3D Geometry Research Articles

A versatile 5-axis melt electrowriting platform for unprecedented design freedom of 3D fibrous scaffolds

Melt electrowriting (MEW) is an electrohydrodynamic additive manufacturing technology for the fabrication of precise microfiber scaffold architectures but is so far restricted to printing onto simple collector geometries and, therefore, constrained in design freedom. This is due to current limitations in print head designs, kinematic systems, and software to generate motion commands. We address these aspects by upgrading a low-cost 5-axis kinematic system and complete it with a custom-designed print head and a collector fabrication workflow to enable collision-free MEW onto arbitrarily shaped multicurvature 3D geometries. A universal graphical approach enables generation of Gcodes customized to the 5-axis MEW requirements. The print head is validated by producing polycaprolactone fibers with diameters ranging from 5.6 ± 1.7 µm to 50.7 ± 5.5 µm and by writing both linear and non-linear fiber patterns onto collectors featuring concave and convex surfaces. Stable printing conditions are achieved by continuously reorienting the print head and collector surface perpendicular to each other at a constant working distance. Ultimately, we demonstrate the system’s potential in shaping anatomically relevant scaffold geometries by stacking microfibers onto collectors resembling a trileaflet valve and a bifurcating vessel. This multi-axis MEW platform unlocks exciting avenues towards unprecedented design freedom for MEW scaffolds.

Bridging Implicit and Explicit Geometric Transformation for Single-Image View Synthesis.

Creating novel views from a single image has achieved tremendous strides with advanced autoregressive models, as unseen regions have to be inferred from the visible scene contents. Although recent methods generate high-quality novel views, synthesizing with only one explicit or implicit 3D geometry has a trade-off between two objectives that we call the "seesaw" problem: 1) preserving reprojected contents and 2) completing realistic out-of-view regions. Also, autoregressive models require a considerable computational cost. In this paper, we propose a single-image view synthesis framework for mitigating the seesaw problem while utilizing an efficient non-autoregressive model. Motivated by the characteristics that explicit methods well preserve reprojected pixels and implicit methods complete realistic out-of-view regions, we introduce a loss function to complement two renderers. Our loss function promotes that explicit features improve the reprojected area of implicit features and implicit features improve the out-of-view area of explicit features. With the proposed architecture and loss function, we can alleviate the seesaw problem, outperforming autoregressive-based state-of-the-art methods and generating an image ≈ 100 times faster. We validate the efficiency and effectiveness of our method with experiments on RealEstate10 K and ACID datasets.

Separation efficiency of a wastewater bar screen based on a 3D computational fluid dynamics modeling

The wastewater screening process is a crucial step in the majority of wastewater treatment plants, frequently using mechanical bar screens as the first filtration step to remove heavy debris from the wastewater flow. In the present study, two 3D geometries of bar screens with different screen openings were presented to investigate the effect of the variation in screen spacing of bars on the separation efficiency of debris. Based on the Ansys Fluent CFD code within the Eulerian-Lagrangian approach, the particle trajectories were tracked, and the retention efficiency of these two bar screens was evaluated. The results show that a higher particle separation efficiency is favored for small bar spacing and coarse particle sizes. Actually, despite the impact of bar spacing on the separation efficiency of particles, the adequate choice of this parameter is related to particle properties and the fluid flow inlet velocity. These parameters also have a great influence on the separation efficiency of bar screens. The study can help for more structural improvements in the shape of the screening media, which leads to enhanced performance of wastewater screening facilities.

Augmented Reality as a Tool to Support the Connection Between Reality and Mathematical Knowledge: A Case for Teaching Parallel Relations of Planes in Space

In the 11th−grade Vietnamese Mathematics Curriculum, students learn about parallel relations between planes in space. This is cognitively challenging for many students. Studies have shown difficulties relating to limited spatial imagination and drawing representations. The teacher’s approach also causes difficulties for some students; for example, some teachers do not approach new knowledge from practice. These approaches lead students to learn math only in that class rather than to relate math knowledge to real life, whereas real-life objects can be good tools for illustrating knowledge of spatial geometry. This study uses an action research method using GeoGebra 3D Calculator software to design teaching situations about parallel relations of lines and planes in space. This study was conducted with 40 students in 11th grade in Long An Province, Vietnam. It was found that learning tasks can be designed to help students construct knowledge effectively and overcome difficulties. The results of this research show that AR software for 3D Geometry, in particular GeoGebra, creates a connection between reality and abstract knowledge about the parallel relations of lines and surfaces in space. The research also shows that the application of augmented reality in teaching helps students understand and test hypotheses, eliminate false hypotheses, and build new knowledge about parallel relations effectively.

