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Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

The main purpose of the study was mechanical designing, simulation and manufacturing process for a new model of octocopter V-frame and to achieve simple manufacturing with 3D printing technology. Moreover, the octocopter PID controller was simulated on the Simulink environment to get performance on the roll and pitch angle control.

Octocopter is one kind of multirotor vehicle (a rotorcraft with more than two rotors), that has lately gained a lot of attention for both the scientific and commercial spheres. With a greater number of rotors, the multirotor is very maneuverable and robust. Multi-copter makes an important contribution to the technological revolution in the military, industry, transportation, mapping and especially agriculture. Nowadays, we are heading to the four-industrial revolutions as well as the new technological application in the agricultural field such as precision agriculture, mapping and surveillance. Due to recently advanced technology about sensors, electronics, 3D printing, battery with high performance, multi-copter can be manufactured at low cost.

The V-frame octocopter was chosen to design in this paper; it had better performance scores including high redundancy rotors, high payload capability and affordable cost than another multi-copter family. The V-frame octocopter increasing freedom field of view of the camera was considered to place the camera position in the front of the drone.

For the future aspects, the mechanical structure of the octocopter could be improved by using more advanced metal 3D printing to produce the aluminum or titan alloy materials for lighter and more rigid compared with ABS material, and finally the assembly to the real test.

The study shows the new platform of the V-frame octocopter kinematics analysis, designed on the CAD software, with some important mechanical parts using FEM analysis to find the highest stress and displacement under high load applied, the result of all connecting the joints 3D printing part is completely safe. Mechanical parts were manufactured by using 3D printing technology and CNC milling. Moreover, the study has shown V-frame octocopter simulation based on Simulink using the second method Ziegler- Nichols to find suitable parameters of the PID controller for roll and pitch angle. Using the block simulation is good for implementing and fast checking the new algorithm when building the new platform of the robot.

The paper presents the Finite Element (FE) evaluation of the magnetic field emitted by a Wireless Power Transfer Systems used to charge the battery of electrical vehicles. An original approach for reducing the mesh size of the 3D FE model is used.

A minicar equipped with a circular coil is considered, while the transmitting coil is coherent with the Society of Automotive Engineers (SAE) standard. The different shape of the coils and a possible misalignment are considered as possible sources of emitted magnetic field, which a person could be exposed to. To this end, a FE model is implemented. Because of the complexity of the mesh, a suitable 3D model is used. This model is previously validated and then used for evaluating the magnetic field around the Wireless Power Transfer Systems (WPTS).

The magnetic flux density around the WPTS is calculated and compared with the International Commission on Non-Ionizing Radiation Protection (ICNIRP) limits.

The proposed 3D model, whose validation is shown in the paper, is able to compute the magnetic field with high accuracy despite the presence of a conductive and ferromagnetic thin structure, the steel layer related to the car frame, which would need a very fine mesh with a large number of elements to solve Maxwell equations.

As a means of data acquisition for the situation awareness, computer vision-based motion capture technologies have increased the potential to observe and assess manual activities for the prevention of accidents and injuries in construction. This study thus aims to present a computationally efficient and robust method of human motion data capture for the on-site motion sensing and analysis.

This study investigated a tracking approach to three-dimensional (3D) human skeleton extraction from stereo video streams. Instead of detecting body joints on each image, the proposed method tracks locations of the body joints over all the successive frames by learning from the initialized body posture. The corresponding body joints to the ones tracked are then identified and matched on the image sequences from the other lens and reconstructed in a 3D space through triangulation to build 3D skeleton models. For validation, a lab test is conducted to evaluate the accuracy and working ranges of the proposed method, respectively.

Results of the test reveal that the tracking approach produces accurate outcomes at a distance, with nearly real-time computational processing, and can be potentially used for site data collection. Thus, the proposed approach has a potential for various field analyses for construction workers’ safety and ergonomics.

Recently, motion capture technologies have rapidly been developed and studied in construction. However, existing sensing technologies are not yet readily applicable to construction environments. This study explores two smartphones as stereo cameras as a potentially suitable means of data collection in construction for the less operational constrains (e.g. no on-body sensor required, less sensitivity to sunlight, and flexible ranges of operations).

