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NASA NTRS2019

Aero-Structural Modeling of the Truss-Braced Wing Aircraft Using Potential Method with Correction Methods for Transonic Viscous Flow and Wing-Strut Interference Aerodynamics

This paper describes an aero-structural modeling method for the Transonic Truss-Braced Wing (TTBW) aircraft using VSPAERO. A vortex-lattice model of the TTBW aircraft is developed, and a transonic and viscous flow correction method is implemented in the VSPAERO models to account for transonic and viscous flow effects. A correction method for the wing-strut interference aerodynamics is developed and applied to the VSPAERO solver. Also, a structural dynamic finite-element model of the TTBW aircraft is developed. This finite-element model includes the geometric nonlinear effect due to the tension in the struts which cause a deflection dependent nonlinear stiffness. The VSPAERO models are coupled to the finite-element model to provide a rapid capability for aero-structural modeling and flutter analysis. A flight-optimized jig twist model is being developed and will be applied for the purpose of generating a full flight dynamic model of the TTBW aircraft.

Fugate, Jason↗

NASA NTRS2019

A Correction Method for Unsteady Transonic Aerodynamics

This paper presents a new method for transonic pitching airfoils based on a RANS CFD study and the Theodorsen model of an oscillating pitching flat plate. This study quantifies the deviation of the lift coefficient predictions using CFD from that obtained using the Theodorsen model, which is based on the incompressible potential flow assumption. The present method corrects this theoretical model by modulating the Theodorsen functions by coefficient functions that depend on the reduced frequency and the Mach number. It is demonstrated that the modified theoretical model predicts lift coefficient in good agreement with the CFD results in the Mach number range from incompressible (M =0.2) to transonic (M =0.755) flow for a range of reduced frequencies typical of transonic flutter. The simulations are first validated by comparing pitching NACA0012 airfoil results with experimental results at transonic flight conditions, which establishes the requirements for a grid converged unsteady transonic solution. The hysteresis loop, Cl versus α, attains a grid independent solution that compares well with experiment. The present correction method will guide the development of a new state space model for the Variable Camber Continuous Trailing Edge Flap (VCCTEF) system and eventually a new transfer function that will be incorporated in a new aeroelastic framework leading to an appropriate transonic flutter model for use in the future aircraft systems in development under the NASA Advanced Air Transportation Technologies (AATT) project.

Kaul, Upender K.↗

NASA NTRSDate not supplied

Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets

RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.

Lauren M. Sanders↗

NASA NTRS1993

Laboratory spectra of field samples as a check on two atmospheric correction methods

Atmospheric correction is the first step toward quantitative analysis of imaging spectroscopy data. Two methods, MODTRAN model and the empirical line, were used to convert AVIRIS radiance values to reflectance values. A set of laboratory spectra of field samples corresponding to AVIRIS coverage was used to assess these methods. This will also serve to select bands for future quantative analyses.

Xu, Pung↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

NASA NTRSDate not supplied

Combining RNA-SEQ Datasets from NASA GENELAB: An Evaluation of Correction Methods

Background: Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. Methods: In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, the median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. Results: The results showed that the reference-based approach introduced several additional (and likely artificial) differentially expressed genes when compared with the respective standard approach. Conclusions: Of the methods tested, standard ComBat_seq and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

Finsam Samson↗

NASA NTRS1992

Experimental results on a wall interference correction method with interface measurements

A wall interference assessment and correction method for subsonic two-dimensional wind tunnel testing is presented. This method calculates a pressure coefficient and angle of attack correction based on velocity measurements on interfaces inside of the wind tunnel. A mathematical representation of the test article is not required. An experimental verification of the suggested technique is given. A NACA 0012 airfoil is tested at a Mach number of 0.70 and at two different angles of attack. Calculated blockage corrections show reasonable agreement with results based on Hackett's method. Corrected surface pressures compare favorably to free-air flow field data if the tunnel flow field is subsonic. The present wall interference correction method can be applied to transonic tunnel flow fields with some restrictions. Errors are estimated and it is shown that the expected error in calculating the pressure coefficient correction on the model surface is in the order of the error of pressure coefficient measurement on interfaces. Necessary testing equipment in existing tunnels can easily be modified if the present method is applied.

