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At least 1,423 records · Page 79

Application of a First-Principles Anomalous Transport Model for Electrons to Multiple Hall Thrusters and Operating Conditions

We have developed a physics-based model based on a pseudo-particle description of the electron cyclotron drift instability. A key improvement of the model with respect to previous work is that linear theory is not applied in the event of wave saturation and deviations of electrons or ions from a Maxwellian distribution function. In the acceleration region, the anomalous collision frequency is computed as the minimum value necessary to prevent the electron drift velocity from exceeding the thermal velocity. A functional based on the electron equilibration time is defined to control the transition from high to low resistivity regions. The model was previously applied to a single Hall thruster at its nominal operating condition, showing promising results that captured accurately the location of the thruster’s acceleration region. In this paper, we extend the use of this firstprinciples models to two additional thrusters, also considering multiple operating conditions for each of them. Numerical results are compared to experimental measurements obtained with non-invasive laser induced fluorescence. In general, the agreement between experiments and simulations is good. The model is able to predict the location of the acceleration region for all cases. We observe however that fine details, such as changes in the plasma potential gradient within the acceleration regions, are not captured. The model is also insensitive to changes in the magnetic field strength while experiments show that small shifts in location (of less than 5% of the acceleration channel length) occur. We plan to address the weaknesses of our method with the help of physical insight gained from kinetic simulations of the acceleration region.

Chaplin, Vernon H.↗

E-Beam Irradiation Beamline at Jefferson Lab for Wastewater Treatment

Electron beam (e-beam) irradiation is an advanced method for removing the emerging organic contaminants in wastewater, such as 1,4-dioxane, and per- and polyfluoroalkyl sub?stances (PFAS), which have the potential to be regulated in the near future but are difficult to degrade by conventional treatment methods. This dissertation was based on a collabo?rating study between Jefferson Lab (Jlab) and Hampton Roads Sanitation District (HRSD) to evaluate the impacts of e-beam irradiation on the degradation of 1,4-dioxane and PFAS. It presents the detailed design of an e-beam irradiation beamline, the beamline simulation using general particle tracer (GPT), the installation, and the successful commissioning. The beamline is an extended section to the Upgraded Injector Test Facility (UITF) at Jlab, which is a continuous wave (CW), superconducting radio frequency (SRF) linear accelerator with an energy up to 10 MeV. To let the sample volume receive a significant and uniform dose distribution, the sample target was designed by investigating the dose distribution simulated with a Monte-Carlo code, FLUKA. The optimized beam energy was 8 MeV and the beam current for irradiation was ? 100 nA. With the use of a solenoid and a raster, the electron beam was expanded to the optimized size, 1? ? 15 mm, at the sample target. This dis?sertation also presents the irradiation experiments for 64 1,4-dioxane samples and 48 PFAS samples in different water matrices, including real wastewater, which were prepared and an?alyzed by HRSD. The absorbed doses of samples were obtained by designing a new method that combines the FLUKA simulation and dose mapping experiments. The irradiation re?sults showed that around 95% of 1,4-dioxane was removed at a low dose of ? 2 kGy, and PFAS was possibly removed at a lower dose compared to similar research. This work is a first implementation of SRF technology for wastewater irradiation. It pro?vides a valuable new research platform for wastewater remediation. This will be in support of future industrial applications of advanced SRF technologies and better understanding of the effect of e-beam irradiation on wastewater or water treatment.

Li, Xi↗

Projective Integral Updates for High-Dimensional Variational Inference

Variational inference is an approximation framework for Bayesian inference that seeks to improve quantified uncertainty in predictions by optimizing a simplified distribution over parameters to stand in for the full posterior. Capturing model variations that remain consistent with training data enables more robust predictions by reducing parameter sensitivity. This work introduces a fixed-point optimization for variational inference that is applicable when every feasible log density can be expressed as a linear combination of functions from a given basis. In such cases, the optimizer becomes a fixed-point of projective integral updates. When the basis spans univariate quadratics in each parameter, the feasible distributions are Gaussian mean-fields and the projective integral updates yield quasi-Newton variational Bayes (QNVB). Other bases and updates are also possible. Since these updates require high-dimensional integration, this work begins by proposing an efficient quasirandom sequence of quadratures for mean-field distributions. Each iterate of the sequence contains two evaluation points that combine to correctly integrate all univariate quadratic functions and, if the mean-field factors are symmetric, all univariate cubics. More importantly, averaging results over short subsequences achieves periodic exactness on a much larger space of multivariate polynomials of quadratic total degree. The corresponding variational updates require four loss evaluations with standard (not second-order) backpropagation to eliminate error terms from over half of all multivariate quadratic basis functions. Furthermore, this integration technique is motivated by first proposing stochastic blocked mean-field quadratures, which may be useful in other contexts. A PyTorch implementation of QNVB allows for better control over model uncertainty during training than competing methods. Experiments demonstrate superior generalizability for multiple learning problems and architectures.

Gaussian mean-field↗

On-Sun Testing of a High-Temperature Solar Receiver's Flux Distribution

Concentrated solar power (CSP) is a promising technology in transitioning to renewable energy because of its abundance in nature and thermal energy storage (TES) capability. Among the four types of available CSP technology, including parabolic trough, linear Fresnel, power tower, and parabolic dishes, a power tower using a central receiver has more potential to generate high-temperature heat in a scale supporting power cycles efficiency and achieve low levelized cost of energy (LCOE). Other than the conventional type of receiver design, the high-absorptive receiver concept developed and presented in this paper is novel in its design approach. The novel receiver design originated from National Renewable Energy Laboratory (NREL) consists of an array of solar flux absorb tubes. The solar absorb tubes require uniform flux distribution and in-depth flux penetration through the three different reflective sections of tubes in a hexagonal shape. To evaluate this unique receiver design and thermal performance, the flux distribution, flux uniformity, and intensity were numerically simulated using ansys fluent and SolTrace modeling program. On-sun testing has been done at NREL high flux solar testing facility, based on the computational analysis.

clean energy↗

Evaluating Lyman- α constraints for general dark-matter velocity distributions: Multiple scales and cautionary tales

One of the most important observational constraints on possible models of dark-matter physics exploits the Lyman-α absorption spectrum associated with photons traversing the intergalactic medium. Because these data allow us to probe the linear matter power spectrum with great accuracy down to relatively small distance scales, finding ways of accurately evaluating such Lyman-α constraints across large classes of candidate models of dark-matter physics is of paramount importance. While such Lyman-α constraints have been evaluated for dark-matter models that give rise to relatively simple dark-matter velocity distributions, more complex models—particularly those whose dark-matter velocity distributions stretch across multiple scales—have recently been receiving increasing attention. In this paper, we undertake a study of the Lyman-α constraints associated with general dark-matter velocity distributions. Although such Lyman-α constraints are difficult to evaluate in principle, in practice there currently exist two classes of methods in the literature through which such constraints can be recast into forms which are easier to evaluate and which therefore allow a more rapid determination of whether a given dark-matter model is ruled in or out. Accordingly, we utilize both of these recasts in order to determine the Lyman-α bounds on different classes of dark-matter velocity distributions. Here we also develop a general method by which the results of these different recasts can be compared. For relatively simple dark-matter velocity distributions, we demonstrate that these two classes of recasts tend to align and give similar results. However, we find that the situation is far more complex for distributions involving multiple velocity scales: while these two classes of recasts continue to yield similar results within certain regions of parameter space, they nevertheless yield dramatically different results within precisely those regions of parameter space which are likely to be phenomenologically relevant. This, then, serves as a cautionary tale regarding the use of such recasts for complex dark-matter velocity distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

A Reduced Order Model of the Linearized Incompressible Navier-Strokes Equations for the Sensor/Actuator Placement Problem

A reduced order modeling approach of the Navier-Stokes equations is presented for the design of a distributed optimal feedback kernel. This approach is based oil a Krylov subspace method where significant modes of the flow are captured in the model This model is then used in all optimal feedback control design where sensing and actuation is performed oil tile entire flow field. This control design approach yields all optimal feedback kernel which provides insight into the placement of sensors and actuators in the flow field. As all evaluation of this approach, a two-dimensional shear layer and driven cavity flow are investigated.

Allan, Brian G.↗

Gamma rays and large scale galactic structure

Gamma ray astronomy is now beginning to provide a new look at the galactic structure and the distribution of cosmic rays, both electrons and nucleons, within the galaxy. The observations are consistent with a galactic spiral-arm model in which the cosmic rays are linearly coupled to the interstellar gas on the scale of the spiral arms. The agreement between the predictions of the model and the observations for regions of the plane where both 21-cm and 2.6-mm CO surveys exist emphasizes the need to extend these observations to include the entire plane. Future gamma-ray observations with more sensitivity and better angular resolutions, combined with these radio surveys, should shed new light on the distribution of cosmic rays, the nature of the galaxy, and the location and intensity of the spiral arms.

