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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

W-Band ARM Scanning Cloud Radar (WSACR) 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross-Polarization Model (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). Beamwidths at Ka and W bands are roughly matched at 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies that are unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the Ka-SACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the W-SACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Electronic Scanning Strategies in Adaptive Electrical Capacitance Volume Tomography: Tradeoffs and Prospects

Electrical Capacitance Volume Tomography (ECVT) has been applied for imaging of multiphase flows found in industrial applications. The ill-posed nature of the image reconstruction problem in ECVT and the consequent low resolution can be alleviated by employing electronic scanning enabled by electrode segmentation and reconfiguration during data acquisition. Here we study electronic scanning strategies that mimic physical rotation and shifting of the sensor along its symmetry axis. First, we study the feasibility of electronic scanning by analyzing the capacitance transducer circuit in SPICE. Then, we simulate electronic scanning using the finite element method for different electrode shapes, for which we compare the image reconstruction results and acquisition time. We find a noticeable improvement in image resolution for the scanning cases over conventional ECVT. Lastly, among the scanning cases, we emphasize a particular electrode shape that provides the best image resolution along with the minimal amount of acquisition time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Safer and optimized vulnerability scanning for operational technology through integrated and automated passive monitoring and active scanning

Vulnerability scanning of embedded sensors and controllers have a history of causing disruption and malfunction within operation technology environments. Traditional information technology vulnerability scanning generally consists of blunt exercising all or a large population of test conditions to understand how equipment responds. Often the large number and varied conditions of the tests are too much for embedded systems to handle. This paper presents a methodology and framework for integrating passive monitoring and active scanning techniques to optimize the type and amount of necessary active communication tests while achieving acceptable levels of device and vulnerability discovery. Bayesian probability and networks are leveraged for inference to drive the automation of the scanning actions to achieve confidence in discovery. Through inference, selecting the optimal active scans with the least risk and highest confidence impact is possible, thereby eliminating unnecessary scans with uncertain effects. Results of experimenting with real power systems and the following probabilities are provided.

Key Management, ICS, SCADA, Authentication↗
DOE OSTI2020

Fast Scanning Probe Microscopy via Machine Learning: Non-Rectangular Scans with Compressed Sensing and Gaussian Process Optimization

Fast scanning probe microscopy enabled via machine learning allows for a broad range of nanoscale, temporally resolved physics to be uncovered. However, such examples for functional imaging are few in number. Here, using piezoresponse force microscopy (PFM) as a model application, a factor of 5.8 reduction in data collection using a combination of sparse spiral scanning with compressive sensing and Gaussian process regression reconstruction is demonstrated. It is found that even extremely sparse spiral scans offer strong reconstructions with less than 6% error for Gaussian process regression reconstructions. Further, the error associated with each reconstructive technique per reconstruction iteration is analyzed, finding the error is similar past ≈15 iterations, while at initial iterations Gaussian process regression outperforms compressive sensing. Finally, this study highlights the capabilities of reconstruction techniques when applied to sparse data, particularly sparse spiral PFM scans, with broad applications in scanning probe and electron microscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Simultaneous scanning near-field optical and X-ray diffraction microscopy for correlative nanoscale structure-property characterization

A multimodal imaging instrument has been developed that integrates scanning near-field optical microscopy with nanofocused synchrotron X-ray diffraction imaging. The instrument allows for the simultaneous nanoscale characterization of electronic/near-field optical properties of materials together with their crystallographic structure, facilitating the investigation of local structure–property relationships. The design, implementation and operating procedures of this instrument are reported. The scientific capabilities are demonstrated in a proof-of-principle study of the insulator–metal phase transition in samarium sulfide (SmS) single crystals induced by applying mechanical pressure via a scanning tip. The multimodal imaging of an in situ tip-written region shows that the near-field optical reflectivity can be correlated with the heterogeneously transformed structure of the near-surface region of the crystal.

insulator–metal transitions↗
DOE OSTI2023

Holistic scan optimization of nacelle-mounted lidars for inflow and wake characterization at the RAAW and AWAKEN field campaigns

In this article, we provide a methodological framework for designing the scanning strategies of nacelle-mounted scanning lidars for wind energy field experiments, and apply it at two major experimental field campaigns. For the Rotor Aerodynamics, Aeroelastics, and Wake project (RAAW), we leverage two scanning lidars on one turbine to characterize the incoming turbulence and the turbine wake. For the American WAKE experimeNt (AWAKEN), we use four scanning lidars on top of four turbines in a large wind power plant to investigate both individual wakes and wind-plant-scale flow features.

17 WIND ENERGY↗
NASA NTRS2021

TLSLEAF: Automatic Leaf Angle Estimates From Single-Scan Terrestrial Laser Scanning

Leaf angle distribution (LAD) in forest canopies affects estimates of leaf area, light interception, and global-scale photosynthesis, but is often simplified to a single theoretical value. Here, we present TLSLeAF (Terrestrial Laser Scanning Leaf Angle Function), an automated open-source method of deriving LADs from terrestrial laser scanning. TLSLeAF produces canopy-scale leaf angle and LADs by relying on gridded laser scanning data. The approach increases processing speed, improves angle estimates, and requires minimal user input. Key features are automation, leaf–wood classification, beta parameter output, and implementation in R to increase accessibility for the ecology community. TLSLeAF precisely estimates leaf angle with minimal distance effects on angular estimates while rapidly producing LADs on a consumer-grade machine. We challenge the popular spherical LAD assumption, showing sensitivity to ecosystem type in plant area index and foliage profile estimates that translate to c. 25% and c. 11% increases in canopy net photosynthesis (c. 25%) and solar-induced chlorophyll fluorescence (c. 11%). TLSLeAF can now be applied to the vast catalog of laser scanning data already available from ecosystems around the globe. The ease of use will enable widespread adoption of the method outside of remote-sensing experts, allowing greater accessibility for addressing ecological hypotheses and large-scale ecosystem modeling efforts.

