Junye Wang, Xiaoxian Zhang, Anthony G. Bengough and John W. Crawford
The cell‐based method of domain decomposition was first introduced for complex 3D geometries. To further assess the method, the aim is to carry out flow simulation in rectangular…
Abstract
Purpose
The cell‐based method of domain decomposition was first introduced for complex 3D geometries. To further assess the method, the aim is to carry out flow simulation in rectangular ducts to compare the known analytical solutions.
Design/methodology/approach
The method is not based on equal subvolumes but on equal numbers of active cells. The variables of the simulation are stored in ordered 1D arrays to replace the conventional 3D arrays, and the domain decomposition of the complex 3D problems therefore becomes 1D. Finally, the 3D results can be recovered using a coordinate matrix. Through the flow simulation in the rectangular ducts how the algorithm of the domain decompositions works was illustrated clearly, and the numerical solution was compared with the exact solutions.
Findings
The cell‐based method can find the subdomain interfaces successfully. The parallelization based on the algorithm does not cause additional errors. The numerical results agree well with the exact solutions. Furthermore, the results of the parallelization show again that domains of 3D geometries can be decomposed automatically without inducing load imbalances.
Practical implications
Although, the approach is illustrated with lattice Boltzmann method, it is also applicable to other numerical methods in fluid dynamics and molecular dynamics.
Originality/value
Unlike the existing methods, the cell‐based method performs the load balance first based on the total number of fluid cells and then decomposes the domain into a number of groups (or subdomains). Thus, the task of the cell‐based method is to recover the interface rather than to balance the load as in the traditional methods. This work has examined the celled‐based method for the flow in rectangular ducts. The benchmark test confirms that the cell‐based domain decomposition is reliable and convenient in comparison with the well‐known exact solutions.
Details
Keywords
D.P. Zielinski and V.R. Voller
The purpose of this paper is to develop an alternative numerical approach for describing fractional diffusion in Cartesian and non‐Cartesian domains using a Monte Carlo random…
Abstract
Purpose
The purpose of this paper is to develop an alternative numerical approach for describing fractional diffusion in Cartesian and non‐Cartesian domains using a Monte Carlo random walk scheme. The resulting domain shifting scheme provides a numerical solution for multi‐dimensional steady state, source free diffusion problems with fluxes expressed in terms of Caputo fractional derivatives. This class of problems takes account of non‐locality in transport, expressed through parameters representing both the extent and direction of the non‐locality.
Design/methodology/approach
The method described here follows a similar approach to random walk methods previously developed for normal (local) diffusion. The key differences from standard methods are: first, the random shifting of the domain about the point of interest with, second, shift steps selected from non‐symmetric, power‐law tailed, Lévy probability distribution functions.
Findings
The domain shifting scheme is verified by comparing predictive solutions to known one‐dimensional and two‐dimensional analytical solutions for fractional diffusion problems. The scheme is also applied to a problem of fractional diffusion in a non‐Cartesian annulus domain. In contrast to the axisymmetric, steady state solution for normal diffusion, a non‐axisymmetric solution results.
Originality/value
This is the first random walk scheme to utilize the concept of allowing the domain to undergo the random walk about a point of interest. Domain shifting scheme solutions of fractional diffusion in non‐Cartesian domains provide an invaluable tool to direct the development of more sophisticated grid based finite element inspired fractional diffusion schemes.