Predictive Science and Engineering Design Cluster and Certificate Requirements

The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.

Cluster

Educating graduate students in predictive science, V&V and Uncertainty Quantification (UQ), and computational design requires substantial, in-depth interdisciplinary training. To receive the fellowship, a Fellow is required to take the PSED seminar course (PSED 510) and participate PS&ED seminar and events.

Certificate

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).

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.

Available Course:
  • PSED Seminar 510-1, 510-2

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.

Available Courses:

  • CHE 451 Applied Molecular Modeling
  • CIV_ENG 426-1 or 2 Advanced Finite Element Methods, I or II
  • (same as MECH_ENG 426-1 or 2 Computational Mechanics I or II)
  • EECS 358 Introduction to Parallel Computing
  • EECS 467 Parallel and Distributed Database Systems
  • IEMS 435 Introduction to Stochastic Simulation
  • MAT_SCI 510 Atomic-Scale Computational Materials Science
  • MECH_ENG 317 or 318 Simulation Techniques I, II

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.

Available Courses:
  • BMD_ENG 384 Biomedical Computing
  • IEMS 465 Simulation Experiment Design and Analysis
  • MAT_SCI 390 Materials Design
  • MECH_ENG 341 Computational Methods for Engineering Design
  • MECH_ENG 366 Finite Elements for Design and Optimization
  • MECH_ENG 441-1 Engineering Optimization for Product Design and Manufacturing

For full course descriptions, see the McCormick Predictive Science and Engineering Design website.