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At least 433 records · Page 24

DESI DR1 Ly α 1D power spectrum: Validation of estimators

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Lyα forest cosmology, accessed through its one-dimensional power spectrum (P 1D ). The Lyα forest P 1D is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure P 1D : the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest k values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 P 1D on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

Lyman alpha forest↗

Nuclear Reactor Heat Extraction for Synthetic Fuel Plants

This report looks at the viability and best approach when producing synthetic fuels using heat and power supplied by advanced nuclear energy systems. The report looks at a low temperature integration pathway with four types of advanced reactors: a pressurized water reactor (PWR), an advanced light water reactor (A-LWR), a sodium fast reactor (SFR), and a high-temperature gas-cooled reactor (HTGR). A failure modes and effects analysis (FMEA) of the coupling system between the nuclear plant and the synthetic fuel systems is performed with the goal of identifying the reliability of such a thermal delivery system. Furthermore, a high temperature pathway is investigated for synfuel coupling to determine if this is more efficient and more cost effective as a coupling approach.

10 - SYNTHETIC FUELS↗

Review of NASA programs in applying aerospace technology to energy

NASA's role in energy research and development, with the aid of aerospace technology, is reviewed. A brief history, which began in 1974 with studies of solar energy systems on earth, is presented, and the major energy programs, consisting of over 60 different projects, are described, and include solar terrestrial systems, conservation and fossil energy systems, and space utilization systems. Special attention is given to the Satellite Power System and the isolation of nuclear wastes in space. Emerging prospects for NASA programs in energy technology include bioenergy, and ocean thermal energy conversion, coal extraction and conversion technologies, and support to the nuclear industry in power plant systems safety.

Schwenk, F. C.↗

Critical Minerals from Waste Streams in the Powder River Basin of Wyoming and Montana, USA

Background/Objectives. Critical minerals (CM) are essential for numerous industrial and defense applications, including green technologies that will help to meet carbon emission reduction goals. Many CM are currently mined and processed in countries that lack stringent environmental and labor regulations. Unconventional sources such as existing industrial waste streams could play a part in building an ethical CM supply chain. Additionally, waste streams created in the extraction and processing of CM could be used for other industrial or commercial purposes, thereby reducing waste and advancing a circular economy. Approach/Activities. The Department of Energy funded Powder River Basin (PRB) CORE-CM project is exploring all aspects of the carbon ore, rare earth element (REE), and CM value chain, including the potential for extraction of CM from industrial waste streams in the basin. Waste streams that have potential as CM feedstocks are being inventoried to assess the concentration of CM in each waste stream and to estimate volume and accessibility. Although basin-specific technologies for extraction of CM are still in development, waste streams that may be produced during these processes are being cataloged and mapped to potential secondary uses. Results/Lessons Learned. Initial studies of the CM potential of PRB coal ash show that this waste stream contains concentrations of greater than 300 ppm total REE (Bagdonas et al., 2022, Renewable and Sustainable Energy Reviews). Moreover, calcium-rich PRB coal ash is amenable to REE extraction (Taggart et al., 2016, Environmental Science and Technology). Wyoming coal is shipped to 28 states, meaning that coal ash produced at power stations across the US represents a potential widespread resource for the extraction of REE. In addition to coal mining and coal fired electricity generation, the PRB is home to other energy industries including oil and gas production, in-situ uranium mining, and bentonite mining. Historically, precious and base metal mining has taken place on the perimeter of the PRB. Waste streams from these industries are currently being evaluated for their CM potential. Assessing the CM resource potential of waste streams could contribute to the development of an ethical CM supply chain. Results from these studies can be replicated for other waste streams, increasing the likelihood of successful creation of circular economies.

Phillips, Erin↗

Evaluation of Protein Extraction Methods for Metaproteomic Analyses of Root-Associated Microbes

Metaproteomics is a powerful tool for the characterization of metabolism, physiology, and functional interactions in microbial communities, including plant-associated microbiota. However, the metaproteomic methods that have been used to study plant-associated microbiota are very laborious and require large amounts of plant tissue, hindering wider application of these methods. We optimized and evaluated different protein extraction methods for metaproteomics of plant-associated microbiota in two different plant species (Arabidopsis and maize). Our main goal was to identify a method that would work with low amounts of input material (40 to 70 mg) and that would maximize the number of identified microbial proteins. We tested eight protocols, each comprising a different combination of physical lysis method, extraction buffer, and cell-enrichment method on roots from plants grown with synthetic microbial communities. We assessed the performance of the extraction protocols by liquid chromatography-tandem mass spectrometry–based metaproteomics and found that the optimal extraction method differed between the two species. For Arabidopsis roots, protein extraction by beating whole roots with small beads provided the greatest number of identified microbial proteins and improved the identification of proteins from gram-positive bacteria. For maize, vortexing root pieces in the presence of large glass beads yielded the greatest number of microbial proteins identified. Based on these data, we recommend the use of these two methods for metaproteomics with Arabidopsis and maize. Furthermore, detailed descriptions of the eight tested protocols will enable future optimization of protein extraction for metaproteomics in other dicot and monocot plants.

