3D Edge Research Articles

Three-Dimensional Leaf Edge Reconstruction Combining Two- and Three-Dimensional Approaches

Leaves, crucial for plant physiology, exhibit various morphological traits that meet diverse functional needs. Traditional leaf morphology quantification, largely 2-dimensional (2D), has not fully captured the 3-dimensional (3D) aspects of leaf function. Despite improvements in 3D data acquisition, accurately depicting leaf morphologies, particularly at the edges, is difficult. This study proposes a method for 3D leaf edge reconstruction, combining 2D image segmentation with curve-based 3D reconstruction. Utilizing deep-learning-based instance segmentation for 2D edge detection, structure from motion for estimation of camera positions and orientations, leaf correspondence identification for matching leaves among images, and curve-based 3D reconstruction for estimating 3D curve fragments, the method assembles 3D curve fragments into a leaf edge model through B-spline curve fitting. The method's performances were evaluated on both virtual and actual leaves, and the results indicated that small leaves and high camera noise pose greater challenges to reconstruction. We developed guidelines for setting a reliability threshold for curve fragments, considering factors occlusion, leaf size, the number of images, and camera error; the number of images had a lesser impact on this threshold compared to others. The method was effective for lobed leaves and leaves with fewer than 4 holes. However, challenges still existed when dealing with morphologies exhibiting highly local variations, such as serrations. This nondestructive approach to 3D leaf edge reconstruction marks an advancement in the quantitative analysis of plant morphology. It is a promising way to capture whole-plant architecture by combining 2D and 3D phenotyping approaches adapted to the target anatomical structures.

Four-in-one strategy to boost the performance of 3-dimensional MoS2 nanostructures for industrial effluent treatment and hydrogen evolution reactions

Two-dimensional (2D) molybdenum disulfide (MoS2) has gained enormous attention as a photocatalytic material due to its extraordinary optical, electrical, and chemical properties which are highly tunable by engineered control of its 2D layers orientation. However, high carrier recombination rates in pristine MoS2 nanostructures hinder their practical applications as an efficient catalyst. There is an upsurge of research on developing new strategies to improving its photocatalytic actions for environmental remediation. One approach is to design MoS2 nanostructures with vertically aligned layer-structures or cross-linking 3-dimensional flower-like morphologies, which exhibit ultrahigh-density 2D edge sites that offer tremendous chemical reactivity. Another challenge is to obtain its highly active metallic 1 T phase by functional design of intrinsic structures without sacrificing its ambient stability. Herein, we reported highly active and mix-phased 1 T/2 H MoS2 nanostructures through elegant synthesis management. By regulating reaction kinetics with the assimilation of NH4+ ions and water molecules, tunable surface morphology from nano wrinkles to nanoflowers was achieved. The morphology regulations induced modifications in the surface areas of final products which were calculated as 64.3 m2g−1, 114.3 m2g−1, and 219.7 m2g−1, respectively. Moreover, the bandgaps were significantly lowered from 2.13 eV to 1.93 eV and 1.85 eV. This four-in-one strategy efficiently boosted photodegradation of organic pollutants up to 94% in less than 20 min with excellent cyclic reproducibility for seven cycles. In addition, exceptional hydrogen evolution reaction (HER) performance with a very low overpotential of 145 mV and Tafel slope of 81.4 mV/dec was recorded. The results obtained in this work demonstrated excellent suitability of these materials as catalysts in environment related applications such as organic dye removal and for efficient hydrogen production.

Edge detection for 3D point clouds via locally max-angular gaps descriptor

Numerous point-cloud-based applications, including surface reconstruction and completion, greatly benefit from the utilization of edge features, which play a crucial role in structuring the target shape. Nevertheless, the current limitations of point cloud edge detection techniques in effectiveness and efficiency have motivated us to develop a more robust 3D edge detection method. In this paper, we introduce a simple yet effective descriptor for evaluating the edge level of 3D point clouds. This descriptor is defined as the variance of the max-angular gaps between the target point and its nearest neighboring points. Leveraging this descriptor, we further propose a multiscale feature fusion strategy that well detect the edge features for the target point cloud. Experimental results demonstrate the superiority of our method over other comparison methods in terms of effectiveness and stability in preserving point cloud edges. Moreover, we investigate the applications of our method in point cloud simplification and registration to provide additional insights into its potential use in some point-cloud-based downstream tasks.

