[1] J.B. Freund, J. Kim, R.H. Ewoldt (2018). Field sensitivity of flow predictions to rheological parameters, Journal of Non-Newtonian Fluid Mechanics, Vol 256, (pp. 71-82) available at: doi.

[2] J. Kim, P.K. Singh, J.B Freund, R.H. Ewoldt (2019). Uncertainty Propagation in Simulation Predictions of Generalized Newtonian Fluid Flows, Journal of Non-Newtonian Fluid Mechanics, available at: doi.

[3] J. Kim, J. D. Park (2020). The non-homogenous flow of a thixotropic fluid around a sphere, Applied Mathematical Modeling, available at: doi.

[4] J. Kim, M. Jacobs, S. Osher, N. C. Admal (2021). A crystal symmetry-invariant Kobayash-Warren-Cater grain boundary model and its implementation using a thresholding algorithm, Computational Materials Science, availalble at: doi.

[5] J. Kim, J. D. Park (2021). A thixotropic fluid flow around two sequentially aligned spheres, Korean Journal of Chemical Engineering, availalble at: doi.

[6] J. Kim, N. C. Admal (2023). A stochastic framework for evolving grain statistics using a neural network model for grain topology transformations, Computational Materials Science, available at: doi.

[7] J. Kim (2023). Adjoint-based sensitivity analysis of viscoelastic fluids at a low deborah number, Applied Mathematical Modeling, available at: doi.

[8] J. Kim, N.C Admal (2024). Statistics of grain microstructure evolution under anisotropic grain boundary energies and mobilities using threshold-dynamics, Modeling and Simulation in Materials Science and Engineering, available at: doi.

[9] H.-J. Park, J. Kim, H. Kim (2024). Segment-Based Wall Treatment Model for Heat Transfer Rate in Smoothed Particle Hydrodynamics, Physics of Fluid, available at: link.

[10] J. Kim, H-J. Park, A. Penumarti, J. Shin (2024). Fast Marching based Rendezvous Path Planning for a Team of Heterogeneous Vehicles IEEE ACCESS, available at: link.

[11] J. Kim, H. Kim, H-J. Park (2025). Comparative Analysis of Granular Material Flow: Discrete Element Method and Smoothed Particle Hydrodynamics Approaches Physics of Fluid, available at: link.

[1] In-situ and Non-contact Etch Depth Prediction in Plasma Etching via Machine Learning (ANN & BNN) and Digital Image Colorimetry, M. Kang, S. Kim, E. Go, D. Paek, G. Lim, M. Kim, S. Kim, S. K. Jang, M. S. Choi, W. S. Kang, J. Kim, Jaekwang Kim*, Hyeong-U Kim* (co-corresponding)

[1] S. Choi, D. H. Lee, J. Choi, J. Kim Numerical Modeling of n-Hexane pyrolysis with an Optimized Kinetic Mechanism in a Rotating Gliding Arc Reactor

[1] J. Kim , Models for grain microstructure evolution and grain statistics University of Illinois at Urbana Champaign, available at: IDEALS.