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
|Title of host publication||2021 IEEE Conference on Technologies for Sustainability, SusTech 2021|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 22 Apr 2021|
|Event||8th IEEE Conference on Technologies for Sustainability, SusTech 2021 - Virtual, Online, United States|
Duration: 22 Apr 2021 → 24 Apr 2021
|Name||2021 IEEE Conference on Technologies for Sustainability, SusTech 2021|
|Conference||8th IEEE Conference on Technologies for Sustainability, SusTech 2021|
|Period||22/04/21 → 24/04/21|
Bibliographical noteFunding Information:
This work is supported by the collaboration of the Universidad Nacional de San Agust?n (UNSA) in Arequipa.
ACKNOWLEDGMENT This work is supported by the collaboration of the Universidad Nacional de San Agustín (UNSA) in Arequipa, Peru, and Purdue University in Indiana, USA, through Discovery Park's Center for the Environment (C4E).
© 2021 IEEE.
- Fuzzy Inference System
- Risk Index
- Soft Computing
- Water Pipelines