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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The role of above-code labeling programs in reducing CO 2 e emissions in residential buildings

Residential buildings account for 15 % of total U.S. carbon dioxide (CO 2 ) emissions. Voluntary, above-code labeling programs, such as the ENERGY STAR and Zero Energy Ready Home programs, can play a crucial role in reducing the carbon footprint of the new construction residential building sector by encouraging adoption of more energy-efficient and lower emissions building practices and technologies. It's important for the industry to understand the carbon dioxide equivalent (CO 2 e) and energy cost savings potential of these programs. Here, to estimate the potential CO 2 e emissions savings for homes built to above-code labeling program levels, it is imperative to have reliable and accurate tools for estimating emissions from buildings. The open-source OpenStudio-ERI workflow employs detailed physics-based building energy modeling (BEM) to estimate energy usage and operational CO 2 e emissions. In this study we use the OpenStudio-ERI workflow and regional, time-varying emissions factors from the Cambium database to compare the CO 2 e emissions and energy costs of homes built to performance levels required by these above-code labeling programs relative to homes built to model energy codes. We present the results of our analysis and provide a range of emissions and annual energy cost savings for the above-code labeling programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Optimizing high energy density sulfur cathodes: A multivariate approach to electrode formulation and processing

Lithium-sulfur (Li-S) batteries involve complex solid-liquid-solid phase transformations during both discharging and charging processes, where cathode materials, formulation, and structure play a crucial role. Here, a design of experiments (DoE) methodology and an empirical model are developed to systematically explore the interactions and trade-offs among cathode factors and process variables, and to obtain generalizable effects estimates for the multivariate system. Compared to the conventional one-factor-at-a-time (OFAT) approach, this work demonstrates advantages in both efficiency and accuracy by allowing the data to guide future research and decisions. Further, an optimized cathode formulation and processing parameters are predicted and validated experimentally, achieving over 1000 mAh g -1 in discharge capacity and improved cycling under practical lean electrolyte (4 µL mg -1 S) and high S-loading cathodes (>4 mg cm -2 ) conditions. The optimized cathode was scaled up and assembled into Li-S pouch cells, achieving 316 Wh kg -1 in cell-level energy, proving that the comprehensive and rigorous framework for optimizing complex systems with DoE leads to improved performance in a practical pouch cell system.

25 ENERGY STORAGE↗
DOE OSTI2020

Distribution System Segmented Model Simplification with Independent Dynamically Changing End-Use Loads

With more emerging technologies in power distribution systems, to support quasi-static time-series (QSTS) simulation over short time frames, accurately modeling the dynamic behavior of end-use load under various conditions is im- portant. However, time and cost can be a burden for the QSTS simulation of thousands of houses representing dynamic load behaviors on large distribution feeders. There are two main contributions of this paper in order to reduce the QSTS simulation complexity. First, the paper presents a method to stochasti- cally model the dynamic behavior of end-use load for QSTS simulations. Second, using the stochastically modeled load behavior as an input to a distribution sys- tem, and building on our previous QSTS simulation simplification/acceleration method that relies on uniform load behavior, this paper presents a segment substitution approach for the simplification of distribution system models with independent dynamically changing end-use loads. Our numerical results show that compared to GridLAB-D, a software tool that simulates end-use load be- havior through physical models, the proposed stochastic modeling approach achieved an 89.3% simulation time reduction for end-use loads, while accurately capturing the temporally changing total load behavior. Moreover, the QSTS simulation of a large test distribution system through OpenDSS showed that the proposed simplification method decreased the feeder simulation time by a factor of three at less than 0.3% voltage error. Compared to our previous method with independent dynamic loads, the voltage error is reduced by a factor of four.

Power distribution system modeling, stochastic pro↗
DOE OSTI2024

Capturing Surface Coverage Effects in Heterogeneous Catalysis

Adsorbate–adsorbate lateral interactions at relevant surface coverages have a significant effect on chemical kinetics, thereby influencing the activity of a heterogeneous catalyst. Coverage-dependent kinetic and thermodynamic parameters therefore must be included in studies of such complex systems to properly predict the turnover frequencies and kinetic trends. Thus, it becomes extremely important to accurately capture the strength of lateral interactions between neighboring species under realistic reaction conditions. In this Perspective, we discuss the various existing computational and experimental methods for determining adspecies coverage and configurational effects. The choice of the tools and methods employed in such studies depends on factors such as time, length scales, computational cost, the presence of solvents, and reaction conditions. The applications of each method and the respective challenges are also discussed here. As a result, we discuss the recent developments and future of the state-of-the-art for inclusion of surface coverage and configuration into a holistic picture for accurate predictions of catalytic behavior.

