Computer Physics Communications最新文献

{"title":"AAVDP: Atomistic analyzer of virtual diffraction patterns from incident X-rays, neutrons, and electrons","authors":"Y. Zhang ,&nbsp;Z.R. Liu ,&nbsp;D. Legut ,&nbsp;R.F. Zhang","doi":"10.1016/j.cpc.2025.109845","DOIUrl":"10.1016/j.cpc.2025.109845","url":null,"abstract":"<div><div>Integrated computational materials engineering (ICME) has become a cornerstone for modern intelligent approaches, accelerating the discovery and design of new materials by providing extensive datasets. To support this, we have developed a straightforward and efficient command-line program named AAVDP (Atomistic Analyzer of Virtual Diffraction Patterns) for high-throughput (HT) virtual diffraction, structural analysis, and in situ visualization of various atomic configurations. AAVDP has integrated a comprehensive suite of virtual diffraction methods, spanning from X-ray diffraction (XRD), neutron diffraction (NED), kinematic electron diffraction (KED), and dynamical electron diffraction (DED), to both kinematic and dynamical Kikuchi diffractions (KKD and DKD), making it a versatile tool for researching crystalline and defective structures at atomic scale. Furthermore, AAVDP provides statistical tools, including the radial distribution function (RDF) and the static structure factor (SSF), which are crucial for understanding amorphous and liquid systems. As a command-line program, AAVDP allows for the customization of complex workflows and the extraction of high-volume statistical results with minimal scripting efforts. The program’s functionality and efficiency have been rigorously validated through a series of critical evaluations and tests, which empower users to delve deeper into the intricate diffraction behaviors and diverse material structures.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109845"},"PeriodicalIF":3.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046040","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":"VirtualFluids – open source parallel LBM solver","authors":"Martin Geier,&nbsp;Konstantin Kutscher,&nbsp;Martin Schönherr,&nbsp;Anna Wellmann,&nbsp;Sören Peters,&nbsp;Hussein Alihussein,&nbsp;Jan Linxweiler,&nbsp;Manfred Krafczyk","doi":"10.1016/j.cpc.2025.109810","DOIUrl":"10.1016/j.cpc.2025.109810","url":null,"abstract":"<div><div>This paper accompanies the publication of the open source lattice Boltzmann solver <span>VirtualFluids</span> [<span><span>DOI: 10.5281/zenodo.10283048</span><svg><path></path></svg></span>]. Key features of <span>VirtualFluids</span> are the cumulant collision operator, the ability to run multi-scale simulations based on compact interpolation grid refinement and its implementations for both GPU and massively parallel CPU systems. The differences in data structure for the different systems are explained in detail.</div></div><div><h3>PROGRAM SUMMARY</h3><div><em>Program Title:</em> <span>VirtualFluids</span></div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/tfzdnz7vwx.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://git.rz.tu-bs.de/irmb/VirtualFluids.git</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3</div><div><em>Programming language:</em> C++, C, Cuda, Python, CMake</div><div><em>Nature of problem:</em> High resolution transient computational fluid dynamics with applications in urban and environmental flows, wind engineering, porous materials, aero-acoustics etc. is implemented in a sustainable software environment.</div><div><em>Solution method:</em> Fluid flow is simulated with the super-convergent cumulant lattice Boltzmann method with compact interpolation grid refinement. The software is designed for massively parallel computation on various computer architectures, ranging from desktop computers to high performance clusters. GPU computation is enabled by a CUDA simulation kernel. A sustainable code basis is obtained through continuous integration and a wide range of tests i.e. unit tests, regression test, etc.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109810"},"PeriodicalIF":3.