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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Time Domain Tool Validation Using ARES I-X Flight Data

The ARES I-X vehicle was launched from NASA's Kennedy Space Center (KSC) on October 28, 2009 at approximately 11:30 EDT. ARES I-X was the first test flight for NASA s ARES I launch vehicle, and it was the first non-Shuttle launch vehicle designed and flown by NASA since Saturn. The ARES I-X had a 4-segment solid rocket booster (SRB) first stage and a dummy upper stage (US) to emulate the properties of the ARES I US. During ARES I-X pre-flight modeling and analysis, six (6) independent time domain simulation tools were developed and cross validated. Each tool represents an independent implementation of a common set of models and parameters in a different simulation framework and architecture. Post flight data and reconstructed models provide the means to validate a subset of the simulations against actual flight data and to assess the accuracy of pre-flight dispersion analysis. Post flight data consists of telemetered Operational Flight Instrumentation (OFI) data primarily focused on flight computer outputs and sensor measurements as well as Best Estimated Trajectory (BET) data that estimates vehicle state information from all available measurement sources. While pre-flight models were found to provide a reasonable prediction of the vehicle flight, reconstructed models were generated to better represent and simulate the ARES I-X flight. Post flight reconstructed models include: SRB propulsion model, thrust vector bias models, mass properties, base aerodynamics, and Meteorological Estimated Trajectory (wind and atmospheric data). The result of the effort is a set of independently developed, high fidelity, time-domain simulation tools that have been cross validated and validated against flight data. This paper presents the process and results of high fidelity aerospace modeling, simulation, analysis and tool validation in the time domain.

Hough, Steven↗
NASA NTRS2011

Development of a NASA 6-U Satellite

NASA/Wallops Flight Facility has focused on the development of new technologies for the advancement of 6 Unit (6U) small satellites. From the design of the structure and instrument support hardware to improvements in the deployer, NASA is concentrating on maximizing the potential of small satellites for the benefit of science. The telemetry system provides much higher data rates than typical I U UHF system. 6U provides up to several hundred kilobits per second and utilizes the existing NASA Ground Network for data reception. The guidance, navigation and control system keeps the satellite pointed within plus or minus 10 degrees of the sun and has knowledge of the sun vector within 1 degree. The 6U power design increased the options for different voltages and power switching capabilities and is capable of supporting instruments with higher power requirements. The Command & Data Handling (C&DH) system includes a low-power 520 MHz flight processor which provides more processing capability than existing I U processor technologies. These optimized technologies will offer the science community a greater opportunity for flying more sophisticated and complex instruments.

Thompson, Linda D.↗
DOE OSTI2018

Unsupervised learning about 4D features of microparticle motion

Material clusters of different sizes are known to exist in high-temperature plasmas due to plasma-wall interactions. The facts that these clusters, ranging from sub-microns to above mm in size, can move from one location to another quickly and that there are a lot of them make high-speed imaging and tracking one of the best, effective, and sometimes only diagnostic. An unsupervised machine learning technique based on deconvolutional neural networks is developed to analyze two-camera videos of high-temperature microparticles generated from exploding wires. The neural network utilizes a locally competitive algorithm to infer representations and optimize a dictionary composed of kernels, or basis vectors, for image analysis. Our primary goal is to use this method for feature recognition and prediction of the time-dependent three-dimensional (or “4D”) microparticle motion. Features equivalent to local velocity vectors have been identified as the dictionary kernels or “building blocks” of the scene. The dictionary elements from the left and right camera views are found to be strongly correlated and satisfy the projection geometrical constraints. The results show that unsupervised machine learning techniques are promising approaches to process large sets of images for high-temperature plasmas and other scientific experiments. In conclusion, machine learning techniques can be useful to handle the large amount of data and therefore aid the understanding of plasma-wall interaction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Tracking ultrafast non-adiabatic dissociation dynamics of the deuterated water dication molecule

