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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Stochastic Fault Detection

This entry describes the state-of-the-art and future perspectives on stochastic fault detection, namely, stochastic fault detection and diagnosis (FDD). Both model-based and data-driven FDD methods for stochastic signals and systems have been included, where the use of hypothesis testing, Kalman filtering, system estimation, principal component analysis (PCA), and stochastic distribution control has been discussed for the construction of effective FDD algorithms. Indeed, stochastic FDD constitute an important and integrated part in developing fault-tolerant controls (FTC) for guaranteed safe operation of control systems, of which increased penetration of random factors is inevitable nowadays.

Wang, Aiping↗
DOE OSTI2026

Multiscale modeling of packed-bed microwave reactors and estimation of intrinsic materials' permittivity

Modeling of packed-bed microwave reactors relies on an accurate representation of particle size, shape, and distribution within the bed, as well as the particles' dielectric properties. The measured permittivity of microwave susceptors (powders or structured materials) depends on the geometric features of the particles and the porosity of the bed, as well as the specific form factor of a structured material. These are effective properties and cannot be used to analyze other reactor configurations unless the geometric effects are removed. Therefore, we introduce a methodology for extracting the intrinsic particle permittivity from experimentally measured effective permittivity by combining cavity-based measurements with multiscale simulations and machine learning. Further, we develop the first multiscale model of packed-bed microwave reactors that incorporate particle effects (geometric features, random packing, and particle contact). This approach bridges macroscopic observables with mesoscopic physics, enabling analysis of local hotspots, arcing, and contact effects that control reactor performance. Using polymer-based spherical activated carbon (PBSAC) and silicon carbide (SiC) as examples, we demonstrate that the inferred particle permittivity is consistent with independent experimental heating profiles we collect from microwave reactors without adjustable parameters. Finally, this methodology establishes a foundation for predictive, multiscale design of microwave packed-bed reactors that explicitly accounts for particle-scale effects, enabling the estimation of intrinsic permittivity for the first time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A tool for assessing demand side management and operating strategies for isolated microgrids

Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sensitivity Analysis of Effectiveness of FLEX Strategies Using a CDF-Based Importance Measure Under Accident Conditions

One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Electron Tunneling and X-Ray Photoelectron Spectroscopy Studies of the Superconducting Properties of Nitrogen-Doped Niobium Resonator Cavities

Scanning tunneling microscopy and spectroscopy and X-ray photoelectron spectroscopy (XPS) have been used to investigate the differences between the surface electronic structures and chemical structure of typically prepared and N-doped Nb cutouts from superconducting radio frequency (SRF) cavities. The goal of this work is to get insights into the fundamental physics and materials mechanisms behind the striking decrease of the surface resistance with the radiofrequency magnetic field, which has been observed by many groups on N-doped Nb cavities. In particular, we address the effects of N-doping on the superconducting properties at the surface of SRF cavities. XPS measurements reveal a significantly more oxidized Nb 3d states on the N-doped Nb surfaces which is confirmed by tunneling spectroscopy measurements. Analysis of the tunneling spectra in the framework of a recent model (A. Gurevich and T. Kubo Phys. Rev. B 96, 184515 (2017)) shows that the N-doping greatly reduces local distribution of superconducting properties on the surface, causes a significant shrinkage of the metallic suboxide and changes the contact resistance between the metallic suboxide and the bulk niobium toward an optimum value, resulting in a lower surface resistance. Combination of these factors enables one to effectively tune the density of states at the surface and to reveal the decrease of the surface resistance with the radio frequency field which follows from the BCS theory. A slightly reduced average gap and a smaller coherence length, revealed by tunneling spectroscopy in the vortex cores, have been found in the N-doped Nb samples compared to typically prepared Nb samples, indicating a stronger impurity scattering caused by nitrogen doping in a moderately disordered material.

Lechner, Eric M.↗
DOE OSTI2024

Up and down quark structure of the proton

We report an improved measurement of the valence u and d quark distributions from the forward-backward asymmetry in the Drell-Yan process using 8.6 fb − 1 of data collected with the D0 detector in p p ¯ collisions at s = 1.96 . This analysis provides the values of new structure parameters that are directly related to the valence up and down quark distributions in the proton. In other experimental results measuring the quark content of the proton, d quark contributions are mixed with those from other quark flavors. In this measurement, the u and d quark contributions are separately extracted by applying a factorization of the QCD and electroweak portions of the forward-backward asymmetry. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Light-front wavefunctions of mesons by design

