Accident Scenario Results

Dutyholders should review their arrangements to communicate with people and establishments likely to be affected by a major accident to ensure that this information takes account of any additional major accident scenarios resulting from, for example, a large flammable vapour cloud. 

The subsequent step is to identify the various scenarios which could cause loss of control of the hazard and result in an accident. This is perhaps the most difficult step in the procedure. Many accidents have been the result of improper characterization of the accident scenarios. For a reasonably complex chemical process, there might exist dozens, or even hundreds, of scenarios for each hazard. The essential part of the analysis is to select the scenarios which are deemed credible and worst case. 

Hazard analysis does have limitations. First, there can never be a guarantee that the method has identified all of the hazards, accident scenarios, and consequences. Second, the method is very sensitive to the assumptions made by the analysts prior to beginning the procedure. A different set of analysts might well lead to a different result. Third, the procedure is sensitive to the experience of the participants. Finally, the results are sometimes difficult to interpret and manage. 

QRA results can guide decision makers in their quest for continuous improvement in risk reduction, but zero risk is an unattainable goal. Any activity involves some risk. Even if it were hypothetically possible to eliminate the risk of every accident scenario in a QRA, some risk would still remain because no QRA examines every possible accident scenario. At best a QRA identifies the dominant contributors to risk from the system as it existed at the time of the analysis. Once those are eliminated, other minor risk contributors (including many that were left out of the original QRA because they were negligible contributors, as well as new risks introduced by changes to eliminate the original risks) remain as the new dominant risk contributors. 

In any case, like frequency analysis, examining the uncertainties and sensitivities of the results to changes in boundary conditions and assumptions provides greater perspective. The level of effort required for a consequence analysis will be a function of the number of different accident scenarios being analyzed the number of effects the accident sequence produces and the detail with which the release, dispersion, and effects on the targets of interest is estimated. The cost of the consequence analysis can typically be 25% to 50% of the total cost of a large QRA. 

Layer of protection analysis (LOPA) is a simplified form of event tree analysis. Instead of analyzing all accident scenarios, LOPA selects a few specific scenarios as representative, or boundary, cases. LOPA uses order-of-magnitLide estimates, rather than specific data, for the frequency of initiating events and for the probability the various layers of protection will fail on demand. In many cases, the simplified results of a LOPA provide sufficient input for deciding whether additional protection is necessary to reduce the likelihood of a given accident type. LOPAs typically require only a small fraction of the effort required for detailed event tree or fault tree analysis. 

A valuable QRA result is the importance of various components, human errors, and accident scenarios contributing to the total risk. The risk importance values highlight the major sources of risk and give the decision maker a clear target(s) for redesign or other loss prevention efforts. For example, two accident scenarios may contribute 90% of the total risk once you realize that, it is obvious that you should first focus... 

This section describes how both hypothetical and real accidents are analyzed. These methods varying greatly in complexity and resource requirements, and multiple methods may be used in an analysis. A simple method is used for screening and prioritization followed by a more complex method for significant accident scenarios. Some methods give qualitative results more complex methods give quantitative results in the form of estimated frequencies of accident scenarios. The process systems in Figures 3.3.1-1 and 3.3.1-2 are used in the examples. 

The results of a What-If/Checklist analysis are documented like the results of a What-lf analysis as a table of accident scenarios, consequences, safety levels, and action items. The results may also include a completed checklist or a narrative. The PrHA team may also document the completion of the checklist to illustrate its completeness. The PSM rule requires detailed... 

The critical results of a PrHA are a list of action items. Action items are written by the PrHA team any time additional effort is warranted to further analyze a specific accident scenario, eliminate the hazard, or reduce risks. Action items are not usually specific corrective actions. Rather, they alert management to potential problems that require action. Sometimes, action items suggest alternatives or recommend safety improvements. However, if a problem is simple, if a PrHA team is quite experienced, or if there is only one solution, an action item may recommend a specific corrective action. 

The damage resulting from the explosion made it impossible to reconstruct the actual accident scenario. However, evidence showed that the standard operating procedures were not appropriately followed. 

We focus on determining the frequency of accident scenarios. The last two sections show how the frequencies are used in QRA and LOPA studies LOPA is a simplified QRA. It should be emphasized that the teachings of this chapter are all easy to use and to apply, and the results... 

Develop an investigation similar to Example 12-1 and an investigation summary for an automobile accident that occurred as a result of a brake failure. Create your own brief accident scenario for this problem. 

Another problem, also identified by Rasmussen (Rasmussen et al., 2000), is that individual actors in the control processes cannot see the effects of their actions in respect to the total picture. Subsequently, acceptance by different actors on different control levels, allows more gaps in different safety barriers. Together, this enables precursors to penetrate the different safety barriers through an alignment of these gaps resulting in an accident scenario. Further research is needed to retrieve insights into how the overview of the total picture and the different effects of the actions of individual actors can be retrieved in theory and practice. 

Another type of qualitative insight could be the result of regularly discussing unusual or unique near misses, i.e. new or unexpected combinations of circumstances might trigger an Aha experience with safety staff members and other employees. This means that their set. of "possible accident scenarios ... 

We must emphasize, however, that many of the unit operations encountered in the analytical laboratory are timeless. These tried and true operations have gradually evolved over the past two centuries. From time to time, the directions given in this chapter may seem somewhat didactic. Although we attempt to explain why unit operations are carried out in the way that we describe, you may be tempted to modify a procedure or skip a step here or there to save time and effort. We must caution you against modifying techniques and procedures unless you have discussed your proposed modification with your instructor and have considered its consequences carefully. Such modifications may cause unanticipated results, including unacceptable levels of accuracy or precision in a worst-case scenario, a serious accident could result. Today, the time required to prepare a carefully standardized solution of sodium hydroxide is about the same as it was 100 years ago. 

To provide the most realistic representation of risk, all forms of uncertainty arc considered. Rather than assuming the existence of some representative condition prior to the accident scenario, a study models the full range of conditions and other uncertainties that can affect the scenario. Results include uncertainties in the frequency and consequences of each scenario. The upper uncertainty bound shown for the QRA risk estimates is a measure of the analysts confidence in the results. There is a 95 percent chance that the risk is less than the upper bound. 

In this step, recombination (crossover) and mutation operators are applied to the individuals selected for reproduction in the previous step. The number of chromosomes, which will be reproduced by crossover operation, as well as, crossover points, can be determined either deterministically by the user or randomly. For example, in case of one-point crossover (see for example in Fig. 11.4) the chromosomes of the parents are cut at some randomly chosen point and the resulting subchromosomes are swapped. As far as the mutation operator is concerned, the user gives the number of genes to be changed per generation. The points to be mutated are chosen either randomly or deterministically according to the accident scenario considered (see for example in Fig. 11.4). 

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