Kniffen, D. A.↗

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity-enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb-and-observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. Comparison results with other control methods on a real distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resource management↗

Quantitative assessment of the influence of external magnetic field on clustering of nano-Fe3O4 particles in cementitious paste

In view of active rheology control of cementitious materials, nano-Fe{sub 3}O{sub 4} can be added as responsive particles. Following the concept of magnetorheological fluids, it is assumed that magnetic nanoparticles will form chains or clusters in cementitious paste following magnetic field lines. A quantitative experimental validation of this assumption is presented herein. The clustering of nano-Fe{sub 3}O{sub 4} particles under magnetic fields is studied by mapping iron (Fe) element distribution in cementitious paste using energy dispersive X-ray spectroscopy. By means of image analysis, the Fe-element patterns are quantified by the deviation of Fe-elements in a unit area from the mean value expected in case of a uniform distribution, as expressed by coefficient of variation (COV). The magneto-rheological responses of cementitious pastes are evaluated using small amplitude oscillatory shear technique. Results show that the magneto-rheological effect exhibits a linear relationship with the relative change of COV, providing a quantitative validation of magnetic clustering in cementitious paste.

36 MATERIALS SCIENCE↗

Role of deep levels and barrier height lowering in current-flow mechanism in 150 μ m thick epitaxial n-type 4H–SiC Schottky barrier radiation detectors

Schottky barrier detectors (SBDs) require larger surface areas than conventional electronics to increase the detection efficiency although such SBDs manifest large diode ideality factors due to inhomogeneous areal distribution of surface barrier height (SBH). Inhomogeneous SBH distributions lead to various current flow mechanisms in SBDs, which need to be identified to optimize detector performance. In this Letter, we identify the current flow mechanism in large area Schottky barrier diodes for radiation detection fabricated on 150 μm thick n-4H–SiC epitaxial layers. The analysis of temperature-dependent forward current–voltage (I–V–T) characteristics of SBDs revealed two linear regions in current–voltage curves up to 450 K, one corresponding to the current flow through a low barrier patch, while the other corresponds to that of average barrier distribution. Applying a SBH distribution model to the reverse I–V–T characteristics, an activation energy of 0.76 eV for the current flow over the Schottky barrier was calculated. Additionally, the activation energy did not directly correspond to any of the defect levels observed from the deep level transient spectroscopy (DLTS). Above 450 K, a Schottky type barrier lowering suggested a current flow through a low barrier patch of ≈ 0.8 eV. The absence of any SBH lowering below 450 K indicated that the current corresponded to a neutrally charged trap level at ≈ 0.6 eV below the conduction band edge, which was consistent with DLTS measurements revealing the presence of an electron trap level Z1/2 at 0.59 eV below the conduction band edge.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Distribution of centrality measures on undirected random networks via the cavity method

The Katz centrality of a node in a complex network is a measure of the node’s importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically because of its “global” character and its definition in terms of a matrix inverse. Leveraging a fast Gaussian Belief Propagation-Cavity algorithm to solve linear systems on tree-like structures, we show that i) the Katz centrality of a single instance can be computed recursively in a very fast way, and ii) the probability P ( K ) that a random node in the ensemble of undirected random graphs has centrality K satisfies a set of recursive distributional equations, which can be analytically characterized and efficiently solved using a population dynamics algorithm. We test our solution on ensembles of Erdős-Rényi and Scale Free networks in the locally tree-like regime, with excellent agreement. The analytical distribution of centrality for the configuration model conditioned on the degree of each node can be employed as a benchmark to identify nodes of empirical networks with over- and underexpressed centrality relative to a null baseline. We also provide an approximate formula based on a rank- 1 projection that works well if the network is not too sparse, and we argue that an extension of our method could be efficiently extended to tackle analytical distributions of other centrality measures such as PageRank for directed networks in a transparent and user-friendly way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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↗

Cold dark matter. 1: The formation of dark halos

We use numerical simulations of critically closed cold dark matter (CDM) models to study the effects of numerical resolution on observable quantities. We study simulations with up to 256(exp 3) particles using the particle-mesh (PM) method and with up to 144(exp 3) particles using the adaptive particle-particle-mesh (P3M) method. Comparisons of galaxy halo distributions are made among the various simulations. We also compare distributions with observations, and we explore methods for identifying halos, including a new algorithm that finds all particles within closed contours of the smoothed density field surrounding a peak. The simulated halos show more substructure than predicted by the Press-Schechter theory. We are able to rule out all omega = 1 CDM models for linear amplitude sigma(sub 8) greater than or approximately = 0.5 because the simulations produce too many massive halos compared with the observations. The simulations also produce too many low-mass halos. The distribution of halos characterized by their circular velocities for the P3M simulations is in reasonable agreement with the observations for 150 km/s less than or = V(sub circ) less than or = 350 km/s.

