Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys
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https://dataverse.lib.virginia.edu/citation?persistentId=doi:10.18130/V3/EXJA3W
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资源简介：
The data in each sheet is described below:
1. Data_train: Training dataset used for all the ML models
2. Data_test: Test dataset used for all the ML models
3. Data_virtual: Dataset having the principal component (PC) values of U-Mo-X alloys absent from train and test set and is the input to predict the TTT curves for these U-Mo-X alloys
4. Data_calibrate_U-10Mo: Calibration set. Predictions on this set are used as an input to the curvature loss term.
5. Train_test_elemental_descriptor: Elemental descriptors describing the input U-Mo-X alloys.
6. Train_test_PC_values: Principal component (PC) values derived from the elemental descriptors for the input U-Mo-X alloys
7. Virtual_elemental_descriptor: Elemental descriptors describing the virtual set which are the U-Mo-X alloys absent from the train and test set.
提供机构：
University of Virginia Dataverse
创建时间：
2026-03-30
