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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Gravity Waves and Mesospheric Clouds in the Summer Middle Atmosphere: A Comparison of Lidar Measurements and Ray Modeling of Gravity Waves Over Sondrestrom, Greenland

We conducted gravity wave ray-tracing experiments within an atmospheric region centered near the ARCLITE lidar system at Sondrestrom, Greenland (67N, 310 deg E), in efforts to understand lidar observations of both upper stratospheric gravity wave activity and mesospheric clouds during August 1996 and the summer of 2001. The ray model was used to trace gravity waves through realistic three-dimensional daily-varying background atmospheres in the region, based on forecasts and analyses in the troposphere and stratosphere and climatologies higher up. Reverse ray tracing based on upper stratospheric lidar observations at Sondrestrom was also used to try to objectively identify wave source regions in the troposphere. A source spectrum specified by reverse ray tracing experiments in early August 1996 (when atmospheric flow patterns produced enhanced transmission of waves into the upper stratosphere) yielded model results throughout the remainder of August 1996 that agreed best with the lidar observations. The model also simulated increased vertical group propagation of waves between 40 km and 80 km due to intensifying mean easterlies, which allowed many of the gravity waves observed at 40 km over Sondrestrom to propagate quasi-vertically from 40-80 km and then interact with any mesospheric clouds at 80 km near Sondrestrom, supporting earlier experimentally-inferred correlations between upper stratospheric gravity wave activity and mesospheric cloud backscatter from Sondrestrom lidar observations. A pilot experiment of real-time runs with the model in 2001 using weather forecast data as a low-level background produced less agreement with lidar observations. We believe this is due to limitations in our specified tropospheric source spectrum, the use of climatological winds and temperatures in the upper stratosphere and mesosphere, and missing lidar data from important time periods.

LIDAR (LIGHT DETECTION AND RANGING)↗
DOE OSTI2025

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗
DOE OSTI2025

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗
NASA NTRS1989

Space applications of artificial intelligence; Proceedings of the Annual Goddard Conference, Greenbelt, MD, May 16, 17, 1989

Theoretical and implementation aspects of AI systems for space applications are discussed in reviews and reports. Sections are devoted to planning and scheduling, fault isolation and diagnosis, data management, modeling and simulation, and development tools and methods. Particular attention is given to a situated reasoning architecture for space repair and replace tasks, parallel plan execution with self-processing networks, the electrical diagnostics expert system for Spacelab life-sciences experiments, diagnostic tolerance for missing sensor data, the integration of perception and reasoning in fast neural modules, a connectionist model for dynamic control, and applications of fuzzy sets to the development of rule-based expert systems.

Rash, James L.↗
DOE OSTI2022

A Robust Event Diagnostics Platform: Integrating Tensor Analytics and Machine Learning into Real-time Grid Monitoring

The objective of this project is to develop a robust event diagnostics (RED) platform by integrating state-of-the-art tensor analytics and machine learning into real-time grid monitoring. The proposed platform can effectively analyze and discover the information hiding within the provided PMU data for effective real-time grid monitoring. The proposed RED platform provides a set of robust diagnostics tools for grid operation and management, including 1) data quality assessment, 2) data completion, 3) event detection, and 4) robust event classification. All the functionalities of the RED platform can help the operator to make informed decisions and respond in a timely manner. The developed RED platform will serve as an innovative advisory tool to reliably identify key events and discover new insights about the events and grid characteristics in the PMU data, and contribute to the efficient, safe, reliable operation and design of the nation’s electric system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Hydrogen shift isomerizations in the kinetics of the second oxidation mechanism of alkane combustion. Reactions of the hydroperoxypentylperoxy OOQOOH radical

