Pub Date : 2024-06-11DOI: 10.1016/j.cpc.2024.109276
Alexandra-Gabriela Şerban , Andrea Coronetti , Rubén García Alía , Francesc Salvat Pujol , FLUKA.CERN Collaboration
FLUKA is among the general-purpose codes for the Monte Carlo simulation of radiation transport that are routinely employed to estimate the production of single-event-upsets (SEUs) in commercial static random access memories (SRAMs) exposed to radiation. Earlier studies concerning the production of SEUs in commercial SRAMs under proton irradiation revealed very good agreement between experimental measurements and FLUKA estimates of the SEU production cross section for proton energies above 20-30 MeV. However, at lower proton energies, where the cross section for SEU production in such low-critical-charge components increases drastically, a FLUKA underestimation of up to two orders of magnitude was observed. Preliminary analyses indicated that this underestimation was in great measure due to the lack of nuclear elastic scattering of protons below 10 MeV in FLUKA up to version 4-3.4. To overcome this limitation, a new model for the nuclear elastic scattering of protons has been developed, combining partial-wave analyses and experimental angular distributions. This newly developed model has been included in FLUKA v4-4.0, and leads to an order-of-magnitude improvement in the agreement between FLUKA and experimental cross sections for the production of SEUs in SRAMs under proton irradiation in the 1–10 MeV energy domain.
{"title":"Nuclear elastic scattering of protons below 250 MeV in FLUKA v4-4.0 and its role in single-event-upset production in electronics","authors":"Alexandra-Gabriela Şerban , Andrea Coronetti , Rubén García Alía , Francesc Salvat Pujol , FLUKA.CERN Collaboration","doi":"10.1016/j.cpc.2024.109276","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109276","url":null,"abstract":"<div><p>FLUKA is among the general-purpose codes for the Monte Carlo simulation of radiation transport that are routinely employed to estimate the production of single-event-upsets (SEUs) in commercial static random access memories (SRAMs) exposed to radiation. Earlier studies concerning the production of SEUs in commercial SRAMs under proton irradiation revealed very good agreement between experimental measurements and FLUKA estimates of the SEU production cross section for proton energies above 20-30 MeV. However, at lower proton energies, where the cross section for SEU production in such low-critical-charge components increases drastically, a FLUKA underestimation of up to two orders of magnitude was observed. Preliminary analyses indicated that this underestimation was in great measure due to the lack of nuclear elastic scattering of protons below 10 MeV in FLUKA up to version 4-3.4. To overcome this limitation, a new model for the nuclear elastic scattering of protons has been developed, combining partial-wave analyses and experimental angular distributions. This newly developed model has been included in FLUKA v4-4.0, and leads to an order-of-magnitude improvement in the agreement between FLUKA and experimental cross sections for the production of SEUs in SRAMs under proton irradiation in the 1–10 MeV energy domain.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524001991/pdfft?md5=8dd5bff6dacad33598ad24bc79c8737e&pid=1-s2.0-S0010465524001991-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141429348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-08DOI: 10.1016/j.cpc.2024.109265
Nan Li , Haoliang Liu , Sateng Li , Junming Guo , Qianwu Li , Fangjie Shi , Yefei Li , Bing Xiao
ScaleLat (Scale Lattice) is a computer program written in C for performing the atomic structure analysis of multi-phase system or high entropy alloys (HEAs). The program implements an atomic cluster cell extraction algorithm to obtain all symmetry independent characteristic atomic cluster cells for the complex atomic configurations which are usually obtained from molecular dynamics or kinetic Monte-Carlo simulations at nanoscale or mesoscopic scale. ScaleLat implements an efficient and unique chemical structure matching algorithm to match all extracted atomic clusters from a large supercell (>104 atoms) to a representative small one (∼ 103 or less), providing the possibility to directly use the highly accurate quantum mechanical methods to study the electronic, magnetic, and mechanical properties of multi-component alloys for complex microstructures. We demonstrate the capability of ScaleLat code by conducting both the atomic structure matching analysis for Fe-12.8 at.% Cr binary alloy and equiatomic CrFeCoNiCu high entropy alloy, successfully obtaining the representative supercells containing 102∼103 atoms for two systems. The reliability of the proposed chemical structure matching scheme is tested and confirmed by calculating the electronic structures of both examples using trial supercells with various sizes. Overall, ScaleLat program provides a universal platform to efficiently map all essential chemical structures of large complex atomic structures to a relatively easy-handling small supercell for quantum mechanical calculations of various user interested properties.
