High order resolution and parallel implementation on unstructured grids

The numerical solution of the two-dimensional inviscid Euler flow equations is given. The unstructured mesh is generated by the advancing front technique. A cell-centred upwind finite volume method has been adopted to discretize the Euler equations. Both explicit and point implicit time stepping algorithms are derived. The flux calculation using Roe's and Osher's approximate Riemann solvers are studied. It is shown that both the Roe and Osher's schemes produce an accurate representation of discontinuities (e.g. shock wave). It is also shown that better convergence performance has been achieved by the point implicit scheme than that by the explicit scheme. Validations have been done for subsonic and transonic flow over airfoils, supersonic flow past a compression corner and hypersonic flow past cylinder and blunt body geometries. An adaptive remeshing procedure is also applied to the numerical solution with the objective of getting improved results. The issue of high order reconstruction on unstructured grids has been discussed. The methodology of the Taylor series expansion is adopted. The calculation of the gradient at a reference point is carried out by the use of either the Green-Gauss integral formula or the least-square methods. Some recently developed limiter construction methods have been used and their performance has been demonstrated using the test example of the transonic flow over a RAE 2822 airfoil. It has been shown that similar pressure distributions are obtained by all limiters except for shock wave regions where the limiter is active. The convergence problem is illustrated by the mid-mod type limiter. It seems only the Venkatakrishnan limiter provides improved convergence. Other limiters do not appear to work as well as that shown in their original publications. Also the convergence history given by the least-square method appears better than that by the Green-Gauss method in the test

Simulation of pore-scale flow using finite element-methods

I present a new finite element (FE) simulation method to simulate pore-scale flow. Within the pore-space, I solve a simplified form of the incompressible Navier-Stoke’s equation, yielding the velocity field in a two-step solution approach. First, Poisson’s equation is solved with homogeneous boundary conditions, and then the pore pressure is computed and the velocity field obtained for no slip conditions at the grain boundaries. From the computed velocity field I estimate the effective permeability of porous media samples characterized by thin section micrographs, micro-CT scans and synthetically generated grain packings. This two-step process is much simpler than solving the full Navier Stokes equation and therefore provides the opportunity to study pore geometries with hundreds of thousands of pores in a computationally more cost effective manner than solving the full Navier-Stoke’s equation. My numerical model is verified with an analytical solution and validated on samples whose permeabilities and porosities had been measured in laboratory experiments (Akanji and Matthai, 2010). Comparisons were also made with Stokes solver, published experimental, approximate and exact permeability data. Starting with a numerically constructed synthetic grain packings, I also investigated the extent to which the details of pore micro-structure affect the hydraulic permeability (Garcia et al., 2009). I then estimate the hydraulic anisotropy of unconsolidated granular packings. With the future aim to simulate multiphase flow within the pore-space, I also compute the radii and derive capillary pressure from the Young-Laplace equation (Akanji and Matthai,2010

Highly scalable solution of incompressible Navier-Stokes equations using the spectral element method with overlapping grids

We present a highly-flexible Schwarz overlapping framework for simulating turbulent fluid/thermal transport in complex domains. The approach is based on a variant of the Schwarz alternating method in which the solution is advanced in parallel in separate overlapping subdomains. In each domain, the governing equations are discretized with an efficient high-order spectral element method (SEM). At each step, subdomain boundary data are determined by interpolating from the overlapping region of adjacent subdomains. The data are either lagged in time or extrapolated to higher-order temporal accuracy using a novel stabilized predictor-corrector algorithm. Matrix stability analysis is used to determine the optimal number of corrector iterations. Stability and accuracy are further improved with an optimal mass flux correction to guarantee mass conservation throughout the domain. The method supports an arbitrary number of subdomains. A new multirate time-stepping scheme is developed (a first for incompressible flow simulations) that allows the underlying equations to be advanced with time-step sizes varying as much as an order-of-magnitude between adjacent domains. All the developments maintain the third-order temporal convergence and exponential convergence of the originating SEM framework. This dissertation also presents a mesh optimizer that has been specifically designed for meshes generated for turbulent flow problems. The optimizer supports surface mesh improvement, which minimizes geometrical approximation errors. The smoother is shown to reduce the computational cost of numerical calculations by as much as 40%. Numerous examples illustrate the effectiveness of these new technologies for analyzing challenging turbulence problems that were previously infeasible.Ope

Unstructured parallel grid generation.

