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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fabrication and testing of the transition section between modules of a wakefield accelerator

The fabrication process is presented for a typical transition section located between each cylindrical corrugated waveguide structure comprising the wakefield accelerator module. The transition section includes couplers for extracting the 180 GHz TM 01 accelerating mode and separate couplers for extracting the 190 GHz HE 11 dipole mode, both modes induced by the electron bunch traversing the cylindrical corrugated waveguide structure. Extraction of the high-power accelerating mode reduces the heat load due to the subterahertz wave power dissipation within the corrugated accelerating structure. Extraction of the low-power dipole mode serves the purpose of detecting the electron bunch transverse oscillations within the wakefield accelerator and identifying the onset of beam breakup instability. Comprehensive testing of the fully functional transition section with an electron beam was done at the Accelerator Test Facility in Brookhaven National Laboratory which verified the functionality of the transition section. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Identifying Interaction Location in SuperCDMS Detectors

The Super Cryogenic Dark Matter Search (SuperCDMS) experiment uses silicon and germanium particle detectors operated at temperatures of ∼ 30 mK to search for Weakly Interacting Massive Particles (WIMPs), which are candidate dark matter particles that interact weakly with nuclei in the detectors. In operating these detectors, it is required not only to measure the energy of the interaction between the WIMP and the nuclei, but also to reconstruct where the interaction occurred, as the location can be used to separate background interactions from signal and to correct for variations with the location of the energy response. In this project, we, as a team from the University of Minnesota, aim to address the problem of accurately reconstructing the locations of interactions in the SuperCDMS detectors using machine learning methods. The dataset we provided here includes interactions at thirteen different locations from test data taken at the University of Minnesota. For each interaction, a set of parameters was extracted from the signals from each of the five sensors. These parameters represent information known to be sensitive to interaction location, including the relative timing between pulses in different channels, and features like the pulse shape. The relative amplitudes of the pulses are also relevant but due to instabilities in amplification during the test, this data is not included. The parameters included for each interaction are described in our project document. For more details, feel free to check our Github page: https://fair-umn.github.io/FAIR-UMN-CDMS/

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2013

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

PEEMD↗
DOE OSTI2021

Revealing Nanoscale Confinement Effects on Hyperbolic Phonon Polaritons with an Electron Beam

Hyperbolic phonon polaritons (HPhPs) in hexagonal boron nitride (hBN) enable the direct manipulation of mid-infrared light at nanometer scales, many orders of magnitude below the free-space light wavelength. High-resolution monochromated electron energy-loss spectroscopy (EELS) facilitates measurement of excitations with energies extending into the mid-infrared while maintaining nanoscale spatial resolution, making it ideal for detecting HPhPs. The electron beam is a precise source and probe of HPhPs, which allows the observation of nanoscale confinement in HPhP structures and directly extract hBN polariton dispersions for both modes in the bulk of the flake and modes along the edge. The measurements reveal technologically important nontrivial phenomena, such as localized polaritons induced by environmental heterogeneity, enhanced and suppressed excitation due to 2D interference, and strong modification of high-momenta excitations such as edge-confined polaritons by nanoscale heterogeneity on edge boundaries. Finally, the work opens exciting prospects for the design of real-world optical mid-infrared devices based on hyperbolic polaritons.

2D materials↗
DOE OSTI2024

Ambient-Frequency-Data Based System-Level Inertia Estimation Using Physical Equation and its Practice on Hawaii Islands

Here, in this paper, a practical ambient-frequency-data-based inertia estimation method using a physical equation is proposed and validated by real measurement data from Hawaii island grids. With high renewable penetration, accurate inertia estimation is important and urgent. Ambient frequency oscillation always exists in power grids, so the proposed method has advantages of real-time inertia estimation and no need for additional disturbances. This paper first developed the physical equation for inertia estimation to offer a clear mechanism for easy implementation in practice. To apply the proposed method in actual grids, a practical method to extract the ambient frequency oscillation from frequency measurement is further proposed. The inertia estimation using the physical equation is validated by KIUC simulation data and HECO field data, in which error rates are around 2% and 8%, respectively. Practical inertia estimation is challenging due to the large amounts of resources contributing to the power grid's effective inertia, but the method provided in this paper can offer a novel way for practical inertia estimation, which can help renewable penetration to boost carbon-free grid.

