Multidimensional and High Frequency Heat Flux Reconstruction Applied to Hypersonic Transitional Flows
Nguyen, Nhat Minh
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The ability to predict and control laminar-to-turbulent transition in high-speed flow has a substantial effect on heat transfer and skin friction, thus improving the design and operation of hypersonic vehicles. The control of transition on blunt bodies is essential to improve the performance of lifting and control surfaces. The objective of this Ph.D. research is to develop efficient and accurate algorithms for the detection of high-frequency heat flux fluctuations supported by hypersonic flow in transitional boundary layers. The focus of this research is on understanding the mathematical properties of the reconstruction such as regularity, sensitivity to noise, multi-resolution, and accuracy. This research is part of an effort to develop small-footprint heat flux sensors able to measure high-frequency fluctuations on test articles in a hypersonic wind tunnel with a small curvature radius. In the present theoretical/numerical study a multi-resolution formulation for the direct and inverse reconstruction of the heat flux from temperature sensors distributed over a multidimensional solid in a hypersonic flow was developed and validated. The solution method determines the thermal response by approximating the system Green's function with the Galerkin method and optimizes the heat flux distribution by fitting the distributed surface temperature data. Coating and glue layers are treated as separate domains for which the Green's function is obtained independently. Connection conditions for the system Green's function are derived by imposing continuity of heat flux and temperature concurrently at all interfaces. The solution heat flux is decomposed on a space-time basis with the temporal basis a multi-resolution wavelet with arbitrary scaling function. Quadrature formulas for the convolution of wavelets and the Green's function, a reconstruction approach based on isoparametric mapping of three-dimensional geometries, and a boundary wavelet approach for inverse problems were developed and verified. This approach was validated against turbulent conjugate heat transfer simulations at Mach 6 on a blunted wedge at 0 angle of attack and wind tunnel experiments of round impinging jet at Mach 0.7 It was found that multidimensional effects were important near the wedge shoulder in the short time scale, that the L-curve regularization needed to be locally corrected to analyze transitional flows and that proper regularization led to sub-cell resolution of the inverse problem. While the L2 regularization techniques are accurate they are also computationally inefficient and lack mathematical rigor. Optimal non-linear estimators were researched both as means to promote sparsity in the regularization and to pre-threshold the inverse heat conduction problem. A novel class of nonlinear estimators is presented and validated against wind tunnel experiments for a flat-faced cylinder also at Mach 6. The new approach to hypersonic heat flux reconstruction from discrete temperature data developed in this thesis is more efficient and accurate than existing techniques.
General Audience Abstract
The harsh environment supported by hypersonic flows is characterized by high-frequency turbulent bursts, acoustic noise, and vibrations that pollute the signals of the sensors that probe at high frequencies the state of the boundary layers developing on the walls. This research describes the search for optimal estimators of the noisy signal, i.e., those that lead to the maximum attenuation of the risk of error pollution by non-coherent scales. This research shows that linear estimators perform poorly at high-frequency and non-linear estimators can be optimized over a sparse projection of the signal in a discrete wavelet basis. Optimal non-linear estimators are developed and validated for wind tunnel experiments conducted at Mach 6 in the Advanced Propulsion and Power Laboratory at Virginia Tech.
- Doctoral Dissertations