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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Resolution requirements for high-speed droplet impact along a rigid wall

The mechanical and thermal loads that are produced on high-speed projectiles from a droplet are key in the projectile development.To accurately predict the pressure produced along the wall surface during impact, it is important to correctly model the air/water interface of the droplet. Novel modeling approaches such as the Phase-Field enable control of the (numerical) interface thickness. However, the interplay between the grid resolution (including potential adaptive mesh refinement) and the interface thickness is unclear. In this work, the resolution requirements for numerical simulations of a two-dimensional cylindrical water droplet impacting a rigid wall at Mach four are computationally investigated. Numerical simulations are performed using a second-order accurate scheme with adaptive mesh refinement and a Phase-Field interface model. The choice of numerical interface thickness and resolution parameters affects the maximum pressure and location of the maximum pressure along the wall. The overall maximum pressure does not converge even at high resolutions. The number of levels and thickness (number of cells across the interface) play a role in obtaining a well behaved solution.

Burrell, E.↗
DOE OSTI2025

SHF: Symmetrical Hierarchical Forest with Pretrained Vision Transformer Encoder for High-Resolution Medical Segmentation

This paper presents a novel approach to addressing the long-sequence problem in high-resolution medical images for Vision Transformers (ViTs). Using smaller patches as tokens can enhance ViT performance, but quadratically increases computation and memory requirements. Therefore, the common practice for applying ViTs to high-resolution images is either to: (a) employ complex sub-quadratic attention schemes or (b) use large to medium-sized patches and rely on additional mechanisms within the model to capture the spatial hierarchy of details. We propose Symmetrical Hierarchical Forest (SHF), a lightweight approach that adaptively patches the input image to increase token information density and encode hierarchical spatial structures into the input embedding. We then apply a reverse depatching scheme to the output embeddings of the transformer encoder, eliminating the need for convolution-based decoders. Unlike previous methods that modify attention mechanisms or use a complex hierarchy of interacting models, SHF can be retrofitted to any ViT model to allow it to learn the hierarchical structure of details in high-resolution images without requiring architectural changes. Experimental results demonstrate significant gains in computational efficiency and performance: on the PAIP WSI dataset, we achieved a 3∼32×speedup or a 2.95%∼7.03% increase in accuracy (measured by Dice score) at a 64K2 resolution with the same computational budget, compared to state-of-the-art production models. On the 3D medical datasets BTCV and KiTS, training was 6×faster, with accuracy gains of 6.93% and 5.9%, respectively, compared to models without SHF.

Zhang, Enzhi [Hokkaido University, Japan]↗
DOE OSTI2017

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Intrinsic energy and time resolution of the Jefferson Lab Hall C Neutral Particle Spectrometer

The Neutral Particle Spectrometer (NPS) is an advanced calorimeter designed to measure neutral electro- magnetic particles with high precision in energy, time, and position, under conditions of high luminosity and significant background. Integrated into the experimental setup of Hall C at Thomas Jefferson National Accelerator Facility, the NPS plays a critical role in studies of nucleon structure through exclusive and semi- inclusive reaction channels. Here, this paper presents an assessment of the detector’s performance characteristics, specifically its energy and timing resolution, derived from elastic electron–proton scattering data. We report an energy resolution between 1.2% and 1.3% in the 4.5–7.3 GeV range, and an intrinsic timing resolution better than 200 ps for energies above 500 MeV. These results serve as a reference for current and future precision measurements in hadronic physics.

Detector performance↗
DOE OSTI2015

Analysis of high-resolution spectra from a hybrid interferometric/dispersive spectrometer

To fully take advantage of a low-cost, small footprint hybrid interferometric/dispersive spectrometer, a math- ematical reconstruction technique was developed to accurately capture the high-resolution and relative peak intensities from complex patterns. A Fabry-Perot etalon was coupled to a Czerny-Turner spectrometer, in- creasing spectral resolution by an order of magnitude without the commensurate increase in spectrometer size. Measurement of the industry standard Hg 313.1555/313.1844 nm doublet yielded a ratio of 0.682 with 1.8%error, which agreed well with an independent measurement and literature values. The doublet separation (29 pm), is similar to the U isotope shift (25 pm) at 424.437 nm that is of interest to monitoring nuclear nonpro-liferation activities. Additionally, the technique was applied to a LIBS measurement of the mineral cinnabar (HgS) and resulted in a ratio of 0.681. In addition, this reconstruction method could enable significantly smaller, portable high-resolution instruments with isotopic specificity, benefiting a variety of spectroscopic applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Global Dust Cycle and Direct Radiative Effect in E3SM Version 1: Impact of Increasing Model Resolution

