Simulation Techniques

Catalog description

An exploration of deterministic and stochastic simulation. Topics will include determining range of validity, boundary issues, managing complexity, optimization and parallelization of code, computational time management, adaptable meshes, fuzzy logic, and fidelity of simulation. Random number generation will also be covered for stochastic simulations. Examples and projects from a broad range of fields will be used. Course may be offered in classroom based, distance or hybrid formats. Typically offered Spring. Course Learning Outcomes 1. Design a deterministic simulation, including evaluating the provided boundary conditions. 2. Design a stochastic simulation, including evaluating the random number generator used. 3. Display the intermediate and final results in various formats, including hard-copy, flat screen, and 3-D visualization, as appropriate. View Class Schedule