Computer Physics Communications最新文献

{"title":"Large scale stress-aware epitaxial growth simulations using a hybrid Molecular Dynamics-Monte Carlo method","authors":"Anthony Payet ,&nbsp;SangJun Yun ,&nbsp;JeongHwan Han ,&nbsp;Alexander Schmidt ,&nbsp;Inkook Jang ,&nbsp;Dae Sin Kim","doi":"10.1016/j.cpc.2025.109849","DOIUrl":"10.1016/j.cpc.2025.109849","url":null,"abstract":"<div><div>A large scale hybrid method combining Molecular Dynamics with Monte Carlo is implemented for the simulation of Silicon Germanium heteroepitaxy and the prediction of dislocation apparition. On one hand, using the Tersoff potential, the Molecular Dynamics part allows for realistic structure relaxation as well as the creation of a highly discretized potential energy surface. On the other hand, the Monte Carlo part allows for a fast deposition simulation. The combination is furthermore improved to apply the method in two different large scale domains. First, with structures holding millions of atoms and second in a supercomputer environment with thousands of processing cores. The method results show a very close agreement regarding the critical thickness of heteroepitaxied structures grown at their stable states.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109849"},"PeriodicalIF":3.4,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linearized quantum lattice-Boltzmann method for the advection-diffusion equation using dynamic circuits","authors":"David Wawrzyniak ,&nbsp;Josef Winter ,&nbsp;Steffen Schmidt ,&nbsp;Thomas Indinger ,&nbsp;Christian F. Janßen ,&nbsp;Uwe Schramm ,&nbsp;Nikolaus A. Adams","doi":"10.1016/j.cpc.2025.109856","DOIUrl":"10.1016/j.cpc.2025.109856","url":null,"abstract":"<div><div>We propose a quantum algorithm for the linear advection-diffusion equation (ADE) Lattice-Boltzmann method (LBM) that leverages dynamic circuits. Dynamic quantum circuits allow for an optimized quantum collision operator algorithm by incorporating partial measurements as an integral step. The quantum circuit efficiently adapts during execution based on digital information obtained via mid-circuit measurements.</div><div>The proposed new collision algorithm is implemented as a fully unitary operator, which facilitates the computation of multiple time steps without state reinitialization. Unlike previous quantum collision operators that rely on linear combinations of unitaries, the proposed algorithm does not exhibit a probabilistic failure rate. Our proposed algorithm embeds no more than two distribution functions simultaneously within the quantum state, irrespective of the velocity set. Compared to previous quantum algorithms, this approach reduces both the qubit overhead and circuit complexity required to execute the collision operator and encode the distributions.</div><div>The quantum collision algorithm is validated against classical LBM simulations in 1D and 2D, showing excellent agreement. Performance analysis over multiple time steps highlights advantages of the proposed method compared to previous methods.</div><div>As an additional variant, a hybrid quantum-digital approach is proposed, which reduces the number of mid-circuit measurements, thus improving the efficiency of the quantum collision algorithm.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109856"},"PeriodicalIF":3.4,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SWtools: A Python package implementing iterative solvers for soliton solutions of nonlinear Schrödinger-type equations","authors":"O. Melchert ,&nbsp;A. Demircan","doi":"10.1016/j.cpc.2025.109851","DOIUrl":"10.1016/j.cpc.2025.109851","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Solitons are ubiquitous in nature and play a pivotal role in the structure and dynamics of solutions of nonlinear propagation equations. In many instances where solitons are expected to exist, analytical expressions of these special objects are not available. The presented software fills this gap, allowing users to numerically calculate soliton solutions for a generic nonlinear Schrödinger-type equation by iteratively solving an associated nonlinear eigenvalue problem. The package implements a range of methods, including the spectral renormalization method, and a relaxation method for the problem with additional normalization constraint. We verify the implemented methods in terms of a problem for which an analytical soliton expression is available, and demonstrate the implemented functionality by numerical experiments for example problems in nonlinear optics and matter-wave solitons in quantum mechanics. For common variants of the considered equation, &lt;span&gt;SWtools&lt;/span&gt; also implements functions retrieving linear stability eigenvalues and modes for its solitons. The presented Python package is open-source and released under the MIT License in a publicly available software repository.