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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Launch flexibility using NLP guidance and remote wind sensing

This paper examines the use of lidar wind measurements in the implementation of a guidance strategy for a nonlinear programming (NLP) launch guidance algorithm. The NLP algorithm uses B-spline command function representation for flexibility in the design of the guidance steering commands. Using this algorithm, the guidance system solves a two-point boundary value problem at each guidance update. The specification of different boundary value problems at each guidance update provides flexibility that can be used in the design of the guidance strategy. The algorithm can use lidar wind measurements for on pad guidance retargeting and for load limiting guidance steering commands. Examples presented in the paper use simulated wind updates to correct wind induced final orbit errors and to adjust the guidance steering commands to limit the product of the dynamic pressure and angle-of-attack for launch vehicle load alleviation.

Cramer, Evin J.↗
DOE OSTI2022

Inference-Based Quantum Sensing

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathscr{R}$⁡(θ) (i.e., changes in the measurement outcomes). For simple cases the form of $\mathscr{R}$⁡(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. Here, in this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathscr{R}$⁡(θ) can be fully characterized by only measuring the system response at 2⁢n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω⁢(log 3 ⁡(n)/δ 2 ). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Comparison of modular analytical wake models to the Lillgrund wind plant

Efficient and accurate wake models are required for wind plant performance modeling and the suite of engineering processes that support wind plant layout, control, and monitoring. Although many analytical and engineering wake models with low computational costs have been proposed, their ability to represent the power production of large wind plants in a wide range of atmospheric conditions is not completely understood. The following validation study reviews the underlying theory for analytical wake models, outlines quality control procedures for observational data, and compares model results with observational data from the Lillgrund Wind Plant. Lillgrund makes a valuable case study for wake modeling because of its regular arrangement and the relatively close spacing of constituent wind turbines, which lead to regular and significant wake interactions within the wind plant and the development of deep array flow conditions. Formulations for the velocity deficit, wake-added turbulence, and wake superposition methods are considered in a modular sense, yielding many possible configurations to represent wind turbine wakes, of which seven are examined in detail. Velocity deficit models that account for flow conditions in the near wake are better able to reproduce power production for wind turbines in the transitional region of the wind plant, where wind turbines experience as many as five wakes from upstream turbines. Finally, in the deep array, where power production reaches asymptotic values and wake statistics become quasi-periodic, wake superposition schemes become the largest driver in error reduction; using the linear or maximum wake superposition methods can reduce the relative root mean square error by as much as 40% in the deep array.

17 WIND ENERGY↗
DOE OSTI2021

Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System

Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-based state estimation approaches (matrix completion and compressive sensing) that have been proposed recently to address the challenge of unobservability. The proposed approach exploits both the low rank structure and a suitable transform domain representation to leverage the correlation structure of the spatio-temporal data matrix while incorporating the powerflow constraints of the distribution grid. Simulations are carried out on three phase unbalanced IEEE 37 test system to verify the effectiveness of the proposed approach. The performance results reveal - (1) the superiority over traditional matrix completion and (2) very low state estimation errors for high compression ratios representing very low observability.

Dahale, Shweta↗
NASA NTRS1979

Geos 3 wave height measurements - An assessment during high sea state conditions in the North Atlantic

The sea state in the North Atlantic Ocean has been monitored in February, 1977 to obtain data for verification of Geos 3 radio altimeter wave form data. The altimeter sea state data were found to be in good agreement with in situ sea state measurements and with aircraft remote sensing measurements of wave height. The average difference between the supporting data and Geos 3 was 0.34 m, and the standard deviation 0.61 m. Contour maps of sea state constructed for large regions of the earth's oceans on the basis of Geos 3 altimeter measurements exhibited systematic differences from operationally available computerized maps. It is thought that the underestimation of significant wave height maxima in the operational maps and the underestimation of the speed of movement of oceanic cyclones may be due to basic errors in the output of atmospheric primitive-equation models. Because of the narrow swath width of the Geos-3 sensor, data from several satellite orbits must be combined to construct contour maps, leading to low values of significant wave heights.

