Accidents data analysis

Figure 1. Construction safety checklist scores and accidents data analysis.

Glendon, A.1.1991. Accident data analysis. Journal of Health and Safety, 1,5-24. 

One example of a component-based testing method is the Vehicle Related Pedestrian Safety Index (VERPS) [73, 74]. This index utilizes a linear scale for both active and passive safety measures. The pedestrian head impact in frontal passenger vehicle collisions is assessed using the Head Injury Criterion (HIC) as metric. The method delivers specific results for a given vehicle and pedestrian combination. The evaluation process includes accident data analysis for relevant scenarios, kinematic analysis (via multi-body simulation), hardware component testing, and a procedure to obtain the VERPS index [73, 74]. The VERPS index takes only the probability for AIS3+ head injuries due to impact on the vehicle into account, since this probability can be derived from the HIC measurement. 

Boyle, A. J., Accident Data Analysis with Microcomputers - An Update, The Safety Practitioner, 4, No 11, 11 (1986)... 

The method for accident data analysis followed in this paper, provided a deeper view of the amount and the characteristics of accidents suffered by vessels during winter time in the Baltic Sea. This study has considered two kinds of winters in the Baltic Sea the winter before the ice sea is present, and the winter under ice sea conditions. This differentiation allowed to accurately identify the types of accidents which are more frequently occurring... 

Regarding accident data analysis and identification of critical scenarios, the currently ongoing EU project Improving the safety and mobility of vulnerable road users through ITS applications [VRU 13], gives an overview on European cyeling accident data. Analysis of a range of databases has been conducted to identify scenarios for cyclists. The CARE database (European Road Accident Database) has been used as the most widely available database for EU accidents and data fiom national databases of Austria, Finland, Spain, Sweden and the UK have been... 

Accident data analysis and identification of critical scenarios... 

Oil and Gas Industry Accident Data and Accident Data Analysis... 

This chapter presents various important aspects of the oil and gas industry accident data and accident data analysis. 

Chapter 9 presents various important aspects of oil and gas industry accident data and accident data analysis. Some of the topics covered in this chapter are oil and gas industry accident databases, onshore and offshore oil and gas industry accident data analysis, and offshore oil and gas rigs accident analysis. Chapter 10 is devoted to oil and gas industry equipment reliability and covers topics such as oil and gas pipeline fault tree analysis, corrosion-related failures, optical connector failures, and fatigue damage initiation assessment in oil and gas steel pipes. 

The frequency analysis step involves estimating the likelihood of occurrence of each of the undesired situations defined in the hazard identification step. Sometimes you can do this through direct comparison with experience or extrapolation from historical accident data. While this method may be of great assistance in determining accident frequencies, most accidents analyzed by QRA are so rare that the frequencies must be synthesized using frequency estimation methods and models. 

Other important considerations in the design of an IRS are the data storage and analysis requirements. These need to be considered early in the design of the system if it is to be used to research and display trends effectively. For example, in addition to the answers to specific questions, the accident data analyst may wish to make use of free text descriptions of the circumstances of the accident. This implies that a text-based retrieval system will be required. 

Fisher et al. (1991) Biokinetic Model A modified biokinetic model for uranium was developed for inhaled soluble uranium based on human data from an accidental release of uranium hexafluoride in Oklahoma. Urinary excretion data from 31 exposed workers were used to test two previously published compartmental models for inhalation exposure to uranium (ICRP 1979 Wrenn et al. 1989). Urinary uranium was measured periodically for 2 years following the accident. Statistical analysis showed that the Wrenn et al. (1989) model produced a better fit to the excretion data than the ICRP (1979) model. 

In my view, realistic safety information should form a specific section in a job description. Figure 3.1 is an example of what a safety section in a job description might look like. The acmal information in the safety section of a job description should be derived from a careful analysis of the job, from internal accident data associated with the job, and from global accident trends associated with the job. For the information to help with expectation setting, it needs to be as realistic (accurate) as possible. Furthermore, the organization should not distort or adjust the ratings based on their expectations of how safety management systems are likely to reduce the risks. 

Chua, D.K.H. and Goh, Y.M. (2004) Utilising the modified loss causation model for the codification and analysis of accident data. In S. Rowlinson (ed.). Construction Safety Management Systems, pp. 443-63. Spon Press, London. 

Note Sometimes data are valid only in special circumstances. For instance, a statistical sourcemay indicate that a specific number of aircraft accidents due to bird strikes take place every 100,000 hours. One may conclude from this data that the probability of a bird strike is comparatively low. Hidden by the data analysis proach is the fact that at certain airfields, such as Boston, the Midway Islands and other coastal and insular areas where birds abound, the probability of a bird strike accident is much higher fiian file average. This example demonstrates that generalized probabilities will not serve well for specific, localized areas. This applies to other environmental hazards such as lightning, fog, rain, snow and hurricanes. 

The evaluation of the current status of OHS at Estonian workplaces is performed using statistical data derived from National Labour Inspectorate (NLI) as well as Statistical Office of the European Communities (Eurostat). Additionally, visits to enterprises from different industries were performed focusing on data about risk assessment and its quality as well as the characterization of occupational accidents occurred. Analysis of safety level in a company of the clothing industry is presented as an illustration. 

Wiegmann, D.A. Shappell, S.A. 2001. Applying the human factor analysis and classification system to the analysis of commercial aviation accident data. Paper presented at the 11th International Symposium on Aviation Psychology. 

Both Ps and Pa can be estimated from an analysis of historical accident data. The principal challenge is in developing a statistical approach for estimating Pe as a function of lightning-strike intensity, induced transient levels, and equipment sensitivity. In addition, the Pe values for several equipment types must be considered when determining a system failure probability. 

The following breakdown in physical conditions is preliminary. More data analysis is necessary. It looks like airport complexity is one of the smallest contributions (Fig. 7) and traffic volumes have the most effect on fatal accident frequency. 

Kvaley, J.T. and Aven, T. 2005, An alternative approach to trend analysis of accident data. RdiabiUty Engineering and System Safety, 90, 75-82... 

In order to give statistical consistence to the analysis, it is of high importance to have a set of accident data covering a long period and related to railways with almost the same characteristics as the ItaUan database that collects accidents information covering the period... 

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