3D Model Data Research Articles

ESTABLISHING INDOOR SUBSPACING REQUIREMENTS OF AN LOD (LEVEL OF DETAIL) MODEL FOR GENERATING NETWORK-BASED TOPOLOGICAL DATA

Abstract. Nowadays, the complexity of structures in urban environments and the interest in location-based applications increase simultaneously. Along with this is the rise in demand for the firm establishment of data models representing these spaces. Establishing network models that portray topological relationships of space have strengthened support for navigation applications. However, researchers have revisited the limitations of existing standards. As analogous standards have specifications for expressing space at various scales, most have focused on outdoor space or the geometric aspect. Hence, this paper proposes subspacing requirements for a Level of Detail (LOD) model for network-based topological data. We examine various constraints that influence space partition and align these with various application cases for indoor navigation. Through these, we investigate appropriate space subdivision approaches for each level according to applicable constraints and recommended applications. This study poses as an initial study towards establishing a general framework for implementing a 3D hierarchical network-based topological data model.

Geothermal Reservoir Identification in Way Ratai Area Based on Gravity Data Analysis

Gravity research in the Way Ratai geothermal prospect area was conducted to determine geothermal reservoirs, heat sources, and the structure of the geothermal reservoir. The research carried out includes 3D inversion modeling of gravity data. The Bouguer anomaly in the study area has 50 mGal to 120 mGal with low anomalies located in the southeast (Ketang and Kelagian), Northeast (Gedong Air, Sungai Langka, Gunung Betung) areas, and in the Pesawaran mountain area. The high anomaly is in Merawan – Hanuberak – Padang Cermin, Sumbersari and Kaliawi. The horizontal gravity gradient map analysis shows a pattern of fault structure trending northwest-southeast and southwest-northeast, according to the main fault structure in the area. 3D inversion modeling obtains a density distribution between 1.8 g/cc to 3g/cc with a low-density distribution in the south, Mount Pesawaran/Ratai, Gunung Betung, and Sidoharum. The location of the manifestation is 9 km southeast of the Mount Ratai/Pesawaran summit. The existence of geothermal reservoirs is estimated to be in the Lubuk Badak and Miwung Hills areas which are located between the peaks of Mount Ratai/Pesawaran and geothermal manifestations. This is supported by the low-density distribution in the area and the resistivity map from audio-magnetotelluric data.

Development of 3D printing entity slicing software

Based on STL (stereo lithography) format file and with Microsoft Visual C++ 6.0 programming language, a 3D printing slicing software appropriate for the surface strengthening of the parts has been developed, which includes three functions: 3D model import, model slicing and data export. Through the grouping of STL model triangle facets before slicing, the judgment times of the relationship between the triangle facets and the cutting planes are reduced, and the slicing efficiency is improved. Aiming at the fact that the surface should be strengthened when the part is formed by using of 3D printing process, the function of identifying and marking the surface of the geometric entity is accomplished in the slicing software, which can strengthen the surface of the part according to the user’s requirements. The developed slicing software can provide an entity slicing file for 3D printing equipment. The related functions can be adjusted and improved according to user’s needs, which makes the software convenient and flexible to use.

SAP-Net: A Simple and Robust 3D Point Cloud Registration Network Based on Local Shape Features.

Point cloud registration is a key step in the reconstruction of 3D data models. The traditional ICP registration algorithm depends on the initial position of the point cloud. Otherwise, it may get trapped into local optima. In addition, the registration method based on the feature learning of PointNet cannot directly or effectively extract local features. To solve these two problems, this paper proposes SAP-Net, inspired by CorsNet and PointNet++, as an optimized CorsNet. To be more specific, SAP-Net firstly uses the set abstraction layer in PointNet++ as the feature extraction layer and then combines the global features with the initial template point cloud. Finally, PointNet is used as the transform prediction layer to obtain the six parameters required for point cloud registration directly, namely the rotation matrix and the translation vector. Experiments on the ModelNet40 dataset and real data show that SAP-Net not only outperforms ICP and CorsNet on both seen and unseen categories of the point cloud but also has stronger robustness.

