CAD Mesh Research Articles

Beyond conventional: An integrated aerostructural optimization approach for innovative tailplane configurations

This research paper presents a comprehensive study focused on optimizing innovative tailplane configurations for transport jet aircraft. This study aims to enhance the aerodynamics of the aircraft's rear end by introducing a novel tail arrangement. The ultimate goal is to reduce the size of the horizontal empennage, which will have a positive impact on aircraft fuel efficiency. To fulfill its objectives, this work develops a systematic approach, integrating advanced methodologies such as the Design of Experiments and Response Surface Models for both aerodynamics and structural disciplines. By levering response surfaces methodology, the aerostructural optimization has been performed towards a size reduction of the horizontal tail. Results indicate a potential 9% reduction in the tailplane reference area, which could result in enhanced aerodynamic performance and weight saving. This target would only be achievable if the innovative design includes a Leading Edge Extension device to maintain the stability and handling characteristics of a conventional reference aircraft. The impact of the innovative optimized tail arrangement developed in this study at the aircraft level resulted in a 1% reduction in block fuel for a mission range of approximately 3,400 nautical miles for a 180-seat capacity jet aircraft (similar to A320neo). Furthermore, from an industrial perspective, this paper also demonstrates how an automated workflow assists with CAD modeling, mesh creation, simulation execution, and surrogate models to accelerate complex multidisciplinary optimization processes, thereby reducing the time and costs associated with the development of a new aircraft configuration.

Semi-automatic 3D crack map generation and width evaluation for structural monitoring of reinforced concrete structures

Bridge inspection is a time-consuming, expensive, but indispensable task. In this work, a new semi-automatic workflow for a concrete bridge condition assessment system is developed and discussed. The workflow consists of three main parts merged in the new methodology. The elements are the data acquisition with cameras, the automated damage detection and localization using a neural network, and the resulting engineering condition assessment. Furthermore, a CAD model serves as a base for the later calculations for the condition assessment. Camera images are used for both sub-millimeter crack detection using semantic segmentation by an artificial neural network and a crack localization based on a combination of a photogrammetric workflow including structure from motion (SfM) and the projection as imprinted points directly onto the as-planned CAD mesh. Moreover, an approach for crack width derivation is given. The captured crack width, crack position, and the date of detection represent the input values for subsequent crack monitoring. Thereby, this new concept is proposed as an essential step towards a time-efficient and objective life-cycle assessment of reinforced concrete structures.

Extraction of English Keyword Information Based on CAD Mesh Model

Traditional methods only consider topic information in English vocabulary information extraction, lose the statistical feature information of the keywords themselves, and easily ignore the semantic information of the words. In order to improve the extraction efficiency of English keyword information, based on the CAD mesh model, this paper adds constraint factors such as vertex neighborhood flatness, vertex degree, side length, and flatness on both sides of the side on the basis of the original QEM quadratic error simplification algorithm, and it incorporates a smoothing effect into the edge folding cost function. Moreover, based on the proposed normal vector-based QEM mesh simplification algorithm, the point selection after the edge folding operation is fixed as the vertices of the original edge, and it is applied to the mesh parameterization. In addition, the algorithm solves the local parameterization problem of partially deleted vertices after the simplification operation of each layer is completed. After the model is constructed, the performance of the model is verified through experiments. The research shows that the English keyword information extraction model constructed in this paper is effective.

Shape Optimization of the Cross-Section for Noncircular Hypersonic Missile Forebody

In the hypersonic regime, noncircular missiles have attracted significant attention from researchers. The paper first summarizes the development and present situation of the noncircular missiles at home and abroad. Previous research found that the cross-section shape of missiles has a direct influence on the aerodynamics performance. To find the best cross-section shape in terms of lift-drag-ratio, an efficient and robust shape optimization framework is developed. Class/shape function transformation (CST) method and power-law curve are introduced to complete the parametric modeling of the noncircular missile. The evolutionary algorithm has been utilized to improve the optimization efficiency. A combination of script and journal files is written to automate the CAD loft, mesh generation, and CFD simulations process. Finally, the forebody section of a missile body is chosen as an example to deliver the whole optimization steps. The optimization results show that the lift-to-drag ratio increases from 1.8 to 2.4 when the hypersonic missile forebody cruises at the design condition. The results also demonstrate that the optimized configuration has a better aerodynamic performance than the original one over a wide speed range from Mach 2 to 8 and a wide attack of angle range from 0 to 30.