{"title":"ScaleLat: A chemical structure matching algorithm for mapping atomic structure of multi-phase system and high entropy alloys","authors":"Nan Li , Haoliang Liu , Sateng Li , Junming Guo , Qianwu Li , Fangjie Shi , Yefei Li , Bing Xiao","doi":"10.1016/j.cpc.2024.109265","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109265","url":null,"abstract":"<div><p>ScaleLat (Scale Lattice) is a computer program written in C for performing the atomic structure analysis of multi-phase system or high entropy alloys (HEAs). The program implements an atomic cluster cell extraction algorithm to obtain all symmetry independent characteristic atomic cluster cells for the complex atomic configurations which are usually obtained from molecular dynamics or kinetic Monte-Carlo simulations at nanoscale or mesoscopic scale. ScaleLat implements an efficient and unique chemical structure matching algorithm to match all extracted atomic clusters from a large supercell (>10<sup>4</sup> atoms) to a representative small one (∼ 10<sup>3</sup> or less), providing the possibility to directly use the highly accurate quantum mechanical methods to study the electronic, magnetic, and mechanical properties of multi-component alloys for complex microstructures. We demonstrate the capability of ScaleLat code by conducting both the atomic structure matching analysis for Fe-12.8 at.% Cr binary alloy and equiatomic CrFeCoNiCu high entropy alloy, successfully obtaining the representative supercells containing 10<sup>2</sup>∼10<sup>3</sup> atoms for two systems. The reliability of the proposed chemical structure matching scheme is tested and confirmed by calculating the electronic structures of both examples using trial supercells with various sizes. Overall, ScaleLat program provides a universal platform to efficiently map all essential chemical structures of large complex atomic structures to a relatively easy-handling small supercell for quantum mechanical calculations of various user interested properties.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434726","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}
Pub Date : 2024-06-06DOI: 10.1016/j.cpc.2024.109267
Peter Ogrin , Cristiano L. Dias , Tomaz Urbic
The Mercedes-Benz (MB) water model is a simple two-dimensional toy model of water that can reproduce many of the anomalous properties of water. Within the model, the water particles are represented as Lennard-Jones disks with explicitly added orientation-dependent interactions that mimic the formation of hydrogen bonds. Due to the simple implementation of the MB model in Monte Carlo simulations, it was mainly studied with Monte Carlo simulations in different ensembles. The implementation of the model in molecular dynamics simulations is not trivial. In this paper we present the code for molecular dynamics simulations. The structural and thermodynamic properties of the model were calculated using molecular dynamics and compared with data from Monte Carlo simulations to confirm that the molecular dynamics code works correctly. We also used molecular dynamics to calculate the dynamic properties of the model. The Fortran source code of our molecular dynamics simulation of the MB water model is provided.
{"title":"Code for molecular dynamics simulation of two dimensional Mercedes-Benz water model","authors":"Peter Ogrin , Cristiano L. Dias , Tomaz Urbic","doi":"10.1016/j.cpc.2024.109267","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109267","url":null,"abstract":"<div><p>The Mercedes-Benz (MB) water model is a simple two-dimensional toy model of water that can reproduce many of the anomalous properties of water. Within the model, the water particles are represented as Lennard-Jones disks with explicitly added orientation-dependent interactions that mimic the formation of hydrogen bonds. Due to the simple implementation of the MB model in Monte Carlo simulations, it was mainly studied with Monte Carlo simulations in different ensembles. The implementation of the model in molecular dynamics simulations is not trivial. In this paper we present the code for molecular dynamics simulations. The structural and thermodynamic properties of the model were calculated using molecular dynamics and compared with data from Monte Carlo simulations to confirm that the molecular dynamics code works correctly. We also used molecular dynamics to calculate the dynamic properties of the model. The Fortran source code of our molecular dynamics simulation of the MB water model is provided.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524001905/pdfft?md5=c7faabbec1a5c5bf10101d941faa7630&pid=1-s2.0-S0010465524001905-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141313564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1016/j.cpc.2024.109264
Bernhard Ramsauer, Johannes J. Cartus, Oliver T. Hofmann
In this publication we introduce MAM-STM, a software to autonomously manipulate arbitrary moieties towards specific positions on a metal surface utilizing the tip of a scanning tunneling microscope (STM). Finding the optimal manipulation parameters for a specific moiety is challenging and time consuming, even for human experts. MAM-STM combines autonomous data acquisition with a sophisticated Q-learning implementation to determine the optimal bias voltage, the z-approach distance, and the tip position relative to the moiety. This then allows to arrange single molecules and atoms at will. In this work, we provide a tutorial based on a simulated response to offer a comprehensive explanation on how to use and customize MAM-STM. Additionally, we assess the performance of the machine learning algorithm by benchmarking it within a simulated stochastic environment.
