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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Climatology of the Vertical Profiles of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Continental/Tropical MCSs and Landfalling Hurricanes

Most existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual-polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. Here, in this study, we utilize the network of operational WSR-88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity Z DR , and specific differential phase K DP as well as the radar-retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter D m , and total number concentration N t of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the “background” vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower D m , higher N t , and often substantial IWC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Metal Amorphous Nanocomposite (MANC) Alloy Cores with Spatially Tuned Permeability for Advanced Power Magnetics Applications

Metal amorphous nanocomposite (MANC) alloys are an emerging class of soft magnetic materials showing promise for a range of inductive components targeted for higher power density and higher efficiency power conversion applications including inductors, transformers, and rotating electrical machinery. Magnetization reversal mechanisms within these alloys are typically determined by composition optimization as well as controlled annealing treatments to generate a nanocomposite structure composed of nanocrystals embedded in an amorphous precursor. Here in this paper we demonstrate the concept of spatially varying the permeability within a given component for optimization of performance by using the strain annealing process. The concept is realized experimentally through the smoothing of the flux profile from the inner to outer core radius achieved by a monotonic variation in tension during the strain annealing process. Great potential exists for an extension of this concept to a wide range of other power magnetic components and more complex spatially varying permeability profiles through advances in strain annealing techniques and controls.

36 MATERIALS SCIENCE↗
DOE OSTI2024

AC Magnetometry Using Nano-ferrofluid Cladded Multimode Interferometric Fiber Optic Sensors for Power Grid Monitoring Applications

The AC magnetic field response of the superparamagnetic nano-ferrofluid is an interplay between the Neel and Brownian relaxation processes and is generally quantified via the susceptibility measurements at high frequencies. The high frequency limit is dictated by these relaxation times which need to be shorter than the time scale of the time varying magnetic field for the nano-ferrofluid to be considered in an equilibrium state at each time instant. Even though the high frequency response of ferrofluid has been extensively investigated for frequencies up to GHz range by non-optical methods, harnessing dynamic response by optical means for AC magnetic field sensing in fiber-optic-based sensors-field remains unexplored. Instead, the incorporation of nano-ferrofluid as sensing materials has been only limited to DC magnetic field sensing, often citing their long response time as a limiting factor to AC field sensing. This work reports the finding of high frequency (up to 15 kHz) AC magnetic field sensing capability of nanomagnetic fluid as the cladding material of a fiber-optic multimode interferometry (MMI) structure optimized for the fourth self-imaging spectral response. The key parameter enabling high frequency response is the short response time (<1 ms) achieved by optimizing both the sensing structure and nano-ferrofluid solution. Focus has been imparted on 60 Hz line-frequency profiles of various current/magnetic fields to test the efficacy of these sensors in metering and monitoring current and current-induced magnetic fields in the electrical power grid systems. The magnetic field sensitivity of 240 mV/Gauss per dBm of transmitted power was achieved for 60 Hz field applied via Helmholtz coil, whereas the 60 Hz AC current sensitivity of 2.83 mV/A was measured due to magnetic field induced by current in a straight conducting wire.

42 ENGINEERING↗
DOE OSTI2024

Multi-omics analysis reveals the dynamic interplay between Vero host chromatin structure and function during vaccinia virus infection

The genome folds into complex configurations and structures thought to profoundly impact its function. The intricacies of this dynamic structure-function relationship are not well understood particularly in the context of viral infection. To unravel this interplay, here we provide a comprehensive investigation of simultaneous host chromatin structural (via Hi-C and ATAC-seq) and functional changes (via RNA-seq) in response to vaccinia virus infection. Over time, infection significantly impacts global and local chromatin structure by increasing long-range intra-chromosomal interactions and B compartmentalization and by decreasing chromatin accessibility and inter-chromosomal interactions. Local accessibility changes are independent of broad-scale chromatin compartment exchange (~12% of the genome), underscoring potential independent mechanisms for global and local chromatin reorganization. While infection structurally condenses the host genome, there is nearly equal bidirectional differential gene expression. Despite global weakening of intra-TAD interactions, functional changes including downregulated immunity genes are associated with alterations in local accessibility and loop domain restructuring. Therefore, chromatin accessibility and local structure profiling provide impactful predictions for host responses and may improve development of efficacious anti-viral counter measures including the optimization of vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Effects of plasma squareness on RMP response in MAST-U

