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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 289 records · Page 16

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NASA NTRS1992

Self-sensing piezoelectric actuation - Analysis and application to controlled structures

Issues related to modeling and implementation of a self-sensing piezoelectric actuator are investigated. The necessary formulation for modeling the simultaneous sensing and actuation phenomenon is provided. Open and closed loop experiments performed on a cantilevered beam test specimen are described. The sensitivity of the results to representative errors introduced in the implementation of the transducer is demonstrated analytically and experimentally. The self-sensing actuator is also implemented using an active piezoelectric strut in a truss structure.

Anderson, Eric H.↗

NASA NTRS2019

Large Contribution of Meteorological Factors to Inter-Decadal Changes in Regional Aerosol Optical Depth

Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =−34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.

Huizheng Che↗

NASA NTRS2014

The Uncertainty of Biomass Estimates from LiDAR and SAR Across a Boreal Forest Structure Gradient

In this study, weexamined the uncertainty of aboveground live biomass (AGB) estimates based on light detection and ranging (LiDAR) and synthetic aperture radar (SAR) measurements distributed across a low-biomass vegetation structure gradient fromforest to non-forest in boreal-like ecosystems. The conifer-dominant structure gradient was compiled from ground data amassed from multiple field expeditions in central Maine (USA), Aurskog (Norway), and across central Siberia (Russia). Single variable empirical models were built tomodel AGB fromremote sensingmetrics. Using thesemodels, we calculated a rootmean square error (RMSE) and a 95% confidence interval (CI) of the RMSE fromthe difference between the remote sensing AGB predictions and the ground reference AGB estimates within AGB intervals across a 0-100 Mg ha(exp.−1) boreal forest structure gradient. The results show that the error in AGB predictions (RMSE) and the error uncertainty (the CI) from LiDAR and SAR change across a forest gradient. The errors of airborne LiDAR and SAR metrics and spaceborne LiDAR platforms show a general trend of reduced relative errors as AGBmagnitudes increase, particularly from0 to 60 Mg ha (exp.−1). Empirical models relating spaceborne metrics to AGB and estimates of spaceborne LiDAR error uncertainty demonstrate the difficulty of characterizing differences in AGB at the site-level with current spaceborne sensors, particularly below 80 Mg ha (exp.−1) with less than 50-100% error.

Taiga↗

NASA NTRS1973

A study of the potential of remote sensors in urban transportation planning

The potential uses of remotely sensed data as applied to the transportation planning process are presented. By utilizing the remote sensing technology developed by the National Aeronautics and Space Administration in the various space programs, it is hoped that both the expense and errors inherent in the conventional data collection techniques can be avoided. Additional bonuses derived from the use of remotely sensed data are those of the permanent record nature of the data and the traffic engineering data simultaneously made available. The major mathematical modeling phases and the role remotely sensed data might play in replacing conventionally collected data are discussed. Typical surveys undertaken in the overall planning process determine the nature and extent of travel desires, land uses, transportation facilities and socio-economic characteristics. Except for the socio-economic data, data collected in the other surveys mentioned can be taken from photographs in sufficient detail to be useful in the modeling procedures.

Rietschier, D.↗

NASA NTRS2007

Control of Formation-Flying Multi-Element Space Interferometers with Direct Interferometer-Output Feedback

The long-baseline space interferometer concept involving formation flying of multiple spacecrafts holds great promise as future space missions for high-resolution imagery. A major challenge of obtaining high-quality interferometric synthesized images from long-baseline space interferometers is to accurately control these spacecraft and their optics payloads in the specified configuration. Our research focuses on the determination of the optical errors to achieve fine control of long-baseline space interferometers without resorting to additional sensing equipment. We present a suite of estimation tools that can effectively extract from the raw interferometric image relative x/y, piston translational and tip/tilt deviations at the exit pupil aperture. The use of these error estimates in achieving control of the interferometer elements is demonstrated using simulated as well as laboratory-collected interferometric stellar images.