PROGRAM SUMMARY
Program title: MAM-STM
CPC Library link to program files: (to be added by Technical Editor)
Code Ocean capsule: (to be added by Technical Editor)
Licensing provisions: GNU General Public License 3 (GPL)
Programming language: Python 3
Nature of problem: Achieving precise control over the arrangement of individual molecules on surfaces is essential for advancing nanofabrication and understanding molecular interaction processes. While self-assembly offers a method for forming nanostructures, achieving arbitrary arrangements of moieties remains difficult. Current approaches, such as scanning probe microscopy (SPM), require extensive manual intervention and precise control is difficult to achieve consistently due to the stochastic nature of quantum mechanical systems at the nanoscale. Thus, learning to manipulate several moieties in order to build even relatively small structures is challenging and time consuming and the automation through conventional expert systems is hindered by the lack of prior knowledge about the surface-moiety interaction processes.
Solution method: This scenario is ideal for machine learning algorithms, like reinforcement learning (RL), which do not require an underlying model but are able to autonomously learn the optimal manipulation parameters by performing manipulations directly at the machine. Introducing MAM-STM, which stands for Molecular and Atomic Manipulation via Scanning Tunneling Microscopy. MAM-STM allows to control molecules and atoms by learning the manipulation parameters for either vertical or lateral manipulations. However, the vast number of manipulation parameter combinations and the inefficient learning procedure of RL agents exhibit several challenges. MAM-STM overcomes these challenges with an autonomous masking routine that eliminates manipulation parameters that induce structural changes to the moiety or lift it off the surface. Additionally, a sophisticated Q-learning approach
{"title":"MAM-STM: A software for autonomous control of single moieties towards specific surface positions","authors":"Bernhard Ramsauer, Johannes J. Cartus, Oliver T. Hofmann","doi":"10.1016/j.cpc.2024.109264","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109264","url":null,"abstract":"<div><p>In this publication we introduce MAM-STM, a software to autonomously manipulate arbitrary moieties towards specific positions on a metal surface utilizing the tip of a scanning tunneling microscope (STM). Finding the optimal manipulation parameters for a specific moiety is challenging and time consuming, even for human experts. MAM-STM combines autonomous data acquisition with a sophisticated Q-learning implementation to determine the optimal bias voltage, the z-approach distance, and the tip position relative to the moiety. This then allows to arrange single molecules and atoms at will. In this work, we provide a tutorial based on a simulated response to offer a comprehensive explanation on how to use and customize MAM-STM. Additionally, we assess the performance of the machine learning algorithm by benchmarking it within a simulated stochastic environment.</p></div><div><h3>PROGRAM SUMMARY</h3><p>Program title: MAM-STM</p><p>CPC Library link to program files: (to be added by Technical Editor)</p><p>Developer's repository link: https://gitlab.tugraz.at/software_public/mam_stm.git</p><p>Code Ocean capsule: (to be added by Technical Editor)</p><p>Licensing provisions: GNU General Public License 3 (GPL)</p><p>Programming language: Python 3</p><p>Nature of problem: Achieving precise control over the arrangement of individual molecules on surfaces is essential for advancing nanofabrication and understanding molecular interaction processes. While self-assembly offers a method for forming nanostructures, achieving arbitrary arrangements of moieties remains difficult. Current approaches, such as scanning probe microscopy (SPM), require extensive manual intervention and precise control is difficult to achieve consistently due to the stochastic nature of quantum mechanical systems at the nanoscale. Thus, learning to manipulate several moieties in order to build even relatively small structures is challenging and time consuming and the automation through conventional expert systems is hindered by the lack of prior knowledge about the surface-moiety interaction processes.</p><p>Solution method: This scenario is ideal for machine learning algorithms, like reinforcement learning (RL), which do not require an underlying model but are able to autonomously learn the optimal manipulation parameters by performing manipulations directly at the machine. Introducing MAM-STM, which stands for Molecular and Atomic Manipulation via Scanning Tunneling Microscopy. MAM-STM allows to control molecules and atoms by learning the manipulation parameters for either vertical or lateral manipulations. However, the vast number of manipulation parameter combinations and the inefficient learning procedure of RL agents exhibit several challenges. MAM-STM overcomes these challenges with an autonomous masking routine that eliminates manipulation parameters that induce structural changes to the moiety or lift it off the surface. Additionally, a sophisticated Q-learning approach ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524001875/pdfft?md5=74c3002522a3586528e738564a9ff30d&pid=1-s2.0-S0010465524001875-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141429351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1016/j.cpc.2024.109268
