Softwares and Datasets

Softwares

Symbolica
K. Pietrzyk and I. Battiato. (2023). Symbolica (v1.0.0-alpha). Zenodo doi

Description
Code that uses symbolic computation to automate multiscale model development via upscaling (asymptotic homogenization).

Related Publications
Pietrzyk, K., Battiato, I., 'Automated Symbolic Upscaling: Model Generation for Extended Applicability Regimes, Part 1',  Water Resour. Res, (2023). doi

Pietrzyk, K., Battiato, I., 'Automated Symbolic Upscaling: Model Generation for Extended Applicability Regimes, Part 2', Accepted,  Water Resour. Res. (2023). 

K. Pietrzyk, S. Korneev, M. Behandish, and I. Battiato. Upscaling and automation: pushing the boundaries of multiscale modeling through symbolic computing. Transp. Porous Media, 140:313-349, 2021.

Data

Dataset 1:
R. Weber, S. Korneev, I. Battiato, "Labeled image dataset of generated porous electrode microstructures and calculated transport parameters for neural network training", Mendeley Data, (2022). doi

Description: 
Computer generated dataset of 100k images depicting representing porous media. The particles are randomly shaped and span a wide range of porosity, effective surface area, and connectivity. For each image, the effective diffusion and conductivity tensors calculated from a PDE closure problem are given.

Related Publication:
R. Weber, S. Korneev, I. Battiato, ‘Estimation of Li-Ion Battery Effective Properties through Convolutional Neural Networks’,  Transport Porous Med. 145, 527–548 (2022). doi