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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Cause and Cure - Deterioration in Accuracy of CFD Simulations with Use of High-Aspect-Ratio Triangular/Tetrahedral Grids

Traditionally high-aspect ratio triangular/tetrahedral meshes are avoided by CFD researchers in the vicinity of a solid wall, as it is known to reduce the accuracy of gradient computations in those regions. Although for certain complex geometries, the use of high-aspect ratio triangular/tetrahedral elements in the vicinity of a solid wall can be replaced by quadrilateral/prismatic elements, ability to use triangular/tetrahedral elements in such regions without any degradation in accuracy can be beneficial from a mesh generation point of view. The benefits also carry over to numerical frameworks such as the space-time conservation element and solution element (CESE), where simplex elements are the mandatory building blocks. With the requirement of the CESE method in mind, a rigorous mathematical framework that clearly identifies the reason behind the difficulties in use of such high-aspect ratio simplex elements is formulated using two different approaches and presented here. Drawing insights from the analysis, a potential solution to avoid that pitfall is also provided as part of this work. Furthermore, through the use of numerical simulations of practical viscous problems involving high-Reynolds number flows, how the gradient evaluation procedures of the CESE framework can be effectively used to produce accurate and stable results on such high-aspect ratio simplex meshes is also showcased.

CESE Method↗
NASA NTRS2017

Cause and Cure-Deterioration in Accuracy of CFD Simulations with Use of High-Aspect-Ratio Triangular/Tetrahedral Grids

In the multi-dimensional space-time conservation element and solution element16 (CESE) method, triangles and tetrahedral mesh elements turn out to be the most natural building blocks for 2D and 3D spatial grids, respectively. As such, the CESE method is naturally compatible with the simplest 2D and 3D unstructured grids and thus can be easily applied to solve problems with complex geometries. However, because (a) accurate solution of a high-Reynolds number flow field near a solid wall requires that the grid intervals along the direction normal to the wall be much finer than those in a direction parallel to the wall and, as such, the use of grid cells with extremely high aspect ratio (103 to 106) may become mandatory, and (b) unlike quadrilateral hexahedral grids, it is well-known that accuracy of gradient computations involving triangular tetrahedral grids tends to deteriorate rapidly as cell aspect ratio increases. As a result, the use of triangular tetrahedral grid cells near a solid wall has long been deemed impractical by CFD researchers. In view of (a) the critical role played by triangular tetrahedral grids in the CESE development, and (b) the importance of accurate resolution of high-Reynolds number flow field near a solid wall, as will be presented in the main paper, a comprehensive and rigorous mathematical framework that clearly identifies the reasons behind the accuracy deterioration as described above has been developed for the 2D case involving triangular cells. By avoiding the pitfalls identified by the 2D framework, and its 3D extension, it has been shown numerically.

CFD↗
NASA NTRS2017

Quantifying TOLNet Ozone Lidar Accuracy During the 2014 DISCOVER-AQ and FRAPPE Campaigns

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry Experiment (FRAPPA) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than +/-15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than +/-5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.

TOLNet↗
NASA NTRS2017

Testing the Accuracy of Data-Driven MHD Simulations of Active Region Evolution

Models for the evolution of the solar coronal magnetic field are vital for understanding solar activity, yet the best measurements of the magnetic field lie at the photosphere, necessitating the development of coronal models which are "data-driven" at the photosphere. We present an investigation to determine the feasibility and accuracy of such methods. Our validation framework uses a simulation of active region (AR) formation, modeling the emergence of magnetic flux from the convection zone to the corona, as a ground-truth data set, to supply both the photospheric information and to perform the validation of the data-driven method. We focus our investigation on how the accuracy of the data-driven model depends on the temporal frequency of the driving data. The Helioseismic and Magnetic Imager on NASA's Solar Dynamics Observatory produces full-disk vector magnetic field measurements at a 12-minute cadence. Using our framework we show that ARs that emerge over 25 hours can be modeled by the data-driving method with only approximately 1 percent error in the free magnetic energy, assuming the photospheric information is specified every 12 minutes. However, for rapidly evolving features, under-sampling of the dynamics at this cadence leads to a strobe effect, generating large electric currents and incorrect coronal morphology and energies. We derive a sampling condition for the driving cadence based on the evolution of these small-scale features, and show that higher-cadence driving can lead to acceptable errors. Future work will investigate the source of errors associated with deriving plasma variables from the photospheric magnetograms as well as other sources of errors, such as reduced resolution, instrument bias, and noise.

