3D Geometric Model Research Articles

WingSegment: A Computer Vision‐Based Hybrid Approach for Insect Wing Image Segmentation and 3D Printing

This article introduces WingSegment, a MATLAB app‐designed tool employing a hybrid approach of computer vision and graph theory for precise insect wing image segmentation. WingSegment detects cells, junctions, Pterostigma, and venation patterns, measuring geometric features and generating Voronoi patterns. The tool utilizes region‐growing, thinning, and Dijkstra's algorithms for boundary detection, junction identification, and vein path extraction. It provides histograms and box plots of geometric features, facilitating comprehensive wing analysis. WingSegment's efficiency is validated through comparisons with established tools and manual measurements, demonstrating accurate results. The tool further enables exporting detected boundaries as FreeCAD macro files for 3D modeling and printing, supporting finite element analysis. Beyond advancing insect wing morphology understanding, WingSegment holds broader implications for diverse planar structures, including leaves and geocells. This tool not only enhances automated geometric analysis and 3D model generation in insect wing studies but also contributes to the broader advancement of analysis, 3D printing, and modeling technologies across various planar structures.

Evaluation of stress distributions of calcium silicate-based root canal sealer in bulk or with main core material: A finite element analysis study.

This research aimed to assess the stress distribution in lower premolars that were obturated with BioRoot RCS or AH Plus, with or without gutta percha (GP), and subjected to vertical and oblique forces. One 3D geometric model of a mandibular second premolar was created using SolidWorks software. Eight different scenarios representing different root canal filling techniques, single cone technique with GP and bulk technique with sealer only with occlusal load directions were simulated as follows: Model 1 (BioRoot RCS sealer and GP under vertical load [VL]), Model 2 (BioRoot RCS sealer and GP under oblique load [OL]), Model 3 (AH Plus sealer with GP under VL), Model 4 (AH Plus sealer with GP under OL), Model 5 (BioRoot RCS sealer in bulk under VL), Model 6 (BioRoot RCS in bulk under OL), Model 7 (AH Plus sealer in bulk under VL), and Model 8 (AH Plus sealer in bulk under OL). A static load of 200 N was applied at three occlusal contact points, with a 45° angle from lingual to buccal. The von Mises stresses in root dentin were higher in cases where AH Plus was used compared to BioRoot RCS. Furthermore, shifting the load to an oblique direction resulted in increased stress levels. Replacing GP with sealer material had no effect on the dentin maximum von Mises stress in BioRoot RCS cases. Presence of a core material resulted in lower stress in dentin for AH Plus cases, however, it did not affect the stress levels in dentin for cases filled with BioRoot RCS. Stress distribution in the dentin under oblique direction was higher regardless of sealer or technique used.

Hydraulic fracturing simulation of concrete dam integrating intelligent crack detection and refined modeling methods

Concrete dams are prone to cracks during construction and operation process. Cracks on the upstream surface may induce the risk of hydraulic fracturing, thereby significantly reducing the safety of dam structure. Nevertheless, image processing technology, non-destructive testing technology and structural performance analysis technology with cracks are in a relatively independent state, leading to difficulties in analysis of actual cracks combined with numerical simulations. This paper proposes a novel approach for combination of intelligent identification technology and refined finite element method (FEM) for modeling and simulating the hydraulic fracturing resistance of the actual crack in concrete dams. With image processing technology and non-destructive testing technology, direction and depth of actual cracks are identified and extracted, then the 3D geometric model of actual cracks is generated. The refined model with the identified actual crack is constructed by the node projection strategy. This approach is used to assess the hydraulic fracturing resistance of the concrete dam with actual cracks in the alpine region. The results demonstrate that the critical crack depth of hydraulic fracturing is 12.93 m, and the opening width is 1.01 mm, which is 2.53 times the limit value for Class D cracks in the code (DL/T5251–2010). The refined modelling method based on actual crack detected on site can accurately evaluate the crack state compared to the conservative code.