09 BIOMASS FUELS↗
DOE OSTI2020

Superthermal Electron Deposition on the Mars Nightside During ICMEs

Superthermal electron precipitation is one of the main sources supporting the Mars nightside ionosphere. It is expected that solar wind electron fluxes are to increase significantly during interplanetary coronal mass ejections (ICMEs) and therefore an enhanced nightside ionospheric density. This study is to quantify the variation of the precipitating and deposited electron fluxes during five extreme ICMEs encountered by Mars Global Surveyor (MGS). We find that energy fluxes correlate better with the upstream dynamic pressure proxy than number fluxes and electron fluxes increase more at high energies, which means that electrons tend to have a lower peak production altitude during storm times. The precipitating and net/deposited fluxes are increased up to an order of magnitude from low to high dynamic pressures. The estimated total electron content (TEC) is a few times of 10 14 m -2 for quiet times and on the order of 1015 m -2 for storm times, with an enhancement up to an order of magnitude locally near strong crustal fields. Crustal magnetic fields have an effect on the deposited fluxes with more prominent magnetic reflection over strong magnetic fields during quiet periods, which is significantly reduced during storm times. Lastly, we estimate a global energy input from downward fluxes of 1.1 × 10 8 and 5.5 × 10 8 W and the globally deposited energy from net fluxes of 2.0 × 10 7 and 1.6 × 10 8 W for quiet and storm time periods, a factor of 5 and 8 enhancement globally, respectively, but up to an order of magnitude locally near strong crustal fields.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients

Wind farm layout optimization (WFLO) studies often aim to maximize the annual energy production (AEP) of a wind farm by choosing an arrangement of turbines that minimizes wake interactions. One way to reduce the cost of WFLO studies is by using more computationally efficient AEP models. The cost of standard AEP modeling approaches, based on the numerical integration of low-fidelity engineering wake models, scales poorly with the number of simulated discrete wind conditions. A second way to reduce cost when using a gradient-based algorithm is to supply exact gradient information instead of finite-difference estimates. However, analytical functions for the derivatives of AEP with respect to turbine positions are not always available in the conventional modeling approach. FLOWERS is a computationally inexpensive, analytical model for wind farm AEP that is specifically developed for WFLO applications. In this paper, we analyze the performance of the FLOWERS AEP model with analytic gradients in a layout optimization study compared with a reference optimization framework across three wind farm case studies. We find that the FLOWERS-based approach reduces computation time by a factor of 50–4000 and improves optimal AEP by about 0.3% with less than half of the variability in AEP across instances with randomized initial conditions. We also find the optimal layouts to be insensitive to model parameter tuning, making FLOWERS-based layout optimization a streamlined, user-friendly approach.

17 WIND ENERGY↗
DOE OSTI2021

Simulated Performance of the Micro-Pocket Fission Detector in the Advanced Test Reactor Critical Facility

The Micro-Pocket Fission Detector (MPFD) is a small-form–factor real-time fission chamber. MPFD performance has been simulated in the Advanced Test Reactor Critical Facility (ATRC), located at Idaho National Laboratory (INL). Here, the neutron and gamma-ray flux profiles and magnitudes were simulated using Monte Carlo N-Particle (MCNP) in the near-core B-8 irradiation position. These simulations were performed at 69 discrete axial locations inside the B-8 position for three separate orientations of the nearby hafnium outer shim control cylinders and at a power level of 700 Wth. The resulting neutron and gamma-ray flux values were used to determine the MPFD response for various fissile masses and detector gas pressures. The optimal gas-operating pressure was determined to be between 30 and 60 psig. The required fissile-layer mass was determined to be between 1–2 µg of 235 U. Additionally, the gamma-ray to fission-fragment interaction rate was determined to be 4.42 × 10 -3 with average energy deposition for gamma rays and fission fragments in 30 psig argon gas to be 1 keV and 9.5 MeV, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models

