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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Coevolution of Machine Learning and Process-Based Modelling to Revolutionize Earth and Environmental Sciences: A Perspective

Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support. In this perspective, we assert that the cultural barriers between the ML and PBM communities limit the potential of ML, and even its ‘hybridization’ with PBM, for EES applications. Fundamental, but often ignored, differences between ML and PBM are discussed as well as their strengths and weaknesses in light of three overarching modelling objectives in EES, (1) nowcasting and prediction, (2) scenario analysis, and (3) diagnostic learning. The paper ponders over a ‘coevolutionary’ approach to model building, shifting away from a borrowing to a co-creation culture, to develop a generation of models that leverage the unique strengths of ML such as scalability to big data and high-dimensional mapping, while remaining faithful to process-based knowledge base and principles of model explainability and interpretability, and therefore, falsifiability.

Saman Razavi↗
NASA NTRS2019

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Snow is an important component of the terrestrial freshwater budget in high mountainAsia (HMA) and contributes to the runoff in Himalayan rivers through snowmelt. Despitethe importance of snow in HMA, considerable spatiotemporal uncertainty exists across the different estimates of snow water equivalent for this region. In order to better estimate snow water equivalent, radiative transfer models are often used in conjunction with microwave brightness temperature measurements. In this study, the efficacy of support vector machines (SVMs), a machine learning technique, to predict passive microwave brightness temperature spectral difference (1Tb) as a function of geophysical variables (snow water equivalent, snow depth, snow temperature, and snow density) is explored through a sensitivity analysis. The use of machine learning (as opposed to radiative transfer models) is a relatively new and novel approach for improving snow water equivalent estimates. The Noah-MP land surface model within the NASALand Information System framework is used to simulate the hydrologic cycle over HMA and model geophysical variables that are then used for SVM training. The SVMsserve as a nonlinear map between the geophysical space (modeled in Noah-MP) andthe observation space (1Tb as measured by the radiometer). Advanced MicrowaveScanning Radiometer-Earth Observing System measured passive microwave brightness temperatures over snow-covered locations in the HMA region are used as training data during the SVM training phase. Sensitivity of well-trained SVMs to each Noah-MP modeled state variable is assessed by computing normalized sensitivity coefficients. Sensitivity analysis results generally conform with the known first-order physics. Input states that increase volume scattering of microwave radiation, such as snow density and snow water equivalent, exhibit a plurality of positive normalized sensitivity coefficients. In general, snow temperature was the most sensitive input to the SVM predictions. The sensitivity of each state is location and time dependent. The signs of normalized sensitivity coefficients that indicate physical irrationality are ascribed to significant cross-correlation between Noah-MP simulated states and decreased SVM prediction capability at specific locations due to insufficient training data. SVM prediction pitfalls do exist that serve to highlight the limitations of this particular machine learning algorithm.

high mountain Asia↗
NASA NTRS1981

Development of Great Lakes algorithms for the Nimbus-G coastal zone color scanner

A series of experiments in the Great Lakes designed to evaluate the application of the Nimbus G satellite Coastal Zone Color Scanner (CZCS) were conducted. Absorption and scattering measurement data were reduced to obtain a preliminary optical model for the Great Lakes. Available optical models were used in turn to calculate subsurface reflectances for expected concentrations of chlorophyll-a pigment and suspended minerals. Multiple nonlinear regression techniques were used to derive CZCS water quality prediction equations from Great Lakes simulation data. An existing atmospheric model was combined with a water model to provide the necessary simulation data for evaluation of the preliminary CZCS algorithms. A CZCS scanner model was developed which accounts for image distorting scanner and satellite motions. This model was used in turn to generate mapping polynomials that define the transformation from the original image to one configured in a polyconic projection. Four computer programs (FORTRAN IV) for image transformation are presented.

Tanis, F. J.↗
NASA NTRS1999

Two Dimensional Dendritic Crystal Growth for Weak Undercooling

We discuss the framework and issues brought forth in the recent work of Kunka, Foster & Tanveer, which incorporates small but nonzero surface energy effects in the nonlinear dynamics of a conformal mapping function z(zeta,t) that maps the upper-half zeta plane into the exterior of a dendrite. In this paper, surface energy effects on the singularities of z(zeta,t) in the lower-half plane were examined, as they move toward the real axis from below. In particular, the dynamics of complex singularities manifests itself in predictions on nature and growth rate of disturbances, as well as of coarsening.

