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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Space Shuttle capabilities, constraints, and cost

The capabilities, constraints, and costs of the Space Transportation System (STS), which combines reusable and expendable components, are reviewed, and an overview of the current planning activities for operating the STS in an efficient and cost-effective manner is presented. Traffic forecasts, performance constraints and enhancements, and potential new applications are discussed. Attention is given to operating costs, pricing policies, and the steps involved in 'getting on board', which includes all the interfaces between NASA and the users necessary to come to launch service agreements.

Lee, C. M.↗
NASA NTRS1987

Allocating Spare Parts In Complicated Systems

Assortments analyzed for cost effectiveness and effects on system functionality. Eisenberger-Maiocco algorithm (EMA) is efficient Markov algorithm to aid in provision of spare parts. Two calculations performed: forecasting availability of system with given pool of spare parts and determining most cost-effective assortment of spares. EMA written in interpreter PC-BASIC.

Eisenberger, I.↗
NASA NTRS1994

Galileo mission planning for Low Gain Antenna based operations

The Galileo mission operations concept is undergoing substantial redesign, necessitated by the deployment failure of the High Gain Antenna, while the spacecraft is on its way to Jupiter. The new design applies state-of-the-art technology and processes to increase the telemetry rate available through the Low Gain Antenna and to increase the information density of the telemetry. This paper describes the mission planning process being developed as part of this redesign. Principal topics include a brief description of the new mission concept and anticipated science return (these have been covered more extensively in earlier papers), identification of key drivers on the mission planning process, a description of the process and its implementation schedule, a discussion of the application of automated mission planning tool to the process, and a status report on mission planning work to date. Galileo enhancements include extensive reprogramming of on-board computers and substantial hard ware and software upgrades for the Deep Space Network (DSN). The principal mode of operation will be onboard recording of science data followed by extended playback periods. A variety of techniques will be used to compress and edit the data both before recording and during playback. A highly-compressed real-time science data stream will also be important. The telemetry rate will be increased using advanced coding techniques and advanced receivers. Galileo mission planning for orbital operations now involves partitioning of several scarce resources. Particularly difficult are division of the telemetry among the many users (eleven instruments, radio science, engineering monitoring, and navigation) and allocation of space on the tape recorder at each of the ten satellite encounters. The planning process is complicated by uncertainty in forecast performance of the DSN modifications and the non-deterministic nature of the new data compression schemes. Key mission planning steps include quantifying resource or capabilities to be allocated, prioritizing science observations and estimating resource needs for each, working inter-and intra-orbit trades of these resources among the Project elements, and planning real-time science activity. The first major mission planning activity, a high level, orbit-by-orbit allocation of resources among science objectives, has already been completed; and results are illustrated in the paper. To make efficient use of limited resources, Galileo mission planning will rely on automated mission planning tools capable of dealing with interactions among time-varying downlink capability, real-time science and engineering data transmission, and playback of recorded data. A new generic mission planning tool is being adapted for this purpose.

Gershman, R.↗
NASA NTRS2012

An OSSE on Mesoscale Model Assimilation of Simulated HIRAD-Observed Hurricane Surface Winds

The hazards of landfalling hurricanes are well known, but progress on improving the intensity forecasts of these deadly storms at landfall has been slow. Many cite a lack of high-resolution data sets taken inside the core of a hurricane, and the lack of reliable measurements in extreme conditions near the surface of hurricanes, as possible reasons why even the most state-of-the-art forecasting models cannot seem to forecast intensity changes better. The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for observing hurricanes, and is operated and researched by NASA Marshall Space Flight Center in partnership with the NOAA Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, the University of Central Florida, the University of Michigan, and the University of Alabama in Huntsville. This instrument?s purpose is to study the wind field of a hurricane, specifically observing surface wind speeds and rain rates, in what has traditionally been the most difficult areas for other instruments to study; the high wind and heavy rain regions. Dr. T. N. Krishnamurti has studied various data assimilation techniques for hurricane and monsoon rain rates, and this study builds off of results obtained from utilizing his style of physical initializations of rainfall observations, but obtaining reliable observations in heavy rain regions has always presented trouble to our research of high-resolution rainfall forecasting. Reliable data from these regions at such a high resolution and wide swath as HIRAD provides is potentially very valuable to mesoscale forecasting of hurricane intensity. This study shows how the data assimilation technique of Ensemble Kalman Filtering (EnKF) in the Weather Research and Forecasting (WRF) model can be used to incorporate wind, and later rain rate, data into a mesoscale model forecast of hurricane intensity. The study makes use of an Observing System Simulation Experiment (OSSE) with a simulated HIRAD dataset sampled during a hurricane and uses EnKF to forecast the track and intensity prediction of the hurricane. Comparisons to truth and error metrics are used to assess the model?s forecast performance.

