An interactive mesh generation environment for geometry-based simulations. Progress updated

We presented an overview of an interactive mesh generation environment in our previous work that it is being developed in the Laboratori de Càlcul Numèric (LaCàN). We started the development of the software in order to unify available legacy code, new developments and research algorithms in only one mesh generation package. This paper presents an update to the last environment overview after significant implementation and conceptual development. We provide a brief summary of: New features, as submapping and data output suitable for geometry-based methods as; current developments, as GUI improvement and 3D modelling tools; and future features, such as the command interpreter. Finally, we conclude that chosen mesh generation paradigm and software engineering concepts have allowed us to improve and scale the environment since last revision

Management, design and developement of a mesh generation environment using open source software

In this paper we present an object oriented implementation of a general-purpose mesh generation environment for geometry-based simulations. The aim of this application is to unify available legacy code and new research algorithms in only one mesh generation suite. We focus in two aspects that can be of the general interest for managers, designers and developers of similar projects. On the one hand, we analyze the software engineering practices that we have followed in the management and development process. In addition, we detail and discuss the Open Source tools and libraries that we have used. On the other hand, we discuss the design and the data structure of the environment. In particular, we first summarize the topological and geometrical representation. Second, we detail our implementation of the hierarchical mesh generation structure. Third we present our design to mediate collaboration between classes. Finally, we present some of the mesh generation features to show the capabilities of the environment

Learning to Reconstruct People in Clothing from a Single RGB Camera

We present a learning-based model to infer the personalized 3D shape of people from a few frames (1-8) of a monocular video in which the person is moving, in less than 10 seconds with a reconstruction accuracy of 5mm. Our model learns to predict the parameters of a statistical body model and instance displacements that add clothing and hair to the shape. The model achieves fast and accurate predictions based on two key design choices. First, by predicting shape in a canonical T-pose space, the network learns to encode the images of the person into pose-invariant latent codes, where the information is fused. Second, based on the observation that feed-forward predictions are fast but do not always align with the input images, we predict using both, bottom-up and top-down streams (one per view) allowing information to flow in both directions. Learning relies only on synthetic 3D data. Once learned, the model can take a variable number of frames as input, and is able to reconstruct shapes even from a single image with an accuracy of 6mm. Results on 3 different datasets demonstrate the efficacy and accuracy of our approach

Development of an Efficient CFD Model for Nuclear Thermal Thrust Chamber Assembly Design

The objective of this effort is to develop an efficient and accurate computational methodology to predict both detailed thermo-fluid environments and global characteristics of the internal ballistics for a hypothetical solid-core nuclear thermal thrust chamber assembly (NTTCA). Several numerical and multi-physics thermo-fluid models, such as real fluid, chemically reacting, turbulence, conjugate heat transfer, porosity, and power generation, were incorporated into an unstructured-grid, pressure-based computational fluid dynamics solver as the underlying computational methodology. The numerical simulations of detailed thermo-fluid environment of a single flow element provide a mechanism to estimate the thermal stress and possible occurrence of the mid-section corrosion of the solid core. In addition, the numerical results of the detailed simulation were employed to fine tune the porosity model mimic the pressure drop and thermal load of the coolant flow through a single flow element. The use of the tuned porosity model enables an efficient simulation of the entire NTTCA system, and evaluating its performance during the design cycle

CLASSIFICATION OF NEUROANATOMICAL STRUCTURES BASED ON NON-EUCLIDEAN GEOMETRIC OBJECT PROPERTIES

Studying the observed morphological differences in neuroanatomical structures between individuals with neurodevelopmental disorders and a control group of typically developing individuals has been an important objective. Researchers study the differences with two goals: to assist an accurate diagnosis of the disease and to gain insights into underlying mechanisms of the disease that cause such changes. Shape classification is commonly utilized in such studies. An effective classification is difficult because it requires 1) a choice of an object model that can provide rich geometric object properties (GOPs) relevant for a given classification task, and 2) a choice of a statistical classification method that accounts for the non-Euclidean nature of GOPs. I lay out my methodological contributions to address the aforementioned challenges in the context of early diagnosis and detection of Autism Spectrum Disorder (ASD) in infants based on shapes of hippocampi and caudate nuclei; morphological deviations in these structures between individuals with ASD and typically developing individuals have been reported in the literature. These contributions respectively lead to 1) an effective modeling of shapes of objects of interest and 2) an effective classification. As the first contribution for modeling shapes of objects, I propose a method to obtain a set of skeletal models called s-reps from a set of 3D objects. First, the method iteratively deforms the object surface via Mean Curvature Flow (MCF) until the deformed surface is approximately ellipsoidal. Then, an s-rep of the approximate ellipsoid is obtained analytically. Finally, the ellipsoid s-rep is deformed via a series of inverse MCF transformations. The method has two important properties: 1) it is fully automatic, and 2) it yields a set of s-reps with good correspondence across the set. The method is shown effective in generating a set of s-reps for a few neuroanatomical structures. As the second contribution with respect to modeling shapes of objects, I introduce an extension to the current s-rep for representing an object with a narrowing sharp tail. This includes a spoke interpolation method for interpolating a discrete s-rep of an object with a narrowing sharp tail into a continuous object. This extension is necessary for representing surface geometry of objects whose boundary has a singular point. I demonstrate that this extension allows appropriate surface modeling of a narrowing sharp tail region of the caudate nucleus. In addition, I show that the extension is beneficial in classifying autistic and non-autistic infants at high risk of ASD based on shapes of caudate nuclei. As the first contribution with respect to statistical methods, I propose a novel shape classification framework that uses the s-rep to capture rich localized geometric descriptions of an object, a statistical method called Principal Nested Spheres (PNS) analysis to handle the non-Euclidean s-rep GOPs, and a classification method called Distance Weighted Discrimination (DWD). I evaluate the effectiveness of the proposed method in classifying autistic and non-autistic infants based on either hippocampal shapes or caudate shapes in terms of the Area Under the ROC curve (AUC). In addition, I show that the proposed method is superior to commonly used shape classification methods in the literature. As my final methodological contribution, I extend the proposed shape classification method to perform the classifcation task based on temporal shape differences. DWD learns a class separation direction based on the temporal shape differences that are obtained by taking differences of the temporal pair of Euclideanized s-reps. In the context of early diagnosis and detection of ASD in young infants, the proposed temporal shape difference classification produces some interesting results; the temporal differences in shapes of hippocampi and caudate nuclei do not seem to be as predictive as the cross-sectional shape of these structures alone.Doctor of Philosoph

