How to Solve a Nonlinear ODE with a Complex Threshold

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    Nonlinear Ode
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Discussion Overview

The discussion revolves around solving or approximating a nonlinear ordinary differential equation (ODE) of the form dy' = exp(-f(t)y) with an initial condition y(0) = y0. The function f(t) can vary in complexity, with examples provided, and the context includes both analytical and numerical approaches to finding solutions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Donifan introduces the nonlinear ODE and seeks methods for solving or approximating it.
  • Some participants suggest using successive approximations, detailing a method involving iterative integrals, while noting that convergence may depend on the behavior of f(t).
  • One participant points out that even for a simple case of f(t) = t^(3/2), the resulting functions become complex quickly.
  • There is a discussion about whether an analytical solution is necessary or if numerical integration would suffice, with some arguing that numerical methods can converge quickly.
  • Participants express confusion over the term "analytical approximation," with one clarifying it as a solution to a related problem that allows for error estimation.
  • Concerns are raised about the complexity of obtaining an analytical solution using methods like Picard iteration, with some suggesting that a look-up table could provide a faster alternative.
  • Donifan clarifies the form of f(t) as (a^2 + b t)^(3/2) - a^3, indicating that a and b are variable, and expresses a desire for a more elegant solution than numerical methods.
  • A later reply corrects a typographical error in the original equation, confirming the intended form of the ODE.

Areas of Agreement / Disagreement

Participants express differing views on the necessity and feasibility of analytical versus numerical solutions, with no consensus reached on the best approach. The discussion reflects a mix of exploratory reasoning and technical debate regarding the complexity of the problem.

Contextual Notes

Participants note the potential for complexity in analytical solutions and the dependence on the specific form of f(t). There are unresolved questions regarding the efficiency and accuracy of various proposed methods.

donifan
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A "simple" nonlinear ode

Hi
Does anyone see a way to solve/approximate this ODE?

dy'=exp(-f(t)y) with y(0)=yo

f(t) can be as simple as c*t^3/2 but it may be more complex. This came out as the solution of a very complex problem. This is the final threshold.

Thanks,

Donifan
 
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You might try using successive approximations, as follows:
[tex]y_1(t) = y0[/tex]
[tex]y_2(t) = y0 + \int_0^t e^{-f(t')y_1(t')}dt'[/tex]
[tex]y_3(t) = y0 + \int_0^t e^{-f(t')y_2(t')}dt'[/tex]
[tex]y_4(t) = y0 + \int_0^t e^{-f(t')y_3(t')}dt'[/tex]

And so on. If f(t) is well behaved, this can converge fairly quickly.
 


phyzguy said:
You might try using successive approximations, as follows:
[tex]y_1(t) = y0[/tex]
[tex]y_2(t) = y0 + \int_0^t e^{-f(t')y_1(t')}dt'[/tex]
[tex]y_3(t) = y0 + \int_0^t e^{-f(t')y_2(t')}dt'[/tex]
[tex]y_4(t) = y0 + \int_0^t e^{-f(t')y_3(t')}dt'[/tex]

And so on. If f(t) is well behaved, this can converge fairly quickly.

I believe your y0 should be [itex]y_{n-1}(t)[/itex] when writing out the equation for [itex]y_n(t)[/itex]

I assume you're doing Picard iteration?
 


Thanks for the suggestion. However even for the simple case of f=t^3/2, y_2 is already a nasty function. I'll keep trying.
 


Do you need an analytic solution, or is a numerical integration adequate? For your t^3/2 case, the successive approximations converge after 2-3 iterations if you do the integrations numerically.
 


For a numerical approximation you can typically use Runge-Kutta.
 


Sorry about the confusion. Yes, I am looking for an analytical solution/approximation. I agree the numerical solution is actually simple. Thanks!
 


You've got me confused at "analytical approximation"... what is that?

An analytical solution gets very complex in a hurry.
 


Analytical approximation would be something like a solution of a different but related problem, so the order of the error can be estimated.

I know. The analytical solution by the Picard method is pretty much impossible.

Maybe there is no solution however the equation seems so simple a compact that you almost feel there should be substitution/trick that quickly solves it, at least for f=c t^3/2.

Thanks.
 
  • #10


Can't you also estimate the error with Runge-Kutta?
How would any analytical approximation, like Picard's method I guess, be better?
 
  • #11


The answer is simple: time. An analytical approximation is faster. The solution is suppose to be part of a humongous code that cannot spare a microsecond.

P.S. When I said error, I meant from the approximated analytical solution to the actual solution.
 
  • #12


How about this: Even faster than an analytic solution is a look-up table. Given f(t), solve the equation numerically, then build a look-up table with interpolation that returns y given t. This is typically quite fast. Can this work? Is f(t) a given, or is f(t) constantly changing?
 
  • #13


The form of f(t) is

[itex]f(t) = (a^{2} +b t)^{3/2} - a^3[/itex]

a and b are constantly changing. The simplest case is a=0. In principle a look up table would work, but I was wondering if a more elegant solution can be reached.

Thanks.
 
  • #14


Just realized there is a typo (there is a d before y' that is no suppose to be there). So the whole problem is

[itex]y'=\exp[-f(t)y][/itex] with [itex]y(0)=y_0[/itex]

and

[itex]f(t) = (a^{2} +b t)^{3/2} - a^3[/itex]

Thanks.
 

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