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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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NASA NTRS2023

Diverging Trends in Rain-on-Snow Over High Mountain Asia

Rain-on-snow (ROS) over snow-dominated regions such as High Mountain Asia (HMA) modulates snowmelt and runoff and is key contributor in influencing water availability and hazards (e.g., floods and landslides). We studied the trends in ROS in HMA over the past two decades from 2001 to 2018 using the land surface model Noah-MP driven by an ensemble precipitation data set. Our results show that changes in precipitation phase and rainfall are altering ROS. Because of the strong physical heterogeneity and atmospheric dynamics of HMA, ROS characteristics and trends are region-dependent and ROS occurs predominantly over the Indus, Ganges-Brahmaputra, and northwestern basins. In the Indus, ROS representing ∼5% of the annual precipitation and ∼20% of the annual snowmelt, has an increasing trend. This is contrary to the Ganges-Brahmaputra characterized by decreasing ROS trends, where it represents ∼11% of the annual precipitation and ∼60% of the annual snowmelt. In the northwestern basins, ROS has bidirectional trends due to elevation patterns and trends in rainfall, and it constitutes ∼5 to ∼10% of the annual precipitation. Increasing trends in ROS over Indus contribute to reducing the snowpack in late summer, with concerns of reduced water availability and increased groundwater exploitation. Similarly, because of its high amount and contribution to snowmelt, the decreasing ROS trends in the Ganges-Brahmaputra will have consequences of decreased recharge from the headwaters and exacerbated use of groundwater unless increasing trends in rainfall compensate for the decreasing snowmelt. These results provide new insights on ROS-driven changes in the hydrological cycle over HMA.

rain-on-snow↗
NASA NTRS2017

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, Rainy Day can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, Rainy Day can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. Rainy Day can be useful for hazard modeling under nonstationary conditions.

Daniel B Wright↗
NASA NTRS2017

Data Production on Past and Future NASA Missions

Data return is a metric that is commonly publicized for all space science missions. In the early days of the Space Program, this figure was small, and could be described in bits or maybe even megabits. But now, missions are capable of returning data volumes two or three orders of magnitude larger. For example, Voyager 1 and 2 combined produced a little over 5 Terabits of data in 39 years of operation. In contrast, the Cassini mission, launched two decades after Voyager, produced about one and a half times those data volumes in half the time. NISAR, an Earth Science Mission currently in implementation, plans to produce over 28 Petabits of raw data in just 3 years. This means that NISAR will produce about as many data in 30 days as the combined data production of nearly all planetary missions to date. These increases in capability are a result of technology enhancements in two main areas: telecommunications architecture (both space and ground segments) and data storage technology. This paper describes the progression of these two technologies over the course of more than three decades of space missions and provides additional insight into the design of the end-to-end NISAR Data System Architecture. Trends in the data are briefly explored and compared to Moore’s Law which provides only a qualitative model for memory growth but not for data production. In summary, early missions are found to be driven by unrefined processes while later missions, having utilized earlier lessons learned, focus more on improvements to flight and ground capabilities. Data return seems to fall into three categories. First, deep space missions are driven by the large distances that limit data return to the Earth. Next, the orbiter infrastructure around Mars helps these missions generate more data than other deep space spacecraft. Finally, near-Earth missions have the greatest capabilities for the studied metrics due to their close proximity to Earth and the ground network availability.

Xaypraseuth, Peter↗
NASA NTRS2010

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Reichle, Rolf↗
NASA NTRS2001

Integrated Workforce Planning Model: A Proof of Concept

Recently, the Workforce and Diversity Management Office at KSC have launched a major initiative to develop and implement a competency/skill approach to Human Resource management. As the competency/skill dictionary is being elaborated, the need for a competency-based workforce-planning model is recognized. A proof of concept for such a model is presented using a multidimensional data model that can provide the data infrastructure necessary to drive intelligent decision support systems for workforce planing. The components of competency-driven workforce planning model are explained. The data model is presented and several schemes that would support the workforce-planning model are presented. Some directions and recommendations for future work are given.