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010266","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":"PySTH: A Python program for calculating and analyzing theoretical solar-to-hydrogen efficiency","authors":"Quan Li ,&nbsp;Maoxiang Tao ,&nbsp;Yuxian Liu ,&nbsp;Hao Huang ,&nbsp;Qian Li ,&nbsp;Xiaojun Zhu","doi":"10.1016/j.cpc.2025.109822","DOIUrl":"10.1016/j.cpc.2025.109822","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Solar-to-hydrogen (STH) efficiency is a key metric for evaluating the economic feasibility of hydrogen production via solar-driven water splitting. However, accurately calculating theoretical STH efficiency remains challenging due to the complexity of the underlying integrals and the presence of multiple interdependent material parameters, which hampers computational efficiency and reproducibility. In this work, we introduce PySTH, a Python-based command-line program designed to enable rapid and reliable computation and intuitive visualization of theoretical STH efficiencies for two-dimensional photocatalysts under various sets of material property parameters. All required parameters are derived from first-principles calculations. The program supports four distinct photocatalytic systems: conventional photocatalysts, Janus materials, Z-scheme heterojunctions, and Janus Z-scheme systems. PySTH also generates high-resolution efficiency maps that reveal how the interplay among different material parameters affects STH efficiency, thereby offering valuable insights into synergistic optimization strategies. A series of benchmark examples demonstrate the accuracy, versatility, and practical utility of the program in theoretical photocatalysis research.&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; PySTH&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/jxc5j8vtvb.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/Quanli2022/PySTH&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 license&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; Python3&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Theoretical solar-to-hydrogen (STH) efficiency is a widely adopted descriptor for assessing the performance of 2D photocatalysts in solar-driven water-splitting applications targeted at hydrogen production. However, accurate evaluation of theoretical STH efficiency remains challenging due to complex integral formulations, multiple input parameters, and the absence of standardized computational tools. Moreover, the combined influence of these parameters on STH efficiency is not yet fully understood.&lt;em&gt;Solution method:&lt;/em&gt; PySTH enables users to compute theoretical STH efficiencies by selecting the photocatalyst type and providing key electronic property parameters (e.g., band-edge potentials and vacuum level difference). The program performs spectral integration using AM1.5G data and outputs both pH-dependent efficiency curves and STH efficiency maps to visualize the effects of synergistic parameter variations.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Additional comments including restrictions and unusual features:&lt;/em&gt; All efficiency calculations in PySTH are based on the AM1.5G solar spectrum. The software supports four classes of 2D materials: conventional photocatalysts, Janus materials, Z-scheme heterojunctions, and Janus Z-scheme sy","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109822"},"PeriodicalIF":3.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922889","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":"GBEES-GPU: An efficient parallel GPU algorithm for high-dimensional nonlinear uncertainty propagation","authors":"Benjamin L. Hanson ,&nbsp;Carlos Rubio ,&nbsp;Adrián García-Gutiérrez ,&nbsp;Thomas Bewley","doi":"10.1016/j.cpc.2025.109819","DOIUrl":"10.1016/j.cpc.2025.109819","url":null,"abstract":"<div><div>Eulerian nonlinear uncertainty propagation methods often suffer from finite domain limitations and computational inefficiencies. A recent approach to this class of algorithm, Grid-based Bayesian Estimation Exploiting Sparsity, addresses the first challenge by dynamically allocating a discretized grid in regions of phase space where probability is non-negligible. However, the design of the original algorithm causes the second challenge to persist in high-dimensional systems. This paper presents an architectural optimization of the algorithm for CPU implementation, followed by its adaptation to the CUDA framework for single GPU execution. The algorithm is validated for accuracy and convergence, with performance evaluated across distinct GPUs. Tests include propagating a three-dimensional probability distribution subject to the Lorenz '63 model and a six-dimensional probability distribution subject to the Lorenz '96 model. The results imply that the improvements made result in a speedup of over 1000 times compared to the original implementation.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109819"},"PeriodicalIF":3.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144912844","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":"NextGenPB: An analytically-enabled super resolution tool for solving the Poisson-Boltzmann equation featuring local (de)refinement","authors":"Vincenzo Di Florio ,&nbsp;Patrizio Ansalone ,&nbsp;Sergii V. Siryk ,&nbsp;Sergio Decherchi ,&nbsp;Carlo de Falco ,&nbsp;Walter Rocchia","doi":"10.1016/j.cpc.2025.109816","DOIUrl":"10.1016/j.cpc.2025.109816","url":null,"abstract":"<div><div>The Poisson-Boltzmann equation (PBE) is a relevant partial differential equation commonly used in biophysical applications to estimate the electrostatic energy of biomolecular systems immersed in electrolytic solutions. A conventional mean to improve the accuracy of its solution, when grid-based numerical techniques are used, consists in increasing the resolution, locally or globally. This, however, usually entails higher complexity, memory demand and computational cost. Here, we introduce NextGenPB, a linear PBE, adaptive-grid, FEM-based solution tool that leverages analytical calculations to maximize the accuracy-to-computational-cost ratio. Indeed, in NextGenPB (aka NGPB), analytical corrections at the surface of the solute enhance the solution's accuracy without requiring grid adaptation. This leads to more precise estimates of the electrostatic potential, fields, and energy at no perceptible additional cost. Also, we apply computationally efficient yet accurate boundary conditions by taking advantage of local grid de-refinement. To assess the accuracy of our methods directly, we expand the traditionally available analytical case set to many non-overlapping dielectric spheres. Then, we use an existing benchmark set of real biomolecular systems to evaluate the energy convergence concerning grid resolution. Thanks to these advances, we have improved state-of-the-art results and shown that the approach is accurate and largely scalable for modern high-performance computing architectures. Lastly, we suggest that the presented core ideas could be instrumental in improving the solution of other partial differential equations with discontinuous coefficients.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109816"},"PeriodicalIF":3.4,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989275","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":"Implicit stochastic uncertainty propagation scheme for two-step Monte Carlo simulations applied to R2S-UNED","authors":"I. Lopez,&nbsp;J. Alguacil,&nbsp;J.P. Catalan,&nbsp;P. Sauvan,&nbsp;J. Sanz","doi":"10.1016/j.cpc.2025.109828","DOIUrl":"10.1016/j.cpc.2025.109828","url":null,"abstract":"<div><div>In recent years, two-step Monte Carlo simulations have become increasingly important in nuclear analysis. However, the quantification of stochastic uncertainties in two-step Monte Carlo simulations, in order to evaluate the statistical convergence of final nuclear responses, remains challenging. At present, stochastic uncertainty propagation methods, mainly developed for rigorous-two-step methodologies, exhibit several limitations. In particular, existing methods rely upon the calculation of the covariance matrix of the radiation field estimated in the first Monte Carlo simulation, which is computationally demanding in terms of memory and time. It is important to note that the size of the covariance matrix depends on the discretisation employed to estimate the radiation field and, therefore, computational resources required for calculating the covariance matrix increase with discretization. Indeed, the calculation of the covariance matrix is unfeasible in nuclear analyses for real-world fusion facilities, such as shutdown dose rate calculations using rigorous-two-step methodologies in JET, where large-scale geometries combined with fine discretizations render the size of the covariance matrix impractical.</div><div>The present paper introduces an innovative methodology, the implicit stochastic uncertainty propagation scheme, to quantify the stochastic uncertainty in the final nuclear response due to the first Monte Carlo simulation, whilst avoiding the calculation of the covariance matrix. The implicit scheme involves the definition of a random variable according to specific criteria. As such, the evaluation of the random variable, as a Monte Carlo tally, allows for quantifying the stochastic uncertainty in the final nuclear response due to the first Monte Carlo simulation. The stochastic uncertainty due to the second Monte Carlo simulation is directly quantified by Monte Carlo codes along with the final nuclear response.