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How to Solve These Nonlinear Equations?

08/21/2019 3:08 AM

Hi folks,

First of all, please look at the paper linked below:

https://link.springer.com/article/10.1007/s11044-005-1756-z

entitled "An Improved Elasto-Kinematic Model of the Human Forearm for Biofidelic Medical Diagnosis."

My questions are as follows:

(12 page) Between Eq.(24) and Eq.(25), there are two nonlinear equations. The paper said that those equations can be solved by a Newton-Raphson method for given input value (phi*) for the three variables "phi", "theta", and "s". To reproduce their simulation, I would set some of the parameters taken from Table.1 (17page), but how did the authors set the parameters of "c_phi" and "phi*" ? and...also how to set up the initial values (phi, theta, s) for the function solver?

Is there anyone who can explain some of details on it?

Thanks!

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#1

Re: How to solve these nonlinear equations ?

08/21/2019 4:04 AM

Surely you don't expect people to pay $40 to try and answer your question....?

Why don't you contact the authors if you have questions...

  • Andrés Kecskeméthy
  • Annelie Weinberg
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#3
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Re: How to solve these nonlinear equations ?

08/21/2019 4:12 AM
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#11
In reply to #3

Re: How to solve these nonlinear equations ?

11/29/2022 2:46 AM

couldn't haven't yet tried hard enough

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#2

Re: How to solve these nonlinear equations ?

08/21/2019 4:10 AM
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#4

Re: How to solve these nonlinear equations ?

08/21/2019 4:33 AM

They seem to be talking about the stiffness, probably arrived at by testing or modeling...

The three positions are likely the range of movement, one extreme, midpoint, other extreme...

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#5

Re: How to Solve These Nonlinear Equations?

08/21/2019 9:44 AM

The Newton-Raphson method is an iterative approximation method for finding when an equation equals zero. I believe the author of the paper took a heuristic "best guess" for the initial values and then just iterated through the process until values converged enough that the error was tolerable. I expect the author's experience in the field of interest informed the author what the range of numbers will be likely to be close.

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#8
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Re: How to Solve These Nonlinear Equations?

08/22/2019 10:10 AM

Good explanation; that confirms what I remembered from college back in the dark ages before computers. Iteration or successive approximation until the error is suitably small. You had to make a "sorta" decent initial guess in order for the method to converge.

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#9
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Re: How to Solve These Nonlinear Equations?

08/25/2019 4:32 AM

Successive approximation is not a bad method.

Some A/D converters use this method,and in certain circumstances,out performs other methods.

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#6

Re: How to Solve These Nonlinear Equations?

08/21/2019 8:36 PM

You won't get much help here without letting us in on what the equations are. It is much easier to analyze a specific example rather than every possible set of non-linear equations.

If you have two equations, you only have solutions for two variables

If each of your two (dependent) variables, say x and y, depend on a third (independent) variable, say t, you can plug in a series of values into t and plot points (x,y) for each equation, and connect these points into a curve.

The points (x,y) where the curve for equation 1 crosses the curve for equation 2 are the solutions (x,y) of both equations.

Best I can do, completely in the dark...

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#7
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Re: How to Solve These Nonlinear Equations?

08/21/2019 9:27 PM

I looked into the paper at work and the equation is a multivariate equation twelve pages deep into a medical paper. The paper is about the kinematics of the forearm in a human body but it is not really mechanical engineering. The non-linear aspect of the paper seems to be rooted in the array of trigonometric functions but since bones do not twist anywhere close to a full circle the range of initial conditions seemed limited and thus appropriate for a Newton-Raphson approximation. (I did not have time to perform a deep dive. I was at work. )

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#10

Re: How to Solve These Nonlinear Equations?

08/25/2019 4:48 AM

Make a first approximation.

Divide by 2.

Which ever value is closest, divide it by 2.

Continue with this process.

After 10 iterations you will be very close.

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