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At least 163 records · Page 9

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NASA NTRS2013

Overview of the Aeroelastic Prediction Workshop

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. This workshop's technical focus was prediction of unsteady pressure distributions resulting from forced motion, benchmarking the results first using unforced system data. The most challenging aspects of the physics were identified as capturing oscillatory shock behavior, dynamic shock-induced separated flow and tunnel wall boundary layer influences. The majority of the participants used unsteady Reynolds-averaged Navier Stokes codes. These codes were exercised at transonic Mach numbers for three configurations and comparisons were made with existing experimental data. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include wall effects and wall modeling, non-standardized convergence criteria, inclusion of static aeroelastic deflection, methodology for oscillatory solutions, post-processing methods. Contributing issues pertaining principally to the experimental data sets include the position of the model relative to the tunnel wall, splitter plate size, wind tunnel expansion slot configuration, spacing and location of pressure instrumentation, and data processing methods.

Heeg, Jennifer↗

NASA NTRS2012

Ionospheric Signatures in Radio Occultation Data

We can extend robustly the radio occultation data record by 6 years (+60%) by developing a singlefrequency processing method for GPS/MET data. We will produce a calibrated data set with profile-byprofile data characterization to determine robust upper bounds on ionospheric bias. Part of an effort to produce a calibrated RO data set addressing other key error sources such as upper boundary initialization. Planned: AIRS-GPS water vapor cross validation (water vapor climatology and trends).

radio occultation↗

NASA NTRS1970

Analysis of strapdown sensor testing

Some topics related to dynamic testing of strapdown sensors are analyzed, with emphasis on measuring parameters which give rise to motion-induced error torques in single-degree-of-freedom inertial sensors. The objective is to determine the dynamic inputs, test equipment characteristics and data processing procedures best suited for measuring these parameters. Single axis, low frequency vibration tests and constant rate tests are studied in detail. Methods for analyzing the effects of test motion errors and measurement errors are developed and illustrated by examples. Candidate test data processing methods are compared and recommendations concerning test equipment and data processing are made.

Crawford, B. S.↗

NASA NTRS2003

Detecting Edges in Images by Use of Fuzzy Reasoning

A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image. During initial processing of image data at a low level of abstraction, the nature of the data is indeterminate. Fuzzy reasoning is used in the present method because it affords an ability to construct useful abstractions from approximate, incomplete, and otherwise imperfect sets of data. Humans are able to make some sense of even unfamiliar objects that have imperfect high-level representations. It appears that to perceive unfamiliar objects or to perceive familiar objects in imperfect images, humans apply heuristic algorithms to understand the images

Dominguez, Jesus A.↗

NASA NTRS1984

The Nimbus 7 ERB data set - A critical analysis

An analysis of the first year of the Nimbus 7 earth radiation budget data set reveals that there are systematic differences between wide and narrow field of view measurements. The larger differences appear in the albedo data and are due primarily to a bias introduced by the processing method. There are smaller differences, associated with the outgoing longwave radiation, which are probably due to errors in calibration. The bias in albedo originates in the factors used for converting the shortwave intensity measured at satellite altitude into a mean daily albedo at the top of the atmosphere. The factor that proves most troublesome is the one that converts measured intensity to the total instantaneous outgoing flux. That factor is determined by angular distribution models, which depend upon the type of scene within the target area. An alternative method of processing the data, which is model independent, is shown to have practically no bias and yields better over-all agreement with the wide field of view measurements.