14 SOLAR ENERGY↗
DOE OSTI2024

STFM: Accurate Spatio-Temporal Fusion Model for Weather Forecasting

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Convolutional Neural Network for Transition Modeling Based on Linear Stability Theory

Transition prediction is an important aspect of aerodynamic design because of its impact on skin friction and potential coupling with flow separation characteristics. Traditionally, the modeling of transition has relied on correlation-based empirical formulas based on integral quantities such as the shape factor of the boundary layer. However, in many applications of computational fluid dynamics, the shape factor is not straightforwardly available or not well-defined. We propose using the complete velocity profile along with other quantities (e.g., frequency, Reynolds number) to predict the perturbation amplification factor. While this can be achieved with regression models based on a classical fully connected neural network, such a model can be computationally more demanding. We propose a novel convolutional neural network inspired by the underlying physics as described by the stability equations. Specifically, convolutional layers are first used to extract integral quantities from the velocity profiles, and then fully connected layers are used to map the extracted integral quantities, along with frequency and Reynolds number, to the output (amplification ratio). Numerical tests on classical boundary layers clearly demonstrate the merits of the proposed method. More importantly, we demonstrate that, for Tollmien-Schlichting instabilities in two-dimensional, low-speed boundary layers, the proposed network encodes information in the boundary layer profiles into an integral quantity that is strongly correlated to a well-known, physically defined parameter – the shape factor.

Laminar-turbulent transition↗
DOE OSTI2021

Galvanostatic Intermittent Titration Technique Reinvented: Part I. A Critical Review

The galvanostatic intermittent titration technique (GITT), introduced in 1977 by Weppner and Huggins, provided a readily accessible means to measuring the chemical diffusion coefficient of electrochemical electrode materials. The method continues to be widely used today, but the reported diffusivity values are highly inconsistent, ranging as much as four orders of magnitude for some Li layered oxide compositions. Even qualitative trends of diffusivity are inconsistent, suggesting significant flaws in the implementation of the method. Other variants of the GITT method also suffer from similar inconsistency problems. Here we identify numerous sources of significant error including composition-dependent reaction overpotentials, mathematical flaws in the relaxation analysis methods, finite-size and non-planar geometry effects, inter-particle inhomogeneity issues, early transient effects, and surface area uncertainties. We propose a simple relaxation analysis scheme using the time variable t relax + τ - t relax , where t relax is relaxation time and τ is the galvanostatic pulse duration. We also propose to use dense diffusion-limited samples to isolate the bulk-diffusion process in the time domain. Chemical diffusivity can be extracted much more reliably with this improved implementation of the GITT method.

25 ENERGY STORAGE↗
DOE OSTI2020

Synergistic effect of dual Brønsted acidic deep eutectic solvents for oxidative desulfurization of diesel fuel

Deep eutectic solvents (DESs) are generally used as attractive solvents or extractants rather than catalysts in the field of synthesis and separation. Herein, dual Brønsted acidic DESs were prepared by mixing sulfonated quaternary ammonium and oxalic acid as extractants and catalysts for deep oxidative desulfurization. Compared to the DESs with single acidic group, the dual acidic DESs exhibited much higher catalytic activity likely due to the synergistic effect. The 1 H NMR study indicated that the weak interaction between DES and sulfur compounds led to a low extraction capacity. However, the sulfur removal could reach 97.7% under optimized reaction conditions. Density functional theory (DFT) calculations demonstrated that sulfonic group and carboxylic group are of equal importance to desulfurization performance. Further, the desulfurization efficiency was also strongly affected by the viscosity of DESs. Here, we put forward a new strategy that the reaction time could be sharply shortened to 40 min and 100 min by adding low viscous acetonitrile and polyethylene glycol into DES to form mixing reaction system, respectively.

