification of injuries was done accordingto Qisas and Diyat Ordinance. Results: A total of 86.4% cases were of physical injuries. Out ofthese cases, 73% of blunt weapon, 11% of firearm weapon, 10% of sharp weapon, 4%of roadtraffic accidents and1.5 % of bomb blast presented in the medico-legal clinic. Males (87.4%)outnumbered females (12.5%) Almost two-third of victims (64.2%) were between 21 and 40years of age. The head and neck were the areas most commonly injured in cases of blunttrauma 48.3% while limbs were more likely to be involved in other physical injuries. All caseswere certified according to Qisas and Diyat Ordinance. Conclusion: It is the hour of need thatboth public and private sectors work together in devising and implementing effective injuryprevention programs.

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35

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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36

Salmon, Paul, Adam Hulme, Guy H. Walker, Patrick Waterson, and Neville A. Stanton. "The Accident Network (AcciNet): A new accident analysis method for describing the interaction between normal performance and failure." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (December 2020): 1676–80. http://dx.doi.org/10.1177/1071181320641407.

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Accidents continue to create an unacceptable personal, social, and economic burden in many domains. Various accident analysis methods exist; however, key limitations have been identified. This paper describes a new accident analysis method, the Accident Network (AcciNet), that was recently developed as part of an ongoing collaboration between Human Factors and Ergonomics research groups from Australia and the United Kingdom. The method is demonstrated via an analysis of the Uber-Volvo fatal pedestrian collision. The analysis demonstrates how AcciNet goes beyond current state-of-the-art accident analysis methods to consider the role of normal performance in accident causation and identify the interrelations between failures, normal performance, and both human and non-human actors in the system. We describe the implications for accident analysis in practice and outline the next steps of the research program, including formal reliability and validity testing of AcciNet and the development of practical training materials.

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Zhang, Jin Feng, Zai Xing Li, Xin Liu, and Zhong Qiang Sun. "Safety System Analysis on Gas-Steam Combined Cycle Power Plant." Advanced Materials Research 860-863 (December 2013): 1458–63. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.1458.

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Risk factor in gas-steam combined cycle power plant (CCPP) was identified by application of safety system engineering principles and techniques. The CCPP system was divided into gas transmission subsystem, gas turbine subsystem, waste heat boiler subsystem, steam turbine subsystem and generation & transformation subsystem. The accident-proneness areas in each subsystem were studied, and various accident-causation modes were clarified. The bursting leakage accident caused by failure of steam-water pipelines was analyzed, and evaluated with Fault Tree method. The targeted countermeasures of safe operation and management were proposed.

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Ancel, Ersin, Ann T. Shih, Sharon M. Jones, Mary S. Reveley, James T. Luxhøj, and Joni K. Evans. "Predictive safety analytics: inferring aviation accident shaping factors and causation." Journal of Risk Research 18, no. 4 (July 18, 2014): 428–51. http://dx.doi.org/10.1080/13669877.2014.896402.

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39

Xi, Jianfeng, Zhonghao Zhao, Wei Li, and Quan Wang. "A Traffic Accident Causation Analysis Method Based on AHP-Apriori." Procedia Engineering 137 (2016): 680–87. http://dx.doi.org/10.1016/j.proeng.2016.01.305.

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40

Smith, E. J., and M. J. Harris. "The Role of Maintenance Management Deficiencies in Major Accident Causation." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 206, no. 1 (February 1992): 55–66. http://dx.doi.org/10.1243/pime_proc_1992_206_198_02.

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There appears to be an increasing awareness that organizational and managerial factors play a critical role in ensuring plant safety. A detailed study is presented of one branch of industrial management, viz. maintenance management. It has highlighted the nature of some of the links between managerial practices and the reliability of plant equipment and personnel. The causes of several major accidents are analysed using a systems approach, with the aim of understanding how the maintenance function was involved. A key conclusion is that, prior to major accidents, there is often a lack of detailed safety objectives and long-term safety control. Without these it becomes very difficult to assess the adequacy or otherwise of other maintenance management elements such as maintenance strategy, resources or administrative structure. In the absence of tight safety and reliability control and consequent corrective actions a mismatch can develop between the perceptions of management and the actual condition of the plant.

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Arboleda, Carlos A., and Dulcy M. Abraham. "Fatalities in Trenching Operations—Analysis Using Models of Accident Causation." Journal of Construction Engineering and Management 130, no. 2 (April 2004): 273–80. http://dx.doi.org/10.1061/(asce)0733-9364(2004)130:2(273).

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Lehto, Mark, and Gavriel Salvendy. "Models of accident causation and their application: Review and reappraisal." Journal of Engineering and Technology Management 8, no. 2 (August 1991): 173–205. http://dx.doi.org/10.1016/0923-4748(91)90028-p.

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Fu, Gui, Jia-Lin Cao, Lin Zhou, and Yuan-Chi Xiang. "Comparative study of HFACS and the 24Model accident causation models." Petroleum Science 14, no. 3 (July 5, 2017): 570–78. http://dx.doi.org/10.1007/s12182-017-0171-4.

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Talbot, Rachel, Helen Fagerlind, and Andrew Morris. "Exploring inattention and distraction in the SafetyNet Accident Causation Database." Accident Analysis & Prevention 60 (November 2013): 445–55. http://dx.doi.org/10.1016/j.aap.2012.03.031.

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45

Otte, Dietmar, Michael Jänsch, and Carl Haasper. "Injury protection and accident causation parameters for vulnerable road users based on German In-Depth Accident Study GIDAS." Accident Analysis & Prevention 44, no. 1 (January 2012): 149–53. http://dx.doi.org/10.1016/j.aap.2010.12.006.

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Nyoni, Wonder, Manikam Pillay, Mark Rubin, and Marcus Jefferies. "Organizational Factors and Risk Management in the Mining Industry." International Journal of Occupational and Environmental Safety 3, no. 3 (November 15, 2019): 53–69. http://dx.doi.org/10.24840/2184-0954_003.003_0006.

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Organizational factors are considered part of the broader human factors domain and have long been suspected to have a significant influence on individual and group behavior in the workplace, although there is little research on their influence in mining workplaces. This paper provides an update of a systematic literature review (SLR), reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis: The PRISMA Statement 2009. The SLR examined the relationship between organizational factors and residual risk management in the context of accident causation in mining. Six electronic databases were searched for peer-reviewed studies published between 1980 and 2018. Following eligibility criteria, 28 studies were selected for quality assessment and reviewed. The results of the SLR included the identification of several organizational factors that are common in the mining industry, as well as the existence of a conceptual relationship between organizational factors, residual risk management and accident causation. In particular, the review found that about two-thirds of the eligible articles acknowledged a linkage between organizational factors and accident causation. The SLR also identified several research gaps associated with the lack of empirical research around the relationship between organizational factors, residual risk and accident causation. More importantly, the review found no empirical studies that utilized the term residual risk thus implying a gap and inconsistency in risk taxonomy in the mining industry. In light of these gaps, further research is recommended to examine the nature and extent of the influence of organizational factors on residual risk management, with particular focus on examining the influence of organizational factors on the functioning and effectiveness of risk controls. It is envisaged that by improving the efficacy of risk controls, mining companies can ultimately improve their safety performance and make it more sustainable.

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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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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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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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Woodcock, Kathryn. "Simulated Investigation of Hypothetical Accidents: Learning about Causation, Causal Reasoning, and Investigation Bias." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 8 (September 2002): 810–14. http://dx.doi.org/10.1177/154193120204600811.

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