03359nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100020001900118024003500137082001400172100003400186245015900220264003800379300003400417336002600451337002600477338003600503347002400539490004400563505013500607520147800742650001702220650002602237650002902263650004402292650001702336650005402353650004702407650005702454650004602511700003202557700003402589700003102623710003402654773002002688776003602708830004402744856010102788978-0-85729-262-9DE-He21320260521092038.0cr nn 008mamaa110303s2011    xxk|    s    |||| 0|eng d  a9780857292629  a997808572926297 a10.1007/978-0-85729-262-92doi04a003.32231 aMilewski, Jarosław.eauthor.10aAdvanced Methods of Solid Oxide Fuel Cell Modelingh[electronic resource] /cby Jarosław Milewski, Konrad Świrski, Massimo Santarelli, Pierluigi Leone. 1aLondon :bSpringer London,c2011.  aXIV, 218 p.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aGreen Energy and Technology,x1865-35290 a1. Introduction -- 2. Theory -- 3. Advanced Methods in Mathematical Modeling -- 4. Experimental Investigation -- 5. SOFC Modeling.  aFuel 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. 0aMATHEMATICS. 0aCHEMICAL ENGINEERING. 0aARTIFICIAL INTELLIGENCE. 0aPRODUCTION OF ELECTRIC ENERGY OR POWER.14aMATHEMATICS.24aMATHEMATICAL MODELING AND INDUSTRIAL MATHEMATICS.24aINDUSTRIAL CHEMISTRY/CHEMICAL ENGINEERING.24aPOWER ELECTRONICS, ELECTRICAL MACHINES AND NETWORKS.24aARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).1 aŚwirski, Konrad.eauthor.1 aSantarelli, Massimo.eauthor.1 aLeone, Pierluigi.eauthor.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780857292612 0aGreen Energy and Technology,x1865-352940uhttp://dx.doi.org/10.1007/978-0-85729-262-9zVer el texto completo en las instalaciones del CICY