G. Le Bars , J. Loizu , S. Guinchard , J.-Ph. Hogge , A. Cerfon , S. Alberti , F. Romano , J. Genoud , P. Kamiński
This paper presents the new 2D electrostatic particle-in-cell code FENNECS developed to study the formation of magnetized non-neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun design, but solves general equations and can be applied in other domains of plasma physics. FENNECS is capable of simulating electron-neutral collisions using a Monte Carlo approach and considers both elastic and inelastic (ionization) processes. It is also capable of solving the Poisson equation on domains with arbitrary geometries with either Dirichlet or natural boundary conditions. The Poisson solver is based on a meshless Finite Element Method, called web-splines, based on b-splines of any order, and used for the first time in the domain of plasma physics. In addition, the effect of fast ions colliding with the electrodes and causing ion induced electron emission at the electrode surfaces has been implemented in the code. In this paper, the governing equations solved by FENNECS and the numerical methods used to solve them are presented. A number of verification cases are then reported. Finally, the parallelization scheme used in FENNECS and its parallel scalability are presented.
本文介绍了为研究具有方位对称性的几何结构中磁化非中性等离子体的形成而开发的新型二维静电粒子池内代码 FENNECS。该代码是在陀螺仪电子枪设计领域开发的，但可求解一般方程，并可应用于等离子体物理的其他领域。FENNECS 能够使用蒙特卡罗方法模拟电子-中性碰撞，并考虑弹性和非弹性（电离）过程。它还能在具有任意几何形状的域上求解泊松方程，并采用迪里希勒或自然边界条件。泊松求解器基于一种无网格有限元方法，称为网状样条，基于任意阶的 b 样条，首次用于等离子体物理领域。此外，代码中还实现了快速离子与电极碰撞并在电极表面引起离子诱导电子发射的效应。本文介绍了 FENNECS 所求解的支配方程以及用于求解这些方程的数值方法。然后报告了一些验证案例。最后，介绍了 FENNECS 中使用的并行化方案及其并行可扩展性。
{"title":"FENNECS: A novel particle-in-cell code for simulating the formation of magnetized non-neutral plasmas trapped by electrodes of complex geometries","authors":"G. Le Bars , J. Loizu , S. Guinchard , J.-Ph. Hogge , A. Cerfon , S. Alberti , F. Romano , J. Genoud , P. Kamiński","doi":"10.1016/j.cpc.2024.109268","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109268","url":null,"abstract":"<div><p>This paper presents the new 2D electrostatic particle-in-cell code FENNECS developed to study the formation of magnetized non-neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun design, but solves general equations and can be applied in other domains of plasma physics. FENNECS is capable of simulating electron-neutral collisions using a Monte Carlo approach and considers both elastic and inelastic (ionization) processes. It is also capable of solving the Poisson equation on domains with arbitrary geometries with either Dirichlet or natural boundary conditions. The Poisson solver is based on a meshless Finite Element Method, called web-splines, based on b-splines of any order, and used for the first time in the domain of plasma physics. In addition, the effect of fast ions colliding with the electrodes and causing ion induced electron emission at the electrode surfaces has been implemented in the code. In this paper, the governing equations solved by FENNECS and the numerical methods used to solve them are presented. A number of verification cases are then reported. Finally, the parallelization scheme used in FENNECS and its parallel scalability are presented.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524001917/pdfft?md5=d12b899e7ef4cc6503231cb81213f8f2&pid=1-s2.0-S0010465524001917-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141313565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01DOI: 10.1016/j.cpc.2024.109266
Baoqing Meng , Junsheng Zeng , Shuai Li , Baolin Tian , Jinhong Liu
Compressible particle-resolved direct numerical simulations (PR-DNS) are widely used in explosion-driven dispersion of particles simulations, multiphase turbulence modelling, and stage separation for two-stage-to-orbit vehicles. The direct forcing immersed boundary method (IBM) is a promising method and widely applied in low speed flow while there is few research regarding compressible flows. We developed a novel IBM to resolve supersonic and hypersonic gas flows interacting with irregularly shaped multi-body particle. The main innovation is that current method can solve the interaction of particles and high-speed fluids, particle translation and rotation, and collision among complex-shaped particles within a uniform framework. Specially, high conservation and computation consumption are strictly satisfied, which is critical for resolving the high speed compressible flow feature. To avoid the non-physical flow penetration around particle surface, an special iterative algorithm is specially derived to handle the coupling force between the gas and particles. The magnitude of the velocity difference error could be reduced by 6–8 orders compared to that of a previous method. Additionally, aerodynamic force integration was achieved using the