Parsons, C. L.↗
NASA NTRS1991

Thermal diffusion in metal-sulfide liquids - Early results

Experiments were carried out to evaluate the Soret effect in liquid Fe-Ni-S-P alloys in order to gain a better understanding of the physical and thermodynamic properties of metallic liquids and to assess the possibility of systematic errors in Czochralski growth techniques. The metal-sulfide liquids were found to show a substantial Soret effect and, contrary to previous expectation, can be as large as that seen in the silicate system. The segregation is largely produced by S-Fe interactions. The P redistribution occurs to reduce activity gradients in P consequent upon S gradients, and P segregation can be approximately predicted in Fe-Ni-S liquids using the activity model of Jones and Malvin (1990). It is inferred that the sense of the Soret segregation, with P going to the cold end and S going to the hot end, is in accordance with the prediction of Malvin et al. (1986), who speculated that the crystal-pulling experiments of Sellamuthu and Goldstein (1985) was influenced by the Soret effect.

Jones, J. H.↗
NASA NTRS2014

Aquarius: Status and Recent Results

Aquarius is a combination active/passive instrument at L band designed to map sea surface salinity globally from space. The radiometer (passive) is the primary instrument for retrieving salinity, and the scatterometer (active) provides information to correct for a major source of error, sea surface roughness (waves). In addition, the radiometer includes a number of special features designed to meet the goal for this challenging measurement, including measurement of the third Stokes parameter to help with the correction for Faraday rotation and rapid sampling to help with the mitigation of radio frequency interference. Aquarius was launched on 10 June 2011 aboard the Aquarius/SAC-D observatory and has been working well. The salinity retrieval continues to improve, and the special features suggest the potential for new applications of remote sensing from space at L band.

Aquarius↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
NASA NTRS2017

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗
DOE OSTI2020

A Chip-Scale Oscillation-Mode Optomechanical Inertial Sensor Near the Thermodynamical Limits

Modern navigation systems integrate the global positioning system (GPS) with an inertial navigation system (INS), which complement each other for correct attitude and velocity determination. Here, the core of the INS integrates accelerometers and gyroscopes used to measure forces and angular rate in the vehicular inertial reference frame. With the help of gyroscopes and by integrating the acceleration to compute velocity and distance, precision and compact accelerometers with sufficient accuracy can provide small–error location determination. Solid–state implementations, through coherent readout, can provide a platform for high performance acceleration detection. In contrast to prior accelerometers using piezoelectric or capacitive readout techniques, optical readout provides narrow–linewidth high–sensitivity laser detection along with low–noise resonant optomechanical transduction near the thermodynamical limits. Here an optomechanical inertial sensor with an 8.2 µg Hz –1/2 velocity random walk (VRW) at an acquisition rate of 100 Hz and 50.9 µg bias instability is demonstrated, suitable for applications, such as, inertial navigation, inclination sensing, platform stabilization, and/or wearable device motion detection. Driven into optomechanical sustained–oscillation, the slot photonic crystal cavity provides radio–frequency readout of the optically–driven transduction with an enhanced 625 µg Hz –1 sensitivity. Measuring the optomechanically–stiffened oscillation shift, instead of the optical transmission shift, provides a 220× VRW enhancement over pre–oscillation mode detection.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Wave Prediction using X-Band Radar (Final Summary Report)

