To affiliate with the cluster a student is required to take three core courses selected from each of the three core cluster areas. To earn a graduate certificate in Predictive Science and Engineering Design, a student must enroll in at least five approved courses (three core courses plus two electives).

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Core Cluster Areas (3 required courses)

PSED Seminar

PSED Seminar 510-1, 510-2
This is a literature and project combined seminar course focusing on the common principles and techniques underlying Predictive Science and Engineering Design (PSED). In addition to learning the fundamental principles and techniques associated with PSED, students will work in teams on interdisciplinary projects related to the current design focus of PSED.

Modeling, Simulation, and High Performance Computing

ChE 451 Applied Molecular Modeling
Introduction to modern, molecular-level, computational methods for calculating thermodynamic, transport, kinetic, and structural properties of molecules and materials.

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)
Methods for treating material and geometric nonlinearities by finite elements; transient analysis: explicit and implicit time integration, partitioned methods, and stability; hybrid and mixed elements; finite elements for plates and shells; convergence, efficiency, and computer implementation.

EECS 358 Introduction to Parallel Computing
Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.

EECS 467 Parallel and Distributed Database Systems
File allocation and load balancing in parallel I/O systems. Distributed, scalable file systems. Declustering and range partitioning. Parallel processing of relational queries: sort, clustering and join algorithms. Distributed database systems architectures. Query processing in distributed database systems: Processing simple queries; using semi-joins and joins for general queries.

IEMS 435 Introduction to Stochastic Simulation
Discrete event simulation modeling. Design and analysis of simulation experiments. Simulation programming in standard languages. Applications to manufacturing and services.

MAT_SCI 510 Atomic-Scale Computational Materials Science
Theory and application of atomic-scale computational materials tools to model, understand, and predict the properties of real materials.

MECH_ENG 317 or 318 Simulation Techniques I, II
Introduction to modern computational methods for calculating thermodynamic, transport, and structural properties of materials. Computational chemistry, molecular simulation, and mesoscopic methods, with emphasis on interfacial engineering applications.

Computational Design Methods

BMD_ENG 384 Biomedical Computing
Principles of modern (computer-based) medical instrumentation, including analog-vs-digital design tradeoffs, efficient digital filter designs and algorithms for physiological signal processing, automated event recognition, and classification. Hardware and software design of microcomputer-based medical instruments.

IEMS 465 Simulation Experiment Design and Analysis
Point of error estimation, experiment design, run-length control, variance reduction, optimization via simulation, and input modeling for discrete-event stochastic simulation.

MAT_SCI 390 Materials Design
Analysis and control of microstructures. Quantitative process/structure/property/performance relations with case studies. Computer lab for modeling multicomponent thermodynamics and transformation kinetics.

MECH_ENG 341 Computational Methods for Engineering Design
Introduction to a wide range of computational techniques for engineering design. Modeling, simulation, optimization, design software, examples/projects with emphasis on computational techniques for design and manufacturing related applications.

MECH_ENG 395: Mechanistic Data Science for Engineering
We introduce mechanistic data science for engineering through the integration of scientific knowledge, such as physics and mechanics through six basic data science concepts: multimodal data generation and collection, feature engineering, dimension reduction, reduced order modeling, regression, and classification.

MECH_ENG 441-1 Engineering Optimization for Product Design and Manufacturing
Introduction to optimization theory and numerical techniques. Formulations, algorithms, computer implementation, examples/projects with emphasis in numerical and emerging techniques for design and manufacturing related applications.

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Electives (2 required courses)

BMD_ENG 366 Biomechanics of Movement
Detailed analysis of human and animal movement. Modeling of muscle and tendon, kinematics of joints, and dynamics of multijoint movement. Applications of the theory to biomechanical problems in sports, rehabilitation, and orthopedics.

BMD_ENG 420 Biostatistics for Experimenters
Statistical methods for the design and analysis of experiments including randomization and blocking, Latin squares, factorial designs, sequential designs, analysis of variance, regression analysis, response surfaces, empirical and mechanistic model building.

IEMS 401 Intermediate Statistics
Linear model theory with application to multiple regression and analysis of variance. Statistical inference methods including likelihood estimation and testing, resampling and the Bayesian approach.

MECH_ENG 359 Reliability Engineering
Probability concepts and random variables. Failure rates and reliability testing. Wear in, wear out, and random failures. Probabilistic treatment of loads, capacity, and safety factors. Reliability of redundant and of maintained systems. Fault tree analysis.

MECH_ENG 382 Experiments in Micro/Nano Science and Engineering
Integrates physical and biological sciences with engineering. Labs provide hands-on experience in clean room microfabrication, flow visualization in microchannels, nanomechanics, AFM and dip pen nanolithography, multi-physics computational tools, and experimental evaluation techniques.

MECH_ENG 432 Optimization Methods in Science and Engineering
Extremizing multivariate functions, the functional and its variation, Euler-Lagrange equations, isoperimetric problems, applications to optics, mechanics, potential theory, fluid mechanics, wave theory and elasticity.

MECH_ENG 442 Metal Forming
Metal forming processes: drawing, extrusion, rolling, forging, and sheet metal forming. Process analysis and design: force estimation, friction and redundant work effects, temperatures generated, defects, and process and equipment limitations.

MECH_ENG 446 Advanced Tribology
Generalized Reynolds equation; thermal, turbulent, inertia, fluid compressibility, and surface roughness effects in sliding bearings; fatigue, scuffing, and wear in elastohydro-dynamic contact; plastohydrodynamic lubrication in metal rolling, extrusion, and forging.

MECH_ENG 451 Micromachining
Fundamental fabrication issues for microscale components used in MEMS/Nanotechnology. Understand and designing microfabrication processes based on photolithography and deposition/etching steps.

MECH_ENG 453 Micro Systems Design
Theory and tools for analyzing and designing microsystems used in MEMS/Nanotechnology. Includes device physics and analysis, design techniques, and computer-aided design tools for micro systems technology.