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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
DOE OSTI2024

Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems

In this article, we introduce an adaptive on-line model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems. Unlike traditional methods that depend on historical data for offline model identification, our approach utilizes real-time data for continuous model updates. This method integrates seamlessly with existing online control and optimization algorithms and provides timely updates in response to real-time changes. This methodology offers significant advantages, including a reduction in the communication network bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt after disturbances. Furthermore, our algorithm is tailored for non-linear convex models, enhancing its applicability to practical scenarios. The efficacy of the proposed method is validated through a numerical study, demonstrating improved control performance using a synthetic IEEE test case.

data-driven model predictive control↗
DOE OSTI2026

Satellite-based Investigation of Power-Line Vegetation Encroachment in the US (SILVANUS)

Rapid wide-area assessments of vegetation encroachment on transmission and distribution line rights-of-way (ROW) is a highly desirable capability for understanding risks to the power grid during severe weather and wildfire events. Conventional assessments are time-consuming and expensive due to the need for in-situ inspections and the use of aerial assets. Performing conventional assessments on a wide area would require immense resources and time that might not be available within the horizon of an expected adverse event. Developing a capability to accurately assess vegetation encroachment into ROWs will enable faster analysis of potential grid vulnerabilities in NAERM. This project sought to develop a prototype capability for rapid ROW vegetation encroachment assessments by using Puerto Rico as a test case. Puerto Rico is a heavily forested island territory frequently impacted by tropical cyclones that threaten the electric grid by downing trees across transmission and distribution lines. Multispectral satellite imagery (MSI) enable very high resolution (i.e., 0.5 - 2 meter) assessment of vegetation conditions at scale and with revisit times appropriate for regular monitoring (e.g., weekly to quarterly, depending on cloud cover) of the entire island. Synthetic aperture radar (SAR) data from satellites was also investigated as solution to the cloud-cover issue as they are active sensors that emit and receive a microwave signal rather than relying on solar illumination, and are therefore unaffected by cloud cover and can collect data during day or night. Finally, MSI-derived digital surface models (DSMs) map the height of objects relative to sea level, and were assessed for their ability to estimate the height of forest canopies relative to coincident transmission lines. The results of the mapping investigation are described in this report.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Efficient geometric rectification techniques for spectral analysis algorithm

The spectral analysis algorithm is a viable technique for processing synthetic aperture radar (SAR) data in near real time throughput rates by trading the image resolution. One major challenge of the spectral analysis algorithm is that the output image, often referred to as the range-Doppler image, is represented in the iso-range and iso-Doppler lines, a curved grid format. This phenomenon is known to be the fanshape effect. Therefore, resampling is required to convert the range-Doppler image into a rectangular grid format before the individual images can be overlaid together to form seamless multi-look strip imagery. An efficient algorithm for geometric rectification of the range-Doppler image is presented. The proposed algorithm, realized in two one-dimensional resampling steps, takes into consideration the fanshape phenomenon of the range-Doppler image as well as the high squint angle and updates of the cross-track and along-track Doppler parameters. No ground reference points are required.

Chang, C. Y.↗
NASA NTRS1982

MAGSAT anomaly field inversion and interpretation for the US

Long wavelength anomalies in the total magnetic field measured by MAGSAT over the United States and adjacent areas are inverted to an equivalent layer crustal magnetization distribution. The model is based on an equal area dipole grid at the Earth's surface. Model resolution, defined as the closest dipole spacing giving a solution having physical significance, is about 220 km for MAGSAT data in the elevation range 300-500 km. The magnetization contours correlate well with large scale tectonic provinces. A higher resolution (200 km) model based on relatively noise free synthetic "pseudodata" is also presented. Magnetic anomaly component data measured by MAGSAT is compared with synthetic anomaly component fields arising from an equivalent source dipole array at the Earth's surface generated from total field anomaly data alone. An excellent inverse correlation between apparent magnetization and heat flow in the western U.S. is demonstrated. A regional heat flow map which is presented and compared with published maps, predicts high heat flow in Nebraska and the Dakotas, suggesting the presence of a "blind" geothermal area of regional extent.

