Título

Woody debris trapping phenomena evaluation in bridge piers: A Bayesian perspective

Autor

Luis Horacio Martínez Martínez

DAVID JOAQUIN DELGADO HERNANDEZ

DAVID DE LEON ESCOBEDO

Jhonnatan Flores Gomora

JUAN CARLOS ARTEAGA ARCOS

Nivel de Acceso

Acceso Abierto

Licencia

http://creativecommons.org/licenses/by-nc-nd/4.0

Materias

Bayesian Net - ([0951-8320]) Bridge - ([0951-8320]) Damage - ([0951-8320]) Pier - ([0951-8320]) Scour - ([0951-8320]) Model - ([0951-8320]) Non-parametric - ([0951-8320]) Overturning - ([0951-8320]) BIOLOGÍA Y QUÍMICA - (CTI)

Resumen o descripción

l artículo propone el uso de una red bayesiana y analiza sus ventajas y desventajas para realizar el diagnóstico y la propuesta de remediación en el caso de puentes sujetos a la acumulación de escombros de madera en la base de las pilas.

A flood occurs when water and other materials such as woody debris overflow dry areas. If there is infrastructure present, woody fragments could be transported downstream and eventually trapped, leading to increments in the hydrodynamic forces over, say, a bridge. Moreover, local scour can be developed in the structure piers. The purpose of this research is to investigate the bridge pier scour phenomena induced by woody debris from a probabilistic point of view. A Non Parametric Bayesian Belief Network comprising seven nodes has consequently been developed. They are: water level, Froude number, blockage amount, drag force, scour depth, damage and overturning. Through both Monte Carlo Simulation and data from a real structure, the nodes’ non parametric probability distributions have been established, an area that has, to date, received very little attention in the literature. By combining the variables under study, it was possible to determine their interaction and dependencies, showing that the depth of the approaching flow is correlated with two nodes: damage and overturning. The results are useful for bridge managers willing to rank investments in maintenance actions within the industry, and to develop optimal risk based strategies for efficiently employing the scarce resources used to that end.

Editor

Elsevier

Fecha de publicación

21 de enero de 2017

Tipo de publicación

Artículo

Recurso de información

http://hdl.handle.net/20.500.11799/65128

Fuente

0951-8320

Idioma

Inglés

Relación

http://dx.doi.org/10.1016/j.ress.2017.01.005;

Audiencia

Estudiantes

Investigadores

Repositorio Orígen

REPOSITORIO INSTITUCIONAL DE LA UAEM

Descargas

326