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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strainbased method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2%, 0.28%, and 0.09%, respectively; and maximum slope errors in roll and pitch directions are 0.28% and -3.2%, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8% of the photogrammetry data and are accurate to within 2.2% in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction.

shape sensing↗
NASA NTRS2015

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strain-based method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2 percent, 0.28 percent, and 0.09 percent, respectively; and maximum slope errors in roll and pitch directions are 0.28 percent and -3.2 percent, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8 percent of the photogrammetry data and are accurate to within 2.2 percent in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction..

system equivalent reduction and expansion process↗
NASA NTRS2015

Wing Shape Sensing from Measured Strain

A new two step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to extrapolate the deflection and slope of the entire structure through the use of System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular wing. It is then applied to test data from a cantilevered swept wing model.

system equivalent reduction and expansion process↗
NASA NTRS2015

Research-Based Monitoring, Prediction, and Analysis Tools of the Spacecraft Charging Environment for Spacecraft Users

The Space Weather Research Center (http://swrc. gsfc.nasa.gov) at NASA Goddard, part of the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov), is committed to providing research-based forecasts and notifications to address NASA's space weather needs, in addition to its critical role in space weather education. It provides a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, and weekly summaries and reports. In this paper, we focus on how (near) real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the integrated Space Weather Analysis system (http://iswa.gsfc.nasa.gov), enable monitoring, analyzing, and predicting the spacecraft charging environment for spacecraft users. Relevant tools and resources are discussed.

space weather↗
NASA NTRS2024

Córdoba Wildland Fires: Assessing Fire Risk Factors in Córdoba, Argentina using Earth Observations

In recent years, Córdoba, Argentina has experienced intensified wildfire activity, with fires in 2020 alone scorching over 300,000 hectares within the province. Potential causes for the increased burn area include climate change, the expanding wildland-urban interface (WUI), and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the environmental parameters influencing fire behavior and growth. We partnered with the Instituto Nacional de Tecnología Agropecuaria (INTA) to address these gaps by utilizing NASA Earth observing data to analyze key wildfire risk factors. Using a combination of data inputs from Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), and Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), we created a ten-year baseline using environmental variables to determine anomalies that influenced the fires of 2020. Baseline data were used to calculate the statistical significance of the environmental factors as precursors to wildfires. We found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, we created a wildfire risk map for the province of Córdoba, which can be used to enhance our partner’s fire management strategies and decision-making processes.

wildland fires↗
NASA NTRSDate not supplied

Exemplifying the Usability of NASA Earth Observations to Analyze Potential Risk Factors that Predispose Wildfires in the Rural-Urban Areas of Córdoba, Argentina

In recent years, Córdoba, Argentina has experienced intensified wildfire activity, with fires in 2020 alone scorching over 300,000 hectares within the province. Potential causes for the increased burn area include climate change, the expanding wildland-urban interface, and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the parameters influencing fire behavior and growth. This project partnered with the Instituto Nacional de Tecnología Agropecuaria to address these gaps by utilizing NASA’s remote sensing capabilities to analyze key wildfire risk factors. Using a combination of data inputs from Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), and Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), a ten-year baseline was created using environmental variables to determine anomalies that influenced the fires of 2020. Of these anomalies, the baseline data were used to calculate the statistical significance of the environmental factors to the wildfires. This study found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, this project created a wildfire risk map for the province of Córdoba, which can be used to enhance partner’s fire management strategies and decision-making processes.

Chassety Raines↗
NASA NTRS2021

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Ghada Y.H. El Serafy↗
NASA NTRS1981

The distribution of maximum temperatures of coronal active region loops

Starting with the integrated emission measure distributions of solar active regions, the distribution of the maximum temperature parameter which characterizes individual plasma loops is determined. The observed emission measure distributions were determined by combining EUV and X-ray data from two separate experiments on ATM/Skylab. The present work sets some limits on such an approach. It is found that the distribution of maximum temperature has approximately the same shape as the integrated emission measure distributions, a result which is expected since most of the loop emission measure is near their maximum temperatures.

Teske, R. G.↗
NASA NTRS2001

Bio-Optical Measurement and Modeling of the California Current and Polar Oceans

This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project contract supports in situ ocean optical observations in the California Current, Southern Ocean, Indian Ocean as well as merger of other in situ data sets we have collected on various global cruises supported by separate grants or contracts. The principal goals of our research are to validate standard or experimental products through detailed bio-optical and biogeochemical measurements, and to combine ocean optical observations with advanced radiative transfer modeling to contribute to satellite vicarious radiometric calibration and advanced algorithm development. In collaboration with major oceanographic ship-based observation programs funded by various agencies (CalCOFI, US JGOFS, NOAA AMLR, INDOEX and Japan/East Sea) our SIMBIOS effort has resulted in data from diverse bio-optical provinces. For these global deployments we generate a high-quality, methodologically consistent, data set encompassing a wide-range of oceanic conditions. Global data collected in recent years have been integrated with our on-going CalCOFI database and have been used to evaluate Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) algorithms and to carry out validation studies. The combined database we have assembled now comprises more than 700 stations and includes observations for the clearest oligotrophic waters, highly eutrophic blooms, red-tides and coastal case two conditions. The data has been used to validate water-leaving radiance estimated with SeaWiFS as well as bio optical algorithms for chlorophyll pigments. The comprehensive data is utilized for development of experimental algorithms (e.g., high-low latitude pigment transition, phytoplankton absorption, and cDOM).

