Faculty Directory
Wing K. Liu

Walter P. Murphy Professor of Mechanical Engineering & Civil and Environmental Engineering and (by courtesy) Materials Science and Engineering

Contact

2145 Sheridan Road
Tech A326
Evanston, IL 60208-3109

847-491-7094Email Wing Liu

Departments

Mechanical Engineering

Affiliations

Theoretical and Applied Mechanics Graduate Program


Download CV

Education

Ph.D. California Institute of Technology, Pasadena, CA

M.S. California Institute of Technology, Pasadena, CA

B.S. Engineering Science (Hons)
University of Illinois at Chicago, Chicago, IL


Research Interests

Mathematical scientific principles provide the fundamental understanding and allow predictions which drive new discoveries and enable future technologies. Unfortunately, development of new scientific principles is often trailing the pace of new inventions with the sheer volume of data that are being generated across multiple spatial, temporal, and parameter scales. In this context, mechanistic data science [Mechanistic Data Science for STEM Education and Applications", Liu, Gan, Fleming, to appear, Springer, December, 2021] provides the critically needed ability to combine known scientific principles with newly collected data, which will be a boon for new inventions.  

HiDeNN-AI (Liu, Wing Kam et al., “HiDeNN: An AI Platform for Scientific and Materials Systems Innovation,” Disc-ID-21-04-06-001, April, 6, 2021) is built on ten integrated modules to form a mechanistic artificial intelligence software framework with new methods and algorithms for extremely fast design, optimization, decision making, and discovery and extraction of mechanistic features simply from signals and images deployable for scientific and engineering processes. The proposed HiDeNN-AI software platform development can also be useful for advanced and additive manufacturing process design including signal analysis, data generation, for the discovery of key processing parameters for close-loop control. Using mechanistic active knowledge transfer module of HiDeNN-AI, we might be able to remove the manufacturing machines dependency and the usage of new material powders with only a limited set of experimental calibration of the new/alternative manufacturing system, and/or material powders.


Significant Recognition

  • International Association for Computational Mechanics: Gauss-Newton Medal, the highest award given by the Society (2012)
  • American Society of Mechanical Engineers (ASME): Robert Henry Thurston Lecture Award, 2007
  • U. S. Association for Computational Mechanics: John von Neumann Medal, the highest award given by USACM, 2007
  • Japan Society of Mechanical Engineers: Computational Mechanics Award, 2004
  • Cited by Institute for Scientific Information (ISI) as one of the most highly cited, influential researchers in Engineering, and an original member, highly cited researchers database (2001)
  • ASME Gustus L. Larson Memorial Award (1995)
  • Thomas J. Jaeger Prize, Int. Association for Structural Mechanics in Reactor Technology (1989)
  • ASME Pi Tau Sigma Gold Medal (1985)
  • Ralph R. Teetor Educational Award, American Society of Automotive Engineers (1983)
  • ASME Melville Medal (1979)

Significant Professional Service

  • Editor, Computational Mechanics
  • Honorary editor-in-chief of the International Journal of Computational Methods
  • Honorary editor-in-chief of the International Journal of Computational Methods
  • 2010- Present Vice President of the International Association for Computational Mechanics (Elected)
  • 2007- Founding Chair of the ASME Wide Nanotechnology Council
  • 2005 Chair, executive committee of Applied Mechanics Division of ASME (Member 2001-2006)
  • 2005 Chair, executive committee of Applied Mechanics Division of ASME (Member 2001-2006)
  • Past President of U. S. Association for Computational Mechanics
  • 2005 Chair, executive committee of Applied Mechanics Division of ASME
  • 2009- present, Visiting Distinguished World Class University Professor of Sung Kyun Kwan University, Korea

