Using nonlinear programming for solving mechanical engineering problems: Designing a two-bar bracket

In my previous blog posts I demonstrated how to use nonlinear programming in R for solving an optimization problem. To be more specific, I used the Augmented Lagrange Multiplier (ALM) method for solving a specific engineering optimization problem.

In this blog post I will again employ the ALM method for solving an engineering optimization problem. This time I will analyze a two-bar bracket design subjected to a load. The goal of this optimization problem is to find the minimal mass of the design so that the bracket will support the load without structural failure.

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Using nonlinear programming for solving mechanical engineering problems: Designing a column subjected to a buckling load

Nonlinear programming is used for solving optimization problems. The goal of such optimization problems is to minimize (or maximize) some objective function. However, these optimization problems often specify a number of constraints. Nonlinear programming is applied when the objective function or some of the specified constraints are nonlinear.

The following R code demonstrates how to solve an optimization problem using nonlinear programming. More specifically, the R code uses the Augmented Lagrange Multiplier (ALM) method for finding the minimum design weight of a circular thin walled column subjected to a buckling load.

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