The effect of the squareness of the plasma boundary shape on the plasma response to the applied n = 2 (n is the toroidal mode number) resonant magnetic perturbation, and consequently on controlling the edge-localized mode (ELM) in MAST-U in the double-null configuration, is numerically systematically investigated. The modeling is performed utilizing three different plasma response models: the single-fluid model, the two-fluid model and the magnetohydrodynamic-kinetic hybrid model. The effect of the plasma squareness on ELM control is found to depend on the equilbrium kinetic profiles. Fixing the equilibrium radial profiles to that from a recent MAST-U discharge, the experimental plasma shape is found to be close to optimal for ELM control in terms of squareness. The optimal coil phasing does not significantly vary with varying plasma squareness. These findings robustly hold with (i) two figures of merit (FoMs) defined for predicting the ELM control feasibility, and (ii) three plasma response models employed for evaluating these FoMs.

MAST-U↗
DOE OSTI2021

Metamorphic Tunnel Junctions Grown Via MOCVD Designed for GaAs 0.75 P 0.25 /Si Tandem Solar Cells

A high-performance metamorphic Al 0.2 Ga 0.8 As 0.75 P 0.25 /GaAs 0.75 P 0.25 heterojunction tunnel junction structure was developed for application to monolithic epitaxial GaAs 0.75 P 0.25 /Si 1.7 eV/1.1 eV bandgap tandem solar cells produced via metal-organic chemical vapor deposition. Doping optimization focused on both bulk doping concentrations and mitigating the transient incorporation effects that otherwise causes non-abrupt doping profiles in the Te doped layer. Furthermore, these efforts resulted in a fully-relaxed metamorphic tunnel diode at the target lattice constant having a peak tunneling current density (JP) of 279.1 A·cm –2 and a zero-bias resistance area product (RA) of 3.0×10 –4 Ω·cm 2 . After post-growth annealing to emulate the thermal load of the GaAs 0.75 P 0.25 top cell growth and elimination of the performance enhancing carbon activation anneal, the device achieved JP = 13.1 A·cm –2 and RA = 1.5×10 –3 Ω·cm 2 . These worst-case values are very promising as they enable the operation of GaAs 0.75 P 0.25 /Si tandems under one-sun AM1.5G illumination with negligible series resistance and at AM1.5D concentrations up to 240 suns with only 0.1% absolute efficiency loss.

14 SOLAR ENERGY↗
DOE OSTI2019

BuildingIQ Technology Field Validation

This document describes a field validation and verification of the BuildingIQ Predictive Energy Optimization (PEO) technology based on a five-site study. BuildingIQ describes its PEO technology as a software-as-a-service (SaaS) platform that optimizes commercial building HVAC control for system efficiency, occupant comfort, and cost. It is targeted for use in large, complex buildings, and integrates with the building automation system (BAS) to conduct supervisory control. The PEO algorithm defines optimal space air temperature setpoints that are automatically implemented at the variable air volume (VAV) terminal units when possible, or through supply air temperature and duct static pressure setpoints at the air handling unit (AHU) level. The optimization is built upon a learned predictive model that provides a 24-hour ahead forecast of the building’s power profile, using weather forecasts and historical operational data; this model is updated every 4 to 6 hours. Demand-responsive load reductions may also be implemented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Searching for Low-Mass Dark Matter with SuperCDMS Soudan Detectors

SuperCDMS is a direct-detection dark matter (DM) experiment that uses cryogenically cooled germanium and silicon detectors to search for interac- tions between DM particles and detector nuclei, and in this thesis I describe my contributions to the experiment. I start with a brief review of DM and motivate the possibility of its de- tection in underground laboratories with sensitive detectors, and I review the SuperCDMS detector fundamentals. Then I focus on detector develop- ment for the future generation of the experiment, which will deploy an array of detectors at SNOLAB in Sudbury, Canada. Specifically I describe char- acterization of prototype detectors from surface facility testing, and discuss measurements of critical values that determine the detectors’ sensitivity to DM particles, such as the baseline resolution and the phonon collection ef- ficiency. I also describe analysis techniques developed to measure intrinsic detector noise in a high radiation environment such as a surface test facility. In the final chapters I describe a DM search analysis using four months of data from operation of SuperCDMS detectors in the Soudan Mine in northern Minnesota. I discuss how a particular detector operating mode, called CDMSlite, lowers the energy threshold of the detectors in order to improve the sensitivity to low-mass DM particles. I also present new analysis techniques that optimize the sensitivity to low-mass DM particles, including noise discrimination with multivariate classifiers, instrumental background modeling, and a profile likelihood signal and background fitting approach. In this analysis we set an upper limit on the DM-nucleon scattering cross section in germanium that is a factor of 2.5 improvement over the previous CDMSlite result for a DM mass that is five times the proton rest mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The multifaceted role of c-di-AMP signaling in the regulation of Porphyromonas gingivalis lipopolysaccharide structure and function

