CHEN 320: Numerical Analysis for Chemical Engineers (3-0).
Credit 3
Applications of numerical analysis techniques to mathematical models of processes common to chemical and associated industries; computational methods and software for analysis of chemical engineering processes. Prerequisites: CHEN 205; MATH 308; or approval of instructor. Instructor: Carl D. Laird, JEB 205, Email:
[email protected] TA: Yu Zhu, JEB 305, Email:
[email protected] Class Schedule: MWF 11:30-12:20, JEB 106 Office Hours: Wed. 3:00-5:00 (Dr. Laird), Mon. 3:00-5:00 (Yu Zhu - JEB 305) Grader Office Hours: TBD Course Website: Can be accessed through http://elearning.tamu.edu (Blackboard Vista) Textbook: Applied Numerical Methods with MATLAB for Engineers and Scientists, 2nd Edition, by S. Chapra
Course Outcomes • simplify engineering and scientific problems into mathematical models using conservation laws and constitutive equations, translate these models to canonical forms • describe the principles of computational data storage, identify sources of error and methods to estimate the magnitude of errors • effectively implement numerical algorithms using basic numerical computing and structured programming principles • develop and apply numerical techniques for solving linear problems • develop and apply numerical techniques for solving general nonlinear problems, including polynomials, single equation problems, and systems of nonlinear equations • develop and apply numerical techniques for solving ordinary differential equations • formulate optimization problems, identify their class, and apply appropriate numerical techniques for optimization of linear and nonlinear models • apply techniques for effective design of experiments • apply regression techniques for linear and nonlinear parameter estimation • identify the class and properties of a particular problem or model (single/multi-variable, linear, nonlinear, differential, etc.) 1
• perform degrees of freedom analysis to identify over-specified and under-specified problems, determine the existence and uniqueness of solutions for particular problem classes • select appropriate numerical methods (and tuning parameters) for particular problem classes based on strengths and weaknesses of available techniques (e.g. convergence guarantees, convergence rate, performance, acceptable errors and tolerances)
Performance Assessment Your final grade in the course will be determined according to the following distribution:
Homework Worksheets Hour Exam #1 Midterm Exam Hour Exam #2 Final Exam
Tentative Sched. every week every lecture Sept. 17 Oct. 15 Nov. 12 Dec. 10
% of Total Grade 25% 5% 10% 25% 10% 25%
Homework: One homework assignment will be given approximately every week. Assignments will be designated as Individual Assignments or Team Assignments. For individual assignments, you may assist each other in groups, however, each individual must complete and hand in their own homework assignment. Plagiarism will not be tolerated. For team assignments, only one homework package will be submitted for each team. The grades on team assignments will be divided according to peer ratings done periodically throughout the semester. Some homework assignments will require that you upload your MATLAB code using the course website on Blackboard Vista. Make sure you can login to the course site as soon as possible and let the instructor know of any problems. The following excerpt will need to be in comments at the top of every MATLAB file that you submit. %% %% %% %% %% %% %% %% %%
BEGIN_TITLE Aggie Honor Code: An Aggie does not lie, cheat, or steal or tolerate those who do. By submitting this homework electronically, I certify that this work is my own and has not been plagiarised. Name: Assignment #: Question #: END_TITLE
All uploaded files MUST use the naming criteria outlined in the assignment. 2
Worksheets: At various points during lectures, you will be asked to complete a short problem as a worksheet assignment. Worksheet assignments will be handed in at the end of each lecture. Full marks will be given for all worksheet assignments that show reasonable effort. Quizzes: There will be two in-class quizzes (each worth 10%) during the semester. Exams: There will be two exams during the semester. The midterm exam is tentatively scheduled for the evening of Oct. 15th. The final exam is comprehensive and is currently scheduled for Wednesday, December 10, 10:30 a.m.-12:30 p.m. Homework and Worksheet Format: Use Engineering paper for all worksheet and handworked homework problems. Start each question on a new page and box the final answers. STAPLE all pages in the assignment. On the first page, indicate the names of everyone that you worked with on the assignment. Label the top of the page as follows: name
date
Assignment #
pg/tot
Late Homework: Completed assignments should be turned in at the beginning of class (or uploaded before the start of class) on the due date. Homework will have 25 percentage points deducted for each day that the homework is late (e.g. less than 24 hours late will get 25 percentage points deducted). Missed Worksheets, Homework, Quizzes, Exams: In general, missed worksheets, homework, quizzes, and exams will not be rescheduled without a university excusable absence. Special situations may be discussed with the in structure PRIOR to the due date or date of the exam. Worksheet, Homework, and Quiz Grading: The responsibility for grading worksheets, homework, and quizzes resides with the course graders. If you believe that an error has been made in grading, bring it to the grader during the grader office hours. For anything other than a simple addition error, you must present the grader with a written statement outlining why you think the grade should be changed. If you are not satisfied with the grader’s decision, bring the statement to the course instructor, who will make the final decision. Exam Grading: All exams will be graded by the course instructor. As with other grading, if you believe that an error has been made (other than a simple addition error), present the instructor with a written statement outlining why you think the grade should be changed.
Policies and Procedures Academic Integrity: Aggie Honor Code: An Aggie does not lie, cheat, or steal or tolerate those who do. Upon accepting admission to Texas A&M University, a student immediately assumes a commitment to uphold the Honor Code, to accept responsibility for 3
learning, and to follow the philosophy and rules of the Honor System. Ignorance of the rules does not exclude any member of the TAMU community from the requirements or the processes of the Honor System. For additional information please visit: www.tamu.edu/aggiehonor/ Disabled Students: The Americans with Disabilities Act (ADA) is a federal antidiscrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Department of Student Life, Services for Students with Disabilities in Cain Hall, Rm. 118 or call 845-1637. Attendance: Attendance is strongly suggested though not enforced. However, be aware that you are responsible for any material that was missed. Instructor Commitment: Students can expect the instructor to be courteous, punctual, well organized, and prepared for lecture and other class activities; to answer questions clearly and in a non-negative fashion; to be available during office hours or to notify the students beforehand if they are unable to keep them; and to ensure uniform and consistent grading.
Relationship of course to Program Outcomes Course Outcomes 1. Simplify engineering and scientific problems into mathematical models and translate these models to canonical forms 2. Describe the principles of computational data storage, identify sources of error and methods to estimate the magnitude of errors 3. Implement numerical algorithms using structured programming principles 4. Develop and apply numerical techniques for solving linear problems 5. Develop and apply numerical techniques for solving general nonlinear problems, including systems of nonlinear equations 6. Develop and apply numerical techniques for solving ordinary differential equations 7. Formulate and solve optimization problems, including linear and nonlinear models 8. Apply techniques for effective design of experiments 9. Apply regression techniques for linear and nonlinear parameter estimation 10. Identify the class and properties of a particular problem or model 11. Perform degrees of freedom analysis and determine the existence and uniqueness of solutions for particular problem classes 12. Select appropriate numerical methods for particular problem classes
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Program Outcomes 11 11 11 11 11 11 2, 11 2 2, 11 11 11 11
Course Outline The following is a tentative schedule of the topics that will be covered each week in this course: Week 1
Begin Date Aug. 25
Reading Ch. 1
2
Sept. 1
Ch. 2-4
3
Sept. 8
Ch. 8, 11
4
Sept. 15
Ch. 9, 10
5
Sept. 22
Ch. 5-6
6
Sept. 29
Ch. 6,12
7
Oct. 6
Ch. 12
8
Oct. 13
Ch. 17-19
9
Oct. 20
Ch. 20
10
Oct. 27
Ch. 20
11
Nov. 3
Ch. 7
12 13
Nov. 10 Nov. 17
(supp.) Ch. 13
14
Nov. 24
Ch. 14
Topics Background: vectors and matrices, modeling, introduction to MATLAB Numerical Computing: structured programming, scripting & functions, sources of error Linear Problems: modeling, canonical forms, matrix inverse, existence & uniqueness Linear Problems: Gaussian elimination, LU decomposition Nonlinear Problems: modeling, canonical forms, polynomial roots, bracketing searches Nonlinear Problems: open searches, systems of nonlinear equations Nonlinear Problems: systems of nonlinear equations (successive substitution, Newton’s method) Differential/Integral Problems: numerical differentiation & integration Differential/Integral Problems: ordinary differential equations, modeling, canonical forms, solution techniques **INFORMS** Differential/Integral Problems: ordinary differential equations, solution techniques Optimization: formulation and solution techniques for unconstrained problems, formulation and application of constrained problems Data: statistics review, design of experiments Data: linear least squares regression, linearization of nonlinear problems **AICHE** Data: general linear least squares, nonlinear regression
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Team Work Policies and Expectations Some homework assignments will be designated as a Team Assignment. This section outlines the policies and expectations of the team with regard to these assignments. • Each team should be 4 students. The team will be composed of the same team members for each assignment throughout the semester. This is to facilitate the team member evaluations (discussed later). Only in special circumstances, at the discretion of the instructor, will students be allowed to change teams. • A team contract will be written and signed by each of the team members. This contract should outline the expectations for the team. These can include things like, – We will each try to set up the problem individually before meeting – We will each have read and tried to understand the problem statement before meeting. – We will discuss errors in previous assignments with the group at the next available meeting. Choose these expectations wisely, your group will be evaluating your performance against these expectations. • Designate a coordinator for each team assignment. The role of coordinator should be rotated so everyone in the group takes a turn at being coordinator. The coordinator is responsible for ensuring the assignment is completed, including submitting it on time. Please indicate the name of the coordinator on each assignment. • Peer rating sheets will be given out before the midterm and the final. Additional peer rating sheets may be given out at the discretion of the instructor. An example of a peer rating sheet is attached. • Consult with the instructor if a conflict arises that cannot be resolved by the team.
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Team Contract Team Name: Team Expectations:
Team Members: Name: Name: Name: Name:
Signed: Signed: Signed: Signed:
Date: Date: Date: Date:
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Example Peer Rating Sheet Your Name Please write the names of all of your team members, INCLUDING YOURSELF, and rate the degree to which each member fulfilled his/her responsibilities in completing the homework assignments. The possible ratings are as follows: Excellent (100%) Consistently did what he/she was supposed to do, very well prepared and cooperative Satisfactory (90%) Usually did what he/she was supposed to do, acceptably prepared and cooperative Satisfactory (80%) Often did what he/she was supposed to do, minimally prepared and cooperative Marginal (70%) Sometimes failed to show up or complete assignments, rarely prepared Deficient (60%) Often failed to show up or complete assignments, rarely prepared Unsatisfactory (50%) Consistently failed to show up or complete assignments, unprepared Superficial (30%) Practically no participation No show (0%) No participation at all These ratings should reflect each individuals level of participation and effort and sense of responsibility, not his or her academic ability. Name of team member
Percentage Rating
Your signature: Based on a document from R.M. Felder, 1998.
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