Tanveer, S.↗
NASA NTRS2004

Microcalorimeters with NTD and Expitaxial Germanium Thermistors for High Resolution X-Ray Spectroscopy

This is a progress report for the second year of a three year SR&T grant to continue the advancement of NTD-based microcalorimeters. We reported last year that we re-prioritized certain aspects of the statement of work and chose to emphasize issues of array development in the first year rather than wait until year two. Consequently, some of the projects scheduled for the first year were delayed to the second year and we report on those topics here. These include: a) Measurements that map out JFET , thermistor, l/f and feedback resistor noise; b) Investigations that evaluate the limits of the JFET preamplifier circuitry as it pertains to stability at the 2 eV level; The results of a) and b) have led to preliminary measurements that demonstrate 3.08 eV resolution at 6 keV. c) Calculations that can predict the current performance.

Silver, Eric↗
NASA NTRS2004

The Utility of Auroral Image-based Activities Metrics

Auroral activity indices such as Hemispheric Power and Auroral Boundary are currently key data products used for space weather predictions and nowcasting. However, these products are necessarily based on limited observations which must be extrapolated to provide global coverage. The advent of routine space-based auroral imaging in the last decade offers the seeming advantage of more detailed measures of auroral activity. Examples of image-derived products include energy deposition maps, oval location, cap size, and morphological classification. However, activity metrics derived from auroral images have shortcomings, as well. For example, limited fields-of-view and orbital motion prevent full coverage of the auroral regions. This paper will examine the utility of activity metrics derived h m auroral images for operational purposes. The eight-year collection of Polar UVI images databased in the UVI Online Search Tool (OST) will be used to illustrate the advantages and shortcomings of auroral activity metrics. The potential role of other currently-active imaging missions will also be examined and correlative studies to date using auroral imaging will be summarized.

Germany, G.↗
NASA NTRSDate not supplied

Benchmark Problem Development for Testing Maturity of Intelligent Contingency Management Tools

This paper presents a process used to develop appropriate scenarios and metrics for evaluating the maturity of intelligent contingency management algorithms. A benchmark scenario is a reference point against which something can be measured, compared, or assessed. Creating an accurate benchmark requires considerable research and expertise. The scenario itself is an artificial representation of a real-world event, designed to achieve a set of learning objectives through experiential learning. Designing an effective benchmark simulation scenario requires careful planning, including identification of clear objectives; capability assessment of the algorithm/tool being evaluated; assessment of necessary levels of fidelity; development of a process flow map of events and event interactions; and identification of metrics that map back to objectives. Thus, a benchmark scenarios for contingency management might consist of one or several commonly used functions taken from real world applications, used for evaluation, characterization and performance measurement of a contingency management algorithm. Behavior of the contingency management algorithm under different environmental conditions should then be able to be predicted using a set of benchmark functions. The paper describes the resulting benchmark problem as an illustration of the application of this process.

Jon Holbrook↗
NASA NTRS2022

Bryce Canyon Water Resources: Monitoring Vegetation Health and Water Availability in Bryce Canyon National Park for Drought Stress Mitigation Planning

Bryce Canyon National Park is home to groundwater-dependent ecosystems (GDEs) that are threatened by a multidecadal drought and increased groundwater extraction due to a spike in tourism. These ecosystems contain unique species that are only found in areas where near-surface groundwater is present, such as aspen groves and fens. These species contribute to the high biodiversity found in Bryce Canyon, which boosts an ecosystem’s productivity and the services it provides to the park. Unfortunately, many of these GDEs are too small to identify with traditional Earth observation platforms and are difficult to physically reach for monitoring purposes. This project partnered with the National Park Service to identify springs and seeps as a proxy for GDEs within Bryce Canyon from 2013–2022. Furthermore, this project tested the feasibility of various methods to detect and monitor springs and seeps and therefore facilitate the partner’s efforts to conserve these ecologically valuable GDEs in Bryce Canyon. The team mapped groundwater discharge with high resolution National Agriculture Imagery Program (NAIP) and assessed park vegetation trends with Landsat 8 Operational Land Imager (OLI) and PlanetScope imagery. In-situ precipitation data and the Western Land Data Assimilation System (WLDAS) were used to produce time series of climatic variables. Seeps and spring locations were predicted using random forest classification and maximum entropy machine learning models.