Guruvadoo, Eranna K.↗
NASA NTRS1975

EUV observations of the active sun from the Harvard experiment on ATM

Some extreme UV observations of solar active regions made with a scanning spectroheliometer are described. Spectroheliograms constructed from digital data using a computer-driven cathode-ray tube display show clearly how the appearance of an active region changes as a function of temperature. Flare studies indicate that the impulsive rise in EUV emission occurs essentially simultaneously at all levels from the transition zone to the corona. Observations of sunspots reveal a very intense emission in transition zone lines. A matrix of Mg x rasters covering the entire sun reveals several hundred bright points having dimensions of 30 arc seconds or less. Other observations include coronal holes and prominences.

Noyes, R. W.↗
NASA NTRS1986

The origin of dwarf galaxies, cold dark matter, and biased galaxy formation

A reexamination is conducted of the formation of dwarf, diffuse, metal-poor galaxies due to supernova-driven winds, in view of data on the systematic properties of dwarfs in the Local Group and Virgo Cluster. The critical condition for global gas loss as a result of the first burst of star formation is that the virial velocity lie below an approximately 100 km/sec critical value. This leads, as observed, to two distinct classes of galaxies, encompassing the diffuse dwarfs, which primarily originate from typical density perturbations, and the normal, brighter galaxies, including compact dwarfs, which can originate only from the highest density peaks. This furnishes a statistical biasing mechanism for the preferential formation of bright galaxies in denser regions, enhancing high surface brightness galaxies' clustering relative to the diffusive dwarfs.

Dekel, A.↗
NASA NTRS1985

MAX: A space station computer option

Information on Max, a space station computer option, is given in viewgraph form. The computer option is characterized by embedded, real-time applications; synchronous, cyclic operation and asynchronous, event driven operation; computationally intensive and data intensive processing; a wide range of throughput and memory requirements; a range of fault tolerant requirements from none to full; and maintainability, including capability for on-line substitution in critical systems.

Smith, D. B.↗
NASA NTRS1988

Pilot factors guidelines for the operational inspection of navigation systems

A computerized human engineered inspection technique is developed for use by FAA inspectors in evaluating the pilot factors aspects of aircraft navigation systems. The short title for this project is Nav Handbook. A menu-driven checklist, computer program and data base (Human Factors Design Criteria) were developed and merged to form a self-contained, portable, human factors inspection checklist tool for use in a laboratory or field setting. The automated checklist is tailored for general aviation navigation systems and can be expanded for use with other aircraft systems, transports or military aircraft. The Nav Handbook inspection concept was demonstrated using a lap-top computer and an Omega/VLF CDU. The program generates standardized inspection reports. Automated checklists for LORAN/C and R NAV were also developed. A Nav Handbook User's Guide is included.

Sadler, J. F.↗
NASA NTRS1993

Compiler-assisted multiple instruction rollback recovery using a read buffer

Multiple instruction rollback (MIR) is a technique that has been implemented in mainframe computers to provide rapid recovery from transient processor failures. Hardware-based MIR designs eliminate rollback data hazards by providing data redundancy implemented in hardware. Compiler-based MIR designs have also been developed which remove rollback data hazards directly with data-flow transformations. This paper focuses on compiler-assisted techniques to achieve multiple instruction rollback recovery. We observe that some data hazards resulting from instruction rollback can be resolved efficiently by providing an operand read buffer while others are resolved more efficiently with compiler transformations. A compiler-assisted multiple instruction rollback scheme is developed which combines hardware-implemented data redundancy with compiler-driven hazard removal transformations. Experimental performance evaluations indicate improved efficiency over previous hardware-based and compiler-based schemes.