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Program summary&lt;/h3&gt;&lt;div&gt;&lt;em&gt;Program Title:&lt;/em&gt; Solitary wave tools (&lt;span&gt;SWtools&lt;/span&gt;)&lt;/div&gt;&lt;div&gt;&lt;em&gt;CPC Library link to program files:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://doi.org/10.17632/y55t9chcz6.1&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Developer's repository link:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://github.com/omelchert/SWtools&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Licensing provisions:&lt;/em&gt; MIT&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; Python&lt;/div&gt;&lt;div&gt;&lt;em&gt;Supplementary material:&lt;/em&gt; Online documentation and usage examples are hosted on GitHub under &lt;span&gt;&lt;span&gt;https://github.com/omelchert/SWtools&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;. A Code Ocean compute capsule demonstrating the calculation of a soliton solution for a higher-order nonlinear Schrödinger equation is available under &lt;span&gt;&lt;span&gt;https://doi.org/10.24433/CO.5557616.v1&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Numerical computation of solitary wave solutions for nonlinear Schrödinger-type equations. Two variants of the corresponding nonlinear eigenvalue problem (NEVP) are considered: a “bare” NEVP, where a solution with prescribed eigenvalue is computed, and a “constrained” NEVP with &lt;em&gt;a priori&lt;/em&gt; unknown eigenvalue, where a solution with prescribed norm is computed.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; &lt;span&gt;SWtools&lt;/span&gt; implements iterative solvers for both problem variants. While the bare NEVP is solved using the spectral renormalization method (SRM) [1], the constrained NEVP is solved using a custom nonlinear successive overrelaxation method (NSOM).&lt;/div&gt;&lt;div&gt;&lt;em&gt;Additional comments including restrictions and unusual features:&lt;/em&gt; This document serves as a reference for &lt;span&gt;SWtools&lt;/span&gt;. For a concise presen","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109851"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep operator networks for Bayesian parameter estimation in PDEs","authors":"Amogh Raj,&nbsp;Sakol Bun,&nbsp;Keerthana Srinivasa,&nbsp;Carol Eunice Gudumotou,&nbsp;Arash Sarshar","doi":"10.1016/j.cpc.2025.109853","DOIUrl":"10.1016/j.cpc.2025.109853","url":null,"abstract":"<div><div>We present a novel framework combining Deep Operator Networks (DeepONets) with Physics-Informed Neural Networks (PINNs) to solve partial differential equations (PDEs) while estimating their unknown parameters. By integrating data-driven learning with physical constraints, our method achieves robust and accurate solutions across diverse scenarios. Bayesian training is implemented through variational inference, allowing for comprehensive uncertainty quantification for both data and model uncertainties. This ensures reliable prediction and parameter estimates even in noisy conditions or when some of the physical equations governing the problem are missing. The framework demonstrates its efficacy in solving forward and inverse problems, including the 1D unsteady heat equation, 2D reaction-diffusion equations, 3D eigenvalue problem, and various regression tasks with sparse, noisy observations. This approach provides a computationally efficient and generalizable method for addressing uncertainty quantification in PDE surrogate modeling.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109853"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A compact gas-kinetic scheme with scalable hp multigrid acceleration for steady-state computation on 3D unstructured meshes","authors":"Hongyu Liu ,&nbsp;Xing Ji ,&nbsp;Yunpeng Mao ,&nbsp;Yuan Ding ,&nbsp;Kun Xu","doi":"10.1016/j.cpc.2025.109820","DOIUrl":"10.1016/j.cpc.2025.109820","url":null,"abstract":"<div><div>In this paper, we present an advanced high-order compact gas-kinetic scheme (CGKS) for 3D unstructured mixed-element meshes, augmented with a <em>hp</em> multigrid technique to accelerate steady-state convergence. The scheme evolves cell-averaged flow variables and their gradients on the original mesh. Mesh coarsening employs a two-step parallel agglomeration algorithm, utilizing a random hash for cell interface selection and a geometric skewness metric for deletion confirmation, thereby ensuring both efficiency and robustness. For the coarser meshes, first-order kinetic flux vector splitting (KFVS) schemes with explicit or implicit time-stepping are used. The proposed multigrid CGKS is tested across various flow regimes on hybrid unstructured meshes, demonstrating significant improvements. A three-level V-cycle multigrid strategy, coupled with an explicit forward Euler method on coarser levels, results in a convergence rate up to ten times faster than standard CGKS. In contrast, the implicit lower-upper symmetric Gauss-Seidel (LU-SGS) method offers limited convergence acceleration. Scalability tests have demonstrated that GMG-CGKS exhibits consistent performance across varying numbers of CPU cores, highlighting its outstanding scalability. Our findings indicate that the explicit multigrid CGKS is highly scalable and effective for large-scale computations, marking a substantial step forward in computational fluid dynamics.