Surface Remeshing and Applications

Due to the focus of popular graphic accelerators, triangle meshes remain the primary representation for 3D surfaces. They are the simplest form of interpolation between surface samples, which may have been acquired with a laser scanner, computed from a 3D scalar field resolved on a regular grid, or identified on slices of medical data. Typical methods for the generation of triangle meshes from raw data attempt to lose as less information as possible, so that the resulting surface models can be used in the widest range of scenarios. When such a general-purpose model has to be used in a particular application context, however, a pre-processing is often worth to be considered. In some cases, it is convenient to slightly modify the geometry and/or the connectivity of the mesh, so that further processing can take place more easily. Other applications may require the mesh to have a pre-defined structure, which is often different from the one of the original general-purpose mesh. The central focus of this thesis is the automatic remeshing of highly detailed surface triangulations. Besides a thorough discussion of state-of-the-art applications such as real-time rendering and simulation, new approaches are proposed which use remeshing for topological analysis, flexible mesh generation and 3D compression. Furthermore, innovative methods are introduced to post-process polygonal models in order to recover information which was lost, or hidden, by a prior remeshing process. Besides the technical contributions, this thesis aims at showing that surface remeshing is much more useful than it may seem at a first sight, as it represents a nearly fundamental step for making several applications feasible in practice

Practical Distribution-Sensitive Point Location in Triangulations

International audienceWe design, analyze, implement, and evaluate a distribution-sensitive point location algorithm based on the classical Jump & Walk, called Keep, Jump, & Walk. For a batch of query points, the main idea is to use previous queries to improve the current one. In practice, Keep, Jump, & Walk is ac- tually a very competitive method to locate points in a triangulation. We also study some constant- memory distribution-sensitive point location algorithms, which work well in practice with the classical space-filling heuristic for fast point location. Regarding point location in a Delaunay triangulation, we show how the Delaunay hierarchy can be used to answer, under some hypotheses, a query q with a O(log #(pq)) randomized expected complexity, where p is a previously located query and #(s) indicates the number of simplices crossed by the line segment s. The Delaunay hierarchy has O(nlogn) time complexity and O(n) memory complexity in the plane, and under certain realistic hypotheses these com- plexities generalize to any finite dimension. Finally, we combine the good distribution-sensitive behavior of Keep, Jump, & Walk, and the good complexity of the Delaunay hierarchy, into a novel point location algorithm called Keep, Jump, & Climb. To the best of our knowledge, Keep, Jump, & Climb is the first practical distribution-sensitive algorithm that works both in theory and in practice for Delaunay triangulations

Algorithms for Triangles, Cones & Peaks

Three different geometric objects are at the center of this dissertation: triangles, cones and peaks. In computational geometry, triangles are the most basic shape for planar subdivisions. Particularly, Delaunay triangulations are a widely used for manifold applications in engineering, geographic information systems, telecommunication networks, etc. We present two novel parallel algorithms to construct the Delaunay triangulation of a given point set. Yao graphs are geometric spanners that connect each point of a given set to its nearest neighbor in each of $k$ cones drawn around it. They are used to aid the construction of Euclidean minimum spanning trees or in wireless networks for topology control and routing. We present the first implementation of an optimal $\mathcal{O}(n \log n)$-time sweepline algorithm to construct Yao graphs. One metric to quantify the importance of a mountain peak is its isolation. Isolation measures the distance between a peak and the closest point of higher elevation. Computing this metric from high-resolution digital elevation models (DEMs) requires efficient algorithms. We present a novel sweep-plane algorithm that can calculate the isolation of all peaks on Earth in mere minutes

