Qualitative analysis logic

Let s look at each of these five groups of cations, briefly examining the logic used in this qualitative analysis scheme. 

Fault Tree Analysis (FTA) is a well known and widely used safety tool, implementing a deductive, top down approach. It starts with a top level hazard, which has to be known in advance and "works the way down" through all causal factors of this hazard, combined with Boolean Logic (mainly AND and OR gates). It can consider hardware, software and human errors and identifies both single and multiple points of failure. Both a quantitative and qualitative analysis is possible. 

Within the overall aim it is the task of quantitative safety analysis to ascertain the frequency or occurrence probability of undesired events leading to incidents. Safety analysis will, in the case of problematic results of qualitative analysis, necessarily inspire the question of whether it should be continued in quantitative form. The question arises in particular when new technical equipment and processes are used. Quantitative safety analysis starts with knowledge of the logic structure of the system to be examined, as has already been ascertained in the course of qualitative analysis. A condition for execution is the presence of sufficient data—information about the behavior of the individual system components and parts. The information must be arranged in such a way that reliability characteristics (failure probabilities, failure rates) and maintenance characteristics (rates of repairs) can be derived. It is only when it is certain that sufficient data are available that quantitative analysis is possible. 

Qualitative FTA consists of determining the minimal cut sets and common cause failures. The qualitative analysis reduces the FT to a logically equivalent form, by using the Boolean algebra, in terms of the speciflc combination of basic events sufficient for the undesired top event to occur (Henley and Kumamoto (1992)). In this case each combination would be a critical set for the undesired event. The relevance of these sets must be carefully weighted and major emphasis placed on those of greatest significance. 

Notwithstanding the formal classification given in Fig. 1.5 there is no fundamental difference between qualitative and quantitative analysis. In each case a specific signal is generated which may be evaluated to meet any component of the following logical sequence ... 

Logic Model Methods The following tools are most commonly used in quantitative risk analysis, but can also be useful qualitatively to understand the combinations of events which can cause an accident. The logic models can also be useful in understanding how protective systems impact various potential accident scenarios. These methods will be thoroughly discussed in the Risk Analysis subsection. Also, hazard identification and evaluation tools discussed in this section are valuable precursors to a quantitative risk analysis (QRA). Generally a QRA quantifies the risk of hazard scenarios which have been identified by using tools such as those discussed above. 

In examining numerical approximations it is as well to bear in mind the general qualitative conclusion of our brief examination of symmetry constraints. In broad terms the result was the simpler the model the more severe the effect of any constraint on the variation principle. This result cannot be carried over directly and used in numerical work since numerical approximation schemes can rarely be brought into a sufficiently coherent logical and mathematical form for analysis. Nevertheless it seems likely that this result can be used as a guideline — a rule of thumb . We therefore expect that the imposition of formal constraints and consistency requirements (derived from a higher level of approximation or the exact solution) on numerical approximation schemes is likely to have far-reaching consequences — particularly on the... 

---