Mayhew, M. A.↗
NASA NTRS2024

Improved Soil Moisture Estimation and Detection of Irrigation Signal By Incorporating SMAP Soil Moisture Into the Indian Land Data Assimilation System (ILDAS)

Land surface models have facilitated the estimation of soil moisture over a range of spatiotemporal scales. However, limitations in model parameterization and under-representation of anthropogenic processes restrict their ability to estimate local-scale soil moisture variability, especially over irrigated areas. Assimilation of satellite-based soil moisture retrievals into land surface models can be a viable approach to overcome these constraints, specially over highly irrigated countries such as India, where such applications are rare. Additionally, large-scale validation of modeled soil moisture has been limited over India till now due to lack of a representative station network. By assimilating Soil Moisture Active Passive (SMAP)-based estimates into the state-of-the-art Indian Land Data Assimilation System (ILDAS) and combining with a new soil moisture station network of more than 200 stations, this study demonstrates improved soil moisture estimations and capture of irrigation signals over the region. The Noah-MP land surface model is forced by multiple local and global meteorological datasets and Ensemble Kalman Filter (EnKF) is used for assimilation of soil moisture. Comparison of open-loop and data assimilated soil moisture against station soil moisture data shows relative spatial mean improvement of 0.0178 in correlation and 0.0029 m3/m3 in RMSE. Further statistical comparison with in-situ data has also shown better results over most of the stations, as evident from improved correlations and reduced unbiased RMSE after assimilation. Finally, the climatology of soil moisture over the different irrigation fractions reveals that data assimilated outputs over irrigated grid cells tend to have higher soil moisture during dry winter season, demonstrating the ability to capture irrigation signals. These findings quantify the value of data assimilation in improving soil moisture estimates and the ability to capture unmodeled processes such as irrigation, which lays the science groundwork for upcoming space missions such as NASA ISRO Synthetic Aperture Radar (NISAR).

Soil Moisture↗
NASA NTRS1997

Biweekly Maps of Wind Stress for the North Pacific from the ERS-1 Scatterometer

The European Remote-sensing Satellite (ERS-1) was launched in July 1991 and contained several instruments for observing the Earth's ocean including a wind scatterometer. The scatterometer measurements were processed by the European Space Agency (ESA) and the Jet Propulsion Laboratory (JPL). JPL reprocessed (Freilich and Dunbar, 1992) the ERS-1 backscatter measurements to produced a 'value added' data set that contained the ESA wind vector as well as a set of up to four ambiguities. These ambiguities were further processed using a maximum-likelihood estimation (MLE) and a median filter to produce a 'selected vector.' This report describes a technique developed to produce time-averaged wind field estimates with their expected errors using only scatterometer wind vectors. The processing described in this report involved extracting regions of interest from the data tapes, checking the quality and creating the wind field estimate. This analysis also includes the derivation of biweekly average wind vectors over the North Pacific Ocean at a resolution of 0.50 x 0.50. This was done with an optimal average algorithm temporally and an over-determined biharmonic spline spatially. There have been other attempts at creating gridded wind files from ERS-1 winds, e.g., kriging techniques (Bentamy et al., 1996) and successive corrections schemes (Tang and Liu, 1996). There are several inherent problems with the ERS-1 scatterometer. Since this is a multidisciplinary mission, the satellite is flown in different orbits optimized for each phase of the mission. The scatterometer also shares several sub-systems with the Synthetic Aperture Radar (SAR) and cannot be operated while the SAR is in operation. The scatterometer is also a single-sided instrument and only measures backscatter along the right side of the satellite. The processing described here generates biweekly wind maps during the wktwo years analysis period regardless of the satellite orbit or missing data.

SYNTHETIC APERTURE RADAR↗
NASA NTRS2009

Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

De Lannoy, Gabrielle J.M.↗
NASA NTRS2004

Simulation of Synthetic Jets in Quiescent Air Using Unsteady Reynolds Averaged Navier-Stokes Equations

We report research experience in applying an Unsteady Reynolds-Averaged Navier-Stokes (URANS) solver for the prediction of time-dependent flows in the presence of an active flow control device. The configuration under consideration is a synthetic jet created by a single diaphragm piezoelectric actuator in quiescent air. Time-averaged and instantaneous data for this case were obtained at Langley Research Center, using multiple measurement techniques. Computational results for this case using one-equation Spalart-Allmaras and two-equation Menter s turbulence models are presented here along with comparisons with the experimental data. The effect of grid refinement, preconditioning and time-step variation are also examined.

Vatsa, Veer N.↗
DOE OSTI2024

Estimation and Visualization of Isosurface Uncertainty from Linear and High-Order Interpolation Methods

Isosurface visualization is fundamental for exploring and analyzing 3D volumetric data. Marching cubes (MC) algorithms with linear interpolation are commonly used for isosurface extraction and visualization. Although linear interpolation is easy to implement, it has limitations when the underlying data is complex and high-order, which is the case for most real-world data. Linear interpolation can output vertices at the wrong location. Its inability to deal with sharp features and features smaller than grid cells can lead to an incorrect isosurface with holes and broken pieces. Despite these limitations, isosurface visualizations typically do not include insight into the spatial location and the magnitude of these errors. We utilize high-order interpolation methods with MC algorithms and interactive visualization to highlight these uncertainties. Our visualization tool helps identify the regions of high interpolation errors. It also allows users to query local areas for details and compare the differences between isosurfaces from different interpolation methods. In addition, we employ high-order methods to identify and reconstruct possible features that linear methods cannot detect. We showcase how our visualization tool helps explore and understand the extracted isosurface errors through synthetic and real-world data.