Groundwater dependent ecosystems↗
NASA NTRSDate not supplied

Performance and Accuracy Assessment of Line Marching Algorithm Computations Utilizing GPUs Within a Predictive GNSS Quality Service

This paper presents a detailed analysis of the accuracy and performance of line marching algorithms executing on a GPU. In the context of an accurate Global Navigation Satellite System(GNSS) quality of service simulation, horizon sky-plots are a useful tool to determine satellite visibility in the presence of obstructions from objects, such as buildings or dense foliage. In order to accurately model satellite visibility at a point of interest on a map, a horizon plot can identify the viewing angles at which objects are blocking the sky. This computation requires traversing a line starting at the point of interest on a 2D altitude map, moving outward for every azimuth angle. To explore the performance of this computation, we propose a new dynamic stopping condition for the traversal of the line, benefiting from objects close to the point of interest. We compare the accuracy of common line marching algorithms, and consider their parallel performance when developed in CUDA. We find that our proposed stopping condition for line marching provides a significant improvement in performance in urban canyon sky-plots, as compared to previous work. Additionally, these results show that simpler algorithms, such as the digital differential analyzer line algorithm, are better suited for GPUs than more sophisticated schemes such as Bresenham’s algorithm, specifically in the context of sky-plothorizon computations. The trade-off between accuracy and performance is analyzed and providing guidance that depends on the targeted goal of the GNSS application.

GNSS↗
NASA NTRS1988

Thermal distortion analysis of the space station solar dynamic concentrator

A method was developed to evaluate the thermal distortion of the Space Station Solar Dynamic Concentrator and the effects of thermal distortion on concentrator optical performance. The analytical method includes generating temperature distributions with TRASYS and SINDA models, interfacing the SINDA results with the SINDA-NASTRAN Interface Program (SNIP), calculating thermal distortion with a NASTRAN/PATRAN finite element model, and providing flux distribution maps within the receiver with the ray tracing OFFSET program. Temperature distributions, thermally induced slope errors, and flux distribution maps within the receiver are discussed. Results during a typical orbit indicate that temperatures of the hexagonal panels and triangular facets range between -18 and 99 C (-1 to 210 F), facet rotations are less than 0.2 mrad, and a change in facet radius due to thermal flattening is less than 5 percent. The predicted power loss with thermal distortion effects was less than 0.3 percent. The thermal distortion of the Solar Dynamic concentrator has negligible effect on the flux distribution within the receiver cavity.

Trudell, Jeffrey J.↗
NASA NTRS1988

Thermal distortion analysis of the Space Station solar dynamic concentrator

A method was developed to evaluate the thermal distortion of the Space Station Solar Dynamic Concentrator and the effects of thermal distortion on concentrator optical performance. The analytical method includes generating temperature distributions with TRASYS and SINDA models, interfacing the SINDA results with the SINDA-NASTRAN Interface Program (SNIP), calculating thermal distortion with a NASTRAN/PATRAN finite element model, and providing flux distribution maps within the receiver with the ray tracing OFFSET program. Temperature distributions, thermally induced slope errors, and flux distribution maps within the receiver are discussed. Results during a typical orbit indicate that temperatures of the hexagonal panels and triangular facets range between -18 and 99 C (-1 to 210 F), facet rotations are less than 0.2 mrad, and a change in facet radius due to thermal flattening is less than 5 percent. The predicted power loss with thermal distortion effects was less than 0.3 percent. The thermal distortion of the Solar Dynamic concentrator has negligible effect on the flux distribution within the receiver cavity.

Trudell, Jeffery J.↗
NASA NTRS1989

Hydrogen-silicon carbide interactions

A study of the thermochemistry and kinetics of hydrogen environmental attack of silicon carbide was conducted for temperatures in the range from 1100 C to 1400 C. Thermodynamic maps based on the parameters of pressure and oxygen/moisture content were constructed. With increasing moisture levels, four distinct regions of attack were identified. Each region is defined by the thermodynamically stable solid phases. The theoretically stable solid phases of Region 1 are silicon carbide and silicon. Experimental evidence is provided to support this thermodynamic prediction. Silicon carbide is the single stable solid phase in Region 2. Active attack of the silicon carbide in this region occurs by the formation of gases of SiO, CO, CH4, SiH4, and SiH. Analysis of the kinetics of reaction for Region 2 at 1300 C show the attack of the silicon carbide to be controlled by gas phase diffusion of H2O to the sample. Silicon carbide and silica are the stable phases common to Regions 3 and 4. These two regions are characterized by the passive oxidation of silicon carbide and formation of a protective silica layer.

