Surface Mesh Research Articles

A Mesh-Based Approach for Computational Fluid Dynamics-Free Aerodynamic Optimisation of Complex Geometries Using Area Ruling

In this paper, an optimisation procedure is introduced that uses a significantly cheaper, and CFD-free, objective function for aerodynamic optimisation than conventional CFD-driven approaches. Despite the reduced computational cost, we show that this approach can still drive the optimisation scheme towards a design with a similar reduction in drag coefficient for wave drag-dominated problems. The approach used is ‘CFD-free’, i.e., it does not require any computational aerodynamic analysis. It can be applied to geometries discretised using meshes more conventionally used for ‘standard’ CFD-based optimisation approaches. The approach outlined in this paper makes use of the transonic area rule and its supersonic extension, exploiting a mesh-based parameterisation and mesh morphing methodology. The paper addresses the following question: ‘To what extent can an optimiser perform (wave) drag minimisation if using ‘area ruling’ alone as the objective (fitness) function measurement?’. A summary of the wave drag approximation in transonic and supersonic regimes is outlined along with the methodology for exploiting this theory on a typical CFD surface mesh to construct an objective function evaluation for a given geometry. The implementation is presented including notes on the considerations required to ensure stability, and error minimisation, of the numerical scheme. The paper concludes with the results from a number of (simple and complex geometry) examples of a drag-minimisation optimisation study and the results are compared with an approach using full-fidelity CFD simulation. The overall conclusions from this study suggest that the approach presented is capable of driving a geometry towards a similar shape to when using full-fidelity CFD at a significantly lower computational cost. However, it cannot account for any constraints, driven by other aerodynamic factors, that might be present within the problem.

Compact and water flushing resistant mesh biofilms forming at short SRT disappeared naturally under extended SRT in dynamic membrane bioreactor

Extending the solids retention time (SRT) has been demonstrated to mitigate membrane biofouling. Nevertheless, it remains an intriguing question whether the compact and water flushing resistant mesh biofilms developed at short SRT can undergo biodegradation and be removed with extended SRT. In present study, the bio-fouled mesh filter in the 10d-SRT dynamic membrane bioreactor (DMBR), with mesh surfaces and pores covered by compact and water flushing resistant biofilms exhibiting low water permeability, was reused in the 40d-SRT DMBR without any cleanings. After being reused at 40d-SRT, its flux driven by gravity occurred from the 10th day and recovered to a regular level of 36.7 L m−2·h−1 on the 27th day. Both scanning electron microscope (SEM) and confocal laser scanning microscopy (CLSM) analyses indicated that the compact mesh biofilms formed at10d-SRT biodegraded and were removed at 40d-SRT, with the residual biofilms becoming removable by water flushing. As a result, the hydraulic resistance of the bio-fouled mesh filter decreased from 4.36 × 108 to 6.97 × 107 m−1, and its flux fully recovered. The protein and polysaccharides densities in mesh-biofilms decreased from 24.4 to 9.7 mg/cm2 and from 10.7 to 0.10 mg/cm2, respectively, which probably have contributed to the disappearance of compact biofilms and the decrease in adhesion. Furthermore, the sludge and mesh-biofilms in the 40d-SRT reactor contained a higher relative abundance of dominant quorum quenching bacteria, such as Rhizobium (3.52% and 1.35%), compared to those in the 10d-SRT sludge (0.096%) and mesh biofilms (0.79%), which might have been linked to a decline in extracellular polymeric substances and, consequently, the biodegradation and disappearance of compact biofilms.

Enhanced mesoscale and macroscale parameters for accurate 3D shape characterization

This paper investigates the limitations of widely used 3D Wadell's roundness and true sphericity metrics for characterizing granular materials. It introduces two improved indices: the mesoscale interlocking index and the radial distance factor. The study involves diverse particles scanned using optical interferometry and X-ray computed tomography. A mean curvature method is employed for surface segmentation, and a computationally efficient 3D mesh simplification procedure is proposed. Python scripts are developed for surface segmentation, mesh simplification, and 3D shape characterization. The new indices are validated by assessing angular and rounded 3D particles and changes in the shape of aggregates through the Los Angeles abrasion test. The results demonstrate the ability of the proposed indices to differentiate visually similar particles with identical Wadell's roundness and true sphericity, showcasing their effectiveness in accurately describing particle shape. The statistical distribution of 3D particle curvatures offers an alternative method for understanding particles' shape and abrasion.