Imprints of the Local Bubble and Dust Complexity on Polarized Dust Emission

Using 3D dust maps and Planck polarized dust emission data, we investigate the influence of the 3D geometry of the nearby interstellar medium (ISM) on the statistics of the dust polarization on large ( 80′ ) scales. We test recent models that assume that the magnetic field probed by the polarized dust emission is preferentially tangential to the Local Bubble wall, but we do not find an imprint of the Local Bubble geometry on the dust polarization fraction. We also test the hypothesis that the complexity of the 3D dust distribution drives some of the measured variation of the dust polarization fraction. We compare sight lines with similar total column densities and find that, on average, the dust polarization fraction decreases when the dust column is substantially distributed among multiple components at different distances. Conversely, the dust polarization fraction is higher for sight lines where the dust is more concentrated in 3D space. This finding is statistically significant for the dust within 1.25 kpc, but the effect disappears if we only consider dust within 270 pc. In conclusion, we find that the extended 3D dust distribution, rather than solely the dust associated with the Local Bubble, plays a role in determining the observed dust polarization fraction at 80′. This conclusion is consistent with a simple analytical prediction and remains robust under various modifications to the analysis. These results illuminate the relationship between the 3D geometry of the ISM and tracers of the interstellar magnetic field. We discuss implications for our understanding of the polarized dust foreground to the cosmic microwave background.

Improved 3D characterization of in-situ soil desiccation cracking by multi-source data integration

Desiccation cracking is a common and natural phenomenon under a drought climate. The geometric and morphologic characteristics of the crack pattern are critical to understanding the response of soil mechanical and hydraulic properties to drought climate. It is always a big challenge to obtain the refined geometric structure of the in-situ soil desiccation crack network. This study proposes an integrated method named ERT+ for determining the three-dimensional geometry of in-situ soil desiccation crack networks by integrating multi-source data from electrical resistivity tomography (ERT), surface image analysis, and depth investigation. The proposed method was applied to three in-situ expansive soil sites with different crack geometries and soil properties. The results showed that the joint application of ERT with other investigations reduced the ambiguity of interpreting each technique independently. The crack network model characterized the three-dimensional geometric structure of the desiccation crack accurately and quantitatively, verifying the effectiveness and feasibility of the ERT+ method. Field and laboratory experiments showed that heterogeneity in soil properties resulted in different cracking morphologies (width, depth, and width-depth ratio). The crack geometric data suggested that the width-depth ratio of the crack network was related to the cracking modes and the soil properties, indicating the non-homology of different crack networks. In addition, the correction gradients calculated from the ERT+ method also varied with the cracking modes and soil properties, further suggesting the reliability and prospect of the proposed method.

Cartesian mesh adaptation: Immersed boundary method based on high-order discontinuous Galerkin method

Immersed boundary method (IBM) can easily distinguish fluid and solid regions in the computational region, thereby the workload of complex grid generation can be reduced. To accurately characterize the solid geometry, a large number of cells are required near the solid surface. The h-adaptive algorithm is adopted to reduce the requirement for the number of cells. In addition, considering the inherent adaptability to the h-adaptive Cartesian grids of the discontinuous Galerkin method, a high-order discontinuous Galerkin solver with an IBM is developed. To validate the h-adaptive algorithm and the solver, three cases are tested, including the steady flow past the National Advisory Committee for Aeronautics 0012 airfoil, the steady flow past a cylinder, and the unsteady flow past a cylinder. Compared with the non-adaptive cases, the h-adaptive cases need smaller total number of cells, and the numerical accuracy is significantly improved with an increasing degree of mesh refinement.

TrajectoryNAS: A Neural Architecture Search for Trajectory Prediction.

