Variational Calculus to minimize distance on a generalize 3D surface

In summary, variational calculus is a mathematical method used to find the optimal solution to a problem by minimizing a specific functional. It is applied in various fields to minimize distance on 3D surfaces by defining a functional and using the Euler-Lagrange equation to find the optimal path or function. A generalized 3D surface is a surface described by a mathematical function and can be represented in three dimensions. Variational calculus can be used to minimize distance on any type of 3D surface, with the complexity of the functional and resulting differential equation varying depending on the surface's shape. The practical applications of using variational calculus to minimize distance on a generalized 3D surface are diverse and include fields such as physics, engineering, computer graphics,
  • #1
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Homework Statement



A mountain is modeled by z=f(x,y) which is a known function.

a) What are the differential equations for x(t) and y(t) that minimize the distance between 2 points.

b) If
[tex] z=f(x,y)=(\sin^2 2\pi x)(\sin^2 2\pi y)[/tex]
Solve the equations.

Homework Equations



The euler-lagrange equation.

The Attempt at a Solution



We have [tex]dz=dx\frac{dz}{dx}+dy\frac{dz}{dy}[/tex] so: [tex]ds=\sqrt{dx^2+dy^2+dz^2}[/tex]
Using t as a parametrization we have
[tex]ds=\sqrt{\dot{x}^2+\dot{y}^2+\dot{z}^2}dt=L(x,y, \dot{x},\dot{y},t)dt[/tex]
then the differential equations for x(t) and y(t) are obtained by:
[tex]\frac{\delta L}{\delta x}=0[/tex]
[tex]\frac{\delta L}{\delta y}=0[/tex]
However when trying to solve the equation I run into really long expressions that seem to be analyticall unsolvable. I think I'm missing a simple trick that needs to be used. A hint given is to note that the problem is symmetric under the exchange of x and y.

This is from hand and finch analytical mechanics Chapter 2 problem 11.
 
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  • #2


Dear student,

Thank you for your post. Solving this problem requires a few steps.

a) To minimize the distance between two points, we need to minimize the length of the curve connecting those two points. This can be done by minimizing the action functional:

S=\int_{t_1}^{t_2} L(x,y,\dot{x},\dot{y},t)dt

where L is the Lagrangian defined as:

L=\sqrt{\dot{x}^2+\dot{y}^2+\dot{z}^2}

To minimize this functional, we need to solve the Euler-Lagrange equations:

\frac{d}{dt}\left(\frac{\partial L}{\partial \dot{x}}\right)-\frac{\partial L}{\partial x}=0

\frac{d}{dt}\left(\frac{\partial L}{\partial \dot{y}}\right)-\frac{\partial L}{\partial y}=0

In this case, the Lagrangian is independent of t, so the Euler-Lagrange equations reduce to:

\frac{\partial L}{\partial \dot{x}}=constant

\frac{\partial L}{\partial \dot{y}}=constant

b) To solve these equations, we need to substitute the given function z=f(x,y) into the Lagrangian and then use the symmetry property noted in the hint. This will simplify the equations and make them easier to solve. The solution will involve the use of elliptic integrals.

I hope this helps. Let me know if you need further clarification.
 

1. What is variational calculus?

Variational calculus is a branch of mathematics that deals with finding the optimal solution to a problem by minimizing a specific functional. In simpler terms, it involves finding the path or function that minimizes a certain quantity, such as distance or energy.

2. How is variational calculus applied to minimize distance on a 3D surface?

In order to minimize distance on a 3D surface using variational calculus, we must first define a functional that represents the distance between two points on the surface. This functional is then minimized using the Euler-Lagrange equation, which results in a differential equation that can be solved to find the optimal path or function.

3. What is a generalized 3D surface?

A generalized 3D surface is a surface that can be described using a mathematical function and can be represented in three dimensions. Examples of generalized 3D surfaces include spheres, cylinders, cones, and tori.

4. Can variational calculus be used to minimize distance on any type of 3D surface?

Yes, variational calculus can be applied to minimize distance on any type of 3D surface that can be described by a mathematical function. However, the complexity of the functional and the resulting differential equation may vary depending on the surface's shape and properties.

5. What are the practical applications of using variational calculus to minimize distance on a generalized 3D surface?

The applications of using variational calculus to minimize distance on a 3D surface are numerous and diverse. It can be used in fields such as physics, engineering, and computer graphics to optimize paths, trajectories, and shapes. It is also commonly used in the study of surfaces and their properties in mathematics.

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