Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"Scientific Computation"”.
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Techniques for the Interactive Development of Numerical Linear Algebra Libraries for Scientific Computation
The development of high-performance numerical algorithms and their effective use in application codes is an iterative process involving the refinement of the algorithms and their implementations that continues during the lifetime of the algorithm. Knowledge and expertise from the areas of numerical …
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Three Novel Algorithms for Triangle Mesh Processing: Progressive Delaunay Refinement Mesh Generation, Mls-Based Scattered Data Interpolation and Constrained Centroid Voronoi-Based Quadrangulation
… quadrilateral meshes show more stability in scientific computation. Because most of acquisition and mesh generation methods result in triangle meshes, converting those to quadrilateral domain has become an important research problem too. The technique that presented in this thesis uses …
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Visualization of Surfaces and 3D Vector Fields
… and vector fields with three components in scientific computation is still a hard problem in compute graphic area. People build their own visualization packages for their special purposes. And there exist some general-purpose packages (MatLab, Vis5D), but they all require extensive user …
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Scalable Methods for Processing Massive Geometric Meshes
… in fields as diverse as the visual arts and scientific computation. Technological advances in the areas of three-dimensional scanning, digital storage, and computer processing speeds have enabled the acquisition of geometric meshes of unprecedented size and detail. Too large to fit in-core on …
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Reliable Data Processing Enabled By Program Analysis
… is often performed by computer programs. In scientific computation, data are collected through instruments or sensors that may be exposed to rough environmental conditions, leading to errors. Furthermore, during the computation process data may not be precisely represented due to the limited …
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Coupled Molecular Dynamics and Finite Element Methods for the simulation of interacting particles and fields
… in many fields: e.g. nuclear and atomic physics, computational material science, computational chemistry, molecular biology and pharmacology. Under the locution Molecular Dynamics (MD) we can regroup a variety of approaches and numerical codes, whereas the commonalities are: 1) the atomistic (or …
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Molecular dynamics-Lattice Boltzmann hybrid method on graphics processors
Molecular Dynamics is an atomistic computational tool that has become popular due to its ability to predict nano-scale fluid phenomena. For studying flows, a non-equilibrium method is implemented involving characterization of boundary and other conditions to properly simulate the flow. Using a …
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Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems
… memory of critical problem domains, including scientific computation and data intensive computing, computing researchers continue to innovate in the high-end distributed memory architecture space to create cost-effective and scalable solutions. The emerging distributed memory architectures are …
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Calculating thermochemical equilibrium for multiphysics simulations of nuclear materials : development of yellowjacket gibbs energy minimiser
… changes with time. For such complex systems, computational thermodynamics plays a valuable role in predicting many phenomena and is often necessary for understanding and informing others. For this reason, there has been an increasing interest in incorporating equilibrium thermodynamics …
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Deep Learning For Surrogate Modeling And Uncertainty Quantification In Science & Engineering
Scientific machine learning (SciML) has become an increasingly important tool for constructing surrogate models of complex physical systems, enabling rapid approximation of expensive numerical solvers and supporting tasks such as design optimization, uncertainty analysis, and autonomous …
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Applications of Machine Learning to Facilitate Software Engineering and Scientific Computing
… remain unexplored due to lack of data or lack of computational tools. This dissertation explores machine learning approaches in case studies involving image classification and natural language processing. In addition, a software library in the form of two-way bridge connecting deep learning models …
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Optimisation of a Modern Numerical Library: a Bottom-Up Approach
… of modern applications, from machine learning, scientific computation and to Internet of Things (IoT). It has dominated many aspects of our daily lives. Numerical library used to lie in the low level of applications, and only need to focus on provide fast calculation. However, with social …
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Simulating biochemical physics with computers
This dissertation is composed of three parts. The first part is to argue the solvent effects on the solvatochromic shift of the n ! !* excitation of acetone in ambient and supercritical water fluid using a hybrid QM!CI/MM potential in MC simulations. The solute is described by the AM1 approach and …
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Runtime support for irregular computation in MPI-based applications
… of applications that have been using irregular computation models in various domains, such as computational chemistry, bioinformatics, nuclear reactor simulation and social network analysis. Due to the irregular and data-dependent communication patterns and sparse data structures involved in …
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The Foundations of Infinite-Dimensional Spectral Computations
Spectral computations in infinite dimensions are ubiquitous in the sciences. However, their many applications and theoretical studies depend on computations which are infamously difficult. This thesis, therefore, addresses the broad question, “What is computationally possible within the field of …