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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗
DOE OSTI2015

Method to measure orientation of discontinuous fiber embedded in the polymer matrix from computerized tomography scan data

Usage of discontinuous glass fibers in injection and compression molded resin components is rapidly increasing to improve their mechanical properties. Since added fiber contributes to more strength along the fiber direction compared to transverse direction, the mechanical properties of such components strongly depend on the fiber orientation. Thus it is important to estimate the fiber orientation distribution in such materials. Here, we are presenting recently developed method to estimate fiber orientation from 3D image of fibers generated using micro CT scan. Typically the 3D images from CT scan are very large and it becomes difficult to separate each fiber and extract end point information. In this paper a novel method to address this challenge is presented. The micro-CT images were broken into finite volume, reducing data size, and then each fiber was reduced to its own center line, further reducing the data size, using Mimics Innovation Suite (Materialise NV). These 3D centerlines were then used to quantify the 2nd order orientation tensor. Our results from the proposed method are compared with the measurements using well established industry standard approach called method of ellipses for validation. The key challenges in estimating the fiber orientation are identified and future improvements are proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Directed plant cell-wall accumulation of iron: Embedding co-catalyst for efficient biomass conversion

Plant lignocellulosic biomass is an abundant, renewable feedstock for the production of biobased fuels and chemicals. Previously, we showed that iron can act as a co-catalyst to improve the deconstruction of lignocellulosic biomass. However, directly adding iron catalysts into biomass prior to pretreatment is diffusion limited, and increases the cost of biorefinery operations. Recently, we developed a new strategy for expressing iron-storage protein ferritin intracellularly to accumulate iron as a catalyst for the downstream deconstruction of lignocellulosic biomass. In this study, we extend this approach by fusing the heterologous ferritin gene with a signal peptide for secretion into Arabidopsis cell walls (referred to here as FerEX). The transgenic Arabidopsis plants. FerEX. accumulated iron under both normal and iron-fertilized growth conditions; under the latter (iron-fertilized) condition, FerEX transgenic plants showed an increase in plant height and dry weight by 12 and 18 %, respectively, compared with the empty vector control plants. The SDS- and native-PAGE separation of cell-wall protein extracts followed by Western blot analyses confirmed the extracellular expression of ferritin in FerEX plants. Meanwhile, Perls' Prussian blue staining and X-ray fluorescence microscopy (XFM) maps revealed iron depositions in both the secondary and compound middle lamellae cell-wall layers, as well as in some of the corner compound middle lamella in FerEX. Remarkably, their harvested biomasses showed enhanced pretreatability and digestibility, releasing, respectively, 21 % more glucose and 34 % more xylose than the empty vector control plants. These values are significantly higher than those of our recently obtained ferritin intracellularly expressed plants. This study demonstrated that extracellular expression of ferritin in Arabidopsis can produce plants with increased growth and iron accumulation, and reduced thermal and enzymatic recalcitrance. Here, the results are attributed to the intimate colocation of the iron co-catalyst and the cellulose and hemicellulose within the plant cell-wall region, supporting the genetic modification strategy for incorporating conversion catalysts into energy crops prior to harvesting or processing at the biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2012

Spectral response of nanocrystalline ZnO films embedded with Au nanoparticles

The optical response of a two-phase composite consisting of Au nanoparticles (AuNPs) in a nanocrystalline ZnO thin film matrix has been systematically studied and analyzed by the Bergman–Milton spectral density formalism. The real and imaginary parts of the effective dielectric function exhibited anomalous dispersion and absorption, respectively, at the characteristic localized surface plasmon resonance (LSPR) wavelength. A multilayer structure consisting of two AuNP–ZnO composite films separated by a thin ZnO film displayed a twofold increase in the absorption at LSPR (with negligible change in FWHM), which is attributed to the increase in the number density of the AuNPs resulting from the nanocrystalline nature of the ZnO film. The results have been used to correlate the spectral density function to the morphology of AuNPs in a ZnO matrix.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Transient Spectroscopy of Glass-Embedded Perovskite Quantum Dots: Novel Structures in an Old Wrapping

Semiconductor doped glasses had been used by the research and engineering communities as color filters or saturable absorbers well before it was realized that their optical properties were defined by tiny specs of semiconductor matter known presently as quantum dots (QDs). Nowadays, the preferred type of QD samples are colloidal particles typically fabricated via organometallic chemical routines that allow for exquisite control of QD morphology, composition and surface properties. However, there is still a number of applications that would benefit from the availability of high-quality glass-based QD samples. These prospective applications include fiber optics, optically pumped lasers and amplifiers and luminescent solar concentrators (LSCs). In addition to being perfect optical materials, glass matrices could help enhance stability of QDs by isolating them from the environment and improving heat exchange with the outside medium. We conduct optical studies of a new type of all-inorganic CsPbBr 3 perovskite QDs fabricated directly in glasses by high-temperature precipitation. These samples are virtually scattering free and exhibit excellent waveguiding properties which makes them well suited for applications in, for example, fiber optics and LSCs. However, the presently existing problem is their fairly low room-temperature emission quantum yields of only ca. 1%–2%. Here we investigate the reasons underlying the limited emissivity of these samples by conducting transient photoluminescence (PL) and absorption measurements across a range of temperatures from 20 to 300K. We observe that the low-temperature PL quantum yield of these samples can be as high as ~25%. However, it quickly drops (in a nearly linear fashion) with increasing temperature. Interestingly, contrary to traditional thermal quenching models, experimental observations cannot be explained in terms of a thermally activated nonradiative rate but rather suggest the existence of two distinct QD sub-ensembles of “emissive” and completely “nonemissive” particles. The temperature-induced variation in the PL efficiency is likely due to a structural transformation of the QD surfaces or interior leading to formation of extremely fast trapping sites or nonemissive phases resulting in conversion of emissive QDs into nonemissive. Thus, future efforts on improving emissivity of glass-based perovskite QD samples might focus on approaches for extending the range of stability of the low-temperature highly emissive structure/phase of the QDs up to room temperature.

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

Field-Emission Electron Source Embedded in a Field-Enhanced Conduction-Cooled Superconducting RF Cavity

We present simulations and experimental progress toward the development of a high-current electron source with the potential to deliver high charge electron bunches at GHz-level repetition rates. To achieve these goals electrons are generated through field-emission and the cathode is immersed in a conduction-cooled superconducting 650-MHz RF cavity. The field-emitters consist of microscopic silicon pyramids and have a typical enhancement factor of about 500. To trigger field-emission, the peak field inside the RF cavity of about 6 MV/m is further enhanced by placing the field-emitters on the top of a superconducting Nb rod inserted in the RF cavity. So far, we cannot control the duration of the electron bunches which is of the order of RF period. Also, the present cryo-cooler power of about 2 W limits the beam current to microamp level.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Spatially Varying Embedded Stochastic Galerkin Methods for Steady-State PDEs

Existing discretizations for stochastic PDEs, based on a tensor product between the deter ministic basis and the stochastic basis, treat the required resolution of uncertainty as uniform across the physical domain. However, solutions to many PDEs of interest exhibit spatially localized features that may result in uncertainty being severely over or under-resolved by existing discretizations. In this report, we explore the mechanics and accuracy of using a spatially varying stochastic expansion. This is achieved through an adaptive refinement algorithm where simple error estimates are used to independently drive refinement of the stochastic basis at each point in the physical domain. Results are presented comparing the accuracy of the adaptive techinque to the accuracy achieved using uniform refinement.

Cyr, Eric C.↗