Model Predictive Control (MPC) is the best controls framework available to wave energy today. It allows for the maximization of energy yield from a WEC system while respecting various constraints and losses in the system. This type of constrained optimization is a critical capability for the techno-economic optimization of WEC devices and is difficult to do effectively with causal controls frameworks. MPC requires a future prediction of wave excitation forces, requiring wave prediction on a future time horizon of up to 30 seconds. The future horizon required is highly dependent on the WEC and PTO type available. To our knowledge no-one has been able to implement MPC on a WEC device at sea, due to the fact that phase-resolved wave-prediction is not a capability that has been sufficiently developed to date. The key objectives of this project are focused on developing “industry-ready” wave prediction technology building blocks that can be applied to a wide range of different wave energy conversion topologies. Our collaborative work with device developers has demonstrated that the level of improvement attainable for any particular device is heavily dependent on the device and PTO topology chosen. The range of annual average power capture improvements is on the order of 10% to over 100%. However, the important aspect is that we can get within about 10% of theoretical upper limits even when considering errors in the wave prediction and more importantly, we can optimize performance while respecting various constraints such as motion amplitude or peak structural loads. The combination of improved performance while limiting structural loads has a net effect of reducing the levelized cost of energy from these emerging technologies and allows us to design control laws that meet an economic optimum. Efforts under a previous project on controls has focused on developing a set of wave-prediction algorithms that work by leveraging a network of wave sensing measurement buoys that are equipped with real-time telemetry. The present work is focusing primarily on using X-band radar to measure the wave-field around the WEC to predict the future excitation forces on the structure and combining the measurements of these different sources to create improvements in the wave-prediction accuracy.

16 TIDAL AND WAVE POWER↗
NASA NTRS2012

Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer

A multi-channel electrometer voltmeter that employs self-nulling lock-in detection electronics in conjunction with a mechanical resonator with noncontact voltage sensing electrodes has been developed for space-based measurement of an Internal Electrostatic Discharge Monitor (IESDM). The IESDM is new sensor technology targeted for integration into a Space Environmental Monitor (SEM) subsystem used for the characterization and monitoring of deep dielectric charging on spacecraft. Use of an AC-coupled lock-in amplifier with closed-loop sense-signal nulling via generation of an active guard-driving feedback voltage provides the resolution, accuracy, linearity and stability needed for long-term space-based measurement of the IESDM. This implementation relies on adjusting the feedback voltage to drive the sense current received from the resonator s variable-capacitance-probe voltage transducer to approximately zero, as limited by the signal-to-noise performance of the loop electronics. The magnitude of the sense current is proportional to the difference between the input voltage being measured and the feedback voltage, which matches the input voltage when the sense current is zero. High signal-to-noise-ratio (SNR) is achieved by synchronous detection of the sense signal using the correlated reference signal derived from the oscillator circuit that drives the mechanical resonator. The magnitude of the feedback voltage, while the loop is in a settled state with essentially zero sense current, is an accurate estimate of the input voltage being measured. This technique has many beneficial attributes including immunity to drift, high linearity, high SNR from synchronous detection of a single-frequency carrier selected to avoid potentially noisy 1/f low-frequency spectrum of the signal-chain electronics, and high accuracy provided through the benefits of a driven shield encasing the capacitance- probe transducer and guarded input triaxial lead-in. Measurements obtained from a 2- channel prototype electrometer have demonstrated good accuracy (|error| < 0.2 V) and high stability. Twenty-four-hour tests have been performed with virtually no drift. Additionally, 5,500 repeated one-second measurements of 100 V input were shown to be approximately normally distributed with a standard deviation of 140 mV.

Blaes, Brent R.↗
DOE OSTI2011

Integrated Sensing & Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier & Syngas Cooler. Topical Rerport for Phase III

This Topical Report for the final Phase III of the program summarizes the results from the Task 3 of the program. In this task, the separately designed extended Kalman Filter (EKF) and model predictive controls (MPC) with ideal sensing, developed in Phase II, were integrated to achieve the overall sensing and control system for the gasification section of an IGCC plant. The EKF and MPC algorithms were updated and re-tuned to achieve closed-loop system stability as well as good steady-state and transient control response. In particular, the performance of the integrated EKF and MPC solution was tested extensively through multiple simulation studies to achieve improved steady-state as well as transient performance, with coal as well as coal-petcoke blended fuel, in the presence of unknown modeling errors as well as sensor errors (noise and bias). The simulation studies demonstrated significant improvements in steady state and transient operation performance, similar to that achieved by MPC with ideal sensors in Phase II of the program.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1990

Satellite remote sensing of sea surface temperature

An overview is conducted of the satellite methods available for investigating sea-surface temperature (SST). Attention is given to the accuracies expected from specific satellite instruments and retrieval methods. The techniques reviewed include IR radiometry, corrections for atmospheric attenuation and cloudiness, and the combination of AVHRR and High-resolution IR Sounder channels. The analytical derivations of surface emission (microwave and IR) and radiative transfer are demonstrated, and the theoretically derived SST retrieval algorithms are discussed for both microwave and IR sensors. The accuracies of satellite and in situ SST products are compared with attention given to the use of composite SST products. The AVHRR data are found to be self-consistent and provide the lowest rms errors and bias variations, and the occurrence of satellite anomalies are considered acceptable in the light of in situ data which does not adequately represent the SST field.