Quantification of dust aerosols in Earth System Models (ESMs) has important implications for water cycle and biogeochemistry studies. This study examines the global life cycle and direct radiative effects (DREs) of dust in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1), and the impact of increasing model resolution both horizontally and vertically. The default 1° E3SMv1 captures the spatial and temporal variability in the observed dust aerosol optical depth (DAOD) reasonably well, but overpredicts dust absorption in the shortwave (SW). Simulations underestimate the dust vertical and long-range transport, compared with the satellite dust extinction profiles. After updating dust refractive indices and correcting for a bias in partitioning size-segregated emissions, both SW cooling and longwave (LW) warming of dust simulated by E3SMv1 are increased and agree better with other recent studies. The estimated net dust DRE of –0.42 Wm –2 represents a stronger cooling effect than the observationally based estimate –0.2 Wm –2 (–0.48 to +0.2), due to a smaller LW warming. Constrained by a global mean DAOD, model sensitivity studies of increasing horizontal and vertical resolution show strong influences on the simulated global dust burden and lifetime primarily through the change of dust dry deposition rate; there are also remarkable differences in simulated spatial distributions of DAOD, DRE, and deposition fluxes. Thus, constraining the global DAOD is insufficient for accurate representation of dust climate effects, especially in transitioning to higher- or variable-resolution ESMs. Better observational constraints of dust vertical profiles, dry deposition, size, and LW properties are needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Operating organic light-emitting diodes imaged by super-resolution spectroscopy

Super-resolution stimulated emission depletion microscopy is adapted here for materials characterization that would not otherwise be possible. With the example of organic lightemitting diodes (OLEDs), spectral imaging with pixel-by-pixel wavelength discrimination allows us to resolve local-chain environment encoded in the spectral response of the semiconducting polymer, and correlate chain packing with local electroluminescence by using externally applied current as the excitation source. We observe nanoscopic defects that would be unresolvable by traditional microscopy. They are revealed in electroluminescence maps in operating OLEDs with 50 nm spatial resolution. We find that brightest emission comes from regions with more densely packed chains. Conventional microscopy of an operating OLED would lack the resolution needed to discriminate these features, while traditional methods to resolve nanoscale features generally cannot be performed when the device is operating. Furthermore, this points the way towards real-time analysis of materials design principles in devices as they actually operate.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗
DOE OSTI2013

Rapid high-resolution spin- and angle-resolved photoemission spectroscopy with pulsed laser source and time-of-flight spectrometer

A high-efficiency spin- and angle-resolved photoemission spectroscopy (spin-ARPES) spectrometer is coupled with a laboratory-based laser for rapid high-resolution measurements. The spectrometer combines time-of-flight (TOF) energy measurements with low-energy exchange scattering spin polarimetry for high detection efficiencies. Samples are irradiated with fourth harmonic photons generated from a cavity-dumped Ti:sapphire laser that provides high photon flux in a narrow bandwidth, with a pulse timing structure ideally matched to the needs of the TOF spectrometer. The overall efficiency of the combined system results in near-E{sub F} spin-resolved ARPES measurements with an unprecedented combination of energy resolution and acquisition speed. This allows high-resolution spin measurements with a large number of data points spanning multiple dimensions of interest (energy, momentum, photon polarization, etc.) and thus enables experiments not otherwise possible. The system is demonstrated with spin-resolved energy and momentum mapping of the L-gap Au(111) surface states, a prototypical Rashba system. The successful integration of the spectrometer with the pulsed laser system demonstrates its potential for simultaneous spin- and time-resolved ARPES with pump-probe based measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A method for coincidence timing resolution enhancement

A method including the coincidence time resolution improvement for a TOF/positron emission tomography system was suggested. The spectrometer for this aim was composed of two NaI(Tl) and two plastic scintillation detectors. Experimental results were supported by FLUKA Monte Carlo simulation program by constructing the detector setup in software medium. Present experimental results verified our previous results and conclusions obtained from the suggested method. It was concluded that better resolutions would help the improvement not only on the TOF gain but also on the spatial resolution, leading to better images and helping the Physician in his/her diagnosis and treatment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Super‐Resolution Lifetime Imaging of Single Molecules Near Gold Bowtie Nanoparticles

Interactions between light and matter serve as the basis of many technologies, but the quality of these devices is inherently limited by the optical properties of their constituents. Plasmonic nanoparticles are a highly versatile and tunable platform for the enhancement of such optical properties. However, the near-field nature of these effects has made thorough study and understanding of these mechanisms difficult. In this work, we introduce a fully confocal technique combining photoswitching super-resolution microscopy with fluorescence lifetime imaging microscopy to study single-molecule decay rate enhancement. We demonstrate that the technique combines a spatial resolution better than 20 nm, and a 16 ps temporal resolution. Simultaneously, an autocorrelation measurement is also performed to confirm that the data indeed originates from single molecules. This work provides insight into the various mechanisms of plasmon-enhanced emission, and allows the study of the correlation between emission intensity and lifetime enhancement. This complicated relationship is shown to be dependent upon the relative influence of various radiative and nonradiative decay pathways. Here, we provide a platform for further study of emission mislocalization, the position-dependent prominence of different decay pathways, and the direct super-resolved measurement of the local density of states.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Photoactivatable BODIPY Probe for Localization-based Super-Resolution Cellular Imaging

