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Agenda Recap of Lecture 3 Dynamic behavior of basic systems

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Presentation on theme: "Agenda Recap of Lecture 3 Dynamic behavior of basic systems"— Presentation transcript:

0 System Dynamics – 1ZM65 Lecture 4 September 23, 2014
Dr. Ir. N.P. Dellaert

1 Agenda Recap of Lecture 3 Dynamic behavior of basic systems
exponential growth growth towards a limit S-shaped growth If time left, some Vensim 4/15/2017 PAGE 1

2 Recap 3: Examples of stocks and flows with their units of measure
‘’the snapshot test’’ 4/15/2017 4/15/2017 PAGE 2

3 Recap 3 Stocks : integrating flows
In mathematical terms, stocks are an integration of the flows Because of the step size, Vensim is in fact using a summation in stead of an integration: Integration is in fact equivalent to finding the area of a region 4/15/2017 4/15/2017 PAGE 3

4 Inflows and outflows for a hypothetical stock recap Challenge p. 239
Inflows and outflows for a hypothetical stock recap Challenge p. 239 © J.S. Sterman, MIT, Business Dynamics, 2000 sketch analytically VENSIM 4/15/2017

5 Analytical Integration of flows recap
4/15/2017

6 Quadratic versus cosine function
4/15/2017

7 Quadratic versus cosine function
4/15/2017

8 Chapter 8: Growth and goal seeking: structure and behavior
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

9 First order, linear positive feedback system: structure and examples
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

10 positive feedback rabbits
growth=birthrate*population 4/15/2017

11 analytical expression positive feedback
4/15/2017

12 Exponential growth over different time horizons
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

13 First-order linear negative feedback: structure and examples
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

14 Phase plots Phase plots show relation between the state of a system and the rate of change Can be used to find equilibria 4/15/2017

15 Phase plot for exponential decay via linear negative feedback
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

16 analytical expression negative feedback
4/15/2017

17 Exponential decay: structure (phase plot) and behavior (time plot)
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

18 First-order linear negative feedback system with explicit goals
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

19 Phase plot for first-order linear negative feedback system with explicit goal
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

20 analytical expression negative feedback with explicit goal
4/15/2017

21 Exponential approach towards a goal
© J.S. Sterman, MIT, Business Dynamics, 2000 The goal is 100 units. The upper curve begins with S(0) = 200; the lower curve begins with s(0) = 0. The adjustment time in both cases is 20 time units. 4/15/2017

22 Relationship between time constant and the fraction of the gap remaining
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

23 Sketch the trajectory for the workforce and net hiring rate
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

24 © J.S. Sterman, MIT, Business Dynamics, 2000
A linear first-order system can generate only growth, equilibrium, or decay 4/15/2017

25 Example First order differential equation
Suppose the behaviour of a population is described as: P’+3P=12 What can you say about P? For solving mathematically you first solve homogeneous equation P’+3P=0 and then adapt the constants For finding an explicit solution more information is needed: P(0) ! Without solving explicitly we can say something about the limiting behavior: the population will (neg.) exponentially grow to 12/3=4! How to model this in Vensim? 4/15/2017

26 Example First Order DE How to model this in Vensim?
P’+3P=12 4/15/2017

27 Diagram for population growth in a capacitated environment
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

28 Nonlinear relationship between population density and the fractional growth rate.
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

29 Phase plot for nonlinear population system
© J.S. Sterman, MIT, Business Dynamics, 2000 4/15/2017

30 Logistic growth model (Ch 9)
General case: Fractional birth and death rate are functions of ratio population P and carrying capacity C Example b(t)=aP*(1-0.25P/C) en d(t)= b*P*(1+P/C). Logistic growth is special case with: Net growth rate=g*P-g*(P/C)*P  g*P-g*P2/C Maximum growth Pinf=C/2 (differentiating over P) 4/15/2017

31 Analysis logistic model
First order non-linear model Making partial fractions 4/15/2017

32 Simulation of logistic model
Net Birth Rate= g* (1-P/C) * P 4/15/2017

33 Logistic growth in action
Figure 9-1 Top: The fractional growth rate declines linearly as population grows. Middle: The phase plot is an inverted parabola, symmetric about (P/C) = 0.5 Bottom: Population follows an S-shaped curve with inflection point at (P/C) =0.5; the net growth rate follows a bell-shaped curve with a maximum value of 0.25C per time period. 4/15/2017

34 Instruction Week 4 26-Sep 15:45-17:30 PAV B2 Vensim Tutorial
Mohammadreza Zolfagharian MSc 4/15/2017

35 Questions? 4/15/2017 PAGE 35


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