3D Geometric Model Research Articles

Variational Relational Point Completion Network for Robust 3D Classification.

Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise, which hampers 3D geometric modeling and perception. Existing point cloud completion methods tend to generate global shape skeletons and hence lack fine local details. Furthermore, they mostly learn a deterministic partial-to-complete mapping, but overlook structural relations in man-made objects. To tackle these challenges, this paper proposes a variational framework, Variational Relational point Completion network (VRCNet) with two appealing properties: 1) Probabilistic Modeling. In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds. One path consumes complete point clouds for reconstruction by learning a point VAE. The other path generates complete shapes for partial point clouds, whose embedded distribution is guided by distribution obtained from the reconstruction path during training. 2) Relational Enhancement. Specifically, we carefully design point self-attention kernel and point selective kernel module to exploit relational point features, which refines local shape details conditioned on the coarse completion. In addition, we contribute multi-view partial point cloud datasets (MVP and MVP-40 dataset) containing over 200,000 high-quality scans, which render partial 3D shapes from 26 uniformly distributed camera poses for each 3D CAD model. Extensive experiments demonstrate that VRCNet outperforms state-of-the-art methods on all standard point cloud completion benchmarks. Notably, VRCNet shows great generalizability and robustness on real-world point cloud scans. Moreover, we can achieve robust 3D classification for partial point clouds with the help of VRCNet, which can highly increase classification accuracy. Our project is available at https://paul007pl.github.io/projects/VRCNet.

Lightweight Geometric Compression Encoding for Additive Manufacturing

In additive manufacturing (AM), 3D geometric models often contain some repetitive structures. To represent model topology more effectively and reduce storage space, this paper introduces a data structure using the repetition encoding framework and the hash encoding framework. First, we identify repeated meshes within the model and establish transformation groups. Then, we cluster the identical transformation groups to optimize storage space usage by utilizing the geometric relationships among facets. Finally, efficient data storage is achieved using the hash encoding framework. We devise three compatible encodings for prevalent additive manufacturing file formats based on these frameworks. We compare the encoding process with three commercial software solutions regarding the reconstruction efficiency and the storage space requirement. Experimental results exhibit that our proposed methods reduce file sizes by over 70% while preserving model topology information.

Enumeration and Identification of Unique 3D Spatial Topologies of Interconnected Engineering Systems Using Spatial Graphs

Abstract Systematic enumeration and identification of unique 3D spatial topologies (STs) of complex engineering systems (such as automotive cooling systems, electric power trains, satellites, and aero-engines) are essential to navigation of these expansive design spaces with the goal of identifying new spatial configurations that can satisfy challenging system requirements. However, efficient navigation through discrete 3D ST options is a very challenging problem due to its combinatorial nature and can quickly exceed human cognitive abilities at even moderate complexity levels. This article presents a new, efficient, and scalable design framework that leverages mathematical spatial graph theory to represent, enumerate, and identify distinctive 3D topological classes for a generic 3D engineering system, given its system architecture (SA)—its components and their interconnections. First, spatial graph diagrams (SGDs) are generated for a given SA from zero to a specified maximum number of interconnect crossings. Then, corresponding Yamada polynomials for all the planar SGDs are generated. SGDs are categorized into topological classes, each of which shares a unique Yamada polynomial. Finally, within each topological class, 3D geometric models are generated using the SGDs having different numbers of interconnect crossings. Selected case studies are presented to illustrate the different features of our proposed framework, including an industrial engineering design application: ST enumeration of a 3D automotive fuel cell cooling system (AFCS). Design guidelines are also provided for practicing engineers to aid the application of this framework to different types of real-world problems such as configuration design and spatial packaging optimization.

Mechanical Stability Analysis of the External Unilateral Fixation Device due to the Impact of Axial Pressure

This study performed a mechanical stability analysis for the impact of axial pressure on an Ultra X external unilateral fixation device applied to a tibia with an open fracture. The real construction of the fixation device was used to create a 3D geometric model using a Finite Element Method (FEM) model, which was made to perform structural analysis in the CATIA V5 (Computer Aided Three-dimensional Interactive Application) CAD/CAE system. Specific stresses and displacements were observed at points of interest using structural analysis. The focus was on the relative displacements of the proximal and distal bone segments in the fracture zone. These displacements were used to calculate the stiffnesses of the bone in the fracture zone and the fixation device itself. The results obtained provide the necessary information regarding the stability of the Ultra X fixation device.

