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Advanced Methods of Solid Oxide Fuel Cell Modeling

Fuel cells are widely regarded as the future of the power and transportation industries. Intensive research in this area now requires new methods of fuel cell operation modeling and cell design. Typical mathematical models are based on the physical process description of fuel cells and require a det...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Milewski, Jarosław (Autor), Świrski, Konrad (Autor), Santarelli, Massimo (Autor), Leone, Pierluigi (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2011.
Edición:1st ed. 2011.
Colección:Green Energy and Technology,
Temas:
Acceso en línea:Texto Completo

MARC

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100 1 |a Milewski, Jarosław.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Advanced Methods of Solid Oxide Fuel Cell Modeling  |h [electronic resource] /  |c by Jarosław Milewski, Konrad Świrski, Massimo Santarelli, Pierluigi Leone. 
250 |a 1st ed. 2011. 
264 1 |a London :  |b Springer London :  |b Imprint: Springer,  |c 2011. 
300 |a XIV, 218 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Green Energy and Technology,  |x 1865-3537 
505 0 |a 1. Introduction -- 2. Theory -- 3. Advanced Methods in Mathematical Modeling -- 4. Experimental Investigation -- 5. SOFC Modeling. 
520 |a Fuel cells are widely regarded as the future of the power and transportation industries. Intensive research in this area now requires new methods of fuel cell operation modeling and cell design. Typical mathematical models are based on the physical process description of fuel cells and require a detailed knowledge of the microscopic properties that govern both chemical and electrochemical reactions. Advanced Methods of Solid Oxide Fuel Cell Modeling proposes the alternative methodology of generalized artificial neural networks (ANN) solid oxide fuel cell (SOFC) modeling. Advanced Methods of Solid Oxide Fuel Cell Modeling provides a comprehensive description of modern fuel cell theory and a guide to the mathematical modeling of SOFCs, with particular emphasis on the use of ANNs. Up to now,  most of the equations involved in SOFC models have required the addition of numerous factors that are difficult to determine. The artificial neural network (ANN) can be applied to simulate an object's behavior without an algorithmic solution, merely by utilizing available experimental data. The ANN methodology discussed in Advanced Methods of Solid Oxide Fuel Cell Modeling can be used by both researchers and professionals to optimize SOFC design. Readers will have access to detailed material on universal fuel cell modeling and design process optimization, and will also be able to discover comprehensive information on fuel cells and artificial intelligence theory. 
650 0 |a Mathematical models. 
650 0 |a Chemistry, Technical. 
650 0 |a Electric power production. 
650 0 |a Artificial intelligence. 
650 1 4 |a Mathematical Modeling and Industrial Mathematics. 
650 2 4 |a Industrial Chemistry. 
650 2 4 |a Electrical Power Engineering. 
650 2 4 |a Artificial Intelligence. 
700 1 |a Świrski, Konrad.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Santarelli, Massimo.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Leone, Pierluigi.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9780857292612 
776 0 8 |i Printed edition:  |z 9781447126409 
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830 0 |a Green Energy and Technology,  |x 1865-3537 
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912 |a ZDB-2-ENG 
912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)