Highlights from the new issue of InterPore Journal
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https://doi.org/10.69631/ipj.v2i3nr99Keywords:
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1. Elmorsy, M., El-Dakhakhni, W., & Zhao, B. (2025). Enhancing Effective Thermal Conductivity Predictions in Digital Porous Media Using Transfer Learning. InterPore Journal, 2(3), IPJ250825-7. https://doi.org/10.69631/ipj.v2i3nr75
2. Han, Z., Tariq, Z., & Yan, B. (n.d.). A novel robust optimization framework based on surrogate modeling for underground hydrogen storage in depleted natural gas reservoirs. InterPore Journal, 2(3), IPJ250825-6. https://doi.org/10.69631/ipj.v2i3nr69
3. I'Anson, J., Simmons, M., Stitt, H., & Gallen, R. (2025). Using Graph Neural Networks to Predict the Permeability of Porous Media. InterPore Journal, 2(3), IPJ250825-2. https://doi.org/10.69631/ipj.v2i3nr47
4. Lander, R., Matteo, E., Bonnell, L., Dewers , T., Mills, M., Guilkey, J., Mitchell , C., & Stormont, J. (2025). Rubble Characteristics Associated with Room Collapse at the Waste Isolation Pilot Plant: Impact of Salt Clast Shapes and Size Distributions on the Depositional Pore System. InterPore Journal, 2(3), IPJ250825-3. https://doi.org/10.69631/ipj.v2i3nr45
5. Lin, J., Yan, X., Zhang, K., Zhang, Z., & Yao, J. (2025). Anchored Physics-Informed Neural Network for Two-Phase Flow Simulation in Heterogeneous Porous Media. InterPore Journal, 2(3), IPJ250825-5. https://doi.org/10.69631/ipj.v2i3nr67
6. Roustazadeh, A., Male, F., Ghanbarian, B., Shadmand, M. B., Taslimitehrani, V., & Lake, L. W. (2025). Machine Learning-Based Estimation of Oil Recovery Factor Using XGBoost: Insights from Classification and Data-Driven Analyses. InterPore Journal, 2(3), IPJ250825-4. https://doi.org/10.69631/ipj.v2i3nr53
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