The ultimate goal of this study is to develop a 'tool' by which large-scale unstructured grids for realistic engineering problems can be generated efficiently on any parallel computer platform. The adopted strategy is based upon a geometrical partitioning concept, where the computational domain is sub-divided into a number of sub-domains which are then gridded independently in parallel. This study focuses on three-dimensional applications only, and it implements a Delaunay triangulation based generator to generate the sub-domain grids. Two different approaches have been investigated, where the variations between them are limited to (i) the domain decomposition and (ii) the inter-domain boundary gridding algorithms only. In order to carry out the domain decomposition task, the first approach requires an initial tetrahedral grid to be constructed, whilst the second approach operates directly on the boundary triangular grid. Hence, this thesis will refer to the first approach as 'indirect decomposition method' and to the second as 'direct decomposition method'. Work presented in this thesis also concerns the development of a framework in which all different sub-algorithms are integrated in combination with a specially designed parallel processing technique, termed as Dynamic Parallel Processing (DPP). The framework adopts the Message Passing Library (MPL) programming model and implements a Single Program Multiple Data (SPMD) structure with a Manager/Workers mechanism. The DPP provides great flexibility and efficiency in exploiting the available computing resources. The framework has proved to be a very effective tool for generating large-scale grids. Grids of realistic engineering problems and to the order of 115 million elements, generated using one processor on an SGI Challenge machine with 512 MBytes of shared memory, will be presented

2D finite volume model for groundwater flow simulations : integrating non-orthogonal grid capability into modflow

The modular finite-difference groundwater flow model MODFLOW is one of the most widely used groundwater modelling programs, and is applicable to most types of flow problems in its field. However, its finite difference formulation decreases its ability to simulate accurately natural aquifer geometries. To enhance its capability in simulating such boundaries, a finite volume scheme has been developed for inclusion in MODFLOW. In this study, the two-dimensional formulation has been considered. Three discretisations of the two-dimensional diffusion equation, governing groundwater flow and for use with structured quadrilateral meshes, have been developed. The three methods rely on a cell-centred finite volume approach, but show distinct differences in the choice of: gradient approximation, head interpolations and control volume. A time implicit formulation has been used in each model. The sparse system of linear equations that result from the implicit formulation has been solved by using an iterative solver, based on the strongly implicit procedure. Five test examples have been undertaken to compare the performance of the newly developed methods against MODFLOW predictions and analytical results. The accuracy of the results obtained was found to depend on the spatial and temporal discretisations. One of the three developed methods proved its robustness, with regard to mesh non-orthogonality and skewness, and was called the GWFV method. In a second step of studies, a field case study was used to test the preferred model. A mesh generator using a structured quadrilateral grid was used to produce the finite volume mesh of the simulated area. The results of MODFLOW and the GWFV model simulations were compared against field observations. A discussion about the performance of the new developed model has been included and the model has been shown to perform well in comparison with MODFLOW. Keywords: numerical models, finite volume discretisations, groundwater flow models, MODFLOW, non-orthogonal grid

Aeronautical engineering: A continuing bibliography with indexes (supplement 271)

This bibliography lists 666 reports, articles, and other documents introduced into the NASA scientific and technical information system in October, 1991. Subject coverage includes design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Deep Learning Based Malware Classification Using Deep Residual Network

The traditional malware detection approaches rely heavily on feature extraction procedure, in this paper we proposed a deep learning-based malware classification model by using a 18-layers deep residual network. Our model uses the raw bytecodes data of malware samples, converting the bytecodes to 3-channel RGB images and then applying the deep learning techniques to classify the malwares. Our experiment results show that the deep residual network model achieved an average accuracy of 86.54% by 5-fold cross validation. Comparing to the traditional methods for malware classification, our deep residual network model greatly simplify the malware detection and classification procedures, it achieved a very good classification accuracy as well. The dataset we used in this paper for training and testing is Malimg dataset, one of the biggest malware datasets released by vision research lab of UCSB