Development of Novel Soft Materials with Mechanical Anisotropy using 3D Printed Lattice Structures and Application for Soft Robots

Introduction: In recent years, soft robots made of soft, highly elastic materials have been attracting attention as an alternative to conventional robots made of hard rigid bodies such as metal. Soft robots are expected to play an active role in fields where there are many opportunities to interact with humans, such as collaborative work, nursing care, and welfare. Soft robots are often made of polymers such as rubber, gel, and plastic. By controlling the properties of flexible materials, such as large elastic deformation, elastic modulus, and viscoelasticity, it is possible to design and develop functionalities that take advantage of the softness, which has not been possible with conventional robot technology. In this study, we investigated how to control the physical properties of soft matter by compositing the 3D printed lattice structure of soft matter with silicone rubber. Experiments: 3D model data of the lattice, called “igeta structure” (beam and girder structure) was designed using OpenSCAD, script-based 3D CAD software. Five 3D models of lattice structures with different crossing angles were created and they were 3D printed with an FDM 3D printer using Thermoplastic polyurethane (TPU) material. The printed lattice models were placed in a 20mm cubic mold, and silicone rubber (Ecoflex00-30) was poured into the mold and cured. Compression tests in three orthogonal axes (X, Y, and Z) were performed on these five models using an ORIENTEC STA-1150 universal testing machine. Results and discussion: Figure 1 shows the Young’s modulus of igeta structure and silicone composite models calculated from compression tests. Anisotropy of Young’s modulus varied depending on the crossing angles of the lattice structure. In particular, the Young's modulus in the x-axis is remarkably changed. These results confirm that it is possible to change the anisotropy of the elastic material depending on the shape of the lattice structure. Its will be useful for designing soft robots and confirming their functions. Figure 1

A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

Collection of 3D data in archaeology is a long-standing practice. Traditionally, the focus of these data has been visualization as opposed to analysis. Three-dimensional data are often recorded during archaeological excavations, with the provenience of deposits, features, and artefacts documented by a variety of methods. Simple analysis of 3D data includes calculating the volumes of bound entities, such as deposits and features, and determining the spatial relationships of artifacts within these. The construction of these volumes presents challenges that originate in computer-aided design (CAD) but have implications for how data are used in archaeological analysis. We evaluate 3D construction processes using data from Waitetoke, Ahuahu Great Mercury Island, Aotearoa, New Zealand. Point clouds created with data collected by total station, photogrammetry, and terrestrial LiDAR using simultaneous localization and mapping (SLAM) are compared, as well as different methods for generating surface area and volumes with triangulated meshes and convex hulls. The differences between methods are evaluated and assessed in relation to analyzing artifact densities within deposits. While each method of 3D data acquisition and modeling has advantages in terms of accuracy and precision, other factors such as data collection and processing times must be considered when deciding on the most suitable.

Parametric studies on laser additive manufacturing of copper on stainless steel

Laser additive manufacturing using directed energy deposition (LAM-DED) technique is one of the recent techniques for fabricating engineering components directly from 3D CAD model data using high power lasers. In this respect, LAM-DED of copper (Cu) and stainless steel (SS) is an enduring research area. However, LAM-DED of Cu is challenging due to higher thermal conductivity, lower absorption to infrared radiation and oxide formation tendency. The present work reports an experimental investigation to evaluate the effect of process parameters on the track geometry, contact angle, inter-diffusion and micro-hardness of Cu tracks deposited on SS 304L substrate using LAM-DED. Analysis of variance is used to estimate the contribution percentage of process parameters on the track geometry. Further, Cu bulk structures are deposited at an identified combination of process parameters and they are subjected to optical microscopy for microstructural characterisation. Further, finite-element-based numerical simulation is performed to understand the temperature distribution during the processing of Cu bulk structures on SS304L and the temperature results are co-related with the microstructural transformation during the processing. This investigation paves a way to understand the effect of processing parameters for building Cu bulk structures on SS Substrate using LAM-DED.

Generating a three-dimensional measuring scene for the forest sector as based on modern geodetic technologies

Modern geodetic technologies of gathering three-dimensional spatial data incorporate terrestrial laser scanning and aerial photo survey from unmanned aerial vehicles. The combination of these technologies and joint result of survey provide the data of 3D point model and accurate information on trunks and crowns of individual trees. The paper examines the experiment with the application of method of formation of 3D measuring scene in the form of dense cloud of points combining the results of terrestrial laser scanning and materials of photogrammetric processing of UAV-provided data. The method eliminates basic shortcomings of each technology, enhances their advantages, and opens the way to the compilation of more representative 3D measuring scenes. A specific advantage of the method is the outcropping of detailed information on the form, size and condition of individual tree crowns. This option finds a practical application in landscape evaluation and design, remote measuring of trunk parameters excluding the felling of model trees for the compilation of regional timber account tables. The closest perspectives of method development are related to increasing the accuracy of combined survey by specifying flight missions and working with the light regime under forest canopy.

Fabrication of personalized lithophane via additive manufacturing

Industry 4.0 encourages the combination of latest technologies and manufacturing systems. The Additive Manufacturing (AM) may play a fundamental role in Industry 4.0 as it has capability of turning a 3D model data into a product without much human intervention. Moreover, the requirement for eliminated tools and fixtures and material waste make it suitable for industry of the future. The 3D model data, generated using modeling software is utilized in order to fabricate a three-dimensional object. However, the modeling software has some limitations regarding the conversion of the 2D digital image into a 3D model. It makes difficult direct additive manufacturing of 2D digital image. Although, there are some online resources available for this purpose. However, the detailed discussion on the algorithm is not available. Therefore, this article presents an approach for additive manufacturing of lithophane using 2D digital image. It mainly concentrates on the development of Graphical User Interface (GUI) for generating point cloud data and STL using a 2D digital image in MATLAB environment. The developed algorithm is discussed in detail for lithophane fabrication. The proposed approach takes 2D digital image from the user and converts it into 3D model data. Furthermore, the material deposition tool path is also prepared using generated 3D model data. Finally, the proposed approach is validated and tested by performing additive manufacturing. The obtained results have shown the conformity between the additive manufactured lithophane and given a 2D digital image. The obtained results of the current study may be useful in industry 4.0 for fashion and jewelry products.

Three-Dimensional Diffusion Model in Sports Dance Video Human Skeleton Detection and Extraction

The research in this paper mainly includes as follows: for the principle of action recognition based on the 3D diffusion model convolutional neural network, the whole detection process is carried out from fine to coarse using a bottom-up approach; for the human skeleton detection accuracy, a multibranch multistage cascaded CNN structure is proposed, and this network structure enables the model to learn the relationship between the joints of the human body from the original image and effectively predict the occluded parts, allowing simultaneous prediction of skeleton point positions and skeleton point association information on the one hand, and refinement of the detection results in an iterative manner on the other. For the combination problem of discrete skeleton points, it is proposed to take the limb parts formed between skeleton points as information carriers, construct the skeleton point association information model using vector field, and consider it as a feature, to obtain the relationship between different skeleton points by using the detection method. It is pointed out that the reorganization problem of discrete skeleton points in multiperson scenes is an NP-Hard problem, which can be simplified by decomposing it into a set of subproblems of bipartite graph matching, thus proposing a matching algorithm for discrete skeleton points and optimizing it for the skeleton dislocation and algorithm problems of human occlusion. Compared with traditional two-dimensional images, audio, video, and other multimedia data, the 3D diffusion model data describe the 3D geometric morphological information of the target scene and are not affected by lighting changes, rotation, and scale transformation of the target and thus can describe the realistic scene more comprehensively and realistically. With the continuous updating of diffusion model acquisition equipment, the rapid development of 3D reconstruction technology, and the continuous enhancement of computing power, the research on the application of 3D diffusion model in the detection and extraction of a human skeleton in sports dance videos has become a hot direction in the field of computer vision and computer graphics. Among them, the feature detection description and model alignment of 3D nonrigid models are a fundamental problem with very important research value and significance and challenging at the same time, which has received wide attention from the academic community.

