ME 342D: MEMS Fabrication/Projects
Emphasis is on process planning, in process testing, nanofabrication training, exposure to MEMS industry applications. Prerequisite:
ENGR 341
Terms: not given this year

Units: 13

Grading: Letter or Credit/No Credit
ME 344: Introduction to High Performance Computing
ME 344 is an introductory course on High Performance Computing (HPC), providing a solid foundation in parallel computer architectures, programming models, and essential optimization strategies. This course will discuss fundamentals of what an HPC cluster consists of, and how we can take advantage of such systems to solve large scale problems in wide ranging applications like computational fluid dynamics, image processing, machine learning and analytics. The course will consist of lectures, and practical handson homework assignments conducted on an Intel® Xeon Phi Processor based HPC Cluster using various software tools that are part of Parallel Studio XE. In addition to classroom instruction, experience with the latest cuttingedge hardware and interaction with industry experts, the course features hands on projects that emphasize on the application of High Performance Computing and enable students to build upon their knowledge. These include fundamental exercises wherein the students build an HPC cluster from the ground up and applied projects where the students utilize HPC paradigms to build a Deep Learning application. This course is open to both computer scientists and computational scientists who are interested in learning about data parallelism, scaling to large number of nodes, and performance tuning methodologies and tools on standards driven languages and parallel models (C/C++/Fortran/MPI/OpenMP/ Threading Building Blocks/Python). As it's desirable to have such a mix of students, the course will not assume much background, though good programming skills will be needed to get the most of the course.
Terms: Sum

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Jones, S. (PI)
;
Patel, J. (TA)
ME 345: Fatigue Design and Analysis
The mechanism and occurrences of fatigue of materials. Methods for predicting fatigue life and for protecting against premature fatigue failure. Use of elastic stress and elasticplastic strain analyses to predict crack initiation life. Use of linear elastic fracture mechanics to predict crack propagation life. Effects of stress concentrations, manufacturing processes, load sequence, irregular loading, multiaxial loading. Subject is treated from the viewpoints of the engineer seeking uptodate methods of life prediction and the researcher interested in improving understanding of fatigue behavior. Prerequisite: undergraduate mechanics of materials.
Terms: not given this year

Units: 3

Grading: Letter (ABCD/NP)
ME 346A: Introduction to Statistical Mechanics
The main purpose of this course is to provide students with enough statistical mechanics background to the Molecular Simulations classes (
ME 346B,C), including the fundamental concepts such as ensemble, entropy, and free energy, etc. The main theme of this course is how the laws at the macroscale (thermodynamics) can be obtained by analyzing the spontaneous fluctuations at the microscale (dynamics of molecules). Topics include thermodynamics, probability theory, information entropy, statistical ensembles, phase transition and phase equilibrium. Recommended:
PHYSICS 110 or equivalent.
Terms: not given this year

Units: 3

Grading: Letter or Credit/No Credit
ME 346B: Introduction to Molecular Simulations
Algorithms of molecular simulations and underlying theories. Molecular dynamics, time integrators, modeling thermodynamic ensembles (NPT, NVT), free energy, constraints. Monte Carlo simulations, parallel tempering. Stochastic equations, Langevin and Brownian dynamics. Applications in solids, liquids, and biomolecules (proteins). Programming in Matlab.
Terms: not given this year

Units: 3

Grading: Letter or Credit/No Credit
ME 346C: Advanced Techniques for Molecular Simulations
Advanced methods for computer simulations of solids and molecules. Methods for longrange force calculation, including Ewald methods and fast multipole method. Methods for free energy calculation, such as thermodynamic integration. Methods for predicting rates of rare events (e.g. nucleation), including nudged elastic band method and umbrella sampling method. Students will work on projects in teams.
Terms: not given this year

Units: 3

Grading: Letter (ABCD/NP)
ME 347: Mathematical Theory of Dislocations
The mathematical theory of straight and curvilinear dislocations in linear elastic solids. Stress fields, energies, and PeachKoehler forces associated with these line imperfections. Anisotropic effects, Green's function methods, and the geometrical techniques of Brown and IndenbornOrlov for computing dislocation fields and for studying dislocation interactions. Continuously distributed dislocations and cracks and inclusions.
Terms: not given this year

Units: 3

Grading: Letter or Credit/No Credit
ME 348: Experimental Stress Analysis
Theory and applications of photoelasticity, strain sensors, and holographic interferometry. Comparison of test results with theoretical predictions of stress and strain. Discussion of other methods (optical fiber strain sensors, digital image correlation, thermoelasticity, brittle coating, Moire interferometry, residual stress determination). Six labs plus miniproject. Limited enrollment. Lab fee.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
Instructors:
Nelson, D. (PI)
;
Silva, H. (TA)
ME 349: Variational Methods in Elasticity and Plate Theory
An introduction to variational calculus methods and their applications to the theories of elasticity and plates.
Terms: not given this year

Units: 3

Grading: Letter (ABCD/NP)
ME 350A: Design @ the Intersection of Science, Technology, and Entrepreneurship
This 1 credit class is for graduate students who are passionate about turning their research into a product or service. This is a chance to explore the potential impact of your work beyond your lab or research group. We are looking for students from the sciences, engineering, or mathematics, or students who have business acumen or startup experience focused on technology driven companies. If you want to get out of your lab, away from your machine, and start to design your future come join us. The class will begin your journey from research to product conceptualization and user centered design through exercises and group activities. We¿ll meet once a week over the quarter in 10 selfcontained 2 hour workshops where students will focus on their own work as well as explore the practical applications of fellow students¿ ideas, experience team formation and collaboration, and begin to explore product and service design. Aside from class time you will need to commit up to one hour per week outside the class on customer and market exploration. Advisors from industry and academia will mentor student teams. The class will be structured for individuals with team formation optional.
Terms: not given this year

Units: 1

Grading: Satisfactory/No Credit
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