Computer Physics Communications

This article presents an innovative open-source software named ModelFLOWs-app,1 written in Python, which has been created and tested to generate precise and robust hybrid reduced order models (ROMs) fully data-driven. By integrating modal decomposition and deep learning in diverse ways, the software uncovers the fundamental patterns in dynamic systems. This acquired knowledge is then employed to enrich the comprehension of the underlying physics, reconstruct databases from limited measurements, and forecast the progression of system dynamics. The hybrid ROMs produced by ModelFLOWs-app combine experimental and numerical databases, serving as highly accurate alternatives to numerical simulations. As a result, computational expenses are significantly reduced, and the models become powerful tools for optimization and control in various applications. The exceptional capability of ModelFLOWs-app in developing reliable data-driven hybrid ROMs has been demonstrated across a wide range of applications, making it a valuable resource for understanding complex nonlinear dynamical systems and providing insights in diverse domains. This article presents the mathematical background, as well as a review of some examples of applications.

This study introduces GeoTaichi, an open-source high-performance numerical simulator designed for addressing multiscale geophysical problems. By leveraging the power of the Taichi parallel language, GeoTaichi maximizes the utilization of modern computer resources on multicore CPU and GPU architectures. It offers robust and reliable modules for the discrete element method (DEM), material point method (MPM), and coupled material point-discrete element method (MPDEM). These modules enable efficient solving of large-scale problems while being implemented in pure Python. The design philosophy of GeoTaichi focuses on creating a framework that is readable, extensible, and user-friendly. This paper highlights the coupling procedure of MPDEM, the code structures, and the most important features of GeoTaichi. Rigorous benchmark tests have been conducted to verify the validity and robustness of GeoTaichi. Additionally, the performance of GeoTaichi is compared with similar software tools in the field, underscoring a notable improvement in both computational efficiency and memory savings when compared to existing alternatives.

This paper presents a parallel implementation of the Discrete Unified Gas Kinetic Scheme (DUGKS) on the GPU system using the CUDA Fortran and CUDA C++ programming languages. Firstly, we conducted an extensive revision of our original CPU-based code, resulting in a threefold decrease in memory usage. This new implementation is also paired with a novel approach to compute cell face flux using trilinear interpolation. It is shown analytically that the interpolation-based approach to flux calculation is more accurate compared to the one used in the original DUGKS. The initial simulation results using this new approach suggest that trilinear interpolation can reduce numerical errors on a coarse mesh. For example, in the case of the decaying Taylor-Green vortex flow at a 1283 mesh resolution, the relative numerical error in the energy dissipation rate at ⁎, using the spectral simulation result as the benchmark, is approximately 30% lower than that of the original implementation. The improved GPU DUGKS method is applied to laminar and turbulent flows in periodic and wall-bounded boundary configurations. A performance comparison of the GPU implementation is also presented and compared to the previous CPU implementation. A maximum speedup of 7.64x was achieved on a desktop-level GPU compared to a 32-core CPU. The strong scaling test, conducted on an eight-GPU node, demonstrated the efficient utilization of available multiple GPU resources by the code.

Determination of topological invariants of graphene flakes, nanotubes, and fullerenes constitutes a challenging task due to its time-intensive nature and exponential scaling. The invariants can be organized in a form of a combinatorial polynomial commonly known as the Zhang-Zhang (ZZ) polynomial or the Clar covering polynomial. We report here a computer program, ZZPolyCalc, specifically designed to compute ZZ polynomials of large carbon nanostructures. The curse of the exponential scaling is avoided for a broad class of nanostructures by employing a sophisticated bookkeeping algorithm, in which each fragment appearing in the recursive decomposition is stored in the cache repository of molecular fragments indexed by a hash of the corresponding adjacency matrix. Although exponential scaling persists for the remaining nanostructures, the computational time is reduced by a few orders of magnitude owing to efficient use of hash-based fragment bookkeeping. The provided benchmark timings show that ZZPolyCalc allows for treating much larger carbon nanostructures than previously envisioned.

A new version of strong laser interaction model package for atoms and molecules is presented. Its capacities are enhanced by incorporating modules related to molecular orbital tomography (MOT) in length and velocity forms based on high-order harmonic spectra (HHS). This advanced package enables two-dimensional and three-dimensional MOT of both symmetric and asymmetric molecules using HHS, providing an efficient means for both experimental and theoretical investigations of molecular orbital structures. In addition, it can calculate the precise theoretical orbitals corresponding to those reconstructed by MOT. Furthermore, the package can calculate the transition dipole moment (TDM) in the plane wave approximation and allow for reference MOT based on TDM. It can evaluate the quality of reconstructed orbitals based on HHS and reveal the physical and numerical effects on MOT. This package is suitable for MOT under conditions of driving laser at different intensities and wavelengths, and can be applied to different molecules with various structures. It is designed to facilitate easy expansion for additional capabilities. The previous version of this program (AEWE_v1_0) may be found at https://doi.org/10.1016/j.cpc.2015.02.031.