Autonomous driving systems are a rapidly evolving technology. Trajectory prediction is a critical component of autonomous driving systems that enables safe navigation by anticipating the movement of surrounding objects. Lidar point-cloud data provide a 3D view of solid objects surrounding the ego-vehicle. Hence, trajectory prediction using Lidar point-cloud data performs better than 2D RGB cameras due to providing the distance between the target object and the ego-vehicle. However, processing point-cloud data is a costly and complicated process, and state-of-the-art 3D trajectory predictions using point-cloud data suffer from slow and erroneous predictions. State-of-the-art trajectory prediction approaches suffer from handcrafted and inefficient architectures, which can lead to low accuracy and suboptimal inference times. Neural architecture search (NAS) is a method proposed to optimize neural network models by using search algorithms to redesign architectures based on their performance and runtime. This paper introduces TrajectoryNAS, a novel neural architecture search (NAS) method designed to develop an efficient and more accurate LiDAR-based trajectory prediction model for predicting the trajectories of objects surrounding the ego vehicle. TrajectoryNAS systematically optimizes the architecture of an end-to-end trajectory prediction algorithm, incorporating all stacked components that are prerequisites for trajectory prediction, including object detection and object tracking, using metaheuristic algorithms. This approach addresses the neural architecture designs in each component of trajectory prediction, considering accuracy loss and the associated overhead latency. Our method introduces a novel multi-objective energy function that integrates accuracy and efficiency metrics, enabling the creation of a model that significantly outperforms existing approaches. Through empirical studies, TrajectoryNAS demonstrates its effectiveness in enhancing the performance of autonomous driving systems, marking a significant advancement in the field. Experimental results reveal that TrajcetoryNAS yields a minimum of 4.8 higger accuracy and 1.1* lower latency over competing methods on the NuScenes dataset.

Advancing Fixed-Source Reactor Analysis Through OpenNode Implementation

OpenNode, a new open-source Fortran code, enables the simulation of fixed-source reactors. Powered by the nodal expansion method (NEM) and seamless Python integration, OpenNode competes with existing nuclear reactor simulation tools. The fixed-source problem plays a crucial role in radioprotection, providing flux calculations and detailed insights into heating effects and dose rates. Users can define and configure reactor models via a JSON input file, specifying critical parameters like geometry, materials, cross-section data, boundary conditions, and fixed sources. OpenNode further empowers users with a Python interface for preprocessing and postprocessing, streamlining result analysis. Distinguishing itself from conventional NEM codes, OpenNode supports three-dimensional (3D) Cartesian geometries, facilitating intricate reactor design simulations. Customization options, including mesh sizes, polynomial orders, and calculation modes, enhance precision and efficiency. In our comprehensive study, we verified OpenNode’s fixed-source mode using the 3D-IAEA reactor, comparing it with the SANM code KOMODO. The results underscore OpenNode’s exceptional accuracy in computing critical parameters, like the effective multiplication factor, power distribution, and nodal flux, within fixed-source reactors. OpenNode stands as a reliable, user-friendly tool poised to advance nuclear reactor simulations.

Digital bead modeling for wire-arc directed energy deposition

Prediction of 2D cross-section and full 3D geometry for stacked weld beads is critical for the outcome of wire-arc directed energy deposition (DED) parts; however, most additive path planning software packages model beads as extrusions of a rectangle. Weld beads are not rectangular, and the resulting shape is dependent upon physics effects at the moment of deposition. Physics phenomena such as the geometry of the underlying surface, the heat input of the welding mode, and the direction of gravity contribute to bead shape. This paper presents a novel implicit modeling method that discretizes a 2D area or 3D volume of space into pixels or voxels and constructs fields based on these physics phenomena. The fields are combined using a weighting scheme trained on 3D scan measurements of welds and wire-arc DED prints. Pixels or voxels are added until the known amount of deposited volume has been achieved. Thereby, a strong conservation of mass principle is applied to the process. Utilizing machine learning techniques, the present model can be trained on a database of scans allowing for the representation of a wide variety of prints. Results show that this method can produce predictions with realistic bead morphology and sub-millimeter form error.

Corrosion-fatigue damage identification in submerged mooring chain links using remote acoustic emission monitoring

This paper investigates the feasibility of detection, localisation, and monitoring of corrosion-fatigue damage in mooring chain links using remote Acoustic Emission (AE) technique in submerged conditions. A large-scale experiment was conducted on a studless R4 chain retrieved after about two decades of operation offshore. Ultrasound signals were continuously measured using fixed and movable arrays of AE transducers placed on perpendicular planes in the water tank enclosing the chain. The AE parameters extracted from the measured signals have been analysed. AE sources were successfully localised on the 3D geometry of the chain links. The results suggest that damage growth can be detected and localised using non-contact underwater AE transducers.

