191 - 200 of 298 results for: ME

Design experiments to learn about the relationship between users and products, with an emphasis on quantitative output that is tested with statistics. Students will be exposed to all components of the experimental design process: research proposition, literature review, detailed hypotheses, method selection, experimental instruments, subject selection, pilot studies, analysis approaches, reporting results, and discussing conclusions. Students will receive human subjects training and complete the IRB certificate. Possible experiment design tools include in-person observation and interviews, web surveys, and eye-tracking.

Theories of plasticity and fracture phenomena from both phenomenological and micromechanical viewpoints. Yield surface, flow rules, strain hardening models, and applications to creep. Plastic zone near crack tip. Linear fracture mechanics and other criteria for crack initiation and growth. Application to fatigue. Classical analytic solutions will be discussed together with numerical solutions of plane elastoplatic problems by Matlab.

Cell mechanobiology topics including cell structure, mechanical models, and chemo-mechanical signaling. Review and apply methods for controlling and analyzing the biomechanics of cells using traction force microscopy, AFM, micropatterning and cell stimulation. Practice and theory for the design and application of methods for quantitative cell mechanobiology.

Emphasis is on process planning, in process testing, nanofabrication training, exposure to MEMS industry applications. Prerequisite: ENGR 341

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.

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 elastic-plastic 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, multi-axial loading. Subject is treated from the viewpoints of the engineer seeking up-to-date methods of life prediction and the researcher interested in improving understanding of fatigue behavior. Prerequisite: undergraduate mechanics of materials.

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.

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.

Advanced methods for computer simulations of solids and molecules. Methods for long-range 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.