3D DENSITY-GRADIENT BASED EDGE DETECTION ON NEURAL RADIANCE FIELDS (NERFS) FOR GEOMETRIC RECONSTRUCTION

Abstract. Generating geometric 3D reconstructions from Neural Radiance Fields (NeRFs) is of great interest. However, accurate and complete reconstructions based on the density values are challenging. The network output depends on input data, NeRF network configuration and hyperparameter. As a result, the direct usage of density values, e.g. via filtering with global density thresholds, usually requires empirical investigations. Under the assumption that the density increases from non-object to object area, the utilization of density gradients from relative values is evident. As the density represents a position-dependent parameter it can be handled anisotropically, therefore processing of the voxelized 3D density field is justified. In this regard, we address geometric 3D reconstructions based on density gradients, whereas the gradients result from 3D edge detection filters of the first and second derivatives, namely Sobel, Canny and Laplacian of Gaussian. The gradients rely on relative neighboring density values in all directions, thus are independent from absolute magnitudes. Consequently, gradient filters are able to extract edges along a wide density range, almost independent from assumptions and empirical investigations. Our approach demonstrates the capability to achieve geometric 3D reconstructions with high geometric accuracy on object surfaces and remarkable object completeness. Notably, Canny filter effectively eliminates gaps, delivers a uniform point density, and strikes a favorable balance between correctness and completeness across the scenes.

Numerical studies of plasma edge in W7-X with 3D FINDIF code

Abstract Modelling of the plasma transport for inherently three-dimensional (3D) problems as in stellarators requires dedicated complex codes. FINDIF is a 3D multifluid plasma edge transport code that has been previously successfully used for the analysis of energy transport in the TEXTOR-DED tokamak [1], where 3D perturbations led to an ergodic structure of field lines in the plasma edge. The ongoing efforts to apply it meaningfully to Wendelstein 7-X (W7-X) plasma problems resulted in advancements in the main model and accompanying tools for mesh generation and post-processing. In order to verify the applicability of the code and to compare with the reported simulation (EMC3-EIRENE) and experimental (OP1.1) results, a series of simulations for varying plasma density, temperature and anomalous transport coefficients as well as for fixed input power were performed. The connection length pattern of FINDIF traced magnetic field lines on the limiter was reproduced and its impact on heat loads was confirmed. An increase in the peak heat load on the limiter with a rise in plasma density, temperature and anomalous plasma transport coefficients was observed. The decay lengths of density, electron temperature and heat flux did not change with density, and were decreasing with temperature and increasing with anomalous plasma transport coefficient, which was compared to the simple scrape-off layer (SOL) model.

BEA-Net: Body and Edge Aware Network with Multi-Scale Short-Term Concatenation for Medical Image Segmentation.

Medical image segmentation is indispensable for diagnosis and prognosis of many diseases. To improve the segmentation performance, this study proposes a new 2D body and edge aware network with multi-scale short-term concatenation for medical image segmentation. Multi-scale short-term concatenation modules which concatenate successive convolution layers with different receptive fields, are proposed for capturing multi-scale representations with fewer parameters. Body generation modules with feature adjustment based on weight map computing via enlarging the receptive fields, and edge generation modules with multi-scale convolutions using Sobel kernels for edge detection, are proposed to separately learn body and edge features from convolutional features in decoders, making the proposed network be body and edge aware. Based on the body and edge modules, we design parallel body and edge decoders whose outputs are fused to achieve the final segmentation. Besides, deep supervision from the body and edge decoders is applied to ensure the effectiveness of the generated body and edge features and further improve the final segmentation. The proposed method is trained and evaluated on six public medical image segmentation datasets to show its effectiveness and generality. Experimental results show that the proposed method achieves better average Dice similarity coefficient and 95% Hausdorff distance than several benchmarks on all used datasets. Ablation studies validate the effectiveness of the proposed multi-scale representation learning modules, body and edge generation modules and deep supervision. The code is available at https://github.com/hulinkuang/BEA-Net.