Hydroperoxyalkylperoxy species are important intermediates that are generated during the autoignition of transport fuels. In combustion, the fate of hydroperoxyalkylperoxy is important for the performance of advanced combustion engines, especially for autoignition. A key fate of the hydroperoxyalkylperoxy is a 1,5 H-shift, for which kinetics data are experimentally unavailable. In the present work, we study 1-hydroperoxypentan-3-yl)dioxidanyl (CH 3 CH 2 CH(OO)CH 2 CH 2 OOH) as a model compound to clarify the kinetics of 1,5 H-shift of hydroperoxyalkylperoxy species, in particular α-H isomerization and alternative competitive pathways. With a combination of electronic structure calculations, we determine previously missing thermochemical data, and with multipath variational transition state theory (MP-VTST), a multidimensional tunneling (MT) approximation, multiple-structure anharmonicity, and torsional potential anharmonicity, we obtained much more accurate rate constants than the ones that can computed by conventional single-structure harmonic transition state theory (TST) and than the empirically estimated rate constants that are currently used in combustion modeling. The roles of various factors in determining the rates are elucidated. The pressure-dependent rate constants for these competitive reactions are computed using system-specific quantum RRK theory. The calculated temperature range is 298–1500 K, and the pressure range is 0.01–100 atm. The accurate thermodynamic and kinetics data determined in this work are indispensable in the detailed understanding and prediction of ignition properties of hydrocarbons and alternative fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The role of moisture in MgCl 2 salt: A multiscale approach to TES performance

This study presents a comprehensive multiscale analysis to evaluate the influence of moisture on the thermal performance of thermal energy storage systems using magnesium chloride (MgCl 2 ) as the phase-changing material. The system uses graphite foam with 90% relative density to enhance thermal conductivity. The analysis includes thermal conductivity calculations and specific heat capacity for different hydrate phases of MgCl 2 : Anhydrous, Mono, Di, Tetra, and Hexa. These properties were evaluated for the first time using the phonon density of states from Density Functional Theory simulations. Results showed that thermal conductivity decreased, while specific heat capacity increased by a factor of two as the phase changed from anhydrous to hexahydrate. Meso-scale models were created to account for the anisotropy of graphite foam and property variations of the MgCl 2 hydrate phases. Asymptotic Expansion homogenization simulations determined the anisotropic thermal conductivity for all phases. This unique methodology improved simulation accuracy, which matched experimental data for anhydrous MgCl 2 . A parametric study examined various operating conditions and their effect on TES performance. It revealed that higher charging temperatures did not enhance exergy efficiency, but increased discharge mass flow rates improved it due to better heat transfer. Thermal performance evaluated by the exergy efficiency remained consistent across hydrate systems under the tested conditions. Furthermore, the study suggests that this uniformity is linked to missing key data, particularly latent heat and melting point for different hydrates. Overall, it highlights the importance of multiscale effects and accurate material properties in designing and optimizing TES systems.

Molten salt degradation↗
DOE OSTI2016

WE-AB-207A-04: Random Undersampled Cone Beam CT: Theoretical Analysis and a Novel Reconstruction Method

Purpose: Reducing x-ray exposure and speeding up data acquisition motived studies on projection data undersampling. It is an important question that for a given undersampling ratio, what the optimal undersampling approach is. In this study, we propose a new undersampling scheme: random-ray undersampling. We will mathematically analyze its projection matrix properties and demonstrate its advantages. We will also propose a new reconstruction method that simultaneously performs CT image reconstruction and projection domain data restoration. Methods: By representing projection operator under the basis of singular vectors of full projection operator, matrix representations for an undersampling case can be generated and numerical singular value decomposition can be performed. We compared properties of matrices among three undersampling approaches: regular-view undersampling, regular-ray undersampling, and the proposed random-ray undersampling. To accomplish CT reconstruction for random undersampling, we developed a novel method that iteratively performs CT reconstruction and missing projection data restoration via regularization approaches. Results: For a given undersampling ratio, random-ray undersampling preserved mathematical properties of full projection operator better than the other two approaches. This translates to advantages of reconstructing CT images at lower errors. Different types of image artifacts were observed depending on undersampling strategies, which were ascribed to the unique singular vectors of the sampling operators in the image domain. We tested the proposed reconstruction algorithm on a Forbid phantom with only 30% of the projection data randomly acquired. Reconstructed image error was reduced from 9.4% in a TV method to 7.6% in the proposed method. Conclusion: The proposed random-ray undersampling is mathematically advantageous over other typical undersampling approaches. It may permit better image reconstruction at the same undersampling ratio. The novel algorithm suitable for this random-ray undersampling was able to reconstruct high-quality images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

