Sustainable Water Management for Steam Generation in Sugarcane Biorefineries: Applying PCA and MST Clustering in Sample Analysis

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorInst Nacl Tecnol Alternat Deteccao Avaliacao Toxic-
Autor(es): dc.creatorSouza, erik Geraldo S.-
Autor(es): dc.creatorPereira, Fabiola M. V.-
Data de aceite: dc.date.accessioned2025-08-21T22:53:01Z-
Data de disponibilização: dc.date.available2025-08-21T22:53:01Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.21577/0103-5053.20250006-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/303512-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/303512-
Descrição: dc.descriptionOur study on sustainable water management in sugarcane biorefineries, which utilizes water as a primary resource for generating bioenergy through steam production, has employed a novel approach. High water quality is crucial for optimal efficiency, particularly in boiler operations. We have utilized unsupervised methods, such as principal component analysis (PCA) and minimum spanning tree (MST), alongside instrumental analysis data, to assess water quality in steam production. The PCA exploratory analysis identified three distinct clusters, with the relevant variables being conductivity and SiO2 content, to differentiate the purity of a dataset of 120 samples. MST-based clustering corroborated the PCA findings, forming three clusters: sample 1 represented the purest water, while samples 3 and 6 were in different clusters, indicating less purity in boiler feedwater. These unsupervised methods are highly effective, providing accurate and reliable data analysis and significantly benefiting sugarcane biorefineries by eliminating subjective biases. The findings of this study promise to improve water management practices in sugarcane biorefineries, leading to more efficient and sustainable operations.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionUniv Estadual Paulista UNESP, Inst Quim, Inst Pesquisa Bioenergia IPBEN, Grp Abordagens Analit Alternat GAAA, BR-14800060 Araraquara, SP, Brazil-
Descrição: dc.descriptionInst Nacl Tecnol Alternat Deteccao Avaliacao Toxic, BR-14800060 Araraquara, SP, Brazil-
Descrição: dc.descriptionUniv Estadual Paulista UNESP, Inst Quim, Inst Pesquisa Bioenergia IPBEN, Grp Abordagens Analit Alternat GAAA, BR-14800060 Araraquara, SP, Brazil-
Descrição: dc.descriptionFAPESP: 2014/50945-4-
Descrição: dc.descriptionCNPq: 302085/2022-0-
Descrição: dc.descriptionCNPq: 465571/2014-0-
Descrição: dc.descriptionCAPES: 001-
Descrição: dc.descriptionCAPES: 88887136426/2017/00-
Formato: dc.format5-
Idioma: dc.languageen-
Publicador: dc.publisherSoc Brasileira Quimica-
Relação: dc.relationJournal Of The Brazilian Chemical Society-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectpurity water-
Palavras-chave: dc.subjectboilers-
Palavras-chave: dc.subjectbioenergy-
Palavras-chave: dc.subjectchemometrics-
Palavras-chave: dc.subjectsustainability-
Título: dc.titleSustainable Water Management for Steam Generation in Sugarcane Biorefineries: Applying PCA and MST Clustering in Sample Analysis-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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