3D Mesh Research Articles

Study on the Mechanical Properties of Roots and Friction Characteristics of the Root–Soil Interface of Two Tree Species in the Coastal Region of Southeastern China

The tensile strength of roots and the friction characteristics of the root–soil interface of tree species are the indicators that play a crucial role in understanding the mechanism of soil reinforcement by roots. To calculate the effectiveness of the reinforcement of soil by tree roots based on essential influencing parameters, typical trees in the coastal region of southeastern China selected for this study were subjected to tests of the tensile mechanical properties of their roots, as well as studies on the friction characteristics of the root–soil interface and the microscopic interfaces. The results indicated that in the 1–7 diameter classes, the root tensile strength of both Pinus massoniana and Cunninghamia lanceolata was negatively correlated with the root diameter in accordance with the power function. The root tensile strength of these two trees, however, was positively correlated with the lignin content but negatively correlated with cellulose and hemicellulose contents. The shear strength at the root–soil interface and the vertical load exhibited a constitutive relationship, which followed the Mohr–Coulomb criterion. As the root diameter increased, both the cohesion and the friction coefficients at the root–soil interface gradually increased, but the growth rate stood at around 15%. The cohesion value of the root–soil interface of the two trees decreased linearly with the increase in soil moisture content within the range of 25 to 45%. At the microinterface, the root surface of C. lanceolata exhibited concave grooves and convex ridges that extended along the axial direction of roots, with their height differences increasing with the enlargement of the root diameter. The rough surface of P. massoniana roots had areas composed of polygonal meshes, with an increase observed in the mesh density with increasing root diameter.

3D meshes dataset of sagittal otoliths from red mullet in the Mediterranean Sea

This paper presents a dataset of 3D sagittal left otolith meshes from 339 individual red mullet (Mullus barbatus). These immature specimens were collected from 17 geographical areas covering the entire Mediterranean Sea. Measured biological parameters were: fish total length (TL ± 1 mm, range from 125 to 238 mm), total weight (W ± 0.1 g, range from 14.9 to 168.0 g), sex (S), sexual maturity staging (Mat). The 3D otolith dataset comprises high-resolution meshes of otoliths obtained using microtomography (29.2 μm voxel size). The data offer valuable insights into the morphological variability and population structure of red mullet populations in the Mediterranean Sea. Potential applications of the dataset include age determination, stock identification, and population connectivity analysis. These applications aim to enhance the understanding of red mullet populations and contribute to the sustainable management of marine resources in the Mediterranean Sea.

Site response analysis by generating a new 3d mesh design with surface topography: a 3d site response analysis of northwest Turkey

Predicting soil behavior under dynamic load due to earthquakes is pivotal for engineering structures and human life. Due to various limitations, such as insufficient computers and difficulties in generating models, the third-dimension effect is generally neglected in many studies. Conversely, the third-dimension effect in regions with high topographic differences, deep basins, three-dimensional heterogeneous and anisotropic environments, and alluvium is at a level that cannot be neglected. This study created a three-dimensional model of the northwest of Turkey for the first time by including surface topography. Soil properties were added to this model, and dynamic analysis was performed. This new model aims to increase the accuracy of ground motion predictions in Northwest Turkey. The accuracy of this model was analyzed using real earthquake data recorded in the study area. In addition, a new software (SiteEffect3D) with various features has been developed to create a three-dimensional mesh with topography using digital elevation model data and to perform dynamic analysis more effectively. This software has been tested comparatively with “Plaxis 3D” software using synthetic terrain models. The importance of this study is that in addition to its contributions to site response analysis and seismic hazard assessment, new software has been developed that can be used in similar studies. The findings will provide valuable information for seismic design and construction practices and facilitate the development of more effective strategies to reduce the potential damage from earthquakes in the region.