The configurations of instruments fielded on an experiment affect the amount of information captured and the quality of subsequent inference. Here, we investigate the problem of optimizing plasma x-ray radiation detectors in a magneto-inertial fusion experiment at Sandia National Laboratories. It is impossible to directly measure properties such as the temperature of the thermonuclear fusion plasma produced in these experiments because of the extreme environment and destructive nature of the experiment. Among other diagnostics, several detectors are placed with significant standoff from the fusion target to capture the x-rays emitted by the fusion plasma, which can be used to infer some of its properties. To optimize the configuration of these detectors, a high-fidelity model (HFM) is used for simulating outputs and a low-fidelity model (LFM) is used for inference. We develop methods based on A- and L-optimality criteria that are efficient to compute while explicitly accounting for the discrepancy between the HFM and the LFM. The method allows us to find detector configurations that perform similarly to or better than the configuration obtained using an existing sampling-based optimization method while decreasing computational time by a factor of 50. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Bayesian optimization↗
DOE OSTI2022

Organizing Large Data Sets for Efficient Analyses on HPC Systems

Upcoming exascale applications could introduce significant data management challenges due to their large sizes, dynamic work distribution, and involvement of accelerators such as graphical processing units, GPUs. In this work, we explore the performance of reading and writing operations involving one such scientific application on two different supercomputers. Our tests showed that the Adaptable Input and Output System, ADIOS, was able to achieve speeds over 1TB/s, a significant fraction of the peak I/O performance on Summit. We also demonstrated the querying functionality in ADIOS could effectively support common selective data analysis operations, such as conditional histograms. In tests, this query mechanism was able to reduce the execution time by a factor of five. More importantly, ADIOS data management framework allows us to achieve these performance improvements with only a minimal amount of coding effort.

Gu, Junmin↗
DOE OSTI2020

Environments of dwarf galaxies with optical AGN characteristics

ABSTRACT This study aims to explore the relation between dwarf galaxies (M* ≤ 5 × 109 M⊙) with active galactic nuclei (AGNs) and their environment by comparing neighbourhood parameters of AGN and non-AGN samples. Using the NASA-Sloan Atlas, both the local environment and the immediate environment of dwarf galaxies with z ≤ 0.055 are analysed. Of the 145 155 galaxies in the catalogue, 62 258 of them are classified as dwarf galaxies, and by employing two AGN selection methods based on emission-line fluxes (BPT and WHAN), 4476 are found to have AGN characteristics in their optical spectra. Regardless of selection method, this study finds no discernible differences in environment between AGN and non-AGN host dwarf galaxies and these results indicate that environment is not an important factor in triggering AGN activity in dwarf galaxies. This is in line with existing literature on environments of regular galaxies with AGNs and suggests universality in terms of reaction to environment across the mass regime. The biases of AGN selection in low-mass galaxies, and the biases of different measures of environment are also considered. It is found that there are several mass trends in emission-line ratios and that the SDSS fibre covers galaxies non-uniformly with redshift. These biases should be accounted for in future work by possibly including other wavelength regimes or mass weighting of emission-line ratios. Lastly, a discussion of the environment estimation methods is included since they may not gauge the desired properties due to factors such as time delay or using loosely constrained proxy parameters.

Kristensen, Mikkel T.↗
DOE OSTI2022

MUSE Analysis of Gas around Galaxies (MAGG) – IV. The gaseous environment of z ∼ 3–4 Ly α emitting galaxies

ABSTRACT We study the link between galaxies and H i-selected absorption systems at z ∼ 3–4 in the MUSE Analysis of Gas around Galaxies (MAGG) survey, an ESO large programme consisting of integral field spectroscopic observations of 28 quasar fields hosting 61 strong absorbers with $\rm N_{\rm H\,{\small I}}\gtrsim 10^{16.5}~\rm cm^{-2}$. We identify 127 Ly α emitting galaxies (LAEs) around the absorbers, corresponding to a detection rate of 82 ± 16 per cent. The luminosity function of these LAEs is ≈5 times higher in normalization than the field population and we detect a significant clustering of galaxies with respect to the gas, confirming that high column density absorbers and LAEs trace each other. Between 30 and 40 per cent of the absorbers are associated with multiple LAEs, which lie preferentially along filaments. Galaxies in groups also exhibit a three times higher covering factor of optically thick gas compared to isolated systems. No significant correlations are identified between the emission properties of LAEs and the absorption properties of optically thick gas clouds, except for a weak preference of brighter and multiple galaxies to reside near broad absorbers. Based on the measured impact parameters and the covering factor, we conclude that the near totality of optically thick gas in the Universe can be found in the outer circumgalactic medium (CGM) of LAEs or in the intergalactic medium (IGM) in proximity to these galaxies. Thus, LAEs act as tracers of larger scale structures within which both galaxies and optically thick clouds are embedded. The patchy and inhomogeneous nature of the CGM and IGM explains the lack of correlations between absorption and emission properties. This implies that very large samples are needed to unveil the trends that encode the properties of the baryon cycle.