Arking, A.↗

DOE OSTI2024

Exploration of signal processing methods for superconducting magnet and quench data

Quenching is the phenomenon of a superconducting magnetic material carrying current transitioning into a regular conducting material. This may cause severe and irreparable damage to the superconductor due to Joule heating. The Magnet Department at Fermi National Accelerator Laboratory (FNAL) has acquired experimental data through quench antenna arrays that are recorded when the quench is detected. These data are in terms of voltage signals that are sampled at 100kHz for several minutes. There are multiple channels and each channel provides a data set of more than 20 million observations, while there is one channel, called the trigger channel which shows the time when quench is detected. Despite some advancements that were made including machine learning, data complexity still shadows the progress. In this work, we studied a multi-resolution analysis of the quench antenna data through the Haar wavelet transform. In particular, we applied the maximally overlapped discrete w avelet transform (MODWT) of a suitable level L to the given data and then projected it onto the wavelet basis. This decomposes a given signal (Original data) $x ϵ \mathbb{R}^N$ into $L + 1$ subspaces of $\mathbb{R}^N$. One of the subspaces called the approximation, captures the trend of the signal, and the others, called the details, capture the fluctuations at different frequency bands. This decomposition provides a clear trend of the data at a suitable level and also various activities (spikes) are seen in the details of the decomposition at every level. These spikes might reveal some information about the quench under investigation but in any case, give information about magnet behavior. Also, this decomposition is seen to be very useful in removing noise present in the data due to the source or mechanism of the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1973

Iterative techniques to estimate signature vectors for mixture processing of multispectral data

Two methods for obtaining the required spectral signatures for a particular mixture model are considered. For the model considered, the spectral signatures become signature vectors. The first method is based upon determination of the signature vectors in such a way that a measure of the inconsistency between the mixture model and the observed data is minimized. The second method is based upon determination of the signature vectors in such a way that the estimated mean percentage coverage of individual species matches apriori or ground truth estimates. The two methods proposed are applied to actual multispectral data in order to verify the concepts presented.

Salvato, P., Jr.↗

NASA NTRS1989

Data acquisition and processing

Fundamental methods of signal processing used in normal mesosphere stratosphere troposphere (MST) radar observations are described. Complex time series of received signals obtained in each range gate are converted into Doppler spectra, from which the mean Doppler shift, spectral width and signal-to-noise ratio (SNR) are estimated. These spectral parameters are further utilized to study characteristics of scatterers and atmospheric motions.

Tsuda, Toshitaka↗

NASA NTRS2016

Comparison of Cross Correlation and Optical Flow Methods for Processing Retroreflective and Natural Background BOS Data

Background oriented schlieren images have historically been generated by calculating the observed pixel displacement between an image pair using normalized cross-correlation methods. This work uses optical flow data reduction methods to solve the displacement fields. A well established method used in the computer vision community, optical flow is the apparent brightness motion in an image sequence. The regularization method of Horn and Schunck is used to create schlieren images using two data sets: a supersonic shockjet plume interaction at the NASA Ames Unitary Plan Wind Tunnel, and a transonic flight test of a T-38 using a naturally occurring background performed in conjunction with NASA Ames and Armstrong research centers. Results are presented and contrasted with those using normalized cross-correlation methods. The optical flow images are found to provided significantly more detail at a decreased computational time.

schlieren↗

NASA NTRSDate not supplied

Improving “Domain-Relevant Metadata Requirements” for Supporting Open-Source Science Initiative

Implementation of the NASA Open-Source Science Initiative (OSSI) requires sharing of all relevant information to ensure “open reproducible science” [1]. However, there are several challenges in applying the OSSI to airborne field campaigns focused on atmospheric composition, which often involve a wide variety of in-situ measurements for trace gases, aerosol and cloud properties, meteorological parameters, and radiation fields. To ensure open reproducibility from airborne field campaigns, it is essential to obtain detailed measurement descriptions, which include the detection principle, sample procedure and treatment, and data processing and correction method. The challenge is that some information, e.g., sampling procedure and treatment, may be instrument-specific and campaign or platform-dependent. The data processing may also involve empirical corrections which may evolve over time. In addition, these details (especially operation- or campaign-specific ones) are often not given in journal publications. Given these issues, there is a need to leverage and improve the current “domain-relevant metadata requirements” to represent the measurement description in standardized metadata. These requirements can then facilitate systematic collection of measurement specific metadata and serve as a foundation to develop tools for making the information accessible and data more interoperable and usable or reusable. Here we show a review of existing metadata collections, use cases, and needs for new standards.

