MIT OpenCourseWare

Browse materialsMIT 10.34 · Fall 2015

Numerical Methods Applied to Chemical Engineering

Subjects: Engineering · Mathematics

Art: Demachy, Jacques-François, 1728-1803, L'art du Distillateur d'Eaux-Fortes, &c., 1775 · Public domain

Instructors: Prof. William Green, Jr., Prof. James W. Swan
Term: Fall 2015
Level: Graduate
What's inside: 23 videos · 5 exams · 3 solutions · 1 lecture note · 1 reading · 90 other files · 4 web pages
Materials open: Videos here · files on MIT OCW

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10.34 · Fall 2015 · Study here (this version)
10.34 · Fall 2005 · On MIT OCW ↗

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About this course

Source: MIT OpenCourseWare 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015, Prof. William Green, Jr., Prof. James W. Swan — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 22, 2026. How RedLectern is built.

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Prerequisites are not listed here. Check MIT's own syllabus for this course.

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Readings

Numerical Methods Applied to Chemical Engineering: Joe Scott notesPDF Download

Lecture Notes

29 files

Assignments

36 files

Exams

7 files

Other materials from this course

2 files

23 video transcripts

1 image

10-34f15th-1JPEG image Open ↗

MIT OpenCourseWare, Prof. William Green, Jr., Prof. James W. Swan, 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015.

License: CC BY-NC-SA 4.0 · Edition: Fall 2015 · Open the original course on OCW ↗

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Numerical Methods Applied to Chemical Engineering

Before you start

What's here, and what isn't

Not included here

Materials by section

Readings

Lecture Notes

Assignments

Exams

Other materials from this course

Session 5: Eigenvalues and Eigenvectors

Session 6: Singular Value Decomposition; Iterative Solutions of Linear Equations

Session 7: Solutions of Nonlinear Equations; Newton-Raphson Method

Session 8: Quasi-Newton-Raphson Methods

Session 9: Homotopy and Bifurcation

Session 11: Unconstrained Optimization; Newton-Raphson and Trust Region Methods

Session 12: Constrained Optimization; Equality Constraints and Lagrange Multipliers

Session 13: ODE-IVP and Numerical Integration 1

Session 16: ODE-IVP and Numerical Integration 4

Session 18: Differential Algebraic Equations 2

Session 19: Differential Algebraic Equations 3

Session 20: Boundary Value Problem 1

Session 21: Boundary Value Problems 2

Session 22: Partial Differential Equations 1

Session 25: Review Session

Session 26: Partial Differential Equations 2

Session 27: Probability Theory 2

Session 28: Models vs. Data 1

Session 30: Models vs. Data 3

Session 33: Monte Carlo Methods 2

Session 34: Stochastic Chemical Kinetics 1

Session 35: Stochastic Chemical Kinetics 2

Session 36: Final Lecture