Computer Physics Communications最新文献

It is essential to precisely determine the evolving concentrations of radioactive nuclides within transmutation problems. It is also a crucial aspect of nuclear physics with widespread applications in nuclear waste management and energy production. This paper introduces CNUCTRAN, a novel computer program that employs a probabilistic approach to estimate nuclide concentrations in transmutation problems. CNUCTRAN directly simulates nuclei transformations arising from various nuclear reactions, diverging from the traditional deterministic methods that solve the Bateman equation using matrix exponential approximation. This approach effectively addresses numerical challenges associated with solving the Bateman equations, therefore, circumventing the need for matrix exponential approximations that risk producing nonphysical concentrations. Our sample calculations using CNUCTRAN shows that the concentration predictions of CNUCTRAN have a relative error of less than 0.001% compared to the state-of-the-art method, CRAM, in different test cases. This makes CNUCTRAN a valuable alternative tool for transmutation analysis.

Program summary

Program Title: CNUCTRAN

CPC Library link to program files: https://doi.org/10.17632/b484w2vx52.1

Developer's repository link: https://github.com/rabieomar92/cnuctran/releases

Licensing provisions: MIT

Programming language: C++

Nature of problem: CNUCTRAN simulates the transmutation of various nuclides such as decays, fissions, and neutron induced reactions using a direct simulation approach. It has the capability of predicting the final concentration of a large system of nuclides altogether after a specified time step, $t_f$.

Solution method: CNUCTRAN works based on the novel probabilistic method such that it does not compute the final nuclide concentrations by solving Bateman equations. Instead, it statistically tracks nuclide transformations into one another in a transmutation problem. The technique encapsulates various possible nuclide transformations into a sparse transfer matrix, $T$, whose elements are made up of various nuclear reaction probabilities. Next, $T$ serves as a matrix operator acting on the initial nuclide concentrations, $y\left(0\right)$, producing the final nuclide concentrations, y.

We present a Python-based open-source library named Jiezi, which provides the means of simulating the electronic transport properties of nanoscaled devices on the atomistic level. The key feature of Jiezi lies in its core algorithm, i.e., self-consistent orchestration between the non-equilibrium Green's function (NEGF) method and a Poisson's equation solver. Beyond the construction of the tight-binding (TB) Hamiltonian with empirical parameters for conventional materials, the package offers a comprehensive framework for constructing the Wannier-based Hamiltonian matrix, enabling the investigation of novel materials and their heterostructures. To expedite the solution of NEGF systems, a methodology based on renormalization theory is proposed for reducing the dimension of the Hamiltonian matrix. Additionally, we adopt a non-linear Poisson equation solver with no analytical approximation in this software. The software facilitates seamless integration with external tools for geometry and mesh generation and post-processing. In this paper, we present the main capabilities and workflow by demonstrating with a simulation for the carbon nanotube field-effect transistor (CNTFET).

Program summary

Program Title: Jiezi

CPC Library link to program files: https://doi.org/10.17632/nk79kbtww4.1

Developer's repository link: https://github.com/Jiezi-negf/Jiezi

Licensing provisions: GPLv3

Programming language: Python

Nature of problem: Simulates the quantum transport property of nano-scaled transistors based on the predefined device structure and the material composition.

Solution method: Solves the coupled Schrödinger equation and Poisson equation by NEGF and finite element method.

A framework is presented for the spectral-element code Nek5000, which has been, and still is, widely used in the computational fluid dynamics (CFD) community to perform high-fidelity numerical simulations of transitional and high Reynolds number flows. Despite the widespread usage, there is a deficiency in having a comprehensive set of tools specifically designed for conducting simulations using Nek5000. To address this issue, we have created a unique framework that allows, inter alia, to perform stability analysis and compute statistics of a turbulent flow. The framework encapsulates modules that provide tools, run-time parameters and memory structures, defining interfaces and performing different tasks. First, the framework architecture is described, showing its non-intrusive approach. Then, the modules are presented, explaining the main tools that have been implemented and describing some of the test cases. The code is open-source and available online, with proper documentation, to-run instructions and related examples.

A nonlinear Harmonic Navier-Stokes (HNS) framework is introduced for simulating instabilities in laminar spanwise-invariant shear layers, featuring sharp and smooth wall surface protuberances. While such cases play a critical role in the process of laminar-to-turbulent transition, classical stability theory analyses such as parabolized or local stability methods fail to provide (accurate) results, due to their underlying assumptions. The generalized incompressible Navier-Stokes (NS) equations are expanded in perturbed form, using a spanwise and temporal Fourier ansatz for flow perturbations. The resulting equations are discretized using spectral collocation in the wall-normal direction and finite-difference methods in the streamwise direction. The equations are then solved using a direct sparse-matrix solver. The nonlinear mode interaction terms are converged iteratively. The solution implementation makes use of a generalized domain transformation to account for geometrical smooth surface features, such as humps. No-slip conditions can be embedded in the interior domain to account for the presence of sharp surface features such as forward- or backward-facing steps. Common difficulties with Navier-Stokes solvers, such as the treatment of the outflow boundary and convergence of nonlinear terms, are considered in detail. The performance of the developed solver is evaluated against several cases of representative boundary layer instability growth, including linear and nonlinear growth of Tollmien-Schlichting waves in a Blasius boundary layer and stationary crossflow instabilities in a swept flat-plate boundary layer. The latter problem is also treated in the presence of a geometrical smooth hump and a sharp forward-facing step at the wall. HNS simulation results, such as perturbation amplitudes, growth rates, and shape functions, are compared to benchmark flow stability analysis methods such as Parabolized Stability Equations (PSE), Adaptive Harmonic Linearized Navier-Stokes (AHLNS), or Direct Numerical Simulations (DNS). Good agreement is observed in all cases. The HNS solver is subjected to a grid convergence study and a simple performance benchmark, namely memory usage and computational cost. The computational cost is found to be considerably lower than high-fidelity DNS at comparable grid resolutions.

Program summary

Program Title: DeHNSSo

CPC Library link to program files: https://doi.org/10.17632/9bnms99kk2.1

Developer's repository link: https://github.com/SvenWesterbeek/DeHNSSo

Licensing provisions: GPLv3

Programming language: Matlab

Supplementary material: The supplementary material contains the code as well as a user manual.

Nature of problem: Fluid flows are subject to laminar-to-turbulent transition following the growth of instabilities.