Conference Tools for 2024 TMS Annual Meeting & Exhibition

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About this Abstract
Meeting	2024 TMS Annual Meeting & Exhibition
Symposium	Materials Informatics to Accelerate Nuclear Materials Investigation
Presentation Title	Inverse Uncertainty Quantification of Dispersion Analysis Research Tool (DART) Parameters Necessary for the Calculation of Fission Gas Swelling in U-Mo Fuel
Author(s)	ATM Jahid Hasan, Zhi-Gang Mei, Bei Ye, Benjamin Beeler
On-Site Speaker (Planned)	ATM Jahid Hasan
Abstract Scope	Accurate prediction and understanding of fission gas swelling (FGS) are essential for fuel qualification of U-Mo monolithic fuel. The Dispersion Analysis Research Tool (DART), a rate-theory-based code developed at Argonne National Laboratory, provides a way to calculate FGS in U-Mo. However, DART utilizes assumed values for some lower-length-scale fuel parameters of U-Mo that are still unknown. Estimation of these parameter distributions is crucial for FGS prediction. This study performs inverse uncertainty quantification to obtain posterior probability distributions (PPDs) of DART parameters. Initially, surrogate models based on neural networks, gaussian processes, and other machine learning methods are built using the available data from DART. Bayesian inference methods, such as Markov Chain Monte Carlo, are then applied to find the parameter PPDs. Finally, the surrogate models are used to compute the push-forward of the parameter PPDs. This work concomitantly establishes a way to perform sensitivity analysis and optimization of DART parameters.
Proceedings Inclusion?	Planned:
Keywords	Nuclear Materials, Computational Materials Science & Engineering, Modeling and Simulation

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