Formulating facial mesh tracking as a differentiable optimization problem: a backpropagation-based solution

Facial mesh tracking enables the production of topologically consistent 3D facial meshes from stereo video input captured by calibrated cameras. This technology is an integral part of many digital human applications, such as personalized avatar creation, audio-driven 3D facial animation, and talking face video generation. Currently, most facial mesh tracking methods are built on computer graphics techniques, which involve complex procedures and often necessitate human annotation within pipelines. As a result, these approaches are difficult to implement and hard to generalize across various scenarios. We propose a backpropagation-based solution that formulates facial mesh tracking as a differentiable optimization problem called the BPMT. Our solution leverages visual clues extracted from the stereo input to estimate vertex-wise geometry and texture information. The BPMT is composed of two steps: automatic face analysis and mesh tracking. In the first step, a range of visual clues are automatically extracted from the input, including facial point clouds, multi-view 2D landmarks, 3D landmarks in the world coordinate system, motion fields, and image masks. The second step can be viewed as a differentiable optimization problem, with constraints comprising stereo video input and facial clues. The primary objective is to achieve topologically consistent 3D facial meshes across frames. Additionally, the parameters to be optimized encompass the positions of free-form deformed vertices and a shared texture UV map. Furthermore, the 3D morphable model (3DMM) is introduced as a form of regularization to enhance the convergence of the optimization process. Leveraging the fully developed backpropagation software, we progressively register the facial meshes to the recorded object, generating high-quality 3D faces with consistent topologies. The BPMT requires no manual labeling within the pipeline, making it suitable for producing large-scale stereo facial data. Moreover, our method exhibits a high degree of flexibility and extensibility, positioning it as a promising platform for future research in the community.

A Heat Method for Generalized Signed Distance

We introduce a method for approximating the signed distance function (SDF) of geometry corrupted by holes, noise, or self-intersections. The method implicitly defines a completed version of the shape, rather than explicitly repairing the given input. Our starting point is a modified version of the heat method for geodesic distance, which diffuses normal vectors rather than a scalar distribution. This formulation provides robustness akin to generalized winding numbers (GWN) , but provides distance function rather than just an inside/outside classification. Our formulation also offers several features not common to classic distance algorithms, such as the ability to simultaneously fit multiple level sets, a notion of distance for geometry that does not topologically bound any region, and the ability to mix and match signed and unsigned distance. The method can be applied in any dimension and to any spatial discretization, including triangle meshes, tet meshes, point clouds, polygonal meshes, voxelized surfaces, and regular grids. We evaluate the method on several challenging examples, implementing normal offsets and other morphological operations directly on imperfect curve and surface data. In many cases we also obtain an inside/outside classification dramatically more robust than the one obtained provided by GWN.

EASI-Tex: Edge-Aware Mesh Texturing from Single Image

We present a novel approach for single-image mesh texturing , which employs a diffusion model with judicious conditioning to seamlessly transfer an object's texture from a single RGB image to a given 3D mesh object. We do not assume that the two objects belong to the same category, and even if they do, there can be significant discrepancies in their geometry and part proportions. Our method aims to rectify the discrepancies by conditioning a pre-trained Stable Diffusion generator with edges describing the mesh through ControlNet, and features extracted from the input image using IP-Adapter to generate textures that respect the underlying geometry of the mesh and the input texture without any optimization or training. We also introduce Image Inversion , a novel technique to quickly personalize the diffusion model for a single concept using a single image , for cases where the pre-trained IP-Adapter falls short in capturing all the details from the input image faithfully. Experimental results demonstrate the efficiency and effectiveness of our edge-aware single-image mesh texturing approach, coined EASI-Tex, in preserving the details of the input texture on diverse 3D objects, while respecting their geometry. Code : https://github.com/sairajk/easi-tex

Very High-Order Accurate Discontinuous Galerkin Method for Curved Boundaries with Polygonal Meshes

Preserving the optimal convergence order of discontinuous Galerkin (DG) discretisations in curved domains is a critical and well-known issue. The proposed approach relies on the reconstruction for off-site data (ROD) method developed originally within the finite volume framework. The main advantages are simplicity, since the PDE solver only considers polygonal domains, and versatility, since any type of boundary condition can be imposed. The developed DG–ROD method consists in splitting the boundary conditions treatment and the leading discrete equations from a classical DG formulation into two independent solvers coupled in a simple and efficient iterative procedure. A numerical benchmark is provided to assess the capability of the method with Dirichlet and Neumann boundary conditions prescribed on curved boundaries, demonstrating that the optimal convergence order is effectively achieved.