</div></div><div><h3>Program summary</h3><div><em>Program title:</em> GMG-CGKS-v0.1</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/t97mh5c78g.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/kevinhongyu/GMG-CGKS-v0.1.git</span><svg><path></path></svg></span></div><div><em>Programming language:</em> C++</div><div><em>Licensing provisions:</em> GPLv2</div><div><em>External Libraries:</em> METIS, MPI, HDF5</div><div><em>Nature of problem:</em> The program is designed to solve the compressible Euler and Navier-Stokes equations, which are widely used in aerodynamics. The program provides steady-state acceleration techniques for third-order CGKS.</div><div><em>Solution method:</em> A three-level geometric multigrid scheme is adopted to improve the convergence rate of CGKS.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109820"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nyström type exponential integrators for strongly magnetized charged particle dynamics","authors":"Tri P. Nguyen ,&nbsp;Ilon Joseph ,&nbsp;Mayya Tokman","doi":"10.1016/j.cpc.2025.109848","DOIUrl":"10.1016/j.cpc.2025.109848","url":null,"abstract":"<div><div>Solving for charged particle motion in electromagnetic fields (i.e. the particle pushing problem) is a computationally intensive component of particle-in-cell (PIC) methods for plasma physics simulations. This task is especially challenging when the plasma is strongly magnetized due numerical stiffness arising from the wide range of time scales between highly oscillatory gyromotion and long term macroscopic behavior. A promising approach to solve these problems is by a class of methods known as exponential integrators that can solve linear problems exactly and are A-stable. This work extends the standard exponential integration framework to derive Nyström-type exponential integrators that integrates the Newtonian equations of motion as a second-order differential equation directly. In particular, we derive second-order and third-order Nyström-type exponential integrators for strongly magnetized particle pushing problems. Numerical experiments show that the Nyström-type exponential integrators exhibit significant improvement in computation speed over the standard exponential integrators.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109848"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic development of an equivalent particle method for efficient simulation of dense granular flows","authors":"Yilong Liu ,&nbsp;Xiping Yu","doi":"10.1016/j.cpc.2025.109862","DOIUrl":"10.1016/j.cpc.2025.109862","url":null,"abstract":"<div><div>Development of a highly efficient model is very important to expand the applicability of discrete element method (DEM) to large-scale granular flows that often include a tremendous number of granular particles. An equivalent particle method is rigorously developed for such a purpose in this study. The kinetic theory for granular flows is taken advantage to understand the relationship between the original particle system and the equivalent particle system, with a focus on conservation of mass and momentum. With the newly established equivalent particle method, the averaged particle velocity, density and volume concentration remain the same as in the original system. Scaling factors for other physical quantities, particularly those describing particle contact processes, are introduced to satisfy the geometric, kinematic and dynamic similarities. Verification of the equivalent particle model are performed by applying it to the computation of granular collapses on both horizontal and inclined bottoms. The computational results on deformation of granular profiles show that existing coarse grain or representative particle models, which were developed for the similar purpose as the present equivalent particle model, underestimate the granular material’s mobility. The numerical results from the present model agree much better with experimental data, indicating a major advancement in this kind of model development. The efficiency is drastically improved by tremendously reducing the number of computed particles, as compared to the standard DEM model.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109862"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Speeding up fermionic lattice calculations with photonic accelerated inverters","authors":"Felipe Attanasio ,&nbsp;Marc Bauer ,&nbsp;Jelle Dijkstra ,&nbsp;Timoteo Lee ,&nbsp;Jan M. Pawlowski ,&nbsp;Wolfram Pernice ,&nbsp;Frank Brückerhoff-Plückelmann","doi":"10.1016/j.cpc.2025.109825","DOIUrl":"10.1016/j.cpc.2025.109825","url":null,"abstract":"<div><div>Lattice field theory (LFT) is the standard non-perturbative method to perform numerical calculations of quantum field theory. However, the typical bottleneck of fermionic lattice calculations is the inversion of the Dirac matrix. This inversion is solved by iterative methods, like the conjugate gradient algorithm, where matrix-vector multiplications (MVMs) are the main operation. Photonic integrated circuits excel in performing quick and energy-efficient MVMs, but at the same time, they are known to have low accuracy. This can be overcome by using mixed precision methods. In this paper, we explore the idea of using photonic technology to fulfil the demand for computational power of fermionic lattice calculations. These methods have the potential to reduce computation costs by one order of magnitude. Because of the hybrid nature of these methods, we call these ‘photonic accelerated inverters (PAIs)’.