Optimizing Cylinder Dimensions for Material Buckling: Calculus Approach?

In summary, the student is trying to find the ratio of height to diameter of a cylinder that produces the minimum material buckling (B_m)^2. However, they are not able to find a solution using the given problem statement. They have attempted to solve the problem by varying the ratio of height to diameter, but this does not seem to produce a minimum material buckling.
  • #1
sippyCUP
6
0

Homework Statement


This isn't that hard but I cannot remember a nice Calculus way of doing it. I'm trying to find the ratio of height to diameter of a cylinder that produces the minimum material buckling (B_m)^2. The problem statement my professor provided states that the minimum is found at H/D=0.924, but my attempt at substitution has shown otherwise.

Homework Equations


The formula for material buckling of a cylinder is (B_g)^2 = (2.405/r)^2 + (pi/h)^2 which I have simplified to (B_g)^2 = 4[(2.405/d)^2 + (3.1416/2h)^2] .


The Attempt at a Solution


I ran a spreadsheet (attached) which varies the ratio H/D from 0.1 to 1.0. Material buckling decreased even beyond H/D=0.924. I fired up Maple but am not that competent with it so I got nowhere. If anyone has any ideas I would be much obliged.

Thanks!
 
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  • #2
sippyCUP said:
I'm trying to find the ratio of height to diameter of a cylinder that produces the minimum material buckling (B_m)^2.

The formula for material buckling of a cylinder is (B_g)^2 = (2.405/r)^2 + (pi/h)^2 which I have simplified to (B_g)^2 = 4[(2.405/d)^2 + (3.1416/2h)^2] .

Hi sippyCUP! :smile:

I don't get it … :confused:

You're trying to minimise a/D² + b/h² …

but what are you fixing? constant D? constant h? constant volume?
 
  • #3
Hey tiny-tim,

Both h and d are free to vary... but only the ratio of them matters for the final answer. I'm trying to prove that h/d=0.924 produces the smallest (B_g)^2.

I ran a spreadsheet with d=10 constant and h varying from 1 to 10. This varied h/d from 0.1 to 1. However, the quantity (B_g)^2 decreased the entire time. If h/d=0.924 for minimum (B_g)^2, I should expect it to produce a minimum (B_g)^2 at h=9.24 and d=10.

Obviously the formula does not hold d and h in ratio form. Therefore, I could try changing h to a different value and playing the same game.

EDIT: Having looked at the formula again, I realize this won't help since d and h are the denominators of fractions that will decrease as (d,h) ----> infinity. So I don't really see how the minimum can even occur.
 
Last edited:

Related to Optimizing Cylinder Dimensions for Material Buckling: Calculus Approach?

What is a basic optimization problem?

A basic optimization problem is a mathematical or computational problem that involves finding the best possible solution given a set of constraints. This can be in the form of maximizing or minimizing a certain variable, while also considering any limitations or restrictions.

What is the difference between linear and nonlinear optimization?

Linear optimization problems involve a linear objective function and linear constraints, while nonlinear optimization problems involve a nonlinear objective function and may have nonlinear constraints. This means that linear optimization problems have a more straightforward and predictable solution, while nonlinear problems may require more complex methods to find the optimal solution.

How is an optimization problem solved?

Optimization problems are typically solved using mathematical or computational methods. These can include analytical solutions, where the optimal solution can be found using mathematical equations, or numerical solutions, where algorithms are used to find the best possible solution given a set of constraints.

What are some real-life applications of optimization problems?

Optimization problems are used in a wide variety of fields, including engineering, economics, finance, and logistics. Some examples of real-life applications include finding the most efficient route for a delivery truck, maximizing profits for a business, and optimizing the design of a bridge or building.

What are some common techniques used to solve optimization problems?

Some common techniques used to solve optimization problems include linear programming, quadratic programming, genetic algorithms, and gradient descent. Each technique has its own advantages and limitations, and the best approach will depend on the specific problem at hand.

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