3D spatial resolution evaluation for helical CT according to ASTM E1695 – 95

We propose a new segmentation method for separating parts of a mechanical assembly in a CT volumetric image. Part segmentation is generally based on edge detection with gradient norms of the CT volumetric image, which often fails when parts made of the same material come into close contact. This is because an image is blurry between the parts with low gradient norms and indistinct edges. In order to enhance weak edges at such faded part boundaries, our idea is to enhance the gradient norm in a CT volumetric image. To find such faded boundaries, auxiliary information needs to be introduced. In this paper, two practical cases of the faded boundaries in plastic and welded assemblies of sheet metal parts are studied. For the former case, CAD mesh models of target parts are used. The faded boundaries are found in blurred regions on the CAD mesh boundaries. For the latter case, the thickness value of the sheet metal parts used, and it is assumed to be constant. The faded boundary can be located at the distance of the thickness from the outer surface of the part. By enhancing the gradient norms in those faded boundaries, the assembly of parts made of the same material can be segmented. The algorithms are implemented, and experimental results are demonstrated.

3D Segmentation of CT Volumetric Image for Mechanical Assemblies with Forcible Edge Enhancement

We propose a new segmentation method for separating parts of a mechanical assembly in a CT volumetric image. Part segmentation is generally based on edge detection with gradient norms of the CT volumetric image, which often fails when parts made of the same material come into close contact. This is because an image is blurry between the parts with low gradient norms and indistinct edges. In order to enhance weak edges at such faded part boundaries, our idea is to enhance the gradient norm in a CT volumetric image. To find such faded boundaries, auxiliary information needs to be introduced. In this paper, two practical cases of the faded boundaries in plastic and welded assemblies of sheet metal parts are studied. For the former case, CAD mesh models of target parts are used. The faded boundaries are found in blurred regions on the CAD mesh boundaries. For the latter case, the thickness value of the sheet metal parts used, and it is assumed to be constant. The faded boundary can be located at the distance of the thickness from the outer surface of the part. By enhancing the gradient norms in those faded boundaries, the assembly of parts made of the same material can be segmented. The algorithms are implemented, and experimental results are demonstrated.

Intelligent systems for volumetric feature recognition from CAD mesh models

This paper presents an intelligent technique to recognise the volumetric features from CAD mesh models based on hybrid mesh segmentation. The hybrid approach is an intelligent blending of facet-based, vertex based, rule-based, and artificial neural network (ANN)-based techniques. Comparing with existing state-of-the-art approaches, the proposed approach does not depend on attributes like curvature, minimum feature dimension, number of clusters, number of cutting planes, the orientation of model and thickness of the slice to extract volumetric features. ANN-based intelligent threshold prediction makes hybrid mesh segmentation automatic. The proposed technique automatically extracts volumetric features like blends and intersecting holes along with their geometric parameters. The proposed approach has been extensively tested on various benchmark test cases. The proposed approach outperforms the existing techniques favourably and found to be robust and consistent with coverage of more than 95% in addressing volumetric features.

Intelligent systems for volumetric feature recognition from CAD mesh models

This paper presents an intelligent technique to recognise the volumetric features from CAD mesh models based on hybrid mesh segmentation. The hybrid approach is an intelligent blending of facet-based, vertex based, rule-based, and artificial neural network (ANN)-based techniques. Comparing with existing state-of-the-art approaches, the proposed approach does not depend on attributes like curvature, minimum feature dimension, number of clusters, number of cutting planes, the orientation of model and thickness of the slice to extract volumetric features. ANN-based intelligent threshold prediction makes hybrid mesh segmentation automatic. The proposed technique automatically extracts volumetric features like blends and intersecting holes along with their geometric parameters. The proposed approach has been extensively tested on various benchmark test cases. The proposed approach outperforms the existing techniques favourably and found to be robust and consistent with coverage of more than 95% in addressing volumetric features.

Reverse Engineering on Jet Engine Turbine Disk

Damaged or broken parts are generally too expensive to replace, or no longer available. Re can be defined as ‘systematic evaluation of a product with the purpose of replication. This includes design of a new part, copy of an existing part, recovery of a damaged or broken part, development of model accuracy and inspection of a numerical model. Task is to reproducing the geometries of aero engine physical component in digitizing process through 3D scanning and complete conversion of physical data into CAD model by using modern measuring machines with its integrated software’s (creo 2.0) extractions of information about geometry to develop part models parts which have to be reverse engineered. CMM inspection and reverse engineering software are employed to evaluate any dimension deformations. Deviation in the dimension is taken in to consideration as evaluating characteristics. The error analysis of some features between 3D scan data, CMM, CAD model, and MESH data are performed.Deviation between scan data, CAD model, and CMM are within acceptable limits. And deformation between CAD model and MESH data are within -0.1 to +0.1mm. The CAD model generated is within acceptable criteria (30 microns).

