How Does Changing Boundary Conditions Affect Nonlinear Shooting Methods in BVPs?

  • Thread starter radiogaga35
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In summary, The nonlinear shooting method can be used to solve a boundary value problem with the given conditions. A bisection algorithm or Newton's method can be implemented for this purpose. If the boundary conditions change to include the slope at one end, a 2nd order IVP can still be used, but with the initial slope fixed and the initial value varied to achieve the second condition. This can also be solved using a bisection algorithm or an adapted Newton's method. Further research may be needed to fully understand the theoretical implications of this approach.
  • #1
radiogaga35
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Given the boundary value problem (primes denote differentiation w.r.t x):
[tex]\begin{array}{l}
y'' = f(x,y,y') \\
y(a) = \alpha \\
y(b) = \beta \\
\end{array}[/tex]

the nonlinear shooting method may be implemented to solve the problem. A bisection algorithm may be used or, with a little more effort, Newton's method may be implemented (in which case one solves a fourth order, and not a second order, IVP - http://www.math.utah.edu/~pa/6620/shoot.pdf" ).

But what happens if the form of the boundary conditions changes to:
[tex]\begin{array}{l}
y'(a) = \alpha \\
y(b) = \beta \\
\end{array}[/tex]

Is one still justified in reducing the BVP to a 2nd order IVP, but this time with initial SLOPE fixed at [tex]y'(a) = \alpha [/tex] and then trying different values of [tex]y(a)[/tex] in order to achieve the condition [tex]y(b) = \beta [/tex]? (As opposed to varying initial slope to achieve second condition).

Furthermore, if this will indeed work, then a bisection method should be easy to implement, but what about adapting Newton's method for this case? Can anyone point me to an appropriate reference that discusses this matter?

Thank you! :-)
 
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  • #2
Ok, I applied the aforementioned approach (with appropriately-adapted Newton-method implementation) to a trial problem and it worked perfectly.

In principle it seems like a sensible enough approach, but I'm not very clued up on BVP methods, so I'm not sure if there is any theoretical reason to avoid this approach? I.e. varying the initial "displacement" instead of slope. Certainly I've only ever seen the initial slope being varied in simple, single shooting methods
 

Related to How Does Changing Boundary Conditions Affect Nonlinear Shooting Methods in BVPs?

What is nonlinear shooting for boundary value problems (BVPs)?

Nonlinear shooting for boundary value problems is a numerical method used to solve differential equations with boundary conditions. It involves converting the differential equations into a system of first-order equations, and then using an iterative process to find the solution that satisfies the boundary conditions.

How does nonlinear shooting differ from other methods for solving BVPs?

Nonlinear shooting differs from other methods for solving BVPs, such as finite difference or finite element methods, in that it does not require the problem to be discretized into a system of algebraic equations. Instead, it directly solves the differential equations with the boundary conditions using an iterative approach.

What types of BVPs can be solved using nonlinear shooting?

Nonlinear shooting can be used to solve a wide range of BVPs, including nonlinear, time-dependent, and higher-order differential equations. It is particularly useful for BVPs that cannot be easily solved using other numerical methods, such as those with complex boundary conditions or singularities.

What are the advantages of using nonlinear shooting for BVPs?

One of the main advantages of nonlinear shooting is its versatility, as it can be applied to a wide range of BVPs. It also does not require the problem to be discretized, which can save time and computational resources. Additionally, it can handle complex boundary conditions and singularities more easily than other methods.

Are there any limitations to using nonlinear shooting for BVPs?

While nonlinear shooting is a powerful method for solving BVPs, it does have some limitations. It may not be as efficient as other methods for certain types of problems, such as those with smooth solutions. It also requires an initial guess for the solution, which may be difficult to obtain for some problems.

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