Hierarchical Competitive Net Architecture

  • Theresa W. Long
  • Emil L. Hanzevack
Part of the Advances in Industrial Control book series (AIC)


Development of hypersonic aircraft requires a high degree of system integration. Design tools are needed to provide rapid, accurate calculations of complex fluid flow patterns. This project demonstrates that neural networks can be successfully applied to calculation of fluid flow distribution and heat transfer in a six leg heat exchanger panel, typical of the type envisioned for use in hypersonic aircraft.

We used training data generated from fluid flow and heat transfer equations in explicit form to train a neural net to solve the associated inverse dynamics problem. We developed an improved competitive net architecture. Finally, we successfully implemented a hierarchical neural network scheme to link multiple heat exchanger panels together. This method is direct, fast, and accurate.


Hide Layer Mass Flow Rate Heat Load Heat Transfer Equation Hypersonic 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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Copyright information

© Springer-Verlag London Limited 1995

Authors and Affiliations

  • Theresa W. Long
    • 1
  • Emil L. Hanzevack
    • 2
  1. 1.NeuroDyne Inc.WilliamsburgUSA
  2. 2.University of South CarolinaColumbiaUSA

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