rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Advanced Methods of Solid Oxide Fuel Cell Modeling
  name:
    name part: Milewski, Jarosław.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Świrski, Konrad.
    role:
      role term: author.
  name:
    name part: Santarelli, Massimo.
    role:
      role term: author.
  name:
    name part: Leone, Pierluigi.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 218 p. online resource.
  abstract: 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.
  table of contents: 1. Introduction -- 2. Theory -- 3. Advanced Methods in Mathematical Modeling -- 4. Experimental Investigation -- 5. SOFC Modeling.
  note: by Jarosław Milewski, Konrad Świrski, Massimo Santarelli, Pierluigi Leone.
  subject:
    topic: Mathematics
  subject:
    topic: Chemical engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: Mathematical models
  subject:
    topic: Power electronics
  subject:
    topic: Mathematics
  subject:
    topic: Mathematical Modeling and Industrial Mathematics
  subject:
    topic: Industrial Chemistry/Chemical Engineering
  subject:
    topic: Power Electronics, Electrical Machines and Networks
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: TA342-343
  classification: 003.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Green Energy and Technology
  identifier: 9780857292629
  identifier: http://dx.doi.org/10.1007/978-0-85729-262-9
  record info:
    record creation date: 110303
    record change date: 20151204182519.0
    record identifier: 978-0-85729-262-9