The analysis of extension evolution law and damage behavior characteristic for line microcracks on Si3N4 bearing balls

To predict the relation between extension evolution law and damage of line microcracks on silicon nitride bearing balls. Firstly, the 3D point cloud features of line microcracks are obtained based on multi-image 3D reconstruction. Next, the point cloud diagram data is optimized to fit the molecular dynamics geometric model of line microcracks extension process. Then, according to the Si3N4 molecular dynamics deep learning potential, the molecular dynamics mechanical model is established. Finally, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is used to numerically solve the extension evolution of line microcracks. The experiment result shows that from the change analysis of single-layer surface mesh, the microcracks extension is concentrated in the central region of the indentation. The new microcracks spread along both sides of the original microcracks. After uniformly distributed load is applied to line microcracks, there is a phenomenon of concentrated swirling microcracks formation under the indentation region. By analyzing the atomic coordination number nephogram, the microcracks extension occurs when the proportion of amorphous atoms is up to 7 % during loading. And the plastic deformation occurs when the proportion of amorphous atoms is dropped to 6 % during unloading. In addition, in the process of indentation loading, plastic deformation and slip zone occur on Si3N4 bearing balls surface. However, the strain is accumulated in the middle region during unloading. The slip zone moves inward and becomes thin, and the elastic deformation partially is recovered.

Automatic Coronary Artery Plaque Quantification and CAD-RADS Prediction Using Mesh Priors.

Coronary artery disease (CAD) remains the leading cause of death worldwide. Patients with suspected CAD undergo coronary CT angiography (CCTA) to evaluate the risk of cardiovascular events and determine the treatment. Clinical analysis of coronary arteries in CCTA comprises the identification of atherosclerotic plaque, as well as the grading of any coronary artery stenosis typically obtained through the CAD-Reporting and Data System (CAD-RADS). This requires analysis of the coronary lumen and plaque. While voxel-wise segmentation is a commonly used approach in various segmentation tasks, it does not guarantee topologically plausible shapes. To address this, in this work, we propose to directly infer surface meshes for coronary artery lumen and plaque based on a centerline prior and use it in the downstream task of CAD-RADS scoring. The method is developed and evaluated using a total of 2407 CCTA scans. Our method achieved lesion-wise volume intraclass correlation coefficients of 0.98, 0.79, and 0.85 for calcified, non-calcified, and total plaque volume respectively. Patient-level CAD-RADS categorization was evaluated on a representative hold-out test set of 300 scans, for which the achieved linearly weighted kappa ( κ ) was 0.75. CAD-RADS categorization on the set of 658 scans from another hospital and scanner led to a κ of 0.71. The results demonstrate that direct inference of coronary artery meshes for lumen and plaque is feasible, and allows for the automated prediction of routinely performed CAD-RADS categorization.

Fabrication of Superhydrophobic (TiO2/PDMS) Coating For Oil-Water Separation

Oil-contaminated water as a result of oil spill disasters or industrial disposal is a threat to human health and environmental sustainability on a global scale. The rising need for efficient oil-water separation has led to a growing interest in superhydrophobic materials for this purpose. Due to the regeneration ability of nanoparticles of titanium dioxide (TiO2), superhydrophobic and superolephilic TiO2/PDMS were created using a simple, low cost dip coating procedure. TiO2 (NPs) was synthesised by hydrothermal method and modified with PDMS (FS-1200 silicon sealant) solution. The mesh coated had remarkable superhydrophobicity, as seen by a contact angle of 155° with water. Additionally, the surface displayed superoleophilicity, as indicated by an oil contact angle (OCA) of 0°. The coated mesh surface was characterized by X-ray diffraction analysis, contact angle measurement, field emissions scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), and energy dispersive spectroscopy (EDS). The separation of kerosene-water, diesel oil-water combinations, and sunflower oil-water may be effectively achieved via a simple filtering approach using a coated mesh. This method demonstrates a notable separation efficiency of 91.6%.