Leake, James E.↗
NASA NTRS2018

On-orbit Validation of the Geolocation Accuracy of the GOES-16 Geostationary Lightning Mapper (GLM) Flashes Using Ground-based Laser Beacons

As part of the geolocation accuracy assessment of lightning flashes detected by the Geostationary Lightning Mapper (GLM) on the GOES-16 and GOES-17 satellites (Geostationary Operational Environmental Satellite), two satellite laser ranging stations employed laser beacon systems to generate transient light pulses that simulate natural lightning around 777.4 nm to validate the pre-launch spec of 5 km. The pulse width, repetition rate, wavelength, and power of the laser-pulses were configured to produce sufficient instrument response to be detected as synthetic lightning events by the GLM instrument. During the testing period from April 2017 to January 2018, the laser systems illuminated the GOES-16 satellite to observe diurnal variation of the GLM system response, with particular emphasis on geolocation accuracy. The final GOES-16 laser beacon tests, which used the latest updates of the geolocation algorithms implemented by the GOES-R Ground Segment, showed the offsets between the GLM geolocated location and the known laser locations were within 5 km.

Lightning↗
NASA NTRS2014

Trajectory Prediction Accuracy and Error Sources for Regional Jet Descents: Results of a 2010 Flight Trial at Denver International Airport using a Global 5000 Test Aircraft - Part I

The Efficient Descent Advisor (EDA) controller automation tool generates trajectory-based speed, path, and altitude-profile advisories to facilitate efficient, continuous descents into congested terminal airspace. While prior field trials have assessed the trajectory-prediction accuracy for large jet (i.e., Boeing and Airbus) types, smaller (i.e., regional and business) jet types present unique challenges involving different descent procedures and Flight Management System (FMS) capabilities. A small-jet field trial was conducted at Denver in the fall of 2010 with the objective of measuring trajectory prediction accuracy and quantifying the primary sources of error. This paper uses data collected onboard a Bombardier Global 5000 test aircraft to quantify the size and sources of trajectory prediction error. Error sources were quantified for the 44 runs by incrementally replacing predicted data with data collected onboard the aircraft and measuring the effect on time error. Results for en-route descents, from prior to top of descent to the meter fix 60-120 nmi downstream, indicate that the aircraft arrived an average 15 seconds earlier than predicted, with a standard deviation of 10 seconds. Target Mach and CAS deceleration were found to be the two largest error sources. If CAS deceleration error was reduced using a typical, more predictable level flight deceleration then the arrival time prediction error in 2010 would be on par with a 2009 flight trial of Airbus and Boeing revenue flights. Four of the error sources, tracker jumps, CAS deceleration, target Mach, and path distance, lend themselves to significant reductions with modest to no changes to ATC automation andor procedures. Wind error and its impact on arrival time error was significantly reduced in 2010 compared to a 1994 flight test using NASAs Boeing 737 test aircraft.

Trajectory Prediction Error↗
NASA NTRS2014

Trajectory Prediction Accuracy and Error Sources for Regional Jet Descents: Results of a 2010 Flight Trial at Denver International Airport using SkyWest Revenue Flights - Part II

The Efficient Descent Advisor (EDA) controller automation tool generates trajectory-based speed, path, and altitude-profile advisories to facilitate efficient, continuous descents into congested terminal airspace. While prior field trials have assessed the trajectory prediction accuracy for large jet (i.e., Boeing and Airbus) types, smaller (i.e., regional and business) jet types present unique challenges involving different descent procedures and Flight Management System (FMS) capabilities. This paper quantifies the trajectory prediction accuracy for small jet revenue flight descents based on SkyWest Canadair Regional Jet 200, 700, and 900 aircraft arrivals to Denver in the fall of 2010. Post flight test data analysis and SkyWest pilot interviews uncovered unexpected variation between flight crews due to different interpretations of (1) which fixed flight path angle (FPA) to fly based on the flight trial procedure and (2) how to fly the descent to achieve the target FPA. Pilot reports were used to select a subset of flights where pilots indicated an FPA according to the flight trial procedure to remove the unexpected variation due to (1) to focus on (2). Results for the subset for en-route descents, from prior to top of descent to the meter fix 30 to 130 nmi downstream, indicate that aircraft arrived to the meter fix six seconds early with about a twelve second standard deviation. Large FPA errors up to one degree relative to the EDA flight trial procedure were detected after the flight trial as a characteristic of the unexpected variation. It is recommended that quantitative validation be performed during future flight trials so that experimental procedures can be adjusted if unexpected results are detected.

