Analytical model for the 3D-RESURF effect

This paper presents an analytical model for the determination of the basic breakdown properties of three-dimensional (3D)-RESURF/CoolMOS/super junction type structures. To account for the two-dimensional (2D) effect of the 3D-RESURF action, 2D models of the electric field distribution are developed. Based on these, expressions are derived for the breakdown voltage as a function of doping concentration and physical dimensions. In addition to cases where the drift regions are fully depleted, the model developed is also applicable to situations involving drift regions which are almost depleted. Accuracy of the analytical approach is verified by comparison with numerical results obtained from the MEDICI device simulator.

Adapting data processing to compare model and experiment accurately: A discrete element model and magnetic resonance measurements of a 3d cylindrical fluidized bed

Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. © 2013 American Chemical Society.

Behaviour of cast-iron tunnel segmental joint from the 3D FE analyses and development of a new bolt-spring model

The behaviour of cast-iron tunnel segments used in London Underground tunnels was investigated using the 3-D finite element (FE) method. A numerical model of the structural details of cast-iron segmental joints such as bolts, panel and flanges was developed and its performance was validated against a set of full-scale tests. Using the verified model, the influence of structural features such as caulking groove and bolt pretension was examined for both rotational and shear loading conditions. Since such detailed modelling of bolts increases the computational time when a full scale segmental tunnel is analysed, it is proposed to replace the bolt model to a set of spring models. The parameters for the bolt-spring models, which consider the geometry and material properties of the bolt, are proposed. The performance of the combined bolt-spring and solid segmental models are evaluated against a more conventional shell-spring model. © 2014 Elsevier Ltd.

Novel fluid grid and voidage calculation techniques for a discrete element model of a 3D cylindrical fluidized bed

A discrete element model (DEM) combined with computational fluid dynamics (CFD) was developed to model particle and fluid behaviour in 3D cylindrical fluidized beds. Novel techniques were developed to (1) keep fluid cells, defined in cylindrical coordinates, at a constant volume in order to ensure the conditions for validity of the volume-averaged fluid equations were satisfied and (2) smoothly and accurately measure voidage in arbitrarily shaped fluid cells. The new technique for calculating voidage was more stable than traditional techniques, also examined in the paper, whilst remaining computationally-effective. The model was validated by quantitative comparison with experimental results from the magnetic resonance imaging of a fluidised bed analysed to give time-averaged particle velocities. Comparisons were also made between theoretical determinations of slug rise velocity in a tall bed. It was concluded that the DEM-CFD model is able to investigate aspects of the underlying physics of fluidisation not readily investigated by experiment. © 2014 The Authors.

Relative Affine Structure: Canonical Model for 3D from 2D Geometry and Applications

We propose an affine framework for perspective views, captured by a single extremely simple equation based on a viewer-centered invariant we call "relative affine structure". Via a number of corollaries of our main results we show that our framework unifies previous work --- including Euclidean, projective and affine --- in a natural and simple way, and introduces new, extremely simple, algorithms for the tasks of reconstruction from multiple views, recognition by alignment, and certain image coding applications.

Inferring 3D Structure with a Statistical Image-Based Shape Model

We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure'' model. The 3D shape of a class of objects may be represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes can then be estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We augment the shape model to incorporate structural features of interest; novel examples with missing structure parameters may then be reconstructed to obtain estimates of these parameters. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a dataset of thousands of pedestrian images generated from a synthetic model, we can perform accurate inference of the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

A Laminar Cortical Model for 3D Perception of Slanted and Curved Surfaces and of 2D Images: Developement, attention, and Bistability

A model of laminar visual cortical dynamics proposes how 3D boundary and surface representations of slated and curved 3D objects and 2D images arise. The 3D boundary representations emerge from interactions between non-classical horizontal receptive field interactions with intracorticcal and intercortical feedback circuits. Such non-classical interactions contextually disambiguate classical receptive field responses to ambiguous visual cues using cells that are sensitive to angles and disparity gradients with cortical areas V1 and V2. These cells are all variants of bipole grouping cells. Model simulations show how horizontal connections can develop selectively to angles, how slanted surfaces can activate 3D boundary representations that are sensitive to angles and disparity gradients, how 3D filling-in occurs across slanted surfaces, how a 2D Necker cube image can be represented in 3D, and how bistable Necker cuber percepts occur. The model also explains data about slant aftereffects and 3D neon color spreading. It shows how habituative transmitters that help to control developement also help to trigger bistable 3D percepts and slant aftereffects, and how attention can influence which of these percepts is perceived by propogating along some object boundaries.