Here, we applied reaction microscopy to elucidate fast non-adiabatic dissociation dynamics of deuterated water molecules after direct photo-double ionization at 61 eV with synchrotron radiation. For the very rare D + + O + + D breakup channel, the particle momenta, angular, and energy distributions of electrons and ions, measured in coincidence, reveal distinct electronic dication states and their dissociation pathways via spin–orbit coupling and charge transfer at crossings and seams on the potential energy surfaces. Notably, we could distinguish between direct and fast sequential dissociation scenarios. For the latter case, our measurements reveal the geometry and orientation of the deuterated water molecule with respect to the polarization vector that leads to this rare 3-body molecular breakup channel. Aided by multi-reference configuration-interaction calculations, the dissociation dynamics could be traced on the relevant potential energy surfaces and particularly their crossings and seams. This approach also unraveled the ultrafast time scales governing these processes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Impact of longitudinal phase-matching variations on three-wave nonlinear interactions

A general study of three-wave nonlinear mixing in the presence of longitudinal variations in phase-matching conditions is presented. The efficiency of second-harmonic generation and optical parametric amplification is quantified using a normalized set of equations and a polynomial description of the wave-vector mismatch as a function of the longitudinal coordinate. These modeling results are used to estimate the impact of spatial variations in wave-vector mismatch experimentally obtained for five partially deuterated potassium dihydrogen phosphate crystals. The longitudinal inhomogeneities in the properties of crystals of similar quality are not expected to have a significant impact on their use for second-harmonic generation and optical parametric amplification, but the efficiency of nonlinear processes in crystals with larger variations could decrease.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Coherent radar measurement of ocean currents from geostationary orbit

A coherent HF radar system developed by Barrick has successfully measured ocean surface currents near shore. This innovative system, called CODAR, can map the current vector for coastal areas as large as 10,000 sq km. CODAR's range is limited owing to the strong attenuation suffered by HF ground waves. An alternate technique was proposed by Schuler, in which the cross-product power spectrum of two (different frequency) microwave signals is processed. The frequency of the resonant peak corresponds close by to the Doppler shift of an ocean gravity wave traveling toward the radar at the phase velocity, v(sub p). The slight difference between the frequency of the measured resonant delta K peak and the Doppler frequency shift caused by the motion of the gravity wave is attributed to be the current velocity in the pointing direction of the radar. The Microwave Remote Sensing Laboratory (MIRSL) has considered the feasibility of using this technique to measure ocean surface currents from geostationary satellite platforms. Problems are discussed that must be overcome if a satellite current measurement system is to be realized. MIRSL research activities that address some of these problem areas are discussed. Current measurements are presented that were made using a specially-designed C-Band, step-frequency delta K radar. These measurements suggest that progress is being achieved in detecting ocean surface current motion for a wide variety of ocean surface conditions.

Mcintosh, R. E.↗
NASA NTRS1989

A fast, preconditioned conjugate gradient Toeplitz solver

A simple factorization is given of an arbitrary hermitian, positive definite matrix in which the factors are well-conditioned, hermitian, and positive definite. In fact, given knowledge of the extreme eigenvalues of the original matrix A, an optimal improvement can be achieved, making the condition numbers of each of the two factors equal to the square root of the condition number of A. This technique is to applied to the solution of hermitian, positive definite Toeplitz systems. Large linear systems with hermitian, positive definite Toeplitz matrices arise in some signal processing applications. A stable fast algorithm is given for solving these systems that is based on the preconditioned conjugate gradient method. The algorithm exploits Toeplitz structure to reduce the cost of an iteration to O(n log n) by applying the fast Fourier Transform to compute matrix-vector products. Matrix factorization is used as a preconditioner.

Pan, Victor↗
NASA NTRS1992

Verification measurement of a polarization Raman elastic-backscatter lidar

By measuring the depolarization of light Raman scattered from a gas of known number density (nitrogen), it is possible to determine the influence of multiple scattering on lidar signals. In order to realize such measurements, linearly polarized laser light is emitted and two components of the nitrogen Raman signals, with E vectors parallel (parallel P sub lambda R) and perpendicular (perpendicular P sub lambda R) to the plane of polarization of the laser light, are measured. The depolarization ratio, delta sub lambda R = perpendicular P sub lambda R/parallel P sub lambda R, is constant if only the Raman scattering process contributes to the signal. Any variation of the depolarization is caused by additional elastic, and, thus, multiple scattering. If the contribution of multiple scattered light to the lidar signals is known, other parameters determined with the systems such as extinction, backscattering, and the depolarization of elastically scattered light, can be corrected for this influence. The lidar system used for the polarization measurements, especially the receiver setup, is described. The calibration of the apparatus and a clear air measurement are discussed.