59 BASIC BIOLOGICAL SCIENCES↗

Pulsed Magnet Power Systems at NSLS-II

The National Synchrotron Light Source - II (NSLS-II) is a 3 GeV X-ray user facility with 29 beamlines. The NSLS-II pulsed power system consists of an event generator for timely injection and extraction of beam in the transport line from linac to booster at 170 MeV, and from booster to storage ring at 3 GeV. We will discuss current pulsed power systems and the future upgrades/improvements on those systems.

43 PARTICLE ACCELERATORS↗

Rarefied-flow pitching moment coefficient measurements of the Shuttle Orbiter

An overview of the process for obtaining the Shuttle Orbiter rarefied-flow pitching moment from flight gyro data is presented. The extraction technique involves differentiation of the output of the pitch gyro after accounting for nonaerodynamic torques, such as those produced by gravity gradient and the Orbiter's auxiliary power unit and adjusting for drift biases. The overview of the extraction technique includes examples of results from each of the steps involved in the process, using the STS-32 mission as a typical sample case. The total pitching moment and moment coefficient (Cm) for that flight are calculated and compared with preflight predictions. The flight results show the anticipated decrease in Cm with increasing altitude. However, the total moment coefficient is less than predicted using preflight estimates.

Blanchard, R. C.↗

Big Data Analytic for Cascading Failure Analysis

With the challenges of increased grid dynamics and more variability of power generation from renewable energy sources, rapidly increasing complexity in the grid model, and abundant data from measurements and simulations, the requirements for computational analysis have also increased dramatically. Power system operators and engineers need to analyze more scenarios, extract meaningful information from a larger set of data, and respond more quickly when faced with these new challenges for large-scale applications, such as contingency analysis. This paper proposes a novel big data analysis approach for power system cascading analysis, prevention, and remediation. The developed techniques will be capable of cascading analysis, better assessment of the system’s vulnerability level, as well as proposing potential remediation. Case studies using IEEE 118-bus system and a 500-bus system, with a comparison against a commercial tool, validate the advantages of the developed big data approach: accurate prediction, and more importantly, faster and effective correction actions.The developed techniques could be further used for other power system applications.

big data, cascading analysis, corrective action, m↗

Ion acceleration in impulsive solar flares

Nonrelativistic spectra of protons and ions accelerated in impulsive solar flares are derived using more realistic turbulence power spectra. The calculation is based on a particle transport equation extracted from a second step acceleration model containing stochastic acceleration. The turbulence model is generalized to waves with a small angle to the magnetic field vector and to turbulence power spectra with spectral indices s smaller than 2. Due to the occurrence of impulsive flares at low coronal heights, Coulomb losses at the dense coronal plasma and diffusive particle escape are taken into account. The ion spectra show deviations from long-duration spectra near the Coulomb barrier, where the losses become maximal. The Z-squared/A-dependence of the Coulomb losses leads to spectral variations for different ions. We present a method to estimate the turbulence parameters and injection conditions of the flare particles using ion ratios like Fe/O of impulsive flares.

Steinacker, Jurgen↗

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

PlasmoData.jl — A Julia framework for modeling and analyzing complex data as graphs

Datasets encountered in scientific and engineering applications appear in complex formats (e.g., images, multivariate time series, molecules, video, text strings, networks). Graph theory provides a unifying framework to model such datasets and enables the use of powerful tools that can help analyze, visualize, and extract value from data. In this work, we present PlasmoData.jl, an open-source, Julia framework that uses concepts of graph theory to facilitate the modeling and analysis of complex datasets. The core of our framework is a general data modeling abstraction, which we call a DataGraph. We show how the abstraction and software implementation can be used to represent diverse data objects as graphs and to enable the use of tools from topology, graph theory, and machine learning (e.g., graph neural networks) to conduct a variety of tasks. We illustrate the versatility of the framework by using real datasets: (i) an image classification problem using topological data analysis to extract features from the graph model to train machine learning models; (ii) a disease outbreak problem where we model multivariate time series as graphs to detect abnormal events; and (iii) a technology pathway analysis problem where we highlight how we can use graphs to navigate connectivity. Further, our discussion also highlights how PlasmoData.jl leverages native Julia capabilities to enable compact syntax, scalable computations, and interfaces with diverse packages. Overall, we show that the DataGraph abstraction and PlasmoData.jl Julia package are able to model data within graphs and enable useful analysis.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

High aspect ratio organic light-emitting diodes

Reliability is particularly challenging for organic light-emitting diodes (OLEDs) used in solid-state lighting applications, because OLED lifetime is inversely proportional to luminance, and most lighting applications demand high luminance. Here we introduce a strategy to overcome this tradeoff by constructing OLEDs on a substrate with sub-mm, high aspect ratio surface texture. By creating more active OLED area per unit lighting panel area, the device current density required to generate a given panel luminance decreases. We validate this approach for fluorescent and phosphorescent OLEDs, demonstrating good thickness uniformity on corrugated substrates with area enhancement factors up to 1.4x using a standard thermal evaporator. Relative to planar controls at the same panel current density, the high aspect ratio devices achieve a 2.7-fold increase in operating lifetime and up to a 40% increase in external light extraction efficiency, indicating that this approach offers a powerful pathway to improve the efficiency and lifetime of OLED lighting.

