BE 350 - Dynamic Systems Modeling

Instructor: Daniel M. Jenkins
Office: Agricultural Science 415L
Office Hours: TBA & by appointment
Telephone: 956-6069
Email: danielje@hawaii.edu

Grading:	Assignments and Lab:	30%
	Midterms (2):	20% each
	Final:	30%

Textbook:	Course notes and additional readings will be posted on WebCT:
	(Log on with your UH username and password, then click "MAN: Dynamic Syst Model"). Note that course notes will not be posted if attendance is not ≥ 75%.

Prerequisites:

BIOL 171, CHEM 162 or 181A, EE 160, MATH 243 or 252A, and PHYS 170; or consent. Co-requisite BE 350L.

Catalog Description:

3 units. Introduction to analytical and numerical solutions for systems of differential equations. Modeling and computer simulation of representative dynamic systems encountered in biological engineering.

Course Content

Week	Topics
1	Introduction of basic principles: conservation of mass, energy, momentum, charge, etc. Review of systems of linear equations and linear algebra.
2	Determinate and indeterminate systems, singularity. Simple biomass balances using linear algebra. Solution of linear ordinary differential equations.
3	Solution of systems of linear ordinary differential equations. Representative biological systems modeled by systems of linear ordinary differential equations.
4	Solutions of systems of differential equations with repeated and/or complex eigenvalues: system oscillation. Introduction to MATLAB programming environment.
5	Direct solution of higher order differential equations and as a system of linear equations. Introduction to Laplace transforms for solving differential equations.
6	Laplace transforms and Exam 1.
7	Software tools for solving systems of linear equations. Introduction to numerical methods for solving differential equations.
8	Continuation of numerical methods for solving differential equations: Euler, modified Euler, and Runge-Kutte approximations.
9	Implementation of numerical models in MATLAB software. Introduction to LabVIEW data acquisition software and commercial data loggers.
10	Simple model validation using experimental data: linear regression, linearization of complex data sets, graphic techniques, non-linear regression tools.
11	Simple modeling of dynamic systems in biological engineering: 'lumped' analysis for transient mass and energy transfer.
12	Finite difference methods (explicit and implicit numerical solutions) for solving multidimensional transport problems in biology.
13	Finite difference methods (continued), Exam 2
14	Models of representative biological systems: enzyme kinetics models, counter current heat exchange, thermal destruction of microbes, growth and bioproduction kinetics, etc.
15	Open for contingencies, quizzes, review, and student evaluations.

* Note that some topics above will require more or less than 1 week to cover, and the syllabus should not be considered an absolute guide to the amount of time spent on each topic.