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The use of DSN radiometric data for enhancing the orbit determination capability for TDRS is examined. Results of a formal covariance analysis are presented which establish the nominal TDRS navigation performance and assess the performance improvement based on augmenting the nominal TDRS data strategy with radiometric data from DSN sites.
The goal of this work is to improve the capability of Reynolds-averaged Navier-Stokes turbulence models for separated flows using data-driven enhancements. The resulting model should be “universal” in the sense that it can be used by anyone and applied to as many flows as possible without concern for unusual or detrimental behavior. At worst, the data-driven corrections should not degrade the accuracy of the baseline model (in this case the Spalart-Allmaras one-equation model), while preserving the Galilean invariance and similar theoretical qualities of the original model. In the literature, most current data-driven improvements to turbulence models are only applicable to very similar types of cases as those used to train the model for a specific class of flows. In this work, the impact of using a wide array of cases in the machine-learning training is described. Unwanted behaviors from trained neural networks are examined, and possible mitigation strategies are proposed. However, to date, consistent and broadly applicable data-driven improvements for separated flows have not been achieved.
The NASA Applied Sciences Program seeks to transfer NASA data, models, and knowledge into the hands of end-users by forming links with partner agencies and associated decision support tools (DSTs). Through the NASA REASoN (Research, Education and Applications Solutions Network) Cooperative Agreement, the Oceanography Division of the Naval Research Laboratory (NRLSSC) is developing new products through the integration of data from NASA Earth-Sun System assets with coastal ocean forecast models and other available data to enhance coastal management in the Gulf of Mexico. The recipient federal agency for this research effort is the National Oceanic and Atmospheric Administration (NOAA). The contents of this report detail the effort to further the goals of the NASA Applied Sciences Program by demonstrating the use of NASA satellite products combined with data-assimilating ocean models to provide near real-time information to maritime users and coastal managers of the Gulf of Mexico. This effort provides new and improved capabilities for monitoring, assessing, and predicting the coastal environment. Coastal managers can exploit these capabilities through enhanced DSTs at federal, state and local agencies. The project addresses three major issues facing coastal managers: 1) Harmful Algal Blooms (HABs); 2) hypoxia; and 3) freshwater fluxes to the coastal ocean. A suite of ocean products capable of describing Ocean Weather is assembled on a daily basis as the foundation for this semi-operational multiyear effort. This continuous realtime capability brings decision makers a new ability to monitor both normal and anomalous coastal ocean conditions with a steady flow of satellite and ocean model conditions. Furthermore, as the baseline data sets are used more extensively and the customer list increased, customer feedback is obtained and additional customized products are developed and provided to decision makers. Continual customer feedback and response with new improved products are required between the researcher and customer. This document details the methods by which these coastal ocean products are produced including the data flow, distribution, and verification. Product applications and the degree to which these products are used successfully within NOAA and coordinated with the Mississippi Department of Marine Resources (MDMR) is benchmarked.
Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.
Floor-fractured craters (FFCs) are a class of lunar craters defined by their distinctly shallow, often plate-like floors, and combinations of radial, con-centric, and polygonal floor-fractures; a variety of other interior features are often observed, such as moats, ridges, small dark-haloed pits, and patches of mare material. They were first classified by Schultz [1] , who recognized eight overall types of floor-fractured crater. These eight subtypes have widely differing appearances, a factor that could provide insight into formation mechanisms (different manifestations of the same mechanism, or indicators of varying formation mechanisms). Two formation mechanisms for FFCs were initially proposed: 1) magmatic intrusion [1], in which magma rising toward the surface in dikes encountered low-density breccia lenses beneath crater floors and spread laterally to form sills, raising and fracturing the crater floor. 2) viscous relaxation [2], in which the properties of the crust permitted viscous flow in the vicinity of the crater, causing long-wavelength relaxation of the topography and uplift and fracturing of the crater floor. Critical to distinguishing between these two end-member hypotheses and identifying others is a quantitative assessment of the topography of FFCs and knowledge of their regional and local settings. The purpose of this study is to use newly available Lunar Reconnaissance Orbiter (LRO) Lunar Orbiter Laser Altimeter (LOLA) altimeter and Lunar Reconnaissance Orbiter Camera (LROC) image data to provide an updated global catalog of the locations, classes, morphometric and morphologic characteristics of all lunar floor-fractured craters. We use the excellent 8-class system initially described in Schultz [1] as a starting point for classification and the enhanced LOLA/LROC data sets to examine and categorize all FFCs; we found evidence for a new FFC class, discernably different from the previously existing types. Our approach, and the global categorization of all FFCs, permits the spatial distribution of each FFC-subtype to be plotted and assessed allowing for further investigation into FFC formation mechanisms. Upon completion, the data set will be made available on our web site at http://www.planetary.brown.edu/html_pages/data.htm.