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

Manufacturing Oxide Dispersion Strengthened (ODS) steel plate via cold spray and friction stir processing

Oxide dispersion strengthened (ODS) steels, traditionally fabricated by ball milling and conventional powder metallurgy techniques to achieve bulk form, followed by intricate rolling and thermal treatment steps to achieve plate or sheet form. Here, we present a novel processing route that combines cold spray (CS) with friction stir processing (FSP) to manufacture ODS steel plate directly from gas atomization reaction synthesis (GARS)-prepared powder, thus no rolling steps involved. Microstructural and mechanical characterizations were performed to assess the quality and properties of the resulting ODS steel plate. Our findings demonstrate that the slightly porous CS deposited layer was fully consolidated after FSP, yielding a fully dense ODS steel plate that exhibited a favorable tradeoff between strength and ductility upon extraction from the substrate. Furthermore, through microstructural analysis, we revealed the presence of an appreciable density (∼10 22 /m 3 ) of nano-sized oxide particles, with the majority being smaller than 5 nm via the combined CS + FSP fabrication route. This work serves as a first proof-of-concept demonstration of the manufacturing approach described herein, offering a possible alternative route for producing ODS steel plates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. Furthermore, the proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2001

A Novel Approach for Reducing Rotor Tip-Clearance Induced Noise in Turbofan Engines

Rotor tip-clearance induced noise, both in the form of rotor self noise and rotor-stator interaction noise , constitutes a significant component of total fan noise. Innovative yet cost effective techniques to suppress rotor-generated noise are, therefore, of foremost importance for improving the noise signature of turbofan engines. To that end, the feasibility of a passive porous treatment strategy to positively modify the tip-clearance flow field is addressed. The present study is focused on accurate viscous flow calculations of the baseline and the treated rotor flow fields. Detailed comparison between the computed baseline solution and experimental measurements shows excellent agreement. Tip-vortex structure, trajectory, strength, and other relevant aerodynamic quantities are extracted from the computed database. Extensive comparison between the untreated and treated tip-clearance flow fields is performed. The effectiveness of the porous treatment for altering the rotor-tip vortex flow field in general and reducing the intensity of the tip vortex, in particular, is demonstrated. In addition, the simulated flow field for the treated tip clearly shows that substantial reduction in the intensity of both the shear layer roll-up and boundary layer separation on the wall is achieved.

Khorrami, Mehdi R.↗
DOE OSTI2023

Metal Sulfide Ion Exchangers: High Acid Stability of Na 2 x Mg 2 y – x Sn 4– y S 8 (NMS) and Topotactic Conversion to 2D Solid Acids with Semiconducting Character

Metal sulfide ion exchange materials (MSIEs) are of interest for nuclear waste remediation applications. Here, we report the high stability of two structurally related metal sulfide ion exchange materials, Na 2x Mg 2y–x Sn 4–y S 8 (Mg-NMS) and Na 2 SnS 3 (Na-NMS), in strongly acid media, in addition to the preparation of Na 2x Ni 2y–x Sn 4–y S 8 (Ni-NMS). Their formation progress during synthesis is studied with in-situ methods, with the target phases appearing in <15 min, reaction completion in <12 h, and high yields (75–80%). Upon contact with nitric or hydrochloric acid, these materials topotactically exchange Na + for H + , proceeding in a stepwise protonation pathway for Na 5.33 Sn 2.67 S 8 . Na-NMS is stable in 2 M HNO 3 and Mg-NMS is stable in 4 M HNO 3 for up to 4 h, while both NMS materials are stable in 6 M HCl for up to 4 days. However, the treatment of Mg-NMS and Na-NMS with 2–6 M H 2 SO 4 reveals a much slower protonation process since after 4 h of contact both NMS and HMS are present in the solution. The resultant protonated materials, H 2x Mg 2y–x Sn 4–y S 8 and H 4x [(H y Na y–1 ) 1.33x Sn 4––1.33x ]S 8 , are themselves solid acids and readily react with and intercalate a variety of organic amines, where the band gap of the resultant adduct is influenced by amine choice and can be tuned within the range of 1.88(5)–2.27(5) eV. The work function energy values for all materials were extracted from photoemission yield spectroscopy in air (PYSA) measurements and range from 5.47 (2) to 5.76 (2) eV, and the relative band alignments of the materials are discussed. DFT calculations suggest that the electronic structure of Na 2 MgSn 3 S 8 and H 2 MgSn 3 S 8 makes them indirect gap semiconductors with multi-valley band edges, with carriers confined to the [MgSn 3 S 8 ] 2– layers. Light electron effective masses indicate high electron mobilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A highly efficient uranium grabber derived from acrylic fiber for extracting uranium from seawater

