Computer Physics Communications

MFC is an open-source tool for solving multi-component, multi-phase, and bubbly compressible flows. It is capable of efficiently solving a wide range of flows, including droplet atomization, shock–bubble interaction, and bubble dynamics. We present the 5- and 6-equation thermodynamically-consistent diffuse-interface models we use to handle such flows, which are coupled to high-order interface-capturing methods, HLL-type Riemann solvers, and TVD time-integration schemes that are capable of simulating unsteady flows with strong shocks. The numerical methods are implemented in a flexible, modular framework that is amenable to future development. The methods we employ are validated via comparisons to experimental results for shock–bubble, shock–droplet, and shock–water-cylinder interaction problems and verified to be free of spurious oscillations for material-interface advection and gas–liquid Riemann problems. For smooth solutions, such as the advection of an isentropic vortex, the methods are verified to be high-order accurate. Illustrative examples involving shock–bubble-vessel-wall and acoustic–bubble-net interactions are used to demonstrate the full capabilities of MFC.

Fluid driven fractures propagate in the upper earth crust either naturally or in response to engineered fluid injections. The quantitative prediction of their evolution is critical in order to better understand their dynamics as well as to optimize their creation. We present an open-source Python implementation of a hydraulic fracture growth simulator based on the implicit level set algorithm originally developed by Peirce & Detournay (2008). This algorithm couples a finite discretization of the fracture with the use of the near tip asymptotic solutions of a steadily propagating semi-infinite hydraulic fracture. This allows to resolve the multi-scale processes governing hydraulic fracture propagation accurately, even on relatively coarse meshes. We present an overview of the mathematical formulation, the numerical scheme and the details of our implementation. A series of problems including a radial hydraulic fracture verification test, the propagation of a height contained hydraulic fracture, the lateral spreading of a magmatic dyke and an example of fracture closure are presented to demonstrate the capabilities, accuracy and robustness of the implemented algorithm.

Simple Quantum Integro-Differential Solver (SQuIDS) is a C++ code designed to solve semi-analytically the evolution of a set of density matrices and scalar functions. This is done efficiently by expressing all operators in an SU(N) basis. SQuIDS provides a base class from which users can derive new classes to include new non-trivial terms from the right hand sides of density matrix equations. The code was designed in the context of solving neutrino oscillation problems, but can be applied to any problem that involves solving the quantum evolution of a collection of particles with Hilbert space of dimension up to six. The previous version of this program (AEXG_v1_0) may be found at https://doi.org/10.1016/j.cpc.2015.06.022.

In this paper we present the algorithm and implementation of an open-source immersed boundary code sdfibm, which is based on OpenFOAM v6 and written in C++. The immersed boundary method (“ibm” of the name) treats the velocity field as the volume average of solid and fluid velocities, and applies the volume-average discrete forcing to account for the solid-fluid interaction. The signed distance field (“sdf” of the name) representation of the solid shape, together with the proposed pyramid decomposition method, allow accurate calculations of the volume fraction field created by solids overlapping with an arbitrary unstructured fluid mesh. SDF removes the need of intersection test between the solid and fluid mesh, or the discretization and re-sampling of the shape. Users can freely combine different solid components (shapes, materials, and motion constraints) into new solids within the plain-text input file, and implement new shapes and motion constrains easily. sdfibm is an efficient and robust tool for exploring complex solid-fluid interactions in a fully-resolved sense, and can generate data for closure models in upscaling procedures.

In this work we present a hybrid discontinuous Galerkin scheme for the solution of extremely anisotropic diffusion problems arising in magnetized plasmas for fusion applications. Unstructured meshes, non-aligned with respect to the dominant diffusion direction, allow an unequalled flexibility in discretizing geometries of any shape, but may lead to spurious numerical diffusion. Curved triangles or quadrangles are used to discretize the poloidal plane of the machine, while a structured discretization is used in the toroidal direction. The proper design of the numerical fluxes guarantees the correct convergence order at any anisotropy level. Computations performed on well-designed 2D and 3D numerical tests show that non-aligned discretizations are able to provide spurious diffusion free solutions as long as high-order interpolations are used. Introducing an explicit measure of the numerical diffusion, a careful investigation is carried out showing an exponential increase of this latest with respect to the non-alignment of the mesh with the diffusion direction, as well as an exponential decrease with the polynomial degree of interpolation. A brief assessment of the method with respect to two finite-difference schemes using non-aligned discretization, but classically used in fusion modeling, is also presented.

