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1 - 10 of 20 results for: ME

ME 12N: The Jet Engine

Preference to freshmen. This seminar describes how a jet engine works with examples given from modern commercial and military engines. We then explore the technologies and sciences required to understand them including thermodynamics, turbomachinery, combustion, advanced materials, cooling technologies, and testing methods. Visits to research laboratories, examination of a partially disassembled engine, and probable operation of a small jet engine. Prerequisites: high school physics and preferably calculus.
Terms: Sum | Units: 3 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit

ME 13AX: Form & Space

In this course students will explore the inherent order in 3-dimensional space that underlies and determines nature of form and structure, and then use that knowledge to inform the design and fabrication of original artworks. A survey of relevant artists and architects will suggest the rich potential for creative expression that results from a deep understanding of the nature of space. Topics will include: symmetry, pattern, tessellation, duality, transformation, polyhedra, space-filling.

The course will be conducted in Room 36, a state-of-the art maker space. Students will learn how to use a professional CAD program and a computer-controlled laser cutter to create models out of paper, plastic, and wood. Students will have access to 3D printers, and other digital and analog fabrication tools.

Students considering taking this course need not have any background in the visual arts, but should have a firm foundation and avid interest in geometry. Access to a Mac or Windows Laptops is required.
Terms: Sum | Units: 2 | UG Reqs: WAY-CE | Grading: Satisfactory/No Credit
Instructors: Edmark, J. (PI)

ME 191: Engineering Problems and Experimental Investigation

Directed study and research for undergraduates on a subject of mutual interest to student and staff member. Student must find faculty sponsor and have approval of adviser.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable for credit | Grading: Satisfactory/No Credit

ME 191H: Honors Research

Student must find faculty honors adviser and apply for admission to the honors program.nn (Staff)
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable for credit | Grading: Satisfactory/No Credit

ME 199A: Practical Training

For undergraduate students. Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the Student Services Office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.
Terms: Sum | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

ME 232: Additive Manufacturing- From Fundamentals to Applications

Additive manufacturing (AM) is an emerging technique for direct conversion of 3D computer aided designs into physical objects using a variety of approaches. AM technologies are simple and flexible processes that allow for the creation of very complex and customizable 3D objects in just a few process steps. This lecture gives an overview of available processes and current research in additive manufacturing. Students will get to know how AM can change the way we prototype and manufacture products in the future.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit

ME 299A: Practical Training

For master's students. Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the Student Services Office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

ME 299B: Practical Training

For Ph.D. students. Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the student services office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

ME 335C: Finite Element Analysis

Newton's method for nonlinear problems; convergence, limit points and bifurcation; consistent linearization of nonlinear variational forms by directional derivative; tangent operator and residual vector; variational formulation and finite element discretization of nonlinear boundary value problems (e.g. nonlinear heat equation, nonlinear elasticity); enhancements of Newton's method: line-search techniques, quasi-Newton and arc-length methods.
Terms: Spr | Units: 3 | 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 hands-on 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 cutting-edge 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 more »
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 hands-on 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 cutting-edge 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
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