Microplasticity induced damping of aluminum foam

Aluminum foam's high dampening properties provide substantial potential for reducing mechanical vibration and noise in lightweight applications. However, inadequate understanding of the damping mechanism cannot provide sufficient theoretical guidance to improve the damping performances. In this study, the DMA (Dynamic Mechanical Analysis) tests results were compared with the numerical simulations to examine the correlation between local plastic deformation and the aluminum foam's damping performances. The 3D geometric modeling of aluminum foam was imported into ABAQUS/Explicit. The loss factors derived from the plastic energy dissipation of the numerical simulations are well consistent with the DMA tests. The simulation showed that the cell walls produces localized plastic deformation at the strains well below the elastic limit of engineering point view. Meanwhile, the plateau borders remain elastic, and thereby maintain the overall elasticity of aluminum foams. Aluminum foam's damping properties are tailorable by altering the pore size and local solid materials thickness. Under vibration loading, the aluminum foam sandwich offers higher damping performances due to greater local plastic deformation within the overall elastic range of the components.

Model-Based 3D Gaze Estimation Using a TOF Camera.

Among the numerous gaze-estimation methods currently available, appearance-based methods predominantly use RGB images as input and employ convolutional neural networks (CNNs) to detect facial images to regressively obtain gaze angles or gaze points. Model-based methods require high-resolution images to obtain a clear eyeball geometric model. These methods face significant challenges in outdoor environments and practical application scenarios. This paper proposes a model-based gaze-estimation algorithm using a low-resolution 3D TOF camera. This study uses infrared images instead of RGB images as input to overcome the impact of varying illumination intensity in the environment on gaze estimation. We utilized a trained YOLOv8 neural network model to detect eye landmarks in captured facial images. Combined with the depth map from a time-of-flight (TOF) camera, we calculated the 3D coordinates of the canthus points of a single eye of the subject. Based on this, we fitted a 3D geometric model of the eyeball to determine the subject's gaze angle. Experimental validation showed that our method achieved a root mean square error of 6.03° and 4.83° in the horizontal and vertical directions, respectively, for the detection of the subject's gaze angle. We also tested the proposed method in a real car driving environment, achieving stable driver gaze detection at various locations inside the car, such as the dashboard, driver mirror, and the in-vehicle screen.

Phenotypic characterization of liver tissue heterogeneity through a next-generation 3D single-cell atlas

Three-dimensional (3D) geometrical models are potent tools for quantifying complex tissue features and exploring structure–function relationships. However, these models are generally incomplete due to experimental limitations in acquiring multiple (> 4) fluorescent channels in thick tissue sections simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we combined deep-tissue immunostaining, multiphoton microscopy, deep-learning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatial single-cell atlas of hepatic architecture (Hep3D), including all main tissue and cellular components at different stages of post-natal development in mice. We used Hep3D to quantitatively study 1) hepatic morphodynamics from early post-natal development to adulthood, and 2) the effect on the liver's overall structure when changing the hepatic environment after removing KCs. In addition to a complete description of bile canaliculi and sinusoidal network remodeling, our analysis uncovered unexpected spatiotemporal patterns of non-parenchymal cells and hepatocytes differing in size, number of nuclei, and DNA content. Surprisingly, we found that the specific depletion of KCs results in morphological changes in hepatocytes and HSCs. These findings reveal novel characteristics of liver heterogeneity and have important implications for both the structural organization of liver tissue and its function. Our next-gen 3D single-cell atlas is a powerful tool to understand liver tissue architecture, opening up avenues for in-depth investigations into tissue structure across both normal and pathological conditions.

Three-Dimensional Accurate Geometric Modeling and Mechanical Analysis of Wire Mesh for Deployable Antennas

Wire meshes are widely used in deployable antennas, and the structure of the wire mesh directly affects the structural and electrical properties of the antenna. This study proposes a set of automated geometric modeling and mechanical analysis processes to realize the automated mechanical analysis and design of complex wire mesh structures. First, considering the tilt in the wire mesh structure owing to the traction of the underlap on the loop, a three-dimensional (3D) geometric model of the repeating unit of the wire mesh structure was established using periodic cubic spline curves. Subsequently, a method using sensitivity matrix adjustment is proposed to eliminate the interstructure inlay phenomenon, and an optimization model is established. The vector superposition method established a 3D geometric model of the overall wire mesh structure without an inlay problem. Finally, a finite element model of the wire mesh considering the contact problem was established by the adaptive matching method for contact pairs of the finite element model of the wire mesh. Mechanical simulation experiments were carried out on the model, comparing the theoretical analysis with the experimental results and verifying its reasonableness.

