Model Of Particle Interactions Research Articles

Self-organization of anti-aligning active particles: Waving pattern formation and chaos.

Recently, it has been shown that purely anti-aligning interaction between active particles may induce a finite wavelength instability. The formed patterns display intricate spatiotemporal dynamics, suggesting the presence of chaos. Here, we propose a quasi-one-dimensional simplification of the particle interaction model. This simplified model allows us to deduce amplitude equationsthat describe the collective motion of the active entities. We show that these equationsexhibit chaotic orbits. Furthermore, via direct numerical simulations of the particle's system, we discuss the pertinence of these amplitude equationsapproach for describing the particle's self-coordinated motions.

Experimental modeling of atmospheric discharge phenomena and charged dust particle interactions

Experimental modeling of atmospheric discharge phenomena and charged dust particle interactions

The Jefferson Lab Positron Physics Program

The Ce+BAF project at the Thomas Jefferson National Accelerator Facility intends to develop over the coming years a high-duty cycle, high intensity, and high polarization positron beam to serve a unique Nuclear Physics experimental program. It generically comprises the study of the effects of the two- and multi-photon exchange mechanisms, the investigation of the nuclear structure at the nucleonic and partonic scales, and tests of the standard model of particle physics and interactions. This proceedings illustrates this physics program through specific examples and presents the Ce+BAF positron injector concept.

Capillary imbibition of confined monodisperse emulsions in microfluidic channels.

We study imbibition of a monodisperse emulsion into high-aspect ratio microfluidic channels with the height h comparable to the droplet diameter d. Two distinct regimes are identified in the imbibition dynamics. In a strongly confined system (the confinement ratio d/h = 1.2 in our experiments), the droplets are flattened between the channel walls and move more slowly compared to the average suspension velocity. As a result, a droplet-free region forms behind the meniscus (separated from the suspension region by a sharp concentration front) and the suspension exhibits strong droplet-density and velocity fluctuations. In a weaker confinement, d/h = 0.65, approximately spherical droplets move faster than the average suspension flow, causing development of a dynamically unstable high-concentration region near the meniscus. This instability results in the formation of dense droplet clusters, which migrate downstream relative to the average suspension flow, thus affecting the entire suspension dynamics. We explain the observed phenomena using linear transport equations for the particle-phase and suspension fluxes driven by the local pressure gradient. We also use a dipolar particle interaction model to numerically simulate the imbibition dynamics. The observed large velocity fluctuations in strongly confined systems are elucidated in terms of migration of self-assembled particle chains with highly anisotropic mobility.

Predicting micro/nanoscale colloidal interactions through local neighborhood graph neural networks

Understanding interparticle interactions has been one of the most important topics of research in the field of micro/nanoscale materials. Many significant characteristics of such materials directly stem from the way their building blocks interact with each other. In this work, we investigate the efficacy of a specific category of Machine Learning (ML) methods known as interaction networks in predicting interparticle interactions within colloidal systems. We introduce and study Local Neighborhood Graph Neural Networks (LN-GNNs), defined according to the local environment of colloidal particles derived from particle trajectory data. The LN-GNN framework is trained for unique categories of particle neighborhood environments in order to predict interparticle interactions. We compare the performance of the LN-GNN to a baseline interaction network with a simpler architecture and to an Instance-Based ML algorithm, which is computationally more expensive. We find that the prediction performance of LN-GNN measured as an average normalized mean absolute error outperforms the baseline interaction network by a factor of 2–10 for different local neighborhood configurations. Furthermore, LN-GNN’s performance turns out to be very comparable to the instance-based ML framework while being an order of magnitude less expensive in terms of the required computation time. The results of this work can provide the foundations for establishing accurate models of colloidal particle interactions that are derived from real particle trajectory data.

