Accelerated optimization method for low-embodied energy concrete box-girder bridge design
Fecha
Autores
Directores
Handle
https://riunet.upv.es/handle/10251/115617
Cita bibliográfica
Penadés-Plà, V.; García-Segura, T.; Yepes, V. (2019). Accelerated optimization method for low-embodied energy concrete box-girder bridge design. Engineering Structures. 179:556-565. https://doi.org/10.1016/j.engstruct.2018.11.015
Titulación
Resumen
[EN] Structural optimization is normally carried out by means of conventional heuristic optimization due to the complexity of the structural problems. However, the conventional heuristic optimization still consumes a large amount of time. The use of metamodels helps to reduce the computational cost of the optimization and, along these lines, kriging-based heuristic optimization is presented as an alternative to carry out an accelerated optimization of complex problems. In this work, conventional heuristic optimization and kriging-based heuristic optimization will be applied to reach the optimal solution of a continuous box-girder pedestrian bridge of three spans with a low embodied energy. For this purpose, different penalizations and different initial sample sizes will be studied and compared. This work shows that kriging-based heuristic optimization provides results close to those of conventional heuristic optimization using less time. For the sample size of 50, the best solution differs about 2.54% compared to the conventional heuristic optimization, and reduces the computational cost by 99.06%. Therefore, the use of a kriging model in structural design problems offers a new means of solving certain structural problems that require a very high computational cost and reduces the difficulty of other problems.
Palabras clave
Post-tensioned concrete, Structural optimization, Box-girder bridge, Metamodel, Low-embodied energy, Kriging
ISSN
0141-0296
ISBN
Fuente
Engineering Structures
DOI
10.1016/j.engstruct.2018.11.015
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Agradecimientos
The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (Project: BIA2017-85098-R).