PointMCD: Boosting Deep Point Cloud Encoders Via Multi-View Cross-Modal Distillation for 3D Shape Recognition

As two fundamental representation modalities of 3D objects, 3D point clouds and multi-view 2D images record shape information from different domains of geometric structures and visual appearances. In the current deep learning era, remarkable progress in processing such two data modalities has been achieved through respectively customizing compatible 3D and 2D network architectures. However, unlike multi-view image-based 2D visual modeling paradigms, which have shown leading performance in several common 3D shape recognition benchmarks, point cloud-based 3D geometric modeling paradigms are still highly limited by insufficient learning capacity due to the difficulty of extracting discriminative features from irregular geometric signals. In this article, we explore the possibility of boosting deep 3D point cloud encoders by transferring visual knowledge extracted from deep 2D image encoders under a standard teacher-student distillation workflow. Generally, we propose PointMCD, a unified multi-view cross-modal distillation architecture, including a pretrained deep image encoder as the teacher and a deep point encoder as the student. To perform heterogeneous feature alignment between 2D visual and 3D geometric domains, we further investigate visibility-aware feature projection (VAFP), by which point-wise embeddings are reasonably aggregated into view-specific geometric descriptors. By pair-wisely aligning multi-view visual and geometric descriptors, we can obtain more powerful deep point encoders without exhausting and complicated network modification. Experiments on 3D shape classification, part segmentation, and unsupervised learning strongly validate the effectiveness of our method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The code and data will be publicly available at</i> <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/keeganhk/PointMCD</uri> .

Numerical study on normal lung sounds in bronchial airways under different breathing intensities

BackgroundDue to the complexity of airways and the limitation of experiments, the production mechanism of the lung sounds in airways has not been fully understood, which often confuses diagnosis. MethodA 3D geometrical model of human airways (G5-G8) has been developed based on Weibel's model. Simulation on transient airflow and the noise production during exhalation under different breathing intensities (Q = 15, 30, 45, 60, 75, 90 L/min) has been carried out with Direct Noise Computation (DNC) and Ffowcs Williams-Hawkings (FW-H) method. Results(1) The junctions between airways are most likely to produce lung sounds, and the peak value is located in the junction between G7 and G6 at the middle of exhalation (about 0.75 s). (2) With the increase in breathing intensity, the average sound pressure level first increases, reaches the peak value at 70–75 L/min, and then drops. (3) Higher breathing intensity is helpful to produce the feature of wheezing, namely a comparatively higher sound pressure level in the range of 200–500 Hz. Moreover, this feature is prominent with the increase in breathing intensity.

Preliminary Assessment of Badajo Cave (Segovia, Spain) Stability Using Empirical, Numerical and Remote Techniques

Badajo cave is a shallow cavity (hemispherical rock shelter) located in the valley of Clamores River (Segovia city, Central Spain). This small canyon carved in Cretaceous dolostones has numerous geosites, as well as a rich archaeological and historical heritage. There are dozens of rock outcrops in the valley’s cliffs and slopes, on both banks, where various types of sedimentary rocks can be easily recognized and differentiated, especially carbonates (dolostones and limestones), and mixed carbonate-detrital (dolomitic sandstones, calcareous silts, marls). The cave was formed by karstic and gravitational processes within a mixed dolomitic sandstones and limestones, and it has an important archaeological interest. This study proposes a preliminary stability analyses of the cave applying: (i) empirical approaches based on geomechanical classifications using Barton’s Q Index, Rock Mass Rating (RMR) and the recently created Cave Geomechanical Index (CGI); (ii) three-dimensional model generated with the remote photogrammetric technique Structure from Motion (SfM) to allow acquisition of data to complete values collected in the geomechanical station, and to create the numerical model of the critical sections of the cave; and (iii) numerical simulations using a 2D model based on the generalized Hoek and Brown failure criterion and a 3D wedge analysis. The results of the analysis show that the cave is stable, although it presents some places with small problems (falls of slabs and blocks) that deserve monitoring. Furthermore, the evaluation by the geomechanical classification Q and the corresponding abacus of cave stability indicates that it is located in the “transition” zone where attention is required. In addition, SfM photogrammetric technique makes possible to generate a geometric 3D model that allowed the acquisition of data that were difficult to take in situ. The geotechnical parameters obtained from the different methods complement each other, resulting in a more realistic engineering representation of the subsurface environment. As a conclusion, a graph showing the two empirical methodologies (Barton’s Q Index and CGI), and some recommendation for a future analysis are given.

