The Multiscale Computational Science and Engineering Laboratory conducts research in areas such as multiscale modeling and simulation, nanocomposites, deep learning, reinforcement learning, robotics and control, and complex systems. 


Research Team

Shaoping Xiao

Shaoping Xiao, PhD

Director, Multiscale Computational Science and Engineering Laboratory
Associate Professor, Department of Mechanical Engineering

Projects and Publications

Machine Learning–Enhanced Multiscale/Multiphysics Modeling of Spatially Tailored Materials with Multiscale Experimental Validation

Sponsor: U.S. National Science Foundation

Project No.: CMMI-2104383

Duration: Aug 15, 2021 – Aug 14, 2024

Principal Investigator: Professor Shaoping Xiao

Co Principal Investigators: Professors Caterina Lamuta and Phillip Deierling

Past and Current Graduate Students: Siamak Attarian, Arunabha Batabyal, Akram Ghaffarigharehbagh, and Mahmudul Alam Shakib

Summary: This project is developing a new computer model to design and study the mechanical behavior of metal-ceramic composites. In most traditional composites, the component distributions are constant to enhance the material properties evenly. In contrast, the metal-ceramics composites studied in this project have component distributions that vary from location to location. Therefore, engineers can design the proper composite structure with various desired material properties at different critical locations. The new computer model includes several computation algorithms at nanoscale, microscale, and macroscale, respectively. In addition, the project provides for validation of the computer model by fabricating the composite samples and testing them on different types of equipment. This project also consists of some outreach activities for undergraduate students and K-12 students.

Related Publications, Presentations, and Other Outcomes:

Attarian, S., Xiao, S. P., “Development of a 2NN-MEAM potential for Ti-B system and studies of the temperature dependence of the nanohardness of TiB2”, Computational Materials Science, 201, 2022, 110875.

El Tuhami, A. and Xiao S. P. “Multiscale Modeling of Metal-Ceramic Spatially Tailored Materials via Gaussian Process Regression and Peridynamics”, International Journal of Computational Methods, 2022, 2250025.

Attarian, S. and Xiao, S. P., “Investigating the strength of Ti/TiB interfaces at multiple scales using density functional theory, molecular dynamics, and cohesive zone modeling”, Ceramic International, 48(22), 2022, 33185-33199.

S. Xiao, “Multiscale modeling of metal-ceramic spatially tailored materials via machine learning,” Engineering Mechanics Institute Conference 2022, Baltimore, Maryland, May 31-June 3, 2022

S.Xiao, S. Attarian, and P. Deierling, “Deeping learning in multiscale modeling of spatially tailored materials,” 15th World Congress on Computational Mechanics, Yokohama, Japan, July 31-Aug 5, 2022

S. Xiao, “Investigating the mechanics of Ti/TiB interfaces at multiple scales: from quantum mechanics to molecular dynamics”, 4th International Conference on Materials Science and Engineering, Houston, TX, April, 2023

Dataset and neural networks:

Modular deep reinforcement learning for continuous motion planning with temporal logic
M Cai, M Hasanbeig, S Xiao, A Abate, Z Kan
IEEE Robotics and Automation Letters 6 (4), 7973-7980, 2021

Machine learning in multiscale modeling of spatially tailored materials with microstructure uncertainties
S Xiao, P Deierling, S Attarian, A El Tuhami
Computers & Structures 249, 106511, 2021

Development of a 2NN-MEAM potential for boron
S Attarian, S Xiao
Journal of Micromechanics and Molecular Physics 5 (03), 2050008, 2020

A machine-learning-enhanced hierarchical multiscale method for bridging from molecular dynamics to continua
S Xiao, R Hu, Z Li, S Attarian, KM Björk, A Lendasse
Neural Computing and Applications 32 (18), 14359-14373, 2020

Investigation of the Observed Rupture Lines in Abdominal Aortic Aneurysms Using Crack Propagation Simulations
S Attarian, S Xiao, TC Chung, ES da Silva, ML Raghavan
Journal of biomechanical engineering 141 (7), 2019

Peridynamics with Corrected Boundary Conditions and Its Implementation in Multiscale Modeling of Rolling Contact Fatigue
MA Ghaffari, Y Gong, S Attarian, S Xiao
Journal of Multiscale Modelling 10 (01), 1841003, 2019

Atomistic simulation of diffusion bonding of dissimilar materials undergoing ultrasonic welding
A Samanta, S Xiao, N Shen, J Li, H Ding
The International Journal of Advanced Manufacturing Technology, 2019

Multiscale modeling and simulation of rolling contact fatigue
MA Ghaffari, Y Zhang, S Xiao
International Journal of Fatigue 108, 9-17, 2018


Shaoping Xiao

UI professor uses AI to model and control water reservoir discharge during flooding

Friday, November 18, 2022
Shaoping Xiao, a University of Iowa mechanical engineering associate professor, is developing an artificial intelligence-powered model to optimize how water reservoirs are used to regulate streamflow during flooding.
Abstract image

UI professor awarded a $1 million grant to research machine learning, modeling, and simulation

Friday, February 25, 2022
University of Iowa Technology Institute faculty affiliates Sharif Rahman, Jia Lu, and Shaoping Xiao, who are all faculty in the Department of Mechanical Engineering, are on a research team led by Ching-Long Lin studying the educational gap between engineering scholars.