3D Modeling Method Research Articles

Extension of a 3D Geological Entity Modeling Method for Discontinuous Deformation Analysis

AbstractWith the development of 3D discontinuous deformation analysis (DDA) in precise stress fields and crack propagation problems, it has also demonstrated outstanding capabilities in solving continuous–discontinuous problems. However, currently, 3D DDA modeling primarily focuses on generating rock joint networks and developing 3D cutting algorithms. Correspondingly, 3D geological modeling methods are not yet mature, and establishing 3D models often demands substantial time. The lack of supporting preprocessing modeling methods and corresponding visual operation interfaces significantly hampers the development of 3D DDA. This method builds upon advanced research achievements in unmanned aerial vehicle oblique photography, 3D reconstruction, 3D cutting, computer graphics, and visualization program design. This research establishes a 3D geological entity modeling method for 3D DDA and constructs a comprehensive program using relevant C++ libraries and C language interfaces. In this method, a 3D geological model that incorporates geological elements such as strata and faults is initially established using non‐uniform rational B‐splines (NURBSs) surfaces as the boundary of the solid model. Subsequently, finite element meshing is applied, followed by corresponding topology transformation, resulting in a 3D block system model suitable for 3D DDA calculation. To cater for diverse application scenarios, continuous–discontinuous models integrated with subblocks and models of arbitrary polyhedra can be established. The proposed method has been validated through several typical modeling examples, showing its ability to rapidly and generate 3D high‐precision geological reality models suitable for 3D DDA calculations. Additionally, some techniques used in this method can be extended for modeling other numerical simulation methods, warranting further research.

Research on laser measurement point cloud preprocessing and 3D reconstruction technology for free-form surfaces.

Surface morphology measurement and reconstruction technology based on point cloud data is one of the key technologies for 3D information processing in the digital manufacturing industry and has been widely applied in fields such as reverse engineering, computer vision, and unmanned driving system navigation. A method for 3D modeling of aircraft-engine blade profiles based on laser measurement point cloud data is proposed to address the difficulties in measuring the 3D morphology of aircraft-engine blades and the low modeling accuracy. This method first preprocesses the measured point cloud and then uses Poisson's algorithm to reconstruct the blade surface in three dimensions based on the calculation of the point cloud normal. Through error statistical analysis, the overall reconstruction effect is good. The experimental results further validated the generality and effectiveness of this method.

Estimation of Longwave Radiation Intensity Emitted from Urban Obstacles in Each Direction Using Drone-Based Photogrammetry

Longwave radiation is a crucial factor affecting human thermal comfort and thermal stress, especially in outdoor spaces in summer, owing to the vast effect of longwave radiation emitted from high-heated asphalt roads, building walls, and automobiles. Although controlling the longwave radiation environment to improve thermal comfort in summer is crucial, the prediction of the longwave radiation environment is frequently conducted only at the assessment stage of the final proposal because of the high computational cost of radiation calculations and unsteady heat balance analysis considering multiple reflections. This is a significant constraint for the design of urban and architectural environments. A previous study proposed a method to rapidly estimate the longwave radiation environment based on a point-by-point method with longwave radiation intensity distributions of the heat sources. To use this method, 3D models of the geographical objects in urban areas, such as buildings and trees, must be accurately generated, and these models should have information on the longwave radiation emitted in each direction from each object. However, no specific examples of a 3D model and longwave radiation intensity distribution have been presented. In this study, a 3D modeling method for geographical objects in urban areas with longwave radiation information based on drones and photogrammetric techniques was utilized. Moreover, a 3D model of a small-scale building was generated. A longwave radiation intensity distribution was produced for the building. Based on the distribution data, the directional characteristics of longwave radiation were discussed, and the availability of the proposed method was assessed.

ALS-Based, Automated, Single-Tree 3D Reconstruction and Parameter Extraction Modeling

