Optimisation - Using the lagrange method

In summary: The conversation is about designing a cantilever beam with 2 steps to support a given force at the end of the beam. The goal is to minimize the weight of the beam while ensuring that the stress at point A does not exceed a given value. To do this, the diameters of the two steps and the length of the smaller shoulder of the beam need to be determined. The solution involves setting up a Lagrange expression with the objective function being the volume of the beam and the constraint being the stress at point A. Taking the derivatives and solving for the variables leads to the final solution for the diameter of the smaller step. In summary, the problem involves designing a cantilever beam with 2 steps to support a given force while minimizing
  • #1
lak91
4
0

Homework Statement


The problem asks to design a cantilever beam of a minimum weight consisting of 2 steps.

Given: total length (L), Force (F) at the end of the beam and allowable stress (σ)
Need to find the diameters D and d, the length of the smaller shoulder of the beam (x).


Homework Equations


MB = F*x
MA= F*L

σB = MB/ZB = (32 * F* x)/ (pi * d^3)
σA = MA/ZA = (32 * F* L)/ (pi * d^3)

Where zA = (pi*D^3)/32 zB = (pi*D^3)/32 section modulus


So this is what I have done so far :

Solve for D = ((32*F*L)/(4*pi*(σ))^1/3
Solve for V = (pi*D^2/4)*(L-2*x) +2*(pi*d^2/4)*x = pi*D^2*x/2+ pi*d^2*x/2



Im not sure how to implement this into the lagrange expression.

I now that the volume represents the objective function and the the condition of strength at point A represents a constraint.
 
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  • #2
I think I need to set up the lagrange expression for this problem. The Attempt at a SolutionL = Length of beamF= Force at end of beamx = length of small shoulderD = diameter of large shoulderd = diameter of small shoulderObjective function: V = (pi*D^2/4)*(L-2*x) +2*(pi*d^2/4)*x Constraint: σA = (32*F*L)/(pi*D^3) =σ Lagrange Expression: L = F(V - (pi*D^2/4)*(L-2*x) +2*(pi*d^2/4)*x) + λ((32 * F * L) / (pi * D^3 ) - σ) Now I need to take the derivative with respect to D, d and x and set them equal to 0 dL/dD = -(pi*D^2/2)*(L-2*x) - (96 * F * L * λ)/ (pi * D^4) = 0ddL/dd = 2*(pi*d^2/4)*x - (96 * F * L * λ)/ (pi * D^4) = 0dL/dx = - (pi*D^2/2) + (pi*d^2/2) = 0 Solve for x = (pi*D^2/2)/(pi*d^2/2) Substitute back in the constraint equation and solve for dσA = (32 * F * L) / (pi * D^3) d = (32 * F * L) / ((4 * pi * σ)^1/3)
 

1. What is the Lagrange method?

The Lagrange method is a mathematical optimization technique used to find the maximum or minimum value of a function subject to constraints. It involves using a specific formula, known as the Lagrange multiplier, to find the optimal values of the variables.

2. How does the Lagrange method work?

The Lagrange method works by converting a constrained optimization problem into an unconstrained one. This is done by introducing a new variable, the Lagrange multiplier, and setting up a system of equations that must be satisfied for the optimal solution to be reached.

3. When is the Lagrange method used?

The Lagrange method is used when trying to optimize a function with constraints. It is particularly useful in economics, engineering, and physics, where constrained optimization problems are common.

4. What are the advantages of using the Lagrange method?

The Lagrange method offers several advantages, including its ability to handle multiple constraints and its versatility in solving both minimization and maximization problems. It also provides a systematic approach to finding solutions and can handle non-linear functions.

5. Are there any limitations to using the Lagrange method?

While the Lagrange method is a powerful tool for optimization, it does have some limitations. It can be computationally intensive, especially for problems with many constraints. It also relies on the existence of a unique solution, which may not always be the case.

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