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At least 145 records · Page 8

Islet: interpolation semi-Lagrangian element-based transport

Abstract. Advection of trace species, or tracers, also called tracer transport, in models of the atmosphere and other physical domains is an important and potentially computationally expensive part of a model's dynamical core. Semi-Lagrangian (SL) advection methods are efficient because they permit a time step much larger than the advective stability limit for explicit Eulerian methods without requiring the solution of a globally coupled system of equations as implicit Eulerian methods do. Thus, to reduce the computational expense of tracer transport, dynamical cores often use SL methods to advect tracers. The class of interpolation semi-Lagrangian (ISL) methods contains potentially extremely efficient SL methods. We describe a finite-element ISL transport method that we call the interpolation semi-Lagrangian element-based transport (Islet) method, such as for use with atmosphere models discretized using the spectral element method. The Islet method uses three grids that share an element grid: a dynamics grid supporting, for example, the Gauss–Legendre–Lobatto basis of degree three; a physics parameterizations grid with a configurable number of finite-volume subcells per element; and a tracer grid supporting use of Islet bases with particular basis again configurable. This method provides extremely accurate tracer transport and excellent diagnostic values in a number of verification problems.

58 GEOSCIENCES↗

Twistor Actions for Integrable Systems

Many integrable systems can be reformulated as holomorphic vector bundles on twistor space. This is a powerful organizing principle in the theory of integrable systems. One shortcoming is that it is formulated at the level of the equations of motion. From this perspective, it is mysterious that integrable systems have Lagrangians. In this paper, we study a Chern-Simons action on twistor space and use it to derive the Lagrangians of some integrable sigma models. Our focus is on examples that come from dimensionally reduced gravity and supergravity. The dimensional reduction of general relativity to two spacetime dimensions is an integrable coset sigma model coupled to a dilaton and 2d gravity. The dimensional reduction of supergravity to two spacetime dimensions is an integrable coset sigma model coupled to matter fermions, a dilaton, and 2d supergravity. We derive Lax operators and Lagrangians for these 2d integrable systems using the Chern-Simons theory on twistor space. In the supergravity example, we use an extended setup in which twistor Chern-Simons theory is coupled to a pair of matter fermions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Lagrangian simulations of spray interaction with a surface using a stochastic multi-regime impingement model

Modeling of spray impingement upon the piston or cylinder surface is important for hydrocarbon emission and soot predictions in high-fidelity simulation of internal combustion engines with direct injections. Due to the complexity of the physical process of spray impingement, current computational models heavily rely on the empirical studies which involve large uncertainties. A computational model is presented for spray impingement on solid walls in general computational fluid dynamics (CFD) simulations. The model adopts the Marmanis-Thoroddsen theory for determining the number of secondary droplets and a stochastic method for calculating the velocities of the secondary droplets. The numerical methods and parallel implementation of the impingement model are presented in detail. The model is implemented in Grit, which is a recently developed CPU/GPU performance-portable Lagrangian particle library, for accelerating spray simulations. The model and its implementation are tested for examples of spray impingements on flat and smooth surfaces with different impingement angles.

Ge, Wenjun↗

Code for the manuscript "Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning"

We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript "Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning ". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

Tian, Yifeng↗

Measurement and simulation of small cryogenic neon pellet Ne-I 640 nm photon efficiency during ablation in DIII-D plasma

Small (~1 mm) neon pellet fragments are fired into DIII-D H-mode plasmas, and resulting trajectory-averaged photon efficiencies (neutral neon ionization events for every photon emitted) of S/XB ≈ 85 are estimated for Ne-I 640 nm by dividing the estimated initial pellet fragment mass by the measured number of emitted Ne-I photons. The experiments are modeled by running the Lagrangian particle (LP) fluid/magneto-hydrodynamic pellet code to estimate axial ablation plume neon density profiles and temperature profiles at each pellet position. These solutions are then fed into the PrismSPECT collisional-radiative code, which calculates resulting neon charge states and photon emission rates, giving a profile-average of S/XB ≈ 109. The burnthrough plasma minor radius predicted by LP (ρ ≈ 0.63) is reasonably close to the experimental observation ρ ≈ 0.6. Furthermore, the modeling indicates that local S/XB is not constant along the pellet trajectory but tends to increase with increasing ablation rate. Non-equilibrium kinetics are predicted to be very important, while line trapping is predicted to be relatively unimportant (for Ne-I 640 nm S/XB).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development, verification, and validation of comprehensive acoustic fluid-structure interaction capabilities in an open-source computational platform