The 3D reconstruction of point cloud trees and the acquisition of stand factors are key to supporting forestry regulation and urban planning. However, the two are usually independent modules in existing studies. In this work, we extended the AdTree method for 3D modeling of trees by adding a quantitative analysis capability to acquire stand factors. We used unmanned aircraft LiDAR (ALS) data as the raw data for this study. After denoising the data and segmenting the single trees, we obtained the single-tree samples needed for this study and produced our own single-tree sample dataset. The scanned tree point cloud was reconstructed in three dimensions in terms of geometry and topology, and important stand parameters in forestry were extracted. This improvement in the quantification of model parameters significantly improves the utility of the original point cloud tree reconstruction algorithm and increases its ability for quantitative analysis. The tree parameters obtained by this improved model were validated on 82 camphor pine trees sampled from the Northeast Forestry University forest. In a controlled experiment with the same field-measured parameters, the root mean square errors (RMSEs) and coefficients of determination (R2s) for diameters at breast height (DBHs) and crown widths (CWs) were 4.1 cm and 0.63, and 0.61 m and 0.74, and the RMSEs and coefficients of determination (R2s) for heights at tree height (THs) and crown base heights (CBHs) were 0.55 m and 0.85, and 1.02 m and 0.88, respectively. The overall effect of the canopy volume extracted based on the alpha shape is closest to the original point cloud and best estimated when alpha = 0.3.

Evaluation of the urban heat island effect based on 3D modeling and planning indicators for urban planning proposals

ABSTRACT Urban planning plays an important role in the formation of urban space and microclimate. As a middle-level planning in the Chinese urban planning system, regulatory planning has a direct impact on the shaping of 3D urban space and can maximize the operability of urban planning. However, 3D space formation is not considered in the present preparation of regulatory plans, which leads to a misunderstanding of possibly formed 3D landscapes and microclimatic effects after the plan implementation. To support 3D visualization and quantitative analysis of the urban heat island effect (UHI) for regulatory planning, this study proposes a rule-based 3D modeling method to efficiently generate 3D models. The main elements of 3D models (terrain, building, road, vegetation, and land parcel) and their content were determined after analyzing the characteristics of 3D models in the regulatory plan. The 3D modeling process was constructed and combined with an UHI evaluation model through CGA programming. An index called heat island potential (HIP) was used as the UHI evaluation index and can be quantified using the correlation equations between planning indicators and HIP. The proposed method can support the planners to generate 3D models for a planning proposal, and simultaneously analyze 3D spatial effect and UHI.

An automatic method of siltation depth detection and 3D modeling in water-filled sewer pipelines based on sonar point clouds

Underground sewer pipeline inspection is essential for ensuring the safety and sustainability of urban infrastructure and improving residents’ quality of life. Traditional sewer pipeline inspection methods incur high manual costs. Therefore, this paper proposes an automated siltation depth identification and three-dimensional pipeline model reconstruction using an iterative farthest point removal fitting process based on a sonar point cloud. This method includes interpreting raw sonar data into point cloud data, point cloud preprocessing, iterative farthest point removal fitting process to fit pipeline profile and reverse interpolation of pipeline slices for three-dimensional model reconstruction. This method is validated in real-world applications, successfully calculating and annotating silt depth for pipeline slice profiles. The quantitative analysis shows an error in the estimated siltation proportion fluctuating within approximately 1%. This method also reconstructs the three-dimensional spatial model of siltation in the sewer pipeline, thereby providing effective technical support for engineering applications and reducing manual effort.

Methods for optimizing additive technologies using the example of loaded plastic products

The article describes the development of methods for optimizing additive technologies (FDM printing), taking into account the loads acting on the body in question, in order to save materials and reduce production time, within the framework of robotics, shipbuilding and the development of water, land and air drones. An analysis of existing modification methods to strengthen models was carried out. Various methods of modifying 3D models for printing have been tested. Based on the tests, a universal method for strengthening parts for three-dimensional printing was proposed and developed. The method is based on the principle of creating spherical cavities inside the part in place of the most loaded areas of the part, which then, when creating G-code programs for the printer, will be surrounded by outer plastic walls, creating a seal inside the part. Inventor and Ansys stress analysis and topology analysis are used to identify areas requiring optimization, based on the results of which 3D models of the most loaded areas, or models of areas requiring reinforcement, were created. A software and hardware complex has been created for modifying three-dimensional models for 3D printing and a software has been developed to automate the main parts of the processing technique for finished parts - creating cavities based on a three-dimensional model of loaded zones.