Acrylic fiber can be chemically converted to an am- idoxime and carboxylate containing chelating adsorbent for extraction of uranium from seawater. At an optimized ratio of amidoxime:carboxylate, the chelating fiber in real seawater shows a higher uranium, shorter saturation time and lower vanadium adsorption capacity relative to similar high-surface area chelating fibers developed recently using a radiation-induced grafting method. This simple and low-cost synthesis method can be scaled up to mass produce the chelating fiber for recovering metals from aquatic environments including production of uranium from seawater.

Pan, H B.↗
NASA NTRS1995

Characterizing SOI Wafers By Use Of AOTF-PHI

Developmental nondestructive method of characterizing layers of silicon-on-insulator (SOI) wafer involves combination of polarimetric hyperspectral imaging by use of acousto-optical tunable filters (AOTF-PHI) and computational resources for extracting pertinent data on SOI wafers from polarimetric hyperspectral images. Offers high spectral resolution and both ease and rapidity of optical-wavelength tuning. Further efforts to implement all of processing of polarimetric spectral image data in special-purpose hardware for sake of procesing speed. Enables characterization of SOI wafers in real time for online monitoring and adjustment of production. Also accelerates application of AOTF-PHI to other applications in which need for high-resolution spectral imaging, both with and without polarimetry.

Cheng, Li-Jen↗
NASA NTRS2005

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Li, Winston↗
DOE OSTI2022

A Mixed PC 61 BM‐CO i 8DFIC Based Electron Transport Material for Inverted High‐performance Perovskite Solar Cells

Abstract This study reports a blend of [6, 6]‐phenyl‐C61‐butyric acid methyl ester (PC 61 BM) and CO i 8DFIC non‐fullerene acceptor (NFA) as an electron transport layer (ETL) in perovskite solar cells (PSCs). This mixed small‐molecule ETL showed good inter‐molecule mixing, reduced intermolecular distances and decent morphology, resulting in excellent charge carrier transport properties. Morever, charge carrier extraction and transport at the perovskite/ETL interface was optimized by reducing surface traps and defects due to the passivation ability of various terminal groups from the CO i 8DFIC molecule. A high power conversion efficiency (PCE) of 19.12 % was achieved by taking advantage of benefits from both molecules, showing much better performance than the invidual PC 61 BM or CO i 8DFIC (7.13% for using the NFA only). Moreover, the storage and ambient stabilities of the mixed ETL‐based PSCs increased dramatically compared to control devices.

Chemistry↗
DOE OSTI2024

Integrating the full four-loop negative geometries and all-loop ladder-type negative geometries in ABJM theory

The decomposition of the four-point ABJM amplituhedron into negative geometries produces compact integrands of logarithmic of amplitudes such that the infrared divergence only comes from the last loop integration, from which we can compute the cusp anomalous dimension of the ABJM theory. In this note, we integrate L – 1 loop momenta of the L-loop negative geometries for all four-loop negative geometries and a special class of all-loop ladder-type negative geometries by a method based on Mellin transformation, and from these finite quantities we extract the corresponding contribution to the cusp anomalous dimension. We find that the infrared divergence of a box-type negative geometry at L = 4 is weaker than other negative geometries, then only tree-type negative geometries contribute to the cusp anomalous dimension at L = 4. For the all-loop ladder-type negative geometries, we prove and conjecture some recursive structures as integral equations in Mellin space and find that they cannot contribute zeta values like ζ 3 , ζ 5 to the cusp anomalous dimension.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