The acoustic fluid-structure interaction (FSI) formulation is a practical numerical approach for the seismic analysis of fluid-filled tanks. However, there are no verification and validation studies reported in the literature that demonstrate the ability of an acoustic FSI numerical model to predict responses important to structural and mechanical design for intense translational and rotational earthquake inputs. Herein, an acoustic FSI formulation is implemented in the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE), and is formally verified and validated using analytical solutions and code-to-code verification, and experimental data, respectively. The analytical solutions are for small amplitude, unidirectional seismic inputs. The code-to-code verification utilizes a previously verified and validated Arbitrary Lagrangian-Eulerian (ALE) numerical model in the commercial finite element code LS-DYNA. The validation studies utilize a comprehensive data set assembled from results of 3D earthquake-simulator tests of a fluid-filled vessel. The acoustic numerical model in MOOSE is verified and validated for hydrodynamic pressures and support reactions except for cases that involve significant convective response. For small amplitude inputs, numerically predicted wave heights match those of the analytical solutions. The numerical model is not verified and validated for wave height calculations under intense 3D seismic inputs. The run times for the acoustic FSI simulations in MOOSE are an order of magnitude, or more, shorter than for the corresponding ALE simulations in LS-DYNA. The utility of the MOOSE acoustic FSI implementation is demonstrated by seismic analysis of a building equipped with a fluid-filled, advanced nuclear reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A low-energy perspective on the minimal left-right symmetric model

We perform a global analysis of the low-energy phenomenology of the minimal left-right symmetric model (mLRSM) with parity symmetry. We match the mLRSM to the Standard Model Effective Field Theory Lagrangian at the left-right-symmetry breaking scale and perform a comprehensive fit to low-energy data including mesonic, neutron, and nuclear β -decay processes, Δ F = 1 and Δ F = 2 CP-even and -odd processes in the bottom and strange sectors, and electric dipole moments (EDMs) of nucleons, nuclei, and atoms. We fit the Cabibbo-Kobayashi-Maskawa and mLRSM parameters simultaneously and determine a lower bound on the mass of the right-handed W R boson. In models where a Peccei-Quinn mechanism provides a solution to the strong CP problem, we obtain $ {M}_{W_R} $ ≳ 5 . 5 TeV at 95% C.L. which can be significantly improved with next-generation EDM experiments. In the P -symmetric mLRSM without a Peccei-Quinn mechanism we obtain a more stringent constraint $ {M}_{W_R} $ ≳ 17 TeV at 95% C.L., which is difficult to improve with low-energy measurements alone. In all cases, the additional scalar fields of the mLRSM are required to be a few times heavier than the right-handed gauge bosons. We consider a recent discrepancy in tests of first-row unitarity of the CKM matrix. We find that, while TeV-scale W R bosons can alleviate some of the tension found in the V ud,us determinations, a solution to the discrepancy is disfavored when taking into account other low-energy observables within the mLRSM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

hi_class background evolution, initial conditions and approximation schemes

Cosmological datasets have great potential to elucidate the nature of dark energy and test gravity on the largest scales available to observation. Theoretical predictions can be computed with hi_class (www.hiclass-code.net), an accurate, fast and flexible code for linear cosmology, incorporating a wide range of dark energy theories and modifications to general relativity. We introduce three new functionalities into hi_class: (1) Support for models based on covariant Lagrangians, including a constraint-preserving integration scheme for the background evolution and a series of worked-out examples: Galileon, nKGB, quintessence (monomial, tracker) and Brans-Dicke. (2) Consistent initial conditions for the scalar-field perturbations in the deep radiation era, identifying the conditions under which modified-gravity isocurvature perturbations may grow faster than adiabatic modes leading to a loss of predictivity. (3) An automated quasistatic approximation scheme allowing order-of-magnitude improvement in computing performance without sacrificing accuracy for wide classes of models. These enhancements bring the treatment of dark energy and modified gravity models to the level of detail comparable to software tools restricted to standard $\Lambda$CDM cosmologies. Finally, the hi_class code is publicly available (https://github.com/miguelzuma/hi_class_public), ready to explore current data and prepare for next-generation experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Implementing a Stochastic Soot Model in a 3D Domain