Building information modeling integrated with damage detection algorithm for structural health monitoring of bridge

In this paper, a method for damage monitoring of bridges using modal parameters is presented. At first, fundamentals of frequency-based damage occurrence alarming are introduced. Second, building information modeling (BIM) software is used to construct a 3D geometric model of a bridge. A custom tool add-in based on Microsoft Excel is linked and analyzed related data for damage detection of the bridge using modal parameters. A finite element model of a bridge girder is established to investigate vibration characteristics under prestressing loss and structural damage. Frequency-based damage detection is implemented to alarm the damage occurrence of an inspected bridge girder. Last, the structural information of the bridge is updated to the BIM model to provide the structural performance of the inspected structure. The result reveals that BIM integrated with the damage detection algorithm can efficiently facilitate structural health bridges.

Mekanik Kilitleme Yöntemi ile Birleştirilen AA7075/AZ91 Malzemelerin Konik Kanal Tasarımı

ABSTRACT Material types with different chemical and physical properties are employed by being joined in industrial applications. The major objective is to generate high-performance prochannels by bringing outstanding properties of materials together. Many conventional methods, primarily welding method such as casting, adhesion, rivet weld, and bolts are employed in joining procedures. Among the joining methods, mechanical locking, a novel and ecologically friendly method, stands out as a successful method, particularly when joining dissimilar metal types. Within the scope of this study, the optimization of the channel geometry was performed on the AZ91 mold part, out of AA7075/AZ91 material pairs joined by using the mechanical locking method. The channel design was paid attention to ensure that it do not adversely affect the stress values and facilitates material flow. Fixed joint angle and fixed channel depth were used in accordance with the data received from previous research results and employed in the analysis. The analyses were completed using the finite element method and the Static Structural Module of the Workbench 18.2 version of the ANSYS software. The whole study was carried out on 3D geometric models. As a result, it was determined that the mechanical properties of the samples joined by MLM significantly changed depending on the channel design. The mechanical properties of the joint improved by roughly 3% with the optimal joint design, while the joint design that will facilitate material flow was achieved.

Radiomic-based Textural Analysis of Intraluminal Thrombus in Aortic Abdominal Aneurysms: A Demonstration of Automated Workflow.

Our main objective is to investigate how the structural information of intraluminal thrombus (ILT) can be used to predict abdominal aortic aneurysms (AAA) growth status through an automated workflow. Fifty-four human subjects with ILT in their AAAs were identified from our database; those AAAs were categorized as slowly- (< 5mm/year) or fast-growing (≥ 5mm/year) AAAs. In-house deep-learning image segmentation models were used to generate 3D geometrical AAA models, followed by automated analysis. All features were fed into a support vector machine classifier to predict AAA's growth status.The most accurate prediction model was achieved through four geometrical parameters measuring the extent of ILT, two parameters quantifying the constitution of ILT, antihypertensive medication, and the presence of co-existing coronary artery disease. The predictive model achieved an AUROC of 0.89 and a total accuracy of 83%. When ILT was not considered, our prediction's AUROC decreased to 0.75 (P-value < 0.001).

Forest Fire Spread Simulation and Fire Extinguishing Visualization Research

There are three main types of forest fires: surface fires, tree crown fires, and underground fires. The frequency of surface fires and tree crown fires accounts for more than 90% of the overall frequency of forest fires. In order to construct an immersive three-dimensional visualization simulation of forest fires, various forest fire ignition methods, forest fire spread, and fire extinguishing simulation exercises are studied. This paper proposes a lightweight forest fire spread method based on cellular automata applied to the virtual 3D world. By building a plant model library using cells to express different plants, and by building a 3D geometric model of plants to truly capture the combustion process of a single plant, we can further simulate forest-scale fire propagation and analyze the factors that affect forest fire spread. In addition, based on the constructed immersive forest scene, this study explored various forms of fire extinguishing methods in the virtual environment, mainly liquid flame retardants such as water guns, helicopter-dropped flame retardants, or simulated rainfall. Therefore, the forest fire occurrence, spread, and fire extinguishing process can be visualized after the interactive simulation is designed and implemented. Finally, this study greatly enhanced the immersion and realism of the 3D forest fire scene by simulating the changes in plant materials during the spread of a forest fire.

