Generalized Intelligent Behavior and Event Recognition Method for Nuclear Engineering Applications

Abstract

In many fields of engineering it is desirable, and often required, to identify certain characteristics of processes, properties, and systems. This effort focuses on the development and demonstration of an intelligent behavior and event recognition method. Using a black-box approach, the method was generalized and applied to several different applications as proof of concept. Quantum mechanics, nuclear supply chain management, and nuclear composition characterization problems were considered. The method utilized data synthesis and genetic algorithms, an artificial intelligence method, to achieve the desired results. This will allow the user to have a single optimization tool which can be applied to a diverse problem set.