From coin to 3D face sculpture portraits in the round of Roman emperors

Representing historical figures on visual media has always been a crucial aspect of political communication in the ancient world, as it is in modern society. A great example comes from ancient Rome, when the emperor’s portraits were serially replicated on visual media to disseminate his image across the countries ruled by the Romans and to assert the power and authority that he embodied by making him universally recognizable. In particular, one of the most common media through which ancient Romans spread the imperial image was coinage, which showed a bi-dimensional projection of his portrait on the very low relief produced by the impression of the coin-die. In this work, we propose a new method that uses a multi-modal 2D and 3D approach to reconstruct the full portrait in the round of Roman emperors from their images adopted on ancient coins. A well-defined pipeline is introduced from the digitization of coins using 3D scanning techniques to the estimation of the 3D model of the portrait represented by a polygonal mesh. A morphable model trained on real 3D faces is exploited to infer the morphological (i.e., geometric) characteristics of the Roman emperor from the contours extracted from a coin portrait using a model fitting procedure. We present examples of face reconstruction of different emperors from coins produced in Rome as well as in the imperial provinces, which sometimes showed local variations of the official portraits centrally designed.

Numerical simulation of the vortex-induced vibrations of a 4:1 rectangular cylinder subjected to yaw uniform currents

The practical engineering structures are not always perpendicular to the wind but often in skew positions. This yawed configuration may lead to more complex three-dimensional flow characteristics and different vortex-induced vibration (VIV) responses. However, the related study is very inadequate. Therefore, comprehensive numerical investigations of the VIV characteristics of a 4:1 rectangular cylinder have been conducted using the three-dimensional (3D) Large-Eddy Simulation (LES) at five different yaw angles (β = 0°, 5°, 10°, 20°, 30°). An innovative method for creating 3D meshes was introduced, demonstrating a good agreement with the experimental results while significantly reducing the mesh number, and consequently the computation time. The VIV response, pressure distribution, aerodynamic force, flow field, and energy input/output were analyzed for various yaw angles. The results demonstrate that the periodic boundary conditions on the spanwise domain side is more reliable than those of the wall boundary conditions. The velocity component parallel to the cylinder axis can be ignored in the analysis of elastically-mounted rectangular rigid cylinders for β up to 30°. If only considering the perpendicular axis velocity component, the amplitudes and lock-in regions for β = 5°, 10°, 20°, and 30° are highly consistent with those of β = 0°, which have effectively validated the accuracy of Independence Principle in evaluating the VIV of a 4:1 rectangular cylinder.

3D Reconstruction from a Single Sketch via View-dependent Depth Sampling.

Reconstructing a 3D shape based on a single sketch image is challenging due to the inherent sparsity and ambiguity present in sketches. Existing methods lose fine details when extracting features to predict 3D objects from sketches. Upon analyzing the 3D-to-2D projection process, we observe that the density map, characterizing the distribution of 2D point clouds, can serve as a proxy to facilitate the reconstruction process. In this work, we propose a novel sketch-based 3D reconstruction model named SketchSampler. It initiates the process by translating a sketch through an image translation network into a more informative 2D representation, which is then used to generate a density map. Subsequently, a two-stage probabilistic sampling process is employed to reconstruct a 3D point cloud: firstly, recovering the 2D points (i.e., the x and y coordinates) by sampling the density map; and secondly, predicting the depth (i.e., the z coordinate) by sampling the depth values along the ray determined by each 2D point. Additionally, we convert the reconstructed point cloud into a 3D mesh for wider applications. To reduce ambiguity, we incorporate hidden lines in sketches. Experimental results demonstrate that our proposed approach significantly outperforms other baseline methods.

