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Robust metamodels for accurate quantitative estimation of turbulent flow in pipe bends

  • N. Ganesh
  • P. Dutta
  • M. Ramachandran
  • A. K. Bhoi
  • K. KalitaEmail author
Original Article

Abstract

Pipe bends are inevitable in industrial piping systems, turbomachinery, heat exchangers, etc. Computational fluid dynamics (CFD), which is commonly employed to understand the flow behavior in such systems has very accurate estimation but is computationally cost intensive. Thus, in this paper, an efficient computational approach for such computationally expensive problems is presented. Using genetic programming (GP), metamodels are built using a small number of samples points from the CFD data. These GP metamodels are then shown to be able to replace the actual CFD models with considerable accuracy. The applicability and suitability of the GP metamodels are validated using a variety of statistical metrics on the training as well as independent test data. It is shown that the use of metamodels leads to significant savings in computational cost.

Keywords

CFD Genetic programming (GP) Metamodel Pipe bend Turbulent flow 

Notes

Funding

This study was not funded by any grant.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringVel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering CollegeChennaiIndia
  2. 2.Department of Aerospace Engineering and Applied MechanicsIndian Institute of Engineering, Science and TechnologyHowrahIndia
  3. 3.Department of Mechanical EngineeringMPSTME SVKM’S Narsee Monjee Institute of Management StudiesShirpurIndia
  4. 4.Department of Electrical and Electronics Engineering, Sikkim Manipal Institute of TechnologySikkim Manipal UniversityMajhitarIndia

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