Njoku, Eni G.↗
NASA NTRS1991

Studies on distributed sensing and processing for the control of large flexible spacecraft

Technology is being developed to process signals from distributed sensors using distributed computations. These distributed sensors provide a new feedback capability for vibration control that has not been exploited. Additionally, the sensors proposed are of an optical and distributed nature and could be employed with known techniques of distributed optical computation (Fourier optics, etc.) to accomplish the control system functions of filtering and regulation in a distributed computer. This paper reviews a procedure for the analytic design of control systems for this application. For illustration, the procedure is applied to the problem of suppressing the vibrations of a simply supported beam. A simulator has been developed to study the effects of sensor and processing errors. An extensive study of the effects of these errors on estimation and regulation performance is presented.

Montgomery, Raymond C.↗
DOE OSTI2022

Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Temporal Land Cover Analysis for Net Ecosystem Improvement

We delineated 8 watersheds contributing to previously defined river reaches within the 1,468-km2 historical floodplain of the tidally influenced lower Columbia River and estuary. We assessed land-cover change at the watershed, reach, and restoration site scales by reclassifying remote-sensing data from the National Oceanic and Atmospheric Administration Coastal Change Analysis Program’s land cover/land change product into forest, wetland, and urban categories. The analysis showed a 198.3 km2 loss of forest cover during the first 6 years of the Columbia Estuary Ecosystem Restoration Program, 2001–2006. Total measured urbanization in the contributing watersheds of the estuary during the full 1996-2006 change analysis period was 48.4 km2. Trends in forest gain/loss and urbanization differed between watersheds. Wetland gains and losses were within the margin of error of the satellite imagery analysis. No significant land cover change was measured at restoration sites, although it was visible in aerial imagery, therefore, the 30-m land-cover product may not be appropriate for assessment of early-stage wetland restoration. These findings suggest that floodplain restoration sites in reaches downstream of watersheds with decreasing forest cover will be subject to increased sediment loads, and those downstream of urbanization will experience effects of increased impervious surfaces on hydrologic processes.

Ke, Yinghai↗
DOE OSTI2018

Quantifying Tip-Sample Interactions in Vacuum Using Cantilever-Based Sensors: An Analysis

Atomic force microscopy is an analytical characterization method that is able to image a sample’s surface topography at high resolution while simultaneously probing a variety of different sample properties. Such properties include tip-sample interactions, the local measurement of which has gained much popularity in recent years. To this end, either the oscillation frequency or the oscillation amplitude and phase of the vibrating force-sensing cantilever are recorded as a function of tip-sample distance and subsequently converted into quantitative values for the force or interaction potential. Here, we theoretically and experimentally show that the force law obtained from such data acquired under vacuum conditions using the most commonly applied methods may deviate more than previously assumed from the actual interaction when the oscillation amplitude of the probe is of the order of the decay length of the force near the surface, which may result in a non-negligible error if correct absolute values are of importance. Caused by approximations made in the development of the mathematical reconstruction procedures, the related inaccuracies can be effectively suppressed by using oscillation amplitudes sufficiently larger than the decay length. To facilitate efficient data acquisition, we propose a technique that includes modulating the drive amplitude at a constant height from the surface while monitoring the oscillation amplitude and phase. Ultimately, such an amplitude-sweep-based force spectroscopy enables shorter data acquisition times and increased accuracy for quantitative chemical characterization compared to standard approaches that vary the tip-sample distance. An additional advantage is that since no feedback loop is active while executing the amplitude sweep, the force can be consistently recovered deep into the repulsive regime.

36 MATERIALS SCIENCE↗