Least-Squares Estimation of Tangent Space for a Triangular Mesh

This paper presents a novel method for computing an orthonormal tangent space at every vertex of a triangular mesh provided with texture coordinates, which is essential in normal mapping. Our method employs least-squares estimation of rotation between two sets of corresponding points: one set from the positions of the 1-ring neighbors of a vertex in texture space and the other set from their corresponding positions in world space. This optimal rotation represents a local space transformation that defines the tangent space at the vertex. Consequently, our method ensures that the resulting tangent space is inherently orthonormal, eliminating the need for intricate operations such as averaging and orthonormalization, which are required in the previous methods. In addition, we introduce texture space alignment of triangles to address vertices on seams, which are inevitable in texture mapping to a closed surface mesh. Experimental results demonstrate the effectiveness of the proposed methods in various experiments.

PaintHuman: Towards High-Fidelity Text-to-3D Human Texturing via Denoised Score Distillation

Recent advances in zero-shot text-to-3D human generation, which employ the human model prior (e.g., SMPL) or Score Distillation Sampling (SDS) with pre-trained text-to-image diffusion models, have been groundbreaking. However, SDS may provide inaccurate gradient directions under the weak diffusion guidance, as it tends to produce over-smoothed results and generate body textures that are inconsistent with the detailed mesh geometry. Therefore, directly leveraging existing strategies for high-fidelity text-to-3D human texturing is challenging. In this work, we propose a model called PaintHuman to addresses the challenges from two perspectives. We first propose a novel score function, Denoised Score Distillation (DSD), which directly modifies the SDS by introducing negative gradient components to iteratively correct the gradient direction and generate high-quality textures. In addition, we use the depth map as a geometric guide to ensure that the texture is semantically aligned to human mesh surfaces. To guarantee the quality of rendered results, we employ geometry-aware networks to predict surface materials and render realistic human textures. Extensive experiments, benchmarked against state-of-the-art (SoTA) methods, validate the efficacy of our approach.Project page: https://painthuman.github.io/.

Learning Explicit Contact for Implicit Reconstruction of Hand-Held Objects from Monocular Images

Reconstructing hand-held objects from monocular RGB images is an appealing yet challenging task. In this task, contacts between hands and objects provide important cues for recovering the 3D geometry of the hand-held objects. Though recent works have employed implicit functions to achieve impressive progress, they ignore formulating contacts in their frameworks, which results in producing less realistic object meshes. In this work, we explore how to model contacts in an explicit way to benefit the implicit reconstruction of hand-held objects. Our method consists of two components: explicit contact prediction and implicit shape reconstruction. In the first part, we propose a new subtask of directly estimating 3D hand-object contacts from a single image. The part-level and vertex-level graph-based transformers are cascaded and jointly learned in a coarse-to-fine manner for more accurate contact probabilities. In the second part, we introduce a novel method to diffuse estimated contact states from the hand mesh surface to nearby 3D space and leverage diffused contact probabilities to construct the implicit neural representation for the manipulated object. Benefiting from estimating the interaction patterns between the hand and the object, our method can reconstruct more realistic object meshes, especially for object parts that are in contact with hands. Extensive experiments on challenging benchmarks show that the proposed method outperforms the current state of the arts by a great margin. Our code is publicly available at https://junxinghu.github.io/projects/hoi.html.