Three-Dimensional Angularity Characterization of Coarse Aggregates by the Optimal Ellipsoid Approximation Algorithm

The three-dimensional (3D) angularity of coarse aggregates was investigated in this study by an optimal ellipsoid approximation algorithm. The minimum volume enclosing ellipsoid (MVEE) of the 3D coarse aggregate particle represented by the surface point cloud was computed by a Python program. An algorithm was proposed to compute the optimal ellipsoid that is inscribed in the aggregate particle as far as possible. In the algorithm, a fitting index was proposed and a cycle program was coded to search the optimal ellipsoid. Based on the optimal ellipsoid and the point cloud of the coarse aggregate particle, a 3D angularity index was proposed. The critical discriminant coefficient was introduced into the angularity index to filter out the tiny convex parts on the particle. Six 3D geometric models were generated and five 3D aggregate particles were randomly selected to verify the effectiveness of the angularity index. The results demonstrate that the angularity index proposed in this study can effectively distinguish the angularity of different geometric models. The effect of mesh precision on the angularity index was analyzed and the critical discriminant coefficient was studied by the parameter analysis method and Delphi expert investigation method.

Mitral valve geometrical echocardiographic analysis and 3D computational modeling of a normal mitral valve.

Aim: This research aims to develop a consistent computational model of a normal mitral valve (MV) and describe mitral regurgitation (MR) geometry based on Carpentier's classification. Materials & methods: MV geometry was assessed by 2D transthoracic echocardiogram in 100 individuals. A 3D parametric geometric model of the MV was developed. A computational model of a normal MV was performed. Results: The simulation of the valve function was successfully accomplished and its kinematics was analyzed. Differences in geometry were revealed between normal and type III MR. Conclusion: 3D computational models of the normal MV can be constructed relying on standard measurements performed by 2D echocardiography. Certain geometrical differences exist among the normal and the most severe type of MR.

3D Cartographic Generalization of LiDAR Point Clouds Based on the Principle of Self-Similarity of a Deterministic Fractal Structure

The rendering of virtual three-dimensional (3D) structures represented by Point Cloud (PC) allows the representation of internal and/or external environments to buildings. However, the compilation of 3D geometric models is influenced by the intrinsic characteristics of PCs, which can be mitigated by the application of an PC simplification operator. According to the mathematical norms of fractal geometry, it was assumed that a PC is characterized by self-similarity. Two experimental datasets acquired with an SLT in static mode indoors were used. Four tasks were accomplished: sampling and structuring of a PC to solve the problem of random distribution, from an octree structure; estimation of the curvature of the points and the roughness of a neighbourhood for the extraction of edge points by the analysis of self-similarity and application of the Statistical Outliers Remove (SOR) algorithm, for the elimination of outliers points; uniform voxelization, to simplify the intermediate points; application of the Iterative Closest Point (ICP) algorithm to register the sets generated in the same local coordinate system. The use of voxelization was satisfactory, but once the voxel size is manually defined, the PC can be oversimplified and lose essential characteristics. This can be minimized by the primary analysis of the edge points, generating a set that is uniform, less noisy, and self- similar to the original set. To achieve a minimum density of points to model an environment three-dimensionally, one must analyse the geometric self- similarity characteristics of the PC to produce a simplified set self-similar to the original, considering the premises of fractal geometry. It is recommended to create an automatic simplification process to minimize the subjectivity coming from the analyst.

THE VAULTING SYSTEM OF THE PALATINE CHAPEL: THE AACHEN CATHEDRAL WORLD HERITAGE SITE DOCUMENTATION PROJECT

Abstract. As part of a comprehensive survey and modelling project involving the Aachen Cathedral, this paper focuses on its oldest part, the Palatine Chapel, a domed octagonal hall supported by eight piers and enveloped by a sixteen-sided outer wall. Working on the data collected during an extensive 3D capturing campaign conducted between 2022 and 2023, this paper will focus on the conic vaults covering the ambulacrum of the 1st floor that represent quite a peculiar architectural and structural solution considering the VIII/IX century building know-how. In this framework, the Chapel's 3D point cloud has been analysed to extract the main 2D generative elements of the conic surfaces and then construct the corresponding 3D geometric models. These outputs have been compared against the captured point cloud to assess the differences between the actual vault data and the reconstructed ideal conic shapes. Finally, the method used to unfold the vaults' surfaces and create high-resolution ortho-images has been displayed.

BIM Search Engine: Effects of Object Relationships and Information Standards

As Building Information Modeling (BIM) models are getting bigger, with more information linked to geometrical 3D models, a dedicated BIM search engine is important. A BIM search engine was developed to examine the value of exploiting a 3D object’s topological relationships to other 3D objects when assessing that object’s relevance to a query. The impacts of two information standards, the Industry Foundation Classes (IFC) and Uniclass-2015, on information retrieval (IR) performance were also measured. The 3DIR Autodesk Revit toolset was used on a structural model of a 16-story building from an industry partner. The retrieval performance measures of Precision and Recall did not clearly highlight the benefit, although the increased relevance values of those objects deemed by experts to be relevant demonstrates the promise of such contextual measures. The effect of shifting from the native Revit file format to various standards was tested: IR performance was poor with the Uniclass-2015 dataset and was comparable to the Revit native model with the IFC model. Although not shown conclusively to improve retrieval performance, the contextual relevance measures presented in this paper are promising and constitute a significant original contribution. Future research is needed to fine-tune these measures and fully realize their potential.

