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At least 1,225 records · Page 68

The NEUT neutrino interaction simulation program library

Abstract is a neutrino–nucleus interaction simulation program library. It can be used to simulate interactions for neutrinos with between 100 MeV and a few TeV of energy. is also capable of simulating hadron interactions within a nucleus and is used to model nucleon decay and hadron–nucleus interactions for particle propagation in detector simulations. This article describes the range of interactions modelled and how each is implemented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Discovering the nature of neutrinos: How nuclear theory will advance this grand endeavor. Final report

Why is there more matter than antimatter in the visible universe? Are neutrinos their own antiparticles? These are some of the most profound questions in science. The detection of a (0vββ) neutrinoless doublebeta decay and the measurement of its half-life is one of the most important experimental endeavors in science because it will answer these questions. Paramount to these measurements are accurate predictions with quantified uncertainties of the 0vββ-decay nuclear transitions, especially for the germanium-76 and xeon-136 nuclei, two candidate materials for building the next generation of DOE funded 0vββ-decay experiments. These predictions will guide the Office of Science’s down selection of experiments as well as aid in determining how much material is needed by these experiments. We studied a specific difficult to assess source of uncertainty that will impact coming microscopic predictions, uncertainty which arises from an incomplete yet systematically improvable model of interactions between nucleons and of nucleons with the other particles involved in decay process, referred to as the theory uncertainty. We employed a surrogate model of the germanium-76 nucleus, and its decay products, just detailed enough to adequately mimic the decaying nucleons need for a reasonable measure of this uncertainty and nothing more, avoiding the immense computational expense required in quantifying uncertainties of the full calculation. We found that microscopic calculations of this process can be expected to achieve relative theory uncertainties around 30%, including an unconstrained contribution that had the potential to spoil microscopic calculations. This results in a nearly order of magnitude on previously estimated uncertainties for this rare decay process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling the Inner Magnetosphere: Radiation Belts, Ring Current, and Composition

The space environment is a complex system defined by regions of differing length scales, characteristic energies, and physical processes. It is often difficult, or impossible, to treat all aspects of the space environment relative to a particular problem with a single model. In our studies, we utilize several models working in tandem to examine this highly interconnected system. The methodology and results will be presented for three focused topics: 1) Rapid radiation belt electron enhancements, 2) Ring current study of Energetic Neutral Atoms (ENAs), Dst, and plasma composition, and 3) Examination of the outflow of ionospheric ions. In the first study, we use a coupled MHD magnetosphere - kinetic radiation belt model to explain recent Akebono/RDM observations of greater than 2.5 MeV radiation belt electron enhancements occurring on timescales of less than a few hours. In the second study, we present initial results of a ring current study using a newly coupled kinetic ring current model with an MHD magnetosphere model. Results of a dst study for four geomagnetic events are shown. Moreover, direct comparison with TWINS ENA images are used to infer the role that composition plays in the ring current. In the final study, we directly model the transport of plasma from the ionosphere to the magnetosphere. We especially focus on the role of photoelectrons and and wave-particle interactions. The modeling methodology for each of these studies will be detailed along with the results.

Glocer, Alex↗

Interactive Framework to Support Open Model-Data Validation Efforts at the CCMC

Validation of models using observation data has been a central activity at the Community Coordinated Modeling Center (CCMC) over more than a decade. The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework is a database-driven implementation of the interactive analysis of model-data comparisons that simultaneously provides a view across a multitude of locations and time periods. CAMEL thus extends the single-location or single-trajectory timeseries data comparison capabilities provided by the CCMC online visualization that formed the backbone of initial validation efforts. We demonstrate CAMEL capabilities for an example application to study Neutral Density in the upper atmosphere among comparisons in the heliosphere, the Earth’s radiation belt, magnetosphere, and ionosphere-thermosphere-mesosphere domains.

Lutz Rastaetter↗

Rotor-Fuselage Interaction: Analysis and Validation with Experiment

The problem of rotor-fuselage aerodynamic interaction has to be considered in industry applications from various aspects. First, in order to increase helicopter speed and reduce operational costs, rotorcraft tend to be more and more compact, with a main rotor closer to the fuselage surface. This creates significant perturbations both on the main rotor and on the fuselage, including steady and unsteady effects due to blade and wake passage and perturbed inflow at the rotor disk. Furthermore,the main rotor wake affects the tail boom, empennage and anti-torque system. This has important consequences for helicopter control and vibrations at low speeds and also on tail rotor acoustics (main rotor wake-tail rotor interactions). This report describes the US Army-France MOD cooperative work on this problem from both the theoretical and experimental aspects. Using experimental 3D velocity field and fuselage surface pressure measurements, three codes that model the interactions of a helicopter rotor with a fuselage are compared. These comparisons demonstrate some of the strengths and weaknesses of current models for the combined rotor-fuselage analysis.