Schulze, Christoph↗
NASA NTRS1989

Fiber-optic three axis magnetometer prototype development

The goal of this research program was to develop a high sensitivity, fiber optic, interferometric, three-axis magnetometer for interplanetary spacecraft applications. Dynamics Technology, Inc. (DTI) has successfully integrated a low noise, high bandwidth interferometer with high sensitivity metallic glass transducers. Also, DTI has developed sophisticated signal processing electronics and complete data acquisition, filtering, and display software. The sensor was packaged in a compact, low power and weight unit which facilitates deployment. The magnetic field sensor had subgamma sensitivity and a dynamic range of 10(exp 5) gamma in a 10 Hz bandwidth. Furthermore, the vector instrument exhibited the lowest noise level when only one axis was in operation. A system noise level of 1 gamma rms was observed in a 1 Hz bandwidth. However, with the other two channels operating, the noise level increased by about one order of magnitude. Higher system noise was attributed to cross-channel interference among the dither fields.

Wang, Thomas D.↗
NASA NTRS1994

The real-time display of interferometry data for Goldstone radar astronomy data acquisition

A method for visualizing radar interferometry data in real time has been developed for the Goldstone radar astronomy ranging data-acquisition system. The presentation is similar in appearance to a vector field display or data-based grid. This form was selected to facilitate the recognition of characteristic patterns of local variation in the phase and magnitude of complex elements in a two-dimensional data array. The design emphasized efficiency under the demands of real-time processing and remote monitoring. The interferometry 'phase-magnitude' presentation, as it has come to be called, has been used to monitor radar interferometry experiments on three targets, beginning with the asteroid 4179 Toutatis, and continuing with Mars and Mercury.

Howard, S. D.↗
NASA NTRS2011

Challenges of Cold Conditioning and Static Testing the Second Ares Demonstration Motor (DM-2)

On August 31, 2010, a five-segment demonstration motor (DM) for the Ares program was successfully tested. A series of demonstration motors (DMs) will be tested in different conditioned environments to confirm they meet their design specifications. The second demonstration motor (DM-2) was the first cold motor. The motor needed to be subjected to sub-freezing temperatures for two months so that its internal propellant mean bulk temperature (PMBT) was approximately 40 F. Several challenges had to be overcome to make this a successful test. One challenge was to condition four field joints to get the O-rings approximately 32 F. This would be done by applying conditioning shrouds to externally cool each field joint after the test bay was pulled off. The purpose of this conditioning was to validate the new O-ring design and allow joint heaters to be eliminated. Another challenge was maintaining temperature requirements for components in the nozzle vectoring system. A separate heating system was used to warm these components during cold conditioning. There were 53 test objectives that required 764 channels of data to be recorded; 460 were specific to DM-2. This instrumentation had to be installed prior to conditioning, which meant the baseline process and timeline had to be modified to meet this time critical schedule.

