Surrogate Machine Learning for Parmec Advanced Gas-cooled Reactor (AGR) Analysis

Data associated with research towards a surrogate machine learning model for the Advanced Gas-cooled Reactor (AGR). This data was generated using the Parmec software package [1] and can be used to train machine learning models using the Surrogate Machine Optimisation and Learning (SMOL) framework [2]. Visit the aforementioned repository, clone the code, then download the files into repository folder. If you are not planning on working with data augmentation, exclude the files with flip and rotate in the title, e.g. dataset__flip_13_rotate_123_cases.pkl. 1. Koziara, T., 2019. Parmec documentation. URL: https://parmes.org/parmec/index.html [Online; accessed 05-August-2022]. 2. Github Repository. URL: https://gitlab.cs.man.ac.uk/q59494hj/parmec_agr_ml_surrogate [Online; accessed 05-August-2022].

Related Organizations

University of Manchester
United Kingdom

Keywords

nuclear, machine learning, surrogate model, data augmentation

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