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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins

An innovative flood-prediction framework is developed using Tropical Rainfall Measuring Mission precipitation forcing and a proxy for river discharge from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) onboard the National Aeronautics and Space Administration's Aqua satellite. The AMSR-E-detected water surface signal was correlated with in situ measurements of streamflow in the Okavango Basin in Southern Africa as indicated by a Pearson correlation coefficient of 0.90. A distributed hydrologic model, with structural data sets derived from remote-sensing data, was calibrated to yield simulations matching the flood frequencies from the AMSR-E-detected water surface signal. Model performance during a validation period yielded a Nash-Sutcliffe efficiency of 0.84. We concluded that remote-sensing data from microwave sensors could be used to supplement stream gauges in large sparsely gauged or ungauged basins to calibrate hydrologic models. Given the global availability of all required data sets, this approach can be potentially expanded to improve flood monitoring and prediction in sparsely gauged basins throughout the world

Distributed hydrologic modeling↗
NASA NTRS2003

Jet Stream Analysis and Forecast Errors Using GADS Aircraft Observations in the DAO, ECMWF, and NCEP Models

We have utilized an extensive set of independent British Airways flight data recording wind vector and temperature observations (the Global Aircraft Data Set [GADS] archive) in three ways: (a) as an independent check of operational analyses; (b) as an analysis observing system experiment (OSE) as if the GADS observations were available in real time; and (c) as the corresponding forecast simulation experiment applicable to future operational forecasts. Using a 31 day sample (0000 UTC 20 December 2000 through 0000 UTC 20 January 2000) from Winter 2000, we conclude that over the data-dense continental U. S. analyzed jet streaks are too weak by -2% to -5%. Over nearby data-sparse regions of Canada, analyzed jet streaks are too weak by -5% to -9%. The second range provides a limit on the accuracy of current jet streak analyses over the portions of the -85% of the earth's surface that are poorly covered by non-satellite observations. The -5% to -9% range is relevant for the pre-third generation satellite (AIRS, IASI, GIFTS) era.

Cardinali, Carla↗
NASA NTRS2016

Constraining the Size of Near Earth Asteroids

Quick and accurate determination of the size of an asteroid is of great interest to the Asteroid Threat Assessment Project and is difficult to accomplish. With a combination of visible and thermal measurements we employ a method that leverages the size estimations of each model as physical constraints on the true diameter. This method breaks degeneracies present in the thermal and visible model from sparse data. In the visible bands we use both the established H-G relationship and its successor the H-G1G2 model, which has improved capabilities in the opposition effect and large phase angles. For the thermal models we use the Near Earth Asteroid Thermal Model (NEATM), the Night Emission Simulated Thermal Model (NESTM), and the Advanced Thermophysical Model (ATPM).

Nelson, Tyler↗
NASA NTRS1992

Requirements for facilities and measurement techniques to support CFD development for hypersonic aircraft

The design of a hypersonic aircraft poses unique challenges to the engineering community. Problems with duplicating flight conditions in ground based facilities have made performance predictions risky. Computational fluid dynamics (CFD) has been proposed as an additional means of providing design data. At the present time, CFD codes are being validated based on sparse experimental data and then used to predict performance at flight conditions with generally unknown levels of uncertainty. This paper will discuss the facility and measurement techniques that are required to support CFD development for the design of hypersonic aircraft. Illustrations are given of recent success in combining experimental and direct numerical simulation in CFD model development and validation for hypersonic perfect gas flows.

Sellers, William L., III↗
NASA NTRS2017

Numerical and Analytical Assessment of a Coupled Rotating Detonation Engine and Turbine Experiment

An analysis is presented of an experimental rig comprising a rotating detonation engine (RDE) with bypass ejector flow coupled to a downstream turbine. The analysis used a validated computational fluid dynamics RDE simulation combined with straightforward algebraic mixing equations for the bypass flow. The objectives of the analysis were to supplement and interpret the necessarily sparse measurements from the rig, and to assess the performance of the RDE itself, which was not instrumented in this installation. The analysis is seen to agree reasonably well with available data. It shows that the RDE is operating in an unusual fashion, with subsonic flow throughout the exhaust plane. The detonation event itself is producing a total pressure rise relative to the pre-detonative pressure; however, the length of the device and the substantial flow restriction at the inlet yield an overall pressure loss. This is not surprising since the objective of the rig test was primarily aimed at investigating RDE/turbine interactions, and not on performance optimization. Furthermore, the RDE was designed for fundamental detonation studies and not performance. Nevertheless, the analysis indicates that with some small alterations to the design, an RDE with an overall pressure rise is possible.

detonation↗
NASA NTRS2017

Numerical and Analytical Assessment of a Coupled Rotating Detonation Engine and Turbine Experiment