Development of an efficient solver for detailed kinetics in reactive flows

The use of chemical kinetic mechanisms in CAE tools for reactive flow simulations is of high importance for studying and predicting pollutant formation. However, usage of complex reaction schemes is accompanied by high computational cost in both 1D and 3-D CFD frameworks. The combustion research community has addressed such challenge via two main approaches: 1) tailor made mechanism reduction strategies; 2) pre-tabulation of the chemistry process and look-up during run-time. The present work covers both topics, although much of the methodology development and validation efforts focused on tabulation. In the first phase of the PhD work, an isomer lumping strategy based on thermodynamic data was developed and applied to a detailed three component reaction mechanism for n-decane, alpha-methylnaphthalene and methyl decanoate comprising 807 species and 7807 reactions. A total of 74 isomer groups were identified within the oxidation of n-decane and methyl decanoate via the assessment of the Gibbs free energy of the isomers. The lumping procedure led to a mechanism of 463 species and 7600 reactions, which was compared against the detailed version over several reactor conditions and over a broad range of temperature, pressure and equivalence ratio. In all cases, excellent agreement between the predictions obtained using the lumped and the detailed mechanism has been observed with an overall absolute error below 12%. In the second phase of the PhD work, a tabulated chemistry approach was developed, implemented and validated against an on-the-fly chemistry solver across different simulation frameworks. As a first attempt, a flamelet-based tabulation method for soot source terms was coupled to the stochastic reactor model and tested against a well stirred reactor-based approach under Diesel engine conditions. The main purpose was to assess and quantify benefits of tabulation within the 0-D SRM framework with respect to soot formation only. Subsequently, a latent enthalpy (h298) based approach was developed and implemented within the SRM model to predict both combustion and emission formation. This approach was widely validated against the detailed on-the-fly solver solutions under 0-D reactor conditions as well as Diesel engine conditions for a wide range of operating points. Good agreement was found between the two solvers and a remarkable speed-up was obtained in terms of computational costs of the simulation. As a last step, the same tabulated chemistry solver was coupled to a commercial CFD software via user defined functions and performances were assessed against the built-in on-the fly chemistry solver under Diesel engine sector simulations. The tabulated chemistry solver proved to be within an acceptable level of accuracy for engineering studies and showed a consistent speed-up in comparison to the online chemistry solver. Across all the investigated frameworks, the developed tabulated chemistry solver was found to be a valid solution to speed-up simulation time without compromising accuracy of the solution for combustion and emissions predictions for engine applications. In fact, the much-reduced CPU times allowed the SRM to be included in broader engine development campaigns where multi-objective optimization methods where efficiently used to explore new engine designs

Modeling of Turbulent Sooting Flames

Modeling multiphase particles in turbulent fluid environment is a challenging task. To accurately describe the size distribution, a large number of scalars need to be transported at each time-step. Add to that the heat release and species mass fraction changes from nonlinear combustion chemistry reactions, and you have a tightly coupled set of equations that describe the (i) turbulence, (ii) chemistry, and (iii) soot particle interactions (physical agglomeration and surface chemistry reactions). Uncertainty in any one of these models will inadvertently introduce errors of up to a few orders of magnitude in predicted soot quantities. The objective of this thesis is to investigate the effect of turbulence and chemistry on soot evolution with respect to different soot aerosol models and to develop accurate models for simulating soot evolution in aircraft combustors. To investigate the effect of small scale turbulence time-scales on soot evolution, a partially-stirred reactor (PaSR) configuration is used and coupled with soot models from semi-empirical to detailed statistical models. Differences in soot property predictions including soot particle diameter and number density among the soot models are highlighted. The soot models will then be used to simulate the turbulent sooting flame in an aircraft swirl combustor to determine the large scale soot-turbulence-chemistry interactions. Highlights of this study include the differences in location of bulk soot mass production in the combustor using different soot models. A realistic aircraft combustor operating condition is simulated using a state-of-the-art minimally dissipative turbulent combustion solver and soot method of moments to investigate pressure scaling and soot evolution in different operating conditions. A separate hydrodynamic scaling is introduced to the pressure scaling, in addition to thermochemical scaling from previous studies. Finally, a Fourier analysis of soot evolution in the combustor will be discussed. A lower sooting frequency mode is found in the combustor, separate from the dominant fluid flow frequency mode that could affect statistical data collection for soot properties in turbulent sooting flame simulations.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147513/1/stchong_1.pd

Numerical Simulation

Nowadays mathematical modeling and numerical simulations play an important role in life and natural science. Numerous researchers are working in developing different methods and techniques to help understand the behavior of very complex systems, from the brain activity with real importance in medicine to the turbulent flows with important applications in physics and engineering. This book presents an overview of some models, methods, and numerical computations that are useful for the applied research scientists and mathematicians, fluid tech engineers, and postgraduate students

