Dynamic failure analysis of process systems using neural networks

Integrating ANN with a probabilistic approach provides an efficient and effective way to estimate process accident probability as a function of time and thus the risk can be easily predicted upon quantifying the damage. The updating mechanism of the approach makes the model adaptive and captures evolving process conditions. The proposed integrated approach is applied to the Tennessee process system as a case study.