Field Test Results↗
NASA NTRS2016

Cassini Navigation: The Road to Consistent Subkilometer Accuracy Satellite Encounters

This paper reviews the orbit determination performance for the last five years of the Cassini Mission Solstice Tour. During this period of time, Cassini had more than 30 satellite encounters, including Titan, Rhea, and Dione. We report on the navigational flyby accuracy, comparing post-flyby reconstructions and encounter predictions, and discuss the performance improvement and challenges over the years. Finally, we give an overview of the "Grand Finale" end of mission planned for 2017.The Cassini mission has been in orbit in the Saturnian system for more than 11 years, and hasreturned a wealth of discoveries and operational knowledge in the outer Solar System. In this paper, we reported on the last three years of navigation operations focusing on orbit determinationand encounter performance. Modeling and strategy changes over the past years now allow us tonavigate bodies at 100s of meters in accuracy, and consider a miss larger than 1 km an outlier.The Cassini Grand Finale will be spectacular - do not miss it!

Bellerose, Julie↗
NASA NTRS2020

Optimizing Performance and Accuracy with LIFQWIK

For the 2020 Summer Internship period, optimization and analysis was performed of a new iteration of the LIFQWIK PLIF model, used to evaluate the accuracy of CFD simulations of fuel injector performance. This presentation details the accuracy and performance optimization steps taken and presents the results of that optimization.

CFD↗
NASA NTRS2004

MSTAR: an absolute metrology system with submicrometer accuracy

Laser metrology systems are a key component of stellar interferometers, used to monitor path lengths and dimensions internal to the instrument. Most interferometers use ‘relative’ metrology, in which the integer number of wavelengths along the path is unknown, and the measurement of length is ambiguous. Changes in the path length can be measured relative to an initial calibration point, but interruption of the metrology beam at any time requires a re-calibration of the system. The MSTAR sensor (Modulation Sideband Technology for Absolute Ranging) is a new system for measuring absolute distance, capable of resolving the integer cycle ambiguity of standard interferometers, and making it possible to measure distance with sub-nanometer accuracy. We describe the design of the system, show results for target distances up to 1 meter, and demonstrate how the system can be scaled to kilometer-scale distances. In recent experiments, we have used white light interferometry to augment the ‘truth’ measurements and validate the zero-point of the system. MSTAR is a general-purpose tool for conveniently measuring length with much greater accuracy than was previously possible, and has a wide range of possible applications

Fetterman, Harrold R.↗
NASA NTRS2004

MSTAR: an absolute metrology system with submicrometer accuracy

Laser metrology systems are a key component of stellar interferometers, used to monitor path lengths and dimensions internal to the instrument. Most interferometers use ‘relative’ metrology, in which the integer number of wavelengths along the path is unknown, and the measurement of length is ambiguous. Changes in the path length can be measured relative to an initial calibration point, but interruption of the metrology beam at any time requires a re- calibration of the system. iThe MSTAR sensor (Modulation Sideband Technology for Absolute Ranging) is a new system for measuring absolute distance, capable of resolving the integer cycle ambiguity of standard interferometers, and making it possible to measure distance with sub-nanometer accuracy. We describe the design of the system, show results for target distances up to 1 meter, and demonstrate how the system can be scaled to kilometer-scale distances. In recent experiments, we have used white light interferometry to augment the ‘truth’ measurements and validate the zero-point of the system. MSTAR is a general-purpose tool for conveniently measuring length with much greater accuracy than was previously possible, and has a wide range of possible applications.

