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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

NASA A-Train and Terra Observations of the 2010 Russian Wildfires

Wildfires raged throughout western Russia and parts of Eastern Europe during a persistent heat wave in the summer of 2010. Anomalously high surface temperatures (35 - 41 C) and low relative humidity (9 - 25 %) from mid- June to mid-August 2010 shown by analysis of radiosonde data from multiple sites in western Russia were ideal conditions for the wildfires to thrive. Measurements of outgoing longwave radiation (OLR) from the Atmospheric Infrared Sounder (AIRS) over western Russian indicate persistent subsidence during the heat wave. Daily three-day back-trajectories initiated over Moscow reveal a persistent anticyclonic circulation for 18 days in August, coincident with the most intense period of fire activity observed by Moderate Resolution Imaging Spectroradiometer (MODIS). This unfortunate meteorological coincidence allowed transport of polluted air from the region of intense fires to Moscow and the surrounding area. We demonstrate that the 2010 Russian wildfires are unique in the record of observations obtained by remote-sensing instruments on-board NASA satellites: Aura and Aqua (part of the A-Train Constellation) and Terra. Analysis of the distribution of MODIS fire products and aerosol optical thickness (AOT), UV aerosol index (AI) and single-scattering albedo (SSA) from Aura's Ozone Monitoring Instrument (OMI), and total column carbon monoxide (CO) from Aqua s Atmospheric Infrared Sounder (AIRS) show that the region in the center of western Russia surrounding Moscow (52-58 deg N, 33 -43 deg E) is most severely impacted by wildfire emissions. Over this area, AIRS CO, OMI AI, and MODIS AOT are significantly enhanced relative to the historical satellite record during the first 18 days in August when the anti-cyclonic circulation persisted. By mid-August, the anti-cyclonic circulation was replaced with westerly transport over Moscow and vicinity. The heat wave

Witte, J. C.↗
NASA NTRS2012

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

What is an RGB Composite Image? (1) Current and future satellite instruments provide remote sensing at a variety of wavelengths. (2) RGB composite imagery assign individual wavelengths or channel differences to the intensities of the red, green, and blue components of a pixel color. (3) Each red, green, and blue color intensity is related to physical properties within the final composite image. (4) Final color assignments are therefore related to the characteristics of image pixels. (5) Products may simplify the interpretation of data from multiple bands by displaying information in a single image. Current Products and Usage: Collaborations between SPoRT, CIRA, and NRL have facilitated the use and evaluation of RGB products at a variety of NWS forecast offices and National Centers. These products are listed in table.

Molthan, Andrew↗
NASA NTRS2012

Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

Miller, Steven↗
NASA NTRS2012

Modeling a Civil Event Case Study for Consequence Management Using the IMPRINT Forces Module

A critical challenge in the Consequence Management (CM) domain is the appropriate allocation of necessary and skilled military and civilian personnel and materiel resources in unexpected emergencies. To aid this process we used the Forces module in the Improved Performance Research Integration Tool (IMPRINT). This module enables analysts to enter personnel and equipment capabilities, prioritized schedules and numbers available, along with unexpected emergency requirements in order to assess force response requirements. Using a suspected terrorist threat on a college campus, we developed a test case model which exercised the capabilities of the module, including the scope and scale of operations. The model incorporates data from multiple sources, including daily schedules and frequency of events such as fire calls. Our preliminary results indicate that the model can predict potential decreases in civilian emergency response coverage due to an involved unplanned incident requiring significant portions of police, fire and civil responses teams.

Gacy, Marc↗
NASA NTRS2013

CEOS Visualization Environment (COVE) Tool for Intercalibration of Satellite Instruments

Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of space agencies and of international and domestic organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration efforts. This paper provides a brief overview of the COVE tool, its validation, accuracies and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.