Enhanced resolution of edge enhancement in three-dimensional vortex imaging based on a modified Michelson interferometer

Edge enhancement is emerging as an essential technique for object recognition in recent years. The edge detection of three-dimensional (3D) imaging has been successfully demonstrated in Fresnel incoherent correlation holograph (FINCH) system; however, with a relatively low resolution which needs to be further improved to meet practical requirements. In this work, a modified Michelson interferometer system using a spatial light modulator (SLM) is proposed, which realizes 3D vortex imaging with high resolution and low background noise. Compared with the spiral phase modulated polarization multiplexing FINCH system, the resolution of this system has apparently improved from 50.80 lp mm−1 to 57.02 lp mm−1. The improvement is assumed to be ascribed to the inherently high luminous flux utilization configuration of the Michelson interferometer and the precision phase shifts. More importantly, the proposed system exhibits prominently improved performance of edge enhancement for different objects, including the standard resolution target and label-free biological living cells. The experimental results of the small watch parts also demonstrate its ability in 3D vortex imaging with edge detection. These results provide a promising strategy for high-quality 3D vortex imaging and edge enhancement, and might pave the way for future applications in the fields such as edge detection and pattern recognition.

3D trapezoidal edge coupler with high efficiency and tolerance based on Silicon-on-Insulator

Edge couplers connecting the optical fiber and the on-chip waveguide are indispensable devices in integrated photonics. In this study, a 3D edge coupler with trapezoidal cross-section is proposed and designed. High coupling efficiencies of the edge couplers are verified by theoretical calculations. The 3D trapezoidal edge couplers are fabricated on the thick-silicon layer of a Silicon-on-Insulator (SOI) substrate by using 3D grayscale lithography. Over the communication band (C-band), the fiber-to-chip measured results indicate that the maximum coupling efficiency of the 3D edge coupler is 0.68/0.99 dB for the TE/TM mode. The misalignment tolerances are less than 0.65 dB and 0.90 dB for the TE and TM modes within ±5 μm in the horizontal direction. The same measured values are less than 0.60 dB for both the TE and TM modes within 4 μm in the vertical direction. The excellent coupling characteristics of the 3D edge coupler are attractive for the large-scale photonic integration.

Fiber-to-Chip Three-Dimensional Silicon-on-Insulator Edge Couplers with High Efficiency and Tolerance.

The edge coupler is an indispensable optical device for connecting an external fiber and on-chip waveguide. The coupling efficiency of the edge coupler affects the effective integration of optical circuits. In this study, three-dimensional (3D) edge couplers with high efficiency and tolerance are proposed. The high coupling efficiency of the 3D edge couplers is verified by theoretical calculations. Three couplers are fabricated on a thick-silicon platform via 3D grayscale lithography. At the 1550 nm band, the fiber-to-chip experimental data show that the maximum coupling efficiencies of the three edge couplers are 0.70 dB and 1.34 dB, 0.80 dB and 1.60 dB, and 1.00 dB and 1.14 dB for the TE and TM modes, respectively. At the 1550 nm band, misalignment tolerances measurement data reveal 0.8 dB/0.9 dB tolerance of ±5 μm in the horizontal direction, and 1.7 dB/1.0 dB tolerance of ±2 μm in the vertical direction for TE/TM mode. This study provides a new idea for the design of 3D edge couplers and demonstrates significant superiority in research and industrial applications.

Valence and Core Photoelectron Spectra of Aqueous I3- from Multi-Reference Quantum Chemistry.

The I3- molecule is known to undergo substantial structural reorganization upon solvation by a protic solvent, e.g., water. However, the details of this process are still controversially discussed in the literature. In the present study, we combined experimental and theoretical efforts to disentangle this controversy. The valence (5p), N4,5 (4d), and M4,5 (3d) edge photoelectron spectra were measured in an aqueous solution and computed using high-level multi-reference methods. Our previous publication mainly focused on obtaining reliable experimental evidence, whereas in the present article, we focused primarily on theoretical aspects. The complex electronic structure of I3- requires the inclusion of both static and dynamic correlation, e.g., via the multi-configurational perturbation theory treatment. However, the resulting photoelectron spectra appear to be very sensitive to problems with variational stability and intruder states. We attempted to obtain artifact-free spectra, allowing for a more reliable interpretation of experiments. Finally, we concluded that the 3d Photoelectron Spectrum (PES) is particularly informative, evidencing an almost linear structure with a smaller degree of bond asymmetry than previously reported.