Application of 3D Information Expression Method of Ancient Buildings Based on Point Cloud Data and BIM

Recently, with the continuous development of technologies such as smart cities and virtual reality, the demand for 3D geospatial data is also growing. 3D laser scanning technology can be used to collect 3D geospatial data, create 3D scenes and collect other data to obtain outstanding Visual effects and scalability. This article puts forward the application research of ancient architecture three-dimensional information expression method based on point cloud data and BIM. Using 3D point cloud modeling and surface reconstruction of 3D point cloud data, in the form of a grid of a given point cloud, a 3D point cloud modeling is used to reconstruct a 3D model based on point cloud data and perform surface reconstruction of 3D point cloud data. process. The 3D digital protection of ancient Chinese buildings is an important way to inherit the essence of Chinese architecture. It helps to record the structural shape and historical, cultural and scientific value of ancient buildings, and provides accurate data support for the maintenance and repair of buildings. Accurate data support for building repairs and maintenance has improved the accuracy and visibility of information by 50% for the protection of ancient buildings.

Integrating Normal Vector Features into an Atrous Convolution Residual Network for LiDAR Point Cloud Classification

LiDAR point clouds are rich in spatial information and can effectively express the size, shape, position, and direction of objects; thus, they have the advantage of high spatial utilization. The point cloud focuses on describing the shape of the external surface of the object itself and will not store useless redundant information to describe the occupation. Therefore, point clouds have become the research focus of 3D data models and are widely used in large-scale scene reconstruction, virtual reality, digital elevation model production, and other fields. Since point clouds have various characteristics, such as disorder, density inconsistency, unstructuredness, and incomplete information, point cloud classification is still complex and challenging. To realize the semantic classification of LiDAR point clouds in complex scenarios, this paper proposes the integration of normal vector features into an atrous convolution residual network. Based on the RandLA-Net network structure, the proposed network integrates the atrous convolution into the residual module to extract global and local features of the point clouds. The atrous convolution can learn more valuable point cloud feature information by expanding the receptive field. Then, the point cloud normal vector is embedded in the local feature aggregation module of the RandLA-Net network to extract local semantic aggregation features. The improved local feature aggregation module can merge the deep features of the point cloud and mine the fine-grained information of the point cloud to improve the model’s segmentation ability in complex scenes. Finally, to resolve the imbalance of the distribution of the various categories of point clouds, the original loss function is optimized by adopting a reweighted method to prevent overfitting so that the network can focus on small target categories in the training process to effectively improve the classification performance. Through the experimental analysis of a Vaihingen (Germany) urban 3D semantic dataset from the ISPRS website, it is verified that the proposed algorithm has a strong generalization ability. The overall accuracy (OA) of the proposed algorithm on the Vaihingen urban 3D semantic dataset reached 97.9%, and the average reached 96.1%. Experiments show that the proposed algorithm fully exploits the semantic features of point clouds and effectively improves the accuracy of point cloud classification.

A market assessment of additive manufacturing potential for the aerospace industry

The additive manufacturing (AM) process, also known as 3D printing, is a process of layer-by-layer material deposition to produce desired parts from 3D model data, as opposed to formative manufacturing methodologies and subtractive manufacturing processes. The AM is one of the most well-suited manufacturing technologies for the aerospace industry where lightweight and unique-shaped components are demanded as this technology produces lightweight and cost-efficient aircraft components with unique geometries. The AM also allows manufacturers to release products with a smaller number of components onto the market; enabling rapid prototyping with less material waste compared to subtractive manufacturing processes. Therefore, during the last two decades, this technology has received research interest and has been adopted by the aerospace industry, resulting in a significant AM market share compared to other sectors. The aerospace industry has been one of the dominant sectors of the global AM market and is forecasted to be one of the leading contributors to the rapidly changing and competitive global AM market. This study reviews the assessment of the recent and forecasted future global aerospace AM market, linked with the historic and forecasted data, and the adoption of this technology, historic and forecasted global aerospace AM market trends, and the impact of Covid-19 pandemic on the current state of the global aerospace sector. Related charts based on historic and forecasted data are given to summarise the global AM market trends and assessment of AM potential for the aerospace industry in this study.

