Cargando…

Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method

Concrete is the most consumed material in the construction industry. Using recycled aggregates (RA) and silica fume (SF) in concrete and mortar could preserve natural aggregates (NA) and reduce CO(2) emissions and construction and demolition waste (C&DW) generation. Optimizing the mixture design...

Descripción completa

Detalles Bibliográficos
Autores principales: Bamshad, Omid, Mahdikhani, Mahdi, Ramezanianpour, Amir Mohammad, Maleki, Zahra, Majlesi, Arsalan, Habibi, Alireza, Delavar, Mohammad Aghajani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248084/
https://www.ncbi.nlm.nih.gov/pubmed/37303530
http://dx.doi.org/10.1016/j.heliyon.2023.e16381
_version_ 1785055295187189760
author Bamshad, Omid
Mahdikhani, Mahdi
Ramezanianpour, Amir Mohammad
Maleki, Zahra
Majlesi, Arsalan
Habibi, Alireza
Delavar, Mohammad Aghajani
author_facet Bamshad, Omid
Mahdikhani, Mahdi
Ramezanianpour, Amir Mohammad
Maleki, Zahra
Majlesi, Arsalan
Habibi, Alireza
Delavar, Mohammad Aghajani
author_sort Bamshad, Omid
collection PubMed
description Concrete is the most consumed material in the construction industry. Using recycled aggregates (RA) and silica fume (SF) in concrete and mortar could preserve natural aggregates (NA) and reduce CO(2) emissions and construction and demolition waste (C&DW) generation. Optimizing the mixture design based on both fresh and hardened properties of recycled self-consolidating mortar (RSCM) has not been performed. In this study, multi-objective optimization of mechanical properties and workability of RSCM containing SF was performed via Taguchi Design Method (TDM) with four main variables including cement content, W/C ratio, SF content and superplasticizer content at three different levels. SF was used to decrease the environmental pollution caused by cement production as well as compensating the negative effect of RA on the mechanical properties of RSCM. The results revealed that TDM could appropriately predict the workability and compressive strength of RSCM. Also, mixture design containing W/C = 0.39, SF = 6%, cement = 750 kg/m(3) and SP = 0.33% was found as the optimum mixture having the highest compressive strength and acceptable workability as well as low cost and environmental concerns.
format Online
Article
Text
id pubmed-10248084
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-102480842023-06-09 Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method Bamshad, Omid Mahdikhani, Mahdi Ramezanianpour, Amir Mohammad Maleki, Zahra Majlesi, Arsalan Habibi, Alireza Delavar, Mohammad Aghajani Heliyon Research Article Concrete is the most consumed material in the construction industry. Using recycled aggregates (RA) and silica fume (SF) in concrete and mortar could preserve natural aggregates (NA) and reduce CO(2) emissions and construction and demolition waste (C&DW) generation. Optimizing the mixture design based on both fresh and hardened properties of recycled self-consolidating mortar (RSCM) has not been performed. In this study, multi-objective optimization of mechanical properties and workability of RSCM containing SF was performed via Taguchi Design Method (TDM) with four main variables including cement content, W/C ratio, SF content and superplasticizer content at three different levels. SF was used to decrease the environmental pollution caused by cement production as well as compensating the negative effect of RA on the mechanical properties of RSCM. The results revealed that TDM could appropriately predict the workability and compressive strength of RSCM. Also, mixture design containing W/C = 0.39, SF = 6%, cement = 750 kg/m(3) and SP = 0.33% was found as the optimum mixture having the highest compressive strength and acceptable workability as well as low cost and environmental concerns. Elsevier 2023-05-19 /pmc/articles/PMC10248084/ /pubmed/37303530 http://dx.doi.org/10.1016/j.heliyon.2023.e16381 Text en © 2023 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Bamshad, Omid
Mahdikhani, Mahdi
Ramezanianpour, Amir Mohammad
Maleki, Zahra
Majlesi, Arsalan
Habibi, Alireza
Delavar, Mohammad Aghajani
Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method
title Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method
title_full Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method
title_fullStr Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method
title_full_unstemmed Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method
title_short Prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using Taguchi design method
title_sort prediction and multi-objective optimization of workability and compressive strength of recycled self-consolidating mortar using taguchi design method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248084/
https://www.ncbi.nlm.nih.gov/pubmed/37303530
http://dx.doi.org/10.1016/j.heliyon.2023.e16381
work_keys_str_mv AT bamshadomid predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod
AT mahdikhanimahdi predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod
AT ramezanianpouramirmohammad predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod
AT malekizahra predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod
AT majlesiarsalan predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod
AT habibialireza predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod
AT delavarmohammadaghajani predictionandmultiobjectiveoptimizationofworkabilityandcompressivestrengthofrecycledselfconsolidatingmortarusingtaguchidesignmethod