Quantitative control of idealized analysis models of thin designs

When preparing a design model for engineering analysis, model idealization is often used, where defeaturing, and/or local dimension reduction of thin regions, are carried out. This simplifies the analysis, but quantitative estimates of the idealization error, the analysis error caused by this idealization, are necessary if the results are to be of practical use. The paper focuses on a posteriori estimation of such idealization error, via both a theoretical analysis and practical algorithms. Our approach can compute bounds for the errors induced by dimension reduction, defeaturing or both in combination. Performance of our error estimate is demonstrated using examples

Error estimation for simplifications of electrostatic models

Based on a posteriori error estimation a method to bound the error induced by simplifying the geometry of a model is presented. Error here refers to the solution of a partial differential equation and a specific quantity of interest derived from it. Geometry simplification specifically refers to replacing CAD model features with simpler shapes. The simplification error estimate helps to determine whether a feature can be removed from the model by indicating how much the simplification affects the physical properties of the model as measured by a quantity of interest. The approach in general can also be extended to other problems governed by linear elliptic equations. Strict bounds for the error are proven for errors expressed in the energy norm. The approach relies on the Constitutive Relation Error to enable practically useful and computationally affordable bounds for error measures in the energy error norm. All methodologies are demonstrated for a second order elliptic partial differential equation for electrostatic problems. Finite element simplification error estimation code is developed to calculate the simplification error numerically. Numerical experiments for some geometric models of capacitors show satisfactory results for the simplification error bounds for a range of different deafeaturing cases and a quantity of interest, linear in the solution of the electrostatic partial differential equation. Overall the numerically calculated bounds are always valid, but are more or less accurate depending on the type of feature and its simplification. In particular larger errors may be overestimated, while good estimates for small errors can be achieved. This makes the bound overall suitable to decide whether simplifying a feature is acceptable or not

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

Generalizing the advancing front method to composite surfaces in the context of meshing constraints topology

International audienceBeing able to automatically mesh composite geometry is an important issue in the context of CAD-FEA integration. In some specific contexts of this integration, such as using virtual topology or meshing constraints topology (MCT), it is even a key requirement. In this paper, we present a new approach to automatic mesh generation over composite geometry. The proposed mesh generation approach is based on a generalization of the advancing front method (AFM) over curved surfaces. The adaptation of the AFM to composite faces (composed of multiple boundary representation (B-Rep) faces) involves the computation of complex paths along these B-Rep faces, on which progression of the advancing front is based. Each mesh segment or mesh triangle generated through this progression on composite geometry is likely to lie on multiple B-Rep faces and consequently, it is likely to be associated with a composite definition across multiple parametric spaces. Collision tests between new front segments and existing mesh elements also require specific and significant adaptations of the AFM, since a given front segment is also likely to lie on multiple B-Rep faces. This new mesh generation approach is presented in the context of MCT, which requires being able to handle composite geometry along with non-manifold boundary configurations, such as edges and vertices lying in the interior domain of B-Rep faces

PHYSICS-AWARE MODEL SIMPLIFICATION FOR INTERACTIVE VIRTUAL ENVIRONMENTS

Rigid body simulation is an integral part of Virtual Environments (VE) for autonomous planning, training, and design tasks. The underlying physics-based simulation of VE must be accurate and computationally fast enough for the intended application, which unfortunately are conflicting requirements. Two ways to perform fast and high fidelity physics-based simulation are: (1) model simplification, and (2) parallel computation. Model simplification can be used to allow simulation at an interactive rate while introducing an acceptable level of error. Currently, manual model simplification is the most common way of performing simulation speedup but it is time consuming. Hence, in order to reduce the development time of VEs, automated model simplification is needed. The dissertation presents an automated model simplification approach based on geometric reasoning, spatial decomposition, and temporal coherence. Geometric reasoning is used to develop an accessibility based algorithm for removing portions of geometric models that do not play any role in rigid body to rigid body interaction simulation. Removing such inaccessible portions of the interacting rigid body models has no influence on the simulation accuracy but reduces computation time significantly. Spatial decomposition is used to develop a clustering algorithm that reduces the number of fluid pressure computations resulting in significant speedup of rigid body and fluid interaction simulation. Temporal coherence algorithm reuses the computed force values from rigid body to fluid interaction based on the coherence of fluid surrounding the rigid body. The simulations are further sped up by performing computing on graphics processing unit (GPU). The dissertation also presents the issues pertaining to the development of parallel algorithms for rigid body simulations both on multi-core processors and GPU. The developed algorithms have enabled real-time, high fidelity, six degrees of freedom, and time domain simulation of unmanned sea surface vehicles (USSV) and can be used for autonomous motion planning, tele-operation, and learning from demonstration applications

Engineering analysis error estimation when removing finite-sized features in nonlinear elliptic problems

The paper provides novel approaches for a posteriori estimation of goal-oriented engineering analysis error caused by removing finite-sized negative features from a complex model, in the case of analysis of nonlinear elliptic physical phenomena. The features may lie within the model’s interior or along its boundary, and may be constrained with either Neumann or Dirichlet boundary conditions. The main use is for deciding whether detail design features can be removed from a model, to simplify meshing and engineering analysis, without unduly affecting analysis results. Error estimates are found using adjoint theory. Using a rigorous mathematical derivation, the error is first reformulated as a local quantity defined over the boundary of the feature to be suppressed, via linearization and Green’s theorem. This intermediate result still involves unknown terms, which we overcome in three ways. In one, an approximate upper bound of the error is obtained rigorously utilizing classical theories of differential operators; the others are heuristic practical approaches. The performance and the effectivity of these three different approaches are examined on 2D and 3D internal and boundary features, with Neumann and Dirichlet boundary conditions

Model Simplification for Efficient Collision Detection in Robotics

Motion planning for industrial robots is a computationally intensive task due to the massive number of potential motions between any two configurations. Calculating all possibilities is generally not feasible. Instead, many motion planners sample a sub-set of the available space until a viable solution is found. Simplifying models to improve collision detection performance, a significant component of motion planning, results in faster and more capable motion planners. Several approaches for simplifying models to improve collision detection performance have been presented in the literature. However, many of them are sub-optimal for an industrial robotics application due to input model limitations, accuracy sacrifices, or the probability of increasing false negatives during collision queries. This thesis focuses on the development of model simplification approaches optimised for industrial robotics applications. Firstly, a new simplification approach, the Bounding Sphere Simplification (BSS), is presented that converts triangle-mesh inputs to a collection of spheres for efficient collision and distance queries. Additionally, BSS removes small features and generates an output model less prone to false negatives

7th International Meshing Roundtable '98

The goal of the 7th International Meshing Roundtable is to bring together researchers and developers from industry, academia, and government labs in a stimulating, open environment for the exchange of technical information related to the meshing process. In the past, the Roundtable has enjoyed significant participation from each of these groups from a wide variety of countries