3D↗
DOE OSTI2025

Advances and Challenges of SCAN and r 2 SCAN Density Functionals in Transition‐Metal Compounds

ABSTRACT Transition‐metal compounds (TMCs) with open‐shell d ‐electrons are characterized by a complex interplay of lattice, charge, orbital, and spin degrees of freedom, giving rise to various fascinating applications. Often exhibiting exotic properties, these compounds are commonly classified as correlated systems due to strong inter‐electronic interactions called Hubbard U . This inherent complexity presents significant challenges to Kohn‐Sham density functional theory (KS‐DFT), the most widely used electronic structure method in condensed matter physics and materials science. While KS‐DFT is, in principle, exact for the ground‐state total energy, its exchange‐correlation energy must be approximated in practice. The mean‐field nature of KS implementations, combined with the limitations of current exchange‐correlation density functional approximations, has led to the perception that DFT is inadequate for correlated systems, particularly TMCs. Consequently, a common workaround involves augmenting DFT with an on‐site Hubbard‐like U correction. In recent years, the strongly constrained and appropriately normed (SCAN) density functional, along with its refined variant r 2 SCAN, has achieved remarkable progress in accurately describing the structural, energetic, electronic, magnetic, and vibrational properties of TMCs, challenging the traditional perception of DFT's limitations. This review explores the design principles of SCAN and r 2 SCAN, highlights their key advancements in studying TMCs, explains the mechanisms driving these improvements, and addresses the remaining challenges in this evolving field.

Zhang, Yubo [Minjiang Collaborative Center for The↗
NASA NTRS1997

PSIDD (2): A Prototype Post-Scan Interactive Data Display System for Detailed Analysis of Ultrasonic Scans

This article presents the description of PSIDD(2), a post-scan interactive data display system for ultrasonic contact scan and single measurement analysis. PSIDD(2) was developed in conjunction with ASTM standards for ultrasonic velocity and attenuation coefficient contact measurements. This system has been upgraded from its original version PSIDD(1) and improvements are described in this article. PSIDD(2) implements a comparison mode where the display of time domain waveforms and ultrasonic properties versus frequency can be shown for up to five scan points on one plot. This allows the rapid contrasting of sample areas exhibiting different ultrasonic properties as initially indicated by the ultrasonic contact scan image. This improvement plus additional features to be described in the article greatly facilitate material microstructural appraisal.

Cao, Wei↗
DOE OSTI2019

Direct Nanoscale Characterization of Deep Levels in AgCuInGaSe 2 Using Electron Energy–Loss Spectroscopy in the Scanning Transmission Electron Microscope

A new experimental framework for the characterization of defects in semiconductors is demonstrated. Through the direct, energy-resolved correlation of three analytical techniques spanning six orders of magnitude in spatial resolution, a critical mid-bandgap electronic trap level (E V + 0.56 eV) within Ag 0.2 Cu 0.8 In 1–x Ga x Se 2 is traced to its nanoscale physical location and chemical source. This is achieved through a stepwise, site-specific correlated characterization workflow consisting of device-scale (≈1 mm 2 ) deep level transient spectroscopy (DLTS) to survey the traps present, scanning probe–based DLTS (scanning-DLTS) for mesoscale-resolved (hundreds of nanometers) mapping of the target trap state’s spatial distribution, and scanning transmission electron microscope based electron energy-loss spectroscopy (STEM-EELS) and X-ray energy-dispersive spectroscopy for nanoscale energy-, structure, and chemical-resolved investigation of the defect source. Furthermore, this first demonstration of the direct observation of sub-bandgap defect levels via STEM-EELS, combined with the DLTS methods, provides strong evidence that the longsuspected Cu In/Ga substitutional defects are indeed the most likely source of the E V + 0.56 eV trap state and serves as a key example of this approach for the fundamental identification of defects within semiconductors, in general.

14 SOLAR ENERGY↗
DOE OSTI2021

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tilted lidar profiling: Development and testing of a novel scanning strategy for inhomogeneous flows

The most common profiling techniques for the atmospheric boundary layer based on a monostatic Doppler wind lidar rely on the assumption of horizontal homogeneity of the flow. This assumption breaks down in the presence of either natural or human-made obstructions that can generate significant flow distortions. The need to deploy ground-based lidars near operating wind turbines for the American WAKE experimeNt (AWAKEN) spurred a search for novel profiling techniques that could avoid the influence of the flow modifications caused by the wind farms. With this goal in mind, two well-established profiling scanning strategies have been retrofitted to scan in a tilted fashion and steer the beams away from the more severely inhomogeneous region of the flow. Results from a field test at the National Renewable Energy Laboratory's 135-m meteorological tower show that the accuracy of the horizontal mean flow reconstruction is insensitive to the tilt of the scan, although higher-order wind statistics are severely deteriorated at extreme tilts mainly due to geometrical error amplification. A numerical study of the AWAKEN domain based on the Weather Research and Forecasting Model and large-eddy simulation are also conducted to test the effectiveness of tilted profiling. It is shown that a threefold reduction of the error on inflow mean wind speed can be achieved for a lidar placed at the base of the turbine using tilted profiling.

17 WIND ENERGY↗