摘要 :
A comprehensive uncertainty analysis for high-fidelity flowfield simulations over a Hypersonic Inflatable Atmospheric Decelerator for Mars entry is presented for fully laminar and turbulent flows. The current study implements a sp...
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A comprehensive uncertainty analysis for high-fidelity flowfield simulations over a Hypersonic Inflatable Atmospheric Decelerator for Mars entry is presented for fully laminar and turbulent flows. The current study implements a sparse-collocation approach for efficient and accurate uncertainty quantification in the high-fidelity numerical modeling of hypersonic reentry flow simulations, which may contain large numbers of aleatory and epistemic uncertainties. The mixed uncertainty quantification results show that the computational cost can be reduced by at least 80% compared to the sample requirements for constructing a total order stochastic expansion. The aerodynamic heating (both convective and radiative) and wall pressure uncertainties are computed and shown to vary due to a small fraction of 65 flowfield and radiation modeling parameters considered. The main contributors to the convective heating uncertainty near the stagnation point are the CO_2-CO_2, CO_2-O, and CO-O binary collision interactions, freestream density, and freestream velocity for both boundary layer flows. In laminar flow, exothermic recombination reactions are more important at the shoulder. The radiative heating and 'wall pressure uncertainties were shown to have consistent contribution for both boundary layer flows. The main contributors to the radiative heating uncertainty were the CO_2 dissociation rate and CO_2-O exchange rate due to the strongly-emitting CO_2 ultraviolet band at peak stagnation-point heating. The freestream density variation dominates the uncertainty in the wall pressure.
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摘要 :
A comprehensive uncertainty analysis for high-fidelity flowfield simulations over a Hypersonic Inflatable Atmospheric Decelerator for Mars entry is presented for fully laminar and turbulent flows. The current study implements a sp...
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A comprehensive uncertainty analysis for high-fidelity flowfield simulations over a Hypersonic Inflatable Atmospheric Decelerator for Mars entry is presented for fully laminar and turbulent flows. The current study implements a sparse-collocation approach for efficient and accurate uncertainty quantification in the high-fidelity numerical modeling of hypersonic reentry flow simulations, which may contain large numbers of aleatory and epistemic uncertainties. The mixed uncertainty quantification results show that the computational cost can be reduced by at least 80% compared to the sample requirements for constructing a total order stochastic expansion. The aerodynamic heating (both convective and radiative) and wall pressure uncertainties are computed and shown to vary due to a small fraction of 65 flowfield and radiation modeling parameters considered. The main contributors to the convective heating uncertainty near the stagnation point are the CO_2-CO_2, CO_2-O, and CO-O binary collision interactions, freestream density, and freestream velocity for both boundary layer flows. In laminar flow, exothermic recombination reactions are more important at the shoulder. The radiative heating and 'wall pressure uncertainties were shown to have consistent contribution for both boundary layer flows. The main contributors to the radiative heating uncertainty were the CO_2 dissociation rate and CO_2-O exchange rate due to the strongly-emitting CO_2 ultraviolet band at peak stagnation-point heating. The freestream density variation dominates the uncertainty in the wall pressure.
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The objective of this study was to investigate the uncertainty in shock layer radiative heat predictions on the surface of a hypersonic inflatable aerodynamics decelerator during Mars and Titan entries at peak radiative heating co...
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The objective of this study was to investigate the uncertainty in shock layer radiative heat predictions on the surface of a hypersonic inflatable aerodynamics decelerator during Mars and Titan entries at peak radiative heating conditions. Computational fluid dynamics simulations of planetary entry flows and radiative heat predictions possess a significant amount of uncertainty due to the complexity of the flow physics and the difficulty in obtaining accurate experimental results of molecular level phenomena. Sources of uncertainty considered include flow field chemical rate models, molecular band emission, and the excitation/deexcitation rates of molecules modeled with a non-Boltzmann approach. Due to the computational cost of the numerical models, uncertainty quantification was performed with a surrogate modeling approach based on a sparse approximation of the point-collocation nonintrusive polynomial chaos technique. Accurate results were obtained with only 500 samples of the computational model. Baseline results indicated that radiative heating during Titan entry was nearly 10 times greater than that of the predicted radiative heating during Mars entry. These results indicated that worst-case uncertainty intervals of surface radiative heating predictions were as wide as 30 W/cm~2 during Mars entry and 150 W/cm~2 during Titan entry. Global nonlinear sensitivity results show that the contribution of the uncertain parameters to output uncertainty measures changes across the surface during Mars entry, whereas Titan radiation uncertainty is dominated by flow field chemistry uncertainty throughout the flow field.