Distribution law of Chang 7 Member tight oil in the western Ordos Basin based on geological, logging and numerical simulation techniques

Abstract Fine characterization of oil plane distribution in highly heterogeneous tight sandstone is a prerequisite for efficient reservoir development. This study systematically evaluated the distribution characteristics of tight oil in the Chang 7 Member of the Western Ordos Basin using a large number of experimental tests, logging interpretation, and 3D modelling methods. The logging interpretation models of shale content, porosity, permeability, and oil saturation were constructed, and the effective reservoir was identified by establishing the intersection identification pattern of reservoir acoustic wave time difference and deep lateral resistivity. The 3D numerical simulation results showed that the tight oil is distributed between injection and production wells. The areas with high tight oil content are mainly distributed along the WE direction, and a series of high remaining oil zones are formed locally. Under the influence of long-term injection and production, a high permeability zone will be formed between wells, which is similar to a high-speed channel and will be flooded quickly, and a banded remaining oil retention zone will be formed around it. For the horizontal well flooding area, the water flooding range of the water injection well is small, and a large amount of remaining oil is enriched between water injection wells. Finally, the classification standard of the remaining oil in the Chang 72 sub-member of the study area is proposed, and then, the strategy of adopting different development and adjustment schemes according to different types of reservoirs is formed.

A method to integrate hydraulic structure models into 3D terrain models for irrigation infrastructure visualization

Seamless integration of three-dimensional (3D) terrain models and hydraulic structure models is a technical challenge in the construction of 3D virtual scenes for irrigation areas. This study proposes a level-of-detail (LOD)-based dynamic classification integration method for hydraulic structure models and 3D terrain models, called CM-D-LOD. Hydraulic structures are classified according to their point, line, and surface morphologies, as well as their dependence on or independence of the terrain into four categories: point-like hydraulic structures independent of terrain, line-like hydraulic structures dependent on terrain, surface-like hydraulic structures dependent on terrain, and surface-like hydraulic structures independent of terrain. By utilizing the proposed model classification integration method, a visualization management platform for virtual geographical environments of irrigation areas is developed, and experiments are conducted in the Zhuluo Ba Irrigation Area within the large economic zone along China’s eastern coast. Results demonstrate that the integration accuracy can be controlled between 0.2 and 0.7 m and that the 3D virtual scene of the irrigation area can be updated in real time. The proposed classification integration method transforms the traditional global model integration approach into a more efficient one, significantly improving the efficiency of constructing virtual geographical scenes for irrigation areas.

Comparison of compartmental analytical Blood-Oxygen-Level-Dependent functional Magnetic Resonance Imaging models against Monte Carlo simulations performed over cortical micro-angiograms.

Blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) arises from a physiological and physical cascade of events taking place at the level of the cortical microvasculature which constitutes a medium with complex geometry. Several analytical models of the BOLD contrast have been developed, but these have not been compared directly against detailed bottom-up modeling methods. Using a 3D modeling method based on experimentally measured images of mice microvasculature and Monte Carlo simulations, we quantified the accuracy of two analytical models to predict the amplitude of the BOLD response from 1.5 to 7T, for different echo time (TE) and for both gradient echo and spin echo acquisition protocols. We also showed that accounting for the tridimensional structure of the microvasculature results in more accurate prediction of the BOLD amplitude, even if the values for SO2 were averaged across individual vascular compartments. A secondary finding is that modeling the venous compartment as two individual compartments results in more accurate prediction of the BOLD amplitude compared with standard homogenous venous modeling, arising from the bimodal distribution of venous SO2 across the microvasculature in our data.

Integrated study of prediction and optimization performance of PBI-HTPEM fuel cell using deep learning, machine learning and statistical correlation

This paper uses 3D modeling and artificial intelligence methods to predict, and find optimal point in high-temperature proton exchange membrane (HTPEM) fuel cells. The main objective is to obtain maximum power and current density at the optimum node of the HTPEM fuel cell. The response surface method (RSM) is used to prevent excessive duplication and ensure adequate data coverage for determining input parameters. Also, for the first time, the correlation presented was compared with AI-based metaheuristic optimization methods i.e., including support vector regression (SVR), Gaussian process regression (GPR), and deep neural networks (DNN) with a dropout layer, alongside metaheuristic algorithms such as whale optimization algorithm (WOA), Grasshopper optimization algorithm (GOA), firefly algorithm (FF), and the genetic algorithm (GA). The results show that SVR, GPR, and DNN methods have excellent performance, with mean absolute percentage error (MAPE) of 0.81 % for DNN, 0.83 % for SVR, and 2.24 % for GPR. Most optimization algorithms exhibit errors below 8 %. The DNN-GOA, SVR-WOA, SVR-GA, and GPR-GOA algorithms have the lowest errors among them. Correlations have a lower computational cost for obtaining maximum power and current density at the optimum node compared to optimization algorithms, with a relative error of less than 6 % in most cases.

