"Optimal design" in Civil Engineering framework is often a word that is used improperly. The lack of definition of an objective function depending on a design variable set, prevents the achievement of a real optimal solution. In practise, an admissible solution becomes the starting point for a "so called" optimization process, even if it only connects mainly with technological aspects. In the literature, several approaches are presented, but they are often focused on the algorithm sacrifying the design effectiveness of results. A careful analysis of the literature shows very few examples of an efficient process for Civil Engineering applications. Even in Precast Industry the choice of a design solution is carried out on experience-based criteria; at most the "best" optimization is performed by comparing a limited set of admissible solutions. In this paper an effective "computer aided optimal design" is suggested. The main idea is to conserve the same approach used by Civil Engineers, but an objective function is first introduced in order to search for an optimal solution throughout the adoption of a suitable algorithm. The proposed method is here applied to two precast structural elements (a column and a pocket foundation), even if it could be better applied to a more complex structural system. A SQP (Sequential Quadratic Programming) algorithm is used: it is regarded as one of the most powerful direct search methods, although it requires a set of starting points in order to find the optimal solution. In the proposed applications the inequalities imposed by Ultimate Limit State design are regarded as constraints. The objective function is the global cost and the final solution takes into account the discretization required by current commercial availabilities. As expected in these cases, the optimal process does not lead to impressive results, although in other applications more significant performances could be expected.

On the optimal design of precast structural elements: a proposal

DI PRISCO, MARCO;MAURI, MASSIMILIANO;SCOLA, MARCELLO
2003-01-01

Abstract

"Optimal design" in Civil Engineering framework is often a word that is used improperly. The lack of definition of an objective function depending on a design variable set, prevents the achievement of a real optimal solution. In practise, an admissible solution becomes the starting point for a "so called" optimization process, even if it only connects mainly with technological aspects. In the literature, several approaches are presented, but they are often focused on the algorithm sacrifying the design effectiveness of results. A careful analysis of the literature shows very few examples of an efficient process for Civil Engineering applications. Even in Precast Industry the choice of a design solution is carried out on experience-based criteria; at most the "best" optimization is performed by comparing a limited set of admissible solutions. In this paper an effective "computer aided optimal design" is suggested. The main idea is to conserve the same approach used by Civil Engineers, but an objective function is first introduced in order to search for an optimal solution throughout the adoption of a suitable algorithm. The proposed method is here applied to two precast structural elements (a column and a pocket foundation), even if it could be better applied to a more complex structural system. A SQP (Sequential Quadratic Programming) algorithm is used: it is regarded as one of the most powerful direct search methods, although it requires a set of starting points in order to find the optimal solution. In the proposed applications the inequalities imposed by Ultimate Limit State design are regarded as constraints. The objective function is the global cost and the final solution takes into account the discretization required by current commercial availabilities. As expected in these cases, the optimal process does not lead to impressive results, although in other applications more significant performances could be expected.
2003
Studies e Research V. 24
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/515741
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