Southern Illinois University
Mechanics · Materials · Manufacturing
We develop predictive models for materials and structures by combining solid mechanics, numerical methods, data-driven modeling, and physical experiment. Our work spans constitutive modeling, elasticity, viscoplasticity, creep, damage, fracture, mechanical characterization, architected materials, metallic additive manufacturing, Bayesian statistics and scientific machine learning.
Research
Recurrent neural operators and learned constitutive models that describe path-dependent response and run inside finite-element solvers. We develop data-driven models for complex multiscale material systems.
Learn more →Viscoplasticity, creep, damage, fracture, and localization in structural and architected materials. We infer constitutive behavior from indirect structural measurements such as indentation using Bayesian inference and uncertainty quantification.
Learn more →Lattice structures printed on in-house laser powder bed fusion equipment, characterized and modeled from unit cell to component. Topics include homogenization, inverse design, defects, and process–property relationships.
Learn more →People
Principal Investigator · Assistant Professor
Mechanics of materials, inverse problems, and scientific machine learning for constitutive modeling.
Ph.D. Student
Additive manufacturing of metal lattice specimens and characterization of their mechanical behavior.
Ph.D. Student
Numerical homogenization of inelastic lattice structures and development of data-driven models.
News
Yupeng Zhang co-organizes a technical track on data-driven methods for inelastic mechanics at the Society of Engineering Science Annual Technical Meeting.
Lab811's metal additive manufacturing laboratory opens in Engineering Building E0040, with a Xact Metal XM200G laser powder bed fusion system, nitrogen supply, powder handling, and specimen preparation equipment.
Yupeng Zhang receives an NSF NAIRR award as single PI, supporting research on machine learning for mechanics.