POINT CLOUD EXPLOITATION FOR STRUCTURAL MODELING AND ANALYSIS: A RELIABLE WORKFLOW

none4noThe digitization and geometric knowledge of the historical built heritage is currently based on point cloud, that rarely or only partially is used as digital twin for structural analysis. The present work deals with historical artefacts survey, with particular reference to masonry structures, aimed to their structural analysis and assessment. In detail, the study proposes a methodology capable of employing semi-directly the original data obtained from the 3D digital survey for the generation of a Finite Element Model (FEM), used for structural analysis of masonry buildings. The methodology described presents a reliable workflow with twofold purpose: the improvement of the transformation process of the point cloud in solid and subsequently obtain a high-quality and detailed model for structural analyses. Through the application of the methodology to a case study, the method consistency was assessed, regarding the smoothness of the whole procedure and the dynamic characterization of the Finite Element Model. The main improvement in respect with similar or our previous workflows is obtained by the introduction of the retopology in data processing, allowing the transformation of the raw data into a solid model with optimal balancing between Level of Detail (LOD) and computational weight. Another significant aspect of the optimized process is undoubtedly the possibility of faithfully respecting the semantics of the structure, leading to the discretization of the model into different parts depending on the materials. This work may represent an excellent reference for the study of masonry artefacts belonging to the existing historical heritage, starting from surveys and with the purpose to structural and seismic evaluations, in the general framework of knowledge-based preservation of heritage.openLucidi, A.; Giordano, E.; Clementi, F.; Quattrini, R.Lucidi, A.; Giordano, E.; Clementi, F.; Quattrini, R

A survey on 3D CAD model quality assurance and testing

[EN] A new taxonomy of issues related to CAD model quality is presented, which distinguishes between explicit and procedural models. For each type of model, morphologic, syntactic, and semantic errors are characterized. The taxonomy was validated successfully when used to classify quality testing tools, which are aimed at detecting and repairing data errors that may affect the simplification, interoperability, and reusability of CAD models. The study shows that low semantic level errors that hamper simplification are reasonably covered in explicit representations, although many CAD quality testers are still unaffordable for Small and Medium Enterprises, both in terms of cost and training time. Interoperability has been reasonably solved by standards like STEP AP 203 and AP214, but model reusability is not feasible in explicit representations. Procedural representations are promising, as interactive modeling editors automatically prevent most morphologic errors derived from unsuitable modeling strategies. Interoperability problems between procedural representations are expected to decrease dramatically with STEP AP242. Higher semantic aspects of quality such as assurance of design intent, however, are hardly supported by current CAD quality testers. (C) 2016 Elsevier Ltd. All rights reserved.This work was supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund, through the ANNOTA project (Ref. TIN2013-46036-C3-1-R).González-Lluch, C.; Company, P.; Contero, M.; Camba, J.; Plumed, R. (2017). A survey on 3D CAD model quality assurance and testing. Computer-Aided Design. 83:64-79. https://doi.org/10.1016/j.cad.2016.10.003S64798

Concurrent Design and Manufacturing for Mechanical Systems

The conventional product development process employs a design-build-break philosophy. The sequentially executed product development process often results in a prolonged lead-time and an elevated product cost. The proposed concurrent design and manu facturing (CDM) paradigm employs physics-based computational methods together with computer graphics techniques for product de sign. This proposed approach employs Virtual Prototyping (VP) technology to support a cross-functional team in analyzing product per formance, reliability, and manufacturing cost early in the product development stage; and in conducting quantitative trade-off for design decision making. Physical prototypes of the product design are then produced using Rapid Prototyping (RP) technique primarily for de sign verification purposes. The proposed CDM approach holds potential for shortening the overall product development cycle, improving product quality, and reducing product cost. A software tool environment that supports CDM for mechanical systems is being built at the Concurrent Design and Manufacturing Research Laboratory (http://cdm.ou.edu) at the University of Oklahoma. A snapshot of the envi ronment is illustrated using a two-stroke engine example. This paper presents three unique concepts and methods for product develop ment : (1) bringing product performance, quality, and manufacturing cost together in early design stage for design considerations, (2) supporting design decision-making through a quantitative approach, and (3) incorporating rapid prototyping for design verification through physical prototypes.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline