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Lattice-physics (PWR fuel assembly neutronics simulation results)

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This dataset encompasses lattice-physics parameters—the infinite multiplication factor (k-inf) and the pin power peaking factor (PPPF)—modeled as functions of variations in fuel pin enrichments for the NuScale US600 fuel assembly type C-01 (NFAC-01) [NuScale FSAR]. These critical parameters were computed using the MCNP6 code, a Monte Carlo-based tool for nuclear reactor criticality simulations. Fuel pin enrichments were uniformly sampled within the range of 0.7–5.0 weight percent (w/o) U-235 to generate the dataset. The dataset contains 39 features, each representing the enrichment of a specific fuel rod in a one-eighth symmetry of the NFAC assembly. The outputs of interest are the k-inf and PPPF values associated with these enrichments.
Subject Area
Physics and Chemistry
Instances
24,000
Features
39
Data Types
Tabular, Multivariate
Tasks
Regression
Feature Types
Continuous

Features

Introductory Paper

A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters
Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu.. 2024.
Institute for Nuclear Science and Technology (INST), Vietnam Atomic Energy Institute (VINATOM), 179 Hoang Quoc Viet, Cau Giay, Hanoi 100000, Vietnam

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Keywords
Authors
Nguyen Huu Tiep
Year Created
2024
License
CC BY 4.0