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Computer Physics Communications

ISSN: 0010-4655

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Datasets associated with articles published in Computer Physics Communications

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  • HTR-1.3 solver: Predicting electrified combustion using the hypersonic task-based research solver
    This manuscript presents an updated open-source version of the Hypersonics Task-based Research (HTR) solver. The solver, whose main features are presented in Di Renzo et al. (2020) [9] and Di Renzo & Pirozzoli (2021) [10], is designed for direct numerical simulation of reacting flows at high Reynolds numbers. This new version extends the applications of the HTR solver to turbulent combustion in the presence of external electric fields. In particular, a new distributed Poisson solver compatible with heterogeneous architectures has been incorporated in the algorithm to compute the electric potential distribution in bi-periodic configurations. The drift fluxes of the electrically charged species are now included in the transport equations using a targeted essentially non-oscillatory scheme. A verification of these new features of the solver is provided using one-dimensional burner stabilized flames, whereas a three dimensional turbulent flame is utilized to discuss the scalability of the proposed numerical tool.
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  • KLIFF: A framework to develop physics-based and machine learning interatomic potentials
    Interatomic potentials (IPs) are reduced-order models for calculating the potential energy of a system of atoms given their positions in space and species. IPs treat atoms as classical particles without explicitly modeling electrons and thus are computationally far less expensive than first-principles methods, enabling molecular simulations of significantly larger systems over longer times. Developing an IP is a complex iterative process involving multiple steps: assembling a training set, designing a functional form, optimizing the function parameters, testing model quality, and deployment to molecular simulation packages. This paper introduces the KIM-based learning-integrated fitting framework (KLIFF), a package that facilitates the entire IP development process. KLIFF supports both physics-based and machine learning IPs. It adopts a modular approach whereby various components in the fitting process, such as atomic environment descriptors, functional forms, loss functions, optimizers, quality analyzers, and so on, work seamlessly with each other. This provides a flexible framework for the rapid design of new IP forms. Trained IPs are compatible with the Knowledgebase of Interatomic Models (KIM) application programming interface (API) and can be readily used in major materials simulation packages compatible with KIM, including ASE, DL_POLY, GULP, LAMMPS, and QC. KLIFF is written in Python with computationally intensive components implemented in C++. It is parallelized over data and supports both shared-memory multicore desktop machines and high-performance distributed memory computing clusters. We demonstrate the use of KLIFF by fitting a physics-based Stillinger–Weber potential and a machine learning neural network potential for silicon. The KLIFF package, together with its documentation, is publicly available at: https://github.com/openkim/kliff.
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  • RadLib: A radiative property model library for CFD
    RadLib is a C++ library of radiation property models that can be applied to variety of systems involving radiative heat transfer, including CFD simulations. RadLib includes three major radiation property models—Planck Mean (PM) absorption coefficients, the weighted sum of gray gases (WSGG) model, and the rank-correlation spectral line weighted-sum-of-gray-gases (RCSLW) model. RadLib includes C++, Python, and Fortran interfaces and can be expanded to include additional models. Several example cases illustrate use of the models with an included ray-tracing solver, compare their accuracy relative to line-by-line (LBL) solutions, and examine their computational costs. Additionally, an integrated CFD example of an ethylene burner configuration using Fire Dynamics Simulator (FDS) is provided. RadLib provides researchers with convenient access to validated radiation property models and a framework for further development.
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  • Analytical formalism for calculations of parameters needed for quantitative analysis by X-ray photoelectron spectroscopy
    Quantitative analysis by X-ray photoelectron spectroscopy (XPS) requires knowledge of a theoretical model relating different features of recorded spectra with needed characteristics of a studied sample. An advanced theoretical approach describing an electron transport in condensed matter typically involved Monte Carlo (MC) simulations of electron trajectories since signal electrons undergo multiple interactions in a solid. The relevant algorithms are relatively slow and are burdened with statistical errors; thus they may be inconvenient in certain applications. However, much effort in the past was devoted to create models that describe electron transport by an analytical formalism with similar accuracy as Monte Carlo simulations. There are two major advantages of analytical approaches: (i) the computing time can be much shorter as compared with MC algorithms, and (ii) the relevant software can be easily included in external programs when large number of calculated parameters is needed. In the present work, the analytical formalism derived within the so-called transport approximation (TA) is described in detail, and implemented in the enclosed software TRANS_APPROX (Fortran 90). The formalism of quantitative XPS is based on an expression that provides a probability that a photoelectron emitted at a given depth reaches an analyzer without energy loss (emission depth distribution function – EMDDF). Consequently, the analytical expression for the EMDDF derived from the TA is discussed here. Stress is also put on parameters descending from the EMDDF: (i) the photoelectron signal intensity, (ii) the information depth, (iii) the mean escape depth, and (iv) the attenuation length for overlayer thickness measurements. The input parameters needed for calculations are briefly overviewed, followed by recommendations for use in the proposed program. Finally, it is indicated that the TA formalism requires calculations of numerous integrals with integrable singularities. It was proven here that these singularities do not need to be removed if the quadrature used is based on the so-called double exponential (DE) rule. This approach ensures high accuracy and fast convergence.
