id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fis-5669	Farooq, Sheikh Aamir; Alajaleen, Danah; Albinmousa, Jafar	Machine learning-assisted fracture prediction: Integrating synthetic and experimental data for quasi-static notch failure analysis	2025	11	.pdf	application/pdf	5769	340	44	The consistency between simulation results and experimental data also indicates that fracture load data generated from PYMAPDL can be used as a reliable input for data- driven modeling approaches. Performance of ML models for fracture load prediction The XGBoost models were trained to evaluate the effect of the synthetic data on the model accuracy and robustness in predicting the fracture loads of U-notched polycarbonate specimens.	cache/fis-5669.pdf	txt/fis-5669.txt