Biomechanical Models of Human Upper and Tracheal Airway Functionality

The respiratory tract, in other words, the airway, is the primary airflow path for several physiological activities such as coughing, breathing, and sneezing. Diseases can impact airway functionality through various means including cancer of the head and neck, Neurological disorders such as Parkinson\u27s disease, and sleep disorders and all of which are considered in this study. In this dissertation, numerical modeling techniques were used to simulate three distinct airway diseases: a weak cough leading to aspiration, upper airway patency in obstructive sleep apnea, and tongue cancer in swallow disorders. The work described in this dissertation, therefore, divided into three biomechanical models, of which fluid and particulate dynamics model of cough is the first. Cough is an airway protective mechanism, which results from a coordinated series of respiratory, laryngeal, and pharyngeal muscle activity. Patients with diminished upper airway protection often exhibit cough impairment resulting in aspiration pneumonia. Computational Fluid Dynamics (CFD) technique was used to simulate airflow and penetrant behavior in the airway geometry reconstructed from Computed Tomography (CT) images acquired from participants. The second study describes Obstructive Sleep Apnea (OSA) and the effects of dilator muscular activation on the human retro-lingual airway in OSA. Computations were performed for the inspiration stage of the breathing cycle, utilizing a fluid-structure interaction (FSI) method to couple structural deformation with airflow dynamics. The spatiotemporal deformation of the structures surrounding the airway wall was predicted and found to be in general agreement with observed changes in luminal opening and the distribution of airflow from upright to supine posture. The third study describes the effects of cancer of the tongue base on tongue motion during swallow. A three-dimensional biomechanical model was developed and used to calculate the spatiotemporal deformation of the tongue under a sequence of movements which simulate the oral stage of swallow