A fast and efficient 3D reflection symmetry detector based on neural networks

Determining the 3D reflection symmetry planes from 3D models is very difficult and time-consuming. In this paper, we formulate the symmetry detection as a per-point classification problem and present a deep neural network based method to solve it. During the training procedure, we firstly collect a lot of CAD mesh models with reflection symmetry as the training data, and then convert each mesh model into a dense point cloud with points located on the symmetry planes labeled as positive. Based on the PointNet++ architecture, we train a multi-scale deep neural network to capture the reflection symmetry property from the point cloud automatically. In addition, a novel weighted cross-entropy loss function is adopted to balance the positive and the negative samples. During the inference procedure, we firstly feed the down-sampled point cloud into the trained neural network. Then, the output per-point classification result is used to calculate an initial symmetry plane equation with RANSAC strategy and the least square method. Finally, iterative closest point algorithm is performed to optimize the fitted symmetry plane. Experimental results on both the synthetic and the real data demonstrate the efficiency, robustness and flexibility of our approach. Our method is pretty fast and generates comparable or better results than the existing methods.

The fixtureless inspection of flexible parts based on semi-geodesic distance

Some types of manufactured parts like sheet metals and skins often have a significantly different shape in a free-state position compared to their state-of-use position (as defined by their nominal CAD models) due to a combination of gravity and/or the residual effects of stress. Traditionally known as flexible (nonrigid compliant) parts, these dedicated fixtures are used for inspection operations in order to maintain flexible parts from a free-state position to a state-of-use position. This paper introduces a new automatic defect identification method primarily intended for two less-investigated manufacturing defect types: contour profile errors and hole localization. By combining simple techniques such as mesh boundary detection, fast boundary-based correspondence searches and accurate fast marching on triangulated meshes, the semi-geodesic distances from each boundary vertex on the acquired SCAN mesh to all the other boundary vertices is calculated, stored in a table and then compared to the corresponding values on the part's nominal CAD mesh. The comparisons found in the tables result in an estimation of the location and amplitude of the two aforementioned defect types. Compared to other work in this field, the overall approach does not rely on any mesh registration or finite-element analysis with tedious boundary conditions setup. It is also relatively fast. A fast algorithm/app based on this method was named the AFDA (Automatic Free-state Defect Approximation) and was validated against case studies in the aerospace sector. The results reflect the utility and effectiveness of the proposed approach.

A slice-based algorithm for automatic and feature-preserving hole-filling in a CAD mesh model

This paper describes an automatic feature-preserving mesh hole filling algorithm to repair a mesh model, obtained by tessellating a 3D CAD model, with arbitrary holes or gaps. Missing triangles in ...

CAD mesh models segmentation into swept surfaces

One of the most significant issues investigated in reverse engineering (RE) is the problem of finding the best surface that approximates point cloud data. In recent years, some studies have been carried out for the segmentation of industrial mesh models into primitive surfaces and simple kinematic surfaces such as revolved and extruded surfaces. But, with regard to the swept surfaces that are widely used in CAD models, most researches just investigated how to extract the generative curves and few researches investigated the segmentation of CAD model into swept surfaces. In this paper, regarding the importance of swept surfaces in the fields of computer design, RE, and tool path planning in CAM software, a method to find the swept surfaces by arbitrary central and profile curves is introduced. To this end, with the help of variational segmentation algorithm, and regarding slippable motion as a segmentation criterion, data points are segmented into regions that could be approximated by extruded surface. Then, an effective algorithm is proposed through which, by employing the concept of hierarchical classification and defining the dual graph of the segmented subregions, swept surface regions may be found. The introduced method is capable of recognizing other surfaces such as blend, extruded and revolved surfaces as well. To validate the proposed algorithm, it is implemented in several models with different conditions and various noise levels. It is observed that the results have good agreement with real model condition, which shows the efficiency of this method in finding the swept surface.

A slice based approach to recognize and extract free-form volumetric features in a CAD mesh model

ABSTRACTThis paper describes an algorithm to recognize and extract volumetric features by directly clustering the triangles constituting a feature in a CAD mesh model. The algorithm involves two steps – isolating features in 2D slices followed by a 3D traversal to cluster all the triangles in the feature. The main advantage of this approach is that processing of the three dimensional mesh occurs only for the triangles associated with its signature identified on the 2D slice. Results from an implementation tested on various mesh models are presented.

Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

Direct Editing on Hexahedral Mesh through Dual Operations

The finite element mesh regeneration, which is usually required during the design model verification process, is time consuming. Mesh editing is a kind of efficient mesh regeneration technique. In this paper, a direct editing method for hexahedral mesh is proposed to achieve high quality and adaptive hexahedral mesh regeneration. After the user applies direct editing on the CAD model, effective mesh deformation and optimization are automatically conducted on the associated hexahedral mesh model. To optimize the deformed mesh, firstly, simplified fundamental sheet configuration conversions are applied to improve the boundary mesh quality; secondly, dual operations are carried out to insert/extract entire sheets; thirdly, according to the measurement of the hexahedron deformation, those mesh regions whose mesh sizes become not reasonable due to the deformation are coarsened and refined through localized dual operations. The proposed method can not only effectively achieve hexahedral mesh editing, but also facilitate the interoperation of CAD model and mesh model.

CAD mesh model simplification with assembly features preservation

This paper aims to investigate a CAD mesh model simplification method with assembly features preservation, in order to satisfy the requirement of assembly field for the information of 3D model. The proposed method simplifies a CAD mesh model as follows. Firstly, the notion of conjugation is incorporated into the definition of assembly features, with the purpose of benefitting the downstream applications such as assembly features recognition and preservation. Subsequently, the attributed adjacency graphs (AAGs) of the regionlevel- represented parts are established. The assembly features are automatically recognized by searching for conjugated subgraphs of every two AAGs based on subgraph isomorphism algorithm. In order to improve the efficiency of assembly features recognition, the characteristics of conjugated subgraphs are adopted to initialize the mapping matrix, and the verifying while matching strategy is used to verify the validity of every two newly founded vertices which are correspondingly matched. Then, simplified CAD mesh model with assembly features preserved is constructed after suppressing the common form features. The method is applied successfully to simplify the CAD mesh model with assembly features well preserved. Moreover, the tradeoff between the cost of time for conjugated subgraphs matching and the complexity of the to-be-matched parts is proven to be almost linear.

CAD mesh model segmentation by clustering

CAD mesh models have been widely employed in current CAD/CAM systems, where it is quite useful to recognize the features of the CAD mesh models. The first step of feature recognition is to segment the CAD mesh model into meaningful parts. Although there are lots of mesh segmentation methods in literature, the majority of them are not suitable to CAD mesh models. In this paper, we design a mesh segmentation method based on clustering, dedicated to the CAD mesh model. Specifically, by the agglomerative clustering method, the given CAD mesh model is first clustered into the sparse and dense triangle regions. Furthermore, the sparse triangle region is separated into planar regions, cylindrical regions, and conical regions by the Gauss map of the triangular faces and Hough transformation; the dense triangle region is also segmented by the mean shift operation performed on the mean curvature field defined on the mesh faces. Lots of empirical results demonstrate the effectiveness and efficiency of the CAD mesh segmentation method in this paper.

Feature suppression based CAD mesh model simplification

Dynamic simulation and high quality FEA mesh generation need the CAD mesh model to be simplified, that is, suppressing the detailed features on the mesh without any changes to the rest. However, the traditional mesh simplification methods for graphical models can not satisfy the requirements of CAD mesh simplification. In this paper, we develop a feature suppression based CAD mesh model simplification framework. First, the CAD mesh model is segmented by an improved watershed segmentation algorithm, constructing the region-level representation required by feature recognition. Second, the form features needing to be suppressed are extracted using a feature recognition method with user defined feature facility based on the region-level representation, establishing the feature-level representation. Third, every recognized feature is suppressed using the most suitable one of the three methods, i.e. planar Delaunay triangulation, Poisson equation based method, and the method for blend features, thus simplifying the CAD mesh model. Our method provides an effective way to make CAD mesh model simplification meet the requirements of engineering applications. Several experimental results are presented to show the superiority and effectivity of our approach.

3304 CADメッシュの姿勢の正規化(OS4-1 デジタルエンジニアリングI,OS4 デジタルエンジニアリング)

This paper presents a simple method for normalizing poses of CAD meshes or polygonization of CAD models. Since CAD models involve many extrusion features, we find normalized poses by voting this extruding direction. This approach can easily capture a normalized pose for the CAD meshes, whereas PCA-based methods are misaligned for most cases and the result is free from numerical errors. This paper also demonstrates our method is efficient for several applications to CAD and voxel-based mesh generation.