A multi-level parallel solver for rarefied gas flows in porous media

A high-performance gas kinetic solver using multi-level parallelization is developed to enable pore-scale simulations of rarefied flows in porous media. The Bhatnagar–Gross–Krook model equation is solved by the discrete velocity method with an iterative scheme. The multi-level MPI/OpenMP parallelization is implemented with the aim to efficiently utilize the computational resources to allow direct simulation of rarefied gas flows in porous media based on digital rock images for the first time. The multi-level parallel approach is analyzed in detail confirming its better performance than the commonly-used MPI processing alone for an iterative scheme. With high communication efficiency and appropriate load balancing among CPU processes, parallel efficiency of 94% is achieved for 1536 cores in the 2D simulations, and 81% for 12288 cores in the 3D simulations. While decomposition in the spatial space does not affect the simulation results, one additional benefit of this approach is that the number of subdomains can be kept minimal to avoid deterioration of the convergence rate of the iteration process. This multi-level parallel approach can be readily extended to solve other Boltzmann model equations

High order parallelisation of an unstructured grid, discontinuous-Galerkin finite element solver for the Boltzmann–BGK equation

This paper outlines the implementation and performance of a parallelisation approach involving partitioning of both physical space and velocity space domains for finite element solution of the Boltzmann-BGK equation. The numerical solver is based on a discontinuous Taylor–Galerkin approach. To the authors' knowledge this is the first time a ‘high order’ parallelisation, or `phase space parallelisation', approach has been attempted in conjunction with a numerical solver of this type. Restrictions on scalability have been overcome with the implementation detailed in this paper. The developed algorithm has major advantages over continuum solvers in applications where strong discontinuities prevail and/or in rarefied flow applications where the Knudsen number is large. Previous work by the authors has outlined the range of applications that this solver is capable of tackling. The paper demonstrates that the high order parallelisation implemented is significantly more effective than previous implementations at exploiting High Performance Computing architectures

A theoretical and empirical investigation into the growth of ultralong carbon nanotubes

Carbon nanotubes (CNTs) were first discovered and named as such by Iijima in 1991. Various institutes and researchers have since widely conducted ongoing research on carbon nanotube growth. The exceptional properties of CNTs, including their electrical and mechanical properties, aim to revolutionise the applications of electronics and devices in the future such as transmission power lines and lightweight high-strength carbon nanotube fibres. Therefore, understanding the mechanisms of growing ultra-long carbon nanotubes (UL-CNTs) that can increase the length to more than a centimetre long can unlock the full potential of the CNTs. This PhD project will have three parts: (Ⅰ) the growth experiments using different types of monometallic & bimetallic iron based catalysts for growing carbon nanotubes; (Ⅱ) the computational simulation of flow fields around carbon nanotube geometry in a micro-scale; (Ⅲ) the applications of carbon nanotubes produced from waste plastics, such as Ethernet & audio cables, and public engagement events about the research. In the growth experiment topic, the primary objective of this research is to study the catalyst activities on the rate of carbon nanotube growth using monometallic (Fe) & bimetallic catalysts (Fe-Cu, Fe-Co, Fe-Ni, Fe-Sn, Fe-Ga, Fe-Mg & Fe-Al) dissolved in deionised water, and find which catalysts have the potential to grow the longest carbon nanotubes with improved characteristics, such as G/D (graphene/ disorders) ratio. As we know, the carbon source gas flow rate and reactor temperature profiles can affect the length of carbon nanotubes from the literature; an effective way to optimise experimental conditions to grow UL-CNTs is to use computational fluid dynamics (CFD) modelling methods. So far, there has been little research on the growth of ultra-long carbon nanotubes under a non-continuous flow environment on a nanoscale. Most computational modelling studies have only focused on the continuity of flow in a traditional approach. This research uses the BGK-Boltzmann equation and molecular collision models to investigate flow behaviours at the nanoscopic scale. Thus, this study provides an exciting opportunity to advance the knowledge of growing ultra-long carbon nanotubes (UL-CNTs) of centimetre length or higher and may be used in applications including the carbon nanotube Ethernet and audio cables as mentioned in this project