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109825"},"PeriodicalIF":3.4,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ray-tracing laser-deposition model for plasma particle-in-cell simulation","authors":"A. Hyder ,&nbsp;W. Fox ,&nbsp;K.V. Lezhnin ,&nbsp;S.R. Totorica","doi":"10.1016/j.cpc.2025.109847","DOIUrl":"10.1016/j.cpc.2025.109847","url":null,"abstract":"<div><div>We develop a ray-tracing model for laser-plasma interaction suitable for coupling in-line into kinetic particle-in-cell plasma simulations. The model is based on inverse Bremsstrahlung absorption and includes oblique incidence effects and reflection at the critical surface. The energy deposition is given to electrons by randomized kicks to momentum. The model is verified against analytic solutions and a 2-D laser ray-tracing code.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109847"},"PeriodicalIF":3.4,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An advanced fully-implicit solver for heterogeneous porous media based on foam-extend","authors":"Roberto Lange,&nbsp;Gabriel M. Magalhães,&nbsp;Franciane F. Rocha,&nbsp;Hélio Ribeiro Neto","doi":"10.1016/j.cpc.2025.109842","DOIUrl":"10.1016/j.cpc.2025.109842","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Multiphase flow in porous media is present in many engineering applications, including hydrogeology, oil recovery, and CO&lt;sub&gt;2&lt;/sub&gt; sequestration. Accurate predictions of fluid behavior in these systems can improve process efficiency while mitigating environmental and health risks. Commercial simulators and open source software, such as the &lt;span&gt;porousMultiphaseFoam&lt;/span&gt; repository based on the OpenFOAM framework, have been developed to model this type of problem. However, simulating heterogeneous porous media with heterogeneous porosity and permeability distributions poses significant numerical challenges. We introduce &lt;span&gt;coupledMatrixFoam&lt;/span&gt;, an OpenFOAM-based solver designed for enhanced numerical stability and robustness. &lt;span&gt;coupledMatrixFoam&lt;/span&gt; integrates the Eulerian multi-fluid formulation for phase fractions with Darcy's law for porous media flow, applying a fully implicit, block-coupled solution for pressure and phase fractions. The solver is based on foam-extend 5.0, leveraging the latest &lt;span&gt;fvBlockMatrix&lt;/span&gt; developments to improve computational efficiency. This approach enables a significant increase in time step sizes, particularly in cases involving capillary pressure effects and other complex physical interactions. This work details the formulation, implementation and validation of &lt;span&gt;coupledMatrixFoam&lt;/span&gt;, including comparisons with &lt;span&gt;porousMultiphaseFoam&lt;/span&gt; that uses a segregated approach, to assess performance improvements. Additionally, a scalability analysis is conducted, demonstrating the solver's ability for high-performance computing (HPC) applications, which are essential for large-scale, real-world simulations.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Program summary&lt;/h3&gt;&lt;div&gt;&lt;em&gt;Program Title:&lt;/em&gt; coupledMatrixFoam&lt;/div&gt;&lt;div&gt;&lt;em&gt;CPC Library link to program files:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://doi.org/10.17632/3d3xdh4x89.1&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Developer's repository link:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://gitlab.com/wikki.brasil/porousmedia&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Licensing provisions:&lt;/em&gt; GPLv3&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; C++&lt;/div&gt;&lt;div&gt;&lt;em&gt;Supplementary material:&lt;/em&gt; Available in the repository &lt;span&gt;&lt;span&gt;porousMedia&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; This software solves multiphase flow in porous media.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; Fully implicit solver based on the Euler-Euler multifluid formulation combined with Darcy's law developed in the OpenFOAM framework, that is based on the Finite Volume Method (FVM). Implicit coupling of phase fraction and pressure equations allowing significantly larger time steps. Complex physical phenomena are accounted for, including capillary pressure effects, gravitational forces, compressibility, and heterogeneous media properties. The porous medium is modeled as a stationary phase, and nonlinear terms are linearized using Taylor series expansions. P","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109842"},"PeriodicalIF":3.4,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}