scholarly journals Analytic Form Fitting in Poor Triangular Meshes

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 304
Author(s):  
Cristian Rendon-Cardona ◽  
Jorge Correa ◽  
Diego A. Acosta ◽  
Oscar Ruiz-Salguero
Keyword(s):  
Real Time ◽  
Computer Aided Design ◽  
Analytic Form ◽  
Boundary Representation ◽  
Triangular Meshes ◽  
Strong Point ◽  
Form Identification ◽  
Fitting In ◽  
Cylinders And Spheres ◽  
Aided Design

Fitting of analytic forms to point or triangle sets is central to computer-aided design, manufacturing, reverse engineering, dimensional control, etc. The existing approaches for this fitting assume an input of statistically strong point or triangle sets. In contrast, this manuscript reports the design (and industrial application) of fitting algorithms whose inputs are specifically poor triangular meshes. The analytic forms currently addressed are planes, cones, cylinders and spheres. Our algorithm also extracts the support submesh responsible for the analytic primitive. We implement spatial hashing and boundary representation for a preprocessing sequence. When the submesh supporting the analytic form holds strict C0-continuity at its border, submesh extraction is independent of fitting, and our algorithm is a real-time one. Otherwise, segmentation and fitting are codependent and our algorithm, albeit correct in the analytic form identification, cannot perform in real-time.

scholarly journals An isogeometric b-rep mortar-based mapping method for non-matching grids in fluid-structure interaction

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Andreas Apostolatos ◽  
Altuğ Emiroğlu ◽  
Shahrokh Shayegan ◽  
Fabien Péan ◽  
Kai-Uwe Bletzinger ◽  
...  
Keyword(s):  
Computer Aided Design ◽  
Fluid Structure Interaction ◽  
Mapping Method ◽  
Boundary Representation ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Discrete Surface ◽  
Cad Models ◽  
Volume Method ◽  
Aided Design

AbstractIn this study the isogeometric B-Rep mortar-based mapping method for geometry models stemming directly from Computer-Aided Design (CAD) is systematically augmented and applied to partitioned Fluid-Structure Interaction (FSI) simulations. Thus, the newly proposed methodology is applied to geometries described by their Boundary Representation (B-Rep) in terms of trimmed multipatch Non-Uniform Rational B-Spline (NURBS) discretizations as standard in modern CAD. The proposed isogeometric B-Rep mortar-based mapping method is herein extended for the transformation of fields between a B-Rep model and a low order discrete surface representation of the geometry which typically results when the Finite Volume Method (FVM) or the Finite Element Method (FEM) are employed. This enables the transformation of such fields as tractions and displacements along the FSI interface when Isogeometric B-Rep Analysis (IBRA) is used for the structural discretization and the FVM is used for the fluid discretization. The latter allows for diverse discretization schemes between the structural and the fluid Boundary Value Problem (BVP), taking into consideration the special properties of each BVP separately while the constraints along the FSI interface are satisfied in an iterative manner within partitioned FSI. The proposed methodology can be exploited in FSI problems with an IBRA structural discretization or to FSI problems with a standard FEM structural discretization in the frame of the Exact Coupling Layer (ECL) where the interface fields are smoothed using the underlying B-Rep parametrization, thus taking advantage of the smoothness that the NURBS basis functions offer. All new developments are systematically investigated and demonstrated by FSI problems with lightweight structures whereby the underlying geometric parametrizations are directly taken from real-world CAD models, thus extending IBRA into coupled problems of the FSI type.

scholarly journals Transformation of the Innovative and Sustainable Supply Chain with Upcoming Real-Time Fashion Systems

2021 ◽  
Vol 13 (3) ◽  
pp. 1081
Author(s):  
Yoon Kyung Lee
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Computer Aided Design ◽  
Production Systems ◽  
Fashion Industry ◽  
Sustainable Supply Chain ◽  
Information Communication ◽  
Manufacturing Planning ◽  
Fashion Products ◽  
Aided Design

Technologies that are ready-to-use and adaptable in real time to customers’ individual needs are influencing the supply chain of the future. This study proposes a supply chain framework for an innovative and sustainable real-time fashion system (RTFS) between enterprises, designers, and consumers in 3D clothing production systems, using information communication technology, artificial intelligence (AI), and virtual environments. In particular, the RTFS is targeted at customers actively involved in product purchasing, personalising, co-designing, and manufacturing planning. The fashion industry is oriented towards 3D services as a service model, owing to the automation and democratisation of product customisation and personalisation processes. Furthermore, AI offers referral services to prosumers or/and customers and companies, and proposes individual designs with perfect styles and measurements using new 3D computer aided design and AI-based product design technologies for fashion and design companies and customers. Consequently, 3D fashion products in the RTFS supply chain are entirely digital, saving time and money with sampling and tracking capabilities, secured, and trusted with personalised service delivery.