Linear Displacement Boundary Condition Replacing Periodic Boundary Condition to Easily and Efficiently Homogenize the Elastic Properties of Composites

Periodic boundary condition is commonly used in the FE homogenization method for predicting the thermo-mechanical properties of composites. However, its existing numerical algorithms are generally inefficient. Linear displacement boundary condition is much easier and more efficient to implement for the Representative Volume Elements (RVEs) with conformal and nonconformal surface meshes. Aiming at replacing the periodic boundary condition by the linear displacement boundary condition to easily and efficiently predict the thermo-mechanical properties of composites, this paper compares the implementation efficiency and prediction accuracy of the periodic and linear displacement boundary conditions. Regarding the prediction of the elastic properties of composites, the balance of micro-energy and macro-energy of the RVEs imposed the periodic and linear displacement boundary conditions is checked, and the results demonstrate that these two boundary conditions guarantee the Hill lemma (i.e. the balance of micro-energy and macro-energy of the RVEs). Moreover, comparing with the experimental test and the multi-step micro-mechanical method, the effectiveness of the periodic and linear displacement boundary conditions to predict the elastic properties of composites is validated.

Trajectory optimization for automated tape placement on triangular mesh surfaces considering gap requirements

Abstract Automated tape placement (ATP) is an important automated process adopted for the fabrication of large composite components. Trajectory planning is the key link of ATP, which directly affects the precision and efficiency of the layup process, and the quality of final products. Presently, most existing trajectory optimization methods for ATP focus on smooth surfaces. Nevertheless, as commercial CAD/CAM software generally uses NURBS (Non-uniform Rational B-Splines) for modelling, the difficulty of finding the solution and the low efficiency associated with the calculation process are inevitable. The discrete methods provide alternatives for designing layup trajectories, whereas their accuracy is seldom analyzed. Furthermore, a path optimization algorithm for eliminating gap problems while preventing wrinkles on discrete models is rarely reported. In this paper, the adjustment of layup trajectories for ATP is considered on triangular meshes. Firstly, the triangular mesh is reconstructed as a Nagata patch to recover the original geometry with good accuracy. Then, a numerical method for tracing desired paths on the Nagata patch set is provided, and the computation efficiency is validated. Next, two optimization methodologies are proposed to improve the layup of composite tapes while avoiding wrinkles. Finally, the presented two strategies are examined on a discrete hyperbolic surface and a discrete freeform surface, and some of the results are delivered.

Preparation of super-hydrophobic BN nanotube mesh and theoretical research of wetting state

In this study, we have fabricated stainless steel mesh with columnar super-hydrophobic boron nitride nanotubes (BNNTs) through the ‘gas-liquid-solid’ mechanism annealing method. We employed iron (Fe) powder as the catalyst and utilized boron (B) and boron oxide (B2O3) as the raw materials. The synthesis took place within a tubular furnace, operating under an NH3 atmosphere at a temperature of 1250C∘. The contact angle of water droplets on the experimental surface measures approximately 150∘, while the sliding angle is approximately 3∘. In the next place, the laboratory carried out a series of experiments on the tensile properties, corrosion resistance, and erosion resistance of the prepared samples. The experimental results showed that the sample material had good mechanical properties and corrosion resistance. In addition, the erosion resistance test results showed that the sample material even at high speed (2800 rpm/min). After washing the sample for 5 min, the surface of the material still has good wettability (contact angle is 136.49∘). Finally, droplet bouncing experiments have demonstrated that the adhesion force on the surface of the boron nitride nanotube stainless steel mesh is notably minimal, indicating its substantial hydrophobic properties. Additionally, we conducted an investigation into the wetting interaction between droplets and the surface of the boron nitride nanotube stainless steel mesh. By applying the Wenzel and Cassie formulas and considering the pertinent geometric parameters of the material surface, we theoretically elucidated that, upon contact, the droplets assume a ‘Cassie’ state on the surface of the super-hydrophobic boron nitride nanotube stainless steel mesh. The research results show that the superhydrophobic boron nitride nanotube stainless steel mesh has broad application prospects in the fields of hydrogen storage, sewage treatment and oil-water separation.