Virtual reality in geoeducation: the case of the Lesvos Geopark

ABSTRACT The aim of this study is to investigate the contribution of cartographic results obtained from data acquired with Unmanned Aerial Vehicles to the management procedures of geoheritage monuments, specifically in geoeducation. 2D orthophotomaps and 3D textured meshes of a fossil site in the Lesvos Geopark, Greece, which has been monitored since 2018, were generated. The data recordings were collected using a UAV at different flight altitudes for three different cartographic scales. After acquiring UAV and Global Navigation Satellite Systems data, the resulting cartographic products were used to create educational material on geosites. This material was used to deliver lectures to students in various settings: (a) in situ at the Natural History Museum of the Lesvos Petrified Forest, (b) live in a traditional classroom, (c) remotely via e-class software, and (d) in a collaborative Virtual Reality environment. Feedback was provided by students through customized questionnaires, and their knowledge acquisition was assessed post-lecture with specially designed assignments. The final section of this work compares learning experiences and knowledge acquisition across these different environments. The results contribute to the debate on 2D and 3D cartography in geoeducation, quantifying the value of new materials in understanding spatial and geographic features and improving geoheritage management.

Optimal convergence analysis of the virtual element methods for viscoelastic wave equations with variable coefficients on polygonal meshes

Optimal convergence analysis of the virtual element methods for viscoelastic wave equations with variable coefficients on polygonal meshes

Depth Prior-Guided 3D Voxel Feature Fusion for 3D Semantic Estimation from Monocular Videos

Existing 3D semantic scene reconstruction methods utilize the same set of features extracted from deep learning networks for both 3D semantic estimation and geometry reconstruction, ignoring the differing requirements of semantic segmentation and geometry construction tasks. Additionally, current methods allocate 2D image features to all voxels along camera rays during the back-projection process, without accounting for empty or occluded voxels. To address these issues, we propose separating the features for 3D semantic estimation from those for 3D mesh reconstruction. We use a pretrained vision transformer network for image feature extraction and depth priors estimated by a pretrained multi-view stereo-network to guide the allocation of image features within 3D voxels during the back-projection process. The back-projected image features are aggregated within each 3D voxel via averaging, creating coherent voxel features. The resulting 3D feature volume, composed of unified voxel feature vectors, is fed into a 3D CNN with a semantic classification head to produce a 3D semantic volume. This volume can be combined with existing 3D mesh reconstruction networks to produce a 3D semantic mesh. Experimental results on real-world datasets demonstrate that the proposed method significantly increases 3D semantic estimation accuracy.

Scaled boundary finite element based two-level learning approach for structural flaw identification

A comprehensive framework that combines classification and regression techniques through machine learning (ML) algorithms to address the inverse problem of flaw identification and quantification is proposed. The framework uses the scaled boundary finite element method (SBFEM) and quadtree (octree mesh in 3D) to compute displacements for various flaw shapes and specified boundary conditions. The flaw data, such as their numbers, location, and size, along with the displacement data, serve as the input for ML models. A random forest model is used to predict the number of flaws, while an artificial neural network (ANN) employing a fully connected multi-layer perceptron is utilized to predict flaw locations and sizes. The framework underwent rigorous testing to identify the number and location of multiple flaws (circular and elliptical) in 2D structures. The accuracy of the classification and regression models for flaw detection, ranging from one to four circular flaws, is observed to be 98%. As an extension of its capabilities, the proposed model successfully identifies multiple flaws and their features in 3D structures as well with 98% accuracy, demonstrating the robustness of the proposed approach.

Accurately Computing the Interacted Volume of Molecules over Their 3D Mesh Models.