Here, the synthesis and application of a photoactivatable boron–alkylated BODIPY probe for localization–based super–resolution microscopy is reported. Photoactivation and excitation of the probe is achieved by a previously–unknown boron–photodealkylation reaction with a single low–power visible laser and without requiring the addition of reducing agents or oxygen scavengers in the imaging buffer. These features lead to a versatile probe for localization–based microscopy of biological systems. The probe can be easily linked to nucleophile–containing molecules to target specific cellular organelles. By attaching paclitaxel to the photoactivatable BODIPY, in vitro and in vivo super–resolution imaging of microtubules is demonstrated. This is the first example of single molecule localization–based super–resolution microscopy using a visible–light activated BODIPY compound as a fluorescent probe.

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

Sampling and resolution characteristics in reduced order models of shallow water equations: Intrusive vs nonintrusive

We investigate the sensitivity of reduced order models (ROMs) to training data spatial resolution as well as sampling rate. In particular, we consider proper orthogonal decomposition (POD), coupled with Galerkin projection (POD-GP), as an intrusive reduced order modeling technique. For non-intrusive ROMs, we consider two frameworks. The first is using dynamic mode decomposition (DMD), and the second is based on artificial neural networks (ANNs). For ANN, we utilized a residual deep neural network, and for DMD we have studied two versions of DMD approaches; one with hard thresholding and the other with sorted bases selection. Also, we highlight the differences between mean-subtracting the data (centering) and using the data without mean-subtraction. We tested these ROMs using a system of 2D shallow water equations for four different numerical experiments, adopting combinations of sampling rates and spatial resolutions. For these cases, we found that the DMD basis obtained with hard threshodling is sensitive to sampling rate. The sorted DMD algorithm helps to mitigate this problem and yields more stabilized and converging solution. Furthermore, we demonstrate that both DMD approaches without mean subtraction provide significantly more accurate results than DMD with mean-subtracting the data. On the other hand, POD is relatively insensitive to sampling rate and yields better representation of the flow field. Meanwhile, spatial resolution has little effect on both POD and DMD performances. Here, the numerical results reveal that an ANN on POD subspace (POD-ANN) performs remarkably better than POD-GP and DMD in capturing system dynamics, even with a small number of modes.

42 ENGINEERING↗
DOE OSTI2021

Projecting climate change in South America using variable‐resolution Community Earth System Model: An application to Chile

Abstract We introduce variable‐resolution enabled Community Earth System Model (VR‐CESM) results simulating historical and future climate conditions at 28 km over South America and 14 km over the Andes. Three 30‐year simulations are performed: a historic (1985–2014), a near future (2030–2059), and an end‐century (2070–2099) simulation under the RCP8.5 scenario. Historic results compare favourably to several temperature and precipitation reanalysis products, though local biases are present, particularly during austral summer. Future simulations highlight broad warming patterns (+3–6°C by end‐century) and heterogeneous precipitation responses across South America that qualitatively agree with prior modelling efforts. Our results reveal that the interaction between temperature and precipitation changes produce shifts in several Köppen–Geiger climates. Notable changes include the near‐elimination of the Andean Tundra or Alpine climates, a 15% decrease in Tropical Rainforests and a Tropical Savannah expansion of 20%. To provide a regionally focused analysis of projected climate change and to illustrate the benefits of variable resolution modelling, we analyse changes in the magnitude and trend in seasonal and daily temperature and precipitation in Chile. We also examined several metrics [e.g., snow water equivalent (SWE), temperatures on wet days, and days below 0°C] to evaluate potential impacts of climate change on the Chilean cryosphere between the end‐of‐century and historic periods, finding wide‐ranging indications of cryospheric decline. These changes are interpreted through reductions in the timing (1–2.5 months earlier peak SWE) and magnitude (200–1,000 mm SWE decreases) of water stored as snow in the Andes, a 10–30% decrease in number of cool season wet days with temperatures below 1°C, and 50–200 fewer days (annually) with minimum temperatures below 0°C. Our aim in producing a high‐resolution dataset of climate projections from VR‐CESM is to support analyses of climate change throughout South America but especially in vulnerable montane regions and to provide additional results for comparison with previous, ongoing, and upcoming modelling efforts.

