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Title: Model-based and Signal-Based Inverse Methods
Authors: Jorge, Ariosto Bretanha
Anflor, Carla Tatiana Mota
Gomes, Guilherme Ferreira
Carneiro, Sérgio Henrique da Silva
metadata.dc.identifier.orcid: 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
Assunto:: Engenharia de materiais
Métodos
Modelos
Issue Date: 2022
Publisher: Universidade de Brasília
Citation: JORGE, Ariosto Bretanha; ANFLOR, Carla Tatiana Mota; GOMES, Guilherme Ferreira; CARNEIRO, Sérgio Henrique da Silva (ed.). Model-based and Signal-Based Inverse Methods. Brasília: Universidade de Brasília, 2022. viii, 535 p. (Discrete Models, Inverse Methods, & Uncertainty Modeling in Structural Integrity, v. 1). ISBN 978-65-86503-71-5. DOI: https://doi.org/10.4322/978-65-86503-71-5. Disponível em: https://livros.unb.br/index.php/portal/catalog/book/196. Acesso em: 18 abr. 2022.
Abstract: This book series is an initiative of the Post Graduate Program in Integrity of Engineering Materials from UnB, organized as a collaborative work involving researchers, engineers, scholars, from several institutions, universities, industry, recognized both nationally and internationally. The book chapters discuss several direct methods, inverse methods and uncertainty models available for model-based and signal based inverse problems, including discrete numerical methods for continuum mechanics (Finite Element Method, Boundary Element Method, Mesh-Free Method, Wavelet Method). The different topics covered include aspects related to multiscale modeling, multiphysics modeling, inverse methods (Optimization, Identification, Artificial Intelligence and Data Science), Uncertainty Modeling (Probabilistic Methods, Uncertainty Quantification, Risk & Reliability), Model Validation and Verification. Each book includes an initial chapter with a presentation of the book chapters included in the volume, and their connection and relationship with regard to the whole setting of methods and models.
metadata.dc.description.unidade: Faculdade UnB Gama (FGA)
Licença:: (CC BY NC ND) [Creative commons license].
DOI: https://doi.org/10.4322/978-65-86503-71-5
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