Selected Publications

  • Saha, Sourav; Kafka, Orion L.; Lu, Ye; Yu, Cheng; Liu, Wing Kam, Microscale Structure to Property Prediction for Additively Manufactured IN625 through Advanced Material Model Parameter Identification, Integrating Materials and Manufacturing Innovation 10(2):142-156.
  • Yu, Cheng; Kafka, Orion L.; Liu, Wing Kam, Multiresolution clustering analysis for efficient modeling of hierarchical material systems, Computational Mechanics 67(5):1293-1306.
  • Mojumder, Satyajit; Gao, Jiaying; Liu, Wing Kam, Self-consistent clustering analysis for modeling of theromelastic heterogeneous materials, American Institute of Physics Inc..
  • Kafka, Orion L.; Jones, Kevontrez K.; Yu, Cheng; Cheng, Puikei; Liu, Wing Kam, Image-based multiscale modeling with spatially varying microstructures from experiments, Journal of the Mechanics and Physics of Solids 150.
  • Tajdari, Mahsa; Pawar, Aishwarya; Li, Hengyang; Tajdari, Farzam; Maqsood, Ayesha; Cleary, Emmett; Saha, Sourav; Zhang, Yongjie Jessica; Sarwark, John F.; Liu, Wing Kam, Image-based modelling for Adolescent Idiopathic Scoliosis, Computer Methods in Applied Mechanics and Engineering 374.
  • Liang, Zhi; Zhirnov, Ivan; Zhang, Fan; Jones, Kevontrez K.; Deisenroth, David; Williams, Maureen; Kattner, Ursula; Moon, Kil won; Liu, Wing Kam; Lane, Brandon; Campbell, Carelyn, Development of computational framework for titanium alloy phase transformation prediction in laser powder-bed fusion additive manufacturing, Materialia 14.
  • Zhang, Lei; Cheng, Lin; Li, Hengyang; Gao, Jiaying; Yu, Cheng; Domel, Reno; Yang, Yang; Tang, Shaoqiang; Liu, Wing Kam, Hierarchical deep-learning neural networks, Computational Mechanics 67(1):207-230.
  • Gan, Zhengtao; Jones, Kevontrez K.; Lu, Ye; Liu, Wing Kam, Benchmark Study of Melted Track Geometries in Laser Powder Bed Fusion of Inconel 625, Integrating Materials and Manufacturing Innovation 10(2):177-195.
  • Saha, Sourav; Gan, Zhengtao; Cheng, Lin; Gao, Jiaying; Kafka, Orion L.; Xie, Xiaoyu; Li, Hengyang; Tajdari, Mahsa; Kim, H. Alicia; Liu, Wing Kam, Hierarchical Deep Learning Neural Network (HiDeNN), Computer Methods in Applied Mechanics and Engineering 373.
  • Lu, Ye; Jones, Kevontrez Kyvon; Gan, Zhengtao; Liu, Wing Kam, Adaptive hyper reduction for additive manufacturing thermal fluid analysis, Computer Methods in Applied Mechanics and Engineering 372.
  • Tang, Shan; Yang, Hang; Qiu, Hai; Fleming, Mark; Liu, Wing Kam; Guo, Xu, MAP123-EPF, Computer Methods in Applied Mechanics and Engineering 373.
  • Yan, Wentao; Lu, Yan; Jones, Kevontrez; Yang, Zhuo; Fox, Jason; Witherell, Paul; Wagner, Gregory; Liu, Wing Kam, Data-driven characterization of thermal models for powder-bed-fusion additive manufacturing, Additive Manufacturing 36.
  • He, Chunwang; Ge, Jingran; Zhang, Binbin; Gao, Jiaying; Zhong, Suyang; Liu, Wing Kam; Fang, Daining, A hierarchical multiscale model for the elastic-plastic damage behavior of 3D braided composites at high temperature, Composites Science and Technology 196.
  • Tang, Shan; Li, Ying; Qiu, Hai; Yang, Hang; Saha, Sourav; Mojumder, Satyajit; Liu, Wing Kam; Guo, Xu, MAP123-EP, Computer Methods in Applied Mechanics and Engineering 364.
  • Gao, Jiaying; Shakoor, Modesar; Domel, Gino; Merzkirch, Matthias; Zhou, Guowei; Zeng, Danielle; Su, Xuming; Liu, Wing Kam, Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers, Composites Science and Technology 186.
  • Li, Hengyang; Kafka, Orion L.; Gao, Jiaying; Yu, Cheng; Nie, Yinghao; Zhang, Lei; Tajdari, Mahsa; Tang, Shan; Guo, Xu; Li, Gang; Tang, Shaoqiang; Cheng, Gengdong; Liu, Wing Kam, Clustering discretization methods for generation of material performance databases in machine learning and design optimization, Computational Mechanics 64(2):281-305.
  • Yu, Cheng; Kafka, Orion L.; Liu, Wing Kam, Self-consistent clustering analysis for multiscale modeling at finite strains, Computer Methods in Applied Mechanics and Engineering 349:339-359.
  • Yan, Wentao; Lian, Yanping; Yu, Cheng; Kafka, Orion L.; Liu, Zeliang; Liu, Wing Kam; Wagner, Gregory J., An integrated process–structure–property modeling framework for additive manufacturing, Computer Methods in Applied Mechanics and Engineering 339:184-204.
  • Wolff, Sarah J.; Gan, Zhengtao; Lin, Stephen; Bennett, Jennifer L.; Yan, Wentao; Hyatt, Gregory; Ehmann, Kornel F.; Wagner, Gregory J.; Liu, Wing Kam; Cao, Jian, Experimentally validated predictions of thermal history and microhardness in laser-deposited Inconel 718 on carbon steel, Additive Manufacturing 27:540-551.

In the Classroom

Finite Element Methods in Mechanics

To learn the basic theory behind the finite element method (FEM); how to program the finite element method using MATLAB as a programming tool; to learn a general commercial FEM code to write interface programs and solve typical engineering problems.

Finite Elements for Design and Optimization

The scope of the course is to provide the analytical and computational tools necessary for the design of complex structural and material systems for modern engineering applications, ranging from structural engineering to micro and nanotechnology.

Advanced Finite Element Methods I

Gain theoretical, programming, and application knowledge of nonlinear finite element methods. Understand the associated continuum mechanics and its finite element implementation and applications.

Advanced Finite Element Methods II

Arbitrary Lagrangian Eulerian (ALE) formulations, Non-linear materials, and introduction to computational fracture mechanics; using ABAQUS, programming VUMAT, UMAT.

Multi-scale Modeling and Simulation in Solid Mechanics

Understand the underlying principles of molecular dynamics. Gain proficiency in designing molecular dynamics simulations using available software (LAMMPS). Understand the connection between information available on small (atomistic) and large (continuum) scales. Applications: Nanostructure materials: Nanowires: single crystal Si.  Nano Carbons: nanotube; Polymer nano-composite: polymer mechanics, polymer and polymer-fillers modeling; Multi-scale modeling.