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== Abstract ==
 
== Abstract ==
  
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El problema de optimización topológica es encontrar la mejor forma de una estructura mecánica sujeta a ciertas condiciones de servicio. Partiendo de una estructura inicial, se pueden agregar y quitar partes, modificar contornos, y dimensiones. En el presente trabajo se aborda el problema de optimización topológica utilizando un Algoritmo de Estimación de Distribución (AED) que utiliza una red bayesiana. La forma de trabajo del algoritmo es la siguiente: propone un conjunto de soluciones (población de estructuras) generadas por el muestreo de cierta distribución de probabilidad, estas son evaluadas para conocer su valor de función objetivo y restricciones. Las estructuras que tienen un mejor desempeño de acuerdo a su evaluación son seleccionadas para recalcular la distribución de probabilidad, con la cual será generada una nueva población. De esta forma se espera generar en cada iteración mejores estructuras. El objetivo a minimizar es el peso de la estructura, las restricciones son el máximo esfuerzo Von Mises, el desplazamiento en los nodos con carga, el desplazamiento máximo en cualquier nodo, y condiciones prácticas y estéticas de la estructura como: el tamaño de los agujeros presentes y la conectividad de sus piezas. La evaluación se realiza utilizando primordialmente el Método del Elemento finito. Los resultados obtenidos muestran la capacidad de la propuesta de proveer soluciones factibles de bajo costo. Summary The topological optimization problema is stated as follows: to find the best shape of a mechanical structure subject to certain service conditions. Usually, the topological optimization problem is tackled by starting from an initial structure which is modified by adding parts, generating gaps, modifying dimensions or the shape contour. This work presents a novel proposal on topological optimization which uses an Estimation of Distribution Algorithm (EDA) based on a Bayesian network. The EDA works as follows: propose a set of candidate solutions (population),the candidate solutions are generated according to a probability distribution, the population is evaluated on the objective function and contraints, and finally, the best structures are selected and used to recomputed the search distribution, and so on. The objective function is the structure weight, and the constraints are maximum Von Mises Stress,the node displacement and practical conditions such as connectivity of all the parts of the structure. The results show that the proposal is capable of designing low weight structures which fulfill the service conditions.
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The topological optimization problema is stated as follows: to find the best shape of a mechanical structure subject to certain service conditions. Usually, the topological optimization problem is tackled by starting from an initial structure which is modified by adding parts, generating gaps, modifying dimensions or the shape contour. This work presents a novel proposal on topological optimization which uses an Estimation of Distribution Algorithm (EDA) based on a Bayesian network. The EDA works as follows: propose a set of candidate solutions (population),the candidate solutions are generated according to a probability distribution, the population is evaluated on the objective function and contraints, and finally, the best structures are selected and used to recomputed the search distribution, and so on. The objective function is the structure weight, and the constraints are maximum Von Mises Stress,the node displacement and practical conditions such as connectivity of all the parts of the structure. The results show that the proposal is capable of designing low weight structures which fulfill the service conditions.
  
 
== Full document ==
 
== Full document ==
 
<pdf>Media:draft_Content_922291762RR263G.pdf</pdf>
 
<pdf>Media:draft_Content_922291762RR263G.pdf</pdf>

Latest revision as of 10:57, 14 June 2017

Abstract

The topological optimization problema is stated as follows: to find the best shape of a mechanical structure subject to certain service conditions. Usually, the topological optimization problem is tackled by starting from an initial structure which is modified by adding parts, generating gaps, modifying dimensions or the shape contour. This work presents a novel proposal on topological optimization which uses an Estimation of Distribution Algorithm (EDA) based on a Bayesian network. The EDA works as follows: propose a set of candidate solutions (population),the candidate solutions are generated according to a probability distribution, the population is evaluated on the objective function and contraints, and finally, the best structures are selected and used to recomputed the search distribution, and so on. The objective function is the structure weight, and the constraints are maximum Von Mises Stress,the node displacement and practical conditions such as connectivity of all the parts of the structure. The results show that the proposal is capable of designing low weight structures which fulfill the service conditions.

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Published on 01/07/10
Accepted on 01/07/10
Submitted on 01/07/10

Volume 26, Issue 3, 2010
Licence: CC BY-NC-SA license

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