Eckel, Andrew J.↗
NASA NTRS1990

Hydrogen-silicon carbide interactions

A study of the thermochemistry and kinetics of hydrogen environmental attack of silicon carbide was conducted for temperatures in the range from 1100 C to 1400 C. Thermodynamics maps based on the parameters of pressure and oxygen/moisture content were constructed. With increasing moisture levels, four distinct regions of attack were identified. Each region is defined by the thermodynamically stable solid phases. The theoretically stable solid phases of region 1 are silicon carbide and silicon. Experimental evidence is provided to support this thermodynamic prediction. Silicone carbide is the single stable solid phase in region 2. Active attack of the silicon carbide in this region occurs by the formation of gases of SiO, CO, CH4, SiH4 and SiH. Analyses of the kinetics of reaction for region 2 at 1300 C show the attack of the silicon carbide to be controlled by gas phase diffusion of H2O to the sample. Silicon carbide and silica are the stable phases common to regions 3 and 4. These two regions are characterized by the passive oxidation of silicon carbide and formation of a protective silica layer.

Eckel, Andrew J.↗
NASA NTRS1991

Application of powder densification models to the consolidation processing of composites

Unidirectional fiber reinforced metal matrix composite tapes (containing a single layer of parallel fibers) can now be produced by plasma deposition. These tapes can be stacked and subjected to a thermomechanical treatment that results in a fully dense near net shape component. The mechanisms by which this consolidation step occurs are explored, and models to predict the effect of different thermomechanical conditions (during consolidation) upon the kinetics of densification are developed. The approach is based upon a methodology developed by Ashby and others for the simpler problem of HIP of spherical powders. The complex problem is devided into six, much simpler, subproblems, and then their predicted contributions are added to densification. The initial problem decomposition is to treat the two extreme geometries encountered (contact deformation occurring between foils and shrinkage of isolated, internal pores). Deformation of these two geometries is modelled for plastic, power law creep and diffusional flow. The results are reported in the form of a densification map.

Wadley, H. N. G.↗
NASA NTRS2000

Gravity and Nonconservative Force Model Tuning for the GEOSAT Follow-On Spacecraft

The US Navy's GEOSAT Follow-On spacecraft was launched on February 10, 1998 and the primary objective of the mission was to map the oceans using a radar altimeter. Three radar altimeter calibration campaigns have been conducted in 1999 and 2000. The spacecraft is tracked by satellite laser ranging (SLR) and Doppler beacons and a limited amount of data have been obtained from the Global Positioning Receiver (GPS) on board the satellite. Even with EGM96, the predicted radial orbit error due to gravity field mismodelling (to 70x70) remains high at 2.61 cm (compared to 0.88 cm for TOPEX). We report on the preliminary gravity model tuning for GFO using SLR, and altimeter crossover data. Preliminary solutions using SLR and GFO/GFO crossover data from CalVal campaigns I and II in June-August 1999, and January-February 2000 have reduced the predicted radial orbit error to 1.9 cm and further reduction will be possible when additional data are added to the solutions. The gravity model tuning has improved principally the low order m-daily terms and has reduced significantly the geographically correlated error present in this satellite orbit. In addition to gravity field mismodelling, the largest contributor to the orbit error is the non-conservative force mismodelling. We report on further nonconservative force model tuning results using available data from over one cycle in beta prime.

Lemoine, Frank G.↗
NASA NTRS2009

An Operational Perspective of Total Lightning Information

The close and productive collaborations between the NWS Warning and Forecast Office, the Short Term Prediction and Research Transition Center at NASA Marshall Space Flight Center and the University of Alabama in Huntsville have provided a unique opportunity for science sharing and technology transfer. One significant technology transfer that has provided immediate benefits to NWS forecast and warning operations is the use of data from the North Alabama Lightning Mapping Array. This network consists of ten VHF receivers deployed across northern Alabama and a base station located at the National Space Science and Technology Center. Preliminary investigations done at WFO Huntsville, along with other similar total lightning networks across the country, have shown distinct correlations between the time rate-of-change of total lightning and trends in intensity/severity of the parent convective cell. Since May 2003 when WFO HUN began receiving these data - in conjunction with other more traditional remotely sensed data (radar, satellite, and surface observations) -- have improved the situational awareness of the WFO staff. The use of total lightning information, either from current ground based systems or future space borne instrumentation, may substantially contribute to the NWS mission, by enhancing severe weather warning and decision-making processes. Operational use of the data has been maximized at WFO Huntsville through a process that includes forecaster training, product implementation, and post event analysis and assessments. Since receiving these data, over 50 surveys have been completed highlighting the use of total lightning information during significant events across the Tennessee Valley. In addition, around 150 specific cases of interest have been archived for collaborative post storm analysis. From these datasets, detailed trending information from radar and total lightning can be compared to corresponding damage reports. This presentation will emphasize the effective use of total lightning information in warning decision making along with best practices for implementation of new technologies into operations.