Astronomy & Astrophysics↗
DOE OSTI2022

Artificial light at night: an underappreciated effect on phenology of deciduous woody plants

Artificial light at night (ALAN), an increasing anthropogenic driver, is widespread and shows rapid expansion with potential adverse impact on the terrestrial ecosystem. However, whether and to what extent does ALAN affect plant phenology, a critical factor influencing the timing of terrestrial ecosystem processes, remains unexplored due to limited ALAN observation. Here, we used the Black Marble ALAN product and phenology observations from USA National Phenology Network to investigate the impact of ALAN on deciduous woody plants phenology in the conterminous United States. We found that (1) ALAN significantly advanced the date of breaking leaf buds by 8.9 ± 6.9 days (mean ± SD) and delayed the coloring of leaves by 6.0 ± 11.9 days on average; (2) the magnitude of phenological changes was significantly correlated with the intensity of ALAN (P < 0.001); and (3) there was an interaction between ALAN and temperature on the coloring of leaves, but not on breaking leaf buds. We further showed that under future climate warming scenarios, ALAN will accelerate the advance in breaking leaf buds but exert a more complex effect on the coloring of leaves. This study suggests intensified ALAN may have far-reaching but underappreciated consequences in disrupting key ecosystem functions and services, which requires an interdisciplinary approach to investigate. Developing lighting strategies that minimize the impact of ALAN on ecosystems, especially those embedded and surrounding major cities, is challenging but must be pursued.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Frustrated magnetic interactions in FeSe

The structurally simplest high-temperature superconductor FeSe exhibits an intriguing superconducting nematic paramagnetic phase with unusual spin excitation spectra that are different from typical spin waves; thus, determining its effective magnetic exchange interactions is challenging. In this work, we report neutron scattering measurements of spin fluctuations of FeSe in the tetragonal paramagnetic phase. We show that the equal-time magnetic structure factor, S(Q), can be effectively modeled using the self-consistent Gaussian approximation calculation with highly frustrated nearest-neighbor (J 1 ) and next-nearest-neighbor (J 2 ) exchange couplings, and very weak further neighbor exchange interaction. Our results elucidate the frustrated magnetism in FeSe, which provides a natural explanation for the highly tunable superconductivity and nematicity in FeSe and related materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Fast and flexible analysis of direct dark matter search data with machine learning

We present the results from combining machine learning with the profile likelihood fit procedure, using data from the Large Underground Xenon (LUX) dark matter experiment. This approach demonstrates reduction in computation time by a factor of 30 when compared with the previous approach, without loss of performance on real data. We establish its flexibility to capture non-linear correlations between variables (such as smearing in light and charge signals due to position variation) by achieving equal performance using pulse areas with and without position-corrections applied. Its efficiency and scalability furthermore enables searching for dark matter using additional variables without significant computational burden. We demonstrate this by including a light signal pulse shape variable alongside more traditional inputs such as light and charge signal strengths. Furthermore, this technique can be exploited by future dark matter experiments to make use of additional information, reduce computational resources needed for signal searches and simulations, and make inclusion of physical nuisance parameters in fits tractable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantum Enhanced Cavity QED Interferometer with Partially Delocalized Atoms in Lattices

Herein, we propose a quantum enhanced interferometric protocol for gravimetry and force sensing using cold atoms in an optical lattice supported by a standing-wave cavity. By loading the atoms in partially delocalized Wannier-Stark states, it is possible to cancel the undesirable inhomogeneities arising from the mismatch between the lattice and cavity fields and to generate spin squeezed states via a uniform one-axis twisting model. The quantum enhanced sensitivity of the states is combined with the subsequent application of a compound pulse sequence that allows us to separate atoms by several lattice sites. This, together with the capability to load small atomic clouds in the lattice at micrometric distances from a surface, make our setup ideal for sensing short-range forces. We show that for arrays of 10 4 atoms, our protocol can reduce the required averaging time by a factor of 10 compared to unentangled lattice-based interferometers after accounting for primary sources of decoherence.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Entanglement Purification and Protection in a Superconducting Quantum Network