Lu, Hui-Ling↗

NASA NTRS2007

Control of Formation-Flying Multi-Element Space Interferometers with Direct Interferometer-Output Feedback

The long-baseline space interferometer concept involving formation flying of multiple spacecraft holds great promise as future space missions for high-resolution imagery. A major challenge of obtaining high-quality interferometric synthesized images from long-baseline space interferometers is to accurately control these spacecraft and their optics payloads in the specified configuration. Our research focuses on the determination of the optical errors to achieve fine control of long-baseline space interferometers without resorting to additional sensing equipment. We present a suite of estimation tools that can effectively extract from the raw interferometric image relative x/y, piston translational and tip/tilt deviations at the exit pupil aperture. The use of these error estimates in achieving control of the interferometer elements is demonstrated using simulated as well as laboratory-collected interferometric stellar images.

Lu, Hui-Ling↗

NASA NTRS1975

Error in temperature measurements due to conduction along the sensors

When a sensor is embedded in a solid body to measure its internal temperature, any conduction to or from its sensing element may cause the indicated temperature to be different from the true temperature. This paper describes an analysis of the error caused by conduction when there is an arbitrary temperature distribution in the body along the sensor. The sensor is modeled as a cylindrical fin and the appropriate conduction equation is solved. The solution gives a correction for the error which depends on such parameters as, depth of immersion, thermocouple wire and insulation properties, contact between the sensor and the body, and temperature distribution in the body. The latter may not be known, but the measured temperature distribution can be used as a first approximation. The corrected value can then be used to obtain a better estimate of the error. The results show good agreement with experimental observations.

Singh, B. S.↗

NASA NTRS1984

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture Remote Sensing

It is believed that the increased spatial resolution will provide solutions to proportion estimation error due to mixed pixels, and the increased spectral resolution will provide for the identification of important agricultural features such as crop stage, and condition. The results of analyses conducted relative to these hypothesis from sample segments extracted from the 4-band Detroit scene and the 7-band Mississippi County, Arkansas engineering test scene are described. Several studies were conducted to evaluate the geometric and radiometric performance of the TM to determine data viability for the more pertinent investigations of TM utility. In most cases this requirement was more than sufficiently satisfied. This allowed the opportunity to take advantage of detailed ground observations for several of the sample segments to assess class separability and detection of other important features with TM. The results presented regarding these TM characteristics show that not only is the increased definition of the within scene variance captured by the increased spatial and spectral resolution, but that the mid-IR bands (5 and 7) are necessary for optimum crop type classification. Both qualitative and quantitative results are presented that describe the improvements gained with the TM both relative to the MSS and on its own merit.

Bizzell, R. M.↗

NASA NTRS1995

Modal Correction Method For Dynamically Induced Errors In Wind-Tunnel Model Attitude Measurements

This paper describes a method for correcting the dynamically induced bias errors in wind tunnel model attitude measurements using measured modal properties of the model system. At NASA Langley Research Center, the predominant instrumentation used to measure model attitude is a servo-accelerometer device that senses the model attitude with respect to the local vertical. Under smooth wind tunnel operating conditions, this inertial device can measure the model attitude with an accuracy of 0.01 degree. During wind tunnel tests when the model is responding at high dynamic amplitudes, the inertial device also senses the centrifugal acceleration associated with model vibration. This centrifugal acceleration results in a bias error in the model attitude measurement. A study of the response of a cantilevered model system to a simulated dynamic environment shows significant bias error in the model attitude measurement can occur and is vibration mode and amplitude dependent. For each vibration mode contributing to the bias error, the error is estimated from the measured modal properties and tangential accelerations at the model attitude device. Linear superposition is used to combine the bias estimates for individual modes to determine the overall bias error as a function of time. The modal correction model predicts the bias error to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment.

Buehrle, R. D.↗

DOE OSTI2024

Optimal function estimation with photonic quantum sensor networks

The problem of optimally measuring an analytic function of unknown local parameters each linearly coupled to a qubit sensor is well understood, with applications ranging from field interpolation to noise characterization. Here we resolve a number of open questions that arise when extending this framework to Mach-Zehnder interferometers and quadrature displacement sensing. In particular, we derive lower bounds on the achievable mean square error in estimating a linear function of either local phase shifts or quadrature displacements. In the case of local phase shifts, these results prove, and somewhat generalize, a conjecture by Proctor []. For quadrature displacements, we extend proofs of lower bounds to the case of arbitrary linear functions. We provide optimal protocols achieving these bounds up to small (multiplicative) constants and describe an algebraic approach to deriving new optimal protocols, possibly subject to additional constraints. Using this approach, we prove necessary conditions for the amount of entanglement needed for any optimal protocol for both local phase and displacement sensing. Published by the American Physical Society 2024