Extending 3D geometric file formats for geospatial applications

This study addresses the representation and exchange of geospatial geometric 3D models, which is a common requirement in various applications like outdoor mixed reality, urban planning, and disaster risk management. Over the years, multiple file formats have been developed to cater to diverse needs, offering a wide range of supported features and target areas of application. However, classic exchange formats like the JavaScript Object Notation and the Extensible Markup Language have been predominantly favored as a basis for exchanging geospatial information, leaving out common geometric information exchange formats such as Wavefront’s OBJ, Stanford’s PLY, and OFF. To bridge this gap, our research proposes three novel extensions for the mentioned geometric file formats, with a primary focus on minimizing storage requirements while effectively representing geospatial data and also allowing to store semantic meta-information. The extensions, named GeoOBJ, GeoOFF, and GeoPLY, offer significant reductions in storage needs, ranging from 14 to 823% less compared to standard file formats, while retaining support for an adequate number of semantic features. Through extensive evaluations, we demonstrate the suitability of these proposed extensions for geospatial information representation, showcasing their efficacy in delivering low storage overheads and seamless incorporation of critical semantic features. The findings underscore the potential of GeoOBJ, GeoOFF, and GeoPLY as viable solutions for efficient geospatial data representation, empowering various applications to operate optimally with minimal storage constraints.

COMPARATIVE ANALYSIS OF THE BEARING CAPACITY OF PLANETARY MECHANISMS FORMED ON THE BASIS BY TWO SIMPLE JAMES PLANETARY MECHANISMS, ACCORDING TO SEQUENTIAL NON-LOOP AND CLOSED KINEMATIC SCHEMES WITH ONE LOOP

The article presents a method for comparative analysis of the bearing capacity of planetary mechanisms of various kinematic schemes using several CAD/CAE software environments. To implement the method of comparative analysis, the KOMPAS-3D and SolidWorks software environments were used. In the first environment, calculations were performed according to the method of the GOST 21354-87 standard. The initial data and results of calculations performed by the KOMPAS-GEARS software package are stored in the appropriate files. In the second environment, a parametric 3D geometric solid model of the kinematic scheme of the planetary mechanism was created. According to this model, such characteristics of gears as mass and axial moment of inertia were determined. These characteristics are used to perform optimization calculations of the mass and speed of the designed planetary mechanism. The study of the speed of the planetary mechanism can be carried out in SolidWorks Motion. The overall dimensions of the model allow the designer to assess the acceptability of the design constraints for given dimensions to the specified requirements. According to the method, a study was made of the suitability of gear designs that were designed for a closed planetary mechanism as gears of an open-loop sequential planetary mechanism. The closed planetary gear is formed by two simple James planetary gears. The circuities planetary gear is formed by the series connection of the same simple planetary gears. Two cases of loading gears for a given kinematic scheme of the planetary mechanism were studied. Keywords: simple James planetary mechanism (mechanisms type ); closed planetary mechanism; contourless planetary gear; moment of inertia of gear-wheel; gear mass; planetary gear mass; contact strength of the gearing; bending strength of the gearing; toothing resource; 3D geometric solid model of the kinematic scheme of the planetary mechanism

Knowledge graph representation method for semantic 3D modeling of Chinese grottoes

