Development and Validation of a First Principles Fluid-Thermal Multi-Physics Solver for Hypersonic Boundary Layer Heat Transfer Problems

Ostoich, Christopher; Bodony, Daniel J.; Geubelle, Philippe H.

doi:10.2514/6.2011-1964

Cited by 10 publications

(19 citation statements)

References 29 publications

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“…On-going research is investigating models for each of the four aerothermoelastic system components, as well as their integration to study the importance of different types of coupling. 3,4,13 In order to validate these models and quantify the confidence in their predictions, experimental data from this extreme, hypersonic environment is required. A candidate for validation data under these conditions are the experiments performed by Glass and Hunt, in which a series of tests were conducted in a hypersonic wind tunnel to investigate the aerodynamic loads on deformed surface panels.…”

Section: Aerothermal Model Definition and Experimentsmentioning

confidence: 99%

“…For the purposes of this study, the analysis is limited to the points along the centerline parallel to the flow. An investigation by Ostoich et al 4 discovered that the recorded data at points 1 and 38 may have been affected by an uncharacterized gap between the dome and plate, thus only the middle 11 data points along the centerline (points 2 -39) are considered. The flat plate and spherical dome measurements provide substantial validation data for error quantification and confidence assessments.…”

Section: Aerothermal Model Definition and Experimentsmentioning

confidence: 99%

“…For example, aerodynamic pressure and heating could be calculated using a computational fluid dynamics (CFD) model, or the decision could be made to use reduced-order models or the simpler piston theory and Eckert's reference enthalpy method, respectively. 3,4,12,16 Substantial research has been performed on investigating the model components for the physics of a coupled aerothermoelastic panel and the solution procedures for both quasi-static and dynamic solutions. 2,3,6-12 However, the current state of the art focuses on deterministic calculations with limited uncertainty analysis.…”

Section: Introductionmentioning

confidence: 99%

“…However, errors inherently exist in all computational model predictions due to imperfect knowledge and physical variability in the system, model order reduction, assumptions and approximations, and the limited experimental data available for model validation. This initial phase of a broader research objective is focused on quantifying the errors in existing aerothermal model predictions 3,4 corresponding to a set of experiments in a high-temperature wind tunnel. 5 The methods implemented in this paper will be used as a basis for expanding error quantification and prediction confidence assessments to a coupled aerothermoelastic model.…”

Section: Introductionmentioning

confidence: 99%

“…5 These comprehensive and unique experiments were conducted in 1986 by Glass and Hunt in the Langley 8-foot High-Temperature Tunnel (HTT) 5 , and the tests are still used for validation purposes in numerous, on-going research efforts. 3,4 The outline of the paper is as follows. Section II describes the coupled aerothermoelastic problem, as well as the simplified aerothermal model corresponding to the Glass and Hunt HTT experiments.…”

mentioning

confidence: 99%

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Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft

Smarslok¹,

Culler²,

Mahadevan³

2012

53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

34
1
16
0

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Assessing prediction confidence and enabling its use as a decision-making metric for autonomous model fidelity selection is essential to the USAF's vision of a 'Digital Twin' as a viable approach for condition-based fleet management by tail number. Significant strides have been made in modeling complex interactions of the multi-physics, fluid-thermalstructural coupling applicable to hypersonic flow conditions. However, validation of these models remains a challenge due to limited experimental data for hypersonic conditions. This research addresses quantifying errors and assessing the confidence in aerodynamic pressure and heating predictions for a spherical dome protruding from a flat ramp. Wellcharacterized aerothermal test data from hypersonic wind tunnel experiments are used to calibrate uncertain model parameters and quantify errors through Bayesian techniques. A Bayesian hypothesis testing-based confidence metric is employed to compare the accuracy in various model predictions. A model selection study is performed for 1 st -, 2 nd -, and 3 rd -order piston theories. The results showed that the greatest confidence in model predictions does not necessarily correspond to the highest-order model. NomenclatureB = Bayes factor C = Bayesian hypothesis testing-based confidence metric D = diameter of the spherical dome e = model error H = height of the spherical dome M = Mach number p = aerodynamic pressure q = dynamic pressure (ρU 2 /2) Q = aerodynamic heat flux R eq = equivalence ratio (fuel-to-air ratio divided by stoichiometric fuel-to-air ratio) S = main effect sensitivity index S T = total effect sensitivity index T = temperature w = transverse panel displacement x = model prediction, location along dome y = observed data β = oblique shock angle relative to freestream ϕ = uncertain input parameters γ = ratio of specific heats µ = mean π = probability density function 2 θ = panel inclination angle to freestream ρ = density σ = standard deviation Subscripts aw = adiabatic wall e = edge of boundary layer i = variable index, position along spherical dome true = true value of x pred = model prediction of x w = wall, aerodynamic surface 1 = freestream flow 3 = flow at the leading edge of panel 4 = flow at location of interest along the panel Superscripts fp = flat plate sd = spherical dome * = flow properties evaluated at Eckert's reference temperature

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Section: Aerothermal Model Definition and Experimentsmentioning
confidence: 99%