EPCAPE-PT-LANL Measurements: Single Particle Soot Photometer

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Single Particle Soot Photometer (Droplet Measurements Technology) Data Notes: Contact us if you want additional data products from this instrument. Reported data is the black carbon (rBC) number and mass concentration with diagnostic flags. The SP2 measures incandescence from particles that is induced with a 1064 Nd-YAG laser. Particles that absorb the laser energy and then emit radiation is assumed to contain black carbon. The amount of intensity of radiation is related to the mass of absorbing material in the particle. Here, we calibrate the incandescence intensity to size selected Regal Black (Cabot) nebulized from solution. Data provided for the EPCAPE campaign used the combined broadband high-gain + low-gain channels (BHBL). Each channel has a lower threshold of detection equivalent to 2-s of the respective channel noise. Thresholding has been applied to select between the high-gain and low-gain channels. The detection limit is 80-540 nm (Deq) or 0.36- 55 fg. It is assumed that rBC is the only aerosol type that is in significant concentration in the sampled atmosphere that absorbs the laser energy. Particle data are integrated over 10 second windows to calculate a rBC number and mass concentration. QC/QA: • Diagnostic flags that impacted measured concentration: - Sample, Sheath, and Purge Flow Rates: Despite observing fluctuations in all flows, the rBC detection and mass quantification are generally observed to be stable, although large changes in sample flow rate did impact detection efficiency. A flag was implemented for sample flow deviations >12 cm3/min from the set point averaged over 30 seconds - Laser Power: Detection efficiency decreases with laser power and deviations in laser power also affect mass quantification. Flag for laser power is set for deviations in laser current from the set value >5 mA. - Primary Detector Threshold: Primary thresholding is the signal value which determines whether a “particle” is recorded. Thresholding errors occur when the threshold value is too HIGH and real particles are ignored. • Several periods without data: - 16-18 Nov: Ultra Zero Air generator failure, flows deviated significantly from set points. rBC # conc recovered but questionable. - 20-21 Nov: Offline for calibrations for several hours each day. - 25-27 Nov: Data is missing. - 30 Nov: Power outage 3 Dec: SP2 hard-drive full. - 3 Dec: Power Outage Header: - BHBL_NumbConc[#/cc]: Refers to the number concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in particles per cubic centimeter. - BHBL_BCMass_Conc[ug/m3]: Refers to the mass concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in micrograms per cubic meter. - NoData_Flag[bool]: A boolean flag that indicates whether no data was recorded during a measurement. - NoBC_Flag[bool]: A boolean flag indicating whether no black carbon particles were recorded during the measurement. - Laser_Flag[bool]: A boolean flag indicating deviations in laser current during the measurement. - SampleFlow_Flag[bool]: A boolean flag indicating deviations from the set sample flow rate during the measurement. - PrimThresh_Flag[bool]: A boolean flag indicating deviations from the set primary threshold during the measurement, potentially ignoring real particles. - Manual_Flag[bool]: A boolean flag indicating manual intervention or adjustments during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active or inactive during the measurement.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

A Comparison of Latent Heat Fluxes over Global Oceans for Four Flux Products

To improve our understanding of global energy and water cycle variability, and to improve model simulations of climate variations, it is vital to have accurate latent heat fluxes (LHF) over global oceans. Monthly LHF, 10-m wind speed (U10m), 10-m specific humidity (Q10h), and sea-air humidity difference (Qs-Q10m) of GSSTF2 (version 2 Goddard Satellite-based Surface Turbulent Fluxes) over global Oceans during 1992-93 are compared with those of HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data), NCEP (NCEP/NCAR reanalysis). The mean differences, standard deviations of differences, and temporal correlation of these monthly variables over global Oceans during 1992-93 between GSSTF2 and each of the three datasets are analyzed. The large-scale patterns of the 2yr-mean fields for these variables are similar among these four datasets, but significant quantitative differences are found. The temporal correlation is higher in the northern extratropics than in the south for all variables, with the contrast being especially large for da Silva as a result of more missing ship data in the south. The da Silva has extremely low temporal correlation and large differences with GSSTF2 for all variables in the southern extratropics, indicating that da Silva hardly produces a realistic variability in these variables. The NCEP has extremely low temporal correlation (0.27) and large spatial variations of differences with GSSTF2 for Qs-Q10m in the tropics, which causes the low correlation for LHF. Over the tropics, the HOAPS LHF is significantly smaller than GSSTF2 by approx. 31% (37 W/sq m), whereas the other two datasets are comparable to GSSTF2. This is because the HOAPS has systematically smaller LHF than GSSTF2 in space, while the other two datasets have very large spatial variations of large positive and negative LHF differences with GSSTF2 to cancel and to produce smaller regional-mean differences. Our analyses suggest that the GSSTF2 latent heat flux, surface air humidity, and winds are likely to be more realistic than the other three flux datasets examined, although those of GSSTF2 are still subject to regional biases.