Pavement Crack Detection Based on 3D Edge Representation and Data Communication With Digital Twins

With digital information applied in intelligent transportation system, pavement crack detection with digital twins has drawn widely attention since the past several years. However, it is still a challenge task to accomplish crack detection satisfactory results due to complex pavement background. This paper presents a pavement crack detection method based on 3D edge representation and data communication with digital twins. Firstly, pavement data is achieved by multiple sensors including video data and 3D scanning technology, and the digital twins based model is constructed based on data communication. Secondly, to distinguish between crack feature and pavement background in depth level, the point cloud data enhancement method based on fractional differential is proposed to strengthen crack boundary and maintain detail simultaneously. Thirdly, a 3D crack segmentation algorithm is proposed based on edge feature representation. After improved filter function with plane proximity and depth similarity, the gradient magnitude values of every point are estimated by the neighborhood and direction. Two thresholds are computed automatically using the iteration method to extract the crack from pavement. Finally, the dataset is established by 2600 crack data, and extensive experiments verify the proposed method could conduct better result compared with other existing methods using F-measure evaluation system.

Coupled KIPP-EDGE2D modeling of parallel transport in the SOL and divertor plasma for the ITER baseline scenario

The KInetic code for Plasma Periphery (KIPP) models the parallel (along magnetic field lines) propagation of charged particles in the scrape-off layer (SOL) and divertor of tokamaks. An iterative coupling between KIPP and a 2D edge fluid code, EDGE2D, which in turn is coupled to the Monte Carlo solver for neutrals, EIRENE, was used to achieve a converged KIPP-EDGE2D-EIRENE solution. In the iterative coupling algorithm, KIPP transfers kinetic parallel electron and ion heat conductivities to EDGE2D, whereas EDGE2D returns to KIPP 2D distributions of macroscopic plasma parameters across the computations grid. The initial EDGE2D-EIRENE solution simulated the SOL and divertor plasma of the ITER inter-edge localized mode (ELM) baseline scenario. This work employs the same methodology as an earlier study based on the analysis of JET high radiative H-mode conditions, with strong nitrogen injection leading to partial detachment at divertor targets (Chankin et al 2022 Plasma Phys. Control. Fusion 64 095007). The results are qualitatively similar to those of the JET study in demonstrating the strong heat flux limiting effect, together with the rise in electron and ion temperatures in the main SOL. At the same time, the kinetic effects of the parallel propagation of charged particles are not expected to drastically change the target power deposition at divertor targets calculated by EDGE2D-EIRENE alone.

Automatic 3D CAD models reconstruction from 2D orthographic drawings

This paper introduces a two-stage approach that automatically generates 3D CAD models from 2D orthographic drawings. First, a pattern-matching algorithm is proposed to reconstruct a network of 3D edges by matching 2D edge features extracted from the multiple views of the 2D drawing. Second, starting from the resulting 3D wireframe and generated graph, a loop detection algorithm allows identifying possible loops of faces. Then, a clustering algorithm recognizes the faces from the set of detected loops. The reconstruction ends while trimming and stitching the faces to get a watertight ready-to-use 3D CAD model. This approach has been validated on a public dataset composed of several thousands of 3D shapes, and it achieved 99.59% of well-reconstructed models in F-score.

Semi-analytic solutions to edge singularities of three-dimensional axisymmetric bodies

Axisymmetric geometries, such as cylindrical elements, are widely used in offshore structures. However, the presence of sharp edges in these geometries introduces challenges in numerical simulations due to singularities. To address this issue, one possible solution is to represent the singularities using analytic eigenfunctions. This approach can provide insights into the essence of the problem and has successfully applied to two-dimensional (2D) corner problems. However, finding appropriate eigenfunctions for the three-dimensional (3D) edges remains an open challenge. This paper proposes a semi-analytic scheme for 3D axisymmetric problems utilizing a scaled boundary finite element method (SBFEM). A dimensional reduction is introduced to the 3D Laplace equation, and a 3D edge is handled on the generatrix plane while governed by a complicated equation. The algorithm for resolving the SBFEM fundamental space is improved, and the singularities are approximated using a fractional-order basis. The effectiveness of the proposed method is demonstrated through its application to solve the radiation problem of a heaving cylinder. The method accurately captures the singular velocity field at the edge tip, ensuring that the boundary condition on the body surface is strictly satisfied in the neighborhood of the singularity. Accuracy of the mean drift force is ensured by performing direct pressure integrations over the body surface using a near-field formulation, which becomes as accurate as the middle-field formulation.

