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At least 613 records · Page 34

Simulations and analysis tools for charge-exchange (d, 2 He) reactions in inverse kinematics with the AT-TPC

Charge-exchange (d, 2 He) reactions in inverse kinematics at intermediate energies are a very promising method to investigate the Gamow–Teller transition strength in unstable nuclei. A simulation and analysis software based on the attpcroot package was developed to study this type of reactions with the active-target time projection chamber (AT-TPC). The simulation routines provide a realistic detector response that can be used to understand and benchmark experimental data. Analysis tools and correction routines can be developed and tested from simulations in ATTPCROOT , because they are processed in the same way as the real data. In particular, we study the feasibility of using coincidences with beam-like particles to unambiguously identify the (d, 2 He) reaction channel, and to develop a kinematic fitting routine for future applications. More technically, the impact of space-charge effects in the track reconstruction, and a possible correction method are investigated in detail. Finally, this analysis and simulation package constitutes an essential part of the software development for the fast-beams program with the AT-TPC.

(d,2He)↗

Robust atom optics for Bragg atom interferometry

Multi-photon Bragg diffraction is a powerful method for fast, coherent momentum transfer of atom waves. However, laser noise, Doppler detunings, and cloud expansion limit its efficiency in large momentum transfer (LMT) pulse sequences. We present simulation studies of robust Bragg pulses developed through numerical quantum optimal control. Optimized pulse performance under noise and cloud inhomogeneities is analyzed and compared to analogous Gaussian and adiabatic rapid passage pulses in simulated LMT Mach–Zehnder interferometry sequences. The optimized pulses maintain robust population transfer and phase response over a broader range of noise, resulting in superior contrast in LMT sequences with thermal atom clouds and intensity inhomogeneities. Large optimized LMT sequences use lower pulse area than Gaussian pulses, making them less susceptible to spontaneous emission loss. The optimized sequences maintain over five times better contrast with tens of momentum separation and offer more improvement with greater LMT. Such pulses could allow operation of Bragg atom interferometers with unprecedented sensitivity, improved contrast, and hotter atom sources.

74 ATOMIC AND MOLECULAR PHYSICS↗

Classical field approximation of ultralight dark matter: Quantum break times, corrections, and decoherence

The classical field approximation is widely used to better understand the predictions of ultralight dark matter. Here, in this work, we use the truncated Wigner approximation method to test the classical field approximation of ultralight dark matter. This method approximates a quantum state as an ensemble of independently evolving realizations drawn from its Wigner function. The method is highly parallelizable and allows the direct simulation of quantum corrections and decoherence times in systems many times larger than have been previously studied in reference to ultralight dark matter. Our study involves simulation of systems in 1, 2, and 3 spatial dimensions. We simulate three systems, the condensation of a Gaussian random field in three spatial dimensions, a stable collapsed object in three spatial dimensions, and the merging of two stable objects in two spatial dimensions. We study the quantum corrections to the classical field theory in each case. We find that quantum corrections grow exponentially during nonlinear growth with the timescale being approximately equal to the system dynamical time. In stable systems the corrections grow quadratically. We also find that the primary effect of quantum corrections is to reduce the amplitude of fluctuations on the de Broglie scale in the spatial density. Finally, we find that the timescale associated with decoherence due to gravitational coupling to baryonic matter is at least as fast as the quantum corrections due to gravitational interactions. These results are consistent with the predictions of the classical field theory being accurate.

79 ASTRONOMY AND ASTROPHYSICS↗

Opening twisted polymer chains for simultaneously high printability and battery fast-charge

Fast-charging is key to the widespread adoption of battery-based electric vehicles. However, improving fast-charging through architecture optimization is expensive. To reduce costs and expand to commercialization, we applied roll-to-roll screen printing technology to create channels and decrease the tortuosity of electrodes. For the first time, this work successfully opened twisted polymer chains within high-solid-content inks to improve their screen printability and battery performance of as-printed electrodes. With LiNi 0.6 Mn 0.2 Co 0.2 O 2 as active materials, the 60% solid content ink presents superior screen printability after opening the twisted binder chains. As-printed electrode exhibits 33% higher charge capacity at 6 C than printed electrode with chains twisted ink at mass loading of 6.5 mg/cm 2 . Furthermore, coarse-grained molecular dynamics simulations are performed to study the underlying mechanism systematically. In conclusion, the new ink preparation procedure provides a scalable, effective strategy for manufacturing screen-printable battery ink and promotes screen-printed electrode technology.

25 ENERGY STORAGE↗

Demonstrating the data center as a flexible grid asset using a C-HIL setup

Increasing data center demand is outpacing grid infrastructure development. Artificial intelligence workloads and hyperscale cloud growth are creating unprecedented demand for power, while traditional grid expansion faces multiyear development timelines. Verrus is developing an innovative datacenter solution for this challenge, data centers that act as active grid-supportive assets rather than passive loads. Our approach integrates a novel grid-aware power flow management system with battery energy storage systems(BESS) into a microgrid-controlled, medium-voltage power distribution architecture that delivers critical capabilities, such as: * Fast response to grid disturbances such over/ under voltage or over/ under frequency * Demand flexibility that can service requests from the utility within 10 s * Uninterrupted transition to islanded operation during grid outages * Continuous uptime assurance for compute loads while maintaining all customer service level agreements. Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), these capabilities were validated using NREL's Advanced Research on Integrated Energy Systems (ARIES) virtual emulation environment to model a 70-MW grid-interactive data center. This paper outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can provide both critical load resilience and ancillary grid support without compromising uptime requirements. Specifically, we present a digital real time simulation of a 70 MW data center integrated with a physical microgrid controller, and demonstrate the data center response in the event of a grid voltage and frequency event, utility demand response request and utility outage.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Whistler waves generated by nongyrotropic and gyrotropic electron beams during asymmetric guide field reconnection

Using a two-dimensional particle-in-cell simulation of asymmetric reconnection with a guide field whose strength is 0.3 times the reconnecting magnetic field, we study electron distribution functions and wave intensities in the diffusion region, focusing on the electron diffusion region (EDR). Wave activities with frequencies below the electron cyclotron frequency are observed, and these are whistler waves propagating almost anti-parallel to the magnetic field. The waves are concentrated near the magnetospheric separatrix away from the X line, but the wave activity also spreads through the EDR near the X line. The reconnection outflows are asymmetric in the outflow direction in the magnetospheric side, and the wave intensity is stronger in the side of the faster electron outflow. We study the whistler waves using the fast Fourier transform, analyses of electron velocity distribution functions, and the dispersion solver calculation. Along the magnetospheric separatrix in the stronger outflow side, highly anisotropic electron beams exist with super-Alfvénic drift speeds. The dispersion analysis shows that there are two modes: a temperature anisotropy mode and a beam mode. Outside the EDR, the whistler wave intensity is highest near the separatrix, but the wave intensity decreases if we move away from the separatrix toward the magnetic neutral line because of the increase in the electron population near zero parallel velocity. In the EDR, in the velocity plane perpendicular to the magnetic field, ring/crescent electron distribution functions are observed. Near the X-line, the wave power is enhanced where nongyrotropic electrons contribute to increase the perpendicular temperature anisotropy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Octofitter: Fast, Flexible, and Accurate Orbit Modeling to Detect Exoplanets

As next-generation imaging instruments and interferometers search for planets closer to their stars, they must contend with increasing orbital motion and longer integration times. These compounding effects make it difficult to detect faint planets but also present an opportunity. Increased orbital motion makes it possible to move the search for planets into the orbital domain, where direct images can be freely combined with the radial velocity and proper motion anomaly, even without a confirmed detection in any single epoch. In this paper, we present a fast and differentiable multimethod orbit-modeling and planet detection code called Octofitter. This code is designed to be highly modular and allows users to easily adjust priors, change parameterizations, and specify arbitrary function relations between the parameters of one or more planets. Octofitter further supplies tools for examining model outputs including prior and posterior predictive checks and simulation-based calibration. We demonstrate the capabilities of Octofitter on real and simulated data from different instruments and methods, including HD 91312, simulated JWST/NIRISS aperture masking interferometry observations, radial velocity curves, and grids of images from the Gemini Planet Imager. We show that Octofitter can reliably recover faint planets in long sequences of images with arbitrary orbital motion. This publicly available tool will enable the broad application of multiepoch and multimethod exoplanet detection, which could improve how future targeted ground- and space-based surveys are performed. Finally, its rapid convergence makes it a useful addition to the existing ecosystem of tools for modeling the orbits of directly imaged planets.

79 ASTRONOMY AND ASTROPHYSICS↗

A Cohesive Deep Drilling Field Strategy for LSST Cosmology

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will image billions of astronomical objects in the wide–fast–deep primary survey and in a set of minisurveys including intensive observations of a group of deep drilling fields (DDFs). The DDFs are a critical piece of three key aspects of the LSST Dark Energy Science Collaboration (DESC) cosmological measurements: they provide a required calibration for photometric redshifts (photo- z ) and weak gravitational lensing (WL) measurements and they directly contribute to cosmological constraints from the most distant Type Ia supernovae (SNe Ia). We present a set of cohesive DDF strategies fulfilling science requirements relevant to DESC and following the guidelines of the Survey Cadence Optimization Committee. We propose a method to estimate the observing strategy parameters and we perform simulations of the corresponding surveys. We define a set of metrics for each science case to assess the performance of the proposed observing strategies. We show that the most promising results are achieved with deep rolling surveys characterized by two sets of fields: ultradeep fields ( z ≲ 1.1) observed at a high cadence with a large number of visits over a limited number of seasons, and deep fields ( z ≲ 0.7), observed with a cadence of ~3 nights for 10 yr. These encouraging results should be confirmed with realistic simulations using the LSST scheduler. A DDF budget of ~8.5% is required to design observing strategies satisfying all the cosmological requirements. A lower DDF budget leads to surveys that either do not fulfill the photo- z /WL requirements or are not optimal for SN Ia cosmology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-Fidelity Models and Fast EMT Simulation Algorithms for Isolated Multi-port Autonomous Reconfigurable Solar power plant (MARS)

The integration of hybrid photovoltaic (PV) and energy storage system (ESS) based plants has become a promising way of solving the intermittency of PV plants and providing frequency support to the power grid. The multi-port autonomous reconfigurable solar power plant (MARS) can integrate the PV systems and ESSs to an ac grid and dc lines. The proposed isolated MARS incorporates an isolated converter that connects to the PV arrays and is based on the dual active bridge (DAB) converter. The high frequency switching in the DAB and the means to control the DAB converter using delays between switching signals lead to the need for a small timestep in simulations. Moreover, several hundreds of modules that include a DAB converter are present in the MARS. The small timestep and the presence of several hundreds of modules lead to a significant rise in the overall simulation time. To address this issue, simulation algorithms like numerical stiffness-based hybrid discretization and the hysteresis relaxation technique are applied to the switched system model of isolated MARS. Additionally, an event-driven interpolating method is introduced to help increase the minimum timestep to simulate the conventional DAB converter model while maintaining high accuracy in the simulation results. The developed model is validated by comparison with its reference model built in the PSCAD/EMTDC and MATLAB software environments using library components.