In this document a highly detailed stochastic soot model limited to 0D simulations is coupled to 3D domains through the use of a Lagrangian parcel-Eulerian fluid method. Although both the stochastic soot model used and the Lagrangian parcel-Eulerian fluid method have long histories of development, their use, as described in this document, is novel and useful. Previous works significant to the model's development include documents from both the stochastic and simpler soot model genre and the fuel, aerosol, and other particle tracking and Lagrangian parcel-Eulerian fluid genres. Developing the theory behind the model is crucial to its implementation because of the unconventional Lagrangian parcel-Eulerian fluid representation. In fact, the Lagrangian parcel-Eulerian fluid coupling is only a means of simplifying the much more difficult theoretical model. Despite the accompanying assumptions, the complete model is validated from the bottom up and then again in a holistic fashion with promising results. Then the model is used in multiple case studies, showcasing capabilities not had by other models. The optical properties of soot generated in a Spray A simulation are calculated to find measured results are likely overpredicting the mass of soot along the central axis via KL extinction measurements. A thermophoresis submodel that calculates force based on the soot particles' shape is installed to find it has a high influence on the path of the heaviest soot particles. Investigations into the HACA mechanism for soot growth and the effect of syngas on soot in 3D domains are performed with much more detail than has been available before.

Strickland, Tyler↗

A particle finite element-based model for droplet spreading analysis

Here, a particle finite element method-based model is proposed to analyze droplet dynamics problems, particularly droplet spreading on solid substrates (wetting). The model uses an updated Lagrangian framework to formulate the governing equations of the liquid. The curvature of the liquid surface is tracked accurately using a deforming boundary mesh. In order to predict the spreading rate of the droplet on the solid substrate and track the corresponding contact angle evolution, dissipative forces at the contact line are included in the formulation in addition to the Navier-slip boundary conditions at the solid–liquid interface. The inclusion of these boundary conditions makes it possible to account for the induced Young’s stress at the contact line and for the viscous dissipation along the solid–liquid interfacial region. These are found to be essential to obtain a mesh-independent physical solution. The temporal evolution of the contact angle and the contact line velocity of the proposed model are compared with spreading droplets and micro-sessile droplet injection experiments and are shown to be in good agreement.

42 ENGINEERING↗

Code for the manuscript "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Mode

We disclose a python/pytorch implementation of the physics-informed machine learning algorithm described in "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Modeling", LA-UR-24-30678. Direct numerical simulation (DNS) of ubiquitous turbulence phenomena is computationally infeasible for realistic flows. As a result, reduced modeling for turbulent flows aim to reduce the number of resolved scales while retaining accurate representations of the small-scale physics. The dynamics of the velocity gradient tensor (VGT) is a key ingredient in reduced or subgrid turbulence models. The evolution equation for the VGT involves nonlocal terms, requiring closure modeling. This implementation of the novel methodology of Lagrangian Attention Tensor Networks (LATN), utilizes a structured representation of the history of the VGT to inform a physics-informed machine learning algorithm. This addition of structured memory terms is shown to outperform previous models when trained and evaluated on DNS data.

Livescu, Daniel [LANL]↗

On the Reliability of Parameter Inferences in a Multiscale Model for Transport in Stream Corridors

Nonreacting tracer tests capture information about physical processes in transient storage zones including the hyporheic zone (HZ). However, reliably extracting this information from breakthrough curves (BTCs) and distinguishing the effects of in-channel dispersion and transient storage are well-known challenges. Using BTCs from a nonreacting tracer test monitored at multiple locations, we explore ways for reliable parameter estimations. The identifiability of parameters is greatly influenced by the choice of forward and inverse modeling frameworks in addition to the quality of the data. Our forward model is a recently proposed multiscale model that uses subgrid transport models written in the Lagrangian form to represent transport along a diverse set of HZ pathways with a shape-free distribution of travel times. Joint distributions of HZ and channel parameters are estimated using the Markov Chain Monte Carlo technique. Numerical experiments show ambiguity between channel dispersion and HZ transport when the reach length is too short to allow significant solute-HZ interaction, the observation period is too brief to observe the tailing behavior, or the solute source is spread in time. In contrast, we obtained reliable parameter estimates by simultaneously fitting BTCs observed at different locations in the test reach using a single set of HZ parameters and section-specific channel areas and dispersion coefficients. Furthermore, this study demonstrates the estimation of travel time distributions, HZ exchange rates, and channel parameters in a new multiscale approach and offers guidance for extracting reliable parameter estimates from multiple BTCs.