</div><div>Finally, the implicit scheme is implemented in R2S-UNED –a two-step Monte Carlo simulation code designed to calculate the shutdown dose rate resulting from material activation– and, subsequently, employed to analyse the ITER shutdown dose rate benchmark exercise –a well-established test case in which the discretisation of the radiation field renders calculation of the covariance matrix infeasible. The comparison of the ITER benchmark against the brute force method demonstrates the correct performance of the implicit scheme, as well as verifies the applicability in nuclear analyses where existing methods are unfeasible because of the calculation of the covariance matrix.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109828"},"PeriodicalIF":3.4,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917938","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":"GRANAD - Simulating GRAphene nanoflakes with ADatoms","authors":"David Dams ,&nbsp;Miriam Kosik ,&nbsp;Marvin Müller ,&nbsp;Abhishek Ghosh ,&nbsp;Antton Babaze ,&nbsp;Julia Szczuczko ,&nbsp;Garnett W. Bryant ,&nbsp;Andrés Ayuela ,&nbsp;Carsten Rockstuhl ,&nbsp;Marta Pelc ,&nbsp;Karolina Słowik","doi":"10.1016/j.cpc.2025.109818","DOIUrl":"10.1016/j.cpc.2025.109818","url":null,"abstract":"&lt;div&gt;&lt;div&gt;GRANAD is a program based on the tight-binding approximation to simulate optoelectronic properties of graphene nanoflakes and Su–Schrieffer–Heeger (SSH) chains with possible adatom defects under electromagnetic illumination. Its core feature is the numerical solution of a time-domain master equation for the spin-traced one-particle reduced density matrix. It provides time-resolved evolution of charge distributions, access to induced-field dynamics, and characterization of the plasmonic response. Other computable quantities include energy profiles, electron distribution in real space, and absorption spectra. GRANAD is written in Python and relies on the JAX library for high-performance array computing, just-in-time (JIT) compilation, and differentiability. It is intended to be lightweight, portable, and easy to set up, offering a transparent and efficient way to access the properties of low-dimensional carbon structures from the nanoscale to the mesoscopic regime. GRANAD is open source, with the full code and extensive documentation with usage examples available at &lt;span&gt;&lt;span&gt;https://github.com/GRANADlauncher/granad.git&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;div&gt;&lt;h3&gt;Program summary&lt;/h3&gt;&lt;div&gt;&lt;em&gt;Program Title:&lt;/em&gt; GRANAD&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/10.17632/723d4m4z9x.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/GRANADlauncher/granad&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; Code, documentation and demo files.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Accessing the dynamical optical properties of graphene nanoflakes and one-dimensional polymer chains up to the mesoscale in the presence of adatoms represents a conceptual and computational challenge. Easily accessible classical methods fail as they do not accommodate relevant quantum effects. At the same time, quantum-mechanical &lt;em&gt;ab initio&lt;/em&gt; time-domain approaches are computationally costly, and their implementations are often difficult for the user to set up and extend due to the high complexity of the codebase.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; A theoretical framework that combines an electronic mean-field approach with a Lindblad-like master equation is implemented to describe these carbon-based systems, where interaction with an external electric field is described semiclassically in the tight-binding approximation. Many-body effects are modeled via a nonlinear interaction term in the Hamiltonian, while dissipative processes are included in the master equation. Simulations are performed in the time domain, providing detailed access to physically relevant quantities. The implementation is lightweight, easily portable, and can be extended to incorporate other materials and nanoflake stacks.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Additional ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109818"},"PeriodicalIF":3.4,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904112","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":"Pointing Probability Driven Semi-Analytic Monte Carlo Method (PDMC) – Part II: Correction of Exponential Approximation for Higher Accuracy","authors":"Pan Qingquan ,&nbsp;He Liaoyuan ,&nbsp;Liu Xiaojing","doi":"10.1016/j.cpc.2025.109824","DOIUrl":"10.1016/j.cpc.2025.109824","url":null,"abstract":"<div><div>We perform exponential approximation correction for the traditional Pointing Probability Driven Semi-Analytic Monte Carlo Method (PDMC) to achieve higher accuracy, re-establish the formula for calculating the global response of pseudo-track, forming a corrected Pointing Probability Driven