Rectangular Prism의 내접 장축 회전 타원체와 슈타이너 내접 장축 회전 타원체에 대한 연구

This study extends the concept of the inscribed Prolate Spheroid defined of tetrahedron to explore the inscribed Prolate Spheroid of Rectangular prism. Furthermore, it extends the concept of the Steiner inellipse, defined in triangles andquadrilaterals on a plane, to three dimensions to explore the Steiner inscribed Prolate Spheroid of Rectangular prism. Through this study, the following results were obtained. First, the positional relationship of the two foci of the inscribedProlate Spheroid of Rectangular prism was elucidated. Second, the existence and number of inscribed Prolate Spheroid of Rectangular prism were determined. Third, the positions of the two foci of the Steiner inscribed Prolate Spheroid ofRectangular prism were clarified. Fourth, the necessary and sufficient conditions for the existence of the Steiner inscribed Prolate Spheroid of Rectangular prism were discovered. Fifth, the volume ratio between the Rectangular prism and its Steiner inscribed Prolate Spheroid were revealed. Activities like this study, which extend existing mathematical concepts to other domains and apply planar results to three-dimensional figures, are expected to contribute to the advancement of mathematics.

Development of the BOLT-2 Roughness Experiment for Flight

A sounding rocket research flight called BOLT-2, which stands for Boundary Layer Turbulence 2, was initiated with the goal of studying hypersonic boundary-layer transition and turbulence. The BOLT-2 research vehicle is based on a three-dimensional geometry with concave surfaces and swept leading edges that provides two separate and distinct, also redundant, flowpaths for conducting measurements. One side of BOLT-2 is dedicated to smooth surface transition and turbulence, to better study the natural instability processes, whereas the other has been assigned to study forced transition and turbulence using discrete roughness trips. The present paper is intended to document the primary drivers and decisions made that lead up to finalizing the roughness-side experiment for the BOLT-2 flight.

Anisotropy-driven magnetic phase transitions in SU(4)-symmetric Fermi gas in three-dimensional optical lattices

Abstract We study SU(4)-symmetric ultracold fermionic mixture in the cubic optical lattice with the variable tunneling amplitude along one particular crystallographic axis in the crossover region from the two- to three-dimensional spatial geometry. To theoretically analyze emerging magnetic phases and physical observables, we describe the system in the framework of the Fermi-Hubbard model and apply dynamical mean-field theory. We show that in two limiting cases of anisotropy there are two phases with different antiferromagnetic orderings in the zero temperature limit and determine a region of their coexistence. We also study the stability regions of different magnetically-ordered states and density profiles of the gas in the harmonic optical trap.

Contribution of Magnetotelluric inversion and potential field modeling to map the Gour Oumelalen deep geological Structure, Central Hoggar, Algeria

The Gour Oumelalen area is situated in the northern part of the Egere-Aleksod terrane (Central Hoggar, South of Algeria). This area is one of the best preserved Palaeoproterozoic and Archaean zones in Central Hoggar. The aim of this study based on a survey of 33 Magnetotelluric (MT) soundings, aeromagnetics and gravity data, is to investigate the crustal structure and its architecture beneath this area.As the first stage, we have determined dimensionality of the regional electric conductivity structure. For this purpose, we have used the impedance and phase tensor approaches. Our results suggest that the underling regional conductivity structure is complex. In the central part it presents a 3D geometry, and beyond, it is mainly 2D; with a strike direction oriented in the North-South direction. Thus, the MT data were inverted using the Occam's inversion algorithm (v.3); which is a powerful tool to modeling and inverting the 2-D MT data. The obtained geo-eletric models, show clearly a high resistive upper crust with a resistivity up to 1000 Ω m; overlies a conductive lower crust with a resistivity approximately less then 100 Ω m. Although, our resulting cross-sections confirm the major Precambrian faults, especially the Ounan shear zone, which is characterized by a high conductivity anomaly.At the second stage, using the joint modeling of gravity and magnetic data, we have characterized the different geological units. Although, our modeling reveals that the thicknesse of the upper crust is deeping toward the East, from 16 to 25 km. The Moho depth reaches an average value of 40 Km. Moreover, in the centre of the survey area, the Moho depth decreases and becomes equal to 20 Km. This uplifting of the upper mantle may corresponds to the high magnetic anomaly of the Tisseliline pluton. It seems also related to the magmatic intrusion along the Ounan Shear Zone.

Ordered structures formed by nematic topological defects and their transformation with changing the Euler characteristics.

Ordered chain structures from topological defects of opposite charges ("necklaces" of defects) were prepared and their dynamics and cooperative rearrangement were investigated. We studied topological defects in nematic films with change of the Euler characteristic induced by temperature. Topological defects emerged due to competing surface anchoring on the nematic-isotropic and nematic-solid interfaces. Transformation of the structure with a circular chain from topological defects to the structure with a single defect and then to a structure without defects takes place as the nematic geometry changes. The temporal evolution of the number of topological defects at their annihilation in the chains differs from coarsening in two-dimensional (2D) and 3D geometry.

Integrating conductive electrodes into hydrogel-based microfluidic chips for real-time monitoring of cell response.