Section: Introductionmentioning
confidence: 99%

mentioning
confidence: 99%

See 3 more Smart Citations
Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft
Smarslok¹,
Culler²,
Mahadevan³
2012
53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
34
1
16
0
View full text Add to dashboard Cite
Assessing prediction confidence and enabling its use as a decision-making metric for autonomous model fidelity selection is essential to the USAF's vision of a 'Digital Twin' as a viable approach for condition-based fleet management by tail number. Significant strides have been made in modeling complex interactions of the multi-physics, fluid-thermalstructural coupling applicable to hypersonic flow conditions. However, validation of these models remains a challenge due to limited experimental data for hypersonic conditions. This research addresses quantifying errors and assessing the confidence in aerodynamic pressure and heating predictions for a spherical dome protruding from a flat ramp. Wellcharacterized aerothermal test data from hypersonic wind tunnel experiments are used to calibrate uncertain model parameters and quantify errors through Bayesian techniques. A Bayesian hypothesis testing-based confidence metric is employed to compare the accuracy in various model predictions. A model selection study is performed for 1 st -, 2 nd -, and 3 rd -order piston theories. The results showed that the greatest confidence in model predictions does not necessarily correspond to the highest-order model. NomenclatureB = Bayes factor C = Bayesian hypothesis testing-based confidence metric D = diameter of the spherical dome e = model error H = height of the spherical dome M = Mach number p = aerodynamic pressure q = dynamic pressure (ρU 2 /2) Q = aerodynamic heat flux R eq = equivalence ratio (fuel-to-air ratio divided by stoichiometric fuel-to-air ratio) S = main effect sensitivity index S T = total effect sensitivity index T = temperature w = transverse panel displacement x = model prediction, location along dome y = observed data β = oblique shock angle relative to freestream ϕ = uncertain input parameters γ = ratio of specific heats µ = mean π = probability density function 2 θ = panel inclination angle to freestream ρ = density σ = standard deviation Subscripts aw = adiabatic wall e = edge of boundary layer i = variable index, position along spherical dome true = true value of x pred = model prediction of x w = wall, aerodynamic surface 1 = freestream flow 3 = flow at the leading edge of panel 4 = flow at location of interest along the panel Superscripts fp = flat plate sd = spherical dome * = flow properties evaluated at Eckert's reference temperature
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Quantifying Confidence in Model Predictions for Hypersonic Aircraft Structures
Smarslok¹
2015
2
0
0
0
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Lack of confidence in structural response and life predictions of a vehicle exposed to combined extreme environments has consistently prevented the USAF from fielding affordable, reliable, and reusable hypersonic space access platforms. Significant strides have been made in modeling complex interactions of the multi-physics, fluid-thermal-structural coupling applicable to hypersonic flow conditions. However, validation of these models remains a challenge due to limited experimental data for hypersonic conditions. This research addresses fundamental and critical issues in quantifying uncertainty and assessing the confidence in model predictions of hypersonic structural response through a systematic framework. The first year of this research focused on identifying and developing the components of the model uncertainty framework for aerodynamic pressure and heating predictions, including global sensitivity analysis, Bayesian model calibration, and validation metric comparison. The second year emphasized effectively integrating information into the coupled system through segmented Bayesian model calibration. The final year brought together model discrepancy in aerodynamic pressure calibrated from aerothermal experiments with nonlinear structural dynamic reduced order models to investigate the uncertainty and sensitivity in coupled aeroelastic response (i.e., flutter and limit cycle oscillation). ix Approved for public release; distribution unlimited. Approved for public release; distribution unlimited. 1.1 Uncertainty Quantification and Model Prediction Confidence Assessment Quantifying the confidence in model prediction consists of two intertwined, yet distinct, activities: uncertainty quantification (UQ) and verification and validation (V&V). The science of uncertainty quantification for numerical simulations (i.e., the quantitative characterization and reduction of uncertainties) has origins dating back to the early-1990's. However, over the past decade there has been a surge in multiple research communities towards formalizing and generalizing the process. Thus, there are now multiple descriptions and implementations of the UQ and V&V processes that are all similar in their objectives, but different in their details. Due to the nature of UQ and V&V research, it is necessary to establish terminology and research scope. Uncertainty is inherent in all computational model predictions due to imperfect knowledge and physical variability in the system, model order reduction, assumptions and approximations, and the limited experimental data available for model calibration and validation. This is especially the case for compliant structures in hypersonic environments due to the complex and poorly-understood loading and the coupled multi-physics nature of the fluidthermal-structural interaction. Physical variability is incorporated in fluid-thermal-structural models through variations in material properties, geometry, boundary conditions, and load interactions. The aerothermoelastic model prediction also has both model-for...

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Fluid-Thermal Response of Spherical Dome Under a Mach 6.59 Laminar Boundary Layer
Ostoich
¹
,
Bodony
²
,
Geubelle
³

2012
AIAA Journal
36
2
28
0
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Development and Validation of a First Principles Fluid-Thermal Multi-Physics Solver for Hypersonic Boundary Layer Heat Transfer Problems

Cited by 10 publications

References 29 publications

Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft

Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft

Quantifying Confidence in Model Predictions for Hypersonic Aircraft Structures

Fluid-Thermal Response of Spherical Dome Under a Mach 6.59 Laminar Boundary Layer

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