The purpose of this study is to explore the effect of the demagnetizing field in the Epstein characterization of grain-oriented electrical steels through a finite element method (FEM) simulations.

A 3D finite element simulation has been realized to represent the parallel and X-stacking configurations in the Epstein frame. The numerical results have been compared with experimental measures.

In a parallel configuration, the measured induction is actually the one in the material, whereas the resulting magnetic field differs from the applied one (in magnitude and angle) due to the shape anisotropy (demagnetizing field). In X-stacking configuration, the resulting magnetic field is close to the applied magnetic field (and then the supposed excitation field in the Epstein frame), whereas the magnetic induction has deviated from the axis of the strips.

Both stacking configurations (parallel and cross) of the Epstein frame are analyzed by three-dimensional finite element simulation.

Existing three-dimensional (3D) road-surface models use approximation methods such as a set of discrete triangular patches and cannot accurately describe changes in the geometrically designed elements along the road. This paper aims to construct a 3D road-surface model with combinations of geometric design invariants and apply the proposed model to analyse the state of motion of a wheel’s centre.

In this paper, the 3D road surface is modelled as a continuous function with combinations of geometric design invariants. By introducing the theories of differential geometries and rigid body dynamics, a wheel-road model wherein a wheel fixed to a Darboux frame moves along a curved road surface is constructed, and the wheel time-dependent properties of the velocity, angular velocity and acceleration at an arbitrary point of the surface are described using road geometry design invariants.

This paper adopts the Darboux frame to study the instantaneous spin-rolling motion of a wheel. It is found that the magnitudes of the spin-rolling velocity, the acceleration and the geometric invariants of the road surface, including the geodesic curvature, the normal curvature and the geodesic torsion, determine the instantaneous states of motion of a wheel.

This work provides a theoretical foundation for future studies of wheel motion states, such as the relationship between road geometry design invariants and driving safety, vehicle lane changing and other vehicle microbehaviours. New insights are gained in the areas of road safety and vehicles incorporating artificial intelligence.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

The purpose of this paper is to establish new computer-aided-design (CAD) framework to design custom product that is fabricated additive manufacturing (AM), which can produce complex three-dimensional (3D) object without additional tool or fixture. Additive manufacturing (AM) enables the fabrication of three-dimensional (3D) objects with complex shapes without additional tools and refixturing. However, it is difficult for user to use traditional computer-aided design tools to design custom products.

In this paper, the authors presented a design system to help user design custom 3D printable products based on some reference freeform shapes. The user can define and edit styling curves on the reference model using the interactive geometric operations for styling curve. Incorporating with the reference models, these curves can be converted into 3D printable models through the fabrication interface.

The authors tested their system with four design applications including a hollow patterned bicycle helmet, a T-rex with skin frame structure, a face mask with Voronoi patterns and an AM-specific night dress with hollow patterns.

The executable prototype of the presented design framework used in the customization process is publicly available.

This paper aims to explore the opportunities and challenges that immersive virtual reality (VR) technologies pose for archival theory and practice.

This conceptual paper reviews research on VR adoption in information institutions and the preservation challenges of VR to identify ways in which VR has the potential to disrupt existing archival theory and practice.

Existing archival approaches are found to be disrupted by the multi-layered structural characteristics of VR, the part–whole relationships between the technological elements of VR environments and the three-dimensional content they contain and the immersive, experiential nature of VR experiences. This paper argues that drawing on perspectives from phenomenology and digital materiality is helpful for addressing the preservation challenges of VR.

The findings extend conceptualizations of preservation by identifying gaps in existing preservation approaches to VR and stressing the importance of “experience” as a central element of archival practice and by emphasizing the embodied dimensions of interpreting archival records and the multiple scales of materiality that archival researchers and practitioners should consider to preserve VR.

These findings provide guidance for digital curators and preservationists by outlining the current thinking on VR preservation and the impact of VR on digital preservation strategies.

This paper gives new insight into VR as an emerging area of concern to digital curation and preservation and expands archival thinking with new conceptualizations that disrupt existing paradigms.