ME 565 - Mechanical Engineering Analysis


Key Links

Video Lectures
Video Lectures (Previous Years)
Homework Dropbox
Midterm (20% of total grade): The midterm will be posted online on Wednesday January 31 and will be due at 5pm on Saturday February 3. This is a 4-hour take-home exam. The 4 hours you use for the exam do not need to be consecutive. For example, you can work on the exam for 2 hours on Wednesday and another 2 hours on Thursday. You are allowed to used course notes (online pdfs and your own handwritten notes), online ME565 lecture videos, and your own homework solutions on the exam. All other resources are prohibited, including: the internet, other books, discussing the exam with other people.
Final [Solutions] (20% of total grade): The final exam will be due at midnight on Sunday March 11th. This is an open-everything exam; for all intents and purposes, you can consider this as a comprehensive HW6 worth 20% of the grade.
Homework (60% of total grade): Please turn in by Friday at 5pm in the ME565 box in the Mechanical Engineering front office or via the HW Dropbox.
MATLAB: Student Edition (recommended if you do not have access)
ICL: Matlab laboratory & login access (Communications Bldg B022 and B027)
Textbook : Advanced Engineering Mathematics, 10th Edition, by E. Kreyszig


Steve Brunton, MEB 305
Office Hours: Wednesday, 10:30-11:30am

Teaching Assistants and Office Hours

Ben Tereshchuk

David Schipf

Zhe Bai

Office Hours, MEB 236:
Tuesday: 2:30-4:00pm
Wednesday: 2:30-4:00pm
Thursday: 10:00-12:00pm, 1:30-3:30pm
Thursday Skype: 6:30-7:30pm
Friday: 2:30-4:00pm

Course Description

This course will provide an in-depth overview of powerful mathematical techniques for the analysis of engineering systems. In addition to developing core analytical capabilities, students will gain proficiency with various computational approaches used to solve these problems. Applications will be emphasized, including fluid mechanics, elasticity and vibrations, weather and climate systems, epidemiology, space mission design, and applications in control.


In this course, we will develop many powerful analytic tools. Equally important is the ability to implement these tools on a computer. The instructor and TAs use Matlab, and all examples in class will be in Matlab.


Part 1 - Complex Analysis

(Lecture 01) Complex numbers and functions (notes)

(Lecture 02) Roots of unity, branch cuts, analytic functions, and the Cauchy-Riemann conditions (notes)

(Lecture 03) Integration in the complex plane (Cauchy-Goursat Integral Theorem) (notes)

(Lecture 04) Cauchy Integral Formula (notes)

(Lecture 05) ML Bounds and examples of complex integration (notes)

(Lecture 06) Inverse Laplace Transform and the Bromwich integral (notes)

Part 2 - Partial Differential Equations and Transform Methods (Laplace and Fourier)

(Lecture 07) Canonical Linear PDEs: Wave equation, Heat equation, and Laplace's equation (notes)

(Lecture 08) Heat Eqaution: derivation and equilibrium solution in 1D (i.e., Laplace's equation) (notes)

(Lecture 09) Heat Equation in 2D and 3D. 2D Laplace Equation (on rectangle) (notes)

(Lecture 10) Analytic Solution to Laplace's Equation in 2D (on rectangle) (notes)

(Lecture 11) Numerical Solution to Laplace's Equation in Matlab. Intro to Fourier Series. (notes, L11_Laplace.m, L11_AnalyticLaplacian.m, L11_HardAnalyticLaplace.m)

(Lecture 12) Fourier Series (notes, L12_Fourier.m)

(Lecture 13) Infinite Dimensional Function Spaces and Fourier Series (notes)

(Lecture 14) Fourier Transforms (notes)

(Lecture 15) Properties of Fourier Transforms and Examples (notes)

(Lecture 16) Discrete Fourier Transforms (DFT) (notes)

(Lecture 17) Fast Fourier Transforms (FFT) and Audio (notes, EX1_FFT.m, EX2_FFT.m)

(Lecture 18) FFT and Image Compression (notes, compress.m)

(Lecture 19) Fourier Transform to Solve PDEs: 1D Heat Equation on Infinite Domain (notes)

(Lecture 20) Numerical Solutions to PDEs Using FFT (notes, HeatConvolution.m, HeatFFT.m, HeatBoth.m, SpectralDerivative.m, benchSpectralDerivative.m, smoothFFTDeriv.m)

(Lecture 21) The Laplace Transform (notes)

(Lecture 22) Laplace Transform and ODEs (notes)

(Lecture 23) Laplace Transform and ODEs with Forcing (step, impulse, and frequency response from transfer functions) (notes)

(Lecture 24) Convolution integrals, impulse and step responses (notes)

(Lecture 25) Laplace transform solutions to PDEs (notes)

(Lecture 26) Solving PDEs in Matlab using FFT (notes)

(Lectures 27-29) Singular value decomposition (SVD) and Data Science (notes)

(Lecture 29) SVD and facial recognition (eigenfaces) (