The conventional real-time screening in organs-on-chips is limited to optical tracking of pre-tagged cells and biological agents. This work introduces an efficient biofabrication protocol to integrate tunable hydrogel electrodes into 3D bioprinted-on-chips. We established our method of fabricating cell-laden hydrogel-based microfluidic chips through digital light processing-based 3D bioprinting. Our conductive ink includes poly-(3,4-ethylene-dioxythiophene)-polystyrene sulfonate (PEDOT: PSS) microparticles doped in polyethylene glycol diacrylate (PEGDA). We optimized the manufacturing process of PEDOT: PSS microparticles characterized our conductive ink for different 3D bioprinting parameters, geometries, and materials conditions. While the literature is limited to 0.5% w/v for PEDOT: PSS microparticle concentration, we increased their concentration to 5% w/v with superior biological responses. We measured the conductivity in the 3-15m/m for a range of 0.5%-5% w/v microparticles, and we showed the effectiveness of 3D-printed electrodes for predicting cell responses when encapsulated in gelatin-methacryloyl (GelMA). Interestingly, a higher cellular activity was observed in the case of 5% w/v microparticles compared to 0.5% w/v microparticles. Electrochemical impedance spectroscopy measurements indicated significant differences in cell densities and spheroid sizes embedded in GelMA microtissues.

Estimation of Inferior Vena Cava Size from Ultrasound Imaging in X-Plane

Ultrasound (US) scans of the inferior vena cava (IVC) provide useful information on the volume status of a patient. However, their investigation is user-dependent and prone to measurement errors. An important technical problem is the objective difficulty in studying a very compliant blood vessel like IVC, which makes large respirophasic movements and shows a complicated three-dimensional geometry. Using bi-dimensional (2D) B-mode views either in a long or short axis has improved the characterization of IVC dynamics compared to measurements along a single direction (M-mode). However, specific movements of the IVC can also challenge the information provided by these 2D sections. Thus, these two orthogonal views, provided by an US system in the X-plane, are integrated here using an innovative method. It is tested on simulated videos of the IVC by performing complicated movements, which are compensated by the new method, overcoming the biased measurements provided by 2D scans. The method is then applied on example experimental data.

Direct electron beam writing of silver using a β-diketonate precursor: first insights.

Direct electron beam writing is a powerful tool for fabricating complex nanostructures in a single step. The electron beam locally cleaves the molecules of an adsorbed gaseous precursor to form a deposit, similar to 3D printing but without the need for a resist or development step. Here, we employ for the first time a silver β-diketonate precursor for focused electron beam-induced deposition (FEBID). The used compound (hfac)AgPMe3 operates at an evaporation temperature of 70-80 °C and is compatible with commercially available gas injection systems used in any standard scanning electron microscope. Growth of smooth 3D geometries could be demonstrated for tightly focused electron beams, albeit with low silver content in the deposit volume. The electron beam-induced deposition proved sensitive to the irradiation conditions, leading to varying compositions of the deposit and internal inhomogeneities such as the formation of a layered structure consisting of a pure silver layer at the interface to the substrate covered by a deposit layer with low silver content. Imaging after the deposition process revealed morphological changes such as the growth of silver particles on the surface. While these effects complicate the application for 3D printing, the unique deposit structure with a thin, compact silver film beneath the deposit body is interesting from a fundamental point of view and may offer additional opportunities for applications.

Semiautomatic Exploration of Conceptual Design Spaces through Parametric Shape Variability and Additive Manufacturing

Design ideation activities that involve the manipulation of geometry rely heavily on manual input. For feasibility reasons, the generation of design alternatives must often be limited, particularly when these alternatives need to be prototyped and tested. This paper describes a conceptual design strategy that leverages variational three-dimensional geometry to automatically generate a large number of design alternatives from a template model and their corresponding physical prototypes for evaluation and testing. In our approach, 3D geometric variations are produced automatically from a single design concept modeled parametrically, which are then used to generate 3D-printable files. Our method is suitable for design scenarios where real-world testing is preferred over virtual simulation and requires designers to consider a concept idea as a family of solutions, instead of a single design option. Our strategy enables an effective exploration of conceptual design spaces in highly constrained situations and facilitates parallel prototyping, which is known to produce better results than serial prototyping. We demonstrate the feasibility and effectiveness of the proposed method through a case study that involves the design of an instrument for ophthalmic surgery for extracting an intraocular lens (IOL) from the eye. Using our approach, nine unique concept families comprising a total of 150 designs were rapidly and successfully prototyped and tested.