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  • CepGen – A generic central exclusive processes event generator for hadron-hadron collisions
    We present an event generator for the simulation of central exclusive processes in hadron-hadron reactions. Among others, it implements the two-photon production of lepton pairs previously introduced in LPAIR. As a proof of principle, we show that the two approaches are numerically consistent. The k_T-factorized description of this process is also handled, along with the two-photon production of a quark, or a W^+- gauge boson pair. This toolbox may be used as a common framework for the definition of many other processes following this approach. Additionally, photoproduction and other photon induced processes are also considered, or being implemented.
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  • Empathes: A general code for nudged elastic band transition states search
    An easy and flexible interface, Empathes (Extensible Minimum PATH EStimator), that allows to perform Nudged Elastic Band calculation for the determination of transition states is presented. The code is designed to be easily modified, in order to be associated with the user's preferred calculation software, even with those which implement composite approaches. In particular, the interfaces to Gaussian and Siesta programs are discussed in details, being the former only used for testing purpose, while the latter can be productively employed for transition states search with that commonly used density functional theory software for periodic calculations.
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  • MAELAS 2.0: A new version of a computer program for the calculation of magneto-elastic properties
    MAELAS is a computer program for the calculation of magnetocrystalline anisotropy energy, anisotropic magnetostrictive coefficients and magnetoelastic constants in an automated way. The method originally implemented in version 1.0 of MAELAS was based on the length optimization of the unit cell, proposed by Wu and Freeman, to calculate the anisotropic magnetostrictive coefficients. We present here a revised and updated version (v2.0) of MAELAS, where we added a new methodology to compute anisotropic magnetoelastic constants from a linear fitting of the energy versus applied strain. We analyze and compare the accuracy of both methods showing that the new approach is more reliable and robust than the one implemented in version 1.0, especially for non-cubic crystal symmetries. This analysis also helps us find that the accuracy of the method implemented in version 1.0 could be improved by using deformation gradients derived from the equilibrium magnetoelastic strain tensor, as well as potential future alternative methods like the strain optimization method. Additionally, we clarify the role of the demagnetized state in the fractional change in length, and derive the expression for saturation magnetostriction for polycrystals with trigonal, tetragonal and orthorhombic crystal symmetry. In this new version, we also fix some issues related to trigonal crystal symmetry found in version 1.0.
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  • PArthENoPE revolutions
    This paper presents the main features of a new and updated version of the program PArthENoPE, which the community has been using for many years for computing the abundances of light elements produced during Big Bang Nucleosynthesis. This is the third release of the PArthENoPE code, after the 2008 and the 2018 ones, and will be distributed from the code's website, http://parthenope.na.infn.it. Apart from minor changes, the main improvements in this new version include a revisited implementation of the nuclear rates for the most important reactions of deuterium destruction, 2H(p,γ)^3 He, 2H(d, n)^3 He and 2H(d, p)^3 H, and a re-designed GUI, which extends the functionality of the previous one. The new GUI, in particular, supersedes the previous tools for running over grids of parameters with a better management of parallel runs, and it offers a brand-new set of functions for plotting the results.
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  • Migration of hyper-fractal analysis from visual basic 6 to C# .Net
    In Grossu et al. (Comput. Phys. Commun. 184 (2013) 1812–1813) we presented Hyper-Fractal Analysis, a visual tool for estimating the fuzzy fractal dimension of images and 4D objects. As Visual Basic 6 could be considered an outdated language, with limited Object-Oriented Programming capabilities, migrating the application to C# .Net was treated in high priority. Following the goal of creating a highly reusable fractal analysis library, the code was also refactored to SOLID. Together with various improvements, the.Net version is also providing new tools for iso-fractal areas identification. The project success was confirmed by a comparative old/new version study. On the other hand, the most relevant functionalities were covered by unit tests.
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  • LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
    Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials.
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