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NASA NTRS2018

Lessons Learned from Recent Rapid Imaging of Earthquake Ruptures with Satellite Geodesy

Rapid determination of the location and extent of earthquake ruptures at the surface and at depth is helpful for disaster response, as it allows prediction of the likely area of major damage from the earthquake and can help with rescue and recovery planning. The Caltech-Jet Propulsion Laboratory (JPL) Advanced Rapid Imaging and Analysis (ARIA) project has responded to many recent large earthquakes to process geodetic data and help determine the location and extent of ruptures. With the increasing availability of near real-time data from the Global Positioning System (GPS) and other global navigation satellite system receivers in active tectonic regions, and with the shorter repeat times of many recent and newly launched radar satellites, geodetic data can now be obtained quickly after earthquakes or other disasters. We have been building an ARIA data system that can ingest, catalog, and process geodetic data and combine it with seismic analysis to estimate the fault rupture locations and slip distributions for large earthquakes that are on or near land.

Simons, Mark↗

NASA NTRS2003

North Alabama Lightning Mapping Array (LMA): VHF Source Retrieval Algorithm and Error Analyses

Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results. However, for many source locations, the Curvature Matrix Theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

Koshak, W. J.↗

NASA NTRS2021

Spatiotemporal Methane Emissions from Global Reservoirs

Methane (CH4) is a greenhouse gas which contributes significantly to global warming and has atmospheric concentrations which have increased considerably in the last few decades, primarily due to human-induced emissions. Natural sources such as wetlands and inland aquatic systems (i.e., reservoirs, lakes, rivers) contribute substantially to global emissions but these natural systems comprise the most uncertain components of the CH4 budget. This study addresses multiple gaps and uncertainties associated with global CH4 emissions from reservoirs and undertakes a spatial and temporal assessment of global reservoir emissions. The results from this study suggest that reservoirs occupy a global area about 300,000 km2 (comparable to the size of the country of Italy) and emit 10.1 Tg CH4 yr-1. We identify data and methodological elements of previous estimates that indicate they may overestimate these emissions. This work provides a suite of global data sets, gridded at 0.25° × 0.25°, considering reservoir surface area, spatial distribution, eco-climatic system type, and the full annual cycle of daily CH4 emissions.

Spatiotemporal↗

NASA NTRSDate not supplied

Low Latency Flux and Concentration Datasets in Support of Greenhouse Gas Monitoring Based on NASA's GEOS Modeling and Data Assimilation System

We present efforts to develop space-based greenhouse gas monitoring systems that can provide low latency information and traceability to independent observations. Through support from its Carbon Monitoring System program, NASA has developed the capability to assimilate XCO2 retrievals from the Orbiting Carbon Observatory, 2 (OCO-2) into the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS) to create gap-filled, three-dimensional (3D) estimates of CO2 mixing ratio. When OCO-2 data are not available, concentration fields are further informed by a bottom-up flux package based on remotely sensed fire radiative power, nighttime lights, and vegetation reflectance combined with estimates of atmospheric growth rate based on surface in situ data. The 3D nature of this dataset supports evaluation with independent aircraft data, helping to ensure transparency of remotely sensed data products. These quasi-operational data are currently produced 2-3 months behind real time and are distributed via NASA and international dashboard services to a variety of end users. In this presentation, we provide an overview of the system as well as remaining data gaps and modeling challenges. We also highlight the application of this dataset for detecting emissions anomalies associated with COVID-19 and comparing against independent emissions estimates. Finally, we highlight a new NASA initiative called the Earth Information System (EIS), which aims to support open science and applications by leveraging emerging cloud computing capabilities to increase access to NASA’s greenhouse gas datasets, opportunities for co-development, and transparency in methods for analysis and flux attribution.

Lesley Ott↗

NASA NTRS2000

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Rutherford, Brian↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Reliability↗

NASA NTRS1993

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.

REAL TIME↗

NASA NTRS1976

On the detection of a cometary mass distribution

The problem of detecting a possible cometary distribution on the fringes of the solar system is examined. The acceleration of a space probe due to a hypothetical cometary mass distribution with the surface density rising to a maximum and subsequently falling off with increasing distance from the sun is analyzed. The total minimum detectable cometary mass for the Pioneer and Mariner spacecraft is estimated on the basis of this model to be on the order of 1000 earth masses. Precision tracking of deep space probes is less sensitive by three orders of magnitude for the detection of an unseen cometary mass distribution at the fringes of the solar system than are the secular perturbations of long-period comets.

