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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Transition Analysis for the CRM-NLF Wind Tunnel Configuration using Transport Equation Models and Linear Stability Correlations

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework rely upon transition correlations that were derived from a limited number of low-speed experiments. Furthermore, these models often account for only a subset of the relevant transition mechanisms and/or cannot accurately predict the sensitivity of those mechanisms to the changes in significant flow parameters. A preceding investigation had targeted the assessment of the transport-equation-based transition models in NASA's OVERFLOW 2.3b solver, namely, the amplification factor transport (AFT-2017b) equation model coupled with the Spalart-Allmaras RANS model and the Langtry-Menter transition models (LM2009 without crossflow effects and LM2015 including the modeling of crossflow transition) implemented with Menter’s shear-stress transport equation (SST2003) RANS model. Comparisons with recent measurements at transonic freestream conditions on the Common Research Model with Natural Laminar Flow (CRM-NLF) reinforced our earlier finding that all three of the above models significantly underpredict the reported extent of the laminar flow region over the entire span of the wing, regardless of the dominant instability mechanism(s) underlying the onset of the transition process. The underprediction of the laminar flow extent was attributed to the failure of the above models in accounting for the stabilizing effect of compressibility on the amplification of Tollmien-Schlichting instabilities. Based on previous linear stability studies related to compressibility effects, the present work proposes modifications to the two classes of transition models that reduce to the original form of each model at low subsonic speeds and do not require any nonlocal flow information or additional transport equation(s). The modifications are shown to significantly improve the predicted laminar extent of the flow and compare well against the data from the CRM-NLF experiment. Additionally, a previous assessment of transition prediction based on the dual, nonparallel N -factor method in conjunction with linear parabolized stability equations (PSE) is extended to additional angles of attack to provide the first comprehensive assessment of transition models based on nonparallel disturbance amplification over the CRM-NLF. In general, the transition criterion based on the dual, nonparallel N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at R eMAC = 15 million for all angles of attack investigated herein and provides additional validation of the improved predictions from the compressibility-corrected transition models.

CFD modeling↗
NASA NTRS2022

Transition Analysis for the CRM-NLF Wind Tunnel Configuration using Transport Equation Models and Linear Stability Correlations

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework rely upon transition correlations that were derived from a limited number of low-speed experiments. Furthermore, these models often account for only a subset of the relevant transition mechanisms and/or cannot accurately predict the sensitivity of those mechanisms to the changes in significant flow parameters. A preceding investigation had targeted the assessment of the transport-equation-based transition models in NASA's OVERFLOW 2.3b solver, namely, the amplification factor transport (AFT-2017b) equation model coupled with the Spalart-Allmaras RANS model and the Langtry-Menter transition models (LM2009 without crossflow effects and LM2015 including the modeling of crossflow transition) implemented with Menter’s shear-stress transport equation (SST2003) RANS model. Comparisons with recent measurements at transonic freestream conditions on the Common Research Model with Natural Laminar Flow (CRM-NLF) reinforced our earlier finding that all three of the above models significantly underpredict the reported extent of the laminar flow region over the entire span of the wing, regardless of the dominant instability mechanism(s) underlying the onset of the transition process. The underprediction of the laminar flow extent was attributed to the failure of the above models in accounting for the stabilizing effect of compressibility on the amplification of Tollmien-Schlichting instabilities. Based on previous linear stability studies related to compressibility effects, the present work proposes modifications to the two classes of transition models that reduce to the original form of each model at low subsonic speeds and do not require any nonlocal flow information or additional transport equation(s). The modifications are shown to significantly improve the predicted laminar extent of the flow and compare well against the data from the CRM-NLF experiment. Additionally, a previous assessment of transition prediction based on the dual, nonparallel N -factor method in conjunction with linear parabolized stability equations (PSE) is extended to additional angles of attack to provide the first comprehensive assessment of transition models based on nonparallel disturbance amplification over the CRM-NLF. In general, the transition criterion based on the dual, nonparallel N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at R eMAC = 15 million for all angles of attack investigated herein and provides additional validation of the improved predictions from the compressibility-corrected transition models.

CFD modeling↗
NASA NTRS1990

Component model reduction via the projection and assembly method

This paper explains the projection and assembly model reduction method which has been used to derive reduced order component models for the Galileo spacecraft. Assembly of reduced order component models produces a reduced order system model which can then be used in multibody simulation codes for efficient run times. The methodology is explained and a proof is given showing the exact reproduction of selected significant system modes. Frequency bounds are obtained for all modes produced when the reduced order components are assembled. The projection and assembly method is demonstrated on two examples. The first example is a simplified model of the Galileo spacecraft, while the second example is the model of the Galileo spacecraft in its early mission configuration. When articulation of components is allowed, the method may not reproduce all system modes precisely. Remedies for this problem are suggested.

