Numerical Calculus of Variations

In summary, the speaker is attempting to solve the brachistochrone problem numerically using a direct method that involves a Lagrange polynomial and a multivariate function. However, the problem arises when the denominator of the integrand becomes zero, and the speaker is struggling to find a solution when this occurs. They suggest reformulating the model to make velocity a function of acceleration instead.
  • #1
Pablo Brubeck
7
0
I attempt to solve the brachistochrone problem numerically. I am using a direct method which considers the curve ##y(x)## as a Lagrange polynomial evaluated at fixed nodes ##x_i##, and the time functional as a multivariate function of the ##y_i##. The classical statement of the problem requires the curve ##y(x)## to have its endpoints on ##(x_0, 0)## and ##(x_1, y_1)## and the initial velocity of the particle to be ##v_0=0##, so that the time functional would take the form

$$ T[y]=\int_{x_0}^{x_1} \sqrt{\frac{1+\left[\frac{dy}{dx}\right]^2}{2gy}} dx $$.

The derivative ##\frac{dy}{dx}## is approximated from the Lagrange polynomial and the integral is computed using a quadrature rule, then the functional is minimized using an interior point method. But the problem comes when the denominator of the integrand vanishes, which will always happen at the endpoint ##(x_0, 0)##. I tried to avoid this by setting ##v_0##, but the method fails to converge to a continuous curve for arbitrary small ##v_0##.

What would be the proper way to handle this situation?
 
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  • #2
Pablo Brubeck said:
What would be the proper way to handle this situation?

Intuitively, your formulation makes velocity a function of displacement, so if there is no initial displacement then there "is no reason" the particle should begin moving. You could reformulate the model so velocity depends on acceleration.
 

Related to Numerical Calculus of Variations

1. What is Numerical Calculus of Variations?

Numerical Calculus of Variations is a branch of mathematics that deals with finding the best possible solution to a problem when there are multiple variables involved. It involves using numerical methods to approximate the solution to a problem, rather than finding an exact analytical solution.

2. What are some real-world applications of Numerical Calculus of Variations?

Numerical Calculus of Variations has many practical applications in fields such as physics, engineering, economics, and optimization problems. It can be used to find the most efficient design for a structure, the optimal path for a rocket or aircraft, or the best way to allocate resources in a business.

3. What are the main techniques used in Numerical Calculus of Variations?

Some of the main techniques used in Numerical Calculus of Variations include Euler's method, Runge-Kutta methods, and finite difference methods. These methods involve breaking down a problem into smaller parts and using iterative processes to find an approximate solution.

4. How does Numerical Calculus of Variations differ from traditional Calculus of Variations?

Numerical Calculus of Variations differs from traditional Calculus of Variations in that it focuses on finding approximate solutions using numerical methods, rather than exact analytical solutions. This allows for more complex problems to be solved, as analytical solutions may not always be possible.

5. What are the advantages of using Numerical Calculus of Variations?

The main advantage of using Numerical Calculus of Variations is that it allows for the solution of complex problems that may not have an exact analytical solution. It also provides a way to check the accuracy of analytical solutions, and it can be used to solve problems with multiple variables and constraints.

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