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摘要 :
The objective of this study was to investigate the uncertainty in shock layer radiative heat predictions on the surface of a hypersonic inflatable aerodynamics decelerator during Mars and Titan entries at peak radiative heating co...
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The objective of this study was to investigate the uncertainty in shock layer radiative heat predictions on the surface of a hypersonic inflatable aerodynamics decelerator during Mars and Titan entries at peak radiative heating conditions. Computational fluid dynamics simulations of planetary entry flows and radiative heat predictions possess a significant amount of uncertainty due to the complexity of the flow physics and the difficulty in obtaining accurate experimental results of molecular level phenomena. Sources of uncertainty considered include flow field chemical rate models, molecular band emission, and the excitation/deexcitation rates of molecules modeled with a non-Boltzmann approach. Due to the computational cost of the numerical models, uncertainty quantification was performed with a surrogate modeling approach based on a sparse approximation of the point-collocation nonintrusive polynomial chaos technique. Accurate results were obtained with only 500 samples of the computational model. Baseline results indicated that radiative heating during Titan entry was nearly 10 times greater than that of the predicted radiative heating during Mars entry. These results indicated that worst-case uncertainty intervals of surface radiative heating predictions were as wide as 30 W/cm~2 during Mars entry and 150 W/cm~2 during Titan entry. Global nonlinear sensitivity results show that the contribution of the uncertain parameters to output uncertainty measures changes across the surface during Mars entry, whereas Titan radiation uncertainty is dominated by flow field chemistry uncertainty throughout the flow field.
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The objective of this study was to demonstrate the use of stochastic expansions in the quantification of margins and uncertainties in complex aerospace systems. In this study, stochastic expansions, based on nonintrusive polynomia...
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The objective of this study was to demonstrate the use of stochastic expansions in the quantification of margins and uncertainties in complex aerospace systems. In this study, stochastic expansions, based on nonintrusive polynomial chaos, were utilized for efficient representation of uncertainty both in design metrics and associated performance limits of a system. Additionally, procedures were outlined for analyzing systems that contain different uncertainty types between the performance metrics and performance limits. These methodologies were demonstrated on three model problems, each possessing mixed (epistemic and aleatory) uncertainty, which was propagated through the models using second-order probability. The first was a complex system of highly nonlinear analytical functions. The second was a multisystem, physics based model for spacecraft reentry. The performance metrics consisted of two systems used to determine the maximum g-load, the necessary bank angle correction, and maximum convective heat load along a reentry trajectory. The last model was a multidisciplinary model for the design and analysis of a High Speed Civil Transport. Overall, the methodologies and examples of this work have detailed an approach for measuring the reliability of complex aerospace systems as well as the importance of quantifying margins and uncertainties for the design of reliable systems.
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摘要 :
The objective of this study was to demonstrate the use of stochastic expansions in the quantification of margins and uncertainties in complex aerospace systems. In this study, stochastic expansions, based on nonintrusive polynomia...
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The objective of this study was to demonstrate the use of stochastic expansions in the quantification of margins and uncertainties in complex aerospace systems. In this study, stochastic expansions, based on nonintrusive polynomial chaos, were utilized for efficient representation of uncertainty both in design metrics and associated performance limits of a system. Additionally, procedures were outlined for analyzing systems that contain different uncertainty types between the performance metrics and performance limits. These methodologies were demonstrated on three model problems, each possessing mixed (epistemic and aleatory) uncertainty, which was propagated through the models using second-order probability. The first was a complex system of highly nonlinear analytical functions. The second was a multisystem, physics based model for spacecraft reentry. The performance metrics consisted of two systems used to determine the maximum g-load, the necessary bank angle correction, and maximum convective heat load along a reentry trajectory. The last model was a multidisciplinary model for the design and analysis of a High Speed Civil Transport. Overall, the methodologies and examples of this work have detailed an approach for measuring the reliability of complex aerospace systems as well as the importance of quantifying margins and uncertainties for the design of reliable systems.
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The objective of this study was to perform an uncertainty analysis of the stagnation-point calibration probe surface predictions for a low-enthalpy condition of the Hypersonic Materials Environmental Test System facility located a...
