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How much complexity is too much? “you should try to make things as simple as possible, but not too simple” A. Einstein “All modeling is a gross simplification.

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Presentation on theme: "How much complexity is too much? “you should try to make things as simple as possible, but not too simple” A. Einstein “All modeling is a gross simplification."— Presentation transcript:

1 How much complexity is too much? “you should try to make things as simple as possible, but not too simple” A. Einstein “All modeling is a gross simplification of the real system.” G. Whelan “Don’t work any harder than you have to.” K. Castleton

2 Talking Points Who is Karl Castleton and “What does he do?” The ADVECTIVE, DISPERSIVE, and DECAY equation. Intuition about the system Intuition about the equation Semi-Analytical techniques Numerical techniques Conclusions

3 Who is Karl Castleton Mesa State Graduate: A.A.S. 1987, B.S. 1992 Computer Science and Mathematics Washington State University: M.S. Computer Science 1997 Works at Pacific Northwest National Laboratory Master Project solved the advective, dispersive, decay equation by three different methods

4 The “Equation” Used in Civil Engineering, Environmental, Pharmaceutical, System Biological modeling Is a partial differential equation A number of analytical solutions for simplified cases Flow, spreading, and degrading

5 Intuition about the system C Dz Dx Ux Uy

6 Intuition about the equation Plug flow Spreading in three dimensions Degradation, decay within the cell Simplification can yield analytical results

7 Semi-Analytical Techniques Take the mathematics as far as it can go and then use a computer to put you over the top. Reduce the model to a system that has an analytical result for instantaneous release. Convolute the instantaneous release with input forcing function.

8 Numerical Techniques Just implement the equation “Easy” to implement Code can be very close to equation Can consume a lot of computer resources Does allow for a variety of values

9 Conclusion There are many ways to solve a modeling question Use no more or less than you need Do not always use the same tool/technique Do not work any harder than you have to.


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