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Content. Introduction to ChaosExamples of ChaosExperimental
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1. Is it all about Chaos?MATH 6514: Industrial Mathematics IFinal Project Presentation Manas Bajaj (ME)
Qingguo Zhang (AE)
Sripathi Mohan (AE)
Thao Tran (AE)
2. Content Introduction to Chaos
Examples of Chaos
Experimental & Numerical Results
Double Pendulum
Magnetic Pendulum
Vibrating String
Swinging Spring
Conclusion
The Road Ahead
Questions?
3. Deterministic theory Advocated by Newton
Example : Laws of Motion
The exact behavior of any dynamical system can be simulated and accurate predictions can be made about the behavior of a dynamical system at a future point in time with the given initial conditions
The dynamical system could be anything from the planets in the solar system to ocean currents.
Real World problems?
How accurate can one be with measuring the initial conditions of systems like the heavenly bodies and ocean currents? ? Can never achieve infinite accuracy
Erroneous notion amongst the faculty of scientists. (“Shrink-Shrink” assumption)
Almost same Initial Conditions ?Almost same behavioral prediction?
4. Loopholes in the beliefAssumptions taken for granted with the deterministic theory Chaos is a challenge to the “Shrink-Shrink” assumption
Henri Poincare´ challenged this (1900)
The predictions can be grossly different for systems like Planets since an accurate measurement of the initial conditions is not possible.
The world didn’t realize the problems yet.
Edward Lorenz’s weather prediction model (1960)
12 equations. Starts a simulation run from somewhere in the middle to check a solution pattern : Enters the value with less precision (0.506 Vs 0.506127)
“Butterfly Effect”
5. What is CHAOS? Chaos is a behavior exhibited by systems that are highly sensitive to Initial Conditions.
Under certain system characteristics, one can witness the “Chaotic Regime”
The behavior of a dynamical system in the “chaotic regime” can be completely different with the slightest change in the initial conditions.
Irregular and highly complex behavior in time that follows deterministic equations. Predictions can be made about the spectrum. (Differs from “randomness”) - Roulette wheel
This phenomenon is known as “Chaos”
6. Examples of CHAOS
7. Examples of CHAOS (cont.)
8. Examples of CHAOS (cont.)- Mathematical Model - Bifurcation diagram Solving:
y = x2 + c (1)
y = x (2)
Studying the behavior for different values of “c”
Convergence with different values of ‘”c”
9. Double Pendulum
10. Governing Equations
11. 1st Initial Condition 1st Trial: ?1 & ?2 vs. Time
12. 1st Initial Condition 2nd Trial: ?1 & ?2 vs. Time
13. 2nd Initial Condition 1st Trial: ?1 & ?2 vs. Time
14. 2nd Initial Condition 2nd Trial: ?1 & ?2 vs. Time
15. Discussion Two sets of initial conditions, different results for each trial within each set. ?
Chaotic behavior
Cannot sustain a-periodic motion due to high damping effects.
Experimental setup challenges
Pendulum has to be constrained in 2-D
Plane of motion of Pendulum has to be on two different planes (parallel)
16. Magnetic Pendulum
17. Governing Equations
18. 1st Trial: Trajectory of PendulumNumerical Solution
19. 2nd Trial: Trajectory of PendulumNumerical Solution
20. 3rd Trial: Trajectory of PendulumNumerical Solution
21. 1st Trial: Trajectory of PendulumExperimental Solution
22. 2nd Trial: Trajectory of PendulumExperimental Solution
23. 3rd Trial: Trajectory of PendulumExperimental Solution
24. Discussion Experimental and Numerical simulations demonstrate that the system is highly sensitive to initial condition
Hence the system is chaotic
No experimental setup challenges as such ?
25. Vibrating StringExperimental Setup
26. Discussion Unable to capture the chaotic regime of the system. ?
The motion of the string is periodic
Limitation on the amplitude of the voltage
Restriction on the amplitude of the vibrating wire
Point light source use to magnify the motion of wire (on a backdrop)
27. Swinging Spring
28. Discussion No mathematical model available for chaotic regime ?
Experimentally, spring tends to follow different trajectories when started with similar initial conditions
Experimental challenge
Lack of freedom to bounce above the plane of suspension (due to suspension point)
Limitation on measuring the amplitude of spring
zoom restriction due to the lack of a “real grid” (we were using graph sheets)
29. Conclusion
Chaos
unstable dynamical system - approaches it in a very regular manner
sensitivity to the initial conditions
Double Pendulum
Sensitivity to initial conditions demonstrated
A-periodic motion of pendulums
System can extend to “n” pendulums
Magnetic Pendulum
Show system sensitivity to initial condition
30. The Road Ahead Double Pendulum
Develop better fixture to reduce damping factor on system
Induce forcing function to system
Magnetic Pendulum
Solve for the system with attracting and repelling underlying magnets
Vibrating String
Stronger electromagnet
Function generator with higher voltage output
Swinging Spring
Better experimental fixture
Can bounce above the plane of fixture
31. Questions?