Berry, John D.↗

Multiplicative noise and the diffusion of conserved densities

Stochastic fluid dynamics governs the long time tails of hydrodynamic correlation functions, and the critical slowing down of relaxation phenomena in the vicinity of a critical point in the phase diagram. In this work we study the role of multiplicative noise in stochastic fluid dynamics. Multiplicative noise arises from the dependence of transport coefficients, such as the diffusion constants for charge and momentum, on fluctuating hydrodynamic variables. We study long time tails and relaxation in the diffusion of a conserved density (model B), and a conserved density coupled to the transverse momentum density (model H). Careful attention is paid to fluctuation-dissipation relations. We observe that multiplicative noise contributes at the same order as non-linear interactions in model B, but is a higher order correction to the relaxation of a scalar density and the tail of the stress tensor correlation function in model H.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Prediction of Multiple Hydrogen Ligation at a Vanadium(II) Site in a Metal–Organic Framework

Densifying hydrogen in a metal-organic framework (MOF) at moderate pressures can circumvent challenges associated with high-pressure compression. The highly tunable structural and chemical composition in MOFs affords vast possibilities to optimize binding interactions. At the heart of this search are the nanoscale characteristics of molecular adsorption at the binding site(s). Using density functional theory (DFT) to model binding interactions of hydrogen to the exposed metal site of cation-exchanged MFU-4 l , we predict multiple hydrogen ligation of H 2 at the first coordination sphere of V(II) in V(II)-exchanged MFU-4 l . We find that the strength of this binding between the metal site and H 2 molecules can be tuned by altering the halide counterion adjacent to the metal site and that the fluoride containing node affords the most favorable interactions for high-density H 2 storage. In conclusion, using energy decomposition analysis, we delineate electronic contributions that enable multiple hydrogen ligation and demonstrate its benefits for hydrogen adsorption and release at modest pressures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

Metal organic frameworks (MOFs) are a large class of porous materials and have garnered significant interest due to their large surface areas and their tunable physical and chemical properties. Numerous prior studies have been performed to screen large databases of this material class for promising DAC sorbent materials. These studies have often relied on classical model potentials. While density functional theory (DFT) calculations have been shown to be very accurate for modeling the interaction of CO2 with MOFs, such calculations are too computationally demanding for statistically significant adsorption predictions. To overcome this barrier, we developed methods for training models to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption using machine learned force fields (MLFFs). These methods were parametrized based on DFT calculations of CO2 in a flexible MOF and used to predict MOF structural properties as well as CO2 adsorption in several MOFs.

Findley, John↗

Software for continuum modeling of controls-structures interactions

It is clear that computer software is needed to assist in the generation of the equations of motion for complex, flexible spacecraft. Daniel Poelaert of ESTEC has developed the software DISTEL with which he has modeled the structural dynamics for different satellites. He is interested in expanding the capabilities of DISTEL to include structural damping and control systems. Unfortunately, the software has not been released. The author has developed similar software, PDEMOD, which has been used to model the Spacecraft control Laboratory Experiment (SCOLE), the Solar Array Flight Experiment (SAFE), the Mini-MAST truss, and the LACE satellite. PDEMOD has been used also for optimal parameter estimation and integrated control-structures design. PDEMOD is also being extended to include structural damping and control systems which are imbedded into the same equations for the structural dynamics. This paper will address the formulation of the equations for the structural dynamics of spacecraft structures which are constructed of a 3-dimensional arrangement of rigid bodies and flexible beam elements. Control system dynamics are imbedded into the same equations so that model order reduction approximations are not necessary. The input data consists of the physical data of the elements and the topological information describing how the elements are connected. PDEMOD accomplishes the following: (1) automatically assembles the equations of motion for the entire structural model; (2) calculates the modal frequencies; (3) calculates the mode shapes; (4) generates perspective views of the mode shapes; and (5) forms selected transfer functions. The software PDEMOD continues to be developed to provide additional features to assist in analyzing and synthesizing control and structural systems for flexible spacecraft.