Building Information Modelling for Application in Geotechnical Engineering

BIM (Building Information Modelling) is used to create and manage data during design, construction, and operation. It helps to effectively manage resources and optimize processes in the construction industry. Geotechnical engineering is one of the complex disciplines that may require BIM integration. Various data types must be provided in a timely manner and require real-time feedback, fast processing, and construction guidance. The first problem presented in the paper is the use of the traditional 2D-based method used by engineers for a particular task. It seems to be impractical when some adjustments are included. Another issue is the lack of communication between the workers. It poses the problem of information exchange and misunderstanding during the interpretation of technical data. This paper aims to find different integration techniques and steps for integrating geotechnical data into the BIM process. Methods used to examine the topic are qualitative research, literature review, and case studies. These methods were useful for studying the problems and introducing the soil information into the BIM application. Firstly, a case study with I-BIM was considered, and the BIM–FEM–BIM interaction was applied to introduce geotechnical information with Plaxis 3D. The results have shown that further development of BIM in infrastructure is needed. Another case study explored the present state of the geotechnical design in BIM and potential solutions. The new frameworks were recreated: many boreholes were imported to the BIM, and a 3D geometric model of the entire hill was created for the hill fortification structure with soil clogging. The last two studies in Malaysia modeled a 3D subsurface and used two geotechnical formats, AGS and CVS. The first includes more information than the second; however, the second can be used for a more generalized model. Overall, BIM–FEM interaction can be used as a geometric model for data transfer. However, the open data format of the Industry Foundation Class (IFC) or geotechnical data format of the AGS and CVS were suggested to be used for greater flexibility. It was also found that excessive information makes the model loaded and complex. Therefore, it was recommended that big data be summarized properly with minimal loss of necessary data. Further research is needed to understand data transmission schemes of geotechnical information better. Moreover, it is recommended to put all the strategies directly into practice to create a geotechnical design.

ПРОМИСЛОВИЙ ЦИКЛОННО-РОТАЦІЙНИЙ ПИЛОВЛОВЛЮВАЧ

Cyclone equipment is easy to manufacture and operate, versatile and economical, but its main drawback is the inability to capture finely dispersed dust. The article discusses the most important characteristics of the highly efficient industrial cyclonic rotary dust collector developed by us. The apparatus implements the principle of two-stage separation of heterogeneous dust-gas systems in a centrifugal field. In the first stage, working on the principle of a cyclone, and in the second - working on the principle of a rotary dust collector. During operation of the apparatus, a higher pressure on the periphery of the rotating part returns a concentrated dusty flow with a low gas flow to the cyclone part. Formed by a gap, between the cyclone body and the dividing cone, a closed circuit connects the output and input of the cyclone-rotational dust collector to each other. There is a negative feedback - an effective control mechanism for such complex probabilistic systems as gas heterogeneous curvilinear flows. Negative feedback stabilizes the processes occurring in such flows. The energy of the electric motor is used in the cyclone-rotational dust collector for the movement of dusty gas, concentration, coagulation of fine dust, its return from the rotary to the cyclone zone, dispersion and capture, with the aim of saving energy and material resources. The main task of the theory of centrifugal separation of dusty flows is to find the minimum diameter of a particle that has a practically perceptible relative radial velocity. Known deterministic models of centrifugal separation are either too simple and ignore many factors that determine the process, or in attempts to account for them are too cumbersome and difficult to solve, although they are also not free from various assumptions and limitations. The stochastic model takes into account the integral set of various influences on the radial drift of the Stokes particle from the center to the periphery of the swirling flow. The paper presents the results of the study of the structure of the three-dimensional two-phase gas flow with highly dispersed inclusions in cyclonic-rotary dust collectors using 3D geometric models with the aim of visualizing these flows using computer graphics methods. Numerical studies were carried out using the k-e model of turbulence with scaled wall functions.

