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Mostrando ítems 1-3 de 3

Artificial neural network and Kriging surrogate model for embodied energy optimization of prestressed slab bridges

Yepes-Bellver, Lorena; Brun-Izquierdo, Alejandro; Alcalá-González, Julián; Yepes, V. (MDPI AG, 2024-10)

[EN] The main objective of this study is to assess and contrast the efficacy of distinct spatial prediction methods in a simulation aimed at optimizing the embodied energy during the construction of prestressed slab bridge ...
Dynamic data driven applications systems (DDDAS) for multidisciplinary optimisation (MDO)

Patón Pozo, Pedro José (Universitat Politècnica de València, 2020-05-04)

[ES] Nowadays, the majority of optimisation processes that are followed to obtain new optimum designs involve expensive simulations that are costly and time comsuming. Besides, designs involving aerodynamics are usually ...
Embodied Energy Optimization of Prestressed Concrete Road Flyovers by a Two-Phase Kriging Surrogate Model

Yepes-Bellver, Lorena; Brun-Izquierdo, Alejandro; Alcalá-González, Julián; Yepes, V. (MDPI AG, 2023-10)

[EN] This study aims to establish a methodology for optimizing embodied energy while constructing lightened road flyovers. A cross-sectional analysis is conducted to determine design parameters through an exhaustive ...

Mostrando ítems 1-3 de 3