Hidden dependencies in model independent tests of DAMA

For nearly two decades the DAMA Collaboration has been observing a modulating signal compatible with that expected from a dark matter presence in our galaxy. However, interpretations of this with the standard assumptions for dark matter particles are strongly ruled out by a large number of other experiments. This tension can be relaxed somewhat by making more tailored choices for the dark matter model and properties of interest, but expanding the models of interest in such a way makes it impossible to test the DAMA modulation conclusively. In order to understand the exact nature of this signal, we need to use a detector based on the same target (NaI(Tl)), which would be sensitive to exactly the same particle interaction models as DAMA. There are a number of such experiments in the data taking or commissioning stages designed to do just this, two of which (ANAIS and COSINE) recently released their results after 3 years of data taking. Interestingly, the modulation observed by the two experiments deviate from each other by 2\sigmaσ, while being within 3\sigmaσ of the DAMA result. This paper addresses potential differences between NaI(Tl) based detectors that could lead to the differing results to date, with a particular focus on the quenching factor

Low-Pressure Cold Spray Deposition Window Derived from a One-Dimensional Analytical Model

Low-pressure cold spray (LPCS) coating deposition requires the consideration of multiple parameters to define spraying conditions. The use of a parameter window provides an integral approach to achieving this goal. In this work, an LPCS deposition window for zinc powders was obtained through the development of a one-dimensional analytical model of fluid and particle interaction. The model considers powder particle injection downstream of the nozzle and follows the particle from injection to impact. The model equations relate the particle velocity (vp) to the process parameters, such as the gas pressure (P0) and temperature (T0), particle size (dp) and stand-off distance (SoD). The values of the particle velocity (vp) at the nozzle exit and during the “free-jet”, as well as the drag coefficient (Cd), were calculated using experimental spraying conditions for Cu and Al that have previously been documented in LPCS studies. The model’s accuracy and applicability to other materials were confirmed upon comparing the results with those in the aforementioned studies. Moreover, the definition of the model equations allowed for the identification of three new parameters: (γ) the maximum ideal particle velocity, (β) the capacity to accelerate the powder particle inside the nozzle and (α) the deceleration of the particle in the free-jet zone. These parameters have not previously been published and allow for comparative evaluation between LPCS processes.

Agglomeration Regimes of Particles under a Linear Laminar Flow: A Numerical Study

In this work, a combined smoothed particle hydrodynamics and discrete element method (SPH-DEM) model was proposed to model particle agglomeration in a shear flow. The fluid was modeled with the SPH method and the solid particles with DEM. The system was governed by three fundamental dimensionless groups: the Reynolds number Re (1.5~150), which measured the effect of the hydrodynamics; the adhesion number Ad (6 × 10−5~6 × 10−3), which measured the inter-particle attraction; and the solid fraction α, which measured the concentration of particles. Based on these three dimensionless groups, several agglomeration regimes were found. Within these regimes, the aggregates could have different sizes and shapes that went from long thread-like structures to compact spheroids. The effect of the particle–particle interaction model was also investigated. The results were combined into ‘agglomeration maps’ that allowed for a quick determination of the agglomerate type once α, Re, Ad were known.

Influence of large seed particle on acoustic particle interaction dynamics: A numerical study

Acoustic agglomeration as a promising preconditioning process for fine particle removal has been proven to be inefficient for submicron particles. In order to enhance the performance of acoustic agglomeration, large seed particles have been introduced into the flue gas. To understand the influence of seed particles on acoustic agglomeration, a nondimensional model of particle interaction was developed by taking into account all important particle interaction mechanisms. The simulated particle trajectories were validated against experimental data. The interaction dynamics of a seed particle and its neighboring fine particles was examined, and the dimensionless first collision time under different conditions was obtained. The results suggest that the enhancement of acoustic agglomeration with seed particle is mainly due to the acoustic wake effect. The overall collision kernel for the acoustic agglomeration was referred from the collision time. The results reveal that the dimensionless collision kernel almost increases linearly with the Stokes number of the seed particle, whereas its dependence on the Schmidt number of the fine particle varies significantly. The collision kernel for acoustic agglomeration was further compared with traditional collision kernels based on differential sedimentation, Brownian diffusion, laminar shear and turbulent shear. The results demonstrate that acoustic field indeed remarkably enhances the collision rate.

