Acceleration of an unstructured hybrid mesh RANS solver by porting to GPU architectures

The modern CFD process consists of mesh generation, flow solving and post-processing integrated into an automated workflow. During the last several years we have developed and published research aimed at producing a meshing and geometry editing system, implemented in an end-to-end parallel, scalable manner and capable of automatic handling of large scale, real world applications. The particular focus of this paper is the associated unstructured mesh RANS flow solver and the porting of it to GPU architectures. After briefly describing the solver itself, the special issues associated with porting codes using unstructured data structures are discussed - followed by some application examples. Copyright © 2011 by W.N. Dawes.

In-situ deposition of sparse vertically aligned carbon nanofibres on catalytically activated stainless steel mesh for field emission applications

We report on an inexpensive, facile and industry viable carbon nanofibre catalyst activation process achieved by exposing stainless steel mesh to an electrolyzed metal etchant. The surface evolution of the catalyst islands combines low-rate electroplating and substrate dissolution. The plasma enhanced chemical vapour deposited carbon nanofibres had aspect-ratios > 150 and demonstrated excellent height and crystallographic uniformity with localised coverage. The nanofibres were well-aligned with spacing consistent with the field emission nearest neighbour electrostatic shielding criteria, without the need of any post-growth processing. Nanofibre inclusion significantly reduced the emission threshold field from 4.5 V/μm (native mesh) to 2.5 V/μm and increased the field enhancement factor to approximately 7000. © 2011 Elsevier B.V. All rights reserved.

Progressive 3D reconstruction of infrastructure with videogrammetry

A number of methods are commonly used today to collect infrastructure's spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic, and cost-efficient at the same time. This paper presents a videogrammetric framework for acquiring spatial data of infrastructure which holds the promise to address this limitation. It uses a calibrated set of low-cost high resolution video cameras that is progressively traversed around the scene and aims to produce a dense 3D point cloud which is updated in each frame. It allows for progressive reconstruction as opposed to point-and-shoot followed by point cloud stitching. The feasibility of the framework is studied in this paper. Required steps through this process are presented and the unique challenges of each step are identified. Results specific to each step are also presented.

Progressive Site Modelling with Videogrammetry

A number of methods are commonly used today to collect as-built spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic and cost-efficient at the same time. LiDARmethods generate high resolution depth information, but the significant cost of the equipment counteracts their benefits for the majority of construction projects. This is true especially for small projects, where projected savings hardly justify adopting this technology. Vision-based technologies, such as videogrammetry, is potentially able to address the existing limitations.