OLED↗

Ab initio electroweak corrections to superallowed β decays and their impact on V ud

Radiative corrections are essential for an accurate determination of V ud from superallowed β decays. In view of recent progress in the single-nucleon sector, the uncertainty is dominated by the theoretical description of nucleus-dependent effects, limiting the precision that can currently be achieved for V ud . In this work, we provide a detailed account of the electroweak corrections to superallowed β decays in effective field theory (EFT), including the power counting, potential and ultrasoft contributions, and factorization in the decay rate. Here, we present a first numerical evaluation of the dominant corrections in light nuclei based on quantum Monte Carlo methods, confirming the expectations from the EFT power counting. Finally, we discuss strategies how to extract from data the low-energy constants that parametrize short-distance contributions and whose values are not predicted by the EFT. Combined with advances in ab initio nuclear-structure calculations, this EFT framework allows one to systematically address the dominant uncertainty in V ud , as illustrated in detail for the 14 O → 14 N transition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The B737 MAX 8 Accidents as Operational Experiences With Automation Transparency

Automation transparency has come into prominence in the human-machine systems literature, with researchers offering definitions, models, design frameworks, and empirical findings. However, missing from the literature are reflections on the actual operational experiences of human crews interacting with intelligent automation conceived from multiple transparency perspectives. The Boeing 737 MAX 8 accidents present a tragic case of a catastrophic failure of automation transparency. We explore this case with an emphasis on extracting design and regulatory insights for the nuclear power and other safety-critical domains.

99 GENERAL AND MISCELLANEOUS↗

Calibration, modeling, parameterization, and verification of the instrument transfer function of an interferometric microscope

Interferometric microscopes are used to measure surface roughness, from which the computed power spectral density function can be used to extract bandwidth-limited values of the various surface properties, such as root-mean-square (rms) height and slope errors. Measurements with a microscope equipped with different objectives that have an overlapping spatial frequency range usually give different rms results over the common frequency bandwidth. This is a result of different instrument transfer functions (ITFs) that attenuate spatial frequencies by different amounts over the overlapping range. We report on the use of binary pseudo-random array (BPRA) standards to characterize the ITF of an interferometric microscope with the various objectives. We use a simple model of a 1D binary Results show that the spectrum for an undersampled array is a cosine function, rather than a straight line, constant white noise spectrum. We have an analytical model of the ITF that includes the effects of an obscured aperture and defocus, in addition to the usual parameters of numerical aperture, wavelength, and sampling period. In addition, the model includes the effect of aliasing of spatial frequency components beyond the Nyquist back into the sub-Nyquist region. We compare the model PSD predictions to the measurements performed with different objectives. Departures of the measured PSDs from the model predictions indicate that there are higher-order ITF corrections yet to be identified and included in the model.

Takacs, PZ↗

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electrically Engaged UnduLation (EEL) Marine Energy System

Current technologies at the forefront of instrumentation for ocean observation through acoustic mapping are powered by batteries that cannot achieve the lasting durations required for high-resolution measurements. Pyro-E has designed an Electrically Engaged unduLation (EEL) system capable of in situ energy harvest and deployment in sub-sea configurations. By extracting kinetic energy from the ocean, EEL proposes to provide power output ranging from 1 mW to 1,000 mW. Such a magnitude of power can sustain active instrumentation with onboard processing of data and over-the-horizon telemetry. Pyro-E and Oak Ridge National Laboratory have utilized software tools and powerful computing resources to develop a techno-economic design of the EEL capable of harvesting 5 W. The material response of the EEL under simulated hydromechanical loads is described through time-accurate predictions. All physical tests were conducted by Pyro-E to guide simulations at Oak Ridge National Laboratory.

16 TIDAL AND WAVE POWER↗

Implementation of a turbine farm model into the Energy Exascale Earth System Model for investigation and quantification of global climate impacts

Although there has been widespread deployment of wind farms in the United States, and plans to continue deployment into the future, the complete effects of wind farms on Earth systems are not well understood. The work performed here has incorporated wind farm models into the Energy Exascale Earth System Model (E3SM) capable of simulating the effects of extracting momentum from the atmospheric flow field using power generating wind farms. This new capability will allow scientists to quantify the impacts of wind farm induced changes on Earth systems by exploiting E3SM’s ability to couple atmospheric, oceanic, and biogeochemical (BGC) models on a global scale and monitor precipitation levels, extreme weather events, soil moisture content and jet stream location over decades-long time periods. This tool will be used to inform decision making on wind farm citing and will contribute to the Lab’s ability to assess energy technology impacts on the environment and evaluate the trade-offs between energy infrastructure investments and their impacts on natural systems.

17 WIND ENERGY↗