Automated Pattern Detection and Generalization of Building Groups

This dissertation focuses on the topic of building group generalization by considering the detection of building patterns. Generalization is an important research field in cartography, which is part of map production and the basis for the derivation of multiple representation. As one of the most important features on map, buildings occupy large amount of map space and normally have complex shape and spatial distribution, which leads to that the generalization of buildings has long been an important and challenging task. For social, architectural and geographical reasons, the buildings were built with some special rules which forms different building patterns. Building patterns are crucial structures which should be carefully considered during graphical representation and generalization. Although people can effortlessly perceive these patterns, however, building patterns are not explicitly described in building datasets. Therefore, to better support the subsequent generalization process, it is important to automatically recognize building patterns. The objective of this dissertation is to develop effective methods to detect building patterns from building groups. Based on the identified patterns, some generalization methods are proposed to fulfill the task of building generalization. The main contribution of the dissertation is described as the following five aspects: (1) The terminology and concept of building pattern has been clearly explained; a detailed and relative complete typology of building patterns has been proposed by summarizing the previous researches as well as extending by the author; (2) A stroke-mesh based method has been developed to group buildings and detect different patterns from the building groups; (3) Through the analogy between line simplification and linear building group typification, a stroke simplification based typification method has been developed aiming at solving the generalization of building groups with linear patterns; (4) A mesh-based typification method has been developed for the generalization of the building groups with grid patterns; (5) A method of extracting hierarchical skeleton structures from discrete buildings have been proposed. The extracted hierarchical skeleton structures are regarded as the representations of the global shape of the entire region, which is used to control the generalization process. With the above methods, the building patterns are detected from the building groups and the generalization of building groups are executed based on the patterns. In addition, the thesis has also discussed the drawbacks of the methods and gave the potential solutions.:Abstract I Kurzfassung III Contents V List of Figures IX List of Tables XIII List of Abbreviations XIV Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1.1 Cartographic generalization 1 1.1.2 Urban building and building patterns 1 1.1.3 Building generalization 3 1.1.4 Hierarchical property in geographical objects 3 1.2 Research objectives 4 1.3 Study area 5 1.4 Thesis structure 6 Chapter 2 State of the Art 8 2.1 Operators for building generalization 8 2.1.1 Selection 9 2.1.2 Aggregation 9 2.1.3 Simplification 10 2.1.4 Displacement 10 2.2 Researches of building grouping and pattern detection 11 2.2.1 Building grouping 11 2.2.2 Pattern detection 12 2.2.3 Problem analysis . 14 2.3 Researches of building typification 14 2.3.1 Global typification 15 2.3.2 Local typification 15 2.3.3 Comparison analysis 16 2.3.4 Problem analysis 17 2.4 Summary 17 Chapter 3 Using stroke and mesh to recognize building group patterns 18 3.1 Abstract 19 3.2 Introduction 19 3.3 Literature review 20 3.4 Building pattern typology and study area 22 3.4.1 Building pattern typology 22 3.4.2 Study area 24 3.5 Methodology 25 3.5.1 Generating and refining proximity graph 25 3.5.2 Generating stroke and mesh 29 3.5.3 Building pattern recognition 31 3.6 Experiments 33 3.6.1 Data derivation and test framework 33 3.6.2 Pattern recognition results 35 3.6.3 Evaluation 39 3.7 Discussion 40 3.7.1 Adaptation of parameters 40 3.7.2 Ambiguity of building patterns 44 3.7.3 Advantage and Limitation 45 3.8 Conclusion 46 Chapter 4 A typification method for linear building groups based on stroke simplification 47 4.1 Abstract 48 4.2 Introduction 48 4.3 Detection of linear building groups 50 4.3.1 Stroke-based detection method 50 4.3.2 Distinguishing collinear and curvilinear patterns 53 4.4 Typification method 55 4.4.1 Analogy of building typification and line simplification 55 4.4.2 Stroke generation 56 4.4.3 Stroke simplification 57 4.5 Representation of newly typified buildings 60 4.6 Experiment 63 4.6.1 Linear building group detection 63 4.6.2 Typification results 65 4.7 Discussion 66 4.7.1 Comparison of reallocating remained nodes 66 4.7.2 Comparison with classic line simplification method 67 4.7.3 Advantage 69 4.7.4 Further improvement 71 4.8 Conclusion 71 Chapter 5 A mesh-based typification method for building groups with grid patterns 73 5.1 Abstract 74 5.2 Introduction 74 5.3 Related work 75 5.4 Methodology of mesh-based typification 78 5.4.1 Grid pattern classification 78 5.4.2 Mesh generation 79 5.4.3 Triangular mesh elimination 80 5.4.4 Number and positioning of typified buildings 82 5.4.5 Representation of typified buildings 83 5.4.6 Resizing Newly Typified Buildings 85 5.5 Experiments 86 5.5.1 Data derivation 86 5.5.2 Typification results and evaluation 87 5.5.3 Comparison with official map 91 5.6 Discussion 92 5.6.1 Advantages 92 5.6.2 Further improvements 93 5.7 Conclusion 94 Chapter 6 Hierarchical extraction of skeleton structures from discrete buildings 95 6.1 Abstract 96 6.2 Introduction 96 6.3 Related work 97 6.4 Study area 99 6.5 Hierarchical extraction of skeleton structures 100 6.5.1 Proximity Graph Network (PGN) of buildings 100 6.5.2 Centrality analysis of proximity graph network 103 6.5.3 Hierarchical skeleton structures of buildings 108 6.6 Generalization application 111 6.7 Experiment and discussion 114 6.7.1 Data statement 114 6.7.2 Experimental results 115 6.7.3 Discussion 118 6.8 Conclusions 120 Chapter 7 Discussion 121 7.1 Revisiting the research problems 121 7.2 Evaluation of the presented methodology 123 7.2.1 Strengths 123 7.2.2 Limitations 125 Chapter 8 Conclusions 127 8.1 Main contributions 127 8.2 Outlook 128 8.3 Final thoughts 131 Bibliography 132 Acknowledgements 142 Publications 14

Emissions predictions in turbulent reacting industrial gas turbine combustor flows using RANS and LES methods

CFD predictions of emissions using conventional RANS methods have been shown to be inaccurate, sometimes by orders of magnitude. In recent years, deeper details of the chemistry-aerodynamics coupling in lean-premixed combustion regimes have been demanded from CFD predictions. Large Eddy Simulation (LES) of non-reacting flows provides high-fidelity predictions of flow field aerodynamics in gas turbine combustor chambers, critical for accurate emissions predictions. While LES has been validated for many simple lab combustors, there are few simulations that have used this method for practical industrial combustors at their baseload conditions. This thesis describes its application to an industrial gas turbine combustor at elevated pressures and temperatures. A well-validated commercial code, Fluent 6.3, has been used to obtain reacting and non-reacting flows that occur in this combustor geometry. The final emissions predictions were compared with rig test results