Uncertainty modeling : fundamental concepts and models

Detalhes bibliográficos
Autor(a) principal: Jorge, Ariosto Bretanha (ed.)
Data de Publicação: 2022
Outros Autores: Anflor, Carla Tatiana Mota (ed.), Gomes, Guilherme Ferreira (ed.), Carneiro, Sergio Henrique da Silva (ed.)
Tipo de documento: Livro
Idioma: por
Título da fonte: Repositório Institucional da UnB
Texto Completo: https://repositorio.unb.br/handle/10482/45108
https://doi.org/10.4322/978-65-86503-88-3
https://orcid.org/0000-0002-8631-1381
https://orcid.org/0000-0003-3941-8335
https://orcid.org/0000-0003-0811-6334
https://orcid.org/0000-0001-6669-2255
Resumo: This book series represents a commendable effort in compiling the latest developments on three important Engineering subjects: discrete modeling, inverse methods, and uncertainty structural integrity. Although academic publications on these subjects are plenty, this book series may be the first time that these modern topics are compiled together, grouped in volumes, and made available for the community. The application of numerical or analytical techniques to model complex Engineering problems, fed by experimental data, usually translated in the form of stochastic information collected from the problem in hand, is much closer to real-world situations than the conventional solution of PDEs. Moreover, inverse problems are becoming almost as common as direct problems, given the need in the industry to maintain current processes working efficiently, as well as to create new solutions based on the immense amount of information available digitally these days. On top of all this, deterministic analysis is slowly giving space to statistically driven structural analysis, delivering upper and lower bound solutions which help immensely the analyst in the decisionmaking process. All these trends have been topics of investigation for decades, and in recent years the application of these methods in the industry proves that they have achieved the necessary maturity to be definitely incorporated into the roster of modern Engineering tools. The present book series fulfills its role by collecting and organizing these topics, found otherwise scattered in the literature and not always accessible to industry. Moreover, many of the chapters compiled in these books present ongoing research topics conducted by capable fellows from academia and research institutes. They contain novel contributions to several investigation fields and constitute therefore a useful source of bibliographical reference and results repository. The Latin American Journal of Solids and Structures (LAJSS) is honored in supporting the publication of this book series, for it contributes academically and carries technologically significant content in the field of structural mechanics.
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spelling Uncertainty modeling : fundamental concepts and modelsMecânica computacionalIntegridade de materiaisModelos do problema diretoThis book series represents a commendable effort in compiling the latest developments on three important Engineering subjects: discrete modeling, inverse methods, and uncertainty structural integrity. Although academic publications on these subjects are plenty, this book series may be the first time that these modern topics are compiled together, grouped in volumes, and made available for the community. The application of numerical or analytical techniques to model complex Engineering problems, fed by experimental data, usually translated in the form of stochastic information collected from the problem in hand, is much closer to real-world situations than the conventional solution of PDEs. Moreover, inverse problems are becoming almost as common as direct problems, given the need in the industry to maintain current processes working efficiently, as well as to create new solutions based on the immense amount of information available digitally these days. On top of all this, deterministic analysis is slowly giving space to statistically driven structural analysis, delivering upper and lower bound solutions which help immensely the analyst in the decisionmaking process. All these trends have been topics of investigation for decades, and in recent years the application of these methods in the industry proves that they have achieved the necessary maturity to be definitely incorporated into the roster of modern Engineering tools. The present book series fulfills its role by collecting and organizing these topics, found otherwise scattered in the literature and not always accessible to industry. Moreover, many of the chapters compiled in these books present ongoing research topics conducted by capable fellows from academia and research institutes. They contain novel contributions to several investigation fields and constitute therefore a useful source of bibliographical reference and results repository. The Latin American Journal of Solids and Structures (LAJSS) is honored in supporting the publication of this book series, for it contributes academically and carries technologically significant content in the field of structural mechanics.Faculdade UnB Gama (FGA)Universidade de Brasília2022-11-04T20:24:53Z2022-11-04T20:24:53Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfJORGE, Ariosto Bretanha (ed.) et al. Uncertainty modeling: fundamental concepts and models. Brasília: Cubo, 2022. x, 743 f., il. DOI 10.4322/978-65-86503-88-3. (Book series indiscrete models, inverse methods, & uncertainty modeling in structural integrity, 3). Disponível em: https://doi.editoracubo.com.br/10.4322/978-65-86503-88-3.pdf. Acesso em: 04 nov. 2022.978-65-86503-88-3https://repositorio.unb.br/handle/10482/45108https://doi.org/10.4322/978-65-86503-88-3https://orcid.org/0000-0002-8631-1381https://orcid.org/0000-0003-3941-8335https://orcid.org/0000-0003-0811-6334https://orcid.org/0000-0001-6669-2255https://repositorio.unb.br/handle/10482/44535(CC BY NC ND) Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.info:eu-repo/semantics/openAccessJorge, Ariosto Bretanha (ed.)Anflor, Carla Tatiana Mota (ed.)Gomes, Guilherme Ferreira (ed.)Carneiro, Sergio Henrique da Silva (ed.)porreponame:Repositório Institucional da UnBinstname:Universidade de Brasília (UnB)instacron:UNB2023-06-10T18:51:17Zoai:repositorio.unb.br:10482/45108Repositório InstitucionalPUBhttps://repositorio.unb.br/oai/requestrepositorio@unb.bropendoar:2023-06-10T18:51:17Repositório Institucional da UnB - Universidade de Brasília (UnB)false
dc.title.none.fl_str_mv Uncertainty modeling : fundamental concepts and models
title Uncertainty modeling : fundamental concepts and models
spellingShingle Uncertainty modeling : fundamental concepts and models
Jorge, Ariosto Bretanha (ed.)
