Computer Physics Communications

This paper presents DeepFlame v2.0, a significant computational framework upgrade designed for high-performance combustion simulations on GPU-based heterogeneous architectures. The updated version implements a comprehensive CUDA-accelerated architecture incorporating fundamental combustion modelling components, including: implicit/explicit finite volume method (FVM) discretisation schemes, chemical kinetics integrators, thermophysical property models, and subgrid-scale closures for both fluid dynamics and combustion processes. The redesigned code supports diverse boundary conditions and discretisation schemes for broad applicability across combustion configurations. Key performance optimisations integrate advanced CUDA features including data coalescing techniques, CUDA Graphs for kernel scheduling, and NCCL-based multi-GPU communication. Validation studies employing the fully-implicit low-Mach solver demonstrate two-order-of-magnitude acceleration compared to conventional CPU implementations across canonical test cases, while maintaining numerical accuracy.

A revised version of the Matlab implementations of the expansions for the Fermi-Dirac integral and its derivatives is presented. In the new version, our functions for computing the Kummer functions M(a, b, x) and U(a, b, x) are incorporated into the software. The algorithms for computing the Kummer functions are described in [1,2]. In this way, the implementations of the expansions for the Fermi-Dirac integral can be used in earlier Matlab versions and can be easily adapted to GNU Octave. The efficiency of the computations is also greatly improved.

We present a Mathematica package AmpRed for the semi-automatic calculations of multi-loop Feynman amplitudes with high efficiency and precision. AmpRed implements the methods of integration by parts and differential equations in the Feynman-parameter representation. It allows for the calculations of general parametric integrals (which may not have momentum-space correspondences). Various user-friendly tools for multi-loop calculations, such as those to construct and solve differential equations for Feynman integrals, are provided. It can also deal with tensor algebras in non-relativistic field theories. Interfaces to some packages, like QGRAF and FORM, are also provided.

Numerical simulations of non-reacting/reacting flows at supercritical pressure near the critical points with real-fluid models in OpenFOAM often encounter instability and divergence issues unless the solution algorithm incorporates special techniques. In this paper, we develop a novel pressure-based solver, realFluidFoam, tailored for simulations of subsonic turbulent flows at transcritical and supercritical conditions in OpenFOAM. The realFluidFoam solver utilizes unique algorithms to enhance the stability and convergency while taking into account real-fluid effects. Its source code and implementation details are provided to facilitate a comprehensive understanding of integrating real-fluid models into fluid flow simulations in OpenFOAM. The realFluidFoam solver is validated against experimental data by performing large-eddy simulations (LESs) of liquid nitrogen injection and coaxial liquid nitrogen/preheated hydrogen injection under transcritical and supercritical conditions. The LES results show a satisfactory agreement with the experimental data, verifying that the realFluidFoam solver can accurately simulate transcritical and supercritical turbulent fluid flows over the wide range of pressure, especially near the critical points.

We introduce a lattice dynamics package which calculates elastic, thermodynamic and thermal transport properties of crystalline materials from data on their force and potential energy as a function of atomic positions. The data can come from density functional theory (DFT) calculations or classical molecular dynamics runs performed in a supercell. First, the model potential parameters, which are anharmonic force constants are extracted from the latter runs. Then, once the anharmonic model is defined, thermal conductivity and equilibrium properties at finite temperatures can be computed using lattice dynamics, Boltzmann transport theories, and a variational principle respectively. In addition, the software calculates the mechanical properties such as elastic tensor, Gruneisen parameters and the thermal expansion coefficient within the quasi-harmonic approximation (QHA). Phonons, elastic constants and thermodynamic properties results applied to the germanium crystal will be illustrated. Using the force constants as a force field, one may also perform molecular dynamics (MD) simulations in order to investigate the combined effects of anharmonicity and defect scattering beyond perturbation theory.

We detail our implementation of the random-phase-approximation based functional (RPAF) derived in Ref. [1] for the QUANTUM ESPRESSO (QE) package. We also make available in the Computer Physics Communications library the source files which are required in order to apply this functional within QE. We also provide the corresponding RPAF projector augmented wave (PAW) and ultrasoft pseudopotentials for most elements. Lastly, we benchmark the performance of the RPAF by calculating the equilibrium lattice constant and bulk modulus of a set of the same 60 crystals used by other authors to benchmark other functionals for both PAW and ultrasoft pseudopotentials. We find that the RPAF performs better overall as compared to the other most popular functionals.

SDGMPS is a Fortran program that calculates differential cross sections of elastic proton-nucleus scattering at intermediate energies based on the spin-dependent Glauber model. In the program, the Glauber model explicitly takes into account spin effects by using the spin-dependent nucleon-nucleon scattering amplitude, where the spin-orbit amplitude parameters are needed as input. It is particularly useful for analyses of the elastic proton scattering at both low and high momentum transfers and studies of the inner density distributions in nuclei. Such studies are an important part of the physics research program of the radiation beam facilities, such as the Heavy Ion Research Facility in Lanzhou (HIRFL).

A new parallelized simulation code is presented, which uses a Monte Carlo method to determine particle spectra in the KATRIN source. Reaction chains are generated from the decay of tritium within the source. The code includes all relevant processes: elastic scattering, ionization, excitation (electric, vibrational, rotational), recombination and various clustering processes. The main emphasis of the code is the calculation of particle spectra and particle densities and currents at specific points within the source. It features a new technique to determine these quantities. It also calculates target fields for the interaction of particles with each other as it is needed for recombination processes. The code has been designed for the KATRIN experiment but is easily adaptable for other tritium based experiments like Project 8. Geometry and background tritium gas flow can be given as user input. The code is parallelized using MPI and writes output using HDF5. Input to the simulation is read from a JSON description.

We present an efficient solver for massively-parallel simulations of convective, wall-bounded and incompressible porous media flows. The algorithm consists of a second-order finite-difference pressure-correction scheme, allowing the use of an efficient FFT-based solver in problems with different boundary conditions. The parallelization method is implemented in a two-dimensional pencil-like domain decomposition, which enables efficient parallel large-scale simulations. The original version of the code presented by van der Poel et al. (2015) [35] has been modified to solve the Darcy equation for the momentum transport, representative of porous media flows driven by buoyancy. Two schemes are implemented to treat the diffusive term of the advection-diffusion equation, namely a fully implicit and semi-implicit formulation. Despite exhibiting a higher computational cost per time step, the fully implicit scheme allows an efficient simulation of transient flows, leading to a smaller time-to-solution compared to the semi-implicit scheme. The implementation was verified against different canonical flows, and the computational performance was examined. To show the code's capabilities, the maximal driving strength explored has been doubled as compared to state-of-art simulations, corresponding to an increase of the associated computational effort of about 8 to 16 times. Excellent strong scaling performance is demonstrated for both schemes developed and for domains with more than 10^10 spatial degrees of freedom.

We present PolyMorph, a lightweight standalone C++ program that extends its predecessor PolyHoop by a finite-difference solver for multi-component reaction-advection-diffusion equations. PolyMorph simulates two integral parts of tissue morphogenesis in two dimensions: 1) the mechanics of cellular deformation, growth and proliferation, and 2) transport and reaction of an arbitrary number of chemical species. Both of these components are bidirectionally coupled, allowing cells to base their behavior on local information on concentrations and flow, and allowing the chemical transport and reaction kinetics to depend on spatial information such as the local cell type. This bidirectional feedback makes PolyMorph a versatile tool to study a variety of cellular morphogenetic processes such as chemotaxis, cell sorting, tissue patterning with morphogen gradients, Turing patterning, and diffusion- or supply-limited growth with sub-cellular resolution.