Research on 3D Geological and Numerical Unified Model of in Mining Slope Based on Multi-Source Data

As mining engineering progresses into the deep excavation phase, the intensification of high pressure, high temperature, strong disturbances, and complex geological conditions becomes increasingly prominent. Researchers perform stability analysis on the excavation area to reduce potential safety hazards during the extraction process. Developing a detailed numerical calculation model that accurately reflects the true geological structure is essential for numerical simulation analysis in mining engineering. Based on the excellent 3D geological modeling capabilities of 3D Mine software, this paper introduces a new 3D geological and numerical unified modeling method (3DMine-Rhino-HyperMesh) involving multi-software coupling and details the specific steps and concepts of this modeling approach. Subsequently, using a certain open-pit mine in Panzhihua as a backdrop, a detailed geological and numerical unified model is established, reflecting the true geological structure of the mining area, and the potential failure mechanisms of the mine slope are analyzed. The results indicate that the modeling method aligns well with the actual geological conditions, enhancing the grid quality of the numerical model and offering a new modeling approach for simulating and analyzing large complex geological entities in mining operations.

Computer Numerical Control Machining Simulations and Experimental Analysis of a Novel C-Gear

C-gear is a novel gear transmission system, with no existing special machining and cutting tools to realize its construction. In this study, we employed a 5-axis computer numerical control (CNC) machining center to construct a C-gear, while solving the prototype manufacturing problem at the experimental research stage. We deduced the C-gear mathematical model and studied the three-dimensional (3D) modeling methods based on the analysis of its generation principle. The C-gear processing technique using the 5-axis CNC machining center and the tool path designs were established using the VERICUT and MASTERCAM softwares, and the C-gears were experimentally constructed. The maximum overcut and residual of the gear positioning hole surface were both found to be 0.094 mm. Moreover, the maximum overcut on the tooth surface and root were 0.02 and 0.03 mm, respectively, and the maximum residual on both the tooth surface and root was 0.03 mm. The machining overcuts and residual amounts of the proposed method were better than those of reference [14]. The existing overcut and residual errors included the errors generated by surface fitting during the 3D modeling of the gears. Therefore, the machining errors of the physically constructed tooth surface are expected to be smaller than the theoretical value, suggesting a high feasibility of the proposed method to realize the machining of C-gears.

3D modelling method and application to a digital campus by fusing point cloud data and image data

ObjectiveThe use of single-source data for real-world 3D modelling currently faces problems such as deformation, pulling and fuzzy texture at the bottom of buildings in some feature models because of the lack of images. Moreover, LIDAR generates a huge amount of data, and the massive raw data processing and point cloud parsing puts high demands on the hardware arithmetic and algorithms. Aiming at the deficiencies and defects of the two data sources of inclined photogrammetry and airborne laser point cloud in the construction of high-quality and high-precision city-level 3D models. Methodsthis study uses a university library building as an example and proposes the main technical process and method of modelling after fusing the point cloud data acquired by inclined photogrammetry and 3D laser scanning technology. This is accomplished in the reconstruction stage of multi-source data fusion through data spatial alignment, coordinate system unification and data spatial integration. At the stage of multi-source data fusion and reconstruction, through data spatial alignment, coordinate system unification, point cloud coarse alignment and the iterative closest point (ICP) algorithm, a realistic 3D model of a building is constructed to verify the effectiveness of the modelling method. ResultsThe method can effectively improve the accuracy of the real-life 3D model, repair the deficiencies in the model and optimise the details of the model. It can also significantly improve the fineness of the tilt photography model and perfectly present the geometric and texture information of the building, making it a superior method for fine 3D reconstruction. ConclusionThis 3D reconstruction method of buildings, which integrates low-altitude inclined photogrammetry and airborne light detection and ranging (LiDAR), has high positional accuracy and can provide new methods and new ideas for the construction of digital campuses as well as for other engineering applications.

3D winding path modeling method with fiber overlap effect

The fibers will repeatedly cross and stack on the liner during the continuous winding process, which poses a challenge in creating accurate local and global structure models. To address the issue, a 3D winding path modeling method is proposed to simulate the fiber overlap effect. First, the initial path is offset equidistantly along the direction of width and thickness to construct the 3D path points. Then, by calculating the overlap thickness, the overlapped fibers are raised to the corresponding overlap thickness to eliminate interference in the 3D path points. Finally, a 3D winding path with the fiber overlap effect is obtained by solving the suspended points before and after the overlapping area to describe the behavior of fibers separating from the liner surface under tension. The proposed method is applied to various winding patterns and liner shapes, and the results show that the established 3D winding path can accurately simulate the fiber overlap effect and correspond with the actual local and global winding structures.