Xia, Qian↗

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗

A Platform for Ultra-Fast Proton Probing of Matter in Extreme Conditions

Recent developments in ultrashort and intense laser systems have enabled the generation of short and brilliant proton sources, which are valuable for studying plasmas under extreme conditions in high-energy-density physics. However, developing sensors for the energy selection, focusing, transport, and detection of these sources remains challenging. This work presents a novel and simple design for an isochronous magnetic selector capable of angular and energy selection of proton sources, significantly reducing temporal spread compared to the current state of the art. The isochronous selector separates the beam based on ion energy, making it a potential component in new energy spectrum sensors for ions. Analytical estimations and Monte Carlo simulations validate the proposed configuration. Due to its low temporal spread, this selector is also useful for studying extreme states of matter, such as proton stopping power in warm dense matter, where short plasma stagnation time (<100 ps) is a critical factor. The proposed selector can also be employed at higher proton energies, achieving final time spreads of a few picoseconds. This has important implications for sensing technologies in the study of coherent energy deposition in biology and medical physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Particle size effect of graphite anodes on performance of fast charging Li-ion batteries

Charging energy-dense lithium-ion batteries (LIBs) with thick graphite electrodes at high current densities are typically accompanied by poor performance and safety issues. The root cause is the onset of Li plating at the surface of graphite when lithiated to a high capacity within a short time period. Here, we investigated the behavior of graphite electrodes with various particle sizes under fast charge operations. Results from the electrochemical characterization on graphite electrodes exhibit the superiority of smaller particles over bigger particles in terms of suppressing the onset of Li plating and growth of plated Li particles. Observations from scanning electron microscopy also corroborate the presence of plated Li in electrodes with big graphite particles and its absence in graphite electrodes with small particles, when the cells were lithiated to 90% of the state of charge (SOC). Further, the improved performance of cells with the small particles might be associated with the low Li-ion concentration at the surface of graphite and thus reduced overpotential in graphite electrodes. The simulated results revealed that, compared to bigger particles, smaller particles have lower surface intercalation at any given cell SOC, which may significantly reduce the overpotential in the graphite electrodes and mitigate the onset of Li plating. This agrees well with experimental observations.

25 ENERGY STORAGE↗

Ponderomotive force driven density modifications parallel to B on the LAPD

The ponderomotive force has previously been identified as a possible driver of observed density modifications close to radio frequency actuators during operation. This nonlinear force redistributes density in regions of gradients in the magnitude of an oscillating electric field and describes the influence of the fast time scale RF wave dynamics on slow time scale plasma transport. Depletion of the saturation current (a proxy for the density) measured at the Large Plasma Device (LAPD) was 30–35% during ion cyclotron range of frequencies operation. A coupled 1D plasma transport and cold plasma frequency domain wave solver was developed to self-consistently describe ponderomotive effects and was used to compare with results obtained from the LAPD experiment. The scaled current density driver for the wave model yielded an RF B field in close agreement with two components of the experimental data. However, the 1D parallel model did not accurately reproduce the amplitude or spatial distribution observed in experimental measurements of By. Within the limitations of the 1D model, initial simulation results showed that the ponderomotive force depleted up to 8% for high power (1 MW) and around 1% for the experimental power of 120 kW. This could suggest that the ponderomotive force is not the main driver of density modification for the LAPD experiments presented in this paper. Higher fidelity tools of at least 2D will be required to give a more realistic description of the RF E fields and the effect of the ponderomotive force on the LAPD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quenching time-scales in the IllustrisTNG simulation

ABSTRACT The time-scales for galaxy quenching offer clues to its underlying physical drivers. We investigate central galaxy quenching time-scales in the IllustrisTNG 100-1 simulation, their evolution over time, and the pre-quenching properties of galaxies that predict their quenching time-scales. Defining quenching duration τq as the time between crossing specific star formation rate (sSFR) thresholds, we find that ${\sim} 40{{\ \rm per\ cent}}$ of galaxies quench rapidly with τq < 1 Gyr, but a substantial tail of galaxies can take up to 10 Gyr to quench. Furthermore, 29 per cent of galaxies that left the star-forming main sequence (SFMS) more than 2 Gyr ago never fully quench by z = 0. While the median τq is fairly constant with epoch, the rate of galaxies leaving the SFMS increases steadily over cosmic time, with the rate of slow quenchers being dominant around z ∼ 2–0.7. Compared to fast quenchers (τq < 1 Gyr), slow-quenching galaxies (τq > 1 Gyr) were more massive, had more massive black holes, had larger stellar radii, and accreted gas with higher specific angular momentum (AM) prior to quenching. These properties evolve little by z = 0, except for the accreting gas AM for fast quenchers, which reaches the same high AM as the gas in slow quenchers. By z = 0, slow quenchers also have residual star formation in extended gas rings. Using the expected relationship between stellar age gradient and τq for inside-out quenching we find agreement with Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) integral field unit (IFU) observations. Our results suggest the accreting gas AM and potential well depth determine the quenching time-scale.