Kissel, Glen J.↗
NASA NTRS1990

State reduction for semi-Markov reliability models

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model construction and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. Automatic model generation programs have been written to help the reliability analyst produce models of complex systems. Because of the importance of these programs, the model reduction technique needs to be precise and easily implemented. This paper presents a model reduction technique called trimming that can be applied to a popular class of systems. An error bound for the trimming procedure is derived that uses readily available system parameters. The trimming procedure is precisely described and appears easy to implement in a model generation program.

Reduced order systems↗
NASA NTRS1959

Effects of Outboard Thickened and Blunted Leading Edges on the Wave Drag of a 45 Degree Swept-Wing and Body Combination

An investigation to evaluate the effects of thickened and blunted leading-edge modifications on the wave drag of a swept wing has been made at Mach numbers from 0.65 to 2.20 and at a Reynolds number of 2,580,000 based on the mean aerodynamic chord of the basic wing. Two leading-edge designs were investigated and they are referred to as the thickened and the blunted modifications although both sections had equally large leading-edge radii. The thickened leading edge was formed by increasing the thickness over the forward 40 percent of the basic wing section. The blunted modification was formed by reducing the wing chords about 1 percent and by increasing the section thickness slightly over the forward 6 percent of the basic section in a manner to keep the wing sweep and volume essentially equal to the respective values for the basic wing. The basic wing had an aspect ratio of 3, a leading-edge sweep of 45 deg., a taper ratio of 0.4, and NACA 64AO06 sections perpendicular to a line swept back 39.45 deg., the quarter-chord line of these sections. Test results indicated that the thickened modification resulted in an increase in zero-lift drag coefficient of from 0.0040 to 0.0060 over values for the basic model at Mach numbers at which the wing leading edge was sonic or supersonic. Although drag coefficients of both the basic and thickened models were reduced at all test Mach numbers by body indentations designed for the range of Mach numbers from 1.00 to 2.00, the greater drag of the thickened model relative to that of the basic model was not reduced. The blunted model, however, had less than one quarter of the drag penalty of the thickened model relative to the basic model at supersonic leading-edge conditions (M greater or equal to root-2).

Holdaway, George H.↗
NASA NTRS2012

Uncertainty Due to Unsteady Fluid/Structure Interaction for the Ares I Vehicle Traversing the Transonic Regime

Rapid reduced-order numerical models are being investigated as candidates to simulate the dynamics of a flexible launch vehicle during atmospheric ascent. There has also been the extension of these new approaches to include gust response. These methods are used to perform aeroelastic and gust response analyses at isolated Mach numbers. Such models require a method to time march through a succession of ascent Mach numbers. An approach is presented for interpolating reduced-order models of the unsteady aerodynamics at successive Mach numbers. The transonic Mach number range is considered here since launch vehicles can suffer the highest dynamic loads through this range. Realistic simulations of the flexible vehicle behavior as it traverses this Mach number range are presented. The response of the vehicle due to gusts is computed. Uncertainties in root mean square and maximum bending moment and crew module accelerations are presented due to assumed probability distributions in design parameters, ascent flight conditions, gusts. The primary focus is on the uncertainty introduced by modeling fidelity. It is found that an unsteady reduced order model produces larger excursions in the root mean square loading and accelerations than does a quasi-steady reduced order model.

Bartels, Robert E.↗
NASA NTRS2003

Aeroelastic System Development Using Proper Orthogonal Decomposition and Volterra Theory

This research combines Volterra theory and proper orthogonal decomposition (POD) into a hybrid methodology for reduced-order modeling of aeroelastic systems. The out-come of the method is a set of linear ordinary differential equations (ODEs) describing the modal amplitudes associated with both the structural modes and the POD basis functions for the uid. For this research, the structural modes are sine waves of varying frequency, and the Volterra-POD approach is applied to the fluid dynamics equations. The structural modes are treated as forcing terms which are impulsed as part of the uid model realization. Using this approach, structural and uid operators are coupled into a single aeroelastic operator. This coupling converts a free boundary uid problem into an initial value problem, while preserving the parameter (or parameters) of interest for sensitivity analysis. The approach is applied to an elastic panel in supersonic cross ow. The hybrid Volterra-POD approach provides a low-order uid model in state-space form. The linear uid model is tightly coupled with a nonlinear panel model using an implicit integration scheme. The resulting aeroelastic model provides correct limit-cycle oscillation prediction over a wide range of panel dynamic pressure values. Time integration of the reduced-order aeroelastic model is four orders of magnitude faster than the high-order solution procedure developed for this research using traditional uid and structural solvers.

