Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology

Detalhes bibliográficos
Autor(a) principal: Rocha, Stéphanie
Data de Publicação: 2023
Outros Autores: Ascensão, Guilherme, Maia, Lino
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.13/5532
Resumo: The ever-evolving construction sector demands technological developments to provide consumers with products that meet stringent technical, environmental, and economic requirements. Self-compacting cementitious mixtures have garnered significance in the construction market due to their enhanced compaction, workability, fluidity, and mechanical properties. This study aimed to harness the potential of statistical response surface methodology (RSM) to optimize the fresh proper ties and strength development of self-compacting mortars. A self-compacting mortar repository was used to build meaningful and robust models describing D-Flow and T-Funnel results, as well as the compressive strength development after 24 h (CS24h) and 28 days (CS28d) of curing. The quantitative input factors considered were A (water/cement), B (superplasticizer/powder), C (water/powder), and D (sand/mortar), and the output variables were Y1 (D-Flow), Y2 (T-Funnel), Y3 (CS24h), and Y4 (CS28d). The results found adjusted response models, with significant R2 values of 87.4% for the D-Flow, 93.3% for the T-Funnel, and 79.1% for the CS24h. However, for the CS28d model, a low R2 of 39.9% was found. Variable A had the greatest influence on the response models. The best correlations found were between inputs A and C and outputs Y1 and Y2, as well as input factors A and D for responses Y3 and Y4. The resulting model was enhanced, thereby resulting in a global desirability of approximately 60%, which showcases the potential for the further refinement and optimization of RSM models applied to self-compacting mortars.
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spelling Exploring Design Optimization of Self-Compacting Mortars with Response Surface MethodologySelf-compacting mortarsDesign of experimentsFresh propertiesCompressive strengthANOVA.Faculdade de Ciências Exatas e da EngenhariaThe ever-evolving construction sector demands technological developments to provide consumers with products that meet stringent technical, environmental, and economic requirements. Self-compacting cementitious mixtures have garnered significance in the construction market due to their enhanced compaction, workability, fluidity, and mechanical properties. This study aimed to harness the potential of statistical response surface methodology (RSM) to optimize the fresh proper ties and strength development of self-compacting mortars. A self-compacting mortar repository was used to build meaningful and robust models describing D-Flow and T-Funnel results, as well as the compressive strength development after 24 h (CS24h) and 28 days (CS28d) of curing. The quantitative input factors considered were A (water/cement), B (superplasticizer/powder), C (water/powder), and D (sand/mortar), and the output variables were Y1 (D-Flow), Y2 (T-Funnel), Y3 (CS24h), and Y4 (CS28d). The results found adjusted response models, with significant R2 values of 87.4% for the D-Flow, 93.3% for the T-Funnel, and 79.1% for the CS24h. However, for the CS28d model, a low R2 of 39.9% was found. Variable A had the greatest influence on the response models. The best correlations found were between inputs A and C and outputs Y1 and Y2, as well as input factors A and D for responses Y3 and Y4. The resulting model was enhanced, thereby resulting in a global desirability of approximately 60%, which showcases the potential for the further refinement and optimization of RSM models applied to self-compacting mortars.MDPIDigitUMaRocha, StéphanieAscensão, GuilhermeMaia, Lino2024-02-06T10:02:38Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.13/5532eng: Rocha, S.; Ascensão, G.; Maia, L. Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology. Appl. Sci. 2023, 13, 10428. https://doi.org/ 10.3390/app13181042810.3390/app131810428info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-11T04:56:38Zoai:digituma.uma.pt:10400.13/5532Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:37:46.333292Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
title Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
spellingShingle Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
Rocha, Stéphanie
Self-compacting mortars
Design of experiments
Fresh properties
Compressive strength
ANOVA
.
Faculdade de Ciências Exatas e da Engenharia
title_short Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
title_full Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
title_fullStr Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
title_full_unstemmed Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
title_sort Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
author Rocha, Stéphanie
author_facet Rocha, Stéphanie
Ascensão, Guilherme
Maia, Lino
author_role author
author2 Ascensão, Guilherme
Maia, Lino
author2_role author
author
dc.contributor.none.fl_str_mv DigitUMa
dc.contributor.author.fl_str_mv Rocha, Stéphanie
Ascensão, Guilherme
Maia, Lino
dc.subject.por.fl_str_mv Self-compacting mortars
Design of experiments
Fresh properties
Compressive strength
ANOVA
.
Faculdade de Ciências Exatas e da Engenharia
topic Self-compacting mortars
Design of experiments
Fresh properties
Compressive strength
ANOVA
.
Faculdade de Ciências Exatas e da Engenharia
description The ever-evolving construction sector demands technological developments to provide consumers with products that meet stringent technical, environmental, and economic requirements. Self-compacting cementitious mixtures have garnered significance in the construction market due to their enhanced compaction, workability, fluidity, and mechanical properties. This study aimed to harness the potential of statistical response surface methodology (RSM) to optimize the fresh proper ties and strength development of self-compacting mortars. A self-compacting mortar repository was used to build meaningful and robust models describing D-Flow and T-Funnel results, as well as the compressive strength development after 24 h (CS24h) and 28 days (CS28d) of curing. The quantitative input factors considered were A (water/cement), B (superplasticizer/powder), C (water/powder), and D (sand/mortar), and the output variables were Y1 (D-Flow), Y2 (T-Funnel), Y3 (CS24h), and Y4 (CS28d). The results found adjusted response models, with significant R2 values of 87.4% for the D-Flow, 93.3% for the T-Funnel, and 79.1% for the CS24h. However, for the CS28d model, a low R2 of 39.9% was found. Variable A had the greatest influence on the response models. The best correlations found were between inputs A and C and outputs Y1 and Y2, as well as input factors A and D for responses Y3 and Y4. The resulting model was enhanced, thereby resulting in a global desirability of approximately 60%, which showcases the potential for the further refinement and optimization of RSM models applied to self-compacting mortars.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
2024-02-06T10:02:38Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.13/5532
url http://hdl.handle.net/10400.13/5532
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv : Rocha, S.; Ascensão, G.; Maia, L. Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology. Appl. Sci. 2023, 13, 10428. https://doi.org/ 10.3390/app131810428
10.3390/app131810428
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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