Utilizing neural networks and finite element method to predict key fracture mechanic parameters under mixed-mode loading - NCN MINIATURA 8, Decision No. DEC-2024/08/X/ST8/00863

The dataset contains data collected during a project financed by National Centre Science (Poland) - Utilising neural networks and finite element method to predict key fracture mechanics parameters under mixed-mode loading (Miniatura 8, Decision No. DEC-2024/08/X/ST8/00863) The app and model files that are part of this dataset can also be obtained from https://github.com/oxygenum44/CTS_crack_path_generator The following files are part of the dataset: Python files *.py - main file is "app" - it enables the user to open the GUI app that enables crack path generation or determining fracture parameters in CTS specimen Machine learning models with the extension *.pkl (pickle objects) that can be loaded using a Python script and reused - they are also utilised by the GUI app Image files *.jpg - used by the app Datasets in the form of txt/csv files for fracture mechanics parameters (dataset 1) and strains (dataset 2) in CTS specimens containing information for diffrent location of the crack