Local bisection for conformal refinement of unstructured 4D simplicial meshes

We present a conformal bisection procedure for local refinement of 4D unstructured simplicial meshes with bounded minimum shape quality. Specifically, we propose a recursive refine-to-conformity procedure in two stages, based on marking bisection edges on different priority levels and defining specific refinement templates. Two successive applications of the first stage ensure that any 4D unstructured mesh can be conformingly refined. In the second stage, the successive refinements lead to a cycle in the number of generated similarity classes and thus, we can ensure a bound over the minimum shape quality. In the examples, we check that after successive refinement the mesh quality does not degenerate. Moreover, we refine a 4D unstructured mesh and a space-time mesh (3D + 1D) representation of a moving object

NC-G-SIM: A Parameterized Generic Simulator for 2D-Mesh, 3D-Mesh

As chip density keeps doubling during each course of generation, the use of NoC has become an integral part of modern microprocessors and a very prevalent architectural feature of all types of SoCs. To meet the ever expanding communication challenges, diverse and novel NoC solutions are being developed which rely on accurate modeling and simulations to evaluate the impact and analyze their performances. Consequently, this aggravates the need to rely on simulation tools to probe and optimize these NoC architectures. In this work, we present NC-G-SIM (Network on Chip-Generic-SIMulator), a highly flexible, modular, cycle-accurate, configurable simulator for NoCs. To make NC-G-SIM suitable for advanced NoC exploration, it is made highly generic that supports extensive range of cores in any kind of topology whether 2D, 3D or irregular. Simulation results have been evaluated in terms of latencies, throughput and the amount of energy consumed during the simulation period at different levels

Noise radiated by an open cavity at low Mach number: Effect of the cavity oscillation mode

The present work focuses on the study of noise generation and radiation of an infinite open three-dimensional cavity at low Mach number with laminar upstream conditions that is of interest to understand noise generation mechanisms in wall-bounded separated flows. A particular feature of this configuration is the oscillatory mode: shear layer mode or wake mode. For the parameters considered in the present study it is seen that while in shear layer mode the flow shows a two-dimensional behavior, in the wake mode the flow is three-dimensional, resulting in significantly different sound sources. The influence of the acoustic feedback mechanism in the shear layer mode has also been investigated comparing the results between different momentum thickness values at the cavity inlet. This paper presents results of sound radiated by a three-dimensional infinite open cavity with aspect ratio L/D = 4 at Reynolds number based on the cavity depth of ReD = 1500 and Mach number of M = 0.15, both for shear layer (L/θ = 67) and wake (L/θ = 84) oscillation modes. To do so, Curle integral evaluated as a post-process of an incompressible solution will be used. The results are compared with the resulting Curle post-process of a two-dimensional incompressible simulationPeer ReviewedPostprint (author's final draft

Thin shell morphology in the circumstellar medium of massive binaries

We investigate the morphology of the collision front between the stellar winds of binary components in two long-period binary systems, one consisting of a hydrogen rich Wolf-Rayet star (WNL) and an O-star and the other of a Luminous Blue Variable (LBV) and an O-star. Specifically, we follow the development and evolution of instabilities that form in such a shell, if it is sufficiently compressed, due to both the wind interaction and the orbital motion. We use MPI-AMRVAC to time-integrate the equations of hydrodynamics, combined with optically thin radiative cooling, on an adaptive mesh 3D grid. Using parameters for generic binary systems, we simulate the interaction between the winds of the two stars. The WNL+O star binary shows a typical example of an adiabatic wind collision. The resulting shell is thick and smooth, showing no instabilities. On the other hand, the shell created by the collision of the O star wind with the LBV wind, combined with the orbital motion of the binary components, is susceptible to thin shell instabilities, which create a highly structured morphology. We identify the nature of the instabilities as both linear and non-linear thin-shell instabilities, with distinct differences between the leading and the trailing parts of the collision front. We also find that for binaries containing a star with a (relatively) slow wind, the global shape of the shell is determined more by the slow wind velocity and the orbital motion of the binary, than the ram pressure balance between the two winds. The interaction between massive binary winds needs further parametric exploration, to identify the role and dynamical importance of multiple instabilities at the collision front, as shown here for an LBV+O star system.Comment: 10 pages, 13 figures. Accepted for publication in A&

Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation

Direct prediction of 3D body pose and shape remains a challenge even for highly parameterized deep learning models. Mapping from the 2D image space to the prediction space is difficult: perspective ambiguities make the loss function noisy and training data is scarce. In this paper, we propose a novel approach (Neural Body Fitting (NBF)). It integrates a statistical body model within a CNN, leveraging reliable bottom-up semantic body part segmentation and robust top-down body model constraints. NBF is fully differentiable and can be trained using 2D and 3D annotations. In detailed experiments, we analyze how the components of our model affect performance, especially the use of part segmentations as an explicit intermediate representation, and present a robust, efficiently trainable framework for 3D human pose estimation from 2D images with competitive results on standard benchmarks. Code will be made available at http://github.com/mohomran/neural_body_fittingComment: 3DV 201

Innovative strategies for 3D visualisation using photogrammetry and 3D scanning for mobile phones

3D model generation through Photogrammetry is a modern overlay of digital information representing real world objects in a virtual world. The immediate scope of this study aims at generating 3D models using imagery and overcoming the challenge of acquiring accurate 3D meshes. This research aims to achieve optimised ways to document raw 3D representations of real life objects and then converting them into retopologised, textured usable data through mobile phones. Augmented Reality (AR) is a projected combination of real and virtual objects. A lot of work is done to create market dependant AR applications so customers can view products before purchasing them. The need is to develop a product independent photogrammetry to AR pipeline which is freely available to create independent 3D Augmented models. Although for the particulars of this research paper, the aim would be to compare and analyse different open source SDK’s and libraries for developing optimised 3D Mesh using Photogrammetry/3D Scanning which will contribute as a main skeleton to the 3D-AR pipeline. Natural disasters, global political crisis, terrorist attacks and other catastrophes have led researchers worldwide to capture monuments using photogrammetry and laser scans. Some of these objects of “global importance” are processed by companies including CyArk (Cyber Archives) and UNESCO’s World Heritage Centre, who work against time to preserve these historical monuments, before they are damaged or in some cases completely destroyed. The need is to question the significance of preserving objects and monuments which might be of value locally to a city or town. What is done to preserve those objects? This research would develop pipelines for collecting and processing 3D data so the local communities could contribute towards restoring endangered sites and objects using their smartphones and making these objects available to be viewed in location based AR. There exist some companies which charge relatively large amounts of money for local scanning projects. This research would contribute as a non-profitable project which could be later used in school curriculums, visitor attractions and historical preservation organisations all over the globe at no cost. The scope isn’t limited to furniture, museums or marketing, but could be used for personal digital archiving as well. This research will capture and process virtual objects using Mobile Phones comparing methodologies used in Computer Vision design from data conversion on Mobile phones to 3D generation, texturing and retopologising. The outcomes of this research will be used as input for generating AR which is application independent of any industry or product