54 ENVIRONMENTAL SCIENCES↗

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗

A theory of dark pions

We present a complete model of a dark QCD sector with light dark pions, broadly motivated by hidden naturalness arguments. The dark quarks couple to the Standard Model via irrelevant Z- and Higgs-portal operators, which encode the low-energy effects of TeV-scale fermions interacting through Yukawa couplings with the Higgs field. The dark pions, depending on their CP properties, behave as either composite axion-like particles (ALPs) mixing with the Z or scalars mixing with the Higgs. The dark pion lifetimes fall naturally in the most interesting region for present and proposed searches for long-lived particles, at the LHC and beyond. This is demonstrated by studying in detail three benchmark scenarios for the symmetries and structure of the theory. Within a coherent framework, we analyze and compare the GeV-scale signatures of flavor-changing meson decays to dark pions, the weak-scale decays of Z and Higgs bosons to hidden hadrons, and the TeV-scale signals of the ultraviolet theory. New constraints are derived from B decays at CMS and from Z-initiated dark showers at LHCb, focusing on the displaced dimuon signature. We also emphasize the strong potential sensitivity of ATLAS and CMS to dark shower signals with large multiplicities and long lifetimes of the dark pions. As a key part of our phenomenological study, we perform a new data-driven calculation of the decays of a light ALP to exclusive hadronic Standard Model final states. The results are provided in a general form, applicable to any model with arbitrary flavor-diagonal couplings of the ALP to fermions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Heating neutron stars with GeV dark matter

An old neutron star (NS) may capture halo dark matter (DM) and get heated up by the deposited kinetic energy, thus behaving like a thermal DM detector with sensitivity to a wide range of DM masses and a variety of DM-quark interactions. Near future infrared telescopes will measure NS temperatures down to a few thousand Kelvin and probe NS heating by DM capture. We focus on GeV-mass Dirac fermion DM (which is beyond the reach of current DM direct detection experiments) in scenarios in which the DM capture rate can saturate the geometric limit. For concreteness, we study (1) a model that invokes dark decays of the neutron to explain the neutron lifetime anomaly, and (2) a framework of DM coupled to quarks through a vector current portal. In the neutron dark decay model a NS can have a substantial DM population, so that the DM capture rate can reach the geometric limit through DM self-interactions even if the DM-neutron scattering cross section is tiny. We find NS heating to have greater sensitivity than multipion signatures in large underground detectors for the neutron dark decay model, and sub-GeV gamma-ray signatures for the quark vector portal model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Three exceptions to the Grossman-Nir bound

A bstract We show that the Grossman-Nir (GN) bound, Br( K L → $$ {\pi}^0\nu \overline{\nu} $$ π 0 ν ν ¯ ) ≤ 4 . 3 Br( K + → $$ {\pi}^{+}\nu \overline{\nu} $$ π + ν ν ¯ ), can be violated in the presence of light new physics with flavor violating couplings. We construct three sample models in which the GN bound can be violated by orders of magnitude, while satisfying all other experimental bounds. In the three models the enhanced branching ratio Br( K L → π 0 + inv) is due to K L → π 0 Φ 1, K L → π 0 Φ 1 Φ 1 , K L → $$ {\pi}^0{\psi}_1{\overline{\psi}}_1 $$ π 0 ψ 1 ψ ¯ 1 transitions, respectively, where Φ 1 ( ψ 1 ) is a light scalar (fermion) that escapes the detector. In the three models Br( K + → π + + inv) remains very close to the SM value, while Br( K L → π 0 + inv) can saturate the present KOTO bound. Besides invisible particles in the final state (which may account for dark matter) the models require additional light mediators around the GeV-scale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Characterizing Reactive Transport Behavior in a Three-Dimensional Discrete Fracture Network

While several studies have linked network and in-fracture scale properties to conservative transport behavior in subsurface fractured media, studies on reactive transport cases remain relatively underdeveloped. In this study, we explore the behavior of an irreversible kinetic reaction during the interaction of two solute plumes, one consisting of species A and the other species B. When the plumes converge, these species react kinetically to form a new species C via A+B→kC. This reactive system is studied using a three-dimensional discrete fracture network (DFN) model coupled with reactive Lagrangian particle tracking. We find that the interplay of network topology and chemical properties of the reactive solutes controls reactive transport processes. The network topology drives species A and B together, and the chemical properties dictate whether and how quickly a reaction occurs. Results demonstrate that reactions are most likely to occur in high-velocity fractures that make up the network backbone. The interplay between species’ chemical properties and transport is characterized by a non-dimensional Damköhler (Da) number. We show that the spatial distribution of reactions is sensitive to Da, which subsequently influences late-time tailing behavior in outlet breakthrough time distributions. The results of this study provide initial insights into how an irreversible reaction occurs during transport in a fracture network, using a methodology that can be applied to study reactive transport in a wide range of fractured media environments and contexts.

58 GEOSCIENCES↗