Lay, Oliver↗
NASA NTRS2018

High Accuracy Coronagraph Flight Model For WFIRST–CGI Raw Contrast Sensitivity Analysis

A high-accuracy high-fidelity flight wavefront control (WFC) model is developed for detailed raw contrast sensitivity analysis of WFIRST-CGI. Built upon features of recently testbed validated model, it is further refined to combine a full Fresnel propagation diffraction model for high accuracy contrast truth evaluation, and an economical compact model for WFC purposes. Extensive individual raw contrast error sensitivities are evaluated systematically, both as known imperfections and as unknown calibration errors, for both spectroscopy mode and wide field-of-view mode with shaped pupil coronagraph. More than 90 distinct error items were identified, including system aberrations, optical misalignment, component manufacturing error, telescope interface related errors, etc. The result forms the basis for raw contrast error budget flow down to a sub-system level, where detailed specifications needed to aid in component design and manufacturing, mechanical alignment and instrument integration, and verification and validation operations. Evaluations are mostly automated, making it relatively easy for repeat runs of revised design or at new desired error quantity. Top error sensitivities and contrast floor contributors are discussed and several observations are noted.

Poberezhskiy, Ilya↗
NASA NTRS2018

Updates to the Absolute Radiometric Accuracy of the AIRS on Aqua

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. The AIRS was designed to measure small changes in the global hydro-thermodynamic cycle and has demonstrated exceptional radiometric and spectral stability and accuracy in-orbit. This accuracy is achieved by transferring the calibration from a Large Area Blackbody (LABB) to the On-Board Calibrator (OBC) blackbody during preflight testing. The LABB theoretical emissivity is in excess of 0.9999 and temperature uncertainty is less than 50 mK. The LABB emitted radiance is NIST traceable through thermistors located on the internal surfaces. The AIRS also provides a full aperture space view every scan for offset calibration. AIRS nonlinearity and polarization calibration coefficients were based on pre-flight testing and have been amongst the highest uncertainty sources in the calibration. A recent method using on-board space view data has reduced the uncertainty of the polarization coefficients and use of separate A side and B side data from preflight testing has reduced the uncertainty of the nonlinearity estimates. An update to the system radiometric uncertainty is made based on the new data and is presented in this paper.

Weiler, Margaret H.↗
NASA NTRS2021

Evaluation of GEOS Precipitation Flagging for SMAP Soil Moisture Retrieval Accuracy

The precipitation flag in the Soil Moisture Active Passive (SMAP) Level 2 passive soil moisture (L2SMP) retrieval product indicates the presence or absence of heavy precipitation at the time of the SMAP overpass. The flag is based on precipitation estimates from the Goddard Earth Observing System (GEOS) Forward Processing numerical weather prediction system. An error in flagging during an active or recent precipitation event can produce either 1) an overestimation of soil moisture due to short-term surface wetting of vegetation and/or surface ponding (if soil moisture retrieval was attempted in the presence of rain) or 2) an unnecessary nonretrieval of soil moisture and loss of data (if retrieval is flagged due to an erroneous indication of rain). Satellite precipitation estimates from the Integrated Multisatellite Retrievals for GPM (IMERG), version 06, Early Run (latency of ~4 h) precipitationCal product are used here to evaluate the GEOS-based precipitation flag in the L2SMP product for both the 1800 local time (LT) ascending and 0600 LT descending SMAP overpasses over the first five years of the mission (2015–20). Consisting of blended precipitation measurements from the Global Precipitation Mission (GPM) satellite constellation, IMERG is treated as the “truth” when comparing to the GEOS model forecasts of precipitation used by SMAP. Key results include (i) IMERG measurements generally show higher spatial variability than the GEOS forecast precipitation, (ii) the IMERG product has a higher frequency of light precipitation amounts, and (iii) the effect of incorporating IMERG rainfall measurements in lieu of GEOS precipitation forecasts are minimal on the L2SMP retrieval accuracy (determined vs in situ soil moisture measurements at core validation sites). Our results indicate that L2SMP retrievals continue to meet the mission’s accuracy requirement [standard deviation of the unbiased RMSE (ubRMSE) less than 0.04 cu. m/cu. m].

IMERG-precipitationCal↗
NASA NTRSDate not supplied

Monte Carlo Simulations for Evaluating the Accuracy of GLM Detection Efficiency and False Alarm Rate Retrievals

The performance of the Geostationary Lightning Mapper has been evaluated through comparison with other satellite lightning sensors and ground-based networks. However, because the performance of these reference sensors is both imperfect and imperfectly known, the true performance of GLM can only be estimated through such a process. In particular, GLM performance metrics such as detection efficiency (DE) and false alarm rate (FAR) retrieved through comparison with reference networks are affected by those networks’ own DE, FAR, and spatiotemporal accuracy, as well as the selected flash matching criteria. This study presents follow-on results from an ongoing analysis that uses a Monte Carlo simulation-based inversion technique to quantify the effect on retrieved GLM performance of a reasonable range of reference network DE, FAR, spatiotemporal accuracy, and the associated geographic patterns of each. These results help quantify and bound the actual performance of GLM and the attendant uncertainties when comparing GLM to imperfect reference networks.

