Computer Physics Communications最新文献

An algorithm was developed for self-consistent field theory (SCFT) simulations of loop-containing polymers (LCPs), where the total number of independent loops (fundamental cycles in the polymer structure) is characterized by the “cycle rank.” Although various multi-ring and cage-like polymers have been reported, there is no explicit SCFT scheme for LCPs with multiple loops. An LCP was cut to open its fundamental cycles to form a pseudo-tree-like polymer. Conventional SCFT calculations for pseudo-tree-like polymers require extra spatial constraints on the pseudo-free endpoints generated by opening the fundamental cycle, which increases the computational cost. A reduction in the computational cost was observed, and the algorithm was applied to microphase-separated structures of small LCPs.

In this paper, a second-order finite volume Non-Homogeneous Riemann Solver is used to obtain an approximate solution for the two-dimensional shallow water magnetohydrodynamic (SWMHD) equations considering non-flat bottom topography. We investigate the stability of a perturbed steady state, as well as the stability of energy in these equations after a perturbation of a steady state using a dispersive analysis. To address the elliptic constraint $\nabla \cdot hB=0$, the GLM (Generalized Lagrange Multiplier) method designed specifically for finite volume schemes, is used. The proposed solver is implemented on unstructured meshes and verifies the exact conservation property. Several numerical results are presented to validate the high accuracy of our schemes, the well-balanced, and the ability to resolve smooth and discontinuous solutions. The developed finite volume Non-Homogeneous Riemann Solver and the GLM method offer a reliable approach for solving the SWMHD equations, preserving numerical and physical equilibrium, and ensuring stability in the presence of perturbations.

The phase transition phenomenon is an important research topic in various physical studies. However, it is difficult to define the order parameters in many complex systems involving self-organized structures. We propose a method to define order parameters using a variational autoencoder network. To demonstrate these capabilities, we trained a deep learning network with a dataset composed of spin configurations in a chiral magnetic system at various temperatures. It removes thermal fluctuations from the input data and leaves the remaining structural information with a spin magnitude. We define an order parameter with magnitude of output spins and compare the results with those of conventional analysis. The comparison indicates similar results. Using the order parameter, the thermal properties of the chiral magnetic system were investigated by varying the physical parameters and data size.

We develop a software package libEMMI_MGFD for 3D frequency-domain marine controlled-source electromagnetic (CSEM) modelling and inversion. It is the first open-source C program tailored for geometrical multigrid (GMG) CSEM simulation. An volumetric anisotropic averaging scheme has been employed to compute effective medium for modelling over uniform and nonuniform grid. The computing coordinate is aligned with acquisition geometry by rotation with the azimuth and dip angles, facilitating the injection of the source and the extraction of data with arbitrary orientations. Efficient nonlinear optimization is achieved using quasi-Newton scheme assisted with bisection backtracking line search. In constructing the modularized Maxwell solver and evaluating the misfit and gradient for 3D CSEM inversion, the reverse communication technique is the key to the compaction of the software while maintaining the computational performance. A number of numeric tests demonstrate the efficiency of the modelling while preserving the solution accuracy. A 3D marine CSEM inversion example has been examined for resistivity imaging.

Magnetocrystalline anisotropy, a crucial factor in magnetic properties and applications like magnetoresistive random-access memory, often requires extensive k-point mesh in first-principles calculations. In this study, we develop a Wannier orbital tight-binding model incorporating crystal and spin symmetries and utilize time-reversal symmetry to divide magnetization components. This model enables efficient computation of magnetocrystalline anisotropy. Applying this method to $L{1}_0$ FePt and FeNi, we calculate the dependence of the anisotropic energy on k-point mesh size, chemical potential, spin-orbit interaction, and magnetization direction. The results validate the practicality of the models to the energy order of $100[\mu \text{eV}/\text{f.u.}]$ for these systems.

In this paper, we present the KelbgLIP code to implement the previously obtained analytical density matrix that includes Coulomb long-range interactions. The method is based on the work of G. Kelbg, who derived a high temperature density matrix for the Coulomb potential. To include all long-range interactions in the density matrix, we use the Ewald technique, specifically the angular-averaged Ewald potential (AAEP). The solution of the Blöch equation within the AAEP has a direct analytic form that can be easily implemented in classical and quantum Monte Carlo or molecular dynamics codes, including exchange effects. The potential part of the density matrix remains finite at small distances, preventing the collapse of a two-component system. Using KelbgLIP, one can calculate the diagonal Kelbg-AAE pseudopotential and the pair density matrix. In the case of a hydrogen plasma, the code is able to calculate action, kinetic and potential energy in the path integral representation. We validated our approach by simulating a nondegenerate weakly coupled hydrogen plasma and obtained the thermodynamic limit in agreement with the Debye-Hückel approximation. In addition, we observe the agreement with classical simulations using the unbounded from below AAEP, which is possible in the weakly-coupled regime.

