{"title":"Self-Compacting Concrete Durability Assessment via Fuzzy-Logic and Bayesian Networks","authors":"Khalil Abdi, Yacine Sahraoui, Nabil Kebaili, Mourad Nahal, Mohamed Djouhri","doi":"10.1007/s40996-024-01576-6","DOIUrl":null,"url":null,"abstract":"<p>This paper presents a hybrid approach for assessing the durability of self-compacting concrete (SCC) in Algeria using Fuzzy-logic and Bayesian network (BN) methods. The methodology comprises three principal steps: Constructing a database based on expert opinions, learning the Bayesian Network (BN) structure, and using the BN for durability assessment. Focusing on the influence of uncertainties for eighty-six (86) basic events, probabilistic inference techniques combined with fuzzy set theories are used to predict SCC durability. The study classifies and evaluates the impact of critical events on SCC durability, conducting a comparative analysis between coastal and desert regions. Results indicate a significant SCC durability rate of 84.73%, highlighting influences from material defects, bad design, corrosion, poor construction sites, external forces, and cracks. These insights aid decision-makers in improving SCC structures.</p>","PeriodicalId":14550,"journal":{"name":"Iranian Journal of Science and Technology, Transactions of Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Science and Technology, Transactions of Civil Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s40996-024-01576-6","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a hybrid approach for assessing the durability of self-compacting concrete (SCC) in Algeria using Fuzzy-logic and Bayesian network (BN) methods. The methodology comprises three principal steps: Constructing a database based on expert opinions, learning the Bayesian Network (BN) structure, and using the BN for durability assessment. Focusing on the influence of uncertainties for eighty-six (86) basic events, probabilistic inference techniques combined with fuzzy set theories are used to predict SCC durability. The study classifies and evaluates the impact of critical events on SCC durability, conducting a comparative analysis between coastal and desert regions. Results indicate a significant SCC durability rate of 84.73%, highlighting influences from material defects, bad design, corrosion, poor construction sites, external forces, and cracks. These insights aid decision-makers in improving SCC structures.
期刊介绍：
The aim of the Iranian Journal of Science and Technology is to foster the growth of scientific research among Iranian engineers and scientists and to provide a medium by means of which the fruits of these researches may be brought to the attention of the world’s civil Engineering communities. This transaction focuses on all aspects of Civil Engineering
and will accept the original research contributions (previously unpublished) from all areas of established engineering disciplines. The papers may be theoretical, experimental or both. The journal publishes original papers within the broad field of civil engineering which include, but are not limited to, the following:
-Structural engineering-
Earthquake engineering-
Concrete engineering-
Construction management-
Steel structures-
Engineering mechanics-
Water resources engineering-
Hydraulic engineering-
Hydraulic structures-
Environmental engineering-
Soil mechanics-
Foundation engineering-
Geotechnical engineering-
Transportation engineering-
Surveying and geomatics.
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