Shock wave interactions such as those that occur during atmospheric re-entry, can produce extreme thermal loads on aerospace structures. These interactions are reproduced experimentally in hypersonic wind tunnels to study how the flow structures relate to the deleterious heat fluxes. In these studies, localized fluid jets created by shock interactions impinge on a test cylinder, where the temperature due to the heat flux is measured. These measurements are used to estimate the heat flux on the surface as a result of the shock interactions. The nature of the incident flux usually involves dynamic transients and severe nonuniformities. Finding this boundary flux from discrete unsteady temperature measurements is characterized by instabilities in the solution. The purpose of this work is to evaluate existing methodologies for the determination of the unsteady heat flux and to introduce a new approach based on an inverse technique. The performance of these methods was measured first in terms of accuracy and their ability to handle inherently ``unstable'' or highly dynamic data such as step fluxes and high frequency oscillating fluxes. Then the method was expanded to estimate unsteady and nonuniform heat fluxes. The inverse methods proved to be the most accurate and stable of the methods examined, with the proposed method being preferable. / Ph. D.

No description available.

A method of performing local transient heat flux measurements in an uncooled axisymmetric hybrid rocket nozzle is presented. Surface temperatures are collected at various axial locations during short duration tests and post processed using finite difference techniques to determine local transient heat fluxes and film coefficients. Comparisons are made between the collected data and the complete Bartz model. Although strong agreement is observed in certain sections of the nozzle, ideal steady state conditions are not observed to entirely validate the Bartz model for hybrid rocket nozzles. An experimental error analysis indicates the experimental heat fluxes are accurate within ±5.2% and supports the accuracy of the results.

No description available.

<p> This study focuses on developing a new online recursive numerical algorithm for a coupled nonlinear inverse heat conduction-microstructure problem. This algorithm is essential in identifying, designing and controlling many industrial applications such as the quenching process for heat treating of materials, chemical vapor deposition and industrial baking. In order to develop the above algorithm, a systematic four stage research plan has been conducted. </P> <p> The first and second stages were devoted to thoroughly reviewing the existing inverse heat conduction techniques. Unlike most inverse heat conduction solution methods that are batch form techniques, the online input estimation algorithm can be used for controlling the process in real time. Therefore, in the first stage, the effect of different parameters of the online input estimation algorithm on the estimate bias has been investigated. These parameters are the stabilizing parameter, the measurement errors standard deviation, the temporal step size, the spatial step size, the location of the thermocouple as well as the initial assumption of the state error covariance and error covariance of the input estimate. Furthermore, three different discretization schemes; namely: explicit, implicit and Crank-Nicholson have been employed in the input estimation algorithm to evaluate their effect on the algorithm performance. </p> <p> The effect of changing the stabilizing parameter has been investigated using three different forms of boundary conditions covering most practical boundary heat flux conditions. These cases are: square, triangular and mixed function heat fluxes. The most important finding of this investigation is that a robust range of the stabilizing parameter has been found which achieves the desired trade-off between the filter tracking ability and its sensitivity to measurement errors. For the three considered cases, it has been found that there is a common optimal value of the stabilizing parameter at which the estimate bias is minimal. This finding is important for practical applications since this parameter is usually unknown. Therefore, this study provides a needed guidance for assuming this parameter. </p> <p> In stage three of this study, a new, more efficient direct numerical algorithm has been developed to predict the thermal and microstructure fields during quenching of steel rods. The present algorithm solves the full nonlinear heat conduction equation using a central finite-difference scheme coupled with a fourth-order Runge-Kutta nonlinear solver. Numerical results obtained using the present algorithm have been validated using experimental data and numerical results available in the literature. In addition to its accurate predictions, the present algorithm does not require iterations; hence, it is computationally more efficient than previous numerical algorithms. </p> <p> The work performed in stage four of this research focused on developing and applying an inverse algorithm to estimate the surface temperatures and surface heat flux of a steel cylinder during the quenching process. The conventional online input estimation algorithm has been modified and used for the first time to handle this coupled nonlinear problem. The nonlinearity of the problem has been treated explicitly which resulted in a non-iterative algorithm suitable for real-time control of the quenching process. The obtained results have been validated using experimental data and numerical results obtained by solving the direct problem using the direct solver developed in stage three of this work. These results showed that the algorithm is efficiently reconstructing the shape of the convective surface heat flux. </p> / Thesis / Doctor of Philosophy (PhD)