This study unveils the intricate functional association between cyclic di-3’,5’-adenylic acid (c-di-AMP) signaling, cellular bioenergetics, and the regulation of lipopolysaccharide (LPS) profile in Porphyromonas gingivalis, a Gram-negative obligate anaerobe considered as a keystone pathogen involved in the pathogenesis of chronic periodontitis. Previous research has identified variations in P. gingivalis LPS profile as a major virulence factor, yet the underlying mechanism of its modulation has remained elusive. We employed a comprehensive methodological approach, combining two mutants exhibiting varying levels of c-di-AMP compared to the wild type, alongside an optimized analytical methodology that combines conventional mass spectrometry techniques with a novel approach known as FLAT n . We demonstrate that c-di-AMP acts as a metabolic nexus, connecting bioenergetic status to nuanced shifts in fatty acid and glycosyl profiles within P. gingivalis LPS. Notably, the predicted regulator gene cdaR, serving as a potent regulator of c-di-AMP synthesis, was found essential for producing N-acetylgalactosamine and an unidentified glycolipid class associated with the LPS profile. The multifaceted roles of c-di-AMP in bacterial physiology are underscored, emphasizing its significance in orchestrating adaptive responses to stimuli. Furthermore, our findings illuminate the significance of LPS variations and c-di-AMP signaling in determining the biological activities and immunostimulatory potential of P. gingivalis LPS, promoting a pathoadaptive strategy. The study expands the understanding of c-di-AMP pathways in Gram-negative species, laying a foundation for future investigations into the mechanisms governing variations in LPS structure at the molecular level and their implications for host-pathogen interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Detection, monitoring, and determination of location of changes in metallic structures using multimode acoustic signals

Acoustic transducers generate and receive acoustic signals at multiple locations along a surface of rigid structure, wherein longitudinal spacing between transducer locations define measurement zones. Acoustic signals with chosen amplitude-time-frequency characteristics excite multiple vibration modes in the structure within each zone. Small mechanical changes in inspection zones lead to scattering and attenuation of broadband acoustic signals, which are detectable as changes in received signal characteristics as part of a through-transmission technique. Additional use of short, narrowband pulse acoustic signals as part of a pulse-echo technique allows determination of the relative location of the mechanical change within each zone based on the differential delay profiles. For accurate acoustic modeling and simulation, the mesh size, time step, time delay, and time-window size are optimized. Frequency normalization of the Short-Time Fourier Transform of acoustic response output improves experiment-simulation cross-validation. Applications of the method to structures with arbitrarily complex geometries are also demonstrated.

Findikoglu, Alp Tugrul↗
DOE OSTI2026

Measurements of three-flavor neutrino oscillations from a PISCES two-detector fit to the NOvA Experiment data

NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA s primary physics goals are to measure the neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ with high precision, determine the neutrino mass hierarchy, and constrain the value of $\delta_{CP}$, primarily via the study of muon neutrino to electron neutrino oscillation. Extracting values for oscillation parameters from fits to data usually relies on treating systematic uncertainties as nuisance parameters, a strategy that suffers from poor scalability as the number of uncertainties becomes larger. This work introduces PISCES (Parameter Inference with Systematic Covariance and Exact Statistics), a novel method that circumvents this scalability problem by encoding systematic uncertainties into a covariance matrix. PISCES utilizes a nested minimization in which optimal systematic pulls are first computed using the covariance matrix in an inner minimization step, then the oscillation parameters are profiled over in the outer minimization. PISCES also uses a Poisson Likelihood term, making it ideal for the inclusion of low-statistic samples in the fits. PISCES is a flexible framework that also supports complex fits, such as a joint Near and Far detector fit. In the standard NOvA analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data indirectly constrain the FD prediction via a ratio method. PISCES, on the other hand, enables a simultaneous ND+FD fit, allowing the high-statistics ND data to directly constrain systematic uncertainties across all samples. This thesis presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, details its implementation, and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method using the full NOvA 10-year data set. The results demonstrate that PISCES can successfully fit NOvA data while incorporating the constraints from the ND detectors consistently, using physically motivated systematic uncertainties to account for data/MC discrepancies.

