CNNs_for_mechanical_property_prediction_of_composites_dataset

Dataset for the ECAI 2025 Paper - Explainable Prediction of the Mechanical Properties of Composites with CNNs Filename and contents: composite_images.zip : collection of 2D black-and-white 500 x 500 pixel images of the composite microstructures (as .tif files) composite_image_coordinates.zip : collection of csv files containing the coordinates for the microstructure images model_generation_and_FE_simulations.py : python code to be inputted into Abaqus FE Software to create FE models (.inp files) and subsequently FE simulation job files (.odb files) to perform FE analysis extract_force_displacement_from_models.py : python code to be inputted into Abaqus FE software to extract force-displacement data from the .odb simulation files extract_E_and_YS_from_force_displacement.py : python code to be run on computer to conver force-displacement data into Youngs Modulus and Yield Strength composite_mechanical_properties.csv : csv file containing the Youngs Modulus and Yield Strength for all models, obtained from FE simulations. This is used for AI models load_images_function.py : python function to help load the .tif image files into desired python notebook for AI models. This is a supplementary file How to reproduce data (Mechanical properties generation): unzip 'composite_images.zip' and 'composite_image_coordinates.zip' into a folder locally open 'model_generation_and_FE_simulations.py' and add the location of the images and coordinates directory (from step 1) into the code. The comments on the very top of this python file point to the necessary lines to be edited to specify the path name Run the modified 'model_generation_and_FE_simulations.py' inside Abaqus FE software open 'extract_force_displacement_from_models.py' and add the location of the '.odb' files into the code. The comments on the very top of this python file point to the necessary lines to be edited to specify the path name Run the modified 'extract_force_displacement_from_models.py' inside Abaqus FE software open 'extract_E_and_YS_from_force_displacement.py' and add the location of the .csv files containing the force-displacement data outputted by Abaqus from step 5. Also add the path name for the .csv file that you want to store the mechanical properties in. The comments on the very top of this python file point to the necessary lines to be edited to specify the path names Run 'extract_E_and_YS_from_force_displacement.py ' as a python script. The final mechanical properties will be outputted. The attached 'composite_mechanical_properties.csv' can be used for sanity check How to reproduce CNNs and XAI results: Split the data from 'composite_mechanical_properties.csv' into a train-test-validation split. For the paper, an 85-10-5 split was used. if needed, use the 'load_images_function.py' to load the images into the file (e.g. jupyter notebook) you want to perform the AI analysis on for the customised CNNs (10 epochs) - follow the architecture shown in the paper to recreate the CNN models on TensorFlow 2.13.0 to predict the Youngs Modulus and Yield Strength