An analysis is presented of an experimental rig comprising a rotating detonation engine (RDE) with bypass ejector flow coupled to a downstream turbine. The analysis used a validated computational fluid dynamics RDE simulation combined with straightforward algebraic mixing equations for the bypass flow. The objectives of the analysis were to supplement and interpret the necessarily sparse measurements from the rig, and to assess the performance of the RDE itself, which was not instrumented in this installation. The analysis is seen to agree reasonably well with available data. It shows that the RDE is operating in an unusual fashion, with subsonic flow throughout the exhaust plane. The detonation event itself is producing a total pressure rise relative to the pre-detonative pressure; however, the length of the device and the substantial flow restriction at the inlet yield an overall pressure loss. This is not surprising since the objective of the rig test was primarily aimed at investigating RDE turbine interactions, and not on performance optimization. Furthermore, the RDE was designed for fundamental detonation studies and not performance. Nevertheless, the analysis indicates that with some small alterations to the design, an RDE with an overall pressure rise is possible.

propulsion↗
NASA NTRS2017

Numerical and Analytical Assessment of a Coupled Rotating Detonation Engine and Turbine Experiment

An analysis is presented of an experimental rig comprising a rotating detonation engine (RDE) with bypass flow coupled to a downstream turbine. The analysis used a validated computational fluid dynamics RDE simulation combined with straightforward algebraic mixing equations for the bypass flow. The objectives of the analysis were to supplement and interpret the necessarily sparse measurements from the rig, and to assess the performance of the RDE itself (which was not instrumented in this installation). The analysis is seen to agree reasonably well with available data. It shows that the RDE is operating in an unusual fashion, with subsonic flow throughout the exhaust plane. The detonation event itself is producing a total pressure rise relative to the pre-detonative pressure; however, the length of the device and the substantial flow restriction at the inlet yield an overall pressure loss. This is not surprising since the objective of the rig test was primarily aimed at investigating RDEturbine interactions, and not on performance optimization. Furthermore, the RDE was designed for fundamental detonation studies and not performance. Nevertheless, the analysis indicates that with some small alterations to the design, an RDE with an overall pressure rise is possible.

detonation↗
NASA NTRS1976

Urban land use monitoring from computer-implemented processing of airborne multispectral data

Machine processing techniques were applied to multispectral data obtained from airborne scanners at an elevation of 600 meters over central Indianapolis in August, 1972. Computer analysis of these spectral data indicate that roads (two types), roof tops (three types), dense grass (two types), sparse grass (two types), trees, bare soil, and water (two types) can be accurately identified. Using computers, it is possible to determine land uses from analysis of type, size, shape, and spatial associations of earth surface images identified from multispectral data. Land use data developed through machine processing techniques can be programmed to monitor land use changes, simulate land use conditions, and provide impact statistics that are required to analyze stresses placed on spatial systems.

Todd, W. J.↗
NASA NTRS1994

Performance issues for iterative solvers in device simulation

Due to memory limitations, iterative methods have become the method of choice for large scale semiconductor device simulation. However, it is well known that these methods still suffer from reliability problems. The linear systems which appear in numerical simulation of semiconductor devices are notoriously ill-conditioned. In order to produce robust algorithms for practical problems, careful attention must be given to many implementation issues. This paper concentrates on strategies for developing robust preconditioners. In addition, effective data structures and convergence check issues are also discussed. These algorithms are compared with a standard direct sparse matrix solver on a variety of problems.

Fan, Qing↗
NASA NTRS2006

The Effect of the Saharan Air Layer on the Formation of Hurricane Isabel (2003) Simulated with AIRS Data

The crucial physics of how the atmosphere really accomplishes the tropical cyclogenesis process is still poorly understood. The presence of the Saharan Air Layer (SAL), an elevated mixed layer of warm and dry air that extends from Africa to the tropical Atlantic and contains a substantial amount of mineral dust, adds more complexity to the tropical cyclogenesis process in the Atlantic basin. The impact of the SAL on tropical cyclogenesis is still uncertain. Karyampudi and Carlson (1988) conclude that a strong SAL can potentially aid tropical cyclone development while Dunion and Velden (2004) argue that the SAL generally inhibits tropical cyclogenesis and intensification. Advancing our understanding of the physical mechanisms of tropical cyclogenesis and the associated roles of the SAL strongly depends on the improvement in the observations over the data-sparse ocean areas. After the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the microwave Humidity Sounder of Brazil (HSB) were launched with the NASA Aqua satellite in 2002, new data products retrieved from the AIRS suite became available for studying the effect of the warm, dry air mass associated with the SAL (referred to as the thermodynamic effect). The vertical profiles of the AIRS retrieved temperature and humidity provide an unprecedented opportunity to examine the thermodynamic effect of the SAL. The observational data can be analyzed and assimilated into numerical models, in which the model thermodynamic state is allowed to relax to the observed state from AIRS data. The objective of this study is to numerically demonstrate that the thermodynamic effect of the SAL on the formation of Hurricane Isabel (2003) can be largely simulated through nudging of the AIRS data.

Wu, iguang↗
NASA NTRS2008

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Hong, Yang↗
NASA NTRS2007

The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS, intelligent use of the quality indicators, and forecast verification.

