101 - 110 of 184 results for: ME

This project based course will cover the application of engineering analysis methods learned in the Mechanics and Finite Element series to real world problems involving the mechanical analysis of a proposed device or process. Students work in teams, and each team has the goal of solving a problem defined jointly with a sponsoring company or research group. Each team will be mentored by a faculty mentor and a mentor from the sponsoring organization. The students will gain experience in the formation of project teams; interdisciplinary communication skills; intellectual property; and project management. Course has limited enrollment.

Newton, Euler, D'Alembert (road-map) methods and computational tools for 3D kinematic, force, and motion analysis of multibody systems. Power, work, and energy. Computational solutions of nonlinear algebraic and differential equations governing the static and dynamic behavior of multibody systems.

Advanced methods and computational tools for the efficient formulation of equations of motion for multibody systems. Lagrange, D'Alembert, and Kane's methods for systems with constraints. Simple-to-complex modeling, analysis, and design (via vehicle dynamics). Quaternions. Advanced control techniques (e.g., feed-forward control). Team-based computational multibody lab project (e.g., vehicle dynamics, biomechanics, robotics, aerospace, alternative energy).

Modeling and analysis of dynamical systems. This class will cover reference frames and coordinate systems, kinematics and constraints, mass distribution, virtual work, D'Alembert's principle, Lagrange, and Hamiltonian equations of motion. We will then consider select topics in controls and machine learning that utilize dynamics concepts. Students will learn and apply these concepts through homework and projects involving dynamic systems simulation. Prerequisites: ENGR15, CME 104, ENGR 154 or equivalent, Recommended: Linear Algebra ( EE 263, Math 113, CME 302 or equivalent), Partial Differential Equations ( Math 131P or equivalent).

Fundamental concepts and techniques of primal finite element methods. Method of weighted residuals, Galerkin's method and variational equations. Linear eliptic boundary value problems in one, two and three space dimensions; applications in structural, solid and fluid mechanics and heat transfer. Properties of standard element families and numerically integrated elements. Implementation of the finite element method using Matlab, assembly of equations, and element routines. Lagrange multiplier and penalty methods for treatment of constraints. The mathematical theory of finite elements.

This course is designed to provide an introduction to discontinuous Galerkin (DG) methods and related high-order discontinuous solution techniques for solving partial differential equations with application to fluid flows. The course covers mathematical and theoretical concepts of the DG-methods and connections to finite-element and finite-volume methods. Computational aspects on the discretization, stabilization methods, flux-evaluations, and integration techniques will be discussed. Problems and examples will be drawn from advection-reaction-diffusion equations, non-linear Euler and Navier-Stokes systems, and related fluid-dynamics problems. As part of a series of homework assignments and projects, students will develop their own DG-method for solving the compressible flow equations in complex two-dimensional geometries.

Introduction to vectors and tensors: kinematics, deformation, forces, and stress concept of continua; balance principles; aspects of objectivity; hyperelastic materials; thermodynamics of materials; variational principles.

This class will give hands-on experience with programming multicore processors, graphics processing units (GPU), and parallel computers. The focus will be on the message passing interface (MPI, parallel clusters) and the compute unified device architecture (CUDA, GPU). Topics will include multithreaded programs, GPU computing, computer cluster programming, C++ threads, OpenMP, CUDA, and MPI. Pre-requisites include C++, templates, debugging, UNIX, makefile, numerical algorithms (differential equations, linear algebra).

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.