Research Topics
- Computational mechanics
- Design optimization
Professor Sharif Rahman's research interests include multiscale mechanics of heterogeneous media, mathematical models of random microstructure, uncertainty quantification of high-dimensional complex systems, random eigenvalue problems, and stochastic mesh-free and finite-element methods.
Research Team
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Sharif Rahman, PhD
Title/Position
Director, Sharif Rahman Research Group
Professor, Department of Mechanical Engineering
Professor, Department of Applied Mathematical and Computational Sciences
Projects
Current research projects:
- Novel Computational Methods for Design under Uncertainty with Arbitrary Dependent Probability Distributions
- CDS&E: Stochastic Isogeometric Analysis by Hierarchical B-Spline Sparse Grids
- High-Dimensional Stochastic Design Optimization by Spline Dimensional Decomposition
- Reliability Analysis and Design Optimization of Fatigue Life of Vehicle Components
- Predictive and Analytical Methods for Rapidly Assessing the Reliability of Commercial Off-the-Shelf Parts and Emerging Technologies
Research summaries:
- Stochastic Optimization for Design under Uncertainty with Dependent Probability Measures
- A New Decomposition Method for Solving Stochastic Eigenvalue Problems in Computational Dynamics
- Reliability-Based Design Optimization of Large-Scale Complex Systems
- Novel Computational Methods for Solving Random Eigenvalue Problems
News
ME professor developing new algorithms to optimize design reliability
Friday, September 15, 2023
Sharif Rahman, a professor of mechanical engineering and a faculty affiliate of the Iowa Technology Institute, is developing advanced computational algorithms to optimize designs of complex engineering systems and structures that could make ground vehicles, aerospace structures, and electronic packaging, among many examples, more reliable.
New $1M grant to bridge educational gaps between modeling and simulation and machine learning
Friday, February 18, 2022
The United States Department of Education has awarded a $1 million grant to Professors Ching-Long Lin (PI), Sharif Rahman, Jia Lu, Shaoping Xiao, Rachel Vitali and Jane Russell to develop artificial intelligence modeling and simulation (AIMS) programs to bridge educational gaps between modeling and simulation and machine learning.