Sean Leavor↗

NASA NTRSDate not supplied

SAGE III/ISS Validation Methods

Spatiotemporal collocation of measurements between instruments is an essential yet challenging component of the data validation process. Traditional methods of collocation may simply consider length of time and physical distance between measurements. However, the distribution of atmospheric constituents may change rapidly over time and space, so care must be taken to ensure that matched measurements represent the same environment and will not introduce unnecessary bias. More advanced collocation methods may consider additional physical parameters to minimize inappropriate matches with large differences caused by local circulation. We report results of SAGE III/ISS validation with ground-based measurements using advanced collocation methods, and assessments are performed on the quality and presence of trends in both datasets.

Mary Cate McKee↗

NASA NTRS1973

Maximum likelihood identification and optimal input design for identifying aircraft stability and control derivatives

A new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion. It is shown that this new method is capable of processing data from both linear and nonlinear models, both with and without process noise and includes output error and equation error methods as special cases. The first application of this method to flight test data is reported for lateral maneuvers of the HL-10 and M2/F3 lifting bodies, including the extraction of stability and control derivatives in the presence of wind gusts. All the problems encountered in this identification study are discussed. Several different methods (including a priori weighting, parameter fixing and constrained parameter values) for dealing with identifiability and uniqueness problems are introduced and the results given. The method for the design of optimal inputs for identifying the parameters of linear dynamic systems is also given. The criterion used for the optimization is the sensitivity of the system output to the unknown parameters. Several simple examples are first given and then the results of an extensive stability and control dervative identification simulation for a C-8 aircraft are detailed.

Stepner, D. E.↗

NASA NTRS1991

A long-range laser velocimeter

A long-range laser velocimeter (LV) developed for remote operation from within the flow fields of large wind tunnels is described. Emphasis is placed on recent improvements in optical hardware as well as recent additions to data acquisition and processing techniques. The method used for data reduction of photon resolved signals is outlined in detail, and measurement accuracy is discussed. To study the performance of the LV and verify the measurement accuracy, laboratory measurements were made in the flow field of a 10-cm-diameter, 30-m/s axisymetric jet. The measured velocity and turbulence intensity surveys are compared with measurements made with a hot-wire anemometer. Additionally, the LV was used during the flow calibration of the 80-ft x 120-ft wind tunnel to measure the test-section boundary-layer thickness at the maximum wind tunnel speed of 51.5 m/s. The requirements and techniques used to seed the flow are discussed, and boundary-layer surveys of mean velocity and turbulence intensity of the streamwise component and the component normal to the surface are presented. The streamwise component of mean velocity is compared with data obtained with a total pressure rake.

Reinath, Michael S.↗

NASA NTRS1981

Computational aspects of geometric correction data generation in the LANDSAT-D imagery processing

A method is presented for systematic and geodetic correction data calculation. It is based on presentation of image distortions as a sum of nominal distortions and linear effects caused by variation of the spacecraft position and attitude variables from their nominals. The method may be used for both MSS and TM image data and it is incorporated into the processing by means of mostly offline calculations. Modeling shows that the maximal of the method are of the order of 5m at the worst point in a frame; the standard deviations of the average errors less than .8m.

