3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Advancing Wound Filling Extraction on 3D Faces:An Auto-Segmentation and Wound Face Regeneration Approach

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network.Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions.To achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the trainedmodels.The selectedmodel demonstrates exceptional segmentation performance for complex 3D facial wounds.Furthermore,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study.Our method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous method.From this result,we use 3D printing technology to illustrate the shape of the wound filling.The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design.By automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient outcomes.Additionally,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants.Our source code is available at https://github.com/SIMOGroup/WoundFilling3D.

Numerical three-dimensional modeling of earthen dam piping failure

A physically-based numerical three-dimensional earthen dam piping failure model is developed for homogeneous and zoned soil dams.This model is an erosion model,coupled with force/moment equilibrium analyses.Orifice flow and two-dimensional(2D)shallow water equations(SWE)are solved to simulate dam break flows at different breaching stages.Erosion rates of different soils with different construction compaction efforts are calculated using corresponding erosion formulae.The dam's real shape,soil properties,and surrounding area are programmed.Large outer 2D-SWE grids are used to control upstream and downstream hydraulic conditions and control the boundary conditions of orifice flow,and inner 2D-SWE flow is used to scour soil and perform force/moment equilibrium analyses.This model is validated using the European Commission IMPACT(Investigation of Extreme Flood Processes and Uncertainty)Test#5 in Norway,Teton Dam failure in Idaho,USA,and Quail Creek Dike failure in Utah,USA.All calculated peak outflows are within 10%errors of observed values.Simulation results show that,for a V-shaped dam like Teton Dam,a piping breach location at the abutment tends to result in a smaller peak breach outflow than the piping breach location at the dam's center;and if Teton Dam had broken from its center for internal erosion,a peak outflow of 117851 m'/s,which is 81%larger than the peak outflow of 65120 m3/s released from its right abutment,would have been released from Teton Dam.A lower piping inlet elevation tends to cause a faster/earlier piping breach than a higher piping inlet elevation.

Review of Artificial Intelligence for Oil and Gas Exploration: Convolutional Neural Network Approaches and the U-Net 3D Model

Deep learning, especially through convolutional neural networks (CNN) such as the U-Net 3D model, has revolutionized fault identification from seismic data, representing a significant leap over traditional methods. Our review traces the evolution of CNN, emphasizing the adaptation and capabilities of the U-Net 3D model in automating seismic fault delineation with unprecedented accuracy. We find: 1) The transition from basic neural networks to sophisticated CNN has enabled remarkable advancements in image recognition, which are directly applicable to analyzing seismic data. The U-Net 3D model, with its innovative architecture, exemplifies this progress by providing a method for detailed and accurate fault detection with reduced manual interpretation bias. 2) The U-Net 3D model has demonstrated its superiority over traditional fault identification methods in several key areas: it has enhanced interpretation accuracy, increased operational efficiency, and reduced the subjectivity of manual methods. 3) Despite these achievements, challenges such as the need for effective data preprocessing, acquisition of high-quality annotated datasets, and achieving model generalization across different geological conditions remain. Future research should therefore focus on developing more complex network architectures and innovative training strategies to refine fault identification performance further. Our findings confirm the transformative potential of deep learning, particularly CNN like the U-Net 3D model, in geosciences, advocating for its broader integration to revolutionize geological exploration and seismic analysis.

A Semantic-Sensitive Approach to Indoor and Outdoor 3D Data Organization

Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.

Modeling Methods of 3D Model in Digital Twins

To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in the􀀀elds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

3D forward modeling and response characteristics of low-resistivity overburden of the CFS-PML absorbing boundary for ground-well transient electromagnetic method

This study used the stable and convergent Dufort-Frankel method to differentially discretize the diffusion equation of the ground-well transient electromagnetic secondary field.The absorption boundary condition of complex frequency-shifted perfectly matched layer(CFS-PML)was used for truncation so that the low-frequency electromagnetic wave can be better absorbed at the model boundary.A typical three-dimensional(3D)homogeneous half-space model was established and a low-resistivity cube model was analyzed under the half-space condition.The response patterns and drivers of the low-resistivity cube model were discussed under the influence of a low-resistivity overburden.The absorption boundary conditions of CFS-PML significantly affected the low-frequency electromagnetic waves.For a low-resistivity cube around the borehole,its response curve exhibited a single-peak,and the extreme point of the curve corresponded to the center of the low-resistivity body.When the low-resistivity cube was directly below the borehole,the response curve showed three extreme values(two high and one low),with the low corresponding to the center of the low-resistivity body.The total field response of the low-resistivity overburden was stronger than that of the uniform half-space model due to the low-resistivity shielding effect of electromagnetic waves.When the receiving-transmitting distance gradually increased,the effect of the low-resistivity overburden was gradually weakened,and the response of the low-resistivity cube was strengthened.It was affected by the ratio of the overburden resistivity to the resistivity of the low-resistivity body.

