Using Artificial Intelligence to Predict and Validate Nuclear Data

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Nuclear data, such as cross sections and reaction products, underpins all of nuclear science and technology. Even the most complex and concisely written nuclear data analysis tools can be unreliable and untrustworthy if they use old or un-benchmarked nuclear data. Common problems encountered in nuclear data are missing and conflicting data and large and untrustworthy uncertainties. The best way to tackle these problems is via targeted experiments. However, nuclear data experiments are complex, expensive and the lifecycle time to plan, perform and analyse the results is relatively long. Hence, the current approach involves the use of statistics and theory in conjunction with experiments. To date, the use of artificial intelligence (AI) and machine learning (ML) in the field of nuclear data evaluation has not been fully explored. Hence, this project aims to explore whether or not it would be advantageous to use AI/ML in conjunction with other nuclear data evaluation methods to assist and enhance the evaluation process