Predestined dark matter varieties in the simplest left-right model

In the simplest left-right extension of the Standard Model of particle interactions with one scalar bidoublet and one SU(2)R triplet for seesaw Majorana neutrino masses, the addition of a variety of fermion and scalar multiplets automatically makes them stable (predestined) dark matter candidates. We discuss the interplay of this dark ensemble in relic abundance and direct searches.

FEM ANALYSIS OF ENERGY LOSS DUE TO WAVE PROPAGATION FOR MICRO-PARTICLE IMPACTING SUBSTRATE WITH HIGH VELOCITIES

The impact between particles and material surface is a micro-scaled physical phenomenon found in various technological processes and in the study of the mechanical properties of materials. Design of materials with desired properties is a challenging issue for most industries. And especially in aviation one of the most important factors is mass. Recently with the innovations in 3D printing technologies, the importance of this phenomenon has increased. Numerical simulation of multi-particle systems is based on considering binary interactions; therefore, a simplified but as much accurate as possible particle interaction model is required for simulations. Particular cases of axisymmetric particle to substrate contact is modelled at select impact velocities and using different layer thicknesses. When modelling the particle impact at high contact velocity, a substrate thickness dependent change in the restitution coefficient was observed. This change happens is due to elastic waves and is important both to coating and 3D printing technologies when building layers of different properties materials.

A note on N-soliton solutions for the viscid incompressible Navier–Stokes differential equation

Repetitive curling of the incompressible viscid Navier–Stokes differential equation leads to a higher-order diffusion equation. Substituting this equation into the Navier–Stokes differential equation transposes the latter into the Korteweg–De Vries–Burgers-equation with the Weierstrass p-function as the soliton solution. However, a higher-order derivative of the studied variable produces the so-called N-soliton solution, which is comparable with the N-soliton solution of the Kadomtsev–Petviashvili equation. Experiments have made it clear that the system behaves like a coupled (an)harmonic oscillator on a discrete collapsed-state level. The streamlines obtained are derivatives of the error function as a function of the obtained Lax functional of the particle filaments dynamics induced by the (hypothetical) Calogero–Moser many-body system with elliptical potential and are the so-called Hermite functions. Hermite tried to introduce doubly periodic Hermite functions (the so-called Hermite problem) using coefficients related to the Weierstrass p-function. A solution-sensitive analysis of the incompressible viscid Navier–Stokes equation is performed using the Lamb vector. Cases with a meaningful potential-energy contribution require a particle interaction model with an N-soliton solution using a hierarchy-like solution of the Kadomtsev–Petviashvili equation. A three-soliton solution is emulated for the cylinder-wake problem. Our analytical results are put in perspective by comparison with two well-studied benchmark cases of fluid dynamics: the cylinder-wake problem and the driven-lid problem. The time-average velocity distribution (limit of streamline patterns) is consistent with published results and is enclosed in an asymmetrical lemniscate.

Electron Acceleration by Magnetosonic Waves in the Deep Inner Belt (L = 1.5–2) Region During Geomagnetic Storm of August 2018

AbstractThe relativistic electron acceleration in the inner radiation belt have received little attention in the past due to sparse measurements. The 90° minimum pitch angle distributions of electrons in extremely low L‐shells during storms are speculated to be preferentially heated by fast magnetosonic waves. The high‐quality measurements of relativistic electrons by instruments onboard Van Allen Probes and ZH–1 provide a great opportunity to investigate the dynamics of relativistic electrons in the inner radiation belt. At extremely low L‐shells (L 2), a weak flux enhancement (increased by 2–3 times) of 100s keV electrons and the corresponding formation of butterfly PADs are observed during the major geomagnetic storm (minimum Dst ≈ −179 nT) occurred in August 2018. Simultaneously the magnetosonic waves, accompanied with weak hiss waves, were observed also in such low L‐shells. Combining with a numerical simulation of wave and particle interaction model, magnetosonic waves are thought to play an important role in electron acceleration and formation of butterfly PADs during this storm, which is the first direct observation in such low L‐shells.

