3D Modeling of Pipe Risk Index for a Sustainable Urban Water System

Thikra Dawood, Emad Elwakil, Hector Mayol Novoa, Jose Fernando Garate Delgado

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The risk assessment and modeling of watermains are complicated tasks, which are proportional to the intricacy of underground water networks. These networks are known to be nonlinear, dynamic, and involve a multitude of influential factors that cannot be measured accurately in any conventional metrics. In general, deterioration factors obtained from field inspections reports or from experts' survey have certain degrees of ambiguity and subjectivity. One of the potent methods that have emerged in the last four decades to solve civil infrastructure problems, is the fuzzy inference system (FIS). This method can encode the deterioration factors into risk indices while coping with the inaccuracy, ambiguity, and fuzziness of data. The objective of this paper is to develop a risk index model for water transmission pipes based on simulation and FIS. First, the input and output datasets of the proposed model are defined based on inspection reports and experts' questionnaire; both the input and output datasets are fed into the FIS engine. Second, the fuzzy logic control engine is designed by defining the membership functions and the rules in the fuzzy operator. The third step includes

Idioma originalInglés
Título de la publicación alojada2021 IEEE Conference on Technologies for Sustainability, SusTech 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9780738124445
DOI
EstadoPublicada - 22 abr. 2021
Evento8th IEEE Conference on Technologies for Sustainability, SusTech 2021 - Virtual, Online, Estados Unidos
Duración: 22 abr. 202124 abr. 2021

Serie de la publicación

Nombre2021 IEEE Conference on Technologies for Sustainability, SusTech 2021

Conferencia

Conferencia8th IEEE Conference on Technologies for Sustainability, SusTech 2021
País/TerritorioEstados Unidos
CiudadVirtual, Online
Período22/04/2124/04/21

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Publisher Copyright:
© 2021 IEEE.

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