3D Modeling and Estimation of the Tonnage of the Granite Quarry of Linguésso (North-West of Côte d’Ivoire) by Electrical Methods

A survey and evaluation was carried out on a potential granitoid quarry site in the locality of Linguésso (North West of Ivory Coast) with the aim of identifying and estimating the quantity of exploitable granite based on the electrical resistivity methods. The combination of electrical trailing, sounding and tomography techniques allowed the determination of the characteristics of the rock deposit, namely the electrical signature (between 19,259 Ωm and 86,316 Ωm), the extension (N90°), the rooting (between 0 and 45 m) and the fracturing (between N14° and N160°) of the granitic formation sought. The modeling resulted in an estimated mineable rock volume of 2,936,250 m3 providing a production quantity of 7,927,875 tonnes.

Effect of the mineral spatial distribution heterogeneity on the tensile strength of granite:Insights from PFC3D-GBM numerical analysis

The mechanical characteristics of crystalline rocks are affected by the heterogeneity of the spatial distribution of minerals.In this paper,a novel three-dimensional(3D)grain-based model(GBM)based on particle flow code(PFC),i.e.PFC3D-GBM,is proposed.This model can accomplish the grouping of mineral grains at the 3D scale and then filling them.Then,the effect of the position distribution,geometric size,and volume composite of mineral grains on the cracking behaviour and macroscopic properties of granite are examined by conducting Brazilian splitting tests.The numerical results show that when an external load is applied to a sample,force chains will form around each contact,and the orientation distribution of the force chains is uniform,which is independent of the external load level.Furthermore,the number of high-strength force chains is proportional to the external load level,and the main orientation distribution is consistent with the external loading direction.The main orientation of the cracks is vertical to that of the high-strength force chains.The geometric size of the mineral grains controls the mechanical behaviours.As the average grain size increases,the number of transgranular contacts with higher bonding strength in the region connecting both loading points increases.The number of high-strength force chains increases,leading to an increase in the stress concentration value required for the macroscopic failure of the sample.Due to the highest bonding strength,the generation of transgranular cracks in quartz requires a higher concentrated stress value.With increasing volume composition of quartz,the number of transgranular cracks in quartz distributed in the region connecting both loading points increases,which requires many high-strength force chains.The load level rises,leading to an increase in the tensile strength of the numerical sample.

Modeling and simulation of solvent behavior and temperature distribution within long stick propellants with large web thickness undergoing drying

Drying is a complicated physical process which involves simultaneous heat and mass transfer in the removal of solvents inside propellants.Inappropriate drying techniques may result in the formation of a hard skin layer near the surface to block the free access of most solvent through for long stick propellants with large web thickness,which lead to lower drying efficiency and worse drying quality.This study aims to gain a comprehensive understanding of drying process and clarify the mechanism of the blocked layer near the propellant surface.A new three-dimensional coupled heat and mass transfer(3D-CHMT)model was successfully developed under transient conditions.The drying experiment results show that the 3DCHMT model could be applied to describe the drying process well since the relative error of the content of solvent between simulation and experiment values is only 5.5%.The solvent behavior simulation demonstrates that the mass transfer process can be divided into super-fast(SF)and subsequent minorfast(MF)stages,and the SF stage is vital to the prevention of the blocked layer against the free access for solvent molecules inside propellant grains.The effective solvent diffusion coefficient(Deff)of the propellant surface initially increases from 3.4×10^(-6)to 5.3×10^(-6)m^(2)/s as the temperature increases,and then decreases to 4.1×10^(-8)m^(2)/s at 60-100 min.The value of Deffof surface between 0-1.4 mm has a unique trend of change compared with other regions,and it is much lower than that of the internal at100 min under simulation conditions.Meanwhile,the temperature of the propellant surface increases rapidly at the SF stage(0-100 min)and then very slowly thereafter.Both the evolution of Deffand temperature distribution demonstrate that the blocked layer near the propellant surface has been formed in the time period of approximately 0-100 min and its thickness is about 1.4 mm.To mitigate the formation of blocked layer and improve its drying quality of finial propellant products effectively,it should be initially dried at lower drying temperature(30-40℃)in 0-100 min and then dried at higher drying temperature(50-60℃)to reduce drying time for later drying process in double base gun propellants.The present results can provide theoretical guidance for drying process and optimization of drying parameters for long stick propellants with large web thickness.