Applied methods for 3D modeling of radio engineering devices

The aim of the paper is to present applied methods for engineering 3D modeling of pyramidal and conical horn antennas, which can contribute to the implementation of experimental research, both in a simulation and in a physical environment. The practical results presented at each step of the model building process are represented by screenshots of the work screen showing the used toolbars from the Autodesk 123D Design software menu. This is done with a view to improving the quality of training in areas related to the study of radio engineering devices, such as telecommunications engineering and aerospace engineering, in which the design and manufacture of various types of antennas help to conduct independent empirical research by the trainees with the help of measuring equipment.

A 3D bedrock modeling method based on information mining of 2D geological map

A 3D bedrock modeling method based on information mining of 2D geological map

Neural Radiance Selector: Find the best 2D representations of 3D data for CLIP based 3D tasks

Representing the world in 3D space provides vivid texture and depth information. However, 3D datasets currently do not match the scale of 2D datasets. There is a growing trend in representing 3D data as multi-view 2D images and using large-scale 2D models, to solve 3D tasks. In this work, we present the Neural Radiance Selector, a method that automatically selects the optimal 2D representations of 3D data. Instead of indiscriminately sampling multi-view 2D images, we define the optimal 2D views as those capable of reconstructing the entire 3D scene with a conditional neural radiance field. We propose two distinct methods for 3D point cloud data and 3D implicit models to achieve faster inference. We demonstrate the efficacy of our methods in various 3D tasks, including zero-shot 3D point cloud classification, 3D implicit model classification, and language-guided NeRF editing.

РАЗРАБОТКА АППАРАТНОЙ ЧАСТИ И 3D-МОДЕЛИРОВАНИЕ КОРПУСА СИСТЕМЫ ТЕХНИЧЕСКОГО ЗРЕНИЯ ДЛЯ ОПРЕДЕЛЕНИЯ ПАРАМЕТРОВ КОРНЕПЛОДОВ САХАРНОЙ СВЁКЛЫ

One of the problems of the sugar industry is the high quality loss of sugar beet roots during storage. The development of a technical vision system is aimed at ensuring greater safety of raw materials during harvesting and storage by analyzing raw materials arriving at factories. The concepts of technical vision and technical vision systems and its components are described in the work. The process of distribution of trucks at the receiving point of sugar factories by humans is considered. The purpose of the article is formulated, which is to develop the hardware of the technical vision system, as well as 3D modeling of the body. All characteristics of all components for the technical vision system have been determined. Based on the characteristics, components were selected to create the system. A block diagram of a technical vision system has been developed and described, including a power supply, a twoposition toggle switch, a DC-DC converter unit, a fuse block, a controller, an eight-channel relay module, a galvanic isolation module, a USB splitter with active power supply, a USB-UART converter, spotlight, laser distance sensor, industrial camera, USB modem, LED display, thermostat, heating plate, case fan, thermistor. The 3D modeling method is the KOMPAS-3D environment, in which models such as the protective housing of the technical vision system and the bracket for mounting it on site were created. The case is printed from PLA plastic, as it has high hardness and density, as a result of which the likelihood of the case breaking is low. The bracket is made of heat treated steel for high strength and durability. Based on the results of the work performed, the technical vision system was sent for testing and identification of deficiencies to the receiving point of a sugar factory in the Kursk region.

Research on the Teaching Resource Construction System of Computer VR Online Interactive Experiment Platform for Mechanical Engineering Graphics

The introduction of three-dimensional design experiment teaching in engineering drawing teaching. The experimental platform of "network engineering drawing" is established, and the corresponding multimedia teaching software is developed using WebVR, ASP, database and other technologies. The 3D modeling method of the reducer is established by using UGNX and optimized accordingly. In order to solve the problem that UGNX mode introduces packet loss in the simulation system, the model and data are reconstructed separately. Using VisualStudio2019 as the development platform, the 3D modeling of the reducer is realized. The establishment of the engineering graphics design virtual simulation system helps enterprises to simulate operations before actual production and processing. It greatly improves production efficiency and reduces production costs.