Framework for a Bayesian network version of IDHEAS

Bayesian Networks (BNs) have been identified as a powerful tool for Human Reliability Analysis (HRA), with multiple advantages over traditional HRA methods. We present a framework for developing a BN version of the IDHEAS (Integrated Decision-Tree Human Event Analysis System) HRA method, which is currently under development at the US NRC. The framework includes an extension of the IDHEAS graphical model to include additional causal paths and the use of BN node reduction algorithms to facilitate quantification of the model. The proposed framework provides the foundation to resolve several needs frequently expressed by the HRA community. Firstly, the developed extended BN structure illustrates the causal paths found in cognitive psychology literature, thereby addressing the need for causal traceability and strong scientific basis. Secondly, by using node reduction algorithms, the BN can be reduced to a level of detail at which quantification is as straightforward as in the original IDHEAS approach.