For quickly predicting the rational arrangement of catalysts and substrates, we previously proposed a method to calculate the interacted volumes of molecules over their 3D point cloud models. However, the nonuniform density in molecular point clouds may lead to incomplete contours in some slices, reducing the accuracy of the previous method. In this paper, we propose a two-step method for more accurately computing molecular interacted volumes. First, by employing a prematched mesh slicing method, we layer the 3D triangular mesh models of the electrostatic potential isosurfaces of two molecules globally, transforming the volume calculation into finding the intersecting areas in each layer. Next, by subdividing polygonal edges, we accurately identify intersecting parts within each layer, ensuring precise calculation of interacted volumes. In addition, we present a concise overview for computing intersecting areas in cases of multiple contour intersections and for improving computational efficiency by incorporating bounding boxes at three stages. Experimental results demonstrate that our method maintains high accuracy in different experimental data sets, with an average relative error of 0.16%. On the same experimental setup, our average relative error is 0.07%, which is lower than the previous algorithm's 1.73%, improving the accuracy and stability in calculating interacted volumes.

Numerical integration in the virtual element method with the scaled boundary cubature scheme

AbstractThe virtual element method (VEM) is a stabilized Galerkin method on meshes that consist of arbitrary (convex and nonconvex) polygonal and polyhedral elements. A crucial ingredient in the implementation of low‐ and high‐order VEM is the numerical integration of monomials and nonpolynomial functions over such elements. In this article, we apply the recently proposed scaled boundary cubature (SBC) scheme to compute the weak form integrals in various virtual element formulations over polygonal and polyhedral meshes. In doing so, we demonstrate the flexibility of the approach and the accuracy that it delivers on a broad suite of boundary‐value problems in 2D and 3D over polytopes with affine faces as well as on elements with curved boundaries. In addition, the use of the SBC scheme is exemplified in an enriched Poisson formulation of the VEM in which weakly singular functions are required to be integrated. This study establishes the SBC method as a simple, accurate and efficient integration scheme for use in the VEM.

A Comparative Study between Intra-Operative Difficulties and Early Postoperative Complications in Laparoscopic Inguinal Hernia Repair Using Conventional Polypropylene Mesh and 3D Mesh – A Meta-Analysis

Abstract Background The fundamental mechanism of abdominal wall hernia formation is the loss of structural integrity at the musculotendinous layer. The exact cause of inguinal hernia is still unknown but the factors contributing in its occurrence include; preformed congenital sac, chronic passive rise in the intra-abdominal pressure and weak abdominal wall. Objective To assess laparoscopic inguinal hernia repair using two different meshes: The conventional polyproline mesh and the three-dimensional (3D) mesh, as regard the operative application time, early post-operative complications including seroma, early pain, sensory impairment, surgical site infection (SSI) and hospital stay time using meta-analysis approach. Patients and Methods In our study ten trials included, three trials regarding 3d mesh versus conventional mesh in laparoscopic inguinal hernia repair including 9,118 participants were selected from electronic databases. Three trials regarding 3d mesh and four trials regarding polyprolene mesh. Data Sources Medline databases (PubMed, Medscape, ScienceDirect. EMF-Portal) and all materials available in the Internet till 2021. Results There is significant heterogeneity among trials (P = 0.002, I2 = 84%), mean difference 1.17, 95% CI -2.18, 4.52 and there is no statistically significance z = 0.49. Conclusion There is no difference between conventional polyprolene and 3d mesh regarding intra- operative difficulties (operative time) and post-operative complications (chronic pain, recurrence, operative time and seroma).

