Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Optimization of Geometric Parameters for Double-Arch Dams through Bayesian Implementation
This paper comprises the search of the optimal geometric parameters (area and volume) for double-arch dams. The approach is structured in several consecutive stages. The process begins with a definition of the problem about Bayesian estimators, to define the dam-shape design values. After that, an iterative sequence of equations calculation was developed until reaching a solution that satisfies the a priori established constraints. A modeling of the optimized dam has been carried out to estimate static and dynamic internal stresses. Data were retrieved from inventories of existing dams, whereas to obtain the unknown data, a Gaussian distribution under hypotheses of the Bayes’ theorem has been employed. This theorem converts the a priori distribution, through unknown parameters, into the a posteriori distribution providing expected estimators. The design of the dam shape is strongly based on the experience, therefore by collecting real information about existing dams a more accurate analysis is possible.
Optimization of Geometric Parameters for Double-Arch Dams through Bayesian Implementation
This paper comprises the search of the optimal geometric parameters (area and volume) for double-arch dams. The approach is structured in several consecutive stages. The process begins with a definition of the problem about Bayesian estimators, to define the dam-shape design values. After that, an iterative sequence of equations calculation was developed until reaching a solution that satisfies the a priori established constraints. A modeling of the optimized dam has been carried out to estimate static and dynamic internal stresses. Data were retrieved from inventories of existing dams, whereas to obtain the unknown data, a Gaussian distribution under hypotheses of the Bayes’ theorem has been employed. This theorem converts the a priori distribution, through unknown parameters, into the a posteriori distribution providing expected estimators. The design of the dam shape is strongly based on the experience, therefore by collecting real information about existing dams a more accurate analysis is possible.
Optimization of Geometric Parameters for Double-Arch Dams through Bayesian Implementation
Zacchei, Enrico (Autor:in) / Molina, José Luis (Autor:in)
21.09.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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