The integration of 3D geometric models with semantic information significantly improves the applicability and comprehensibility of cultural heritage. The semantic 3D modeling of Chinese grottoes poses challenges for individuals without expertise in cultural heritage due to gaps in domain knowledge and discrepancies in understanding. However, the existing domain ontology and knowledge graph provide an insufficient representation of the knowledge of Chinese grottoes. To overcome these obstacles, we propose a knowledge graph representation method to provide explicit knowledge for participants at different stages of semantic 3D modeling of Chinese grottoes, which includes schema layer construction and data layer construction. On the schema layer, we design a domain ontology named ChgOnto (Chinese Grottoes Ontology) that consists of four high-level concept classes: spatial object, informational object, digital device, and temporal object. Among the classes in the ChgOnto, the components (e.g., cliff wall, cave roof, cliff wall footing), elements (e.g., primary Buddha statue, pedestal, decoration), the properties (e.g., length, width, depth) of caves and niches in Chinese grottoes as well as the spatial relationships between them are all precisely defined. ChgOnto also reuse the classes from the renowned CIDOC CRM ontology in the cultural heritage field and GeoSPARQL in the geospatial domain, facilitating integration between the two subjects. Considering the schema layer as the conceptual data model, the data layer extracts knowledge from unstructured text through natural language processing tools to instantiate the abstract classes and fill the properties of the schema layer. Finally, the knowledge required for semantic 3D modeling of Chinese grottoes is expressed in the data layer by a knowledge graph in a fixed expression form. Dazu Rock Carvings, a World Heritage site in China, is selected as a case study to validate the practicality and effectiveness of the proposed method. The results reveal that our method offers a robust knowledge-sharing platform for the semantic 3D modeling of Chinese grottoes and demonstrates excellent scalability. The method proposed in this paper can also serve as an informative reference for other types of cultural heritage.

Modeling of a Public Utility Facility from Total BIM Data

The purpose of this work is to present the possibilities of using tacheometric measurement technology in the development of a 3D geometric model of an existing building and the directions of using BIM technology in the process of building operation. General information on the development of BIM technology was presented, and issues related to the construction of 3D models were discussed. Attention was also drawn to the need to update the information assigned to the model on an ongoing basis in order to effectively manage the building. Supplementing the model with metadata regarding the building materials used will allow for a precise and quick analysis of all renovation assumptions. The created 3D model can be used to control the condition of structures or in safety and risk management.

Self-training based augmented reality for robust 3D object registration and task assistance

Typical augmented reality (AR) technologies superimpose virtual information onto the real environment for task guidance and assistance by tracking fiducial markers. However, these have narrow recognition ranges due to the markers, and it is difficult to track markers when occlusion occurs. Therefore, it is challenging to seamlessly register real objects in AR scenes captured by the camera without requiring fiducial markers. Deep learning–based approaches to 3D object registration and task assistance have recently indicated promising directions for superimposing 3D virtual objects onto corresponding real objects or their surroundings seamlessly. However, since supervised learning-based object registration requires many pose annotations on images for the locations and orientations of real objects, this process is a time-consuming and labor-intensive task. Thus, this paper proposes a new self-training based augmented reality method for seamless real object registration and task assistance without time-consuming pose annotations. As the industrial components or objects have their 3D geometric models, the proposed approach utilizes them as their synthetic data. The automatically generated synthetic dataset is used for training the deep learning model, which outputs a colored coordinate map of objects to be detected. 2D–3D key point matching between the 2D colored coordinate map and 3D colored coordinate model is then performed for 3D object registration in an AR environment. In particular, self-training is performed for fine-tuning the deep learning model by generating pseudo-labels with the highest probability for mask intersection over union (IoU) in the unlabeled real object dataset. We compared the proposed approach with previous studies to confirm its effectiveness and advantages. Also, we performed ablation studies by training a custom dataset based on various industrial 3D virtual models. Finally, we present AR-based task guidance and assistance, such as industrial robot manipulation.

