Computational Modeling and Machine Learning (ML) Models in Rock Mechanics and Geotechnical Engineering
This repository contains all the data and codes needed to reproduce the results presented in our published project papers as follows:
Project 1a = "Kolawole, O., & Assaad, R. H. (2023). Modeling and prediction of temporal biogeomechanical properties using novel machine learning approach. Rock Mechanics and Rock Engineering, 56(8), 5635–5655. https://doi.org/10.1007/s00603-023-03353-9".
Project 1b = "Kolawole, O., Assaad, R. H., Ngoma, M. C., & Ozotta, O. (2023). An Artificial Neural Network Model for Predicting Microbial-Induced Alteration of Rock Strength. In E. Rathje, B.M. Montoya, & M.H. Wayne (Eds.), Geotechnical Special Publication 340, Geo-Congress 2023: Geotechnical Characterization, pp. 243-251. https://doi.org/10.1061/9780784484678.025".
Project 2 = "Kolawole, O., Assaad, R. H., Adams, M. P., Ngoma, M. C., Anya, A., & Assaf, G. (2023). Coupled experimental assessment and machine learning prediction of mechanical integrity of MICP and cement paste as underground plugging materials. Biogeotechnics, 1(2), 100020. https://doi.org/10.1016/j.bgtech.2023.100020".
Dr. Oladoyin Kolawole
Email: oladoyin.kolawole@njit.edu