Impact trials were performed at the NASA vertical gun range to study low-temperature brittle-ductile transitions in meteoritic, steel and iron targets. The trials were performed to enhance the data base underlying the concept of formation of planetesimals in collisional coagulation. Impact velocities of 1.6-5.5 km/sec were used, as were temperatures from 100-300 K. Spallation was observed in the tests with meteorite samples, even at room temperature, and brittleness was enhanced at temperature below 200 C. Net mass losses were induced at the higher impact velocities. It is suggested that iron meteorite agglomerations could form in the inner solar region during nebular condensation, but would not form in farther-out regions such as the asteroid belt. The protoplanets could have an iron core, with metallicity decreasing with radius from the core, which may have happened with the earth.
Day-IR, day-visible, and night-IR image data sets were analyzed. All three images were contrast enhanced, using a linear stretch. The night-IR image was destriped using a box-car filtering approach. Apparent thermal inertia images were generated from the data. The enhanced data and the apparent thermal inertia image were also registered and overlayed onto shaded relief images depicting topography and onto a colored version of the Missouri geologic map. The combination of the apparent thermal inertial image and the shaded relief map proved to have the greatest discriminability in terms of portraying linear features. The reason seems to be that the vegetation canopy on the Ozark Plateau is different topography, tend to emphasize subtle topographic effects.
A synoptic of programmatic and technical lessons learned in the development of aerothermodynamic data bases for the X-33 and X-34 programs is presented in general terms and from the perspective of the NASA Langley Research Center Aerothermodynamics Branch. The format used is that of the "aerothermodynamic chain," the links of which are personnel, facilities, models/test articles, instrumentation, test techniques, and computational fluid dynamics (CFD). Because the aerodynamic data bases upon which the X-33 and X-34 vehicles will fly are almost exclusively from wind tunnel testing, as opposed to CFD, the primary focus of the lessons learned is on ground-based testing. The period corresponding to the development of X-33 and X-34 aerothermodynamic data bases was challenging, since a number of other such programs (e.g., X-38, X-43) competed for resources at a time of downsizing of personnel, facilities, etc., outsourcing, and role changes as NASA Centers served as subcontractors to industry. The impact of this changing environment is embedded in the lessons learned. From a technical perspective, the relatively long times to design and fabricate metallic force and moment models, delays in delivery of models, and a lack of quality assurance to determine the fidelity of model outer mold lines (OML) prior to wind tunnel testing had a major negative impact on the programs. On the positive side, the application of phosphor thermography to obtain global, quantitative heating distributions on rapidly fabricated ceramic models revolutionized the aerothermodynamic optimization of vehicle OMLs, control surfaces, etc. Vehicle designers were provided with aeroheating information prior to, or in conjunction with, aerodynamic information early in the program, thereby allowing trades to be made with both sets of input; in the past only aerodynamic data were available as input. Programmatically, failure to include transonic aerodynamic wind tunnel tests early in the assessment phase led to delays in the optimization phase, as OMLs required modification to provide adequate transonic aerodynamic performance without sacrificing subsonic and hypersonic performance. Funding schedules for industry, based on technical milestones, also presented challenges to aerothermodynamics seeking optimum flying characteristics across the subsonic to hypersonic speed regimes and minimum aeroheating. This paper is concluded with a brief discussion of enhancements in ground-based testing/CFD capabilities necessary to partially/fully satisfy future requirements.
