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31 - 40 of 40 results for: ME 1: Introduction to Mechanical Engineering

ME 340: Mechanics - Elasticity and Inelasticity

Introduction to the theories of elasticity, plasticity and fracture and their applications. Elasticity: Definition of stress, strain, and elastic energy; equilibrium and compatibility conditions; and formulation of boundary value problems. Stress function approach to solve 2D elasticity problems and Green’s function approach in 3D. Applications to contact and crack. Plasticity: Yield surface, associative flow rule, strain hardening models, crystal plasticity models. Applications to plastic bending, torsion and pressure vessels. Fracture: Linear elastic fracture mechanics, J-integral, Dugdale-Barrenblatt crack model. Applications to brittle fracture and fatigue crack growth. Computer programming in Matlab is used to aid analytic derivation and numerical solutions.
Terms: Aut | Units: 3
Instructors: Gu, W. (PI)

ME 344: Introduction to High Performance Computing

ME 344 is an introductory course on High Performance Computing Systems, providing a solid foundation in parallel computer architectures, cluster operating systems, and resource management. This course will discuss fundamentals of what an HPC cluster consists of, and how we can take advantage of such systems to solve large scare problems in wide ranging applications like computational fluid dynamics, image processing, machine learning and analytics. You will learn how to take advantage of Open HPC, Intel Parallel Studio, Environment Modules, Containers, Spack, and Cloud-based architectures via lectures, practical hands-on homework assignments, and hands-on laboratory work. While we provide software and supporting libraries to complete homework, you are welcome to bring you own application to learn how to build and make use of it in an HPC, Container, or Cloud-based compute environment. There are no prerequisites for computer programming languages. Many of the tasks involve scripting languages, knowledge of bash, python, or similar is helpful. Group work and collaboration on projects is both allowed and encouraged.
Terms: Sum | Units: 3
Instructors: Jones, S. (PI)

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: Spr | Units: 3
Instructors: Cai, W. (PI)

ME 351B: Fluid Mechanics

Laminar viscous fluid flow. Governing equations, boundary conditions, and constitutive laws. Exact solutions for parallel flows. Creeping flow limit, lubrication theory, and boundary layer theory including free-shear layers and approximate methods of solution; boundary layer separation. Introduction to stability theory and transition to turbulence, and turbulent boundary layers. Prerequisite: 351A.
Terms: Win | Units: 3

ME 352B: Fundamentals of Heat Conduction

Physical description of heat conduction in solids, liquids, and gases. The heat diffusion equation and its solution using analytical and numerical techniques. Data and microscopic models for the thermal conductivity of solids, liquids, and gases, and for the thermal resistance at solid-solid and solid-liquid boundaries. Introduction to the kinetic theory of heat transport, focusing on applications for composite materials, semiconductor devices, micromachined sensors and actuators, and rarefied gases. Prerequisite: consent of instructor.
Terms: Win | Units: 3
Instructors: Goodson, K. (PI)

ME 352C: Convective Heat Transfer

Prediction of heat and mass transfer rates based on analytical and numerical solutions of the governing partial differential equations. Heat transfer in fully developed pipe and channel flow, pipe entrance flow, laminar boundary layers, and turbulent boundary layers. Superposition methods for handling non-uniform wall boundary conditions. Approximate models for turbulent flows. Comparison of exact and approximate analyses to modern experimental results. General introduction to heat transfer in complex flows. Prerequisite: 351B or equivalent.
Terms: Spr | Units: 3
Instructors: Eaton, J. (PI)

ME 373: Nanomaterials Synthesis and Applications for Mechanical Engineers

This course provides an introduction to both combustion synthesis of functional nanomaterials and nanotechnology. The first part of the course will introduce basic principles, synthesis/fabrication techniques and application of nanoscience and nanotechnology. The second part of the course will discuss combustion synthesis of nanostructures in zero-, one- two- and three- dimensions, their characterization methods, physical and chemical properties, and applications in energy conversion systems.
Terms: Win | Units: 3
Instructors: Zheng, X. (PI)

ME 374: Dynamics and Kinetics of Nanoparticles

Part 1: Thermodynamics, transport theories and properties, aerosol dynamics and reaction kinetics of nanoparticles in fluids. Nucleation, gas kinetic theory of nanoparticles, the Smoluchowski equation, gas-surface reactions, diffusion, thermophoresis, conservation equations and useful solutions. Part 2: Introduction to soot formation, nanoparticles in reacting flows, particle transport and kinetics in flames, atmospheric heterogenous reactions, and nanocatalysis.
Terms: Win | Units: 3
Instructors: Wang, H. (PI)

ME 377: Design Thinking Studio

Design Thinking Studio is an immersive introduction to design thinking. You will engage in the real world with your heart, hands and mind to learn and apply the tools and attitudes of design. The class is project-based and emphasizes adopting new behaviors of work. Fieldwork and collaboration with teammates are required and are a critical component of the class. Application required, see dschool.stanford.edu/classes for more information.
Terms: Aut, Win, Spr | Units: 4

ME 405: Asymptotic Methods in Computational Engineering

This course is not a standard teaching of asymptotic methods as thought in the applied math programs. Nor does it involve such elaborate algebra and analytical derivations. Instead, the class relies on students' numerical programming skills and introduces improvements on numerical methods using standard asymptotic and scaling ideas. The main objective of the course is to bring physical insight into numerical programming. The majority of the problems to be explored involve one- and two-dimensional transient partial differential equations inspired by thermal-fluid and transport engineering applications. Topics include: 1-Review of numerical discretization and numerical stability, 2-Implicit versus explicit methods, 3-Introduction to regular and singular perturbation problems, 4-Method of matched asymptotic expansions, 5-Stationary thin interfaces: boundary layers, Debye layers, 6-Moving thin interfaces: shocks, phase-interfaces, 7-Reaction-diffusion problems, 8-Directional equilibrium and lubrication theory.
Last offered: Winter 2019
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