Boss, A. P.↗

NASA NTRS1971

Estimating Weibull parameters for materials

The statistical analysis of strength and fracture of materials in general, with application to fiber composites are discussed. The weakest link model is considered in a fairly general form, and the resulting equations are demonstrated by using a Weibull distribution for flaws. This distribution appears naturally in a variety of problems, and therefore additional attention is devoted to analysis and statistical estimation connected with this distribution. Special working charts are included to facilitate interpretation of observed data and estimation of parameters. Implications of the size effect are considered for various kinds of flaw distributions. Failure and damage in a fiber-reinforced system are described. Some useful graphs are included for predicting the strength of such a system. Recent data on organic-fiber (PRD 49) composite material is analyzed by the Weibull distribution with the methods presented.

Robinson, E. Y.↗

NASA NTRS1974

Evaluation of usefulness of Skylab EREP S-190 and S-192 imagery in multistage forest surveys

The author has identified the following significant results. The digital timber volume prediction system was tested with another test area in the Trinity Alps. The estimated gain in precision was somewhat lower than the estimate for the first test area (35%). A combined interpretation of the two areas was made, yielding an estimated gain of 44%, with high statistical significance. This interpretation was used to calibrate the system for an interpretation of 43 primary sample units distributed over 1600 square miles. Preliminary results indicate that a gain of 35% can be realized over this large area in northern California.

Langley, P. G.↗

NASA NTRS1996

First Two Years of Observations NASA ACTS Propagation Experiment Central Oklahoma Site

Continuous observations from December 1, 1993 through November 30, 1995 were made at the ACTS Propagation Terminal on the roof of the Sarkeys Energy Center at the University of Oklahoma in Norman, Oklahoma. Beacon and radiometer observations were combined to calibrate the beacon system for the estimation of total attenuation (attenuation relative to free space) and attenuation relative to clear sky (gaseous absorption component removed). Empirical cumulative distributions (edf's) were compiled for each month of observation and for each year. The annual edf's are displayed in the figures, the monthly and annual edf's are listed in the tables. The tables are organized by blocks and pages within a block. The blocks correspond to the headings in the edf files generated by the ACTS Preprocessing (actspp) software and contained in the fourth disk in the set of ACTS Propagation Experiment CD-ROMs generated by the University of Texas.

Crane, Robert K.↗

NASA NTRS1982

Application of future remote sensing systems to irrigation

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Miller, L. D.↗

NASA NTRS1993

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that the authors' techniques allow more accurate estimation of the global system loading, resulting in fewer object migrations than local methods. The authors' method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive load-balancing methods. Results from a preliminary analysis of another system and from simulation with a synthetic load provide some evidence of more general applicability.

LOAD CONTROL↗

NASA NTRS2005

A Tower-based Prototype VHF/UHF Radar for Subsurface Sensing: System Description and Data Inversion Results

Knowledge of subsurface characteristics such as permittivity variations and layering structure could provide a breakthrough in many terrestrial and planetary science disciplines. For Earth science, knowledge of subsurface and subcanopy soil moisture layers can enable the estimation of vertical flow in the soil column linking surface hydrologic processes with that in the subsurface. For planetary science, determining the existence of subsurface water and ice is regarded as one of the most critical information needs for the study of the origins of the solar system. The subsurface in general can be described as several near-parallel layers with rough interfaces. Each homogenous rough layer can be defined by its average thickness, permittivity, and rms interface roughness assuming a known surface spectral distribution. As the number and depth of layers increase, the number of measurements needed to invert for the layer unknowns also increases, and deeper penetration capability would be required. To nondestructively calculate the characteristics of the rough layers, a multifrequency polarimetric radar backscattering approach can be used. One such system is that we have developed for data prototyping of the Microwave Observatory of Subcanopy and Subsurface (MOSS) mission concept. A tower-mounted radar makes backscattering measurements at VHF, UHF, and L-band frequencies. The radar is a pulsed CW system, which uses the same wideband antenna to transmit and receive the signals at all three frequencies. To focus the beam at various incidence angles within the beamwidth of the antenna, the tower is moved vertically and measurements made at each position. The signals are coherently summed to achieve focusing and image formation in the subsurface. This requires an estimate of wave velocity profiles. To solve the inverse scattering problem for subsurface velocity profile simultaneously with radar focusing, we use an iterative technique based on a forward numerical solution of the layered rough surface problem. The layers are each defined in terms of a small number of unknown distributions as given above. An a priori estimate of the solution is first assumed, based on which the forward problem is solved for the backscattered measurements. This is compared with the measured data and using iterative techniques an update to the solution for the unknowns is calculated. The process continues until convergence is achieved. Numerical results will be shown using actual radar data acquired with the MOSS tower radar system in Arizona in Fall 2003, and compared with in-situ measurements.