Abstract We develop a mechanism to build the light-front wavefunctions (LFWFs) of meson bound states on a small-sized basis function representation. Unlike in a standard Hamiltonian formalism, the Hamiltonian in this method is implicit, and the information of the system is carried directly by the functional form and adjustable parameters of the LFWFs. In this work, we model the LFWFs for four charmonium states, $$\eta _c$$ η c , $$J/\psi $$ J / ψ , $$\psi '$$ ψ ′ , and $$\psi (3770)$$ ψ ( 3770 ) as superpositions of orthonormal basis functions. We choose the basis functions as eigenfunctions of an effective Hamiltonian, which has a longitudinal confining potential in addition to the transverse confining potential from light-front holographic QCD. We determine the basis function parameters and superposition coefficients by employing both guidance from the nonrelativistic description of the meson states and the experimental measurements of the meson decay widths. With the obtained wavefunctions, we study the features of those meson states, including charge radii and parton distribution functions. We use the $$J/\psi $$ J / ψ LFWF to calculate the meson production in diffractive deep inelastic scattering and ultra-peripheral heavy-ion collisions, and the $$\eta _c$$ η c LFWF to calculate its diphoton transition form factor. Both results show good agreement with experiments. The obtained LFWFs have simple-functional forms and can be readily used to predict additional experimental observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

The environmental impact, carbon emissions and sustainability of computing in the ATLAS experiment

ATLAS, a general-purpose experiment at the Large Hadron Collider (LHC), makes use of a large internationally-distributed computing infrastructure, including over 10 6 TB of managed data on disk and tape and almost one million simultaneously running CPU cores. Upgrades for the High-Luminosity LHC (HL-LHC) will increase the required computing resources by a factor of 3–4 by the beginning of the 2030s, and by an order of magnitude before the conclusion of data taking at the beginning of the 2040s. These resources are spread over around 100 computing sites worldwide. Efforts are underway within the experiment to evaluate and mitigate various aspects of the environmental impact of the sites, with the additional long-term goal of making recommendations to the sites that will significantly reduce the total expected environmental impact in the HL-LHC era. These efforts take several forms: building awareness in the experiment community, adjusting aspects of the computing policy, and modifications of data center configurations, either in ways that take advantage of particular features of ATLAS workloads or in generic ways that reduce the environmental impact of the computing resources. This paper describes the ongoing investigations and approaches that have already provided useful and actionable outcomes.

Aad, G. [CNRS/IN2P3] (ORCID:0000000266654934)↗
DOE OSTI2022

Atypical Carboxysome Loci: JEEPs or Junk?

Carboxysomes, responsible for a substantial fraction of CO 2 fixation on Earth, are proteinaceous microcompartments found in many autotrophic members of domain Bacteria, primarily from the phyla Proteobacteria and Cyanobacteria. Carboxysomes facilitate CO 2 fixation by the Calvin-Benson-Bassham (CBB) cycle, particularly under conditions where the CO 2 concentration is variable or low, or O 2 is abundant. These microcompartments are composed of an icosahedral shell containing the enzymes ribulose 1,5-carboxylase/oxygenase (RubisCO) and carbonic anhydrase. They function as part of a CO 2 concentrating mechanism, in which cells accumulate HCO 3 - in the cytoplasm via active transport, HCO 3 - enters the carboxysomes through pores in the carboxysomal shell proteins, and carboxysomal carbonic anhydrase facilitates the conversion of HCO 3 - to CO 2 , which RubisCO fixes. Two forms of carboxysomes have been described: α-carboxysomes and β-carboxysomes, which arose independently from ancestral microcompartments. The α-carboxysomes present in Proteobacteria and some Cyanobacteria have shells comprised of four types of proteins [CsoS1 hexamers, CsoS4 pentamers, CsoS2 assembly proteins, and α-carboxysomal carbonic anhydrase (CsoSCA)], and contain form IA RubisCO (CbbL and CbbS). In the majority of cases, these components are encoded in the genome near each other in a gene locus, and transcribed together as an operon. Interestingly, genome sequencing has revealed some α-carboxysome loci that are missing genes encoding one or more of these components. Some loci lack the genes encoding RubisCO, others lack a gene encoding carbonic anhydrase, some loci are missing shell protein genes, and in some organisms, genes homologous to those encoding the carboxysome-associated carbonic anhydrase are the only carboxysome-related genes present in the genome. Given that RubisCO, assembly factors, carbonic anhydrase, and shell proteins are all essential for carboxysome function, these absences are quite intriguing. In this review, we provide an overview of the most recent studies of the structural components of carboxysomes, describe the genomic context and taxonomic distribution of atypical carboxysome loci, and propose functions for these variants. We suggest that these atypical loci are JEEPs, which have modified functions based on the presence of Just Enough Essential Parts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Blazars at the Cosmic Dawn

