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[null,"1.","Record Nr.",null,"UNINA9910625193403321"]
[null,null,"Titolo",null,"Conference record for ... IEEE ... Conference on Human Factors and Power Plants"]
[null,null,"Pubbl/distr/stampa",null,"New York, : IEEE"]
[null,null,"ISSN",null,"2152-5366"]
[null,null,"Disciplina",null,"621.48"]
[null,null,"Soggetti",null,"Nuclear power plants - Human factors"]
[{"$nulls":4},"Nuclear power plants - Control rooms - Human factors"]
[{"$nulls":4},"Human engineering"]
[{"$nulls":4},"Centrales nucléaires - Facteurs humains"]
[{"$nulls":4},"Centrales nucléaires - Salles de commande - Facteurs humains"]
[{"$nulls":4},"Ergonomie"]
[{"$nulls":4},"Conference papers and proceedings."]
[{"$nulls":4},"Periodicals."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Periodico"]
[null,null,null,"Note generali","Editor: 1988- E.W. Hagen."]
[null,"2.","Record Nr.",null,"UNINA9910437642603321"]
[null,null,"Autore",null,"Benner Peter"]
[null,null,"Titolo",null,"Model Order Reduction . Volume 3 Applications / / Peter Benner, Wil Schilders, Stefano Grivet-Talocia, Alfio Quarteroni, Gianluigi Rozza, Luís Miguel Silveira"]
[null,null,"Pubbl/distr/stampa",null,"Berlin/Boston, : De Gruyter, 2020"]
[{"$nulls":4},"Berlin ; ; Boston : , : De Gruyter, , [2020]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"9783110497755"]
[{"$nulls":4},"3110497751"]
[{"$nulls":4},"9783110499001"]
[{"$nulls":4},"3110499002"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (VIII, 466 p.)"]
[null,null,"Collana",null,"Model Order Reduction ; ; Volume 3"]
[null,null,"Classificazione",null,"SK 955"]
[null,null,"Disciplina",null,"515.353"]
[null,null,"Soggetti",null,"MATHEMATICS / Numerical Analysis"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Frontmatter -- Preface to the third volume of Model Order Reduction -- Contents -- 1 Model reduction in chemical process optimization -- 2 Model order reduction in mechanical engineering -- 3 Case studies of model order reduction for acoustics and vibrations -- 4 Model order reduction in microelectronics -- 5 Complexity reduction of electromagnetic systems -- 6 Model reduction in computational aerodynamics -- 7 Model order reduction in neuroscience -- 8 Reduced-order modeling for applications to the cardiovascular system -- 9 From the POD-Galerkin method to sparse manifold models -- 10 Model order reduction in uncertainty quantification -- 11 Reduced-order modeling of large-scale network systems -- 12 Model order reduction and digital twins -- 13 MOR software -- Index"]
[null,null,null,"Sommario/riassunto","An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science."]