Taylor, Lawrence W., Jr.↗

Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate

Abstract Plant growth and distribution in high-latitude tundra ecosystems is strongly limited by nutrient availability and is critical for quantifying centennial-scale carbon-climate interactions. However, land model representations of plant–nutrient interactions are uncertain, leading to poor comparisons with high-latitude observations. Although it has been recognized for decades in the observational community that plants continue to acquire nutrients well past when aboveground activity has ceased, most large-scale land models ignore this process. Here we address the role tundra plant nutrient acquisition during the non-growing season (NGS) has on centennial-scale vegetation growth and dynamics, with a focus on shrub expansion. We apply a well-tested mechanistic model of coupled plant, microbial, hydrological, and thermal dynamics that explicitly represents nutrient acquisition based on plant and microbial traits, thereby allowing a prognostic assessment of NGS nutrient uptake. We first show that the model accurately represents observed seasonality of NGS plant nutrient uptake in a northern Alaskan tundra site. Applying the model across the North America tundra indicates that NGS nutrient uptake is consistent with observations and ranges between ∼5% and 50% of annual uptake, with large spatial variability and dependence on plant functional type. We show that NGS plant nutrient acquisition strongly enhances modeled 21 st century tundra shrub growth and expansion rates. Our results suggest that without NGS nutrient uptake, total shrub aboveground dominance would be ∼50% lower, limited primarily by their inability to grow tall enough to maximize their inherent capacity for light competition. Evergreen shrubs would be more strongly affected because of their relatively lower capacity for nutrient remobilization and acquisition compared to deciduous shrubs. Our results highlight the importance of NGS plant and soil processes on high-latitude biogeochemistry and vegetation dynamics and motivate new observations and model structures to represent these dynamics.

54 ENVIRONMENTAL SCIENCES↗

Liquid drop behavior in dense and dilute clusters

It is argued that models of droplet clusters must be flexible enough to accommodate both dilute and dense configurations, and cluster drop number density influences many of the crucial aspects of combustion. Current models of drop interactions are described, and it is shown that they have limitations that prevent their being used as subgrid models. An approach for modeling drop interactions which has the potential for use as a subgrid model is presented.

Bellan, Josette↗

A hybrid full-wave Markov chain approach to calculating radio-frequency wave scattering from scrape-off layer filaments

The interaction of radio-frequency (RF) waves with edge turbulence modifies the incident wave spectrum, and can significantly affect RF heating and current drive in tokamaks. Previous lower hybrid (LH) scattering models have either used the weak-turbulence approximation, or treated more realistic, filamentary turbulence in the ray tracing limit. In this study, a new model is introduced which retains full-wave effects of RF scattering in filamentary turbulence. First, a Mie-scattering technique models the interaction of an incident wave with a single Gaussian filament. Next, an effective differential scattering width is derived for a statistical ensemble of filaments. Lastly, a Markov chain solves for the transmitted wave spectrum in slab geometry. This model is applied to LH launching for current drive. The resulting wave spectrum is asymmetrically broadened in angular wavenumber space. This asymmetry is not accounted for in previous LH scattering models. The modified wave spectrum is coupled to a ray tracing/Fokker–Planck solver (GENRAY/CQL3D) to study its impact on current drive. The resulting current profile is greatly altered, and there is significant increase in the on-axis current and decrease in the off-axis peaks. This is attributed to a portion of the modified wave spectrum that is strongly dampened on-axis during the first pass.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Practical challenges of model predictive control (MPC) for grid interactive small and medium commercial buildings

To the urgent call for mitigating climate change, substantial initiatives have been undertaken to deploy grid-interactive heating, ventilation, and air-conditioning (HVAC) controls, such as model predictive control (MPC) for buildings. These efforts typically aim to curtail peak energy demand, shift load and enhance overall energy efficiency. With the recent development of low-cost MPC technologies that don’t require extensive instrumentation or manual modeling, small and medium commercial buildings (SMCBs), which rarely utilize advanced HVAC control systems, have become candidates for grid-interactive efficient buildings (GEBs). However, despite the potential benefits and maturity of the technology itself, several practical challenges remain in real-world implementation. In this paper, we share the practical challenges that we have encountered in implementing and testing three types of MPC solutions (ON/OFF unit, dualfuel, and VRF systems) on multiple SMCB sites. We describe the MPC deployment process and discuss the lessons learned. The site selection, eligibility, and retrofit availability (e.g., utility price structure, thermostat communications, etc.) are the main discussion points at the beginning of the project. Also, the modeling automation and the best practices for interacting with endusers and handling erroneous situations are presented for successful operations.

woo Ham, Sang↗

Physics-constrained Gaussian process model for prediction of hydrodynamic interactions between wave energy converters in an array

