Exploring Design Optimization of Self-Compacting Mortars with Response Surface Methodology
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
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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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 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137428478361600 |