Katrina Virts↗
NASA NTRSDate not supplied

Assessment of the Accuracy and Consistency of Cloud Property Retrievals from Passive Radiometers with Varying Spectral Information

Over the past few decades, space-based passive radiometers have been used to study the spatial distribution of clouds and some of their basic properties. Modern radiometers have significantly higher spatial resolution and collect more spectral information (i.e., have more spectral bands) than early instruments, and these advances have allowed researchers to characterize cloud physical and microphysical properties with greater detail. There is significant interest in utilizing as much of the existing satellite record as possible to study global and regional changes in cloud occurrence and distribution as well as the associated changes in reflected shortwave and outgoing longwave fluxes. Cloud property retrieval algorithms such as the NASA Satellite Cloud Optical and Radiative Property System (SatCORPS) have traditionally utilized as much spectral information as possible in order to maximize the accuracy of the retrievals. However, changes to the retrieval algorithm over time in order to take advantage of progressively more spectral information results in inconsistencies in cloud properties which in turn results in inconsistencies with products derived from these properties. It is not possible to implement modern state-of-the-art algorithms to earlier instruments which lack diverse spectral information, but many instruments since the early 2000s generally have approximately similar spectral bands in the visible (~0.65 microns), longwave infrared (~11 microns), and in many cases, the midwave infrared (~3.8 microns) and water vapor absorption (~6.7 microns), portions of the electromagnetic spectrum. Different versions of SatCORPS have been implemented with either the full set of spectral information collected by imagers such as GOES-16 and MODIS or with a reduced set of spectral bands in order to be more consistent with past imagers that lack such diverse spectral information. This study uses independent cloud property retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to assess the accuracy of the retrievals (e.g., cloud fraction, thermodynamic phase, altitude) from the different retrieval methods and to demonstrate the advantages and disadvantages of using a reduced set of common spectral bands in order to achieve temporal and spatial consistency across different instruments.

Christopher R. Yost↗
NASA NTRSDate not supplied

Analysis of the Tropospheric Doppler Radar Wind Profiler Measurement Accuracy

Space launch vehicle trajectory design uses atmospheric winds to determine vehicle performance and structural margin assessments prior to flight. For launches at the United States Space Force’s Eastern Range (ER) at the Cape Canaveral Space Force Station (CCSFS), tropospheric wind measurements come from either in-situ or remote sensing instrumentation. The use of the National Aeronautics and Space Administration’s (NASA) Kennedy Space Center (KSC) 48-MHz Tropospheric Doppler Radar Wind Profiler (TDRWP) has become the primary wind measurement source for several launch vehicles. Extensive evaluations of TDRWP data have occurred to quantify the system performance. This includes quantifying the accuracy of wind estimates over the entire sampling altitude as well as at discrete altitudes. This paper will describe methodology and analyses used to quantify the measurement accuracy of TDRWP data when operating in an alternative mission support mode over a 2-year period from March 2020 to March 2022.

Meghan E. Carrico↗
NASA NTRSDate not supplied

Exploring the Accuracy of RANS Simulations for Mars Entry Vehicles

Accurate yet inexpensive predictions of aerodynamic coefficients for Mars entry vehicles have remained a consistent challenge over the past five decades. Below Mach 6, drag on the backshell becomes significant and must be accurately predicted. Steady Reynolds-averaged Navier-Stokes (RANS) models are commonly used, despite their poor predictions of backshell pressure. While scale-resolving simulations have shown promise in the past decade, there is still a need for cheap, accurate RANS predictions for large aerodynamic databases. The Mars Science Laboratory (MSL) is used as a case study to examine predictive accuracy and known shortcomings for RANS predictions of Mars entry vehicles. Several different grid generation techniques are compared, including a comparison between prismatic boundary layer grids and fully unstructured, tetrahedral grids. Comparisons are made to experimental data for Mach 2.5, 3.5, and 4.5. The accuracy of predicted aerodynamic coefficients is examined. Overpredictions in axial force and drag are explained by a closer examination of the surface pressure. These findings document sensitivities and best practices for future RANS database development of Mars entry vehicles.

RANS↗