variable-resolution global climate models↗
DOE OSTI2022

Advantages of a variable‐resolution global climate model in reproducing the seasonal evolution of East Asian summer monsoon

Abstract The East Asian summer monsoon (EASM) is unique among monsoon systems that it features meridional evolution of the summer monsoon. In this study, we evaluate the performances of a Variable‐Resolution Community Earth System Model (VR‐CESM) regionally refined over eastern China (14 km) in reproducing the seasonal evolution of EASM precipitation over China. Compared with reference datasets, VR‐CESM shows better performance than the corresponding globally uniform coarse‐resolution model CESM (quasi‐uniform 1°), especially over western China where complex local topography exists. The northward monsoon migration is closely related to low‐level southerly flows and vertical moisture advection, which are more reasonably simulated in VR‐CESM. The four critical timings of the EASM (monsoon onset, withdrawal, peak, and duration) are also better captured in VR‐CESM than in CESM. The corresponding spatial Pearson correlation coefficients of the four critical timings with respect to reference datasets are about 0.1 higher in VR‐CESM than those in CESM. Both models are most accurate in simulating monsoon onset and least accurate at simulating the monsoon peak. The overestimated zonal thermal contrast in CESM is responsible for the earlier monsoon onset and excessive precipitation in September over the Yangtze River valley. Finer resolution in VR‐CESM, especially over the Tibetan Plateau (TP), appears to be a main factor in simulating better zonal thermal contrast and seasonal evolution of the EASM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Broadband surface-enhanced coherent anti-Stokes Raman spectroscopy with high spectral resolution

Both the surface-enhanced Raman spectroscopy (SERS) and coherent anti-Stokes Raman spectroscopy (CARS) are widely used methods in the bio-sensing field for improving the intensity of Raman scattering process. By combining the mechanisms of CARS (coherence and nonlinear process) and SERS (plasmon resonance), a multiplicative enhancement can be achieved through surface-enhanced CARS (SECARS). Besides sensitivity, high specificity with wide spectral bandwidth is also preferred for bio-sensing techniques but not well developed in SECARS setups reported in the literature. A broadband SECARS setup with high sensitivity and high spectral resolution is presented. Rhodamine 6G dye molecules and several biomolecules are used as the model system to benchmark the functionality of the SECARS system in terms of its sensitivity, the lowest detectable concentration, and the spectral resolution. Our setup rendered single-molecule sensitivity with spectral resolution of <35 cm -1 . More than 10 2 times stronger signal-to-noise ratio compared with that of SERS is observed with the detection limit being 10 -9 m. Different from the SECARS systems in the literature, our setup employs a unique graphene-Au pyramids hybrid platform. The graphene in this structure provides additional SERS enhancement and a bio-compatible surface. Finally, this powerful technique could be instrumental in furthering the understanding of various chemical and biological processes.

42 ENGINEERING↗
DOE OSTI2020

High Resolution Data Analysis: Plans and Prospects [Book Chapter]

Herein, a report on the progress on the high resolution data analysis of the ADMX experimental results is presented. In this paper, tools are developed and tested on a blind injection mimicking a Maxwellian like signal in the frequency domain. This blind injection will be used as a test bed which can be later implemented on all the high resolution data. The high resolution data is stored in the Fermilab server. In this analysis a PostgreSQL query was made to ensure the blind injection is in the middle of the frequency spectrum and 19 such files were found. The time series data is read using a c++ program. An apodization function is applied on the time series data and zero filled to reduce the frequency spacing in order to achieve a better interpolation. A FFTW header is used to compute the Fourier transform of the time series data. A Savitzky–Golay filter is applied on the unnormalized power which then can be used to remove the spectral shape. Each frequency spectrum has a bandwidth of 50 kHz.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Finding Hidden Patterns in High Resolution Wind Flow Model Simulations

Wind flow data is critical in terms of investment decisions and policy making. High resolution data from wind flow model simulations serve as a supplement to the limited resource of original wind flow data collection. Given the large size of data, finding hidden patterns in wind flow model simulations are critical for reducing the dimensionality of the analysis. In this work, we first perform dimension reduction with two autoencoder models: the CNN-based autoencoder (CNN-AE) [1], and hierarchical autoencoder (HIER-AE) [2], and compare their performance with the Principal Component Analysis (PCA). We then investigate the super-resolution of the wind flow data. By training a Generative Adversarial Network (GAN) with 300 epochs, we obtained a trained model with 2× resolution enhancement. We compare the results of GAN with Convolutional Neural Network (CNN), and GAN results show finer structure as expected in the data field images. Also, the kinetic energy spectra comparisons show that GAN outperforms CNN in terms of reproducing the physical properties for high wavenumbers and is critical for analysis where high-wavenumber kinetics play an important role.

97 MATHEMATICS AND COMPUTING↗