Grants per year
Personal profile
Research Interests
I am interested in the development and application of computational simulations methods for multi-scale and multi-physics problems in engineering, especially in the areas of fluid dynamics, heat transfer, and material transport. Many of the most fascinating engineering systems are characterized by two or more physical phenomena coupled together in a single domain or across an interface. My research is focused on the development of models for these of these types of problems, and their solution using high performance computing tools. Examples include melting and solidification of metal in advanced manufacturing processes, fluid-structure interaction in the human heart and vascular system, heat transfer in multi-phase flows, and multi-scale transport in environmental systems.
Education/Academic qualification
Mechanical Engineering, PhD, Northwestern University
… → 2001
Mechanical Engineering, MS, Northwestern University
… → 1999
Mechanical Engineering, BS, Boston University
… → 1996
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Collaborations and top research areas from the last five years
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Machine learning enhanced models: enabling new materials for hypersonic and protection applications
Purdue University, U.S. Army Research Laboratory
7/6/22 → 7/5/27
Project: Research project
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Process modeling software for additive manufacturing of metals
Wagner, G. J., Ehmann, K., Fleming, M. A. & Liu, W. K.
Beijing Institute of Collaborative Innovation
9/1/18 → 5/31/20
Project: Research project
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Convolution hierarchical deep-learning neural network (C-HiDeNN) with graphics processing unit (GPU) acceleration
Park, C., Lu, Y., Saha, S., Xue, T., Guo, J., Mojumder, S., Apley, D. W., Wagner, G. J. & Liu, W. K., Aug 2023, In: Computational Mechanics. 72, 2, p. 383-409 27 p.Research output: Contribution to journal › Article › peer-review
4 Scopus citations -
Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN): finite elements, isogeometric analysis, tensor decomposition, and beyond
Lu, Y., Li, H., Zhang, L., Park, C., Mojumder, S., Knapik, S., Sang, Z., Tang, S., Apley, D. W., Wagner, G. J. & Liu, W. K., Aug 2023, In: Computational Mechanics. 72, 2, p. 333-362 30 p.Research output: Contribution to journal › Article › peer-review
3 Scopus citations -
Impact of assuming a circular orifice on flow error through elliptical regurgitant orifices: computational fluid dynamics and in vitro analysis of proximal flow convergence
Lee, J., Mitter, S. S., Van Assche, L., Huh, H., Wagner, G. J., Wu, E., Barker, A. J., Markl, M. & Thomas, J. D., Feb 2023, In: International Journal of Cardiovascular Imaging. 39, 2, p. 307-318 12 p.Research output: Contribution to journal › Article › peer-review
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Multiphysics modeling of mixing and material transport in additive manufacturing with multicomponent powder beds
Samaei, A., Sang, Z., Glerum, J. A., Mogonye, J. E. & Wagner, G. J., Apr 5 2023, In: Additive Manufacturing. 67, 103481.Research output: Contribution to journal › Article › peer-review
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A physics-informed machine learning method for predicting grain structure characteristics in directed energy deposition
Kats, D., Wang, Z., Gan, Z., Liu, W. K., Wagner, G. J. & Lian, Y., Feb 1 2022, In: Computational Materials Science. 202, 110958.Research output: Contribution to journal › Article › peer-review
23 Scopus citations