Aleksandra Pachalieva

According to our database, Aleksandra Pachalieva authored at least 14 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2026

Physics-informed reservoir characterization from bulk and extreme pressure events with a differentiable simulator.

Harun Ur Rashid, Mingxin Li, Aleksandra Pachalieva, Georg Stadler, Daniel O'Malley

CoRR, April, 2026

Out-of-distribution transfer of PDE foundation models to material dynamics under extreme loading.

Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh, Aleksandra Pachalieva, Bradley C. Love, Daniel O'Malley, Alexander Scheinker, Kyle Hickmann, Diane Oyen, Nathan DeBardeleben, Earl Lawrence, Ayan Biswas

CoRR, March, 2026

2025

Differentiable multiphase flow model for physics-informed machine learning in reservoir pressure management.

Harun Ur Rashid, Aleksandra Pachalieva, Daniel O'Malley

CoRR, August, 2025

A Foundation Model for Material Fracture Prediction.

Agnese Marcato, Aleksandra Pachalieva, Ryley G. Hill, Kai Gao, Xiaoyu Wang, Esteban Rougier, Zhou Lei, Vinamra Agrawal, Janel Chua, Qinjun Kang, Jeffrey D. Hyman, Abigail Hunter, Nathan DeBardeleben, Earl Lawrence, Hari S. Viswanathan, Daniel O'Malley, Javier E. Santos

CoRR, July, 2025

Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials.

Sakib Matin, Emily Shinkle, Yulia Pimonova, Galen T. Craven, Aleksandra Pachalieva, Ying Wai Li, Kipton Barros, Nicholas Lubbers

CoRR, March, 2025

2024

Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction.

Paul Schwerdtner, Prakash Mohan, Aleksandra Pachalieva, Julie Bessac, Daniel O'Malley, Benjamin Peherstorfer

CoRR, 2024

Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks.

Emily Shinkle, Aleksandra Pachalieva, Riti Bahl, Sakib Matin, Brendan Gifford, Galen T. Craven, Nicholas Lubbers

CoRR, 2024

2023

DPFEHM: a differentiable subsurface physics simulator.

Daniel O'Malley, Sarah Y. Greer, Aleksandra Pachalieva, Wu Hao, Dylan Robert Harp, Velimir V. Vesselinov

J. Open Source Softw., October, 2023

Learning the Factors Controlling Mineralization for Geologic Carbon Sequestration.

Aleksandra Pachalieva, Jeffrey D. Hyman, Daniel O'Malley, Hari S. Viswanathan, Gowri Srinivasan

CoRR, 2023

Computationally Efficient and Error Aware Surrogate Construction for Numerical Solutions of Subsurface Flow Through Porous Media.

Aleksei G. Sorokin, Aleksandra Pachalieva, Daniel O'Malley, James Mac Hyman, Fred J. Hickernell, Nicolas W. Hengartner

CoRR, 2023

Impact of artificial topological changes on flow and transport through fractured media due to mesh resolution.

Aleksandra A. Pachalieva, Matthew R. Sweeney, Hari S. Viswanathan, Emily Stein, Rosie Leone, Jeffrey D. Hyman

CoRR, 2023

2022

GLUE Code: A framework handling communication and interfaces between scales.

Aleksandra Pachalieva, Robert S. Pavel, Javier E. Santos, Abdourahmane Diaw, Nicholas Lubbers, Mohammed Mehana, Jeffrey R. Haack, Hari S. Viswanathan, Daniel Livescu, Timothy C. Germann, Christoph Junghans

J. Open Source Softw., December, 2022

Predictive Scale-Bridging Simulations through Active Learning.

Satish Karra, Mohammed Mehana, Nicholas Lubbers, Yu Chen, Abdourahmane Diaw, Javier E. Santos, Aleksandra Pachalieva, Robert S. Pavel, Jeffrey R. Haack, Michael M. McKerns, Christoph Junghans, Qinjun Kang, Daniel Livescu, Timothy C. Germann, Hari S. Viswanathan

CoRR, 2022

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management.

Aleksandra Pachalieva, Daniel O'Malley, Dylan Robert Harp, Hari S. Viswanathan

CoRR, 2022