Lo, C. F.↗

NASA NTRS2019

Extending A Correction Method for Unsteady Transonic Aerodynamics to Variable Camber Continuous Trailing Edge Flap

In this study, we have extended our correction method for transonic aerodynamics to baseline and variable camber continuous trailing edge (VCCTEF) geometries of super-critical airfoils at cruise conditions. This correction method modifies Theodorsen theory, which is based on incompressible potential flow over a flat plate. The method is partly based on CFD RANS simulations of oscillating NASA generic transport model (GTM) baseline cruise and VCCTEF airfoil geometries in pitch and shows promise for addressing transonic flutter problems of aeroelasticity. In the earlier study1, the Theodorsen functions were modulated with non-linear functions of Mach number, M, and reduced frequency, k, and thus the correction was demonstrated for the symmetrical NACA0012 airfoil. In the present study, the modulation functions are also allowed to account for the effects of camber and thickness of the airfoil. This is demonstrated by applying the correction method to various symmetric NACA00xx airfoil geometries (NACA001, NACA0002, NACA0012, NACA0015 and NACA0018), the NASA GTM super-critical baseline and VCCTEF airfoil geometries, e.g., the circular airfoil, VCCTEF222. First results indicate that the correction method accounts for a large variation of thickness of airfoils and camber. The present correction method will guide the development of a new state space model for the VCCTEF system and eventually a new transfer function that will be incorporated in a new aeroelastic framework leading to an appropriate transonic flutter model for use in the future aircraft systems in development under the NASA Advanced Air Transportation Technologies (AATT) project.

Kaul, Upender K.↗

NASA NTRS1995

Modal Correction Method For Dynamically Induced Errors In Wind-Tunnel Model Attitude Measurements

This paper describes a method for correcting the dynamically induced bias errors in wind tunnel model attitude measurements using measured modal properties of the model system. At NASA Langley Research Center, the predominant instrumentation used to measure model attitude is a servo-accelerometer device that senses the model attitude with respect to the local vertical. Under smooth wind tunnel operating conditions, this inertial device can measure the model attitude with an accuracy of 0.01 degree. During wind tunnel tests when the model is responding at high dynamic amplitudes, the inertial device also senses the centrifugal acceleration associated with model vibration. This centrifugal acceleration results in a bias error in the model attitude measurement. A study of the response of a cantilevered model system to a simulated dynamic environment shows significant bias error in the model attitude measurement can occur and is vibration mode and amplitude dependent. For each vibration mode contributing to the bias error, the error is estimated from the measured modal properties and tangential accelerations at the model attitude device. Linear superposition is used to combine the bias estimates for individual modes to determine the overall bias error as a function of time. The modal correction model predicts the bias error to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment.

Buehrle, R. D.↗

NASA NTRS2015

Laser Radar Through the Window (LRTW) Coordinate Correction Method

A method for corrections of measurements of points of interests measured by beams of radiation propagating through stratified media including performance of ray-tracing of at least one ray lunched from a metrology instrument in a direction of an apparent point of interest, calculation a path length of the ray through stratified medium, and determination of coordinates of true position of the point interest using the at least one path length and the direction of propagation of the ray.

Hayden, Joseph Ethan↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗

NASA NTRS1968

Differential correction methods in spacecraft attitude determination

Crocker, J. P.↗

NASA NTRS1968

Error correcting method and apparatus Patent

Description of error correcting methods for use with digital data computers and apparatus for encoding and decoding digital data

Anderson, T. O.↗

NASA NTRSDate not supplied

Transonic Correction Method for Flight Dynamic Stability Analysis of Mach 0.745 Transonic Truss-Braced Wing