Kessler, Paul D.↗
NASA NTRS2013

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗
NASA NTRS2014

America's Next Great Ship: Space Launch System Core Stage Transitioning from Design to Manufacturing

The Space Launch System (SLS) Program is essential to achieving the Nation's and NASA's goal of human exploration and scientific investigation of the solar system. As a multi-element program with emphasis on safety, affordability, and sustainability, SLS is becoming America's next great ship of exploration. The SLS Core Stage includes avionics, main propulsion system, pressure vessels, thrust vector control, and structures. Boeing manufactures and assembles the SLS core stage at the Michoud Assembly Facility (MAF) in New Orleans, LA, a historical production center for Saturn V and Space Shuttle programs. As the transition from design to manufacturing progresses, the importance of a well-executed manufacturing, assembly, and operation (MA&O) plan is crucial to meeting performance objectives. Boeing employs classic techniques such as critical path analysis and facility requirements definition as well as innovative approaches such as Constraint Based Scheduling (CBS) and Cirtical Chain Project Management (CCPM) theory to provide a comprehensive suite of project management tools to manage the health of the baseline plan on both a macro (overall project) and micro level (factory areas). These tools coordinate data from multiple business systems and provide a robust network to support Material & Capacity Requirements Planning (MRP/CRP) and priorities. Coupled with these tools and a highly skilled workforce, Boeing is orchestrating the parallel buildup of five major sub assemblies throughout the factory. Boeing and NASA are transforming MAF to host state of the art processes, equipment and tooling, the most prominent of which is the Vertical Assembly Center (VAC), the largest weld tool in the world. In concert, a global supply chain is delivering a range of structural elements and component parts necessary to enable an on-time delivery of the integrated Core Stage. SLS is on plan to launch humanity into the next phase of space exploration.

Birkenstock, Benjamin↗
NASA NTRS2013

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

PEEMD↗
NASA NTRS2010

Daytime Water Detection Based on Color Variation

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies (such as ponds). At far range, reflections of the sky provide a strong cue for water. But at close range, the color coming out of a water body dominates sky reflections and the water cue from sky reflections is of marginal use. We model this behavior by using water body intensity data from multiple frames of RGB imagery to estimate the total reflection coefficient contribution from surface reflections and the combination of all other factors. Then we describe an algorithm that uses one of the color cameras in a forward- looking, UGV-mounted stereo-vision perception system to detect water bodies in wide open areas. This detector exploits the knowledge that the change in saturation-to-brightness ratio across a water body from the leading to trailing edge is uniform and distinct from other terrain types. In test sequences approaching a pond under clear, overcast, and cloudy sky conditions, the true positive and false negative water detection rates were (95.76%, 96.71%, 98.77%) and (0.45%, 0.60%, 0.62%), respectively. This software has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA.

reflection coefficient↗
NASA NTRS2010

Altair Navigation During Trans-Lunar Cruise, Lunar Orbit, Descent and Landing

The Altair lunar lander navigation system is driven by a set of requirements that not only specify a need to land within 100 m of a designated spot on the Moon, but also be capable of a safe return to an orbiting Orion capsule in the event of loss of Earth ground support. These requirements lead to the need for a robust and capable on-board navigation system that works in conjunction with an Earth ground navigation system that uses primarily ground-based radiometric tracking. The resulting system relies heavily on combining a multiplicity of data types including navigation state updates from the ground based navigation system, passive optical imaging from a gimbaled camera, a stable inertial measurement unit, and a capable radar altimeter and velocimeter. The focus of this paper is on navigation performance during the trans-lunar cruise, lunar orbit, and descent/landing mission phases with the goal of characterizing knowledge and delivery errors to key mission events, bound the statistical delta V costs for executing the mission, as well as the determine the landing dispersions due to navigation. This study examines the nominal performance that can be obtained using the current best estimate of the vehicle, sensor, and environment models. Performance of the system under a variety sensor outages and parametric trades is also examined.

lunar lander↗
NASA NTRS2015

Desensitized Optimal Filtering and Sensor Fusion Toolkit

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

Karlgaard, Christopher D.↗
NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗
NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗
NASA NTRS2015

Real Time Radiation Exposure And Health Risks

Radiation from solar particle events (SPEs) poses a serious threat to future manned missions outside of low Earth orbit (LEO). Accurate characterization of the radiation environment in the inner heliosphere and timely monitoring the health risks to crew are essential steps to ensure the safety of future Mars missions. In this project we plan to develop an approach that can use the particle data from multiple satellites and perform near real-time simulations of radiation exposure and health risks for various exposure scenarios. Time-course profiles of dose rates will be calculated with HZETRN and PDOSE from the energy spectrum and compositions of the particles archived from satellites, and will be validated from recent radiation exposure measurements in space. Real-time estimation of radiation risks will be investigated using ARRBOD. This cross discipline integrated approach can improve risk mitigation by providing critical information for risk assessment and medical guidance to crew during SPEs.