High-fidelity quantum entanglement is a key resource for quantum communication and distributed quantum computing, enabling quantum state teleportation, dense coding, and quantum encryption. Any sources of decoherence in the communication channel, however, degrade entanglement fidelity, thereby increasing the error rates of entangled state protocols. Entanglement purification provides a method to alleviate these nonidealities by distilling impure states into higher-fidelity entangled states. In this work, we demonstrate the entanglement purification of Bell pairs shared between two remote superconducting quantum nodes connected by a moderately lossy, 1-meter long superconducting communication cable. We use a purification process to correct the dominant amplitude damping errors caused by transmission through the cable, with fractional increases in fidelity as large as 25%, achieved for higher damping errors. The best final fidelity the purification achieves is 94.09 ± 0.98%. In addition, we use both dynamical decoupling and Rabi driving to protect the entangled states from local noise, increasing the effective qubit dephasing time by a factor of 4, from 3 to 12 μs. These methods demonstrate the potential for the generation and preservation of very high-fidelity entanglement in a superconducting quantum communication network.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

LaRIS: Targeting Portability and Productivity for LAPACK Codes on Extreme Heterogeneous Systems by Using IRIS

In keeping with the trend of heterogeneity in high-performance computing, hardware manufacturers and vendors are developing new architectures and associated software stacks (e.g., libraries) to harness the best possible performance from commonly used kernels (e.g., linear algebra kernels). However, kernels tuned for one architecture are not portable to others. Moreover, the coexistence of different architectures in a single node makes orchestration difficult. To address these challenges, we introduce LaRIS, a portable framework for LAPACK functionalities. LaRIS ensures a separation between linear algebra algorithms and vendor-library kernels by using the IRIS run time and IRIS-BLAS library. Such abstraction at the algorithm level makes the implementation completely agnostic to the vendor library and architecture. LaRIS uses the IRIS run time to dynamically select the vendor-library kernel and suitable processor architecture at run time. Through LU factorization, we demonstrate that LaRIS can fully utilize different heterogeneous systems by launching and orchestrating different vendor-library kernels without any change in the source code.

Monil, M. A. H.↗
DOE OSTI2023

Laminar Burning Speed Measurements of Hydrogen/Natural Gas Mixtures

Abstract To address the shortage of fossil fuels and the environmental impact of exhaust emissions, research efforts in combustion seek to identify candidates for sustainable fuels. Hydrogen is an example, from which water is produced as the main combustion product. However, when used as neat hydrogen, it is very difficult to control hydrogen combustion due to its high flame speed, pre-ignition propensity, and flashback characteristics. One method to control hydrogen combustion is to blend it with a well-established fuel. Natural gas is a common fuel for use in engines or gas turbines. Natural gas is characterized by slow flame speeds and poor lean-burn ability; thus, engine power is decreased in the lean-burn region. Consequently, natural gas engines are typically operated at stoichiometric conditions to maximize output. Blending hydrogen to natural gas has several advantages: (i) Control of hydrogen’s ignition characteristics, (ii) extension of Natural gas’s lower flammability limit — making it easier to ignite, and (iii) reduced greenhouse gas emissions. In this study, the laminar burning speed (LBS) for neat natural gas and natural gas/hydrogen mixtures at 5 atm and 296 K were measured. Schlieren optical imaging was utilized to validate laminar flame conditions and further investigate the structure of natural gas/hydrogen flames. Results indicate that replacing 50% of natural gas with hydrogen increases the peak laminar burning velocity by a factor of ∼1.6 times. LBS simulations were conducted with NUI 1.1 and UCF NG/H2 mechanisms; Predictions by both mechanisms were found to be satisfactory for neat NG mixtures. However, for 50% NG/ 50% H2 mixture, the true LBS for fuel-lean conditions was under-predicted by both models, while predictions for fuel-rich conditions were satisfactory. Additionally, a literature review and similar experimental analysis will be performed for methane, ammonia, and hydrogen fuel blends to better understand the combustion phenomena of natural gas fuels.

Yovino, Louis↗