A navigation error covariance analysis of four highly elliptical Earth orbits is described, with apogee heights ranging from 20,000 to 76,800 km and perigee heights ranging from 1,000 to 5,000 km. This analysis differs from earlier studies in that improved navigation data-processing modes were used to reduce the radio metric data. For this study, X-band (8.4-GHz) Doppler data were assumed to be acquired from two Deep Space Network radio antennas and reconstructed orbit errors propagated over a single day. Doppler measurements were formulated as total-count phase measurements and compared to the traditional formulation of differenced-count frequency measurements. In addition, an enhanced data-filtering strategy was used, which treated the principal ground system calibration errors affecting the data as filter parameters. Results suggest that a 40- to 60-percent accuracy improvement may be achievable over traditional data-processing modes in reconstructed orbit errors, with a substantial reduction in reconstructed velocity errors at perigee. Historically, this has been a regime in which stringent navigation requirements have been difficult to meet by conventional methods.
Cryogenic flow boiling physics is of paramount importance for future cryogenic space applications employing Cryogenic Fluid Management (CFM) technologies. This experimental study investigates the two-phase flow and heat transfer performance of LN 2 flow boiling across five distinct flow orientations: vertical upflow, vertical downflow, horizontal flow, 45° inclined upflow, and 45° inclined downflow. The study employed the steady- state heating method within a circular heated tube featuring an 8.5-mm inner diameter and a 680-mm heated length. High-speed video recordings were utilized to capture two-phase flow patterns and interfacial behaviors across various flow orientations. The experiments covered a wide range of operating conditions, including mass velocities ranging from 351.80 to 1572.77 kg/m 2 s and inlet pressures from 297.14 to 1032.97 kPa, primarily with near-saturated inlet subcooling. Distinct two-phase flow patterns and regime transitions were identified for each flow orientation. Symmetrical flow patterns were evident in vertical orientations, whereas non-vertical orientations exhibited asymmetric flow stratifications, primarily influenced by the buoyancy force in a terrestrial gravity environment. Bubble dynamic parameters were quantified, and bubble collision and dispersion phenomena were visualized. Analyzing heat transfer performance based on local flow boiling curves and variations in heat transfer coefficients (HTCs), it was observed that vertical upflow demonstrated the most enhanced heat transfer performance, while vertical downflow exhibited the lowest. As mass velocity exceeded 830 kg/ m 2 s, the differences in heat transfer among orientations became less distinct, emphasizing the role of flow inertia in mitigating the influence of flow orientation. A direct comparison of microgravity HTC data from a recent study by the authors against the 1-𝘨 e HTC data indicated enhanced heat transfer performance in microgravity for flow orientation configurations in terrestrial gravity. However, this enhancement progressively diminished as the heat flux increased. Distinct HTC trends were observed as mass velocity increased for different flow orientations and gravity levels.
In the ensuing period we were able to demonstrate that the origin of these filamentous patterns resulted from the action of synoptic-scale vortical velocity field on the global-scale background gradient of ozone concentration in the meridional direction. Hyperbolic flow patterns between long-lived atmospheric vortices bring together air parcels from different latitudes, thus creating large gradients along the separatrices leaving the hyperbolic (stagnation) point. This result is further confirmed by the KL analysis of the ozone field in the equatorial region, where the background concentration gradient vanishes. The spectral slope in this region has been found to lie close to -1, in agreement with Batchelor's prediction. Another outcome of this result is that it at least provides indirect evidence about the kinetic energy spectrum of the atmospheric turbulence in the range of scales approximately 200 to 2000 km. Namely, Batchelor's analysis is based on the assumption that the velocity field is large-scale, that is the kinetic energy spectrum decays as O(k(sup -3)) or steeper. Since the scalar spectrum is confirmed, this also supports this form of the kinetic energy spectrum. The study of equatorial regions of TOMS data revealed the efficiency of the KL method is in detecting and separating a wave-like measurement artifact inherently present in the dataset due to the non-perfect correction for cross-track bias. Just two to three eigenfunctions represent the error, which makes it possible to enhance the data by reconstituting it from the data by eliminating the subspace of artifactual eigenfunctions. This represents a highly efficient means for achieving an improved rendering of the data. This has been implemented on the database. A wide range of techniques and algorithms have been developed for the repair and extension of the TOMS database.