momentum equation to ensure momentum conservation for two-phase coupling. A high-efficiency cell-type identification method for each step was proposed, and mapping among LPs and cells was used again to select the immersed cells. As for the collision force calculation, the complex shape of a particle was represented by a cloud of LPs and the mapping of LPs and cells was used to reduce the complexity of the algorithm for contact searching. The repetitive use of the mapping relationship could reduce the internal memory and improve the efficiency of the proposed algorithm. Moreover, various verification cases were conducted to evaluate the simulation performance of the proposed algorithm, including two- and three-dimensional moving and motionless particles with regular and complex shapes interacting with high-speed flow. Specifically, an experiment involving a shock passing through a sphere was designed and conducted to provide high-precision data. The corresponding results of the large-scale numerical simulation agree well with those obtained experimentally. The current method supports flow simulations at a particle-resolved scale in engineering.
{"title":"A particle-resolved direct numerical simulation method for the compressible gas flow and arbitrary shape solid moving with a uniform framework","authors":"Baoqing Meng , Junsheng Zeng , Shuai Li , Baolin Tian , Jinhong Liu","doi":"10.1016/j.cpc.2024.109266","DOIUrl":"10.1016/j.cpc.2024.109266","url":null,"abstract":"<div><p>Compressible particle-resolved direct numerical simulations (PR-DNS) are widely used in explosion-driven dispersion of particles simulations, multiphase turbulence modelling, and stage separation for two-stage-to-orbit vehicles. The direct forcing immersed boundary method (IBM) is a promising method and widely applied in low speed flow while there is few research regarding compressible flows. We developed a novel IBM to resolve supersonic and hypersonic gas flows interacting with irregularly shaped multi-body particle. The main innovation is that current method can solve the interaction of particles and high-speed fluids, particle translation and rotation, and collision among complex-shaped particles within a uniform framework. Specially, high conservation and computation consumption are strictly satisfied, which is critical for resolving the high speed compressible flow feature. To avoid the non-physical flow penetration around particle surface, an special iterative algorithm is specially derived to handle the coupling force between the gas and particles. The magnitude of the velocity difference error could be reduced by 6–8 orders compared to that of a previous method. Additionally, aerodynamic force integration was achieved using the momentum equation to ensure momentum conservation for two-phase coupling. A high-efficiency cell-type identification method for each step was proposed, and mapping among LPs and cells was used again to select the immersed cells. As for the collision force calculation, the complex shape of a particle was represented by a cloud of LPs and the mapping of LPs and cells was used to reduce the complexity of the algorithm for contact searching. The repetitive use of the mapping relationship could reduce the internal memory and improve the efficiency of the proposed algorithm. Moreover, various verification cases were conducted to evaluate the simulation performance of the proposed algorithm, including two- and three-dimensional moving and motionless particles with regular and complex shapes interacting with high-speed flow. Specifically, an experiment involving a shock passing through a sphere was designed and conducted to provide high-precision data. The corresponding results of the large-scale numerical simulation agree well with those obtained experimentally. The current method supports flow simulations at a particle-resolved scale in engineering.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141233316","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}
Pub Date : 2024-05-31DOI: 10.1016/j.cpc.2024.109245
W. Haeck, N. Gibson, P. Talou
ENDFtk is a recently developed C++ and Python interface to interact with ENDF-6 formatted nuclear data files. It provides a robust and complete interface, allowing the reading and writing of all formats currently part of the ENDF-6 formats manual, as well as some non-ENDF formats used by the NJOY processing code. It provides an interface that mimics the names in the ENDF-6 formats manual as well as an equivalent interface using human-readable attribute names. It is robust and powerful enogh for nuclear data experts to develop complex applications, while also simple enough to be used non-experts to retrieve and manipulate evaluated nuclear data. ENDFtk offers the ability to easily interrogate and manipulate data either in large-scale code projects or in simple Python scripts. In this paper, a brief overview of the interface is given, as well as more substantial examples demonstrating plotting simple data, interacting with more complex data, and writing new data to files. ENDFtk is open source and available for download via GitHub (https://github.com/njoy/ENDFtk).
