Mathematical Imaging and Surface Processing

Within the last decade image and geometry processing have become increasingly rigorous with solid foundations in mathematics. Both areas are research fields at the intersection of different mathematical disciplines, ranging from geometry and calculus of variations to PDE analysis and numerical analysis. The workshop brought together scientists from all these areas and a fruitful interplay took place. There was a lively exchange of ideas between geometry and image processing applications areas, characterized in a number of ways in this workshop. For example, optimal transport, first applied in computer vision is now used to define a distance measure between 3d shapes, spectral analysis as a tool in image processing can be applied in surface classification and matching, and so on. We have also seen the use of Riemannian geometry as a powerful tool to improve the analysis of multivalued images. This volume collects the abstracts for all the presentations covering this wide spectrum of tools and application domains

Modelling and quantification of structural uncertainties in petroleum reservoirs assisted by a hybrid cartesian cut cell/enriched multipoint flux approximation approach

Efficient and profitable oil production is subject to make reliable predictions about reservoir performance. However, restricted knowledge about reservoir distributed properties and reservoir structure calls for History Matching in which the reservoir model is calibrated to emulate the field observed history. Such an inverse problem yields multiple history-matched models which might result in different predictions of reservoir performance. Uncertainty Quantification restricts the raised model uncertainties and boosts the model reliability for the forecasts of future reservoir behaviour. Conventional approaches of Uncertainty Quantification ignore large scale uncertainties related to reservoir structure, while structural uncertainties can influence the reservoir forecasts more intensely compared with petrophysical uncertainty. What makes the quantification of structural uncertainty impracticable is the need for global regridding at each step of History Matching process. To resolve this obstacle, we develop an efficient methodology based on Cartesian Cut Cell Method which decouples the model from its representation onto the grid and allows uncertain structures to be varied as a part of History Matching process. Reduced numerical accuracy due to cell degeneracies in the vicinity of geological structures is adequately compensated with an enhanced scheme of class Locally Conservative Flux Continuous Methods (Extended Enriched Multipoint Flux Approximation Method abbreviated to extended EMPFA). The robustness and consistency of proposed Hybrid Cartesian Cut Cell/extended EMPFA approach are demonstrated in terms of true representation of geological structures influence on flow behaviour. In this research, the general framework of Uncertainty Quantification is extended and well-equipped by proposed approach to tackle uncertainties of different structures such as reservoir horizons, bedding layers, faults and pinchouts. Significant improvements in the quality of reservoir recovery forecasts and reservoir volume estimation are presented for synthetic models of uncertain structures. Also this thesis provides a comparative study of structural uncertainty influence on reservoir forecasts among various geological structures

Synthetic turbulence generation for LES on unstructured Cartesian grids

A parallel CFD code to solve incompressible fluid flow on unstructured Cartesian meshes has been developed almost from ground up. Turbulence statistics have been computed using the Large Eddy Simulation technique. The new code was subjected to some validation where results are compared to available reference data. An analysis on the iteration and discretisation errors was carried out. This code was then applied to predict the lid driven cubical cavity flow in at a bulk Reynolds number of 10,000. Three different mesh sizes were used to investigate independence of results on grid size. Amongst others, turbulence statistics were checked against Kolmogorov -5/3 law. A detailed study of synthetic turbulence methods was carried out and applied to the prediction of flow in a duct with square cross section using an inlet and outflow boundaries. Three different turbulence generation methods were investigated namely the artificial turbulence generation method, random perturbation method and a novel hybrid particle-wave method also termed as the enhanced vortex particle method in this study. The mean and instantaneous field variables together with the turbulence statistics from each method were compared and analysed. Finally, the code was used to solve turbulent flow over arrays of wall-mounted obstacles with mesh densities comparable to previous studies. The velocity profiles and vector fields at various locations in the domain were compared to data obtained from recent LES simulations. The artificial turbulence generation case was applied for the first time to produce turbulence at the inlet. The turbulence kinetic energy spectrum distribution agrees well with reference data. Important findings from this study are clarified and some suggestions for future work are given in the conclusions section.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

NAS (Numerical Aerodynamic Simulation Program) technical summaries, March 1989 - February 1990

Given here are selected scientific results from the Numerical Aerodynamic Simulation (NAS) Program's third year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP supercomputer. Topics covered include flow field analysis of fighter wing configurations, large-scale ocean modeling, the Space Shuttle flow field, advanced computational fluid dynamics (CFD) codes for rotary-wing airloads and performance prediction, turbulence modeling of separated flows, airloads and acoustics of rotorcraft, vortex-induced nonlinearities on submarines, and standing oblique detonation waves

Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018

This open access book features a selection of high-quality papers from the presentations at the International Conference on Spectral and High-Order Methods 2018, offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions

Supercomputing in Aerospace

Topics addressed include: numerical aerodynamic simulation; computational mechanics; supercomputers; aerospace propulsion systems; computational modeling in ballistics; turbulence modeling; computational chemistry; computational fluid dynamics; and computational astrophysics