Chou, Shu-Hsien↗
NASA NTRS2018

An Overview of the XRT Observations for the September 10 2017 X Flare

The September 10 2017 X8 flare was one of the biggest of the current solar cycle, and it was also incredibly well observed. This presentation will review the available XRT data for this flare. XRT observed the initial flux rope eruption, which was also well observed by AIA and SUVI. XRT data is missing for some of the impulsive phase of the flare, but the late phase shows some very interesting features. There is some nice XRT imaging of a plasma sheet above cusp-shaped loops between 16:47 and 18:39 UT. After 18:40 UT, a double loop structure becomes apparent, with a more rounded loop nested within a larger, cusp-shaped structure. The flare loops continue to grow, and at around 1 UT on September 11, supra-arcade down flows and shrinking loops become visible. There is also interesting data in the late phase of this flare from RHESSI and the Expanded Owens Valley Solar Array (EOVSA).

Reeves, Kathy↗
DOE OSTI2026

Assessing shellfish water exposure to fecal bacteria pollution in Salish Sea: three-dimensional modeling and implications for monitoring

Fecal bacteria (FB) contamination poses significant risks to shellfish safety and management in coastal and estuarine waters. Despite extensive pollution identification and correction efforts, FB contamination in shellfish-growing areas persists in the Salish Sea, highlighting the need to identify overlooked sources and better understand FB transport from riverine and shoreline inputs to shellfish beds. To address this, a high-resolution three-dimensional hydrodynamic model coupled with FB kinetics was developed and applied to a case study site in Salish Sea—Portage Bay—to simulate freshwater plume circulation, flushing dynamics, and bacterial transport. Daily FB loading from the major freshwater inflow—Nooksack River was generated by both linear interpolation and integrating a machine learning approach (XGBoost), trained on historical hydrological and meteorological data. The model successfully reproduced both the magnitude and seasonal variation of FB concentrations in Portage Bay for the year of 2021, demonstrating that simplified FB kinetics with first-order decay due to mortality was effective in this dynamic coastal environment with short flushing time. Model results identified the Nooksack River as the dominant far-field FB source, while scenario simulations showed that near-field coastal stormwater outfalls elevated local FB levels following rainfall, particularly under low-flow conditions. The XGBoost prediction provided comparable or superior accuracy to linear interpolation, particularly during periods of missing observational data, by capturing short-term variability and event-driven loading more effectively. Integrating data-driven riverine FB inputs with mechanistic coastal numerical modeling provides a robust framework for operational forecasting of shellfish bed exposure risk and supports adaptive monitoring and management of shellfish growing areas in the Salish Sea and similar coastal systems.

Salish Sea↗
NASA NTRS1985

Application of satellite data to tropic/subtropic moisture coupling

The objective is to develop analysis tools for use of satellite data to interpret synoptic-scale systems in data-void regions. Interim goals are to: (1) quantify the synoptic information content of satellite data; and (2) utilize these data in the diagnosis of moisture bursts in the eastern tropical Pacific Ocean. Researchers developed and implemented a statistical procedure for using TIROS N microwave data to infer infrared channel data for overcast conditions; they used the same procedure for deducing full TIROS N channel radiance profiles from NOAA 5 VTPR channel data over regions where the TIROS N data are missing. An empirical orthogonal function analysis of twice-daily channel radiance fields over the tropical eastern Pacific was completed. The vertically oriented eigenfunctions were interpreted in terms of typical meteorological events. The horizontal distribution of the eigenfunction amplitudes relates these meteorological signals to moisture bursts. A pair of moisture burst climatologies is complete: one of four years using infrared imagery (including the highly anomalous 1982 to 83 cold season); the other implementing 850 to 200 mb wind analyses in conjunction with GOES imagery. A number of different evaluations of the synoptic evolution of moisture fields (enhanced infrared imagery, moisture channel data, FGGE humidity analysis, and in situ station and sounding observations) are compared. All have limitations; all can be utilized together; all together are still less than adequate in the tropical Pacific.