Big Data in multiscale modelling: from medical image processing to personalized models

The healthcare industry is different from other industries–patient data are sensitive, their storage needs to be handled with care and in compliance with regulative, while prediction accuracy needs to be high. This fast expansion in medical image modalities and data collection leads to generation of so called “Big Data” which is time-consuming to be analyzed by medical experts. This paper provides an insight into the Big Data from the aspect of its role in multiscale modelling. Special attention is paid to the workflow, starting from medical image processing all the way to creation of personalized models and their analysis. A review of literature regarding Big Data in healthcare is provided and two proposed solutions are described–carotid artery ultrasound image processing and 3D reconstruction, and drug testing on personalized heart models. Related to the carotid artery ultrasound image processing, the starting point is ultrasound images, which are segmented using convolutional neural network U-net, while segmented masks were further used in 3D reconstruction of geometry. Related to the drug testing on personalized heart model, similar approach was proposed, images were used in creation of personalized 3D geometrical model that is used in computational modelling to determine pressure in the left ventricle before and after drug testing. All the aforementioned methodologies are complex, include Big Data analysis and should be performed using servers or high-performance computing. Future development of Big Data applications in healthcare domains offers a lot of potential due to new data standards, rapid development of research and technology, as well as strong government incentives.

Simulation of a Power Skiving Gear Cutting Process

Abstract The results of the computer simulation of the cutting process of gears by the power skiving method are presented. Following the kinematics of the process, a method for generating 3D geometric models of undeformed sheared layers were developed, and their parameters were analyzed. The influence of tool geometry and technological parameters on cutting conditions is investigated. The simulation results and calculation of the tangential force and torque on the tool axis and their influence on the error due to angular elastic deformation of the tool are given.

GRAPE: A Stochastic Geometrical 3D Model for Aggregates of Particles With Tunable 2D Morphological Projected Properties

The main goal of this paper is to propose a method for the 3D morphological characterization of compact aggregates using 2D image analysis. The problem at hand is the 3D morphometric characterization of latex nanoparticle aggregates. The only available information is 2D projection images of these aggregates, one projection per aggregate. In this context, a method to estimate the 3D morphological characteristics of an aggregate such as the Volume, Surface Area or Solidity from a single projection is proposed. This method is based on a stochastic geometric model called GRAPE (Geometrical Random Aggregation of Particles Emulation) and requires some strong assumptions, and in particular prior estimation of the volume. The model is based on an iterative packing of spheres of identical radii. For each iteration, a fitting function allows to reach objectives corresponding to the desired 2D properties (Area, Perimeter, Aspect Ratio, ...). In order to implement the method, an optimization process must be performed on two parameters of the model: the radius of the elementary particles r and an overlapping distance di. As a validation, this process will be applied to synthetic aggregates, themselves generated from the GRAPE model, then to a population of 104 synthetic aggregates, and finally to 3D printed aggregates whose 3D morphological properties are known thanks to an STL file, and whose projected images have been produced using a morphogranulometer. The results obtained show an excellent approximation of 2D properties by the GRAPE model, and very good results for 3D properties, with less than 5% error on average and less than 2% error in most cases.

Integration of NDT, 3D parametric modelling, and nonlinear numerical analysis for the seismic assessment of a vaulted stone-masonry historical building

This paper presents the integration of parametric modelling with NDT (NDT) and advanced numerical simulations for assessing the seismic response of an emblematic stone-masonry vaulted construction, the 16th-century church of the Society of Jesus located in Cusco, Peru. Revit parametric families allowed the creation of complex curved elements such as vaults and 3D geometrical models of the church based on a hybrid point cloud. The onsite survey results indicated that the main anomalies correspond to the presence of biological agents and cracking. In contrast, NDT allowed the estimation of the masonry material properties and the modal identification primarily of the towers. Finally, the application of pushover analyses allowed the estimation of the structure's maximum load capacity and post-peak behavoir. It was possible to determine that some collapse mechanisms (overturning of main façade and bell towers, and the generation of hinges in curved elements) can be activated in medium-strong earthquakes.

Investigation of Electromagnetic Scattering Mechanisms from Dynamic Oil Spill–Covered Sea Surface

The electromagnetic (EM) scattering mechanism of dynamic oil spill–covered sea surface area is studied in this manuscript. Utilizing the theory of oil film diffusion combined with oil spill volume, a three–dimensional (3D) geometric model of dynamic oil spill–covered sea surface area is established. The changes of the geometric structure and statistical characteristics of the sea surface area under the influence of the oil film are also analyzed. The thinner the oil spill thickness, the more sensitive it is to the sea surface slope and wave height. The facet-based hybrid model and the multilayer dielectric scattering method are combined to measure the EM scattering on the sea surface when covered by dynamic oil spills. In addition, the hydrodynamic and tilt effect are discussed. The EM scattering mechanism of the dynamic oil spill–covered sea surface area is revealed, and the tilt modulation is greater than the hydrodynamic effect in the dynamic process of an oil spill. It provides an important reference for the remote sensing monitoring of oil.