The generalized geometric pore size distribution P(r; r_p | r_c) as function of pore radius r, probe sphere radius r_p, and coating thickness r_c for a periodic two-dimensional system composed of circles (GPSD-2D) had been defined recently. For r_p = r_c = 0 it reduces to the widely accepted pore radius distribution P(r) introduced by Gelb and Gubbins. The three-dimensional counterpart GPSD-3D for periodic systems composed of spheres is implemented here using an efficient Voronoi-based semi-analytic strategy that offers significant advantages compared with both a grid-based implementation and constrained nonlinear optimization with respect to speed, precision and memory requirements. Moreover, GPSD-3D is fully parallelized using OpenMP.

We present TTCF4LAMMPS, a toolkit for performing non-equilibrium molecular dynamics (NEMD) simulations to study the fluid behaviour at low shear rates using the LAMMPS software. By combining direct NEMD simulations and the transient-time correlation function (TTCF) technique, we study the fluid response to shear rates spanning 15 orders of magnitude. We present two examples for simple monatomic systems: one consisting of a bulk liquid and another with a liquid layer confined between two solid walls. The small bulk system is suitable for testing on personal computers, while the larger confined system requires high-performance computing (HPC) resources. We demonstrate that the TTCF formalism can successfully detect the system response for arbitrarily weak external fields. We provide a brief mathematical explanation for this feature. Although we showcase the method for simple monatomic systems, TTCF can be readily extended to study more complex molecular fluids. Moreover, in addition to shear flows, the method can be extended to investigate elongational or mixed flows as well as thermal or electric fields. The high computational cost needed for the method is offset by the two following benefits: i) the cost is independent of the magnitude of the external field, and ii) the simulations can be made highly efficient on HPC architectures by exploiting the parallel design of the algorithm. We expect the toolkit to be useful for computational researchers striving to study the nonequilibrium behaviour of fluids under experimentally-accessible conditions.

Validation is a vital part of any computational fluid dynamics study. Validation is done by comparing the computed results to the experimental measurements performed in a known configuration. In sooting flames, such a comparison is non-trivial since the measurements have a wide range of uncertainty due to difficulties in directly measuring soot volume fractions. This work introduces a different way to verify the computations using a software package called SootImage. In this proposed methodology, comparisons are not made directly to the computed properties of interest (soot volume fraction and temperature). Instead, a post-processing procedure is performed to obtain an image of the flame based on the computed properties. This reconstructed image is compared to an actual image of the flame being studied. The algorithm of the image reconstruction utilized within SootImage is presented in detail. Finally, the usage of SootImage is demonstrated on a co-flowing, laminar ethylene/air diffusion flame.

Reaction-diffusion systems are ubiquitous in nature, therefore they are widely studied both experimentally and theoretically. The driving force behind reaction-diffusion phenomena can be investigated via numerical modeling. However, in many cases the differential equations describing the systems are stiff, thus small temporal time step and high spatial resolution are required. These conditions result in expensive calculations, which hinders the exploration of such systems. PaReDiSo, is an open source program, developed to solve any kind of reaction-diffusion systems in two spatial dimensions. The kinetic equations with rate coefficients, the initial and boundary conditions specific to the system have to be provided in a user-friendly manner. Moreover, the frequently used boundary conditions, such as the Neumanm, Dirichlet and periodic boundaries, are built in the software. Due to the utilized CVODE integrator module both stiff and non-stiff equations can be solved. The software enables the user to run the calculations in parallel mode, using multiple CPU threads, since OpenMPI libraries are implemented. Thus, significant decrease in the required calculation time can be achieved. In this article the algorithm and the usage of the program is presented. The capabilities of the solver are tested on three commonly known reaction-diffusion phenomena: Turing pattern formation, Belousov-Zhabotinsky waves propagation, and diffusive fingering by autocatalysis. The results are validated on experimental and theoretical data found in the literature. Moreover, a performance test was executed, to investigate the extent of acceleration by the parallelization.

The search for new comparably light (well below the electroweak scale) feebly interacting particles is an exciting possibility to explain some mysterious phenomena in physics, among them the origin of Dark Matter. The sensitivity study through detailed simulation of projected experiments is a key point in estimating their potential for discovery. Several years ago we created the DMG4 package for the simulation of DM (Dark Matter) particles in fixed target experiments. The natural approach is to integrate this simulation into the same program that performs the full simulation of particles in the experiment setup. The Geant4 toolkit framework was chosen as the most popular and versatile solution nowadays. The simulation of DM particles production by this package accommodates several possible scenarios, employing electron, muon or photon beams and involving various mediators, such as vector, axial vector, scalar, pseudoscalar, or spin 2 particles. The bremsstrahlung, annihilation or Primakoff processes can be simulated. The package DMG4 contains a subpackage DarkMatter with cross section methods weakly connected to Geant4. It can be used in different frameworks. In this paper, we present the latest developments of the package, such as extending the list of possible mediator particle types, refining formulas for the simulation and extending the mediator mass range. The user interface is also made more flexible and convenient. In this work, we also demonstrate the usage of the package, the improvements in the simulation accuracy and some cross check validations.