CT trachea surface roughness is associated with chronic obstructive pulmonary disease symptoms

Abstract Background Trachea structural abnormalities occur in patients with chronic obstructive pulmonary disease (COPD), yet there are few methods for quantifying trachea surface topology. Purpose To develop a method to quantify trachea surface roughness on CT imaging and investigate the association with airflow limitation and symptoms in COPD. Materials and Methods Participants from the multicenter prospective Canadian Cohort Obstructive Lung Disease study between 2009 and 2015 underwent CT imaging and analysis. Established CT measurements included: tracheal index (TI), defined as the smallest ratio of coronal-to-sagittal trachea diameter, low attenuation areas below –950 HU, and wall thickness of a theoretical 10-mm airway. Trachea surface roughness shape (SRS) was calculated as the percent fraction of the measurement box filled by the surface mesh. Multivariable regression models were used to determine association for CT measurements with forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC), and Medical Research Council dyspnea scale (MRC)≥3, adjusting for covariates. Results A total of 1253 participants (mean age, 66 ± 10 years; 727 men) from 9 centers were investigated: n = 267 never smokers, n = 369 ever smokers, n = 352 mild COPD, and n = 265 moderate-to-severe COPD. There were no differences between groups for age or race (P < .05). In models including SRS and TI, a 1-standard deviation (SD) increase in SRS was independently associated with a 0.11-SD decrease in FEV1 (β = –0.11; P < .001) and a 0.16-SD decrease in FEV1/FVC (β = –0.16; P < .001); a 1-point increase in SRS was associated with a 13% increased likelihood of MRC ≥ 3 (odds ratio = 1.13; P = .003). In models including SRS, low attenuation areas below –950 HU and wall thickness of a theoretical 10-mm airway, a 1-SD increase in SRS was associated with a 0.21-SD decrease in FEV1 (β = –0.21; P < .001) and a 0.13-SD decrease in FEV1/FVC (β = –0.13; P < .001); a 1-point increase in SRS was associated with a 12% increased likelihood of MRC ≥ 3 (odds ratio = 1.12; P = .006). Conclusion Increased trachea surface shape roughness is independently associated with worse airflow and increased symptom burden in COPD.

Aging behavior and leaching characteristics of microfibers in landfill leachate: Important role of surface mesh structure

Mesh-structured films formed by the post-processing of microfibers improves their permeability and dexterity, such as disposable masks. However, the aging behavior and potential risks of mesh-structured microfibers (MS-MFs) in landfill leachate remain poorly understood. Herein, the aging behavior and mechanisms of MS-MFs and ordinary polypropylene-films (PP-films) microplastics, as well as their leaching concerning dissolved organic matter (DOM) in landfill leachate were investigated. Results revealed that MS-MFs underwent more significant physicochemical changes than PP-films during the aging process in landfill leachate, due to their rich porous habitats. An important factor in the photoaging of MS-MFs was related to reactive oxygen species produced by DOM, and this process was promoted by photoelectrons under UV irradiation. Compared with PP-films, MS-MFs released more DOM and nano-plastics fragments into landfill leachate, altering the composition and molecular weight of DOM. Aged MS-MFs-DOM generated new components, and humus-like substances produced by photochemistry showed the largest increase. Correlation analysis revealed that leached DOM was positively correlated with oxygen-containing groups accumulated in aged MS-MFs. Overall, MS-MFs will bring higher environmental risks and become a new long-term source of DOM contaminants in landfill leachate. This study provides new insights into the impact of novel microfibers on landfill leachate carbon dynamics.

Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall

Computational fluid dynamics (CFD) is a valuable asset for patient-specific cardiovascular-disease diagnosis and prognosis, but its high computational demands hamper its adoption in practice. Machine-learning methods that estimate blood flow in individual patients could accelerate or replace CFD simulation to overcome these limitations. In this work, we consider the estimation of vector-valued quantities on the wall of three-dimensional geometric artery models. We employ group-equivariant graph convolution in an end-to-end SE(3)-equivariant neural network that operates directly on triangular surface meshes and makes efficient use of training data. We run experiments on a large dataset of synthetic coronary arteries and find that our method estimates directional wall shear stress (WSS) with an approximation error of 7.6% and normalised mean absolute error (NMAE) of 0.4% while up to two orders of magnitude faster than CFD. Furthermore, we show that our method is powerful enough to accurately predict transient, vector-valued WSS over the cardiac cycle while conditioned on a range of different inflow boundary conditions. These results demonstrate the potential of our proposed method as a plugin replacement for CFD in the personalised prediction of hemodynamic vector and scalar fields.