Chou, Shih-Hung↗
NASA NTRS2024

DAVINCI: Venus Atmospheric Model Comparisons

The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging(DAVINCI) mission aims to answer long-standing questions regarding Venus’ origin using Zephyr, an atmospheric descent probe. Zephyr will be the first probe to take high-resolution aerial photographs of a mountainous tesserae surface as it descends over the Alpha Regio highlands region, which has the oldest surfaces of Venus. The Zephyr’s descent trajectory that determines the touchdown in the Alpha Regio, which is crucial for the DAVINCI mission, depends on Venus’ atmospheric properties and winds. Unfortunately, the atmospheric data for Venus from previous missions is sparse. Therefore, it is essential to consider various atmospheric models and scenarios from past flight data to predict Zephyr’s flight performance, specifically landing ellipse. To this end, this work compares three atmospheric models: the Venus Global Reference Atmospheric Model (Venus-GRAM), the Venus Climate Database(VCD), and an empirical wind model developed by Ralph Lorenz for the DAVINCI trajectory simulation and modeling. This paper compares the mean and variations of different atmospheric properties and winds from these atmospheric models. In addition, this work combines the atmospheric properties and the wind variability from the Venus-GRAM with the winds from the Lorenz-based model to have more stressing Venus wind dispersions that allow for more conservative trajectory analysis. Furthermore, this work relies on the DAVINCI landing ellipse size as a metric to measure how robust the trajectory analysis will be to the change in the atmospheric properties and winds of the Venus atmosphere.

Pardha Sai Chadalavada↗
NASA NTRS2012

A Systematic Approach for Real-Time Operator Functional State Assessment

A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in time compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement.

Zhang, Guangfan↗
NASA NTRSDate not supplied

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗
NASA NTRS1986

Investigation of advanced fault insertion and simulator methods

The cooperative agreement partly supported research leading to the open-literature publication cited. Additional efforts under the agreement included research into fault modeling of semiconductor devices. Results of this research are presented in this report which is summarized in the following paragraphs. As a result of the cited research, it appears that semiconductor failure mechanism data is abundant but of little use in developing pin-level device models. Failure mode data on the other hand does exist but is too sparse to be of any statistical use in developing fault models. What is significant in the failure mode data is that, unlike classical logic, MSI and LSI devices do exhibit more than 'stuck-at' and open/short failure modes. Specifically they are dominated by parametric failures and functional anomalies that can include intermittent faults and multiple-pin failures. The report discusses methods of developing composite pin-level models based on extrapolation of semiconductor device failure mechanisms, failure modes, results of temperature stress testing and functional modeling. Limitations of this model particularly with regard to determination of fault detection coverage and latency time measurement are discussed. Indicated research directions are presented.

Dunn, W. R.↗
NASA NTRS2023

Assessment of the Impact of Discontinuity in Satellite Instruments and Retrievals on Global PM2.5

Exposure to fine particulate matter (PM2.5) is the leading environmental risk factor for mortality globally. Satellite-derived estimates of surface PM2.5 developed from a combination of satellites, simulations, and ground monitor data are relied upon for health impact studies. The ability to develop satellite-derived PM2.5 estimates requires the continued availability of aerosol optical depth (AOD) sources. This work examines the impact of the addition or loss of satellite AOD data sources on global PM2.5 estimation and the impact of continuing the longterm record with AOD from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar orbiting Partnership (S-NPP) satellite after the loss of the MODIS (MODerate resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer) instruments on board the Terra and Aqua satellites. We find that the addition of VIIRS S-NPP AOD products to geophysical PM2.5 estimates from satellites and simulations causes regional differences that correspond to differences in the VIIRS and MODIS Deep Blue AOD algorithms and sampling. Changes in long-term trends and timeseries due to the addition or loss of AOD data sources are generally within their uncertainties. Statistical fusion with ground monitor data partially corrects for changes due to sampling differences when introducing the VIIRS AOD products, but uncertainty remains over desert regions where ground monitor coverage is sparse. This work provides promise for the sustained development of global satellite-derived PM2.5 estimates, despite discontinuities in instruments and retrieval methods.

Remote sensing↗
NASA NTRS2011

A High-Resolution Capability for Large-Eddy Simulation of Jet Flows

A large-eddy simulation (LES) code that utilizes high-resolution numerical schemes is described and applied to a compressible jet flow. The code is written in a general manner such that the accuracy/resolution of the simulation can be selected by the user. Time discretization is performed using a family of low-dispersion Runge-Kutta schemes, selectable from first- to fourth-order. Spatial discretization is performed using central differencing schemes. Both standard schemes, second- to twelfth-order (3 to 13 point stencils) and Dispersion Relation Preserving schemes from 7 to 13 point stencils are available. The code is written in Fortran 90 and uses hybrid MPI/OpenMP parallelization. The code is applied to the simulation of a Mach 0.9 jet flow. Four-stage third-order Runge-Kutta time stepping and the 13 point DRP spatial discretization scheme of Bogey and Bailly are used. The high resolution numerics used allows for the use of relatively sparse grids. Three levels of grid resolution are examined, 3.5, 6.5, and 9.2 million points. Mean flow, first-order turbulent statistics and turbulent spectra are reported. Good agreement with experimental data for mean flow and first-order turbulent statistics is shown.

DeBonis, James R.↗