Guest Editorial: Building Trust in Additive Manufacturing, Layer by Layer

Nearly three-quarters (71%) of senior oil and gas professionals have sharpened their focus on digitalization over the past year, according to a 2021 survey by DNV (DNV Outlook). The pandemic has not only increased attention on how digital solutions can make organizations more adaptable and cost efficient, it has also forced companies to discard the normal rules and become more open to change. While data collaboration, cloud-based applications, and remote surveillance top the investment priorities for the year ahead, a growing number of respondents (7%) see additive manufacturing (AM)—the industry equivalent of 3D printing—on their spending list. As an emerging technology, AM uses 3D model data to fabricate parts, enabling, among other benefits, significant cost and time savings in contrast to many traditional manufacturing methods, where the final parts are machined out of a pre-made form. Its purpose is to alleviate and avoid long, expensive production shutdowns and reduce supply chain carbon footprints. Building trust in “printed” parts is key to unlocking this potential. Rapid, Reliable Reproduction The global AM market is expected to reach $350 billion by 2035 (DailyAlts 2021). The technology also has the potential to be enhanced by—or in the other direction, augment—other digital solutions, given it is based on a 3D file. Though accelerating at a slower rate compared to the aerospace and automotive industries, there is increased pressure to shorten the development cycle of components for the oil, gas, and renewables sectors and perform rapid proto-typing and testing of new, more sustain-able concepts. New business models will be developed and a new way of thinking adopted by design engineers to fully utilize its potential (DNV Technology Outlook 2030). To support the digital transformation of the energy industry, DNV, which has been actively investigating the potential of AM since 2014, has unveiled a new service specification document to ensure AM products, assets, and systems are safe, economical, and efficient. DNVGL-SE-0568 “Qualification of Additive Manufacturing Service Providers, Manufacturers, and Parts,” is part of a portfolio of six different AM-related standards and recommended practices (Fig. 1).

Machine Learning for Additive Manufacturing

Additive manufacturing (AM) is the name given to a family of manufacturing processes where materials are joined to make parts from 3D modelling data, generally in a layer-upon-layer manner. AM is rapidly increasing in industrial adoption for the manufacture of end-use parts, which is therefore pushing for the maturation of design, process, and production techniques. Machine learning (ML) is a branch of artificial intelligence concerned with training programs to self-improve and has applications in a wide range of areas, such as computer vision, prediction, and information retrieval. Many of the problems facing AM can be categorised into one or more of these application areas. Studies have shown ML techniques to be effective in improving AM design, process, and production but there are limited industrial case studies to support further development of these techniques.

Multidisciplinary analysis of hydraulic stimulation and production effects within the Niobrara and Codell reservoirs, Wattenberg Field, Colorado — Part 2: Analysis of hydraulic fracturing and production

Enhanced hydrocarbon recovery is essential for continued economic development of unconventional reservoirs. We have focused on dynamic characterization of the Niobrara and Codell Formations in Wattenberg Field through the development and analysis of a full integrated reservoir model. We determine the effectiveness of the hydraulic fracturing and production with two seismic monitor surveys, surface microseismic, completion data, and production data. The two monitor surveys were recorded after stimulation and again after two years of production. Identification of reservoir deformation due to hydraulic fracturing and production improves reservoir models by mapping nonstimulated and nonproducing zones. Monitoring these time-variant changes improves the prediction capability of reservoir models, which in turn leads to improved well and stage placement. We quantify dynamic reservoir changes with time-lapse P-wave seismic data using prestack inversion and velocity-independent layer stripping for velocity and attenuation changes within the Niobrara and Codell reservoirs. A 3D geomechanical model and production data are history matched, and a simulation is run for two years of production. Results are integrated with time-lapse seismic data to illustrate the effects of hydraulic fracturing and production. Our analyses illustrate that chalk facies have significantly higher hydraulic fracture efficiency and production performance than marl facies. In addition, structural and hydraulic complexity associated with faults generate spatial variability in a well’s total production.