The uncharted territory of the high-redshift (z ≳ 3) universe holds the key to understanding the evolution of quasars. In an attempt to identify the most extreme members of the quasar population, that is, blazars, we have carried out a multiwavelength study of a large sample of radio-loud quasars beyond z = 3. Our sample consists of nine γ-ray-detected blazars and 133 candidate blazars selected based on the flatness of their soft X-ray spectra (0.3–10 keV photon index $\leqslant$ 1.75), including 15 with Nuclear Spectroscopic Telescope Array (NuSTAR) observations. The application of the likelihood profile stacking technique reveals that the high-redshift blazars are faint γ-ray emitters with steep spectra. The high-redshift blazars host massive black holes ($\langle$log M BH , M$\bigodot$ $\rangle$> 9) and luminous accretion disks ($\langle$L disk $\rangle$ > 10 46 erg s -1 ). Their broadband spectral energy distributions are found to be dominated by high-energy radiation, indicating their jets are among the most luminous ones. Focusing on the sources exhibiting resolved X-ray jets (as observed with the Chandra satellite), we find the bulk Lorentz factor to be larger with respect to other z > 3 blazars, indicating faster moving jets. In this paper, we conclude that the presented list of high-redshift blazars may act as a reservoir for follow-up observations, such as with NuSTAR, to understand the evolution of relativistic jets at the dawn of the universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Medium-Voltage Testbed for Comparing Advanced Power Line Sensors vs. Measurement Transformers with Electrical Grid Events

Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medi-um-voltage sensor is compared with a reference PT and CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the US De-partment of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with integrator for current monitoring. The advanced outdoor power line sensor testbed has a real-time simulator that was used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, service restoration), while the analog signals were recorded by the same high resolution power meter. The behavior of analog signals, harmonic components, total harmonic distortion, and crest factors were assessed for this power line sensor compared with the reference PT/CT, because of the absence for testing standards for advanced outdoor power line sensors.

Piesciorovsky, Emilio↗
DOE OSTI2024

Data assimilation for combustion ignition delay time simulation using schlieren image velocimetry

This study sought to improve the accuracy of simulating spray penetration and combustion ignition delay by means of data assimilation (DA). The simulations were conducted using the Reynolds-averaged Navier–Stokes (RANS) equations and assimilating the schlieren image data. In DA, an ensemble square root filter (EnSRF) was used to build the statistical model, making the simulation results more accurate without any change in the governing equations. Recognizing that the spray-cone injection angle has a large effect on penetration, we created ensemble members with different injection angles. And we applied the two-component velocity distribution calculated via SIV and updated both velocity and temperature by using a DA statistical model derived from RANS ensemble simulations. The ignition delay time is generally known to vary even under the same experimental conditions because it is influenced by many factors. In this study, we attempted the transient DA-assisted RANS simulation to predict the ignition delay time even when the temporal resolution and accuracy of the observation data ware insufficient. Our trials offer an example of how a combination of techniques can be effectively used to assimilate experimental data obtained under restricted conditions.

Combustion simulation↗
DOE OSTI2021

Tuning successive linear programming to solve AC optimal power flow problem for large networks

Successive linear programming (SLP) is a practical approach for solving large-scale nonlinear optimization problems. Alternating current optimal power flow (ACOPF) is no exception, particularly the large size of real-world networks. However, in order to achieve tractability, it is essential to tune the SLP algorithm presented in the literature. This paper presents a modified SLP algorithm to solve the ACOPF problem, specified by the U.S. Department of Energy’s (DOE) Grid Optimization (GO) Competition Challenge 1, within strict time limits. The algorithm first finds a near-optimal solution for the relaxed problem (i.e., Stage 1). Then, it finds a feasible solution in the proximity of the near-optimal solution (i.e., Stage 2 and Stage 3). The numerical experiments on test cases ranging from 500-bus to 30,000-bus systems show that the algorithm is tractable. Here the results show that our proposed algorithm is tractable and can solve more than 80% of test cases faster than the well-known Interior Point Method while significantly reduce the number of iterations required to solve ACOPF. The number of iterations is considered an important factor in the examination of tractability which can drastically reduce the computational time required within each iteration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Observationally Constrained Modeling of the Reactive Uptake of Isoprene-Derived Epoxydiols under Elevated Relative Humidity and Varying Acidity of Seed Aerosol Conditions