Program summary
Program title:ENDFtk 1.0
CPC Library link to program files:https://doi.org/10.17632/9p4kxc2cvd.1
Nature of problem: Provide an interface to read, write and manipulate nuclear data files using the ENDF-6 format. This interface can be integrated into other libraries requiring access to nuclear data, or be used directly using the Python interface.
Solution method: Library of C++ routines, with their Python bindings, to be integrated in higher-level codes and scripts
{"title":"ENDFtk: A robust tool for reading and writing ENDF-formatted nuclear data","authors":"W. Haeck, N. Gibson, P. Talou","doi":"10.1016/j.cpc.2024.109245","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109245","url":null,"abstract":"<div><p><span>ENDFtk</span> is a recently developed C++ and Python interface to interact with ENDF-6 formatted nuclear data files. It provides a robust and complete interface, allowing the reading and writing of all formats currently part of the ENDF-6 formats manual, as well as some non-ENDF formats used by the NJOY processing code. It provides an interface that mimics the names in the ENDF-6 formats manual as well as an equivalent interface using human-readable attribute names. It is robust and powerful enogh for nuclear data experts to develop complex applications, while also simple enough to be used non-experts to retrieve and manipulate evaluated nuclear data. <span>ENDFtk</span> offers the ability to easily interrogate and manipulate data either in large-scale code projects or in simple Python scripts. In this paper, a brief overview of the interface is given, as well as more substantial examples demonstrating plotting simple data, interacting with more complex data, and writing new data to files. <span>ENDFtk</span> is open source and available for download via GitHub (<span>https://github.com/njoy/ENDFtk</span><svg><path></path></svg>).</p></div><div><h3>Program summary</h3><p><em>Program title:</em> <span>ENDFtk</span> 1.0</p><p><em>CPC Library link to program files:</em> <span>https://doi.org/10.17632/9p4kxc2cvd.1</span><svg><path></path></svg></p><p><em>Developer's repository link:</em> <span>https://github.com/njoy/ENDFtk</span><svg><path></path></svg></p><p><em>Licensing provisions:</em> BSD-3 clause</p><p><em>Programming language:</em> C++ and Python</p><p><em>External routines/libraries:</em> pybind11, ranges-v3, spdlog</p><p><em>Nature of problem:</em> Provide an interface to read, write and manipulate nuclear data files using the ENDF-6 format. This interface can be integrated into other libraries requiring access to nuclear data, or be used directly using the Python interface.</p><p><em>Solution method:</em> Library of C++ routines, with their Python bindings, to be integrated in higher-level codes and scripts</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141291808","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}
Pub Date : 2024-05-28DOI: 10.1016/j.cpc.2024.109263
Xiang-Ren Zhou, Li Zhang
Particle pushers widely used in Particle-in-Cell(PIC) simulations are commonly required to be unconditionally stable and meet the basic physical laws. In this work, basing on central difference, we propose an unconditionally stable and well posed particle pusher. By mathematical deduction, the high-dimensional non-linear problem for solving tensor-form relativistic Lorentz force law equation is transformed to a quartic scalar problem and a following linear problem. Some practical suggestions for programming and some numerical results are also given.