Influence of NaI background and mass on testing the DAMA modulation

NaI experiments should be sensitive to the same DM-SM interactions proposed to explain the observed DAMA modulation. As such, they are often called a ‘model independent’ test of the signal. While the same signal will be produced at all NaI detectors, the ability to observe it is strongly dependent on the experimental set up - in particular the mass and background of the target. We present here a study on how changes to these values influence the ability of a detector to observe a characteristic DM modulation. We consider both the standard elastic, spin independent WIMP and a model independent analysis assuming exactly the modulation signal observed by DAMA (i.e., making no assumptions about the particle interaction model producing this signal), and find that in both cases a lower background is favoured over a higher exposure mass (based on currently achievable levels).

Solid Particle Simulation with a New Particle Interaction

A particle method is a state-of-the-art method in computational fluid dynamics. The specialty of the particle method is tracking each particle that carries its own physical quantities, such as velocity, pressure, and position. Therefore, the large deformation of a free surface can be simulated. In this paper, the concept of the fully Lagrangian approach is extended in its applicability to the solid particle with new particle interaction models, which are the friction and drag models. The newly developed particle method with the new particle interaction models simulated mobile sea-bed behavior under very violent waves due to the broken dam problem. The numerical results were compared to corresponding experimental results for validation. The validated particle method demonstrated the mobile sea-bed behavior with various densities of soil particles. Furthermore, solid-particle interaction model results were also compared with those of fluid models to show the difference and to prove the implementation.

A Simulation of Soil Dumping Using Moving Particle Semi-Implicit Method

Kim, K.S. and Lee, J.H., 2021. A simulation of soil dumping using moving particle semi-implicit method. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 549–553. Coconut Creek (Florida), ISSN 0749-0208. Soil dumping is one of most important problems on the coastal and ocean construction project. In general, the computational fluid dynamics method used grid system to simulate soil particle under flow with concentration. It can be useful for fast calculation; however, it is restricted to demonstrate its movement. The Moving Particle Semi-implicit (MPS) method follows fully Lagrangian approach, thus it can simulate soil particle behavior due to tracking each particle. In this study, the newly developed MPS method modified for solid particle was used to simulate soil dumping. For the solid particle interaction, drag force and friction force term were implemented instead of viscosity term in the governing equation. The friction force is due to friction between solid particles, and the drag force can be calculated by relative velocity around center particle within effective range. All the solid particle interaction models were validated by corresponding physical phenomena. The numerical results were compared to the corresponding experimental results and they show good agreement in the tendency of behavior.

LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials. Program SummaryProgram Title: Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS)CPC Library link to program files:https://doi.org/10.17632/cxbxs9btsv.1Developer's repository link:https://github.com/lammps/lammpsLicensing provisions: GPLv2Programming language: C++, Python, C, FortranSupplementary material:https://www.lammps.orgNature of problem: Many science applications in physics, chemistry, materials science, and related fields require parallel, scalable, and efficient generation of long, stable classical particle dynamics trajectories. Within this common problem definition, there lies a great diversity of use cases, distinguished by different particle interaction models, external constraints, as well as timescales and lengthscales ranging from atomic to mesoscale to macroscopic.Solution method: The LAMMPS code uses parallel spatial decomposition, distributed neighbor lists, and parallel FFTs for long-range Coulombic interactions [1]. The time integration algorithm is based on the Størmer-Verlet symplectic integrator [2], which provides better stability than higher-order non-symplectic methods. In addition, LAMMPS supports a wide range of interatomic potentials, constraints, diagnostics, software interfaces, and pre- and post-processing features.Additional comments including restrictions and unusual features: This paper serves as the definitive reference for the LAMMPS code.