Improved Winding Losses Calculation Based on Bessel Functions

In this paper, an approach combining semi-empirical equations and the method of images is proposed for round conductor layer windings with un-gapped core. The new equation for proximity effect can convert the constant field strength from the magneto-motive force (MMF) across the core window into a frequency dependent uniform background magnetic field strength, which can take partly the interaction between conductors into account. Geometric factors are introduced by fitting the finite element method (FEM) results to improve the accuracy. The method of images is used to calculate the field strength in order to counteract the impact of 2D edge effect. The new method is compared with the 2D FEM, analytical methods, and is also validated by measurements with EE core transformers. The proposed method shows good accuracy (<10% error) compared to 2D FEM for both high and low porosity factor windings. Therefore, it can handle more winding configurations than other 1D analytical methods.

Real-time automated forest field inventory using a compact low-cost helmet-based laser scanning system

Forest field inventory plays a crucial role in forestry management and the estimation of carbon circular economy, as it provides information on forest parameters, assesses carbon storage, and identifies the impact factors of ecological change. Terrestrial Laser Scanning (TLS) and Mobile Mapping Systems (MMS) are commonly used for forest field inventory, but they are unable to verify the inventory results in real time. With real-time forest inventory, forestry workers can immediately verify if all trees have been correctly extracted without requiring expertise in point clouds. The advences of miniaturized, low-cost 3D sensors (such as solid-state laser scanners and Inertial Measurement Units [IMUs]) and edge computing units have made it possible to achieve real-time forest inventory using a compact, low-cost helmet. To this end, this paper presents a real-time automated forest field inventory method, which is validated on a compact, low-cost helmet-based laser scanning system. Firstly, a Fast Candidate Tree Detection (FCTD) approach is proposed to identify individual trees as candidates by utilizing a novel 2D corner detection technique based on point cloud projection, taking into account point density and geometry features. Secondly, a Spatiotemporal Consistency-based Tree Parameter Estimation (SCTPE) method is proposed to estimate the tree parameters by considering both the current submap and submaps that have been scanned in real-time. The proposed method was tested in three typical forest areas in Wuhan, China, where the main tree species present include Sapindaceae, dawn redwoods, and Platycladus. The results showed that the proposed method achieves high accuracy in tree detection (recall=0.97,precision=0.94,F=0.96). The average error and root-mean-square error (RMSE) of DBH are 0.033 m and 0.038 m, which outperforms the existing one-circle fitting model. The average error and RMSE of tree height are 0.231 m and 0.294 m. Overall, these results demonstrate the high potential of the helmet-based laser scanning system for real-time forest field inventory.

Simulation and comparison between multi-fluid and kinetic models of impurity transport

Impurity transport is a highly significant research topic in international fusion plasma simulations, which are mainly simulated by numerical codes at present. Most of the numerical simulation codes for impurity transport adopt multi-fluid or kinetic model to treat impurity particles. Therefore, it is necessary to select a suitable transport model for the simulation process. For impurity particles, if the mean free path of particles λ is much smaller than the gradient scale length of particles λ g, it is sufficient to treat the particles by the multi-fluid model. However, under some conditions, λ will be much larger than λ g. The applicability of the fluid model is limited when λ is larger than or equal to λ g. A comparison with the simulations on impurity transport treated with multi-fluid and kinetic models is necessary, respectively. In this study, the simulation results of carbon (C) impurity transport in the EAST scrape-off layer with the 2D edge plasma fluid code SOLPS-ITER and the 2D Monte Carlo impurity transport code DIVIMP are compared. The comparison between the distributions of carbon impurities ( C 0 ∼ C + 6) in the different ionization states and the CIII emissivity predicted by SOLPS-ITER and DIVIMP shows that the density distributions of carbon atoms C 0 predicted by the SOLPS-ITER and DIVIMP codes are similar. However, for carbon ions in different ionization states, the variations between the density distributions simulated from the SOLPS-ITER and DIVIMP codes can become larger with the increase in ionization states. DIVIMP performs slightly better than SOLPS-ITER in reproducing the shape of the CIII profile when drifts are switched off in SOLPS-ITER, but the difference is extremely small in terms of the uncertainties involved in these calculations.