scholarly journals Body Bias Optimization for Real-Time Systems

2020 ◽  
Vol 10 (1) ◽  
pp. 8
Author(s):  
Carlos C. Cortes Torres ◽  
Ryota Yasudo ◽  
Hideharu Amano
Keyword(s):  
Real Time ◽  
Computer Aided Design ◽  
Optimization Method ◽  
Design Guidelines ◽  
Real Time Systems ◽  
Total Energy Consumption ◽  
Aided Design ◽  
Time Systems ◽  
Parameter Constraints ◽  
Body Bias

The energy of real-time systems for embedded usage needs to be efficient without affecting the system’s ability to meet task deadlines. Dynamic body bias (BB) scaling is a promising approach to managing leakage energy and operational speed, especially for system-on-insulator devices. However, traditional energy models cannot deal with the overhead of adjusting the BB voltage; thus, the models are not accurate. This paper presents a more accurate model for calculating energy overhead using an analytical double exponential expression for dynamic BB scaling and an optimization method based on nonlinear programming with consideration of the real-chip parameter constraints. The use of the proposed model resulted in an energy reduction of about 32% at lower frequencies in comparison with the conventional model. Moreover, the energy overhead was reduced to approximately 14% of the total energy consumption. This methodology provides a framework and design guidelines for real-time systems and computer-aided design.

Applied NURBS on the Research of Interactive Curved Hull Computer Aided Design

2013 ◽  
Vol 328 ◽  
pp. 149-153
Author(s):  
Zhi Hui Dong ◽  
Duan Feng Han ◽  
Li Hao Yuan
Keyword(s):  
Real Time ◽  
Computer Aided Design ◽  
Tree Structure ◽  
Parameter Adjustment ◽  
The Real ◽  
Geometric Data ◽  
Computer Aided ◽  
Aided Design

Based on NURBS algorithm, this paper processes and renders curved hull in OpenGL platform, and applies Tree-Structure to manage all the real-time geometric data. And what is more, extend the functions into curved ratio check, the model's parameter adjustment and output etc. At last, results of instances will be given to illuminate the effects.

Interval Method for Interrogation of Implicit Solid Models

2000 ◽  
Author(s):  
Jack Chang ◽  
Mark Ganter ◽  
Duane Storti
Keyword(s):  
Computer Aided Design ◽  
Boundary Representation ◽  
Free Form ◽  
Solid Models ◽  
Cad Cam ◽  
Implicit Modeling ◽  
Manufacturing Applications ◽  
Determine Surface Area ◽  
Implicit Solid ◽  
Aided Design

Abstract Computer-aided design/manufacturing (CAD/CAM) systems intended to support automated design and manufacturing applications such as shape generation and solid free-form fabrication (SFF) must provide not only methods for creating and editing models of objects to be manufactured, but also methods for interrogating the models. Interrogation refers to any process that derives information from the model. Typical interrogation tasks include determine surface area, volume or inertial properties, computing surface points and normals for rendering, and computing slice descriptions for SFF. While currently available commercial modeling systems generally employ a boundary representation (B-rep) implementation of solid modeling, research efforts have considered implicit modeling schemes as a potential source of improved robustness. Implicit implementations are available for a broad range of modeling operations, but interrogation operations have been widely considered too costly for many applications. This paper describes a method based on interval analysis for interrogating implicit solid models that aims at achieving both robustness and efficiency.

Orthogonal Distance Fields Representation for Machine-Learning Based Manufacturability Analysis

2020 ◽  
Author(s):  
Aditya Balu ◽  
Sambit Ghadai ◽  
Soumik Sarkar ◽  
Adarsh Krishnamurthy
Keyword(s):  
Machine Learning ◽  
Computer Aided Design ◽  
Boundary Representation ◽  
Engineering Product ◽  
Distance Fields ◽  
Computer Aided ◽  
Cad Models ◽  
Product Design Process ◽  
3D Cnn ◽  
Aided Design

Abstract Computer-aided Design for Manufacturing (DFM) systems play an essential role in reducing the time taken for product development by providing manufacturability feedback to the designer before the manufacturing phase. Traditionally, DFM rules are hand-crafted and used to accelerate the engineering product design process by integrating manufacturability analysis during design. Recently, the feasibility of using a machine learning-based DFM tool in intelligently applying the DFM rules have been studied. These tools use a voxelized representation of the design and then use a 3D-Convolutional Neural Network (3D-CNN), to provide manufacturability feedback. Although these frameworks work effectively, there are some limitations to the voxelized representation of the design. In this paper, we introduce a new representation of the computer-aided design (CAD) model using orthogonal distance fields (ODF). We provide a GPU-accelerated algorithm to convert standard boundary representation (B-rep) CAD models into ODF representation. Using the ODF representation, we build a machine learning framework, similar to earlier approaches, to create a machine learning-based DFM system to provide manufacturability feedback. As proof of concept, we apply this framework to assess the manufacturability of drilled holes. The framework has an accuracy of more than 84% correctly classifying the manufacturable and non-manufacturable models using the new representation.

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