Preoperative 3D reconstruction and fluorescent indocyanine green for laparoscopic duodenum preserving pancreatic head resection:A case report

BACKGROUND Duodenum-preserving pancreatic head resection(DPPHR)is the choice of surgery for benign or low-grade malignant tumors of the pancreatic head.Laparoscopic DPPHR(LDPPHR)procedure can be improved by preoperative 3D model reconstruction and the use of intravenous indocyanine green fluorescent before surgery for real-time navigation with fluorescent display to guide the surgical dissection and prevention of from injury to vessels and biliary tract.CASE SUMMARY Here we report the successful short-and long-term outcomes after one year following LDPPHR for a 60-year lady who had an uneventful recovery and was discharged home one week after the surgery.CONCLUSION There was no bile leakage or pancreatic leakage or delayed gastric emptying.The histopathology report showed multiple cysts in the pancreatic head and localized pancreatic intraepithelial tumor lesions.The resected margin was free of tumor.

Building 3D CityGML models of mining industrial structures using integrated UAV and TLS point clouds

Mining industrial areas with anthropogenic engineering structures are one of the most distinctive features of the real world.3D models of the real world have been increasingly popular with numerous applications,such as digital twins and smart factory management.In this study,3D models of mining engineering structures were built based on the CityGML standard.For collecting spatial data,the two most popular geospatial technologies,namely UAV-SfM and TLS were employed.The accuracy of the UAV survey was at the centimeter level,and it satisfied the absolute positional accuracy requirement of creat-ing all levels of detail(LoD)according to the CityGML standard.Therefore,the UAV-SfM point cloud dataset was used to build LoD 2 models.In addition,the comparison between the UAV-SfM and TLS sub-clouds of facades and roofs indicates that the UAV-SfM and TLS point clouds of these objects are highly consistent,therefore,point clouds with a higher level of detail and accuracy provided by the integration of UAV-SfM and TLS were used to build LoD 3 models.The resulting 3D CityGML models include 39 buildings at LoD 2,and two mine shafts with hoistrooms,headframes,and sheave wheels at LoD3.

Effects of 3D deformation and nonlinear stress–strain relationship on the Brazilian test for a transversely isotropic rock

To improve the accuracy of indirect tensile strength for a transversely isotropic rock in the Brazilian test, this study considered the three-dimensional (3D) deformation and the nonlinear stress–strain relationship. A parametric study of a numerical Brazilian test was performed for a general range of elastic constants, revealing that the 3D modeling evaluated the indirect tensile strength up to 40% higher than the plane stress modeling. For the actual Asan gneiss, the 3D model evaluated the indirect tensile strength up to 10% higher and slightly enhanced the accuracy of deformation estimation compared with the plane stress model. The nonlinearity in stress–strain curve of Asan gneiss under uniaxial compression was then considered, such that the evaluated indirect tensile strength was affected by up to 10% and its anisotropy agreed well with the physical intuition. The estimation of deformation was significantly enhanced. The further validation on the nonlinear model is expected as future research.

Building Information Modeling-Based Secondary Development System for 3D Modeling of Underground Pipelines

Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.

A New Three-Dimensional(3D)Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

Background:Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes.The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case.Methods:We performed the prospective cohort study which included 29 children with congenital heart defects.The hearts and the great vessels were modeled and printed out.Measurements of the same cardiac areas were taken in the same planes and points at multislice computed tomography images(group 1)and on printed 3D models of the hearts(group 2).Pre-printing treatment of the multislice computed tomography data and 3D model preparation were performed according to a newly developed algorithm.Results:The measurements taken on the 3D-printed cardiac models and the tomographic images did not differ significantly,which allowed us to conclude that the models were highly accurate and informative.The new algorithm greatly simplifies and speeds up the preparation of a 3D model for printing,while maintaining high accuracy and level of detail.Conclusions:The 3D-printed models provide an accurate preoperative assessment of the anatomy of a defect in each case.The new algorithm has several important advantages over other available programs.They enable the development of customized preliminary plans for surgical repair of each specific complex congenital heart disease,predict possible issues,determine the optimal surgical tactics,and significantly improve surgical outcomes.

Structural Variation between the Western and Eastern Kuqa Fold-and-thrust Belt,China:Insights from Seismic Interpretation and Analog Modeling

The Kuqa fold-and-thrust belt exhibits apparent structural variation in the western and eastern zone.Two salt layer act as effective decollements and influence the varied deformation.In this study,detailed seismic interpretations and analog modeling are presented to construct the suprasalt and subsalt structures in the transfer zone of the middle Kuqa and investigate the influence of the two salt layers.The results reveal that the relationship of the two salt layers changes from separated to connected,and then overlapped toward the foreland in the transfer zone.Different structural models are formed in the suprasalt and subsalt units due to the interaction of the two salt layers.The imbricate thrust faults form two broom-like fault systems in the subsalt units.The suprasalt units develop detached folds terminating toward the east in the region near the orogenic belt.Whereas,two offset anticlines with different trends develop at the frontal edge of the lower salt layer and the trailing edge of the upper salt layer,respectively.According to exploration results in this region,the relationship between suprasalt and subsalt structures has an influence on hydrocarbon accumulation.We believe that the connected deformation contains high-risk plays while the decoupled deformation contains well-preserved plays.