Multi-view 3D reconstruction based on deep learning: A survey and comparison of methods

An important objective in computer vision is to analyze multiple images and subsequently reconstruct the shape and structure in 3D. Traditional multi-view 3D reconstruction techniques extract and match key features from images with known camera parameters. However, this approach is inefficient and fails to fully exploit the advantages of multi-view information. Advancements in deep learning have revolutionized multi-view 3D reconstruction by enabling end-to-end 3D shape inferencing without the need for sequential feature matching typically found in conventional algorithms. Recent rapid progress in this field necessitates a thorough review of current algorithms and provide insight into method of improving 3D reconstruction performance. This review classifies reconstruction algorithms according to their resultant model, including depth map, voxel, point cloud, mesh, and implicit surface. Additionally, this review encompasses the inclusion of frequently employed network training loss functions for network training, assessment metrics, and the incorporation of 3D datasets. Experimental results are also presented to assess the performance of different algorithms. Finally, the paper concludes with a summary, discussion of challenges, and potential future directions.

Injectable Double Crosslinked Hydrogel-Polypropylene Composite Mesh for Repairing Full-Thickness Abdominal Wall Defects.

Abdominal wall defects are common clinical diseases, and mesh repair is the standard treatment method. The most commonly used polypropylene (PP) mesh in clinical practice has the advantages of good mechanical properties, stable performance, and effective tissue integration effect. However, direct contact between abdominal viscera and PP mesh can lead to severe abdominal adhesions. To prevent this, the development of a hydrogel-PP composite mesh with anti-adhesive properties may be an effective measure. Herein, biofunctional hydrogel loaded with rosmarinic acid is developed by modifying chitosan and Pluronic F127, which possesses suitable physical and chemical properties and commendable in vitro biocompatibility. In the repair of full-thickness abdominal wall defects in rats, hydrogels are injected onto the surface of PP mesh and applied to intraperitoneal repair. The results indicate that the use of hydrogel-PP composite mesh can alleviate abdominal adhesions resulting from traditional PP mesh implantation by decreasing local inflammatory response, reducing oxidative stress, and regulating the fibrinolytic system. Combined with the tissue integration ability of PP mesh, hydrogel-PP composite mesh has great potential for repairing full-thickness abdominal wall defects.

Validation of a 3D Local-Scale Adaptive Solar Radiation Model by Using Pyranometer Measurements and a High-Resolution Digital Elevation Model.

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows us to estimate direct, diffuse, and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterization techniques and allows the generation of high-quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data, and its resolution is two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient.

Fast reconstruction of water-tight surface mesh of neurons

Fast reconstruction of water-tight surface mesh of neurons

Design and analysis of scissor-like hoop truss deployable antenna mechanism with arbitrary curvature support ribs

To align with the development trend of large aperture, high stiffness, and high expansion ratio for space antennas, we propose a scissor-like hoop truss deployable antenna mechanism with arbitrary curvature mesh support. Compared to classical AstroMesh-hoop structures, this configuration features parabolic support ribs under the mesh surface, eliminating the need for additional high columns. It has a lower stowed height and higher in-plane stiffness, which helps maintain high surface accuracy. Firstly, the Four-Parameter Method is proposed for the dimensional design of scissor-like chains with arbitrary curvature from the perspective of the deployable antenna support structure. This method allows for controlling the deployment configuration of the scissor-like support structure by adjusting the semi-major axis length and the focal length of the initial ellipse, the angles of the unit lines, and the x-coordinates of the fitting points. Then, a three-dimensional scissor-like hoop design with joint scale that satisfies the deployable conditions is performed. Subsequently, two major issues called over-deployment and bistability are discussed, which need to be considered when applying scissor-like elements (SLEs) to space-deployable antennas. The mechanisms behind these issues are analyzed from a kinematic perspective, and optimization methods are proposed. The effectiveness of the optimization methods is verified through dynamic software simulations and a prototype. The high in-plane stiffness of the configuration is verified by finite element analysis.