Predictive Molecular Dynamics simulations of thermal transport require forcefields that can simultaneously reproduce several structural, thermodynamic and vibrational properties of materials like lattice constants, phonon density of states, and specific heat. This requires a multi-objective optimization approach for forcefield parameterization. Existing methodologies for forcefield parameterization use ad-hoc and empirical weighting schemes to convert this into a single-objective optimization problem. Here, we provide and describe software to perform multi-objective optimization of Stillinger–Weber forcefields (SWFF) for two-dimensional layered materials using the recently developed 3rd generation non-dominated sorting genetic algorithm (NSGA-III). NSGA-III converges to the set of optimal forcefields lying on the Pareto front in the multi-dimensional objective space. This set of forcefields is used for uncertainty quantification of computed thermal conductivity due to variability in the forcefield parameters. We demonstrate this new optimization scheme by constructing a SWFF for a representative two-dimensional material, 2H-MoSe_2 and quantifying the uncertainty in their computed thermal conductivity.

A recently discovered universal rank-based matrix method to extract trends from noisy time series is described in Ierley and Kostinski (2019) but the formula for the output matrix elements, implemented there as an open-access supplement MATLAB computer code, is O(N^4), with N the matrix dimension. This can become prohibitively large for time series with hundreds of sample points or more. Based on recurrence relations, here we derive a much faster O(N^2) algorithm and provide code implementations in MATLAB and in open-source JULIA. In some cases one has the output matrix and needs to solve an inverse problem to obtain the input matrix. A fast algorithm and code for this companion problem, also based on the recurrence relations, are given. Finally, in the narrower, but common, domains of (i) trend detection and (ii) parameter estimation of a linear trend, users require, not the individual matrix elements, but simply their accumulated mean value. For this latter case we provide a yet faster O(N) heuristic approximation that relies on a series of rank one matrices. These algorithms are illustrated on a time series of high energy cosmic rays with N > 4 x 10^4 .

We present the Tight-Binding Studio (TB Studio) software package that calculates the different parameters of a tight-binding Hamiltonian from a set of Bloch energy bands obtained from first principle theories such as density functional theory, Hartree–Fock calculations or semi-empirical band-structure theory. This will be helpful for scientists who are interested in studying electronic and optical properties of structures using Green’s function theory within the tight-binding approximation. TB Studio is a cross-platform application written in C++ with a graphical user interface design that is user-friendly and easy to work with. This software is powered by Linear Algebra Package C interface library for solving the eigenvalue problems and the standard high performance OpenGL graphic library for real time plotting. TB Studio and its examples together with the tutorials are available for download from tight-binding.com.

Fractal dimension (FD) has become a very useful tool in neuroscience with a wide range of applications in characterizing several neurodegenerative diseases. The most commonly used method for computing the FD of brain tissues is box-counting. This technique performs very well on 2D images and 3D volumes; however, it presents several drawbacks when processing cortical surfaces in 3D. In this study, we present a MATLAB program for computing the FD of 3D surfaces based on spherical harmonics. We developed a novel MATLAB program, called UJA-SHFD, based on a spherical harmonics FD algorithm which overcomes the limitations of the classical box-counting algorithm when processing 3D surfaces. Moreover, spherical-harmonic-based FD (SHFD) enables the processing of both global (providing a single FD value for the entire surface) and local level assessments in each cortical surface vertex. UJA-SHFD has been specifically designed and tested for processing cortical surfaces obtained from the FreeSurfer software suite. Nevertheless, the program can also process any kind of surface in the Wavefront OBJ format. UJA-SHFD can be used both through a graphical user interface and at the command line. The present study demonstrates the usefulness of UJA-SHFD through its application to a neuroimaging study looking at the progression of brain atrophy in Alzheimer’s disease. UJA-SHFD is a novel MATLAB program with the goal of developing neuroimaging analyses of FD computation for the investigation of brain morphological changes in neurodegenerative and neuropsychiatric disorders. The MATLAB source code of UJA-SHFD is freely available.

We introduce the package SIDES (Schrödinger Integro-Differential Equation Solver) that solves the integro-differential Schrödinger equation for elastic scattering of a nonlocal optical potential in coordinate space. The code is capable of treating the Coulomb interaction without restrictions. The method is based on previous developments by Jacques Raynal in the DWBA07 code. Elastic scattering observables such as differential and integral cross sections, as well as analyzing power and spin rotation functions for both neutron and proton projectiles are evaluated, with no restriction on the type of nonlocality of the potential nor on the beam energy. The corresponding distorted wavefunctions are calculated as well. The SIDES package includes a Perey–Buck potential generator with two parametrizations. It includes as well local potential parametrizations and allows for mixing local and nonlocal contributions. Benchmarks are performed and discussed.