Hu, Shaowen↗
NASA NTRS2016

Supra Arcade Downflows with XRT Informed by Dipolarization Fronts with THEMIS

Magnetic reconnection can rapidly reconfigure the magnetic field of the corona, accelerating plasma through the site of reconnection. Ambiguities due to the nature of remote sensing have complicated the interpretation of observations of the inflowing and outflowing plasma in reconnecting regions. In particular, the interpretation of sunward moving density depletions above flare arcades (known as Supra Arcade Downflows - SADs) is still debated. Hinode/XRT has provided a wealth of observations for SADs and helped inform our current understanding of these structures. SADs have been interpreted as wakes behind newly reconnected and outflowing loops (Supra Arcade Downflowing Loops - SADLs). Models have shown the plausibility of this interpretation, though this interpretation has not yet been fully accepted. We present here observations of newly reconnected outflowing loops observed via in situ instruments in the magnetosphere. These observations, provided by five THEMIS spacecraft, show that around retracting loops (dipolarization fronts in this context) similar dynamic temperature and density structures are found as seen in SADs. We compare data from multiple SADs and dipolarization fronts to show that the observational signatures implied in the corona can be directly observed in similar plasma regimes in the magnetosphere, strongly favoring the interpretation of SADs as wakes behind retracting loops.

magnetism↗
NASA NTRS2016

Supra Arcade Downflows with XRT Informed by Dipolarization Fronts with THEMIS

Magnetic reconnection can rapidly reconfigure the magnetic field of the corona, accelerating plasma through the site of reconnection. Ambiguities due to the nature of remote sensing have complicated the interpretation of observations of the inflowing and outflowing plasma in reconnecting regions. In particular, the interpretation of sunward moving density depletions above flare arcades (known as Supra Arcade Downflows - SADs) is still debated. Hinode/XRT has provided a wealth of observations for SADs and helped inform our current understanding of these structures. SADs have been interpreted as wakes behind newly reconnected and outflowing loops (Supra Arcade Downflowing Loops - SADLs). Models have shown the plausibility of this interpretation, though this interpretation has not yet been fully accepted. We present here observations of newly reconnected outflowing loops observed via in situ instruments in the magnetosphere. These observations, provided by five THEMIS spacecraft, show that around retracting loops (dipolarization fronts in this context) similar dynamic temperature and density structures are found as seen in SADs. We compare data from multiple SADs and dipolarization fronts to show that the observational signatures implied in the corona can be directly observed in similar plasma regimes in the magnetosphere, strongly favoring the interpretation of SADs as wakes behind retracting loops.

corona↗
NASA NTRS2017

Cleared for Launch - Lessons Learned from the OSIRIS-REx System Requirements Verification Program

Requirements verification of a large flight system is a challenge. It is especially challenging for engineers taking on their first role in space systems engineering. This paper describes our approach to verification of the Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) system requirements. It also captures lessons learned along the way from developing systems engineers embroiled in this process. We begin with an overview of the mission and science objectives as well as the project requirements verification program strategy. A description of the requirements flow down is presented including our implementation for managing the thousands of program and element level requirements and associated verification data. We discuss both successes and methods to improve the managing of this data across multiple organizational interfaces. Our approach to verifying system requirements at multiple levels of assembly is presented using examples from our work at instrument, spacecraft, and ground segment levels. We include a discussion of system end-to-end testing limitations and their impacts to the verification program. Finally, we describe lessons learned that are applicable to all emerging space systems engineers using our unique perspectives across multiple organizations of a large NASA program.

Requirements Verification↗