Alewine, N. J.↗
NASA NTRS1993

Capillary movement of liquid in granular beds

Knowledge of capillary migration of liquids in granular beds in microgravity is essential for the development of a substrate based nutrient delivery sytem for the growth of plants in space. This problem is also interesting from the theoretical as well as the practical point of view. The purpose of this study was to model capillary water propagation through a granular bed in microgravity. In our ground experiments, water propagation is driven primarily by capillary force. Data for spherical partical sizes in the range from 0.46 to 2 mm have been obtained. It was shown that the velocity of water propagation is very sensitive to particle size. Theoretical consideration is also provided. Actual space flight experiments are planned for the future to confirm our results.

Yendler, Boris↗
NASA NTRS1999

Advanced Design and Implementation of a Control Architecture for Long Range Autonomous Planetary Rovers

An advanced design and implementation of a Control Architecture for Long Range Autonomous Planetary Rovers is presented using a hierarchical top-down task decomposition, and the common structure of each design is presented based on feedback control theory. Graphical programming is presented as a common intuitive language for the design when a large design team is composed of managers, architecture designers, engineers, programmers, and maintenance personnel. The whole design of the control architecture consists in the classic control concepts of cyclic data processing and event-driven reaction to achieve all the reasoning and behaviors needed. For this purpose, a commercial graphical tool is presented that includes the mentioned control capabilities. Messages queues are used for inter-communication among control functions, allowing Artificial Intelligence (AI) reasoning techniques based on queue manipulation. Experimental results show a highly autonomous control system running in real time on top the JPL micro-rover Rocky 7 controlling simultaneously several robotic devices. This paper validates the sinergy between Artificial Intelligence and classic control concepts in having in advanced Control Architecture for Long Range Autonomous Planetary Rovers.

Martin-Alvarez, A.↗
NASA NTRS2000

The Distribution of Carbon Monoxide in the GOCART Model

Carbon monoxide (CO) is an important trace gas because it is a significant source of tropospheric Ozone (O3) as well as a major sink for atmospheric hydroxyl radical (OH). The distribution of CO is set by a balance between the emissions, transport, and chemical processes in the atmosphere. The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model is used to simulate the atmospheric distribution of CO. The GOCART model is driven by the assimilated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS DAS) in an off-line mode. We study the distribution of CO on three time scales: (1) day to day fluctuation produced by the synoptic waves; (2) seasonal changes due to the annual cycle of CO sources and sinks; and (3) interannual variability induced by dynamics. Comparison of model results with ground based and remote sensing measurements will also be presented.

Fan, Xiaobiao↗
NASA NTRS1997

Interannual Variability in Soil Trace Gas (CO2, N2O, NO) Fluxes and Analysis of Controllers

Interannual variability in flux rates of biogenic trace gases must be quantified in order to understand the differences between short-term trends and actual long-term change in biosphere-atmosphere interactions. We simulated interannual patterns (1983-1988) of global trace gas fluxes from soils using the NASA Ames model version of CASA (Carnegie-Ames-Stanford Approach) in a transient simulation mode. This ecosystem model has been recalibrated for simulations driven by satellite vegetation index data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. The predicted interannual pattern of soil heterotropic CO2 emissions indicates that relatively large increases in global carbon flux from soils occurred about three years following the strong El Nino Southern Oscillation (ENSO) event of 1983. Results for the years 1986 and 1987 showed an annual increment of +1 Pg (1015 g) C-CO2 emitted from soils, which tended to dampen the estimated global increase in net ecosystem production with about a two year lag period relative to plant carbon fixation. Zonal discrimination of model results implies that 80-90 percent of the yearly positive increments in soil CO2 emission during 1986-87 were attributable to soil organic matter decomposition in the low-latitudes (between 30 N and 30 S). Soils of the northern middle-latitude zone (between 30 N and 60 N) accounted for the residual of these annual increments. Total annual emissions of nitrogen trace gases (N2O and NO) from soils were estimated to vary from 2-4 percent over the time period modeled, a level of variability which is consistent with predicted interannual fluctuations in global soil CO2 fluxes. Interannual variability of precipitation in tropical and subtropical zones (30 N to 20 S appeared to drive the dynamic inverse relationship between higher annual emissions of NO versus emissions of N2O. Global mean emission rates from natural (heterotrophic) soil sources over the period modeled (1983-1988) were estimated at 57.1 Pg C-CO2yr-1, 9.8Tg (1012 g) N-NO yr-1, and 9.7 Tg N-N2O yr-1. Chemical fertilizer contributions to global soil N gas fluxes were estimated at between 1.3 to 7.3 Tg N-NO yr-1, and 1.2 to 4.0 Tg N-N2O yr-1.