Ouermi, Timbwaoga↗
NASA NTRSDate not supplied

A Large-Eddy Simulation Of Turbulent Flow Over A Backward Facing Step

Large-eddy simulation (LES) was used to study the turbulent flow over a backward facing step. The simulations examine the details of the turbulent flow’s separated and reattaching regions created by the step geometry. An explicit high-order of accuracy/high resolution finite-difference computational fluid dynamics solver was used for both LES and Reynolds-averaged Navier-Stokes (RANS) simulations. The experimental data from the backward facing step experiment of Driver and Seegmiller was used for comparison. Data presented are derived from a RANS simulation using the Spalart-Allmaras turbulence model and LES simulations using the implicit LES assumption on three different grids of varying resolution. The RANS solution agrees with past work. It does an adequate job of predicting the flowfield and reattachment point, but misses details such as the strength of the recirculating region and magnitudes of the Reynolds stresses. The synthetic eddy method was used to provide a turbulent inflow to the quasi-2D LES domains. For the LES, the coarse grid was of insufficient resolution and under-predicted the skin friction coefficient and over-predicted the normal stresses. The finer grid LES results accurately predict the skin friction coefficient and provide more accurate Reynolds stresses. Triple product velocity correlations are also computed from the LES and the finer grid results did a good job predicting the magnitudes of the curves and the shapes were reasonably represented. It is recommended that future work include investigating the turbulent inflow domain length, width of the quasi-2D domain, and additional grid refinement

turbulence↗
NASA NTRSDate not supplied

A Large-Eddy Simulation Of Turbulent Flow Over A Backward Facing Step

Large-eddy simulation (LES) was used to study the turbulent flow over a backward facing step. The simulations examine the details of the turbulent flow's separated and reattaching regions created by the step geometry. An explicit high-order of accuracy/high resolution finite-difference computational fluid dynamics solver was used for both LES and Reynolds-averaged Navier-Stokes (RANS) simulations. The experimental data from the backward facing step experiment of Driver and Seegmiller was used for comparison. Data presented are derived from a RANS simulation using the Spalart-Allmaras turbulence model and LES simulations using the implict LES assumption on three different grids of varying resolution. The RANS solution agrees with past work. It does an adequate job of predicting the flowfield and reattachment point, but misses details such as the strength of the recirculating region and magnitudes of the Reynolds stresses. The synthetic eddy method was used to provide a turbulent inflow to the quasi-2D LES domains. For the LES, the coarse grid was of insufficient resolution and under-predicted the skin friction coefficient and over-predicted the normal stresses. The finer grid LES results accurately predict the skin friction coefficient and provide more accurate Reynolds stresses. Triple product velocity correlations are also computed from the LES and the finer grid results did a good job predicting the magnitudes of the curves and the shapes were reasonably represented. It is recommended that future work include investigating the turbulent inflow domain length, width of the quasi-2D domain, and additional grid refinement.

turbulence↗
NASA NTRS1994

Sea ice lead dynamics from ERS-1 SAR

The use of ERS-1 SAR (Synthetic Aperture Radar) images to measure ice lead changes and ice deformation, and thus to determine their relationships and compare them to theory, is reported. ERS-1 SAR data collected at the Alaska (U.S.) SAR facility are processed into low resolution geocoded images which are used as input to the Geophysical Processor System (GPS). The GPS uses cross correlation and edge detection on sequential pairs of images to track a regular 5 km array of grid points. The result for each sequential image pair is a field of ice displacement that contains, on average, more than 200 vectors. The GPS also classifies all the pixels of the images into one of four ice types based on the normalized backscatter coefficients and a seasonal look-up table. This allows all pixels to be labeled as either multiyear ice or as the first year ice and open water that comprise leads.

Stern, Harry L.↗
DOE OSTI2025

Analog In-Memory Computing for the Synthetic Aperture Radar Polar Format Algorithm

As the utility of synthetic aperture radar (SAR) systems increases in autonomous vehicles, satellites, and other power- and space-constrained edge applications, there is a growing need for processors that can form SAR images at low power. In recent years, analog in-memory compute (AIMC) has shown immense promise for accelerating neural networks and other matrix-vector multiplication (MVM) heavy workloads at the edge. Here, in this work, we examine how the polar format algorithm (PFA), a popular SAR image formation algorithm, can be mapped to these AIMC systems. The PFA maps readily onto analog MVMs because it primarily consists of two linear operations: interpolation of frequency-domain data to a Cartesian grid, followed by a 2-D Fourier transform. This work presents two approaches to map the interpolation operation onto MVMs in analog hardware: a chirp transform and a modified form of sinc interpolation. These mappings introduce algorithmic errors, and their effect on the quality of SAR image formation is examined, both quantitatively and qualitatively. In addition, the impact of errors introduced by the analog hardware is explored to determine which approach is optimal under varying assumptions about the underlying analog memory devices and circuits.

