3 Cr. (Hrs.:3 Lec.)
Covers various computational modeling and simulation principles and techniques applicable to various domains of engineering and science. Students will implement and apply these methods, including model verification and validation, for basic examples. Students will then complete a project within their discipline to design a representative model, implement the model, complete a verification and validation of the model, and update the model to reflect corrections, improvements and enhancements. Specific topics include matrix languages, ODE solving, PDE solving, finite difference approximation, finite element methods, and visualize data generated from computer simulations. Prerequisites: CSCI 112 or CSCI 117 or CSCI 135 (1st)
Course generally offered fall (1st) semester.
E1. The student should be able to program in a high-level programming language and/or create programs within a software packages – such as MATLAB, R, etc.
E2. The student should have a foundation in calculus and statics.
E3. Student should have explored mathematical models within their discipline.
R1. Be familiar with the importance of modeling for science and engineering.
R2. Be able to identify different types of models and simulation.
R3. Be able to create a computer simulation of a set of observations based on the system’s physical characteristics.
R4. Be able to solve both ordinary and partial differential equations with computers.
R5. Know how to verify and validate a computational model using data.
R6. Know how to construct a computer visualization of the model results.
R7. Understand the quality of the model and sources of errors.
R8. Have made use of one of the simulation frameworks discussed throughout the course to create a term modeling project within their discipline and present a working computational model at the end of the term.