A low-computational-cost inverse heat transfer technique for convective heat transfer measurements in hypersonic flows

A low-computational-cost inverse heat transfer technique for convective heat transfer... The measurement of the convective wall heat flux in hypersonic flows may be particularly challenging in the presence of high-temperature gradients and when using high-thermal-conductivity materials. In this case, the solution of multidimensional problems is necessary, but it considerably increases the computational cost. In this paper, a low-computational-cost inverse data reduction technique is presented. It uses a recursive least-squares approach in combination with the trust-region-reflective algorithm as optimization procedure. The computational cost is reduced by performing the discrete Fourier transform on the discrete convective heat flux function and by identifying the most relevant coefficients as objects of the optimization algorithm. In the paper, the technique is validated by means of both synthetic data, built in order to reproduce physical conditions, and experimental data, carried out in the Hypersonic Test Facility Delft at Mach 7.5 on two wind tunnel models having different thermal properties. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

A low-computational-cost inverse heat transfer technique for convective heat transfer measurements in hypersonic flows

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2015 by Springer-Verlag Berlin Heidelberg
Subject
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s00348-015-1951-5
Publisher site
See Article on Publisher Site

Abstract

The measurement of the convective wall heat flux in hypersonic flows may be particularly challenging in the presence of high-temperature gradients and when using high-thermal-conductivity materials. In this case, the solution of multidimensional problems is necessary, but it considerably increases the computational cost. In this paper, a low-computational-cost inverse data reduction technique is presented. It uses a recursive least-squares approach in combination with the trust-region-reflective algorithm as optimization procedure. The computational cost is reduced by performing the discrete Fourier transform on the discrete convective heat flux function and by identifying the most relevant coefficients as objects of the optimization algorithm. In the paper, the technique is validated by means of both synthetic data, built in order to reproduce physical conditions, and experimental data, carried out in the Hypersonic Test Facility Delft at Mach 7.5 on two wind tunnel models having different thermal properties.

Journal

Experiments in FluidsSpringer Journals

Published: Apr 14, 2015

References

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