Nadler, David J.↗
NASA NTRS2005

NASA Tech Briefs, December 2005

Topics covered include: Video Mosaicking for Inspection of Gas Pipelines; Shuttle-Data-Tape XML Translator; Highly Reliable, High-Speed, Unidirectional Serial Data Links; Data-Analysis System for Entry, Descent, and Landing; Hybrid UV Imager Containing Face-Up AlGaN/GaN Photodiodes; Multiple Embedded Processors for Fault-Tolerant Computing; Hybrid Power Management; Magnetometer Based on Optoelectronic Microwave Oscillator; Program Predicts Time Courses of Human/ Computer Interactions; Chimera Grid Tools; Astronomer's Proposal Tool; Conservative Patch Algorithm and Mesh Sequencing for PAB3D; Fitting Nonlinear Curves by Use of Optimization Techniques; Tool for Viewing Faults Under Terrain; Automated Synthesis of Long Communication Delays for Testing; Solving Nonlinear Euler Equations With Arbitrary Accuracy; Self-Organizing-Map Program for Analyzing Multivariate Data; Tool for Sizing Analysis of the Advanced Life Support System; Control Software for a High-Performance Telerobot; Java Radar Analysis Tool; Architecture for Verifiable Software; Tool for Ranking Research Options; Enhanced, Partially Redundant Emergency Notification System; Close-Call Action Log Form; Task Description Language; Improved Small-Particle Powders for Plasma Spraying; Bonding-Compatible Corrosion Inhibitor for Rinsing Metals; Wipes, Coatings, and Patches for Detecting Hydrazines; Rotating Vessels for Growing Protein Crystals; Oscillating-Linear-Drive Vacuum Compressor for CO2; Mechanically Biased, Hinged Pairs of Piezoelectric Benders; Apparatus for Precise Indium-Bump Bonding of Microchips; Radiation Dosimetry via Automated Fluorescence Microscopy; Multistage Magnetic Separator of Cells and Proteins; Elastic-Tether Suits for Artificial Gravity and Exercise; Multichannel Brain-Signal-Amplifying and Digitizing System; Ester-Based Electrolytes for Low-Temperature Li-Ion Cells; Hygrometer for Detecting Water in Partially Enclosed Volumes; Radio-Frequency Plasma Cleaning of a Penning Malmberg Trap; Reduction of Flap Side Edge Noise - the Blowing Flap; and Preventing Accidental Ignition of Upper-Stage Rocket Motors.

Source record↗
NASA NTRS2015

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites (PART 1)

By the end of the current decade, there are plans to deploy several geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of geostationary platforms to achieve continuous time-resolved high-density observations over continental domains for mapping pollutant sources and variability at diurnal and local scales. In this paper, we use a novel approach to sample a very high global resolution model (GEOS-5 at 7 km horizontal resolution) to produce a dataset of synthetic carbon monoxide pollution observations representative of those potentially obtainable from a GEO satellite constellation with predicted measurement sensitivities based on current remote sensing capabilities. Part 1 of this study focuses on the production of simulated synthetic measurements for air quality OSSEs (Observing System Simulation Experiments). We simulate carbon monoxide nadir retrievals using a technique that provides realistic measurements with very low computational cost. We discuss the sampling methodology: the projection of footprints and areas of regard for geostationary geometries over each of the North America, East Asia and Europe regions; the regression method to simulate measurement sensitivity; and the measurement error simulation. A detailed analysis of the simulated observation sensitivity is performed, and limitations of the method are discussed. We also describe impacts from clouds, showing that the efficiency of an instrument making atmospheric composition measurements on a geostationary platform is dependent on the dominant weather regime over a given region and the pixel size resolution. These results demonstrate the viability of the "instrument simulator" step for an OSSE to assess the performance of a constellation of geostationary satellites for air quality measurements.

GEOS-5↗