Multiscale nonequilibrium physics at large variations of local Knudsen number are encountered in applications of aerospace engineering and micro-electro-mechanical systems, such as high-speed flying vehicles and low pressure of the encapsulation. An accurate description of flow physics in all flow regimes within a single computation requires a genuinely multiscale method. The adaptive unified gas-kinetic scheme (AUGKS) is developed for such multiscale flow simulation. The AUGKS applies discretized velocity space to accurately capture the non-equilibrium physics in the multiscale UGKS, and adaptively employs continuous distribution functions following Chapman–Enskog expansion to efficiently recover near-equilibrium flow region in GKS. The UGKS and GKS are dynamically connected at the cell interface through the fluxes from the discretized and continuous gas distribution functions, which avoids any buffer zone between them. In this study, the AUGKS with rotation and vibration non-equilibrium is developed based on a multiple temperature relaxation model. The real gas effect in different flow regimes has been properly captured. To capture aerodynamic heating accurately, the heat flux modifications from the rotation and vibration modes are also included in the current scheme. Unstructured discrete particle velocity space is adopted to further improve the computational performance of the AUGKS. Numerical tests, including Sod tube, normal shock structure, high-speed flow around the two-dimensional cylinder and three-dimensional sphere and space vehicles, and an unsteady nozzle plume flow from the continuum flow to the background vacuum, have been conducted to validate the current scheme. In comparison with the original UGKS, the current scheme speeds up the computation, reduces the memory requirement, and maintains the equivalent accuracy for multiscale flow simulation, which provides an effective tool for nonequilibrium flow simulations, especially for the flows at low and medium speed.

The direct simulation Monte Carlo (DSMC) method has become a powerful tool for studying rarefied gas flows. However, for the DSMC method to be effective, the cell size must be smaller than the mean free path, and the time step smaller than the mean collision time. These constraints make it difficult to use the DSMC method in multiscale rarefied gas flows. Over the past decade, the particle Fokker-Planck (FP) method has been studied to address computational cost issues in the near-continuum regime. To capture the main features of the Boltzmann equation, various FP models have been proposed, such as the quadratic entropic FP (Quad-EFP) and the ellipsoidal statistical FP (ESFP). Nevertheless, few studies have clearly demonstrated that the FP method offers a computational advantage over the DSMC method without sacrificing accuracy. This is because conventional particle FP methods have employed first-order accuracy schemes. The present study proposes a unified stochastic particle ESFP (USP-ESFP) model. This model improves the accuracy of shear stress and heat flux predictions. Additionally, a spatial interpolation scheme is introduced to the particle FP method. The numerical test cases include relaxation problem, Couette flows, Poiseuille flows, velocity perturbation, and hypersonic flows around a cylinder. The results show that the USP-ESFP model agrees well with both analytical and DSMC results. Furthermore, the USP-ESFP model is found to be less sensitive to cell size and time step than the DSMC method, resulting in a factor of four speed-up for the considered hypersonic flow around a cylinder.

The presented software package is an advanced analogue of the famous HBOOK and, in part, ROOT packages.

The main features of the package are as follows.

Standard operations (accumulation, simulation, transformation) are extended up to 5D objects.

A new type of transformations of objects has been introduced, the x- transformation, which includes convolution of distributions.

Objects are accessed mainly by alphabetical name.

The formation of the object space is carried out using a data file, where the user can choose the form of setting attributes.

Automatic adjustment of object attributes is possible (only the number of channels is set).

The number of channels for each of the axes of the object is unlimited.

Operations between two objects (addition, subtraction, etc.) are possible with mismatched attributes. Only the ranks of the objects should match.

Data output is carried out in two forms, for graphics and for fit.

Group operations are provided for visualization, outputting files for graphics.

In the last version the program for x-converting 2D to 2D has been added.

A group of small programs has been added to simplify the user interface.

Improved representation of 2D objects, while removing the limit on the number of channels for all axes.

A number of bugs are fixed.

All programmes are written in FORTRAN-90.

The investigation has been performed at the Veksler and Baldin Laboratory of High Energy Physics, JINR.

This study presents an innovative direct numerical simulation approach for complex particle systems with irregular shapes and large numbers. Using partially saturated methods, it accurately models arbitrary shapes, albeit at considerable computational cost when integrating a compatible contact model. The introduction of a novel parallelization strategy significantly improves the performance of the contact model, enabling efficient four-way coupled simulations. Through hindered settling studies, the criticality of the explicit contact model for maintaining simulation accuracy is highlighted, especially at high particle volume fractions and low Archimedes numbers. The feasibility of simulating thousands of arbitrarily shaped convex particles is demonstrated with up to 1934 surface-resolved particles. The study also confirms the grid independence and linear convergence of the method. It shows for the first time that cube swarms settle 13 to 26% slower than swarms of volume-equivalent spheres across different Archimedes numbers (500 to 2000) and particle volume fractions (10 to 30%). These findings emphasize the shape dependence of particle systems and suggest avenues for exploring their nuanced dynamics.