Course Overview
Engineering Computation provides graduate students with essential computational skills for modern mechanical engineering practice. The course covers fundamental numerical methods, their implementation, and application to real-world engineering problems.
Course Structure
Module 1: Fundamentals of Numerical Computing
- Error analysis and numerical precision
- Root finding algorithms
- Linear algebra computations
- Interpolation and curve fitting
Module 2: Differential Equations
- Ordinary differential equations (ODEs)
- Partial differential equations (PDEs)
- Numerical integration methods
- Boundary value problems
Module 3: Finite Element Methods
- Introduction to FEA concepts
- Element formulations
- Assembly procedures
- Commercial software applications
Module 4: Advanced Topics
- Computational fluid dynamics basics
- Optimization techniques
- Introduction to machine learning in engineering
- High-performance computing considerations
Assessment
- Homework Assignments (40%): Weekly computational problems
- Midterm Project (25%): Implementation of a numerical method
- Final Project (35%): Application to an engineering problem of choice
Software Tools
Students will work with various computational tools including:
- MATLAB/Python for algorithm implementation
- ANSYS/Abaqus for finite element analysis
- ParaView for visualization
- Git for version control
Office Hours
Dr. Shimada: Tuesdays and Thursdays, 2:00 PM - 3:30 PM Location: Scaife Hall 317
For additional support, please utilize the course discussion forum on Canvas or schedule individual appointments as needed.