Albers, Cerese↗
NASA NTRS2017

Oculomotor Behavior Metrics Change According to Circadian Phase and Time Awake

There is a need for non-invasive, objective measures to forecast performance impairment arising from sleep loss and circadian misalignment, particularly in safety-sensitive occupations. Eye-tracking devices have been used in some operational scenarios, but such devices typically focus on eyelid closures and slow rolling eye movements and are susceptible to the intrusion of head movement artifacts. We hypothesized that an expanded suite of oculomotor behavior metrics, collected during a visual tracking task, would change according to circadian phase and time awake, and could be used as a marker of performance impairment.

sleep deprivation↗
NASA NTRS2019

Impacts of the Mount Pinatubo eruption on ENSO in the GEOS seasonal-to-subseasonal forecasting system

The eruption of Mount Pinatubo in June 1991 introduced a perturbation of the Earth's global energy budget by increasing the stratospheric aerosol loading by an order of magnitude, with effects on the global climate. In this presentation we analyze the effects of the Mt. Pinatubo eruption on the seasonal forecast performed with Goddard Earth Observing System Seasonal-to Subseasonal (GEOS-S2S) system, an Earth System Model that includes an interactive ocean and a bulk aerosol model coupled to radiation. We performed 10-member ensembles for the year after the eruption (June 1991-May 1992) at ~0.5 horizontal resolution, with and without the inclusion of the Mt. Pinatubo eruption. In GEOS-S2S, the eruption leads to ta strengthening of El Nino peaking in January 1992. The strengthening is mainly due to the weakening of the trade winds, which is caused by a attening of the temperature gradient across the Pacic due to a differential response to the volcanic forcing between the central and eastern Pacic (ocean-dynamical thermostat). This response largely depends on the assumed size for the volcanic aerosols. Indeed, we performed simulations assuming a volcanic aerosol effective radius of 0.35 m (similar to tropospheric aerosol, and the default in GEOS) and 0.6 m (closer to observations of volcanic aerosol from Pinatubo-sized eruptions). We nd that in the latter case the tropical radiative forcing is lower, since smaller aerosols scatter shortwave radiation more eciently than larger ones. Accordingly, the impact on ENSO is not statistically signicant when a larger and more realistic particle radius is assumed.

Aquila, Valentina↗
NASA NTRSDate not supplied

The OSSE Framework at the NASA Global Modeling and Assimilation Office (GMAO)

The Global Modeling and Assimilation Office (GMAO) has been developing an Observing System Simulation Experiment (OSSE) framework. The OSSE system is currently based on the Nature Run (NR) developed by GMAO called G5NR. The G5NR is currently being tested for use in the GMAO OSSE framework. Synthetic observations have been generated based on the G5NR fields, including conventional observations, GPS, and satellite radiances. These synthetic observations are ingested using the Gridpoint Statistical Interpolation data assimilation system, with forecasts performed by the GEOS-5 model at 55 km/72L.

OSSE Framework↗
NASA NTRS2022

The Simulation and Subseasonal Forecasting of Hydrological Variables: Insights from a Simple Water Balance Model

Past work has shown that a land surface model’s (LSM’s) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM’s hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the U.S., and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in-situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in Nature and can serve as potentially useful targets for further LSM development.

Water Balance Model↗
NASA NTRSDate not supplied

Status and Progress of All-Sky Hyperspectral IR Radiance Assimilation in GEOS

The majority of hyperspectral infrared radiance observations that peak in the lower and mid-troposphere have been excluded from the assimilation in the operational GEOS by the cloud detection scheme. The significance and challenges of assimilating these cloud-affected observations have attracted the attention of the research community, encouraged by the progress in utilizing all-sky microwave radiances affected by clouds and precipitation in many data assimilation systems, including GEOS. While the Global Modeling and Assimilation Office (GMAO) has made significant progress on the assimilation of cloud-cleared infrared radiances, this parallel study marks the first effort to directly assimilate cloud-affected hyperspectral infrared radiances in the GEOS. This initial study is focused on CrIS-FSR wa:wqter-vapor channels. The capability of the GEOS model and CRTM in simulating infrared radiances affected by clouds has been evaluated, and the all-sky brightness temperature Jacobians with respect to temperature, specific humidity, and hydrometeors are examined closely in varying cloud conditions. With hydrometeor control variables in the GEOS, several important aspects of all-sky IR radiance assimilation are investigated. The symmetric cloud effects are assessed for their robustness when used as the cloud proxy in observation error modeling that incorporates the inter-channel correlations with error situation dependency on the amount of cloud. The effective radius, bias correction and quality control processes will also be adapted to accommodate modifications necessary for all-sky infrared assimilation before comprehensive four-dimensional ensemble-variational(4dEnVar) experiments are conducted to assess their impacts on the analysis and forecast performance of GEOS.

Wei Gu↗
NASA NTRS2014

The Main Pillar: Assessment of Space Weather Observational Asset Performance Supporting Nowcasting, Forecasting and Research to Operations

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations.

Extreme events↗
NASA NTRS1971

Forecasting of the performance of MOS device for space applications

Analysis of radiation damage of MOSFET data from Explorer 34 (IMP-F), and radiation damage characteristics of MOSFET with boron diffused between a silicon semiconductor and silicon oxide are considered. The first subject is an interpretation of the discrepancy between the space data and the laboratory data. The second subject is an attempt to analyze the radiation damage characteristic of MOSFET when there is modification of electrical properties in the gate oxide region.

