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Lecture Notes

Special software is required to use some of the files in this section: .m.


SES # LECTURE NOTES ADDITIONAL FILES
L1 Using MATLAB® to Evaluate and Plot Expressions (PDF) rate.m (M)
L2 Solving Systems of Linear Equations (PDF) rate.m (M)
L3

Matrix Factorization (PDF)

Modularization

gausselim_pivot.m (M)

gauss.m (M)

L4 When Algorithms Run into Problems: Numerical Error, Ill-conditioning, and Tolerances
L5 Introduction to Systems of Nonlinear Equations (PDF)
L6 Modern Methods for Solving Nonlinear Equations
L7 Introduction to Eigenvalues and Eigenvectors
L8 Constructing and Using the Eigenvector Basis
L9 Function Space vs. Real Space Methods for Partial Differential Equations (PDEs)
L10 Function Space
L11

Numerical Calculation of Eigenvalues and Eigenvectors (PDF)

Singular Value Decomposition (SVD)

interpolateV.m (M)

setup_interV.m (M)

L12 Ordinary Differential Equation - Initial Value Problems (ODE-IVP) and Numerical Integration
L13

Stiffness

MATLAB® Ordinary Differential Equation (ODE) Solvers

L14

Implicit Ordinary Differential Equation (ODE) Solvers

Shooting

L15

Differential Algebraic Equations (DAEs)

Introduction: Optimization

L16 Unconstrained Optimization
L17 Constrained Optimization
L18

Optimization

Sensitivity Analysis

Introduction: Boundary Value Problems (BVPs)

L19 Boundary Value Problems (BVPs) Lecture 2

makeA_sparse.m (M)

makeAforLaplacian.m (M)

L20 Boundary Value Problems (BVPs) Lecture 3: Finite Differences, Method of Lines, and Finite Elements
L21 TA Tutorial on BVPs, FEMLAB®
L22 Introduction: Models vs. Data
L23 Models vs. Data Lecture 2: Bayesian View
L24 Uncertainties in Model Predictions
L25 Conclude Models vs. Data
L26 TA Led Review Review Exam 2 (PDF) (Courtesy of Sandeep Sharma. Used with permission.)
L27

Models vs. Data Recapitulation (PDF)

Monte Carlo and Molecular Dynamics

L28 Guest Lecture on Monte Carlo / Molecular Dynamics: Frederick Bernardin Intro to Monte Carlo Methods (PDF) (Courtesy of Frederick Bernardin. Used with permission.)
L29 Genetic Algorithms
L30

Modeling Intrinsically Stochastic Processes

Multiscale Modeling

L31 Fluctuation-dissipation Theorem
L32 Kinetic Monte Carlo and Turbulence Modeling
L33

Operator Splitting

Strang Splitting

L34

Fourier Transforms

Fast Fourier Transform (FFT)

L35 Summary: Problem Solving (PDF)
L36 TA Led Final Review Review Final Exam (PDF) (Courtesy of Sandeep Sharma. Used with Permission.)