Intelligent Machine Learning Analysis for Fuel Cell Operations
A performance computational model for a 100 kW nominal solid oxide fuel cell generator system is described. The calculational methods are based on the FORTRAN programming language. Comprehensive parameter input options are presented, and constraints are identified. Example reactant, electrical, and efficiency outputs are demonstrated over the relevant operating ranges. A sample calculated output display at nominal operating conditions is given.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE)
- DOE Contract Number:
- DE-AC05-00OR22725
- OSTI ID:
- 940376
- Report Number(s):
- ORNL96-0431; ORNL99-0564; TRN: US200902%%228
- Country of Publication:
- United States
- Language:
- English
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