Methods Engineering Computation
HOME ::

Methods Engineering Computation - 27728 - CE 5332

Modern Methods/Engr Computation - CE 6332 001

Class 3:00- 4:20pm TR
CRBL 304

Office Hours: 10:30 - 2:35 T, R

# Goal:

Despite the title, this will be a fun “tools” class. Many, many engineering (and living) problems require some type of numerical solution or analysis. Mostly this is performed by purchased codes, however it is important for engineers to understand the usage and limitations of numerical methods and at least the basics of what is behind the black box solution.
We will use Excel to explore the basics of interpolation, systems of linear equations, nonlinear equations, curve fitting, numerical integration, differentiation, ordinary differential equations, partial differential equations, and Monte Carlo simulation.
Class will consist of students completing Excel workbooks based upon real world problems such as: a) how to get rich in the stock market, b) river flow measurement, c) heat transfer in soil, and d) spread of disease throughout the world.
The context will illustrate the importance of the methods being taught. Subsequent to the class the student will be better prepared to address a variety of engineering and life problems.

Date Topics and Assignments
T January 19 Root finding and minimization - Find Depth with Manning Equation  Interest  Answers Reading
T January 26 Simple Regression and Curve Fitting Reference Exercise Answer  Reading
R January 28 Simple Regression and Curve Fitting Sheet Answer
R February 4

Non-linear Curve Fitting - Stage Discharge Relationship Answer Sheet
(note: this exercise didn't work well because USGS uses the equation to generate the data and thus there is no normal uncertainty; found some measured data from internet, use it next time) Reading A  Reading BReading C

T February 9 Brute Force Method, Correlation Matrix - Efficient Frontier -propagation of uncertainty through models - get rich in the Stock Market  Video Sheet  Answer    Reading A  Reading B
R February 11 Brute Force Method, Correlation Matrix - Efficient Frontier - go broke in the Stock Market Answer  Sheet Reading
T February 16 Monte Carlo Method - Saving for Retirement Sheet Answer Reading
R February 18 Monte Carlo Method - Retirement Income - leave the working class forever Sheet Answer
T February 23 Monte Carlo Method - Retirement Income - optimizing risk and safety, take the spreadsheets from last two times and create a new income algorithm (e.g., part constant, part variable, take more out when market is high, less when it is low, buy an annuity with some of the money, etc), find the best portfolio(s) for robust wealth creation and a safe, secure, reasonably high income retirement, make sure you never go broke, present your solution to the class
R February 25 Present Optimization Results; Reading for Best Solution
T March 1

T March 8 Spring Break
R March 10 Spring Break
T March 15

Numerical Differentiation - Path Through Groundwater   Answer Sheet

R March 17 Review (password for protected files is "class notes") Summary Sheet
T March 22

First Midterm Exam

R March 24 Ordinary Differential Equations - Epidemic answer sheet
T March 28

Ordinary Differential Equations - boundary value problem; finish ODE system of equations from last period and begin boundary value problems

Boundary Value Problems

The shooting method
https://en.wikipedia.org/wiki/Shooting_method

Heat transfer example
http://www.mech.utah.edu/~pardyjak/me6700/Lect15_BoundEigenvalueProblemsCh27.pdf

R March 31 Ordinary Differential Equations - boundary value problem; finish boundary value problems Linear NonlinearAnswers
T April 5

Finite Difference Introduction - Partial Differential Equations

Derivation of Equations

go over rest of semester remaining spreadsheets, note that some are easy modifications of others:

1. 1D transient 2 meters of soil sheet answer

2. 1D Monmouth soil data hand calibration sheet

3. 1D Monmouth calibrate using solver (create objective function using measured vs modeled data; minimize it by letting the solver change the soil heat K and rho*Cp)

4. 2D homogeneous steady relaxation factor, compare to analytical solution (note: students didn't understand what to do with this one, explain what is needed better if class is taught again, they didn't seem to understand boundary conditions in the analytical solution and how to mimic that in a numerical solution)

sheet

5. 2D heterogeneous steady anisotropic kegerator

6. 2D heterogeneous steady anisotropic flux planes and optimization

Derive finite difference equations and discuss different types of solutions; path across the field and fluxes; model calibration versus data; model verification versus analytical solutions; begin PDE solver

R April 7 Partial Differential Equations - Soil Temperature Data - 1D transient heterogeneous; derive your own equation and solve; sheet (1)
T April 12 (Walton out of town) Partial Differential Equations sheet (2)
R April 14 Partial Differential Equations - Soil Temperature Data - sheet (3)
T April 19 Partial Differential Equations - sheet (4)
R April 21 Partial Differential Equations -sheet (5)
T April 26 Partial Differential Equations - sheet (6)
R April 28 Partial Differential Equations -finish sheets
T May 3 Review
R May 5

Grading will consist of turning in required spreadsheets for each assignment. Spreadsheets may be recycled until a satisfactory grade is obtained. Recycling and late cost 5% of the grade.  Late penalty is by day (5%/day). Assignments will be turned in with a strict subject line to assist your abject professor with smart sorting of an out of control email stream. Each subject line will contain: CE COMPUTATIONAL SHEET 6332: _description_; from Jane Q. Student Where the description and student name are changed as appropriate.

Due dates for spreadsheets are one week from end of listing on syllabus. 80% of grade

Two midterm exams will be given. They will be closed book/notes/computer. Each exam counts for 10% of the overall class grade. The tests will primarily be graphical/ conceptual.

# Policy on Cheating

Students are expected to be above reproach in all scholastic activities. Students who engage in scholastic dishonesty are subject to disciplinary penalties, including the possibility of failure in the course and dismissal from the university. "Scholastic dishonesty included but is not limited to cheating, plagiarism, collusion, the submission for credit of any work or materials that are attributable in whole or in part to another person, taking an examination for another person, any act designed to give unfair advantage to a student or the attempt to commit such acts." Regents' Rules and regulations, Part One, Chapter VI, Section 3, Subsection 3.2, Subdivision 3.22. Since, scholastic dishonesty harms the individual, all students, and the integrity of the university, policies on scholastic dishonesty will be strictly enforced. In short, cheating will not be tolerated.

Class Format

Class format will consist of brief lectures along with linked or printed course reference materials. Each student should come to class with a working computer with Excel installed. We will work on the assignments in class.