Semi-Analytic Monte Carlo Method (cPDMC). cPDMC draws on the point kernel integral method, has the same calculation process as the traditional PDMC, and inherits all the advantages of PDMC, having high geometric universality due to the independence of deterministic procedures and high efficiency due to the independence of iterative computation. cPDMC is tested in the China Fusion Engineering Test Reactor (CFETR) and the HBR2 benchmark. Compared with the traditional PDMC, cPDMC improves the Average Figure of Merit (AV.FOM) by 1.2 ∼ 410.5 times with the CFETR model and 113.10 ∼ 13,818.18 times with the HBR2 benchmark, proving the superiority of this exponential approximation correction method and showing that cPDMC can further improve the accuracy and efficiency of PDMC and is helpful for large-scale radiation analysis.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109824"},"PeriodicalIF":3.4,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907712","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":"Spectrally accelerated edge and scrape-off layer gyrokinetic turbulence simulations","authors":"B.J. Frei ,&nbsp;P. Ulbl ,&nbsp;J. Trilaksono ,&nbsp;F. Jenko","doi":"10.1016/j.cpc.2025.109817","DOIUrl":"10.1016/j.cpc.2025.109817","url":null,"abstract":"<div><div>This paper presents the first gyrokinetic (GK) simulations of edge and scrape-off layer (SOL) turbulence accelerated by a velocity-space spectral approach in the full-<em>f</em> GK code <span>GENE-X</span>. Building upon the original grid velocity-space discretization, we derive and implement a new spectral formulation and verify the numerical implementation using the method of manufactured solution. We conduct a series of spectral turbulence simulations focusing on the TCV-X21 reference case (Oliveira et al., 2022 <span><span>[26]</span></span>) and compare these results with previously validated grid simulations (Ulbl et al., 2023 <span><span>[25]</span></span>). The spectral approach reproduces the outboard midplane (OMP) profiles (density, temperature, and radial electric field), dominated by trapped electron mode (TEM) turbulence, with excellent agreement and significantly lower velocity-space resolution. As a consequence, the spectral approach reduces the computational cost (CPUh) by at least an order of magnitude, of approximately 50 for the TCV-X21 case. This enables high-fidelity GK simulations to be performed within a few days on modern CPU-based supercomputers for medium-sized devices and establishes <span>GENE-X</span> as a powerful tool for studying edge and SOL turbulence, moving towards reactor-relevant devices like ITER.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109817"},"PeriodicalIF":3.4,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144885831","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":"Three-dimensional simulation of cohesive granular flows using lattice Boltzmann method with a μ(I)-rheology-based viscoplastic model","authors":"Yi-Yang Shen ,&nbsp;Liu-chao Qiu ,&nbsp;Tang-Jing Yuan ,&nbsp;Yi Liu","doi":"10.1016/j.cpc.2025.109821","DOIUrl":"10.1016/j.cpc.2025.109821","url":null,"abstract":"<div><div>This paper introduces a novel three-dimensional numerical framework by combining the free-surface lattice Boltzmann method (LBM) with a μ(I)-rheology-based viscoplastic model for simulating cohesive granular flows. The proposed method aims to provide an accurate and efficient modelling of granular flow with a free-surface. In the present method, the evolution of the granular-air interface is modeled through a single-phase free-surface approach. A novel μ(I)-rheology-based viscoplastic model is used to describe the mechanical response of the granular material. We investigated the performance of the lattice Boltzmann method in conjunction with the μ(I)-rheology within a continuum framework, particularly examining how cohesion influences flow dynamics and the rheological properties of granular materials. A benchmark simulation of cohesive granular collapse is first presented, showing that the LBM results are in strong agreement with experimental data. The effect of aspect ratio on the final deposit shape and instability modes during column collapse is also verified. Finally, the sensitivity of the model’s parameters is assessed for the combined LBM and μ(I)-rheology approach. The findings demonstrate that the proposed LBM framework can accurately capture the flow characteristics of cohesive granular flows.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109821"},"PeriodicalIF":3.4,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893476","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}