ECE 411
Numeric Modeling of Physics & Biological Systems
Required course: No
Course Level
Units
Instructor(s)
Prerequisite(s)
Course Texts
Required Books:
- Wolfgang Fink, ECE 411/511 "Numeric Modeling of Physics & Biological Systems" Class Notes @ Bookstore.
- WH Press, BP Flannery, SA Teukolsky, and WT Vetterling "Numerical Recipes in C: The Art of Scientific Computing" Cambridge University Press, Cambridge, NY (2nd Edition freely available).
- Holly Moore, "MATLAB for Engineers" 3rd Edition, Pearson (potentially accessible per "Inclusive Access" via D2L).
Recommended:
- EW Schmid, G Spitz, W Loesch, "Theoretical Physics on the Personal Computer" 2nd Edition, Springer.
- lSBN-10: 3540522433; ISBN-13: 978-3540522430 (available as EBook free-of-charge via D2L).
- B. Mueller, J Reinhardt, "Neural Networks: An Introduction" Berlin: Springer (available as EBook free-of-charge via D2L).
- J Hertz, A Krogh, RG Palmer, "Introduction to the Theory of Neural Computation (Lecture Notes vol 1)" Reading, MA: Addison-Wesley (available as EBook free-of-charge via D2L).
Schedule
Course Description
Specific Course Information:
2021-2022 Catalog Data: This course combines themes from mechanics, electromagnetics, thermal physics, and neural networks with an introduction to numerical methods as well as the use of MATLAB. Students will become familiar with the underlying theory for a variety of systems in physics and biology (e.g., harmonic, anharmonic, and coupled oscillators; electric fields of electric lenses; geothermal power stations; and artificial neural networks), derive the necessary mathematical equations describing these systems, learn the necessary numerical methods to solve the underlying equations, and implement the system equations and numerical methods in MATLAB to simulate these systems. As a result, students will be prepared to formulate problems or model systems in physics, biology, and related disciplines, and to solve them numerically or in simulation.
Learning Outcomes
Specific Goals for the Course:
Outcomes of Instruction: By the end of this course the student will be able to:
- Use MATLAB for data manipulation, data plotting, and programming (411: basic; 511: advanced).
- Numerically differentiate and integrate functions with several techniques of different accuracy and efficiency (411: intermediate; 511: intermediate).
- Transform systems of differential equations and solve them numerically with several techniques of increasing numerical accuracy (411: intermediate; 511: intermediate).
- Solve systems of linear equations efficiently (411: basic; 511: advanced).
- Understand the underlying theory for a variety of systems in physics and biology, model these systems by deriving the necessary mathematical equations describing these systems, understand and apply the necessary numerical methods to solve the underlying equations, and program the system equations and numerical methods in MATLAB to simulate the systems (411: intermediate; 511: advanced).
- Formulate problems or model systems in physics, biology, and related disciplines, and solve them numerically or in simulation (411: intermediate; 511: advanced).
- Know and assess the validity, limits, and pitfalls of numerical simulations (411: basic; 511: intermediate).
Course Topics
Brief list of topics to be covered:
- Basic introduction to Matlab
- Numerical differentiation
- Numerical integration
- Harmonic Oscillations with Sliding and Static Friction.
- Anharmonic Free and Forced Oscillations
- Coupled Harmonic Oscillations
- Artificial Neural Networks
- Computation of Electric Fields
- Geo-Thermal Power Station (may potentially be replaced with modeling COVID-19 pandemic
Relationship to Student Outcomes
ECE 411 contributes directly to the following specific electrical and computer engineering student outcomes of the ECE department:
1. An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
2. An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
4. An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts