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.
Experiments in Fluids – Springer Journals
Published: Apr 14, 2015
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