Fang, P. H.↗
NASA NTRS2013

Range-Specific High-resolution Mesoscale Model Setup

This report summarizes the findings from an AMU task to determine the best model configuration for operational use at the ER and WFF to best predict winds, precipitation, and temperature. The AMU ran test cases in the warm and cool seasons at the ER and for the spring and fall seasons at WFF. For both the ER and WFF, the ARW core outperformed the NMM core. Results for the ER indicate that the Lin microphysical scheme and the YSU PBL scheme is the optimal model configuration for the ER. It consistently produced the best surface and upper air forecasts, while performing fairly well for the precipitation forecasts. Both the Ferrier and Lin microphysical schemes in combination with the YSU PBL scheme performed well for WFF in the spring and fall seasons. The AMU has been tasked with a follow-on modeling effort to recommended local DA and numerical forecast model design optimized for both the ER and WFF to support space launch activities. The AMU will determine the best software and type of assimilation to use, as well as determine the best grid resolution for the initialization based on spatial and temporal availability of data and the wall clock run-time of the initialization. The AMU will transition from the WRF EMS to NU-WRF, a NASA-specific version of the WRF that takes advantage of unique NASA software and datasets. 37

Watson, Leela R.↗
NASA NTRS1992

Dynamically stratified Monte Carlo forecasting

A new method for performing Monte Carlo forecasts is introduced. The method, called dynamic stratification, selects initial perturbations based on a stratification of the error distribution. A simple implementation is presented in which the error distribution used for the stratification is estimated from a linear model derived from a large ensemble of 12-h forecasts with the full dynamic model. The stratification thus obtained is used to choose a small subsample of initial states with which to perform the dynamical Monte Carlo forecasts. Several test cases are studied using a simple two-level general circulation model with uncertain initial conditions. It is found that the method provides substantial reductions in the sampling error of the forecast mean and variance when compared to the more traditional approach of choosing the initial perturbations at random. The degree of improvement, however, is sensitive to the nature of the initial error distribution and to the base state. In practice the method may be viable only if the computational burden involved in obtaining an adequate estimate of the error distribution is shared with the data-assimilation procedure.

Schubert, Siegfried↗
NASA NTRS2021

USA Crop Yield Estimation with MODIS NDVI: Are Remotely Sensed Models Better Than Simple Trend Analyses?

Crop yield forecasting is performed monthly during the growing season by the United States Department of Agriculture’s National Agricultural Statistics Service. The underpinnings are long-established probability surveys reliant on farmers’ feedback in parallel with biophysical measurements. Over the last decade though, satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been used to corroborate the survey information. This is facilitated through the Global Inventory Modeling and Mapping Studies/Global Agricultural Monitoring system, which provides open access to pertinent real-time normalized difference vegetation index (NDVI) data. Hence, two relatively straightforward MODIS-based modeling methods are employed operationally. The first model constitutes mid-season timing based on the maximum peak NDVI value, while the second is reflective of late-season timing by integrating accumulated NDVI over a threshold value. Corn model results nationally show the peak NDVI method provides a R^(2) of 0.88 and a coefficient of variation (CV) of 3.5%. The accumulated method, using an optimally derived 0.58 NDVI threshold, improves the performance to 0.93 and 2.7%, respectively. Both these models outperform simple trend analysis, which is 0.48 and 7.4%, correspondingly. For soybeans the R^(2) results of the peak NDVI model are 0.62, and 0.73 for the accumulated using a 0.56 threshold. CVs are 6.8% and 5.7%, respectively. Spring wheat’s R2performance with the accumulated NDVI model is 0.60 but just 0.40 with peak NDVI. The soybean and spring wheat models perform similarly to trend analysis. Winter wheat and upland cotton show poor model performance, regardless of method. Ultimately, corn yield forecasting derived from MODIS imagery is robust, and there are circumstances when forecasts for soybeans and spring wheat have merit too.

crop yield↗
NASA NTRS1978

The present situation and forecasts of semiconductor elements performance within the microwave range, 1970-1985

The present situation and possible developments over the period 1970-1985 for active semiconductor elements in the microwave range are outlined. After a short historical survey of FT techniques, the following are discussed: Generation, power amplification, amplification of small signals, frequency conversion, detection, electronic signal control and integrated microwave circuits.

Peterson, B.↗
NASA NTRS1975

Civil mini-RPA's for the 1980's: Avionics design considerations

A number of remote sensing or surveillance tasks (e.g., fire fighting, crop monitoring) in the civilian sector of our society may be performed in a cost effective manner by use of small remotely piloted aircraft (RPA). This study was conducted to determine equipment (and the associated technology) that is available, and that could be applied to the mini-RPA and to examine the potential applications of the mini-RPA with special emphasis on the wild fire surveillance mission. The operational considerations of using the mini-RPA as affected by government regulatory agencies were investigated. These led to equipment requirements (e.g., infra-red sensors) over and above those for the performance of the mission. A computer technology survey and forecast was performed. Key subsystems were identified, and a distributed microcomputer configuration, that was functionally modular, was recommended. Areas for further NASA research and development activity were also identified.

Karmarkar, J. S.↗