Potter, C.↗
NASA NTRS2004

Sensory-Motor Adaptation to Space Flight: Human Balance Control and Artificial Gravity

Gravity, which is sensed directly by the otolith organs and indirectly by proprioceptors and exteroceptors, provides the CNS a fundamental reference for estimating spatial orientation and coordinating movements in the terrestrial environment. The sustained absence of gravity during orbital space flight creates a unique environment that cannot be reproduced on Earth. Loss of this fundamental CNS reference upon insertion into orbit triggers neuro-adaptive processes that optimize performance for the microgravity environment, while its reintroduction upon return to Earth triggers neuro-adaptive processes that return performance to terrestrial norms. Five pioneering symposia on The Role of the Vestibular Organs in the Exploration of Space were convened between 1965 and 1970. These innovative meetings brought together the top physicians, physiologists, and engineers in the vestibular field to discuss and debate the challenges associated with human vestibular system adaptation to the then novel environment of space flight. These highly successful symposia addressed the perplexing problem of how to understand and ameliorate the adverse physiological effects on humans resulting from the reduction of gravitational stimulation of the vestibular receptors in space. The series resumed in 2002 with the Sixth Symposium, which focused on the microgravity environment as an essential tool for the study of fundamental vestibular functions. The three day meeting included presentations on historical perspectives, vestibular neurobiology, neurophysiology, neuroanatomy, neurotransmitter systems, theoretical considerations, spatial orientation, psychophysics, motor integration, adaptation, autonomic function, space motion sickness, clinical issues, countermeasures, and rehabilitation. Scientists and clinicians entered into lively exchanges on how to design and perform mutually productive research and countermeasure development projects in the future. The problems posed by long duration missions dominated these discussions and were driven by the paucity of data available. These issues along with more specific recommendations arising from the above discussions will be addressed an upcoming issue of the Journal of Vestibular Research.

Paloski, William H.↗
NASA NTRS2011

The Influence of Summertime Convection Over Southeast Asia on Water Vapor in the Tropical Stratosphere

The relative contributions of Southeast Asian convective source regions during boreal summer to water vapor in the tropical stratosphere are examined using Lagrangian trajectories. Convective sources are identified using global observations of infrared brightness temperature at high space and time resolution, and water vapor transport is simulated using advection-condensation. Trajectory simulations are driven by three different reanalysis data sets, GMAO MERRA, ERA-Interim, and NCEP/NCAR, to establish points of consistency and evaluate the sensitivity of the results to differences in the underlying meteorological fields. All ensembles indicate that Southeast Asia is a prominent boreal summer source of tropospheric air to the tropical stratosphere. Three convective source domains are identified within Southeast Asia: the Bay of Bengal and South Asian subcontinent (MON), the South China and Philippine Seas (SCS), and the Tibetan Plateau and South Slope of the Himalayas (TIB). Water vapor transport into the stratosphere from these three domains exhibits systematic differences that are related to differences in the bulk characteristics of transport. We find air emanating from SCS to be driest, from MON slightly moister, and from TIB moistest. Analysis of pathways shows that air detrained from convection over TIB is most likely to bypass the region of minimum absolute saturation mixing ratio over the equatorial western Pacific; however, the impact of this bypass mechanism on mean water vapor in the tropical stratosphere at 68 hPa is small 0.1 ppmv). This result contrasts with previously published hypotheses, and it highlights the challenge of properly quantifying fluxes of atmospheric humidity.

Wright, J. S.↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
NASA NTRSDate not supplied

Communication Demand in the National Airspace - A Federated Learning Approach

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc.). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