79 ASTRONOMY AND ASTROPHYSICS↗

Detector Characterization for Accurate Monte Carlo Simulation and Neutron Energy-spectrum Unfolding

This report details the characterization of a deuterated scintillation detector for use in neutron spectroscopy via the spectrum unfolding technique. The active volume of the detector consists of a 3-in. diameter by 3 in. depth right circular cylinder that contains 337 cm3 of liquid scintillator EJ-315, deuterated benzene with a D:H ratio of 141:1. A deuterated scintillator is desirable for unfolding fast neutron energy spectra because the backscattering of neutrons from deuterium produces peaks in the pulse height response corresponding to the incident neutron energy. Spectrum unfolding requires the detector’s response to be accurately known for any input neutron energy. The characterization in this report supports using a simulated response matrix calibrated by the measured light output and convolved with the measured resolution to produce a response matrix without bringing the detector to a neutron beam facility for characterization. In particular, characterization measurements were performed that included calibration of the detector’s light output to recoil electrons from gamma sources, calibration of the detector’s resolution to recoil electrons, and calibration of the detector’s light output to recoil protons from a time-tagged neutron source and a monoenergetic 14.1 MeV neutron source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High Speed, Localized Multi-Point Strain Measurements on a Containment Vessel at 1.7 MHz Using Swept-Wavelength Laser-Interrogated Fiber Bragg Gratings

Dynamic elastic strain in ~1.8 and 1.0 m diameter containment vessels containing a high explosive detonation was measured using an array of fiber Bragg gratings. The all-optical method, called real-time localized strain measurement, recorded the strain for 10 ms after detonation with additional measurements being sequentially made at a rate of 1.7 MHz. A swept wavelength laser source provided the repetition rate necessary for such high-speed measurements while also providing enough signal strength and bandwidth to simultaneously measure 8 or more unique points on the vessel’s surface. The data presented here arethen compared with additional diagnostics consisting of a fast spectral interferometer and an optical backscatter reflectometer to show a comparison between the local and global changes in the vessel strain, both dynamically and statically to further characterize the performance of the localized strain measurement. The results are also compared with electrical resistive strain gauges and finite element analysis simulations.

47 OTHER INSTRUMENTATION↗

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL's Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

47 OTHER INSTRUMENTATION↗

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Aircraft icing represents a serious hazard in aviation which has caused a number of fatal accidents over the years. In addition, it can lead to substantial increase in drag and weight, thus reducing the aerodynamics performance of the airplane. The process of ice accretion on a solid surface is a complex interaction of aerodynamic and environmental variables. The complex relationship makes machine learning-based methods an attractive alternative to traditional numerical simulation-based approaches. In this study, we introduce a purely data-driven approach to find the complex pattern between different flight conditions and aircraft icing severity prediction. The supervised learning algorithm Extreme Gradient Boosting (XGBoost) is applied to establish the prediction framework which makes prediction based on any set of observations. The input flight conditions for the proposed prediction framework are liquid water content, droplet diameter and exposure time. The proposed approach is demonstrated in three cases: maximum ice thickness prediction, icing area prediction and icing severity level evaluation. Performance comparison studies and error analysis are also conducted to verify the effectiveness and performance of the proposed method. Results show that the proposed method has reasonable capability in evaluating aircraft icing severity.

Li, Sibo (ORCID:000000021705844X)↗