Mitchell, B. Greg↗
NASA NTRSDate not supplied

The Human Research Program Grant Lifecycle & Data Integration Schedule: Infographic

The Human Research Program (HRP) Grant Lifecycle process can be described using information from several government authoritative sources with overlapping generalizations. It is the responsibility of the HRP Program Planning & Control (PP&C) Office and the Data Management Integration Office (DMIO)to interpret this information into a cohesive process that can be communicated to the human research organization. PP&C and DMIO have been exploring training opportunities to facilitate understanding through the form of infographics. This communication tool combines eye-catching visuals and text making complex information and data more digestible and shareable. The infographic poster tells a short story about a federally awarded grant and is intended to help both the new and experienced HRP workforce understand the timeline for a research procurement and where their specific tasks fall within the 4 phases of the grant lifecycle. The Pre-Award, Award, Post-Award, and Closeout phases are overlayed with business swimlanes so HRP stakeholders can see where they fit into the timeline rather than working in an isolated part. This includes the Chief Scientist Office (CSO), PP&C, the Data Management Integration Office (DMIO), the Principal Investigator (PI), the Element stakeholders, the LSDA Archivists, and the Research & Operations Integration (ROI) team along with the stakeholders in the Human Health and Performance Directorate. Additionally, the poster introduces (1) the HRP Data Integration Schedule identified in the HRP Data Management Plan HRP-48047, Table 8-2 and (2) a Smartsheet Solution to automate the grants tracking business process. Emphasis is given to the Data Integration Schedule which is the basis for the milestone tasks that are to be completed during the Post-Award phase in the grant lifecycle. The poster is also an opportunity to present the Smartsheet Solution, a software collaboration and work management tool used to assign tasks and track project progress. This PP&C FY24 effort will facilitate an end-to-end solution to track grants and provide insight to the health of HRP grant research procurements using metrics, reports, and dashboards.

J Peace↗
NASA NTRS2004

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

Miller, David W.↗
NASA NTRS1989

An integrated CFD/experimental analysis of aerodynamic forces and moments

Aerodynamic analysis using computational fluid dynamics (CFD) is most fruitful when it is combined with a thorough program of wind tunnel testing. The understanding of aerodynamic phenomena is enhanced by the synergistic use of both analysis methods. A technique is described for an integrated approach to determining the forces and moments acting on a wind tunnel model by using a combination of experimentally measured pressures and CFD predictions. The CFD code used was FLO57 (an Euler solver) and the wind tunnel model was a heavily instrumented delta wing with 62.5 deg of leading-edge sweep. A thorough comparison of the CFD results and the experimental data is presented for surface pressure distributions and longitudinal forces and moments. The experimental pressures were also integrated over the surface of the model and the resulting forces and moments are compared to the CFD and wind tunnel results. The accurate determination of various drag increments via the combined use of the CFD and experimental pressures is presented in detail.

Melton, John E.↗
NASA NTRS1977

Integration of socioeconomic data and remotely sensed imagery for land use applications

The Image Based Information System (IBIS) uses techniques of digital image processing to interface geocoded data sets, information management systems, thematic maps, and remotely sensed imagery. For two cases IBIS has been used to integrate remotely sensed imagery and socioeconomic data. In the first case thematically classified Landsat imagery covering Orange County, California is combined with census tracts and municipalities. In the second case, thematically classified Landsat imagery over Los Angeles, California is combined with census tracts.

Bryant, N. A.↗
NASA NTRS1984

The validation of Nimbus 7 LIMS measurements of ozone

Approximately seven and one half months of stratospheric ozone profiles have been processed from the LIMS (Limb Infrared Monitor of the Stratosphere) experiment on the Nimbus 7 satellite. Data profiles cover the stratosphere and mesosphere from 100 to 0.1 mbar and from 84 degrees N to 64 degrees S latitude. Topics covered include the ozone channel characteristics, precision, systematic uncertainties, and comparisons with data from balloon and rocket underflights, Umkehr soundings, and Dobson measurements. Comparisons with Dobson total ozone are made by integrating combined LIMS plus balloon profiles. The estimated on-orbit precision is 0.02-0.16 ppmv. Simulations of the experiment indicate potential systematic uncertainties ranging from 15 percent in the 1-mbar region to an upper limit of 40 percent at 100 mbar and 0.1 mbar. Results are well within the uncertainties for the correlative sensors themselves. LIMS detects significant vertical structure in the ozone profile even below the ozone mixing ratio peak. Several other comparisons showing good agreement are noted.

Remsberg, E. E.↗
NASA NTRS1986

A rotorcraft flight/propulsion control integration study

An eclectic approach was taken to a study of the integration of digital flight and propulsion controls for helicopters. The basis of the evaluation was the current Gen Hel simulation of the UH-60A Black Hawk helicopter with a model of the GE T700 engine. A list of flight maneuver segments to be used in evaluating the effectiveness of such an integrated control system was composed, based on past experience and an extensive survey of the U.S. Army Air-to-Air Combat Test data. A number of possible features of an integrated system were examined and screened. Those that survived the screening were combined into a design that replaced the T700 fuel control and part of the control system in the UH-60A Gen Hel simulation. This design included portions of an existing pragmatic adaptive fuel control designed by the Chandler-Evans Company and an linear quadratic regulator (LQR) based N(p) governor designed by the GE company, combined with changes in the basic Sikorsky Aircraft designed control system. The integrated system exhibited improved total performance in many areas of the flight envelope.

Ruttledge, D. G. C.↗
NASA NTRSDate not supplied

ICME for NASA Aerospace Applications: Batteries for Electric Aviation

NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.

John Lawson↗