| week |
Tuesday Lecture |
Thursday Lecture |
Lab |
| 1 |
|
Sept 30: lecture 1: Introduction to Modeling (compartmental models, checking solutions, numerical solutions to higher order ODEs)
- discussion issues 1: how do you know if an analytic or numerical solution is mathematically correct?
- Recommended : Khoo, Chapter 1
|
Oct 1/2 Lab 1:
(lab 1 posted here openly so everyone can access while registrations is finalized)
Introduction to Modeling with MATLAB |
| 2 |
Oct 5, lecture 2: Linear Systems Model Building (mechanical, fluid, chemical, electrical systems and the systems approach.
|
Oct 7, lecture 3: Solutions to Linear Systems. (superposition, state-space, Laplace transforms) (Deepak Chandran)
- discussion issues 2: level of certainty.
- lab 1 due at 10:00 am via CollectIt
|
Oct 7/8 Lab 2:
Linear Model building |
3
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Oct 12, lecture 4 Steady State Analysis
- recommended: Khoo, Chapter 4.1 to 4.6, and 6.1 and 6.2,
|
Oct 14, lecture 5 Time Domain Analysis, Feedback and Stability
- Discussion 3: Impact of Models.
- Lab 2 due
|
Oct 14/15 Lab 3:
Linear Systems Analysis |
| 4 |
Oct 19, lecture 6 Nonlinear Systems Analysis I(Jacobian and Stability, Phase-plane response and nullclines)
- Recommended: Khoo, Chapter 9.1 to 9.3
- Article Discussion 3 due via CollectIt at 10:00: Gardner et al and model impacts
|
Oct 21, lecture 7 Nonlinear Analysis cont. (Nondimensionalization, Bifurcation Theory, Sensitivity Analysis.)
- P.G. Drazin, "Nonlinear Systems", chapter 1: "Introduction", sections 1 through 6
- Discussion 4.
- Lab 3 due
|
Oct 21/22: Lab 4
Nonlinear Systems Analysis
|
| 5 |
Oct 26, lecture 8 System Identification I ( Parameter estimation, least squares, The importance of measurement error and weighting schemes)
- Recommended: Khoo, Chapter 7.1, 7.2.1 and 7.2.2
- no written article discussion due. Instead:
- Project 1 proposal due at 10:00 am via (project plan).
|
Oct 28, lecture 9 System Identification II (Examples)
|
Oct 28/29 lab 5
System Identification
data file for lab 5 |
6
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Nov 2, lecture 10. Stochastic Simulations Overview (Review of probability distributions and statistics, definition of stochastic processes, examples)
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Nov 4, lecture 11. Brownian Dynamics (Diffusion; Langevan Equation, Wiener Process)
|
Nov 4/5 Lab 6
Diffusive Stochastic Processes |
| 7 |
Nov 9, lecture 12. Stochastic chemical reaction equations (Gillespie Exact, Tau-leap method, Chemical Langevin Equation)
- no reading or discussion assignment
- Project 1 delayed until Nov 12
|
Nov 11, lecture 13
Veteran's Day - no lecture, no lab
|
Nov 12
- Project 1 due 10:00 am to collectit
|
| 8 |
Nov 16, lecture 14. Stochastic Chemical Reactions examples (Deepak Chandran)
|
Nov 18, lecture 15 Stochastic Chemical Reactions (Deepak Chandran)
- stochastic chemical reactions: examples
- discuss project ideas.
- Lab 6 due 10:00 am
|
Nov 19/20 Lab 7 Stochastic chemical reaction equations
|
9
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Nov 23, lecture 16 class cancelled due to snow
- project 2 proposal due 10 am
|
No lecture -
- Thanksgiving Holiday
- spend this week working on project 2!
|
No lab -
|
| 10 |
Nov 30 , lecture 17 Introduction to Partial Differential Equations (old ppt overview and new handwritten intro notes).
- project 2 impact discussion due 10 am
|
Dec 2, lecture 18 analytic and numerical solutions methods
|
Dec 3/4
|
| 11 |
Dec 7, lecture 19. Nondimensionalization for PDE and ODE models (helps identify fundamental behaviors of model)
- project 2 validation discussion due 10 am
- posted: digitize data m-file, which can be used to pluck numerical data from a digital figure.
|
Dec 9, lecture 20: Review and Course Evaluations.
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Dec 11/12. Model demonstrations in lab
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| finals week |
Tuesday, Dec 14
|
Wednesday, Dec 15 4:30-6:20 MGH 271.
|
happy winter break!
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