Qinjun Kang

According to our database, Qinjun Kang authored at least 14 papers between 2010 and 2025.

Collaborative distances:

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

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

2024

Pore-Scale Modeling of Carbon Dioxide and Hydrogen Transport during Geologic Gas Storage.

Prakash Purswani, Eric Guiltinan, Yu Chen, Qinjun Kang, Mohammed Mehana, Chelsea Neil, Timothy C. Germann, Michael Gross

Dataset, March, 2024

Learning a general model of single phase flow in complex 3D porous media.

Javier E. Santos, Agnese Marcato, Qinjun Kang, Mohamed Mehana, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers

Mach. Learn. Sci. Technol., 2024

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

2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media.

Kun Wang, Yu Chen, Mohammed Mehana, Nicholas Lubbers, Kane C. Bennett, Qinjun Kang, Hari S. Viswanathan, Timothy C. Germann

J. Comput. Phys., 2021

Multi-Scale Neural Networks for to Fluid Flow in 3D Porous Media.

Javier E. Santos, Ying Yin, Honggeun Jo, Wen Pan, Qinjun Kang, Hari S. Viswanathan, Masa Prodanovic, Michael J. Pyrcz, Nicholas Lubbers

CoRR, 2021

2020

Modeling nanoconfinement effects using active learning.

Javier E. Santos, Mohammed Mehana, Hao Wu, Masa Prodanovic, Michael J. Pyrcz, Qinjun Kang, Nicholas Lubbers, Hari S. Viswanathan

CoRR, 2020

Physics-Informed Machine Learning for Real-time Reservoir Management.

Maruti Kumar Mudunuru, Daniel O'Malley, Shriram Srinivasan, Jeffrey D. Hyman, Matthew R. Sweeney, Luke Frash, Bill Carey, Michael R. Gross, Nathan J. Welch, Satish Karra, Velimir V. Vesselinov, Qinjun Kang, Hongwu Xu, Rajesh J. Pawar, Tim Carr, Liwei Li, George D. Guthrie, Hari S. Viswanathan

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020

2016

Three-dimensional lattice Boltzmann simulations of microdroplets including contact angle hysteresis on topologically structured surfaces.

Yan Ba, Qinjun Kang, Haihu Liu, Jinju Sun, Chao Wang

J. Comput. Sci., 2016

Contact Angle Effects on Pore and Corner Arc Menisci in Polygonal Capillary Tubes Studied with the Pseudopotential Multiphase Lattice Boltzmann Model.

Soyoun Son, Li Chen, Qinjun Kang, Dominique Derome, Jan Carmeliet

Comput., 2016

2014

Lattice Boltzmann phase-field modeling of thermocapillary flows in a confined microchannel.

Haihu Liu, Albert J. Valocchi, Yonghao Zhang, Qinjun Kang

J. Comput. Phys., 2014

2013

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes.

Li Chen, Ya-Ling He, Qinjun Kang, Wen-Quan Tao

J. Comput. Phys., 2013

2010

Modeling electrokinetic flows in microchannels using coupled lattice Boltzmann methods.

Moran Wang, Qinjun Kang

J. Comput. Phys., 2010

Viscous flow and colloid transport near air-water interface in a microchannel.

Xiao-yan Shi, Hui Gao, Volha I. Lazouskaya, Qinjun Kang, Yan Jin, Lian-Ping Wang

Comput. Math. Appl., 2010