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The objective of this study was to perform an uncertainty analysis of the stagnation-point calibration probe surface predictions for a low-enthalpy condition of the Hypersonic Materials Environmental Test System facility located at NASA Langley Research Center. In this study, a second-order stochastic expansion was constructed over 47 uncertain parameters to evaluate the sensitivities, identify the most significant uncertain variables, and quantify the uncertainty in the stagnation-point heat flux and pressure of the calibration probes. The sensitivity analysis showed that measurement bias uncertainty is the most significant contributor to the stagnation-point pressure and heat flux variance for the low-enthalpy condition. A comparison between the prediction and measurement uncertainty of the stagnation-point conditions showed that there was evidence of statistical disagreement. A validation metric was proposed and applied to the prediction uncertainty to account for the statistical disagreement when compared to the possible stagnation-point heat flux and pressure measurements.
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The objective of this study was to perform an uncertainty analysis of the stagnation-point calibration probe surface predictions for a low-enthalpy condition of the Hypersonic Materials Environmental Test System facility located a...
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The objective of this study was to perform an uncertainty analysis of the stagnation-point calibration probe surface predictions for a low-enthalpy condition of the Hypersonic Materials Environmental Test System facility located at NASA Langley Research Center. In this study, a second-order stochastic expansion was constructed over 47 uncertain parameters to evaluate the sensitivities, identify the most significant uncertain variables, and quantify the uncertainty in the stagnation-point heat flux and pressure of the calibration probes. The sensitivity analysis showed that measurement bias uncertainty is the most significant contributor to the stagnation-point pressure and heat flux variance for the low-enthalpy condition. A comparison between the prediction and measurement uncertainty of the stagnation-point conditions showed that there was evidence of statistical disagreement. A validation metric was proposed and applied to the prediction uncertainty to account for the statistical disagreement when compared to the possible stagnation-point heat flux and pressure measurements.
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The objective of this study was to demonstrate the use of a combined sparse sampling and stochastic expansion approach for efficient and accurate uncertainty quantification of high-fidelity, hypersonic reentry flow simulations, wh...
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The objective of this study was to demonstrate the use of a combined sparse sampling and stochastic expansion approach for efficient and accurate uncertainty quantification of high-fidelity, hypersonic reentry flow simulations, which may contain large numbers of aleatory and epistemic uncertainties. Stochastic expansion coefficients were obtained using the point-collocation non-intrusive polynomial chaos technique under sparse sampling conditions, utilizing a number of samples less than the minimum number required for a total order expansion. This study introduced two methods of measuring the accuracy of the expansion coefficients as well as their convergence with iteratively increasing sample size. The sparse sampling solution technique and accuracy and convergence measures were demonstrated on two model problems. The first was a model for stagnation point, con-vective heat transfer in hypersonic flow. Mixed uncertainty quantification analysis results showed that accurate expansion coefficients could be obtained with half the number of samples required for an analytically obtained total order expansion. The second problem was a high-fidelity, computational fluid dynamics model for radiative heat flux on a Hypersonic Inflatable Aerodynamic Decelerator during Mars entry. The model consisted of 93 uncertain parameters, coming from both flow field and radiation modeling. Results indicated that an accurate surrogate model could be obtained with only about 15% of the number of samples required for a total order expansion when compared to previous work.
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摘要 :
The objective of this study was to demonstrate the use of a combined sparse sampling and stochastic expansion approach for efficient and accurate uncertainty quantification of high-fidelity, hypersonic reentry flow simulations, wh...
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The objective of this study was to demonstrate the use of a combined sparse sampling and stochastic expansion approach for efficient and accurate uncertainty quantification of high-fidelity, hypersonic reentry flow simulations, which may contain large numbers of aleatory and epistemic uncertainties. Stochastic expansion coefficients were obtained using the point-collocation non-intrusive polynomial chaos technique under sparse sampling conditions, utilizing a number of samples less than the minimum number required for a total order expansion. This study introduced two methods of measuring the accuracy of the expansion coefficients as well as their convergence with iteratively increasing sample size. The sparse sampling solution technique and accuracy and convergence measures were demonstrated on two model problems. The first was a model for stagnation point, con-vective heat transfer in hypersonic flow. Mixed uncertainty quantification analysis results showed that accurate expansion coefficients could be obtained with half the number of samples required for an analytically obtained total order expansion. The second problem was a high-fidelity, computational fluid dynamics model for radiative heat flux on a Hypersonic Inflatable Aerodynamic Decelerator during Mars entry. The model consisted of 93 uncertain parameters, coming from both flow field and radiation modeling. Results indicated that an accurate surrogate model could be obtained with only about 15% of the number of samples required for a total order expansion when compared to previous work.
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