Rajaoalisoa, Miriama [Cincinnati U.]↗
DOE OSTI2021

Oxygen enrichment combustion to reduce fossil energy consumption and emissions in hot rolling steel production

The reheating furnace operation in the hot mill is natural gas- and electricity-intensive. Oxygen enrichment combustion for reheating furnaces has been proposed to curb and replace natural gas use. In this study, heat transfer in steel slabs in the combustion environment of a push-type reheating furnace was simulated using a computational fluid dynamics (CFD) model. Two oxygen enrichment methods that optimized for performance were selected— a medium oxygen enrichment (MOE) case and an oxy-fuel (OF) case. A life cycle analysis (LCA) characterized the energy and emission profiles of an integrated iron and steel manufacturing process using the two oxygen enrichment cases for the hot mill. These conditions were evaluated for energy use and carbon intensity and compared with a baseline case. Results show that with oxygen enrichment, natural gas consumption can decrease by 19.6%–26.8%, total energy consumption (natural gas and electricity) can decrease by 15.1%–20.7% in the hot mill. Emissions of greenhouse gases can decrease by 11.1%–15.2% in the two optimized cases with 14%–27% reductions in regulated criteria pollutants (nitrogen oxides, carbon monoxide, particulate matter, volatile organic compounds, black carbon, organic carbon, and volatile organic carbons). There is a tradeoff between reducing natural gas consumption and increasing electricity demand from a life cycle perspective. Although the OF case resulted in higher energy- and emissions-related benefits, the MOE case showed the more desirable heat flux uniformity, which is key to maintaining product quality. The analysis suggests that oxygen enrichment in the reheating furnace process can have a significant impact on hot mill environmental performance and become a contributing factor in transitioning to low-carbon steel manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units

In this paper, genetic algorithm (GA)-based voltage optimization of a modified IEEE-34 node distribution feeder with high penetration of distributed energy resources (DERs) is proposed using two megawatt-scale reactive power sources. Traditional voltage support units present in distribution grids are not suitable for DER-rich feeders, while voltage support using small-scale DERs present in the feeder requires considerable communication effort to reach a global solution. In this work, two megawatt-scale units are placed to improve the voltage profile across the IEEE 34-node feeder, which has been modified to include several PV units and an energy storage unit. The megawatt-scale units are optimized using GA for fast and accurate operation. The performance of the proposed scheme is verified using simulation results with a multi-platform setup where the modified IEEE-34 node feeder is modeled in OpenDSS while the GA optimization scheme is programmed in MATLAB.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Real-time capable modeling of neutral beam injection on NSTX-U using neural networks

A new model of heating, current drive, torque and other effects of neutral beam injection on NSTX-U that uses neural networks has been developed. The model has been trained and tested on the results of the Monte Carlo code NUBEAM for the database of experimental discharges taken during the first operational campaign of NSTX-U. By projecting flux surface quantities onto empirically derived basis functions, the model is able to efficiently and accurately reproduce the behavior of both scalars, like the total neutron rate and shine through, and profiles, like beam current drive and heating. With this being said, the model has been tested on the NSTX-U real-time computer, demonstrating a rapid execution time orders of magnitude faster than the Monte Carlo code that is well suited for the iterative calculations needed to interpret experimental results, optimization during scenario development activities, and real-time plasma control applications. Simulation results of a proposed design for a nonlinear observer that embeds the neural network calculations to estimate the poloidal flux profile evolution, as well as Z eff and fast ion diffusivity, are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Taguchi Design of Experiment Enabling the Reduction of Spikes on the Sides of Patterned Thin Films for Tunnel Junction Fabrication

