Predictive Science and Engineering Design Certificate
The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.
Certificate
Total Units Required: 5
Course Requirements:
To earn a graduate certificate in Predictive Science and Engineering Design, a student must enroll in at least 5 approved courses (three core courses plus two electives).
| Course | Title |
|---|---|
| Core Area 1: PSED Seminar | |
| This is a literature and project combined seminar course focusing on the common principles and techniques underlying Predictive Science and Engineering Design (PS&ED). In addition to learning the fundamental principles and techniques associated with PS&ED, students will work in teams on interdisciplinary projects related to the current design focus of PS&ED. | |
| Predictive Science & Engineering Design Cluster Seminar | |
| Predictive Science & Engineering Design Cluster Seminar | |
| Core Area 2: Modeling, Simulation, and High Performance Computing | |
| This topic introduces the next generation of advanced computational methods for predictive simulation of multiscale, multiphysics phenomena. Topics include molecular dynamics, lattice mechanics, methods of thermodyanmics, statistical mechanics, multiscale modeling, bridging scale methods, supercomputing, etc. Students will also become proficient in computing technology, including numerical computation and the practical use of advanced computer architectures. | |
| Applied Molecular Modeling | |
| Advanced Finite Element Methods 1 | |
| Advanced Finite Element Methods I | |
| Advanced Finite Element Methods 2 | |
| Advanced Finite Element Methods II | |
| Introduction to Parallel Computing | |
| Stochastic Simulation | |
| Special Topics (Atomic-Scale Computational Materials Science) | |
| Multi-scale Modeling and Simulation in Solid Mechanics | |
| Multi-Scale Modeling and Simulation in Fluid Mechanics | |
| Core Area 3: Computational Design Methods | |
| This topic provides students across all disciplines a view of using computational techniques (including topics like modeling, simulation, optimization, uncertainty quantification, risk-based decision making) and the simulation-based design paradigm for designing complex “engineered” systems based on predictive models. | |
| Simulation Experiment Design & Analysis | |
| Materials Design | |
| Computational Methods for Engineering Design | |
| Special Topics in Mechanical Engineering (Mechanistic Data Science for Engineering) | |
| Engineering Optimization for Product Design and Manufacturing | |
| Electives (2 required courses) | |
| Biomechanics of Movement | |
| Applied Mathematical Statistics | |
| Reliability Engineering | |
| Experiments in Micro- and Nano Science and Engineering | |
| The Calculus of Variations and Its Applications (Optimization Methods in Science and Engineering) | |
| Metal Forming | |
| Advanced Tribology | |
| Micromachining | |