Levine, I.↗

NASA NTRS2004

Hybrid Image-Plane/Stereo Manipulation

Hybrid Image-Plane/Stereo (HIPS) manipulation is a method of processing image data, and of controlling a robotic manipulator arm in response to the data, that enables the manipulator arm to place an end-effector (an instrument or tool) precisely with respect to a target (see figure). Unlike other stereoscopic machine-vision-based methods of controlling robots, this method is robust in the face of calibration errors and changes in calibration during operation. In this method, a stereoscopic pair of cameras on the robot first acquires images of the manipulator at a set of predefined poses. The image data are processed to obtain image-plane coordinates of known visible features of the end-effector. Next, there is computed an initial calibration in the form of a mapping between (1) the image-plane coordinates and (2) the nominal three-dimensional coordinates of the noted end-effector features in a reference frame fixed to the main robot body at the base of the manipulator. The nominal three-dimensional coordinates are obtained by use of the nominal forward kinematics of the manipulator arm that is, calculated by use of the currently measured manipulator joint angles and previously measured lengths of manipulator arm segments under the assumption that the arm segments are rigid, that the arm lengths are constant, and that there is no backlash. It is understood from the outset that these nominal three-dimensional coordinates are likely to contain possibly significant calibration errors, but the effects of the errors are progressively reduced, as described next. As the end-effector is moved toward the target, the calibration is updated repeatedly by use of data from newly acquired images of the end-effector and of the corresponding nominal coordinates in the manipulator reference frame. By use of the updated calibration, the coordinates of the target are computed in manipulator-reference-frame coordinates and then used to the necessary manipulator joint angles to position and orient the end-effector at the target with respect to the same kinematic model from the calibration step. As the end-effector/target distance decreases, the computed coordinates of the end-effector and target become more nearly affected by the same errors, so that the differences between their coordinates become increasingly precise. When the end-effector reaches the target, the remaining effective position error is the distance that corresponds to more than about one pixel in the stereoscopic images of the target.

Baumgartner, Eric↗

DOE OSTI2025

Machine Learning-Driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State

We present a novel machine learning (ML)-based method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditional root-finding techniques are computationally expensive, particularly for large-scale relativistic hydrodynamics simulations. To address this, we employ feedforward neural networks (NNC2PS and NNC2PL), trained in PyTorch (2.0+) and optimized for GPU inference using NVIDIA TensorRT (8.4.1), achieving significant speedups with minimal accuracy loss. The NNC2PS model achieves 𝐿 1 and 𝐿 ∞ errors of 4.54 × 10 −7 and 3.44 × 10−6, respectively, while the NNC2PL model exhibits even lower error values. TensorRT optimization with mixed-precision deployment substantially accelerates performance compared to traditional root-finding methods. Specifically, the mixed-precision TensorRT engine for NNC2PS achieves inference speeds approximately 400 times faster than a traditional single-threaded CPU implementation for a dataset size of 1,000,000 points. Ideal parallelization across an entire compute node in the Delta supercomputer (dual AMD 64-core 2.45 GHz Milan processors and 8 NVIDIA A100 GPUs with 40 GB HBM2 RAM and NVLink) predicts a 25-fold speedup for TensorRT over an optimally parallelized numerical method when processing 8 million data points. Moreover, the ML method exhibits sub-linear scaling with increasing dataset sizes. We release the scientific software developed, enabling further validation and extension of our findings. By exploiting the underlying symmetries within the equation of state, these findings highlight the potential of ML, combined with GPU optimization and model quantization, to accelerate conservative-to-primitive inversion in relativistic hydrodynamics simulations.

conservative-to-primitive conversion↗

NASA NTRS1985

Direct finite element equation solving algorithms

This paper presents and examines direct solution algorithms for the linear simultaneous equations that arise when finite element models represent an engineering system. It identifies the mathematical processing of four solution methods and assesses their data processing implications using concurrent processing.

Melosh, R. J.↗

NASA NTRS1996

Durable High-Density Data Storage

The focus ion beam (FIB) micromilling process for data storage provides a new non-magnetic storage method for archiving large amounts of data. The process stores data on robust materials such as steel, silicon, and gold coated silicon. The storage process was developed to provide a method to insure the long term storage life of data. We estimate that the useful life of data written on silicon or gold-coated silicon to be on the order of a few thousand years without the need to rewrite the data every few years. The process uses an ion beam to carve material from the surface, much like stone cutters in ancient civilizations removed material from stone. The deeper the information is carved into the media, the longer the expected life of the information. The process can record information in three formats: (1) binary at densities of 23 Gbits/square inch, (2) alphanumeric at optical or non-optical density, and (3) graphical at optical and non-optical density. The formats can be mixed on the same media; and thus, it is possible to record, in a human-viewable format, instructions that can be read using an optical microscope. These instructions provide guidance on reading the remaining higher density information.

Lamartine, Bruce C.↗