Photolithographically patterned thin films often possess unwanted spikes along the side edges. These spikes are a significant issue for the development of spinvalve memory, tunnel junction based molecular devices, and micro-electromechanical systems. Here, we report a very simple, economical, and fast way of creating an optimum photoresist profile for the production of spike-free patterned films. This approach is based on performing a soaking step in the positive-photoresist’s developer solution before the UV exposure. However, the success of this method depends on multiple photolithography factors: photoresist thickness (governed by spin speed), soft baking temperature, soaking time in developer, and exposure time. In this paper, we report our systematic experiments to study the effect of these factors by following the L9 experimental scheme of the Taguchi Design of experiment (TDOE) approach. The L9 experiment scheme effectively accommodated the study of four photolithography factors, each with three levels. After performing photolithography as per L9 TDOE scheme, we sputter deposited 20 nm Tantalum to check the side edge profile of the patterned film by atomic force microscope (AFM). We measured the heights of the spikes along the thin film edges. We utilized spike height as the desired property and chose “smaller the better” criteria for the TDOE analysis. TDOE enabled us to understand the relative importance of the parameters, relationship among the parameters, and impact of the various levels of the parameters on the thin film edge profile. TDOE analysis yielded an optimum combination of levels for the four photolithography factors. The optimum combination of photolithography factors included spin speed 4000 rpm, 100 °C soft baking temperature, 60 sec pre-soaking in the developer solution, and 15 sec UV exposure. We validated the TDOE by AFM and observed spike free patterned films. Here, we also made complete tunnel junction devices by utilizing the optimized photolithography factors for the bottom electrode and obtained excellent tunneling behavior. In summary, this study provides a very simple, economical, and fast photolithography approach for creating optimum photoresist profile for the micro-nano scale devices and electromechanical structures.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Structure-based lead optimization to improve the antifungal potency of the tetrahydroimidazo pyridine inhibitors targeted to Candida albicans dihydrofolate reductase and lanosterol 14-alpha-demethylase

We investigate the binding and inhibition profiles for a selected dataset of tetrahydroimidazo pyridine molecules against Candida albicans dihydrofolate reductase (DHFR) and lanosterol 14-alpha-demethylase (CYP51). A hit molecule was screened and identified through Lipinski’s rule of five, ADMET (absorption, distribution, metabolism, excretion, and toxicity), and the molecular docking. Some inhibitors of our design have shown positive drug scores, good solubilities, and high docking scores over the selected dataset. The first-principles calculation based on the density functional theory was carried out to understand how the electronic distributions of frontier orbitals of molecules affect their inhibition profiles. The present structure-based approach enabled us to design new pharmacophore analogs with improved ADMET profile, drug scores, and docking scores against selected receptors. .

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Exosomal proteome analysis of human plasma to monitor sepsis progression

Highlights: • As low as 300 μL human plasma is sufficient for exosome isolation using our one-step density gradient ultracentrifugation. • Protein profiling of septic plasma exosomes are closely related to immune responses. • SPTLC3 may play important roles in development of sepsis. Exosomes are cell-derived vesicles containing RNA, lipid, and protein, which act in body immune response, intercellular signaling and some other important biological processes. Exosomes have been extensively studied in the past several years on their disease related mechanisms and potential roles to monitor disease progression as biomarkers. Compared with analyzing exosome RNA, comprehensive proteome profiling of exosomes in clinical samples (e.g. blood) are highly demanded but limited mainly due to lack of a reproducible method for efficient exosome extraction. In this study, we evaluated and optimized an exosome preparation approach using one-step ultracentrifugation through an Optiprep™ cushion. Exosomes prepared via this method and analyzed by mass spectrometry using Q-Exactive plus, has led to reproducible identification and quantification of 200 + proteins from human plasma samples of as little as 300 μL. Therefore, such a straightforward exosome extract method has enable us to deeply profile exosome proteomes from human blood at a scale of clinical studies. As a proof of principal, we practiced this approach in analyzing the exosome proteomic profiles of blood samples collected from a sepsis patient during six time points after diagnosis. Among the 238 proteins identified and quantified across the 6 samples, protein SPTLC3 involved in the sphingolipid metabolism, shows a negative correlation (p = 0.02, correlation coefficient = −0.984) with disease progression indicated by body temperature (BD) and C-reactive protein (CRP). Therefore, SPTLC3 could be an interesting target for future study on molecular mechanism of sepsis development, as well as potential classifier to monitor clinical progression of sepsis.

60 APPLIED LIFE SCIENCES↗