Dosimetry in mixed radiation fields

Imperial Users onl

KINETICALLY CONSISTENT THERMAL LATTICE BOLTZMANN MODELS

The lattice Boltzmann (LB) method has developed into a numerically robust and efficient technique for simulating a wide variety of complex fluid flows. Unlike conventional CFD methods, the LB method is based on microscopic models and mesoscopic kinetic equations in which the collective long-term behavior of pseudo-particles is used to simulate the hydrodynamic limit of a system. Due to its kinetic basis, the LB method is particularly useful in applications involving interfacial dynamics and complex boundaries, such as multiphase or multicomponent flows. However, most of the LB models, both single and multiphase, do not satisfy the energy conservation principle, thus limiting their ability to provide quantitatively accurate predictions for cases with substantial heat transfer rates. To address this issue, this dissertation focuses on developing kinetically consistent and energy conserving LB models for single phase flows, in particular. Firstly, through a procedure similar to the Galerkin method, we present a mathematical formulation of the LB method based on the concept of projection of the distributions onto a Hermite-polynomial basis and their systematic truncation. This formulation is shown to be capable of approximating the near incompressible, weakly compressible, and fully compressible (thermal) limits of the continuous Boltzmann equation, thus obviating the previous low-Mach number assumption. Physically it means that this formulation allows a kinetically-accurate description of flows involving large heat transfer rates. The various higher-order discrete-velocity sets (lattices) that follow from this formulation are also compiled. The resulting higher-order thermal model is validated for benchmark thermal flows, such as Rayleigh-Benard convection and thermal Couette flow, in an off-lattice framework. Our tests indicate that the D2Q39-based thermal models are capable of modeling incompressible and weakly compressible thermal flows accurately. In the validation process, through a finite-difference-type boundary treatment, we also extend the applicability of higher-order la ttices to flow-domains with solid boundaries, which was previously restricted. Secondly, we present various off-lattice time-marching schemes for solving the discrete Boltzmann equation. Specifically, the various temporal schemes are analyzed with respect to their numerical stability as a function of the maximum allowable time-step . We show that the characteristics-based temporal schemes offer the best numerical stability among all other comparable schemes. Due to this enhanced numerical stability, we show that the usual restriction no longer applies, enabling larger time-steps, and thereby reducing the computational run-time. The off-lattice scheme were also successfully extended to higher-order LB models. Finally, we present the algorithm and single-core optimization techniques for a off-lattice, higher-order LB code. Using simple cache optimization techniques and a proper choice of the data-structure, we obtain a 5-7X improvement in performance compared to a naive, unoptimized code. Thereafter, the optimized code is parallelized using OpenMP. Scalability tests indicate a parallel efficiency of 80% on shared-memory systems with up to 50 cores (strong scaling). An analysis of the higher-order LB models also show that they are less memory-bound if the off-lattice temporal schemes are used, thus making them more scalable compared to the stream-collide type scheme

Finite element solution of the Boltzmann equation for rarefied macroscopic gas flows.

This thesis presents research carried out at The Civil and Computational Engineering Centre at Swansea University between September 2004 and December 2007. The focus of the research was the application of modern finite element solution techniques to the governing equations of molecular gas dynamics in order to solve macroscopic gas flow problems. The journey of research began by considering and comparing various finite difference and finite element formulations in the solution of a simple scalar convection equation. This formed the basis for developing a solver for a variety of forms of the Boltzmann equation of molecular gas dynamics, and application of these solvers to a range of subsonic, transonic and supersonic gas flow problems. The merits and drawbacks of the molecular approach, particularly when compared with more traditional continuum CFD solvers, are identified along with possible extensions to the work presented here

Coupled Flow Discrete Element Method Application in Granular Porous Media using Open Source Codes