This paper presents a transonic correction method for obtaining dynamic stability derivatives for flight dynamic stability analysis. The method provides a transonic correction to the Theodorsen's theory of unsteady aerodynamics using FUN3D CFD solver of unsteady Reynolds-averaged Navier-Stokes equations (RANS) for a series of wing sections of the Mach 0.745 Transonic Truss-Braced Wing in pitch and plunge oscillations. Unsteady lift and pitching moment coefficients are obtained and used to develop the correction terms in the Theodorsen's theory to account for transonic aerodynamics. The unsteady lift and pitching moment derivatives with respect to the unsteady angle of attack are obtained as frequency response functions of the reduced frequency. These frequency response functions are used to compute the dynamic stability derivatives of lift and pitching moment due to the angle of attack and pitch rate and the dynamic stability derivatives for the rolling moment and yawing moment with respect to the roll rate and yaw rate. A transonic correction is applied to steady-state stability derivatives computed by VSPAERO solver using transonic small disturbance code TSFOIL coupled to an integral boundary method. A dynamic stability analysis is conducted for longitudinal and lateral-directional motions. Without transonic corrections and dynamic stability derivatives, the analysis indicates an unstable phugoid mode. The transonic correction applied to the steady-state stability derivatives computed by VSPAERO shows a stable phugoid mode. This is due to the increase of the drag stability derivatives as a result of the additional wave drag contribution in transonic flow. The effect of the transonic dynamic stability derivatives is observed to be a significant contributor to the increase in the damping values of all the flight dynamic modes of the Mach 0.745 Transonic-Truss Braced Wing.

Transonic↗

NASA NTRS1986

An entropy correction method for unsteady full potential flows with strong shocks

An entropy correction method for the unsteady full potential equation is presented. The unsteady potential equation is modified to account for entropy jumps across shock waves. The conservative form of the modified equation is solved in generalized coordinates using an implicit, approximate factorization method. A flux-biasing differencing method, which generates the proper amounts of artificial viscosity in supersonic regions, is used to discretize the flow equations in space. Comparisons between the present method and solutions of the Euler equations and between the present method and experimental data are presented. The comparisons show that the present method more accurately models solutions of the Euler equations and experiment than does the isentropic potential formulation.

Whitlow, W., Jr.↗

NASA NTRS1986

An entropy correction method for unsteady full potential flows with strong shocks

Whitlow, W., Jr.↗

NASA NTRS2012

Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods

The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km×10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Landsat↗

NASA NTRS2005

Statistical Calibration and Validation of a Homogeneous Ventilated Wall-Interference Correction Method for the National Transonic Facility

Wind tunnel experiments will continue to be a primary source of validation data for many types of mathematical and computational models in the aerospace industry. The increased emphasis on accuracy of data acquired from these facilities requires understanding of the uncertainty of not only the measurement data but also any correction applied to the data. One of the largest and most critical corrections made to these data is due to wall interference. In an effort to understand the accuracy and suitability of these corrections, a statistical validation process for wall interference correction methods has been developed. This process is based on the use of independent cases which, after correction, are expected to produce the same result. Comparison of these independent cases with respect to the uncertainty in the correction process establishes a domain of applicability based on the capability of the method to provide reasonable corrections with respect to customer accuracy requirements. The statistical validation method was applied to the version of the Transonic Wall Interference Correction System (TWICS) recently implemented in the National Transonic Facility at NASA Langley Research Center. The TWICS code generates corrections for solid and slotted wall interference in the model pitch plane based on boundary pressure measurements. Before validation could be performed on this method, it was necessary to calibrate the ventilated wall boundary condition parameters. Discrimination comparisons are used to determine the most representative of three linear boundary condition models which have historically been used to represent longitudinally slotted test section walls. Of the three linear boundary condition models implemented for ventilated walls, the general slotted wall model was the most representative of the data. The TWICS code using the calibrated general slotted wall model was found to be valid to within the process uncertainty for test section Mach numbers less than or equal to 0.60. The scatter among the mean corrected results of the bodies of revolution validation cases was within one count of drag on a typical transport aircraft configuration for Mach numbers at or below 0.80 and two counts of drag for Mach numbers at or below 0.90.

Walker, Eric Lee↗