Gelb, James M.↗

Assessing Dynamic Behaviors in Converter- Dominated Power Systems via RMS and EMT Simulations: A Study of Hawaii’s NELHA Microgrid

The transition from conventional power systems to converter-based microgrids has significantly advanced sustainability, clean energy integration, and operational reliability. However, this paradigm shift introduces operational challenges due to the intermittent nature of renewable energy sources and the non-linear characteristics of power electronic loads, inducing voltage fluctuations and harmonic distortions that complicate voltage and frequency regulation. Accurate dynamic modeling is hypothesized to be critical for capturing such effects, enabling reliable simulation and control strategy development. This study introduces an innovative dynamic modeling framework for a real-world converter-based microgrid, utilizing both root mean square (RMS) and electromagnetic transient (EMT) simulation methods. The microgrid was modeled in DIgSILENT PowerFactory, with simulations calibrated against high-resolution field measurements from SEL-735 power quality meters. Results show that RMS simulations effectively characterize steady-state dynamics, while EMT simulations are essential for capturing high-frequency transients and non-linear effects from photovoltaic inverters and variable frequency drives (VFDs). This complementary approach provides a comprehensive understanding of microgrid behavior, providing critical insights for improving simulation accuracy, advancing protection schemes, and improving resilience in future low-inertia power networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework: Preprint

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb and observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. The proposed DERMS online platform is generalizable to deal with various types of distributed energy resources (DERs), including distributed photovoltaics (PVs), energy storage, electric vehicles, demand response, etc. Comparison results with other control methods on a realistic distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resources management↗

First-Principles Simulations of CuCl in High-Temperature Water Vapor

Experimental data suggest that the solubility of copper in high-temperature water vapor is controlled by the formation of hydrated clusters of the form CuCl(H 2 O) n , where the average number of water molecules in the cluster generally increases with increasing density [Migdisov, A. A.; et al. Geochim. Cosmochim. Acta2014, 129, 33–53]. However, the precise nature of these clusters is difficult to probe experimentally. Moreover, there are some discrepancies between experimental estimates of average cluster size and prior simulation work [Mei, Y. Geofluids2018, 2018, 4279124]. Here, we have performed first-principles Monte Carlo (MC) and molecular dynamics (MD) simulations to explore these clusters in finer detail. We find that molecular dynamics is not the most appropriate technique for studying aggregation in vapor phases, even at relatively high temperatures. Specifically, our MD simulations exhibit substantial problems in adequately sampling the equilibrium cluster size distribution. In contrast, MC simulations with specialized cluster moves are able to accurately sample the phase space of hydrogen-bonding vapors. At all densities, we find a stable, slightly distorted linear H 2 O–Cu–Cl structure, which is in agreement with the earlier simulations, surrounded by a variable number of water molecules. The surrounding water molecules do not form a well-defined second solvation shell but rather a loose network of hydrogen-bonded water with molecular CuCl on the outside edge of the water cluster. We also find a broad distribution of hydration numbers, especially at higher densities. In contrast to previous simulation work but in agreement with experimental data, we find that the average hydration number substantially increases with increasing density. Moreover, the value of the hydration number depends on the choice of cluster definition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sequential Perturbation-based FDIA Detection using DERs for Unbalanced Distribution System

The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.

Attack Detection↗

Venus tectonics - Initial analysis from Magellan

The styles of lithospheric deformation, the inferred mechanical properties of the lithosphere, and their implications for the tectonic history of Venus are discussed on the basis of radar imaging and altimetry data from Magellan. Observations of the planet plains reveal a superposition of different episodes of deformation and volcanism, strain both distributed and concentrated into zones of extension and shortening, and features reflecting a crustal response to mantle dynamic processes. Lithospheric shortening and crustal thickening are represented by ridge belts and mountain belts. The latter show the evidence for extension and collapse both during and following crustal compression. Venus displays quasi-circular coronae and broad rises with linear rift zones, associated with significant volcanism. Large-offset strike-slip faults have not been observed, although horizontal shear is accommodated across broad zones of crustal shortening. On Venus strain is distributed across zones that are one to a few hundred kilometers wide, and separated by stronger and less deformed blocks hundreds of kilometers in width, as in actively deforming continental regions on earth.

Solomon, Sean C.↗