Quinn, Shyla↗
NASA NTRS2011

In Situ Surface Characterization

Operation of in situ space assets, such as rovers and landers, requires operators to acquire a thorough understanding of the environment surrounding the spacecraft. The following programs help with that understanding by providing higher-level information characterizing the surface, which is not immediately obvious by just looking at the XYZ terrain data. This software suite covers three primary programs: marsuvw, marsrough, and marsslope, and two secondary programs, which together use XYZ data derived from in situ stereo imagery to characterize the surface by determining surface normal, surface roughness, and various aspects of local slope, respectively. These programs all use the Planetary Image Geometry (PIG) library to read mission-specific data files. The programs themselves are completely multimission; all mission dependencies are handled by PIG. The input data consists of images containing XYZ locations as derived by, e.g., marsxyz. The marsuvw program determines surface normals from XYZ data by gathering XYZ points from an area around each pixel and fitting a plane to those points. Outliers are rejected, and various consistency checks are applied. The result shows the orientation of the local surface at each point as a unit vector. The program can be run in two modes: standard, which is typically used for in situ arm work, and slope, which is typically used for rover mobility. The difference is primarily due to optimizations necessary for the larger patch sizes in the slope case. The marsrough program determines surface roughness in a small area around each pixel, which is defined as the maximum peak-to-peak deviation from the plane perpendicular to the surface normal at that pixel. The marsslope program takes a surface normal file as input and derives one of several slope-like outputs from it. The outputs include slope, slope rover direction (a measure of slope radially away from the rover), slope heading, slope magnitude, northerly tilt, and solar energy (compares the slope with the Sun s location at local noon). The marsuvwproj program projects a surface normal onto an arbitrary plane in space, resulting in a normalized 3D vector, which is constrained to lie in the plane. The marsuvwrot program rotates the vectors in a surface normal file, generating a new surface normal file. It also can change coordinate systems for an existing surface normal file. While the algorithms behind this suite are not particularly unique, what makes the programs useful is their integration into the larger in situ image processing system via the PIG library. They work directly with space in situ data, understanding the appropriate image metadata fields and updating them properly. The secondary programs (marsuvwproj, marsuvwrot) were originally developed to deal with anomalous situations on Opportunity and Spirit, respectively, but may have more general applicability.

Deen, Robert G.↗
NASA NTRS2015

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP), in collaboration with the Behavioral Health and Performance (BHP) Element, is conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within that volume. NASA is looking for innovative methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods for collecting such data exist yet many are obtrusive and require significant post‐processing. Example technologies used in terrestrial settings include infrared (IR) retro‐reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multiple camera filmography. However due to constraints of space operations many such methods are infeasible, such as inertial tracking systems which typically rely upon a gravity vector to normalize sensor readings, and traditional IR systems which are large and require extensive calibration. However multiple technologies have not yet been applied to space operations for these explicit purposes. Two of these include 3‐Dimensional Radio Frequency Identification Real‐Time Localization Systems (3D RFID‐RTLS) and depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR‐depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light‐Radar systems, referred to as LIDAR).

Vos, Gordon A.↗
NASA NTRSDate not supplied

The Doppler Wind Temperature Sensor (DWTS) Flight Evaluation and Experiments (TES-16, 17)

The Doppler Wind and Temperature Sounder instrument (DWTS), developed by Global Atmospheric Technologies and Sciences (GATS), is a simple but powerful tool that has the potential to become a new window through which to study the dynamics of the upper atmosphere. Based around a defense-grade infrared camera peering through a static gas cell used as a scanning spectral filter, the DWTS instrument infers wind velocities and kinetic temperatures through the stratosphere and lower thermosphere. The DWTS achieves this scanning by measuring the induced Doppler shift and Doppler broadening of emissions as they pass through the DWTS field of view (Gordley, et al., 2011). The DWTS holds promise in improving accuracy in weather determination , and the core technology can be adapted to study other planetary atmospheres. In partnership with GATS, NOAA, and other collaborators, NASA Ames and the Nano Orbital Workshop group have been working to evaluate the DWTS instrument on orbit and optimize it as a flexible nanosatellite payload. The first mission selected for DWTS evaluation is preparing for flight in early 2024, which will be followed by a more capable science mission in 2025, with both missions being part of the TES-n/NOW heritage flight series. The first rapid technology demonstration flight, TES-16/DWTS-A, will demonstrate a single DWTS instrument in an approximately 2U payload volume with the imaging aperture perpendicular to the flight velocity vector. With an estimated power consumption of 50 watts, supplied via a custom NOW-designed DC-DC converter, the instrument will maintain the imaging sensor plane at 80K during instrument evaluation periods using an integrated pulse-tube cryocooler. Data from DWTS will be captured and processed via a NOW-designed custom data interface unit before being transmitted via S-band radio back to select ground stations, with instrument command and control operated via L-band global-coverage radio. The subsequent TES-17/DWTS-B mission will be a dedicated science mission to obtain full altitude coverage from 20 to 200 km during both day and night, all from a single small-satellite equipped with three DWTS instruments, each hosting a different gas cell chemistry. The intention of this flight series, and one of NASA’s interests in this instrument, is to advance a Martian atmospheric instrument (Colaprete, Gordley, et al) which, if successful, would greatly further understanding of Martian atmospheric behavior. The proposed paper will review the flight series in detail, including challenges facing the TES-16 flight tests and the projected challenges and application to Mars study. Additional detail regarding the possible applications of a Cognitive Communication technique in current flight development by NOW collaborators at the NASA Glenn Research Center will also be discussed, including the implications of using an automated User Initiated Service (UIS) protocol to maximize the data collected per orbit.