247 Prophylactic Use of 3D Intraperitoneal Mesh in the Prevention of Parastomal Hernia in Permanent Colostomies After Rectal Cancer Resection

Abstract Background Parastomal hernia (PSH) is the most common complication of stomas associated with significant morbidity. Prophylactic mesh in preventing PSH is less well studied, and evidence is conflicting. We compare PSH rates in patients in whom 3D intraperitoneal mesh was and was not used prophylactically in a cohort of rectal cancer patients undergoing elective curative resection. Method Retrospective data from the Somerset Database and Electronic Patient Record were collected on patients under a single consultant surgeon between May 2016 and December 2021. Follow up was for a minimum of 2 years (excluding deaths). Appropriate statistical tests of difference significance were performed for proportions of categorical data, and time to hernia occurrence in patients with and without Dynamesh IPST placement. (Fisher’s Exact test; Kaplan Meier) Results From 397 colorectal cancer patients under the care of a single surgeon, 223 had elective surgery with curative intent, of which 63 (28%) underwent total mesorectal excision (TME) (30 TME & ileostomy, 12 TME Hartmann and 21 APER) - 90% laparoscopic. 16 patients had prophylactic mesh used. Demographics and co-morbidities between groups were similar. PSH incidence was 1 (6%) (radiological) vs.7 (41%) (clinical) in the mesh vs. non-mesh group; P=0.039. Post operative complications and pain scores differed only slightly. Time to hernia development did not differ between groups. Conclusions Use of prophylactic mesh during permanent stoma formation in our practice appears safe, and effective in preventing PSH. Further studies may answer the question “Should 3D collared mesh be routinely placed during the formation of permanent stomas to prevent parastomal hernia?”

Deep learning and integrated approach to reconstruct meshes from tomograms of 3D braided composites

The meticulous reconstruction of three-dimensional (3D) braided composite materials serves as a crucial foundation for achieving high-fidelity simulations. Nonetheless, the transition from tomographic images to a 3D mesh entails a laborious and time-intensive process. To address this, an integrated procedure based on artificial intelligence is proposed for reconstructing meshes from tomograms. The initial stage of the process involves employing artificial intelligence techniques to segment complex contours and optimize high-dimensional contours. This facilitates the input of high-quality images needed to reconstruct accurate digital twins with strong convergence. The subsequent reconstruction phase integrates various calculations, including shape interpolation, contour extraction, 3D surface reconstruction, 3D mesh reconstruction, and element data interpolation. During this process, optimization objectives are set to minimize the deviation between the digital twin's surface and the actual surface, as well as to optimize the aspect ratio of the element mesh. Upon completion of the aforementioned steps, high-quality input files suitable for finite element calculations are directly generated. Ultimately, the proposed method utilizes the reconstructed finite element model for mechanical analysis, and the results are found to be in good agreement with experimental tests. This method offers an efficient and rapid way to achieve high-quality reconstruction of complex digital twins.

Influence of Magnetic Polarization on Diagrams of Inductive and Electromagnetic Logs

Abstract ––We present the results of the study of the effect of induced magnetic polarization of clay beds under the influence of an external harmonic electromagnetic field (frequencies 70 and 875 kHz). A two-stage numerical modeling procedure is proposed. At the first stage we determine the effective relative magnetic permeability of a synthetic sample with inclusions of clay particles. In this case a 3D heterogeneous mesh sample is generated. Then we numerically model a spatial distribution of an electric field. The electromotive force (EMF) induced in the measuring coil is calculated from this distribution. Relative magnetic permeability is determined by comparison with EMF of homogeneous samples with different values of magnetic permeability. It has been found that during the electric field excitation by an alternating current coil, the effect of induced magnetic polarization appears in the sample with clay particles. Its manifestation is that the effective magnetic permeability becomes complex. At the second stage we calculate the EMF diagram of the three-coil logging probe in the macro-model ‘clay cap – reservoir’. Magnetic permeability of the clay cap is given by a complex value. In the generated logs, extremes appear in the vicinity of the bottom of the clay cap; they do not correspond to the distribution of electrical conductivity and magnetic permeability in the given model. They can be incorrectly interpreted when analyzing real logs into individual formations. Numerical modeling at all stages is performed by the Vector Finite Element Method on a consistent adaptive tetrahedral partition and the first-order Webb vector basis.