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

Analytical Elastic Stiffness Model for 3D Woven Orthogonal Interlock Composites

This research presents the development of an analytical model to predict the elastic stiffness performance of orthogonal interlock bound 3D woven composites as a consequence of altering the weaving parameters and constituent material types. The present approach formulates expressions at the micro level with the aim of calculating more representative volume fractions of a group of elements to the layer. The rationale in representing the volume fractions within the unit cell more accurately was to improve the elastic stiffness predictions compared to existing analytical modelling approaches. The models developed in this work show good agreement between experimental data and improvement on existing predicted values by models published in literature.

FROM LINE-DRAWINGS TO IMPRESSIONS OF 3D OBJECTS - DEVELOPING A MODEL TO ACCOUNT FOR THE SHAPES THAT PEOPLE SEE

The interpretations people attach to line drawings reflect shape-related processes in human vision. Their divergences from expectations embodied in related machine vision traditions are summarized, and used to suggest how human vision decomposes the task of interpretation. A model called IO implements this idea. It first identifies geometrically regular, local fragments. Initial decisions fix edge orientations, and this information constrains decisions about other properties. Relations between fragments are explored, beginning with weak consistency checks and moving to fuller ones. IO's output captures multiple distinctive characteristics of human performance, and it suggests steady progress towards understanding shape-related visual processes is possible.

Single crystal CVD diamond growth strategy by the use of a 3D geometrical model: Growth on (113) oriented substrates

The quality of single crystal diamond obtained by microwave CVD processes has been drastically improved in the last 5 years thanks to surface pretreatment of the substrates [A. Tallaire, J. Achard, F. Silva, R.S. Sussmann, A. Gicquel, E. Rzepka, Physica Status Solidi (A) 201, 2419-2424 (2004); G. Bogdan, M. Nesladek, J. D'Haen, J. Maes, V.V. Moshchalkov, K. Haenen, M. D'Olieslaeger, Physica Status Solidi (A) 202, 2066-2072 (2005); M. Yamamoto, T. Teraji, T. Ito, Journal of Crystal Growth 285, 130-136 (2005)]. Additionally, recent results have unambiguously shown the occurrence of (110) faces on crystal edges and (113) faces on crystal corners [F. Silva, J. Achard, X. Bonnin, A. Michau, A. Tallaire, O. Brinza, A. Gicquel, Physica Status Solidi (A) 203, 3049-3055 (2006)]. We have developed a 3D geometrical growth model to account for the final crystal morphology. The basic parameters of this growth model are the relative displacement speeds of (111), (110) and (113) faces normalized to that of the (100) faces, respectively alpha, beta, and gamma. This model predicts both the final equilibrium shape of the crystal (i.e. after infinite growth time) and the crystal morphology as a function of alpha, beta, gamma, and deposition time.

An optimized operating point, deduced from the model, has been validated experimentally by measuring the growth rate in (100), (111), (110), and (113) orientations. Furthermore, the evolution of alpha, beta, gamma as a function of methane concentration in the gas discharge has been established. From these results, crystal growth strategies can be proposed in order, for example, to enlarge the deposition area. In particular, we will show, using the growth model, that the only possibility to significantly increase the deposition area is, for our growth conditions, to use a (113) oriented substrate. A comparison between the grown crystal and the model results will be discussed and characterizations of the grown film (Photoluminescence spectroscopy, EPR, SEM) will be presented. (C) 2008 Elsevier B.V. All rights reserved.

3D deflagration simulations leaving bound remnants:A model for 2002cx-like Type Ia supernovae

2002cx-like supernovae are a sub-class of sub-luminous Type Ia supernovae (SNe). Their light curves and spectra are characterized by distinct features that indicate strong mixing of the explosion ejecta. Pure turbulent deflagrations have been shown to produce such mixed ejecta. Here, we present hydrodynamics, nucleosynthesis and radiative-transfer calculations for a 3D full-star deflagration of a Chandrasekhar-mass white dwarf. Our model is able to reproduce the characteristic observational features of SN 2005hk (a prototypical 2002cx-like supernova), not only in the optical, but also in the near-infrared. For that purpose we present, for the first time, five near-infrared spectra of SN 2005hk from -0.2 to 26.6 d with respect to B-band maximum. Since our model burns only small parts of the initial white dwarf, it fails to completely unbind the white dwarf and leaves behind a bound remnant of ~1.03Mconsisting mainly of unburned carbon and oxygen, but also enriched by some amount of intermediate-mass and iron-group elements from the explosion products that fall back on the remnant.We discuss possibilities for detecting this bound remnant and how it might influence the late-time observables of 2002cx-like SNe. © 2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.

3D Morphable Model Construction for Robust Ear and Face Recognition

Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online.