To improve the efficiency of wave farms and achieve maximum power generation, the layout of wave energy converters (WECs) in an array needs to be carefully designed so that the hydrodynamic interactions can be positively exploited. For this, the hydrodynamic characteristics of the WEC array in different layouts need to be calculated. However, such calculations using numerical models usually entail significant computational cost, especially for large arrays of WECs. To address the computational challenge, a physics-constrained Gaussian process (GP) model is proposed to replace the original expensive numerical model and predict the hydrodynamic characteristics of the WECs for any array layout. By exploring the relationship between the WEC array (i.e., the input) and different hydrodynamic characteristics (i.e., the output), here we summarize a set of physical constraints/features, including invariance, symmetry, and additivity. This prior knowledge about the input-output relationship is then directly embedded in the constructed GP model through the design of physics-constrained kernels. In particular, a double-sum invariant kernel is first developed to incorporate the invariance and symmetry features, and then an additive kernel is developed to incorporate the additive feature of the problem. The invariant kernel and the additive kernel are then integrated to construct the physics-constrained GP model. Compared to the standard GP model, the proposed physics-constrained GP models require less training data to achieve the desired accuracy in predicting the hydrodynamic characteristics and are also less vulnerable to the curse of dimensionality (i.e., good scalability for large arrays) due to the use of an additive kernel. The efficiency, accuracy, and scalability of the proposed approach are demonstrated through an application to predict the hydrodynamic characteristics for WEC arrays of different sizes and layouts.

16 TIDAL AND WAVE POWER↗

Three-state Potts nematic order in stacked frustrated spin models with SO(3) symmetry

Here, we propose stacked two-dimensional lattice designs of frustrated and SO(3) symmetric spin models consisting of antiferromagnetic (AF) triangular and ferromagnetic (FM) sixfold symmetric sublattices that realize emergent $\mathbb{Z}_{3}$ Potts nematic order. Considering bilinear-biquadratic spin interactions, our models describe an SO(3)-symmetric triangular lattice AF subject to a fluctuating magnetization arising from the FM coupled sublattice. We focus on the classical AFM-FM windmill model and map out the zero- and finite-temperature phase diagram using Monte Carlo simulations and analytical calculations. We discover a state with composite Potts nematic order above the ferrimagnetic three-sublattice up-up-down ground state and relate it to Potts phases in SO(3)-broken Heisenberg and Ising AFMs in external magnetic fields. Finally, we show that the biquadratic exchange in our model is automatically induced by thermal and quantum fluctuations in the purely bilinear Heisenberg model, easing the requirements for realizing these lattice designs experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Closure Learning for Nonlinear Model Reduction Using Deep Residual Neural Network

Developing accurate, efficient, and robust closure models is essential in the construction of reduced order models (ROMs) for realistic nonlinear systems, which generally require drastic ROM mode truncations. We propose a deep residual neural network (ResNet) closure learning framework for ROMs of nonlinear systems. The novel ResNet-ROM framework consists of two steps: (i) In the first step, we use ROM projection to filter the given nonlinear system and construct a spatially filtered ROM. This filtered ROM is low-dimensional, but is not closed. (ii) In the second step, we use ResNet to close the filtered ROM, i.e., to model the interaction between the resolved and unresolved ROM modes. We emphasize that in the new ResNet-ROM framework, data is used only to complement classical physical modeling (i.e., only in the closure modeling component), not to completely replace it. We also note that the new ResNet-ROM is built on general ideas of spatial filtering and deep learning and is independent of (restrictive) phenomenological arguments, e.g., of eddy viscosity type. The numerical experiments for the 1D Burgers equation show that the ResNet-ROM is significantly more accurate than the standard projection ROM. The new ResNet-ROM is also more accurate and significantly more efficient than other modern ROM closure models.

Xie, Xuping↗

Properties of giant dipole resonances within an extended pairing model with a focus on spectral statistics

In this paper, we report on a study of the spectral features associated with dipole resonances in medium mass nuclei (E ≤ 12 MeV), as revealed in the framework of the spd-interacting boson model. The effect of pairing correlations on the theory follows from solutions obtained through an application of the Bethe Ansatz Equation. In general, calculated spectra around the critical point of the vibrational to γ-soft transitions appears to approach that of a Gaussian Orthogonal Ensemble, while near the rotational and vibrational limits of the theory the spectra show more regular behavior. Specifically, the results reveal that the statistical features of the spectra are sensitive to the vector boson pairing strength, c p , in the transition region; that is, when c p is zero, or when the system approaches one of its dynamical symmetries limits the spectrum display regular features, while for stronger c p values, or when near to the critical phase transition region, the spectral feature show more chaotic behavior. Overall, our results indicate that the statistical features are governed by the interplay between dipole resonant energies, pairing correlations, and interactions between and among the single and vector bosons modes of the theory. As part of this work we also found out that chaoticity occurs when results were fit to a Berry-Robnik distribution. Throughout our analyses, we used experimentally known information about both positive and negative parity states. Our findings suggest that dipole resonances appear to be best-described by Poisson statistics for A ≈ 32-138 nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

dGen (Distributed Generation Market Demand) Model Data: Alpha Release

Open sourced data needed to run the basic alpha release version of the dGen model. Includes a pre-generated agent file of 100,000 agents in pickle file format along with the base schema and table data in parquet format that are needed to create a postgreSQL database for the model to interact with.

14 SOLAR ENERGY↗