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Pub Date : 2024-05-24DOI: 10.1016/j.cpc.2024.109261
Alexander V. Smirnov , Mao Zeng
FIRE is a program which performs integration-by-parts (IBP) reductions of Feynman integrals. Originally, the C++ version of FIRE relies on the computer algebra system Fermat by Robert Lewis to simplify rational functions. We present an upgrade of FIRE which incorporates a new library FUEL initially described in a separate publication, which enables a flexible choice of third-party computer algebra systems as simplifiers, as well as efficient communications with some of the simplifiers as C++ libraries rather than through Unix pipes. We achieve significant speedups for IBP reductions of Feynman integrals involving many kinematic variables, when using an open source backend based on FLINT newly added in this work, or the Symbolica backend developed by Ben Ruijl as a potential successor of FORM.
Program summary
Program title: FIRE, version 6.5 (FIRE 6.5)
CPC Library link to program files:https://doi.org/10.17632/cy6k69pb3y.2
Does the new version supersede the previous version?: Yes.
Reasons for the new version: The new version no longer relies on a single computer algebra system, Fermat [1], but instead allows a flexible choice of several systems, some of which offer higher performance, especially when the number of variables is large.
Summary of revisions: A new library FUEL [2] is used as a core component of the new version of FIRE to access different computer algebra systems as simplifiers of rational function expressions. Since the first release of FUEL described elsewhere, FUEL version 1.0 here has been enhanced with a new backend based on the open source library FLINT [3] that provides highly performant simplification of rational functions.
Nature of problem: Feynman integrals of a given family are reduced to a finite set of master integrals, by solving linear equations arising from integration by parts, using Gaussian elimination. The coefficients of the linear equations are generally rational functions in kinematic variables and the spacetime dimension, and the simplification of such rational functions during Gaussian elimination is a key task that is improved in this upgrade of FIRE.
Solution method: Computer algebra systems with state-of-the-art capabilities for polynomial GCD computations are used as simplification backends, or simp
FIRE 是一个对费曼积分进行逐部积分（IBP）还原的程序。最初，FIRE 的 C++ 版本依赖于罗伯特-刘易斯（Robert Lewis）的计算机代数系统费马（Fermat）来简化有理函数。我们介绍了 FIRE 的升级版，它集成了一个新库 FUEL（最初在另一出版物中介绍），可以灵活选择第三方计算机代数系统作为简化器，并以 C++ 库的形式而不是通过 Unix 管道与某些简化器进行高效通信。在使用本研究中新添加的基于 FLINT 的开源后端，或 Ben Ruijl 开发的作为 FORM 潜在后继者的 Symbolica 后端时，我们在涉及许多运动学变量的费曼积分的 IBP 简化方面取得了显著的加速：FIRE, version 6.5 (FIRE 6.5)CPC Library program files link: https://doi.org/10.17632/cy6k69pb3y.2Developer's repository link: https://gitlab.com/feynmanintegrals/fire.gitLicensing provisions：GPLv2 编程语言Wolfram Mathematica 8.0 或更高版本，C++17补充材料：有关安装说明，请参见链接的资源库：Comput.Phys.247 (2020) 106877新版本是否取代旧版本？是：新版本不再依赖于单一的计算机代数系统费马[1]，而是允许灵活选择多个系统，其中一些系统性能更高，尤其是当变量数量较多时：新版 FIRE 的核心组件是一个新库 FUEL [2]，用于访问不同的计算机代数系统，作为有理函数表达式的简化器。问题的性质：通过使用高斯消元法求解分部积分所产生的线性方程组，将给定族的费曼积分简化为一组有限的主积分。线性方程的系数通常是运动变量和时空维度的有理函数，在高斯消元过程中简化这些有理函数是 FIRE 升级版改进的一项关键任务：解决方法：计算机代数系统具有最先进的多项式 GCD 计算能力，可用作简化后端，简称简化器。由于 FIRE 的设计，文本字符串被用作有理函数简化前后的交换格式。我们编写了一个快速 C++ 解析器，用于将字符串解析为外部化简器 FLINT [3] 的内部格式，该化简器在多变量多项式计算方面性能一流。同样，简化器 Symbolica [4] 在 GCD 计算和解析方面也有很高的性能，并已集成到 FIRE 中。参考文献[1]https://home.bway.net/lewis/，免费软件，有一些限制。[2]https://doi.org/10.26089/NumMet.v24r425，开源软件。[3]https://flintlib.org/，开源软件。[4]https://symbolica.io/，商业软件，有免费许可证，供学生和业余爱好者使用。
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