This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.
This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.
The Astromaterials Acquisition and Curation office at NASA Johnson Space Center curates all of NASA's extraterrestrial samples, the most extensive set of astromaterials samples available to the research community worldwide. The office allocates ~1500 individual samples to researchers and students each year and has served the planetary research community for 45+ years. The Astromaterials Curation office provides access to its sample data repository and digital resources to support the research needs of sample investigators and to aid in the selection and request of samples for scientific study. These resources can be found on the Astromaterials Acquisition and Curation website at https://curator.jsc.nasa.gov. To better serve our users, we have engaged in several activities to enhance the data available for astromaterials samples, to improve the accessibility and performance of the website, and to address user feedback. We havealso put plans in place for continuing improvements to our existing data products.
Progress on the Mesoscale and Severe Storms (MASS) data management and analysis system is described. An interactive atmospheric data base management software package to convert four types of data (Sounding, Single Level, Grid, Image) into standard random access formats is implemented and integrated with the MASS AVE80 Series general purpose plotting and graphics display data analysis software package. An interactive analysis and display graphics software package (AVE80) to analyze large volumes of conventional and satellite derived meteorological data is enhanced to provide imaging/color graphics display utilizing color video hardware integrated into the MASS computer system. Local and remote smart-terminal capability is provided by installing APPLE III computer systems within individual scientist offices and integrated with the MASS system, thus providing color video display, graphics, and characters display of the four data types.
A synoptic of programmatic and technical lessons learned in the development of aerothermodynamic data bases for the X-33 and X-34 programs is presented in general terms and from the perspective of the NASA Langley Research Center Aerothermodynamics Branch. The format used is that of the aerothermodynamic chain, the links of which are personnel, facilities, models/test articles, instrumentation, test techniques, and computational fluid dynamics (CFD). Because the aerodynamic data bases upon which the X-33 and X-34 vehicles will fly are almost exclusively from wind tunnel testing, as opposed to CFD, the primary focus of the lessons learned is on ground-based testing.
The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.
A new technique for estimating electron density perturbation amplitudes of traveling ionospheric disturbances (TIDs), using HF radar data, is presented. TIDs are observed in HF radar data as enhancements of the ground-scattered power which propagate through the radar's field of view. These TIDs are the ionospheric manifestation of atmospheric acoustic-gravity waves. TID electron density perturbation amplitudes were estimated by simulating the radar returns, using HF ray tracing through a model ionosphere perturbed by a model gravity wave. The simulation determined the return power in the ground-scattered portion of the signal as a function of range, and this was compared to HF radar data from the Goose Bay HF radar at a time when evidence of gravity waves was present in the data. By varying the amplitude of the electron density perturbation in the model it was possible to estimate the perturbation of the actual wave. It was found that the perturbations that are observed by the Goose Bay HF radar are of the order of 20% to 35%. It was also found that the number of observable power enhancements, and the relative amplitudes of these enhancements, depended on the vertical thickness of the gravity wave's source region. From the simulations and observations it was estimated that the source region for the case presented here was approximately 20 km thick. In addition, the energy in the wave packet was calculated and compared to an estimate of the available energy in the source region. It was found that the wave energy was about 0.2% of the estimated available source region energy.