Moghaddam, Mahta↗

NASA NTRS1997

Computer Code Study of Asteroid Entry into Venusian Atmosphere: Pressure and Density Fields

Analysis of the cratering records on the Moon, Mercury, and Mars have shown similar size-frequency distributions of craters produced during the late heavy bombardment of the inner solar system (Strom, 1988). Venus provides a valuable data base of information on the impacting population for more recent time. Because of resurfacing events, the Venusian cratering record has been estimated to be only about 500 million years old, and for the most part is in pristine condition, thereby producing an opportunity to discover the properties (size/velocity distribution) of the objects that recently impacted its surface. The Magellan IR mapping of the Venusian surface has produced an extremely high-quality set of crater topographies. The observed deficit of small craters is qualitatively explained by atmospheric effects on impactor breakup and the retardation effects of pressure on crater formation. Information about resurfacing history and impactor flux population can only be conjectured using arrant approximations for atmospheric effects on crater size scaling, such as assuming the absence of pressure effects or using other ad hoc approximations for this dependence. The recent work by Ivanov et al.(1986; 1992); Phillips et al.(199 1; 1992); Schaber et al. (1992) and others support the notion that atmospheric effects may have strongly influenced the Venusian cratering record. The work reported here looks at the potential synergism of aerodynamic entry and the gas dynamic flow fields that govern during the time scale and in the vicinity of crater formation.

Schmidt, Robert M.↗

NASA NTRS2000

Dietary Sodium Effects on Bone Loss and Calcium Metabolism During Bed Rest

The acceleration of age-related bone loss is one of the most detrimental effects of space flight. The ability to understand and counteract this loss will be critical for crew health and safety during and after long-duration missions. Studies in healthy ambulatory individuals have linked high salt (sodium) diets, hypercalciuria, and increased renal stone risk. Dietary salt may modulate bone loss through changes in calcium metabolism and the calcium endocrine system. The research proposed here will determine the role of dietary salt in the loss of bone during simulated space flight. Calcium metabolism will be determined through calcium kinetics studies, endocrine and biochemical measurements; and estimates of the mass, distribution and mechanical properties of bone, in subjects fed low (100 mmol sodium/day) or high (250 mmol sodium/day) levels of dietary salt during 28 days of headdown tilt bedrest. This research addresses the role of dietary salt in the loss of bone and calcium in space flight, and integrates the changes in calcium metabolism with those occurring in other physiologic systems. These data will be critical for both countermeasure development, and in determination of nutritional requirements for extended-duration space flight. The potential countermeasures resulting from this research will reduce health risks due to acceleration of age-related osteoporosis and increased risk of renal stone formation..

Smith, Scott M.↗

NASA NTRS1983

Temperature-time distribution and thermal stresses on the RTG fins and shell during water cooling

Radioisotope thermoelectric generator (RTG) packages designed for space missions generally do not require active cooling. However, the heat they generate cannot remain inside of the launch vehicle bay and requires active removal. Therefore, before the Shuttle bay door is closed, the RTG coolant tubes attached to the heat rejection fins must be filled with water, which will circulate and remove most of the heat from the cargo bay. There is concern that charging a system at initial temperature around 200 C with water at 24 C can cause unacceptable thermal stresses in the RTG shell and fins. A computer model is developed to estimate the transient temperature distribution resulting from such charging. The thermal stresses resulting from the temperature gradients do not exceed the elastic deformation limit for the material. Since the simplified mathematical model for thermal stresses tends to overestimate stresses, it is concluded that the RTG can be cooled by introducing water at 24 C to the initially hot fin coolant tubes while the RTG is in the Shuttle cargo bay.

Turner, R. H.↗