The Atomic Drill Bit: Precision Controlled Atomic Fabrication of 2D Materials.

The ability to deterministically fabricate nanoscale architectures with atomic precision is the central goal of nanotechnology, whereby highly localized changes in the atomic structure can be exploited to control device properties at their fundamental physical limit. Here, an automated, feedback-controlled atomic fabrication method is reported and the formation of 1D-2D heterostructures in MoS2 is demonstrated through selective transformations along specific crystallographic orientations. The atomic-scale probe of an aberration-corrected scanning transmission electron microscope (STEM) is used, and the shape and symmetry of the scan pathway relative to the sample orientation are controlled. The focused and shaped electron beam is used to reliably create Mo6 S6 nanowire (MoS-NW) terminated metallic-semiconductor 1D-2D edge structures within a pristine MoS2 monolayer with atomic precision. From these results, it is found that a triangular beam path aligned along the zig-zag sulfur terminated (ZZS)direction forms stable MoS-NW edge structures with the highest degree of fidelity without resulting in disordering of the surrounding MoS2 monolayer. Density functional theory (DFT) calculations and ab initio molecular dynamic simulations (AIMD) are used to calculate the energetic barriers for the most stable atomic edge structures and atomic transformation pathways. These discoveries provide an automated method to improve understanding of atomic-scale transformations while opening a pathway toward more precise atomic-scale engineering of materials.

Parametric study of midplane gas puffing to maximize ICRF power coupling in ITER

Midplane gas puffing close to the ion cyclotron range of frequencies (ICRF) antennae has been demonstrated to be robust in improving ICRF power coupling in current tokamaks. It is also shown in a previous study (Zhang 2019 Nucl. Mater. Energy 19 364–71) that in ITER, midplane gas puffing with a puff rate of ∼4.5 × 1022 electrons s−1 can increase the antenna loading/coupling resistance by about a factor of two. In this paper, a comprehensive parametric study has been carried out to characterize the influence of midplane gas puffing on ICRF power coupling in additional and broader range of parameter scans. The new parameter scans include the gas puff rate, the poloidal location of the gas pipe orifices (GPOs), the separatrix density, the particle perpendicular diffusion coefficient, the radial distance between the plasma and antenna as well as the antenna phasing. The 3D edge plasma fluid and neutral transport code EMC3-EIRENE code has been used to simulate the 3D distributions of plasma density in the presence of gas puffing, which are then used in the antenna code ANTITER II to calculate the antenna coupling. The simulation results indicate that the ITER ICRF local midplane gas injection layout (with the GPOs located on one side of each antenna port) increases the ICRF power coupling significantly in all studied plasma scenarios and antenna parameters. We are hence confident that the chosen layout for the ICRF local gas injection on ITER is appropriate. We are also confident that the ITER local gas injection will allow boosting the ICRF coupling with all studied plasma conditions and antenna phasings.

3D SOI edge coupler design for high tolerance

We designed and manufactured two single-mode fiber-to-chip three-dimensional (3D) edge couplers with taper and semi-cone structures on a 3.5 µm silicon device layer of a silicon-on-insulator. The 3D finite-difference time-domain is used to simulate and optimize the structure of the edge couplers within the 1550 nm band. The simulation results reveal a maximum coupling efficiency of the 3D edge couplers above 91.42% for the TE mode. The 3 dB coupling tolerances of the TE mode in horizontal and vertical directions are ±4.5 and ±1.5 µm, respectively. Laser-direct-writing grayscale lithography and inductive coupled plasma-reactive ion etching are used in the fabrication of 3D edge couplers. Experimental data show that 3D couplers have a maximum coupling efficiency of about 83.41% in the TE mode.