Lucia, David J.↗
NASA NTRS1991

Krylov model reduction algorithm for undamped structural dynamics systems

Krylov vectors furnish an efficient basis for eigenvalue analysis and model reduction of structural dynamics systems. The reduced-order model obtained by the present Krylov model-reduction algorithm for an undamped structural-dynamics system is found to match low-frequency moments. The transformed system equation in Krylov coordinates reflects the structure of a tandem system.

Craig, Roy R., Jr.↗
NASA NTRS2022

NASA Engineering and Safety Center Technical Bulletin No. 22-04: Uncertainty Quantification of Reduced Order Structural Dynamic Models

Uncertainty quantification (UQ) provides statistical bounds on prediction accuracy based on finite element model (FEM) uncertainty. An alternate method for UQ, called the Hybrid Parametric Variation (HPV) combines a parametric variation of the Hurty/Craig-Bampton (HCB) fixed-interface (FI) modal frequencies with a nonparametric variation (NPV) method. This provides a UQ method that can be traced to test data, which can be updated as additional data and improved correlated models become available.

Uncertainty Quantification↗
NASA NTRSDate not supplied

AeroFusion: Data Fusion and Uncertainty Quantification for Entry Vehicles

AeroFusion is a NASA Langley initiative to incorporate advances in data science into the aerodynamic modeling process to improve efficiency. The effort can largely be categorized in three components: reduced-order modeling techniques, surrogate modeling techniques, and uncertainty quantification. By combining various methods from these categories, AeroFusion aims to reduce the development cost of aerodynamic models, both in terms of time and money.

Steven Snyder↗
NASA NTRSDate not supplied

AeroFusion: Data Fusion and Uncertainty Quantification for Entry Vehicles

AeroFusion is a NASA Langley initiative to incorporate advances in data science into the aerodynamic modeling process to improve efficiency. The effort can largely be categorized in three components: reduced-order modeling techniques, surrogate modeling techniques, and uncertainty quantification. By combining various methods from these categories, AeroFusion aims to reduce the development cost of aerodynamic models, both in terms of time and money.

Steven Snyder↗
NASA NTRSDate not supplied

Topographic Slant Range Modeling and Fault Detection for Precision Planetary Landing

This work presents a novel landing site relative topographic measurement model for aslant range sensor being utilized for precision planetary landing operations. The measurement model accounts for the local terrain the slant range sensor captures and leverages knowledge of the estimated landing site provided by the navigation filter. Notably, in contrast to previous works, the new model does not rely on surface normal approximation, reducing the model’s sensitivity to noisy digital elevation maps which represent the local topography. In addition to the measurement model, this work introduces a novel fault detection method, denoted the probabilistic inspection of topographic filter altitude likelihood (PITFAL) algorithm, that implements a statistical outlier rejection algorithm. PITFAL is designed for multi-beam slant range sensors, such as the Navigation Doppler LIDAR (NDL), and identifies statistically inconsistent range estimates through a consensus check on the set of apparent altitudes computed for each individual beam. These models are numerically validated by the Safe and Precise Landing Capability Evolution (SPLICE) project’s high-fidelity terrestrial and lunar lander simulations.

Davis W Adams↗
NASA NTRS2025

Topographic Slant Range Modeling and Fault Detection for Precision Planetary Landing

This work presents a novel landing site relative topographic measurement model for aslant range sensor being utilized for precision planetary landing operations. The measurement model accounts for the local terrain the slant range sensor captures and leverages knowledge of the estimated landing site provided by the navigation filter. Notably, in contrast to previous works, the new model does not rely on surface normal approximation, reducing the model’s sensitivity to noisy digital elevation maps which represent the local topography. In addition to the measurement model, this work introduces a novel fault detection method, denoted the probabilistic inspection of topographic filter altitude likelihood (PITFAL) algorithm, that implements a statistical outlier rejection algorithm. PITFAL is designed for multi-beam slant range sensors, such as the Navigation Doppler LIDAR (NDL), and identifies statistically inconsistent range estimates through a consensus check on the set of apparent altitudes computed for each individual beam. These models are numerically validated by the Safe and Precise Landing Capability Evolution (SPLICE) project’s high-fidelity terrestrial and lunar lander simulations.

Davis W Adams↗
NASA NTRS1982

Analysis of driver performance under reduced visibility

Mathematical models describing vehicle dynamics as well as human behavior may be useful in evaluating driver performance and in establishing design criteria for vehicles more compatible with man. In 1977, a two level model of driver steering behavior was developed, but its parameters were identified for clear visibility conditions only. Since driver performance degrades under conditions of reduced visibility, e.g., fog, the two level model should be investigated to determine its applicability to such conditions. The data analysis of a recently performed driving simulation experiment showed that the model still performed reasonably well under fog conditions, although there was a degradation in its predictive capacity during fog. Some additional parameters affecting anticipation and lag time may improve the model's performance for reduced visibility conditions.

Kaeppler, W. D.↗