Research on the design of booth space in furniture exhibitions based on big data analysis

Abstract In this paper, we first use VR technology to spatially calibrate the flat images of furniture booths and use a fisheye camera to obtain the visual features of booth space layout with coordinate information and color information in 3D space to construct a 3D geometric model. Then, the booth layout framework is used to extract the scene information, and the visualization processing and fusion of layout nodes are realized using coordinate conversion to complete the multi-user interactive genetic algorithm-based booth space layout to visualize and analyze the furniture layout of the booth space. After testing, we found that before optimizing, the area occupied by individual furniture SA tends to increase with the increase in a number of furniture. After optimization, the average area utilization of the booth increased by 23.6%, the number of furniture that can be accommodated in a single furniture area increased by 81.82% on average, and the booth space utilization was highly improved.

Build an accurate 3D geometrical model of a soft knife profile of abrasive water jet

Build an accurate 3D geometrical model of a soft knife profile of abrasive water jet

Package Design Thermal Optimization for Metal-Oxide Gas Sensors by Finite Element Modeling and Infra-Red Imaging Characterization.

We designed a 3D geometrical model of a metal-oxide gas sensor and its custom packaging and used it in finite element modeling (FEM) analysis for obtaining temperature and heat flux distribution. The 3D computer simulation, performed with GetDP software (version 3.5.0, 13 May 2022), accurately predicted the temperature distribution variation across the entire assembly. Knowing the temperature variation and the location of the hot spots allowed us to select the best electrical interconnect method and to choose the optimal materials combination and optimal geometry. The thermal modeling also confirmed the need to use a low thermal conductivity material to insulate the MOX sensor since the latter is heated to its operational temperature of 250 °C. For that purpose, we used the in-house formulated xerogel-epoxy composite of thermal conductivity of 0.108 W m-1 K-1, which is at least 30% less compared to the best-in-class among commercially available materials. Based on the 3D FEM outputs, we designed, assembled, and characterized a fully functional packaged MOX gas sensor in several configurations. We measured the temperature distribution on all parts of the MOX gas sensor assembly using a thermal imaging infrared (IR) microscope. The results of 3D FEM are in good agreement with the temperature distribution obtained by the non-contact IR thermal characterization.

Mechanical behavior of three‐harness twill woven composite plates under tension loading

AbstractThree‐harness twill woven composite (THT‐WC) is an advanced carbon fiber reinforced composite that compromises the mechanical behaviors in both longitudinal and latitudinal directions. To explore the further practical application, the structural characteristics and static mechanical behavior of the material were investigated in this article. X‐ray computerized tomography was adopted to obtain the mesostructure details and to capture the key characteristics. With the help of mesoscale information, the 2D and 3D geometric models were established in the form of representative volume elements (RVEs). Combined with voxel mesh generation technology, a finite element model was proposed based on a 3D geometric model where macroscopic mechanical properties of materials along different yarn directions were gained. To verify the simulated geometry and predicted mechanical properties, mesoscale geometric comparison and specimen tensile tests were performed. The results show that the geometric model established in this article can reasonably reflect the periodicity fluctuation of binder warp yarns and the randomness fluctuation of weft yarns. Compared with the experimental results, the relative error of stiffness in the weft direction of the RVE is 4.25%, and that in the warp direction is 5.33%.Highlights The mechanical properties of THT‐WC were investigated experimentally. Meso‐scale reconstruction of THT‐WC was presented. A model to predict the mechanical properties of THT‐WC is established.

A novel in silico Nuss procedure for pectus excavatum patients

The purpose of this study is to suggest a novel in silico Nuss procedure that can predict the results of chest wall deformity correction. Three-dimensional (3D) geometric and finite element model of the chest wall were built from the 15-year-old male adolescent patient’s computed tomography (CT) image with pectus excavatum of the mild deformity. A simulation of anterior translating the metal bar (T) and a simulation of maintaining equilibrium after 180-degree rotation (RE) were performed respectively. A RE simulation using the chest wall finite element model with intercostal muscles (REM) was also performed. Finally, the quantitative results of each in silico Nuss procedure were compared with those of postoperative patient. Furthermore, various mechanical indicators were compared between simulations. This confirmed that the REM simulation results were most similar to the actual patient’s results. Through two clinical indicators that can be compared with postoperative patient and mechanical indicators, the authors consider that the REM of silico Nuss procedure proposed in this study is best simulated the actual surgery.