Isoprene is the non-methane volatile organic compound (VOC) emitted in largest amounts to the atmosphere, and it is a significant source of secondary organic aerosol (SOA) mass. The uptake of isoprene oxidation products followed by multiphase chemistry in fine particles is the key pathway to form isoprene epoxydiol-derived SOA (IEPOX-SOA). However, many parameters that relate to diffusion and reaction of IEPOX in the particle phase remain uncertain, since reaction kinetics previously measured in bulk aqueous phase solutions might be different from atmospheric aerosols. Here, we use simultaneous environmental chamber measurements of multiple parameters governing IEPOX-SOA formation at timescales of ~hours: particle size distribution, composition, and volatility of IEPOX-SOA to constrain the key parameters governing IE-POX-SOA formation under humid (i.e., 50% relative humidity, RH) and varying seed aerosol acidity conditions. Reducing the 2-methyltetrol (tetrol) reaction rate constants by a factor of 4 brings the model predictions in agreement with the IEPOX-SOA measurements with acidified ammonium bisulfate seed aerosols. For less acidic ammonium sulfate aerosols both the organo-sulfate (OS) and tetrol reaction rate constants need to be reduced to bring model predictions closer to chamber observations. Using the measured non-volatile content of IEPOX-SOA we constrain the oligomerization timescale of 2-methyltetrols. We find that the oligomerization timescale is 4 hours with acidified seed aerosols, but a much longer time scale of 24 hours is needed for non-acidified seed aerosols, indicating that the aerosol acidity greatly affects the oligomerization rate of tetrols. Here we show that the actual kinetics of IEPOX-SOA formation rate on aerosol seeds consisting of both ammonium bisulfate and ammonium sulfate are a factor of 4~5 slower under 50-60% RH conditions compared to their application in previous models, which were based on bulk aqueous solution measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Atomic Three-Dimensional Investigations of Pd Nanocatalysts for Acetylene Semi-hydrogenation

Deciphering the three-dimensional (3D) insight into nanocatalyst surfaces at the atomic level is crucial to understanding catalytic reaction mechanisms and developing high-performance catalysts. Nevertheless, better understanding the inherent insufficiency of a long-range ordered lattice in nanocatalysts is a big challenge. Here, in this work, we report the local structure of Pd nanocatalysts, which is beneficial for demonstrating the shape-structure-adsorption relationship in acetylene hydrogenation. The 5.27 nm spherical Pd catalyst (Pd sph ) shows an ethylene selectivity of 88% at complete acetylene conversion, which is much higher than those of the Pd octahedron and Pd cube and superior to other reported monometallic Pd nanocatalysts so far. By virtue of the local structure revelation combined with the atomic pair distribution function (PDF) and reverse Monte Carlo (RMC) simulation, the atomic surface distribution of the unique compressed strain of Pd-Pd pairs in Pd sph was revealed. Density functional theory calculations verified the obvious weakening of the ethylene adsorption energy on account of the surface strain of Pd sph . It is the main factor to avoid the over-hydrogenation of acetylene. The present work, entailing shape-induced surface strain manipulation and atomic 3D insight, opens a new path to understand and optimize chemical activity and selectivity in the heterogeneous catalysis process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Serpent and MCNP Calculations of the Energy Deposition in the Transformational Challenge Reactor

This paper focuses on the calculation of the energy deposition in the Transformational Challenge Reactor by two major Monte Carlo codes: Serpent and MCNP. The first software computation relies on Kinetic Energy Released per unit Mass (KERMA) factors while the second one relies on Q-values. The results from these two independent computation methodologies are in very good agreement; however, Serpent runs much faster than MCNP (for the same computational model) and allows for a detailed energy deposition distribution from a 1-mm-side square mesh with a relative statistical error between 0.5% and 1%. This detailed energy deposition is suitable for multiphysics analyses aimed at design optimizations. In order to calculate the energy deposition, Serpent needs enhanced ACE files (distributed by the software developers). Unlike other Monte Carlo software that uses inputs based on Python or Java languages, the Serpent input syntax is very similar to that of MCNP; a Python script can convert a MCNP input to a Serpent input in seconds. For simulations not requiring the calculation of the energy deposition, Serpent can also read nuclear data from MCNP ACE files, which eventually improves the comparison of the results of the two codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Measurement of the branching fraction of the decay B − → D 0 ρ ( 770 ) − at Belle II

We measure the branching fraction of the decay B − → D 0 ρ ( 770 ) − using data collected with the Belle II detector. The data contain 387 million B B ¯ pairs produced in e + e − collisions at the ϒ ( 4 S ) resonance. We reconstruct 8360 ± 180 decays from an analysis of the distributions of the B − energy and the ρ ( 770 ) − helicity angle. We determine the branching fraction to be ( 0.939 ± 0.021 ( stat ) ± 0.050 ( syst ) ) % , in agreement with previous results. Our measurement improves the relative precision of the world average by more than a factor of two. Published by the American Physical Society 2024

Astronomy & Astrophysics↗