Mcguirk, J. P.↗
NASA NTRS2007

NASA Tech Briefs, March 2007

Topics include: Advanced Systems for Monitoring Underwater Sounds; Wireless Data-Acquisition System for Testing Rocket Engines; Processing Raw HST Data With Up-to-Date Calibration Data; Mobile Collection and Automated Interpretation of EEG Data; System for Secure Integration of Aviation Data; Servomotor and Controller Having Large Dynamic Range; Digital Multicasting of Multiple Audio Streams; Translator for Optimizing Fluid-Handling Components; AIRSAR Web-Based Data Processing; Pattern Matcher for Trees Constructed From Lists; Reducing a Knowledge-Base Search Space When Data Are Missing; Ground-Based Correction of Remote-Sensing Spectral Imagery; State-Chart Autocoder; Pointing History Engine for the Spitzer Space Telescope; Low-Friction, High-Stiffness Joint for Uniaxial Load Cell; Magnet-Based System for Docking of Miniature Spacecraft; Electromechanically Actuated Valve for Controlling Flow Rate; Plumbing Fixture for a Microfluidic Cartridge; Camera Mount for a Head-Up Display; Core-Cutoff Tool; Recirculation of Laser Power in an Atomic Fountain; Simplified Generation of High-Angular-Momentum Light Beams; Imaging Spectrometer on a Chip; Interferometric Quantum-Nondemolition Single-Photon Detectors; Ring-Down Spectroscopy for Characterizing a CW Raman Laser; Complex Type-II Interband Cascade MQW Photodetectors; Single-Point Access to Data Distributed on Many Processors; Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data; Computing a Stability Spectrum by Use of the HHT; Theoretical Studies of Routes to Synthesis of Tetrahedral N4; Estimation Filter for Alignment of the Spitzer Space Telescope; Antenna for Measuring Electric Fields Within the Inner Heliosphere; Improved High-Voltage Gas Isolator for Ion Thruster; and Hybrid Mobile Communication Networks for Planetary Exploration.

Source record↗
DOE OSTI2016

SU-F-J-140: Using Handheld Stereo Depth Cameras to Extend Medical Imaging for Radiation Therapy Planning

Purpose: A correct body contour is essential for the accuracy of dose calculation in radiation therapy. While modern medical imaging technologies provide highly accurate representations of body contours, there are times when a patient’s anatomy cannot be fully captured or there is a lack of easy access to CT/MRI scanning. Recently, handheld cameras have emerged that are capable of performing three dimensional (3D) scans of patient surface anatomy. By combining 3D camera and medical imaging data, the patient’s surface contour can be fully captured. Methods: A proof-of-concept system matches a patient surface model, created using a handheld stereo depth camera (DC), to the available areas of a body contour segmented from a CT scan. The matched surface contour is then converted to a DICOM structure and added to the CT dataset to provide additional contour information. In order to evaluate the system, a 3D model of a patient was created by segmenting the body contour with a treatment planning system (TPS) and fabricated with a 3D printer. A DC and associated software were used to create a 3D scan of the printed phantom. The surface created by the camera was then registered to a CT model that had been cropped to simulate missing scan data. The aligned surface was then imported into the TPS and compared with the originally segmented contour. Results: The RMS error for the alignment between the camera and cropped CT models was 2.26 mm. Mean distance between the aligned camera surface and ground truth model was −1.23 +/−2.47 mm. Maximum deviations were < 1 cm and occurred in areas of high concavity or where anatomy was close to the couch. Conclusion: The proof-of-concept study shows an accurate, easy and affordable method to extend medical imaging for radiation therapy planning using 3D cameras without additional radiation. Intel provided the camera hardware used in this study.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2008

Re-Engineering the Tropical Rainfall Measuring Mission (TRMM) Satellite Utilizing Goddard Space Flight Center (GSFC) Mission Services Center (GMSEC) Middleware Based Technology to Enable Lights Out Operations and Autonomous Re-Dump of Lost Telemetry Data

