# On profile reconstruction of Euler-Bernoulli beams by means of an energy based genetic algorithm

## TL;DR

This paper presents an energy-based genetic algorithm approach for reconstructing Euler-Bernoulli beam profiles from response data, effectively identifying profiles in many cases but facing challenges with similar static responses.

## Contribution

It introduces a novel energy measurement method combined with genetic algorithms for inverse profile reconstruction of beams, improving identification accuracy.

## Key findings

- Successfully identifies beam profiles in many cases
- Shows limitations when different profiles produce similar responses
- Demonstrates the effectiveness of energy-based optimization

## Abstract

This paper studies the inverse problem related to the identification of the flexural stiffness of an Euler Bernoulli beam in order to reconstruct its profile starting from available response data. The proposed identification procedure makes use of energy measurements and is based on the application of a closed form solution for the static displacements of multi-stepped beams. This solution allows to easily calculate the energy related to beams modeled with arbitrary multi-step shapes subjected to a transversal roving force, and to compare it with the correspondent data obtained through direct measurements on real beams. The optimal solution which minimizes the difference between measured and calculated data is then sought by means of genetic algorithms. In the paper several different stepped beams are investigated showing that the proposed procedure allows in many cases to identify the exact beam profile. However it is shown that in some other cases different multi-step profiles may correspond to very similar static responses, and therefore to comparable minima in the optimization problem, thus complicating the profile identification problem.

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Source: https://tomesphere.com/paper/1701.06432