3D Model Occlusion Culling Optimization Method Based on WebGPU Computing Pipeline

Nowadays,Web browsers have become an important carrier of 3D model visualization because of their convenience and portability.During the process of large-scale 3D model visualization based on Web scenes with the problems of slow rendering speed and low FPS(Frames Per Second),occlusion culling,as an important method for rendering optimization,can remove most of the occluded objects and improve rendering efficiency.The traditional occlusion culling algorithm(TOCA)is calculated by traversing all objects in the scene,which involves a large amount of repeated calculation and time consumption.To advance the rendering process and enhance rendering efficiency,this paper proposes an occlusion culling with three different optimization methods based on the WebGPU Computing Pipeline.Firstly,for the problem of large amounts of repeated calculation processes in TOCA,these units are moved from the CPU to the GPU for parallel computing,thereby accelerating the calculation of the Potential Visible Sets(PVS);Then,for the huge overhead of creating pipeline caused by too many 3D models in a certain scene,the Breaking Occlusion Culling Algorithm(BOCA)is introduced,which removes some nodes according to building a Hierarchical Bounding Volume(BVH)scene tree to reduce the overhead of creating pipelines;After that,the structure of the scene tree is transmitted to the GPU in the order of depth-first traversal and finally,the PVS is obtained by parallel computing.In the experiments,3D geological models with five different scales from 1:5,000 to 1:500,000 are used for testing.The results show that the proposed methods can reduce the time overhead of repeated calculation caused by the computing pipeline creation and scene tree recursive traversal in the occlusion culling algorithm effectively,with 97%rendering efficiency improvement compared with BOCA,thereby accelerating the rendering process on Web browsers.

3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV Remote Sensing

The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote sensing.Considering the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data.Using professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is evaluated.Based on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water body.The results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.

Survey of lightweighting methods of huge 3D models for online Web3D visualization

Background With the rapid development of Web3D technologies, the online Web3D visualization, particularly for complex models or scenes, has been in a great demand. Owing to the major conflict between the Web3D system load and resource consumption in the processing of these huge models, the huge 3D model lightweighting methods for online Web3D visualization are reviewed in this paper. Methods By observing the geometry redundancy introduced by man-made operations in the modeling procedure, several categories of light-weighting related work that aim at reducing the amount of data and resource consumption are elaborated for Web3D visualization. Results By comparing perspectives, the characteristics of each method are summarized, and among the reviewed methods, the geometric redundancy removal that achieves the lightweight goal by detecting and removing the repeated components is an appropriate method for current online Web3D visualization. Meanwhile, the learning algorithm, still in improvement period at present, is our expected future research topic. Conclusions Various aspects should be considered in an efficient lightweight method for online Web3D visualization, such as characteristics of original data, combination or extension of existing methods, scheduling strategy, cache man-agement, and rendering mechanism. Meanwhile, innovation methods, particularly the learning algorithm, are worth exploring.

Integrating deep learning and logging data analytics for lithofacies classification and 3D modeling of tight sandstone reservoirs

The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience of geologists.This approach has strong subjectivity,low efficiency,and high uncertainty.This uncertainty may be one of the key factors affecting the results of 3 D modeling of tight sandstone reservoirs.In recent years,deep learning,which is a cutting-edge artificial intelligence technology,has attracted attention from various fields.However,the study of deep-learning techniques in the field of lithofacies classification has not been sufficient.Therefore,this paper proposes a novel hybrid deep-learning model based on the efficient data feature-extraction ability of convolutional neural networks(CNN)and the excellent ability to describe time-dependent features of long short-term memory networks(LSTM)to conduct lithological facies-classification experiments.The results of a series of experiments show that the hybrid CNN-LSTM model had an average accuracy of 87.3%and the best classification effect compared to the CNN,LSTM or the three commonly used machine learning models(Support vector machine,random forest,and gradient boosting decision tree).In addition,the borderline synthetic minority oversampling technique(BSMOTE)is introduced to address the class-imbalance issue of raw data.The results show that processed data balance can significantly improve the accuracy of lithofacies classification.Beside that,based on the fine lithofacies constraints,the sequential indicator simulation method is used to establish a three-dimensional lithofacies model,which completes the fine description of the spatial distribution of tight sandstone reservoirs in the study area.According to this comprehensive analysis,the proposed CNN-LSTM model,which eliminates class imbalance,can be effectively applied to lithofacies classification,and is expected to improve the reality of the geological model for the tight sandstone reservoirs.