Bringewatt, Jacob↗

NASA NTRS1982

Investigation of geomagnetic field forecasting and fluid dynamics of the core

It was established that the total absolute magnetic flux crossing the core- mantle boundary has been a constant of the core motion for the last 50 years. This provides a scalar constraint that could be added to the geometric modelling procedure. The GSFC 8 8/80 model is being evaluated. The absolute magnetic flux linking the CMB to that model was plotted as a function of time during the span covered by the data, and increasing truncation level. The inclusion of the standard error of each Gauss coefficient derived from the statistics of fit in the GSFC 9/80 model is useful. The magnitude and sense (upwelling or downe welling) of vertical fluid motion adjacent to the core-mantle boundary was calculated using the model. Standard errors were found to be sufficiently small at all but one or two of the 40 or more critical points of B sub r. They do not nearly overlap the value gamma u/gamma r = 0. It is concluded that the core is upwelling and downwelling at an observationally detectable level.

Benton, E. R.↗

NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗

NASA NTRS1979

Pressure sensing of the atmosphere by solar occultation using broadband CO2 absorption

A technique for obtaining pressure at the tangent point in an IR solar occulation experiment is described. By measuring IR absorption in bands of atmospheric CO2 (e.g., 2.0, 2.7, or 4.3 microns), mean pressure values for each tangent point layer (vertical thickness 2 km or less) of the atmosphere can be obtained with rms errors of less than 3%. The simultaneous retrieval of pressure and gas concentration in a remote-sensing experiment will increase the accuracy of inverted gas concentrations and minimize the dependence of the experiment on pressure or mass path error resulting from use of climatological pressure data, satellite ephemeris, and instrument pointing accuracy.

Park, J. H.↗

NASA NTRS1973

Heat conduction errors and time lag in cryogenic thermometer installations

Installation practices are recommended that will increase rate of heat exchange between the thermometric sensing element and the cryogenic fluid and that will reduce the rate of undesired heat transfer to higher-temperature objects. Formulas and numerical data are given that help to estimate the magnitude of heat-conduction errors and of time lag in response.

Warshawsky, I.↗

DOE OSTI2020

Dynamic compressed sensing for real-time tomographic reconstruction

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by ~3-fold while also reducing its error by 27% for a Au/SrTiO 3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within ~33% of completion and fine details are visible as early as ~66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, we report reconstruction parameters that tune data fidelity can be manipulated throughout the computation without re-running the entire process.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Conservative finite‐volume schemes for the quasi‐geostrophic equation on coastal‐conforming unstructured primal–dual meshes

In this article we propose finite‐volume schemes for solving the inviscid and viscous quasi‐geostrophic equations on coastal‐conforming unstructured primal–dual meshes. Several approaches for enforcing the boundary conditions are also explored along with these schemes. The pure transport parts in these schemes are shown to conserve the potential vorticity along fluid paths in an averaged sense, and conserve the potential enstrophy up to the time truncation errors. Numerical tests based on the centroidal Voronoi–Delaunay meshes are performed to confirm these properties, and to distinguish the dynamical behaviours of these schemes. Finally some potential applications of these schemes in different situations are discussed.

Chen, Qingshan↗

DOE OSTI2018

Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds

In this study, the computational burden of a large-eddy simulation for reactive flows is exacerbated in the presence of uncertainty in flow conditions or kinetic variables. A comprehensive statistical analysis, with a sufficiently large number of samples, remains elusive. Statistical learning is an approach that allows for extracting more information using fewer samples. Such procedures, if successful, will greatly enhance the predictability of models in the sense of improving exploration and characterization of uncertainty due to model error and input dependencies, all while being constrained by the size of the associated statistical samples. In this paper, it is shown how a recently developed procedure for probabilistic learning on manifolds can serve to improve the predictability in a probabilistic framework of a scramjet simulation. The estimates of the probability density functions of the quantities of interest are improved together with estimates of the statistics of their maxima. Lastly, it is also demonstrated how the improved statistical model adds critical insight to the performance of the model.

42 ENGINEERING↗

NASA NTRS1969

Automatic frequency control of voltage-controlled oscillators

Optical-capacitive coupling is used for isolation of control voltages, such as the high-voltage level of a klystron control electrode that is not referenced to ground, to serve as error voltages referenced to system ground so that the magnitude and sense of correction may be transferred.

Kolbly, R. B.↗