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ANN modeling applied to NOX reduction with octane. Ann future in personal vehicles

  • Mats Rönnholm
  • Kalle Arve
  • Kari Eränen
  • Fredrik Klingstedt
  • Tapio Salmi
  • Henrik Saxén
Conference paper

Abstract

A silver/alumina catalyst was tested for its NOX reduction activity during oxygen-rich conditions and during variation in the input parameters (nitric oxide, octane and oxygen). A multi-bed approach was tested where the initial bed was divided into four beds acting in different temperature rages. The experimental data were investigated by means of artificial neural networks that were demonstrated to be able to model the process.

Keywords

Artificial Neural Network Selective Catalytic Reduction Nitrogen Monoxide Reactor Concept Personal Vehicle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Eränen, K., Klingstedt, F., Arve, K., Murzin, D. Yu., (2004). On the mechanism of the selective catalytic reduction of NO with higher hydrocarbons over a silver/alumina catalyst. Journal of Catalysis 227: 328–343.CrossRefGoogle Scholar
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    Arve, K., Popov, E. A., Rönnholm, M., Klingstedt, F., Eloranta, J., Eränen, K., Murzin D. Yu., (2004). From a fixed bed Ag-alumina catalyst to a modified reactor design: how to enhance the crucial heterogeneous-homogeneous reactions in HC-SCR. Chemical Engineering Science 59: 5277–5282.CrossRefGoogle Scholar
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    Saxén, B. Saxén, H. (1995). NNDT — A Neural Network Development Tool, Proc. Intern. Conf. on Artificial Neural Networks and Genetic Algorithms (ICANNGA’95), Alés, France, 325–328.Google Scholar
  4. [4]
    Rönnholm, M., Klingstedt, F., Eränen, K., Lindfors, L-E. (2003). Artificial neural network modelling applied on NOX reduction with octane in excess oxygen over Ag/Al2O3. Reaction Kinetics and Catalysis Letters, Vol. 78, No 2, 331–340.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag/Wien 2005

Authors and Affiliations

  • Mats Rönnholm
    • 1
  • Kalle Arve
    • 1
  • Kari Eränen
    • 1
  • Fredrik Klingstedt
    • 1
  • Tapio Salmi
    • 1
  • Henrik Saxén
    • 2
  1. 1.Laboratory of Industrial Chemistry, Process Chemistry CentreÅbo Akademi UniversityÅbo/TurkuFinland
  2. 2.Heat Engineering LaboratoryÅbo Akademi UniversityÅbo/TurkuFinland

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