Analog computing↗
NASA NTRS2006

Simulation of Synthetic Jets in Quiescent Air Using Unsteady Reynolds Averaged Navier-Stokes Equations

We apply an unsteady Reynolds-averaged Navier-Stokes (URANS) solver for the simulation of a synthetic jet created by a single diaphragm piezoelectric actuator in quiescent air. This configuration was designated as Case 1 for the CFDVAL2004 workshop held at Williamsburg, Virginia, in March 2004. Time-averaged and instantaneous data for this case were obtained at NASA Langley Research Center, using multiple measurement techniques. Computational results for this case using one-equation Spalart-Allmaras and two-equation Menter's turbulence models are presented along with the experimental data. The effect of grid refinement, preconditioning and time-step variation are also examined in this paper.

Vatsa, Veer N.↗
NASA NTRS1987

Automated rectification and geocoding of SAR imagery

An automated post-processing system has been developed for rectification and geocoding of SAR (Synthetic Aperture Radar) imagery. The system uses as input a raw uncorrected image from the operational SAR correlator, and produces as a standard output a rectified and geocoded product. The accurate geolocation of SAR image pixels is provided by a spatial transformation model which maps the slant range-azimuth SAR image pixels into their location on a prespecified map grid. This model predicts the geodetic location of each pixel by utilizing: the sensor platform position; a geoid model; the parameters of the data collection system and the processing parameters used in the SAR correlator. Based on their geodetic locations, the pixels are mapped by using the desired cartographic projection equations. This rectification and geocoding technique has been tested with Seasat and SIR-B images. The test results demonstrate absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 percent relative to local variations from the assumed geoid.

Kwok, R.↗
NASA NTRS2003

Modified Polar-Format Software for Processing SAR Data

HMPF is a computer program that implements a modified polar-format algorithm for processing data from spaceborne synthetic-aperture radar (SAR) systems. Unlike prior polar-format processing algorithms, this algorithm is based on the assumption that the radar signal wavefronts are spherical rather than planar. The algorithm provides for resampling of SAR pulse data from slant range to radial distance from the center of a reference sphere that is nominally the local Earth surface. Then, invoking the projection-slice theorem, the resampled pulse data are Fourier-transformed over radial distance, arranged in the wavenumber domain according to the acquisition geometry, resampled to a Cartesian grid, and inverse-Fourier-transformed. The result of this process is the focused SAR image. HMPF, and perhaps other programs that implement variants of the algorithm, may give better accuracy than do prior algorithms for processing strip-map SAR data from high altitudes and may give better phase preservation relative to prior polar-format algorithms for processing spotlight-mode SAR data.

Chen, Curtis↗
NASA NTRS1999

Review of Recent Results in Global MHD Modeling: ISTP Project Scientist for Theory and Ground-Based Observations

Global MHD (magnetohydrodynamic) simulations have shown a remarkable ability to describe the global dynamics of geospace. The limitations of the physical approximations underlying MHD would seem to limit the effectiveness of these codes, since kinetic and hybrid effects should manifest themselves by cross-scale coupling from microscales to mesoscales to global scales. However three effects appear to allow the codes to operate much more successfully than one would at first believe. They are:(l) the globally self-consistent nature of the codes with very well defined exterior boundary conditions (the solar wind) which allows the proper intercommunication between magnetospheric regions on MHD scales, (2) the control by global dynamics of the boundary layer locations where micro and meso scale processes operate, and (3) the critical role of numerical diffusion and with a sufficiently high resolution grid, the use of an empirical resistivity term, which if set at a level where the major magnetosphere boundaries properly calibrate against their observed locations, appear to well represent the effects of kinetic and hybrid processes on the global dynamics. The effectiveness of the global MHD codes, which have been developed under the ISTP mission, in describing Wind, Polar and Geotail observations, as well as ground-based observations are described. Particular emphasis is placed upon the Polar imaging data which when combined with ground-based data and global MHD-based synthetic aurora and convection patterns provide a powerful tool in understanding the final link in the solar-terrestrial chain: coupling into the atmosphere and ionosphere.

Curtis, Steven↗
NASA NTRS2021

The NASA AfriSAR Campaign: Airborne SAR and Lidar Measurements of Tropical Forest Structure and Biomass in Support of Current and Future Space Missions

In 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1 hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform Lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community.

AfriSAR↗