- Conference Article
- 10.2514/6.2024-4032
Heat Flux Reconstruction Using Embedded Discrete Sensors
- Jul 27, 2024
- Raj Ajmani + 3 more +3
Creating heat flux maps is one of the major data reduction tasks of ground-test hypersonic facilities. The ability to embed multiple high-frequency sensing elements improves the performance of Schmidt-Bolter gauges when there is significant lateral heat flux, i.e., close to the leading edge of fin elements and wings. Because the number of surface sensors is small compared to the number of basis functions necessary to resolve the spatial variation of the heat flux, the problem is ill-posed. Regularization techniques are analyzed and non-linear least squares methods are investigated. The ability of different bases to select the correct spatial distribution is investigated. New measures of the efficiency of the reconstruction when varying the number of bases are discussed. The main findings of this research are that regularization approaches perform well in resolving the depth-wise variation of the lateral component of the heat flux in embedded sensor gauges, that the generalized cross-validation technique is more accurate but less reliable than the L-curve method, and that the performance metrics of the reconstruction algorithm are mostly dependent on the symbolic evaluation of the Green's function in a novel Python hybrid approach (numerical-symbolical).
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