nanosatellite↗
NASA NTRS2023

Comparative Analysis of Empirical and Machine Learning Models for Chla Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges

Remote retrieval of near-surface chlorophyll-a (Chla) concentration in small inland waters is challenging due to substantial optical interferences of various water constituents and uncertainties in the atmospheric correction (AC) process. Although various algorithms have been developed to estimate Chla from moderate-resolution terrestrial missions (∼10–60 m), the production of both accurate distribution maps and time series of Chla has proven challenging, limiting the use of remote analyses for lake monitoring. Here, we develop a support vector regression (SVR) model, which uses satellite-derived remote-sensing reflectance spectra () from Sentinel-2 and Landsat-8 images as input for Chla retrieval in a representative eutrophic prairie lake, Buffalo Pound Lake (BPL), Saskatchewan, Canada. Validated against in situ Chla from seven ice-free seasons (N ∼ 200; 2014–2020), the SVR model outperformed both locally tuned, -fed empirical models (Normalized Difference Chlorophyll Index, 2- and 3-band, and OC3) and Mixture Density Networks (MDNs) by 15–65%, while exhibiting comparable performance to a locally trained MDN, with an error of ∼35%. Comparison of Chla retrieval models, AC processors (iCOR, ACOLITE), and radiometric products (Rayleigh-corrected, surface, and top-of-atmosphere reflectance) showed that the best Chla maps and optimal time series (up to 100 mg m−3) were produced using a coupled SVR-iCOR system.

algal blooms↗
DOE OSTI2018

Cross-Correlation Analysis of Digital Speckle Photography

This paper describes new algorithms for processing noisy specklograms, which permit quantitative diagnostics of the microstructure of shock-wave flows with a subpicosecond accuracy with the use of statistical analysis of numerically registered speckle fields disturbed by the refraction in the investigated flows. The software developed by us permits reconstructing up to 10,000 vector angles of probe radiation deflection in a two-dimensional region of size 20 × 30 mm{sup 2} in imaging a speckle field with optical magnification M = 1.

42 ENGINEERING↗
DOE OSTI2021

Predicting measures of soil health using the microbiome and supervised machine learning

Soil health encompasses a range of biological, chemical, and physical soil properties that sustain the commercial and ecological value of agroecosystems. Monitoring soil health requires a comprehensive set of diagnostics that can be cost-prohibitive for routine analyses. The soil microbiome provides a rich source of information about soil properties, which can be assayed in a high-throughput, cost-effective way. We evaluated the accuracy of random forest (RF) and support vector machine (SVM) regression and classification models in predicting 12 measures of soil health, tillage status, and soil texture from 16S rRNA gene amplicon data with an operationally relevant sample set. We validated the efficacy of the best performing models against independent datasets and also tested best practices for processing microbiome data for use in machine learning. Soil health metrics could be predicted from microbiome data with the best models achieving a Kappa value of ~0.65, for categorical assessments, and a R2 value of ~0.8, for numerical scores. Biological health ratings were better predicted than chemical or physical ratings. Validation with independent datasets revealed that models had general predictive value for soil properties, including yield. The ecological profiles of several taxa important for model accuracy matched the observed relationships with soil health, including Pyrinomonadaceae, Nitrososphaeraceae, and Candidatus Udeaobacter. Models trained at the highest taxonomic resolution proved most accurate, with losses in accuracy resulting from rarefying, sparsity filtering, and aggregating at higher taxonomic ranks. Furthermore, our study provides the groundwork for developing scalable technology to use microbiome-based diagnostics for the assessment of soil health.

16S rRNA gene↗
DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