The flow of fluid through an assembly of particles is of interest to a range of fields such as civil engineering, powder technology, and liquid chromatography. The Discrete Element Method (DEM) is a numerical approximation used to model the interaction of particles and fluid. This study starts with the verification of the open source 3D DEM code (YADE) by investigating simple, one and two-particle contact problems, and DEM results are shown to compare very well with the classical 1D vibration solutions. 2D and 3D simulations of particles flowing through a hopper were then investigated. The stability of the sinkhole repair for a range of rock particle diameters (relative to the sinkhole throat diameter) was investigated by presenting a statistical description to describe the gradual transition from unstable to stable behavior. This was followed by an investigation of a fluid-solid two phase flow system. The fluid phase is modeled by solving the averaged Navier-Stokes equation using the Finite Volume Method (FVM) and the solid phase was modeled using the DEM. A framework was developed to couple two open source codes: YADE-OpenDEM for the DEM and OpenFOAM for the computational fluid dynamics. The particle-fluid interaction is quantified using a semi-empirical relationship proposed by Ergun (1952). 1D solutions for the classic upward seepage flow and consolidation were obtained and compared well with the analytical solutions. These verification problems were also used to explore the appropriate time step size for both the fluid and mechanical solution processes, and the choice of the viscous damping coefficient. Finally, the coupled DEM-CFD code is used in the solution of a classical 2D seepage problem of flow beneath a sheet pile and the slurry packing of a chromatography column. For the sheet pile problem, both the quantity of seepage and the pressure gradient leading to the quick condition are investigated. The effect of the fluid volume size relative to particle size was also investigated. For the packing of a chromatography column, the method was able to reproduce the “wall effects” during the axial upward compression procedure, providing a displacement field similar to that observed in experiments

Graduate catalog, University of Missouri--Columbia, 2001-2003

208 page

Guided Automatic Binary Parallelisation

For decades, the software industry has amassed a vast repository of pre-compiled libraries and executables which are still valuable and actively in use. However, for a significant fraction of these binaries, most of the source code is absent or is written in old languages, making it practically impossible to recompile them for new generations of hardware. As the number of cores in chip multi-processors (CMPs) continue to scale, the performance of this legacy software becomes increasingly sub-optimal. Rewriting new optimised and parallel software would be a time-consuming and expensive task. Without source code, existing automatic performance enhancing and parallelisation techniques are not applicable for legacy software or parts of new applications linked with legacy libraries. In this dissertation, three tools are presented to address the challenge of optimising legacy binaries. The first, GBR (Guided Binary Recompilation), is a tool that recompiles stripped application binaries without the need for the source code or relocation information. GBR performs static binary analysis to determine how recompilation should be undertaken, and produces a domain-specific hint program. This hint program is loaded and interpreted by the GBR dynamic runtime, which is built on top of the open-source dynamic binary translator, DynamoRIO. In this manner, complicated recompilation of the target binary is carried out to achieve optimised execution on a real system. The problem of limited dataflow and type information is addressed through cooperation between the hint program and JIT optimisation. The utility of GBR is demonstrated by software prefetch and vectorisation optimisations to achieve performance improvements compared to their original native execution. The second tool is called BEEP (Binary Emulator for Estimating Parallelism), an extension to GBR for binary instrumentation. BEEP is used to identify potential thread-level parallelism through static binary analysis and binary instrumentation. BEEP performs preliminary static analysis on binaries and encodes all statically-undecided questions into a hint program. The hint program is interpreted by GBR so that on-demand binary instrumentation codes are inserted to answer the questions from runtime information. BEEP incorporates a few parallel cost models to evaluate identified parallelism under different parallelisation paradigms. The third tool is named GABP (Guided Automatic Binary Parallelisation), an extension to GBR for parallelisation. GABP focuses on loops from sequential application binaries and automatically extracts thread-level parallelism from them on-the-fly, under the direction of the hint program, for efficient parallel execution. It employs a range of runtime schemes, such as thread-level speculation and synchronisation, to handle runtime data dependences. GABP achieves a geometric mean of speedup of 1.91x on binaries from SPEC CPU2006 on a real x86-64 eight-core system compared to native sequential execution. Performance is obtained for SPEC CPU2006 executables compiled from a variety of source languages and by different compilers.St John's Benefactor Scholarship ARM Sponsorshi