Numerical investigation of oxidation and dissolution behavior in the fuel cladding using MPS-CV method

The Moving Particle Semi-implicit-Controlled Volume (MPS-CV) method, based on the MPS method and Finite Volume Method (FVM), is a particle-grid coupling method. In this method, the particle interaction models in the MPS method are used to discretize and solve the momentum equation. For the eutectic reaction model, the FVM is used to solve the mass transfer equation if the particle locates at the boundary or the interface between different substances. In contrast, the particle interaction models are still used to discretize and solve the remaining particles' mass transfer equations. Therefore, it has advantages in describing fluid interfaces with large deformation and phase transition problems. Simultaneously, the MPS-CV method avoids the apparent error in calculating the mass transfer equation of boundary and interface between different substances due to the truncation of support domain in that area particles while using particle interaction models in the MPS method. In this study, the simulation of one-dimensional mass transfer and phase transition was used to verify the MPS-CV method, and the results were compared with those obtained by the MPS method. It showed that the MPS-CV method could get more accurate results in the calculation than the MPS method. Then the cladding oxidation mechanism at 1300 ~ 1800 K and the dissolution behavior between ZrO2 and molten zirconium at 2373 ~ 2573 K were analyzed using the MPS-CV method. The results indicated that the change of oxygen content obeyed parabolic laws. So did the oxide and α-Zr(O) layers' growth rates in cladding oxidation. And compared with the fixed parabolic relations used in commercial codes, the MPS-CV method can obtain the corresponding relationships according to different reaction conditions. The dissolution between ZrO2 and molten zirconium at high temperatures showed a parabolic pattern in the early stage. In the later stage of the reaction, the oxygen in the melt gradually reached saturation, and the solid ZrO2 did not continue to melt. The simulation results of the molten zirconium with the same volume but different contact areas with ZrO2 crucible showed that the larger the contact area was, the higher the growth rate of oxygen content in the melting the early stage of the reaction was. And it also showed that the larger the contact area was, the less dissolution volume of the ZrO2 crucible was.

ЭФФЕКТИВНОСТЬ РЕГИСТРАЦИИ НЕЙТРОНОВ НИЗКОЙ ЭНЕРГИИ НЕЙТРОННЫМИ ДЕТЕКТОРАМИ НА ОСНОВЕ ГАЗОРАЗРЯДНЫХ СЧЕТЧИКОВ

When analyzing the results obtained in measurements on neutron detectors with a low energy threshold, it is necessary to know the dependence of the neutron detection efficiency on their kinetic energy in information channels of various types, both for "open" neutron counters, and for counters surrounded by a moderator. Having a physical model of particle interactions based on the Geant4 package, it is possible to calculate the detection efficiency for various types of detectors, which are used in experiments conducted at the Tien Shan high-mountain station related to the registration of a neutron flux. The paper presents several simulation models developed for neutron detectors.

Nonhomogeneity of phase state in a dusty plasma monolayer with nonreciprocal particle interactions

A monolayer—quasi-two-dimensional finite system—of Yukawa particles in a harmonic trap is under consideration. The effect of monolayer nonhomogeneity on dynamic properties and melting is studied. The results for two models of particle interactions are compared. The first model includes the reciprocal Yukawa potential and electrostatic harmonic trap. The second model additionally employs the point charge approximation of plasma wakes. It accounts for the nonreciprocity of interactions and anomalous heating of particle motion observed in dusty plasma experiments. It is demonstrated that in the point-wake model, both out-of-plane and in-plane kinetic energies of particles are radially dependent. This effect transforms the spatial distribution of dynamic characteristics in the monolayer. We show that the nonuniformity of monolayer properties might lead to several nonuniform melting scenarios and several scenarios of phase coexistence in the system. In the monolayer without nonreciprocal interactions, molten periphery coexists with a solid core. In the monolayer with plasma wakes, the opposite scenario is observed due to the joint effect of nonreciprocity and structural nonuniformity in the system. A perspective method to determine the position of the phase boundary is proposed.