The overall goal of this work is to provide a systematic methodology by which the difficulties associated with the inverse heat conduction problem (IHCP) can be resolved. To this end, two inverse heat conduction methods are presented. First, a space-marching IHCP method (discrete space, discrete time) utilizing a Gaussian low-pass filter for regularization is studied. The stability and accuracy of this inverse prediction is demonstrated to be more sensitive to the temporal mesh than the spatial mesh. The second inverse heat conduction method presented aims to eliminate this feature by employing a global time, discrete space inverse solution methodology. The novel treatment of the temporal derivative in the heat equation, combined with the global time Gaussian low-pass filter provides the regularization required for stable, accurate results. A physical experiment used as a test bed for validation of the numerical methods described herein is also presented. The physics of installed thermocouple sensors are outlined, and loop-current step response (LCSR) is employed to measure and correct for the delay and attenuation characteristics of the sensors. A new technique for the analysis of LCSR data is presented, and excellent agreement is observed between this model and the data. The space-marching method, global time method, and a new calibration integral method are employed to analyze the experimental data. First, data from only one probe is used which limits the results to the case of a semi-infinite medium. Next, data from two probes at different depths are used in the inverse analysis which enables generalization of the results to domains of finite width. For both one- and two-probe analyses, excellent agreement is found between the actual surface heat flux and the inverse predictions. The most accurate inverse technique is shown to be the calibration integral method, which is presently restricted to one-probe analysis. It is postulated that the accuracy of the global time method could be improved if the required higher-time derivatives of temperature data could be more accurately measured. Some preliminary work in obtaining these higher-time derivatives of temperature from a voltage-rate interface used in conjunction with the thermocouple calibration curve is also presented.

We consider the design of finite element methods for inverse problems with full-field data governed by elliptic forward operators. Such problems arise in applications in inverse heat conduction, in mechanical property characterization, and in medical imaging. For this class of problems, novel finite element methods have been proposed (Barbone et al., 2010) that give good performance, provided the solutions are in the H^1(Ω) function space. The material property distributions being estimated can be discontinuous, however, and therefore it is desirable to have formulations that can accommodate discontinuities in both data and solution. Toward this end, we present a mixed variational formulation for this class of problems that handles discontinuities well. We motivate the mixed formulation by examining the possibility of discretizing using a discontinuous discretization in an irreducible finite element method, and discuss the limitations of that approach. We then derive a new mixed formulation based on a least-square error in the constitutive equation. We prove that the continuous variational formulations are well-posed for applications in both inverse heat conduction and plane stress elasticity. We derive a priori error bounds for discretization error, valid in the limit of mesh refinement. We demonstrate convergence of the method with mesh refinement in cases with both continuous and discontinuous solutions. Finally we apply the formulation to measured data to estimate the elastic shear modulus distributions in both tissue mimicking phantoms and in breast masses from data collected in vivo.

Neste trabalho apresenta-se uma discussão geral sobre problemas inversos, problemas mal-postos c técnicas de regularização, visando sua aplicabilidade em problemas térmicos. Métodos numéricos especiais são discutidos para a solução de problemas que apresentam instabilidade em relação aos dados. Tais métodos baseiam-se na utilização de restrições ou informações adicionais sobre a solução procurada. O problema de determinação da condição inicial da equação do calor é resolvido numericamente através destas técnicas, particularmente a regularização de Tikhonov e o príncipio da máxima entropia conectados ao príncipio da discrepância de Morozov são utilizados. / In this work we present a general discussion on invcrse problems, ill-posed problems and regularization techniqucs, applying these techniques to thermal problcms. Special numerical methods are discusscd in order to solve problerns for which the solution is unstable under data perturbations. Such methods are based on the utilization of restrictions or additional information on thc solution. The problern of determining the initial condition of thc heat equation is numerically solved beyond thesc techniques, particularly thc T ikhonov regularization and thc maximum entropy principie connected to thc Morozov's discrepancy principie are used.

Neste trabalho apresenta-se uma discussão geral sobre problemas inversos, problemas mal-postos c técnicas de regularização, visando sua aplicabilidade em problemas térmicos. Métodos numéricos especiais são discutidos para a solução de problemas que apresentam instabilidade em relação aos dados. Tais métodos baseiam-se na utilização de restrições ou informações adicionais sobre a solução procurada. O problema de determinação da condição inicial da equação do calor é resolvido numericamente através destas técnicas, particularmente a regularização de Tikhonov e o príncipio da máxima entropia conectados ao príncipio da discrepância de Morozov são utilizados. / In this work we present a general discussion on invcrse problems, ill-posed problems and regularization techniqucs, applying these techniques to thermal problcms. Special numerical methods are discusscd in order to solve problerns for which the solution is unstable under data perturbations. Such methods are based on the utilization of restrictions or additional information on thc solution. The problern of determining the initial condition of thc heat equation is numerically solved beyond thesc techniques, particularly thc T ikhonov regularization and thc maximum entropy principie connected to thc Morozov's discrepancy principie are used.

Neste trabalho apresenta-se uma discussão geral sobre problemas inversos, problemas mal-postos c técnicas de regularização, visando sua aplicabilidade em problemas térmicos. Métodos numéricos especiais são discutidos para a solução de problemas que apresentam instabilidade em relação aos dados. Tais métodos baseiam-se na utilização de restrições ou informações adicionais sobre a solução procurada. O problema de determinação da condição inicial da equação do calor é resolvido numericamente através destas técnicas, particularmente a regularização de Tikhonov e o príncipio da máxima entropia conectados ao príncipio da discrepância de Morozov são utilizados. / In this work we present a general discussion on invcrse problems, ill-posed problems and regularization techniqucs, applying these techniques to thermal problcms. Special numerical methods are discusscd in order to solve problerns for which the solution is unstable under data perturbations. Such methods are based on the utilization of restrictions or additional information on thc solution. The problern of determining the initial condition of thc heat equation is numerically solved beyond thesc techniques, particularly thc T ikhonov regularization and thc maximum entropy principie connected to thc Morozov's discrepancy principie are used.