Lightweight Visualization of 3D Model Based on Cloud Computing Information System

The processing requirements of 3D model data in modern manufacturing industry and the data type characteristics of 3D model data source. With the popularity of modern cloud computing platform and the technical advantages of cloud computing platform, the 3D model information is stored in the information system, and the cloud computing technology is used to manage the information system. The purpose of this article is to combine cloud computing technology with lightweight 3D visualization technology such as acrobat 3D to realize lightweight visualization of 3D model in information system. With the advantage of cloud computing platform which does not occupy local resources and has large data processing capacity combined with lightweight 3D visualization technology such as Acrobat 3D,3D model data can be visualized in cloud fast traffic. This paper investigates and studies, compares the speed of reading information between the information system using cloud computing technology and the ordinary local storage information system, and tries to find out the advantages of cloud computing compared with the traditional information system. In addition, this paper also optimizes lightweight on the basis of 3D model data set. Reduce the collective product of its data without destroying the visualization of its basic information.

Investigating the spatial distribution of resident’s outdoor heat exposure across neighborhoods of Philadelphia, Pennsylvania using urban microclimate modeling

Cities are experiencing more and more frequent extreme heat events in hot summers in the context of rising global temperatures. A precise understanding of the spatial distribution of the human outdoor heat exposure across neighborhoods in cities is of great importance for urban heat management. Different from remote sensing based the land surface temperature, this study calculated the mean radiant temperature, which is more objective to indicate human heat stress, to study the spatial distribution of human outdoor heat exposure in Philadelphia, Pennsylvania. The SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry) model was applied to estimate the mean radiant temperature based on the high-resolution urban 3D model and meteorological data. This study further examined the spatial distributions of heat exposure levels across neighborhoods of different groups in Philadelphia. Results show that there is no significant disparity in terms of outdoor heat exposure levels for different racial/ethnic groups in Philadelphia. Generally, the elderly, who usually are more vulnerable to extreme heat, tend to live in neighborhoods with less outdoor heat exposure in summer (p<0.001). The higher-income people tend to live in thermally more comfortable neighborhoods (p<0.001). The study provides a precise understanding of the heat distribution across neighborhoods, which would further help to develop strategies to allocate resources to the most needed neighborhoods to maximumly mitigate the negative impact of urban heat.

Hyperspectral z-scan: Measurement of spectrally resolved nonlinear optical properties

Broadband hyperspectral z-scan using a supercontinuum light source is a convenient technique to obtain spectrally resolved nonlinear optical properties of the materials under investigation. Post-processing and segregation of the data obtained from the supercontinuum based hyperspectral z-scan measurement aids in determining the nonlinear optical properties with high spectral resolution. However, few data models exist to store and represent the large amount of information acquired from the hyperspectral z-scan measurement. In this paper, a 3D data model for representing the data obtained from broadband z-scan measurements and analysis is presented. This method would help in the quick characterization of spectrally resolved nonlinear optical properties of materials from a single z-scan measurement. The proposed model is used for obtaining the spectrally resolved nonlinear optical properties of rhodamine 6G.

Special Issue on Digital Geometry Processing for Large-Scale Structures and Environments

The application of digital geometry processing is undergoing an extension from small industrial products to large-scale structures and environments, including plants, factories, ships, bridges, buildings, forests, and indoor/outdoor/urban environments. This extension is being supported by recent advances in long-range 3D laser scanning technology. Laser scanners are mounted on various platforms, such as tripods, wheeled vehicles, airplanes, and UAVs, and the laser scanning systems are used to efficiently acquire dense and accurate digitized 3D data of the geometry, called point clouds, of large-scale structures and environments. As another technology for the acquisition of digital 3D data of structures and environments, 3D reconstruction methods from digital images are also attracting a great deal of attention because of their flexibility. The utilization of digital 3D data for various purposes still has many challenges, however, in terms of data processing. The extraction of accurate and meaningful information from the data is an especially important and difficult problem, and many studies on object and scene recognition are being conducted in many fields. How to acquire useful and high-quality digital 3D data of large-scale structures and environments is another problem to be solved for digital geometry processing to be widely used. This special issue addresses the latest research advances in digital geometry processing for large-scale structures and environments. It covers a broad range of topics in geometry processing, including new technologies, systems, and reviews for 3D data acquisition, recognition, and modeling of ships, factories, plants, forests, river dikes, and urban environments. The papers will help the readers explore and share their knowledge and experience in technologies and development techniques in this area. All papers were refereed through careful peer reviews. We would like to express our sincere appreciation to the authors for their excellent submissions and to the reviewers for their invaluable efforts in producing this special issue.