Quantification of MCS with BDD, Accuracy and Inclusion of Success in the Calculation – the RiskSpectrum MCS BDD Algorithm

A quantification of a PSA can be performed through different techniques, of which the Minimal Cut Set (MCS) generation technique and Binary Decision Diagrams (BDD) are the most well known. There is only one advantage with the MCS approach compared to the BDD approach calculation time, or rather, the capability to always solve the problem. In most cases the MCS approach is fully sufficient. But as the number of high probability events increases, e.g. due to seismic risk assessments, more accurate methods may be necessary. In some applications, a relevant numerical treatment of success in event trees may also be required to avoid overly conservative results. We discuss the quantification algorithm in RiskSpectrum MCS BDD, especially with regard to success in event trees. A BDD for both the failure and success parts of a sequence can be generated separately and thereafter, the BDD structures can be combined. Under some conditions, this calculation will yield exactly the same result as if a complete BDD for both the failure and success parts was generated. Properties of the algorithm are also demonstrated on several examples including a large size PSA.