Mecânica computacional
Integridade de materiais
Modelos do problema direto
title_short Uncertainty modeling : fundamental concepts and models
title_full Uncertainty modeling : fundamental concepts and models
title_fullStr Uncertainty modeling : fundamental concepts and models
title_full_unstemmed Uncertainty modeling : fundamental concepts and models
title_sort Uncertainty modeling : fundamental concepts and models
author Jorge, Ariosto Bretanha (ed.)
author_facet Jorge, Ariosto Bretanha (ed.)
Anflor, Carla Tatiana Mota (ed.)
Gomes, Guilherme Ferreira (ed.)
Carneiro, Sergio Henrique da Silva (ed.)
author_role author
author2 Anflor, Carla Tatiana Mota (ed.)
Gomes, Guilherme Ferreira (ed.)
Carneiro, Sergio Henrique da Silva (ed.)
author2_role author
author
author
dc.contributor.author.fl_str_mv Jorge, Ariosto Bretanha (ed.)
Anflor, Carla Tatiana Mota (ed.)
Gomes, Guilherme Ferreira (ed.)
Carneiro, Sergio Henrique da Silva (ed.)
dc.subject.por.fl_str_mv Mecânica computacional
Integridade de materiais
Modelos do problema direto
topic Mecânica computacional
Integridade de materiais
Modelos do problema direto
description This book series represents a commendable effort in compiling the latest developments on three important Engineering subjects: discrete modeling, inverse methods, and uncertainty structural integrity. Although academic publications on these subjects are plenty, this book series may be the first time that these modern topics are compiled together, grouped in volumes, and made available for the community. The application of numerical or analytical techniques to model complex Engineering problems, fed by experimental data, usually translated in the form of stochastic information collected from the problem in hand, is much closer to real-world situations than the conventional solution of PDEs. Moreover, inverse problems are becoming almost as common as direct problems, given the need in the industry to maintain current processes working efficiently, as well as to create new solutions based on the immense amount of information available digitally these days. On top of all this, deterministic analysis is slowly giving space to statistically driven structural analysis, delivering upper and lower bound solutions which help immensely the analyst in the decisionmaking process. All these trends have been topics of investigation for decades, and in recent years the application of these methods in the industry proves that they have achieved the necessary maturity to be definitely incorporated into the roster of modern Engineering tools. The present book series fulfills its role by collecting and organizing these topics, found otherwise scattered in the literature and not always accessible to industry. Moreover, many of the chapters compiled in these books present ongoing research topics conducted by capable fellows from academia and research institutes. They contain novel contributions to several investigation fields and constitute therefore a useful source of bibliographical reference and results repository. The Latin American Journal of Solids and Structures (LAJSS) is honored in supporting the publication of this book series, for it contributes academically and carries technologically significant content in the field of structural mechanics.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-04T20:24:53Z
2022-11-04T20:24:53Z
2022
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
format book
status_str publishedVersion
dc.identifier.uri.fl_str_mv JORGE, Ariosto Bretanha (ed.) et al. Uncertainty modeling: fundamental concepts and models. Brasília: Cubo, 2022. x, 743 f., il. DOI 10.4322/978-65-86503-88-3. (Book series indiscrete models, inverse methods, & uncertainty modeling in structural integrity, 3). Disponível em: https://doi.editoracubo.com.br/10.4322/978-65-86503-88-3.pdf. Acesso em: 04 nov. 2022.
978-65-86503-88-3
https://repositorio.unb.br/handle/10482/45108
https://doi.org/10.4322/978-65-86503-88-3
https://orcid.org/0000-0002-8631-1381
https://orcid.org/0000-0003-3941-8335
https://orcid.org/0000-0003-0811-6334
https://orcid.org/0000-0001-6669-2255
identifier_str_mv JORGE, Ariosto Bretanha (ed.) et al. Uncertainty modeling: fundamental concepts and models. Brasília: Cubo, 2022. x, 743 f., il. DOI 10.4322/978-65-86503-88-3. (Book series indiscrete models, inverse methods, & uncertainty modeling in structural integrity, 3). Disponível em: https://doi.editoracubo.com.br/10.4322/978-65-86503-88-3.pdf. Acesso em: 04 nov. 2022.
978-65-86503-88-3
url https://repositorio.unb.br/handle/10482/45108
https://doi.org/10.4322/978-65-86503-88-3
https://orcid.org/0000-0002-8631-1381
https://orcid.org/0000-0003-3941-8335
https://orcid.org/0000-0003-0811-6334
https://orcid.org/0000-0001-6669-2255
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://repositorio.unb.br/handle/10482/44535
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 Universidade de Brasília
publisher.none.fl_str_mv Universidade de Brasília
dc.source.none.fl_str_mv reponame:Repositório Institucional da UnB
instname:Universidade de Brasília (UnB)
instacron:UNB
instname_str Universidade de Brasília (UnB)
instacron_str UNB
institution UNB
reponame_str Repositório Institucional da UnB
collection Repositório Institucional da UnB
repository.name.fl_str_mv Repositório Institucional da UnB - Universidade de Brasília (UnB)
repository.mail.fl_str_mv repositorio@unb.br
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