Genetically-inspired convective heat transfer enhancement in a turbulent boundary layer Articles uri icon

publication date

  • July 2023

start page

  • 1

end page

  • 16

issue

  • 120621

volume

  • 230

International Standard Serial Number (ISSN)

  • 1359-4311

Electronic International Standard Serial Number (EISSN)

  • 1873-5606

abstract

  • The convective heat transfer in a turbulent boundary layer (TBL) on a flat plate is enhanced using an artificial intelligence approach based on linear genetic algorithms control (LGAC). The actuator is a set of six slot jets in crossflow aligned with the freestream. An open-loop optimal periodic forcing is defined by the carrier frequency, the duty cycle and the phase difference between actuators as control parameters. The control laws are optimised with respect to the unperturbed TBL and to the actuation with a steady jet. The cost function includes the wall convective heat transfer rate and the cost of the actuation. The performance of the controller is assessed by infrared thermography and characterised also with particle image velocimetry measurements. The optimal controller yields a slightly asymmetric flow field. The LGAC algorithm converges to the same frequency and duty cycle for all the actuators. It is noted that such frequency is strikingly equal to the inverse of the characteristic travel time of large-scale turbulent structures advected within the near-wall region. The phase difference between multiple jet actuation has shown to be very relevant and the main driver of flow asymmetry. The results pinpoint the potential of machine learning control in unravelling unexplored controllers within the actuation space. Our study furthermore demonstrates the viability of employing sophisticated measurement techniques together with advanced algorithms in an experimental investigation.

subjects

  • Aeronautics
  • Biology and Biomedicine
  • Chemistry
  • Computer Science
  • Information Science
  • Materials science and engineering
  • Mechanical Engineering
  • Robotics and Industrial Informatics

keywords

  • machine learning; genetic algorithms; flow control; pulsed crossflow jets; turbulent boundary layers; convective heat transfer enhancement