A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Shape Optimization of Double-Arch Dams by Using Parameters Obtained Through Bayesian Estimators
Abstract The aim of this paper is to define the optimum shape of double-arch dams. This is studied here considering the shape of existing double-arch dams located in Spain. The analysis has been carried out in two consecutive stages. The first one refers to defining issues about Bayesian estimators to obtain the value for designing the optimum dam shape. In the second stage, the shape equations are iterated step-by-step. Data are taken from the inventory of Spanish existing dams. To obtain the non-available data, the Gaussian distribution under the Bayesian theorem hypotheses has been employed. This theorem converts the prior distribution using unknown parameters into the posterior distribution which provides expected parameters, i.e. the Bayesian estimators. The main challenge of the analysis is to identify the parameters which define the optimum shape of an existing dam. For this, over 30 dams have been selected and over 700 data have been collected. One of the main practical implications of this research comprises a reduction of the concrete volume, which implies a reduction of the financial costs and the environmental impact.
Shape Optimization of Double-Arch Dams by Using Parameters Obtained Through Bayesian Estimators
Abstract The aim of this paper is to define the optimum shape of double-arch dams. This is studied here considering the shape of existing double-arch dams located in Spain. The analysis has been carried out in two consecutive stages. The first one refers to defining issues about Bayesian estimators to obtain the value for designing the optimum dam shape. In the second stage, the shape equations are iterated step-by-step. Data are taken from the inventory of Spanish existing dams. To obtain the non-available data, the Gaussian distribution under the Bayesian theorem hypotheses has been employed. This theorem converts the prior distribution using unknown parameters into the posterior distribution which provides expected parameters, i.e. the Bayesian estimators. The main challenge of the analysis is to identify the parameters which define the optimum shape of an existing dam. For this, over 30 dams have been selected and over 700 data have been collected. One of the main practical implications of this research comprises a reduction of the concrete volume, which implies a reduction of the financial costs and the environmental impact.
Shape Optimization of Double-Arch Dams by Using Parameters Obtained Through Bayesian Estimators
Zacchei, Enrico (author) / Molina, José Luis (author)
2018-12-18
14 pages
Article (Journal)
Electronic Resource
English
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