The Tropical Rainfall Measuring Mission (TRMM) spacecraft was launched in November of 1996 in order to obtain unique three dimensional radar cross sectional observations of cloud structures with particular interest in hurricanes. The TRMM mission life was recently extended with current estimates that operations will continue through the 2012-2013 timeframe. Faced with this extended mission profile, the project has embarked on a technology refresh and re-engineering effort. TRMM has recently implemented a re-engineering effort to expand a middleware based messaging architecture to enable fully redundant lights-out of flight operations activities. The middleware approach is based on the Goddard Mission Services Evolution Center (GMSEC) architecture, tools and associated open-source Applications Programming Interface (API). Middleware based messaging systems are useful in spacecraft operations and automation systems because private node based knowledge (such as that within a telemetry and command system) can be broadcast on the middleware messaging bus and hence enable collaborative decisions to be made by multiple subsystems. In this fashion, private data is made public and distributed within the local area network and multiple nodes can remain synchronized with other nodes. This concept is useful in a fully redundant architecture whereby one node is monitoring the processing of the 'prime' node so that in the event of a failure the backup node can assume operations of the prime, without loss of state knowledge. This paper will review and present the experiences, architecture, approach and lessons learned of the TRMM re-engineering effort centered on the GMSEC middleware architecture and tool suite. Relevant information will be presented that relates to the dual redundant parallel nature of the Telemetry and Command (T and C) and Front-End systems and how these systems can interact over a middleware bus to achieve autonomous operations including autonomous commanding to recover missing science data during the same spacecraft contact.

Marius, Julio L.↗
DOE OSTI2018

Estimating the joint distribution of rate parameters across multiple reactions in the absence of experimental data

Here, a procedure for determining the joint uncertainty of Arrhenius parameters across multiple combustion reactions of interest is demonstrated. This approach is capable of constructing the joint distribution of the Arrhenius parameters arising from the uncertain measurements performed in specific target experiments without having direct access to the underlying experimental data. The method involves constructing an ensemble of hypothetical data sets with summary statistics consistent with the available information reported by the experimentalists, followed by a fitting procedure that learns the structure of the joint parameter density across reactions using this consistent hypothetical data as evidence. The procedure is formalized in a Bayesian statistical framework, employing maximum-entropy and approximate Bayesian computation methods and utilizing efficient Markov chain Monte Carlo techniques to explore data and parameter spaces in a nested algorithm. We demonstrate the application of the method in the context of experiments designed to measure the rates of selected chain reactions in the H 2 -O 2 system and highlight the utility of this approach for revealing the critical correlations between the parameters within a single reaction and across reactions, as well as for maximizing consistency when utilizing rate parameter information in predictive combustion modeling of systems of interest.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Atmospheric Disturbance Environment Definition

Traditionally, the application of atmospheric disturbance data to airplane design problems has been the domain of the structures engineer. The primary concern in this case is the design of structural components sufficient to handle transient loads induced by the most severe atmospheric "gusts" that might be encountered. The concern has resulted in a considerable body of high altitude gust acceleration data obtained with VGH recorders (airplane velocity, V, vertical acceleration, G, altitude, H) on high-flying airplanes like the U-2 (Ehernberger and Love, 1975). However, the propulsion system designer is less concerned with the accelerations of the airplane than he is with the airflow entering the system's inlet. When the airplane encounters atmospheric turbulence it responds with transient fluctuations in pitch, yaw, and roll angles. These transients, together with fluctuations in the free-stream temperature and pressure will disrupt the total pressure, temperature, Mach number and angularity of the inlet flow. For the mixed compression inlet, the result is a disturbed throat Mach number and/or shock position, and in extreme cases an inlet unstart can occur (cf. Section 2.1). Interest in the effects of inlet unstart on the vehicle dynamics of large, supersonic airplanes is not new. Results published by NASA in 1962 of wind tunnel studies of the problem were used in support of the United States Supersonic Transport program (SST) (White, at aI, 1963). Such studies continued into the late 1970's. However, in spite of such interest, there never was developed an atmospheric disturbance database for inlet unstart analysis to compare with that available for the structures load analysis. Missing were data for the free-stream temperature and pressure disturbances that also contribute to the unStart problem.

Tank, William G.↗