Mesh Deformation Research Articles

Quad‐fisheye Image Stitching for Monoscopic Panorama Reconstruction

AbstractMonoscopic panorama provides the display of omnidirectional contents surrounding the viewer. An increasingly popular way to reconstruct a panorama is to stitch a collection of fisheye images. However, such non‐planar views may result in problems such as distortions and boundary irregularities. In most cases, the computational expense for stitching non‐planar images is also too high to satisfy real‐time applications. In this paper, a novel monoscopic panorama reconstruction pipeline that produces better quad‐fisheye image stitching results for omnidirectional environment viewing is proposed. The main idea is to apply mesh deformation for image alignment. To optimize inter‐lens parallaxes, unwarped images are firstly cropped and reshuffled to facilitate the circular environment scene composition by the seamless ring‐connection of the panorama borders. Several mesh constraints are then adopted to ensure a high alignment accuracy. After alignment, the boundary of the result is rectified to be rectangular to prevent gapping artefacts. We further extend our approach to video stitching. The temporal smoothness model is added to prevent unexpected artefacts in the panoramic videos. To support interactive applications, our stitching algorithm is programmed using CUDA. The camera motion and average gradient per video frame are further calculated to accelerate for synchronous real‐life panoramic scene reconstruction and visualization. Experimental results demonstrate that our method has advantages in respects of alignment accuracy, adaptability and image quality of the stitching result.

Numerical Investigations on Static and Rotordynamic Characteristics for Two Types of Liquid Hole-Pattern Seals With Tilted Cavities

Abstract Two types of liquid hole-pattern seals with axially oblique (A-HPS) or circumferentially oblique (C-HPS) hole cavities are designed. To evaluate the leakage and rotordynamic characteristics of the liquid hole-pattern seals, a 3D transient perturbation method is employed, which based on the multifrequency one-dimensional rotor whirling model and the mesh deformation technique. The accuracy and reliability of the proposed numerical approach is demonstrated based on the published experimental data of the leakage and rotordynamic force coefficients for a hole-pattern seal (HPS). Seal leakage and force coefficients are presented and compared for the A-HPS (axially oblique angle α=−30degto30deg), C-HPS (circumferentially oblique angle β=−30degto30deg), and HPS (α = 0, β = 0) at various rotational speeds (n = 0.05, 2.0, 4.0, and 6.0 krpm). Results reveal that the tilted hole cavity with positive α or β can reduce the seal effective clearance and strengthen the kinetic dissipation in hole cavities, yielding less leakage by 5–10%, especially at higher rotational speeds. The tilted hole cavity with a positive oblique angle (α=30deg,β=30deg) results in a moderate growth (by ∼6% for the A-HPS, by ∼15% for C-HPS) in the effective stiffness. Furthermore, the tilted hole cavity shows a very weak influence (<4.0%) on the effective damping, particularly for higher rotational speeds and vibration frequencies. Considering the decreasing leakage and nonworse rotordynamic characteristics, a tilted hole cavity with suitable positive oblique angles (10deg–30deg) is beneficial for the liquid hole-pattern seal.

N‐Cloth: Predicting 3D Cloth Deformation with Mesh‐Based Networks

AbstractWe present a novel mesh‐based learning approach (N‐Cloth) for plausible 3D cloth deformation prediction. Our approach is general and can handle cloth or obstacles represented by triangle meshes with arbitrary topologies. We use graph convolution to transform the cloth and object meshes into a latent space to reduce the non‐linearity in the mesh space. Our network can predict the target 3D cloth mesh deformation based on the initial state of the cloth mesh template and the target obstacle mesh. Our approach can handle complex cloth meshes with up to 100K triangles and scenes with various objects corresponding to SMPL humans, non‐SMPL humans or rigid bodies. In practice, our approach can be used to generate plausible cloth simulation at 30 – 45 fps on an NVIDIA GeForce RTX 3090 GPU. We highlight its benefits over prior learning‐based methods and physically‐based cloth simulators.

Application of active magnetic bearings in control and estimation of geared-rotor faults in high speed offset spur gear transmission system

This study is focused on the mathematical modelling, analysis, active transverse vibration control and fault analysis of a single-stage spur geared-rotor system. It uses Active Magnetic Bearings (AMBs) as an auxiliary bearing in addition to the conventional mechanical bearing in rotor fault detection considering the dynamic model with gyroscopic effects. The change in dynamic forces primarily due to the mesh deformation, gear runout, and variable transmission error are considered, which causes unwanted vibration and noise. To prevent the damage of gears and other supporting structures, these forced vibrations and control currents are meticulously investigated. From the dynamic responses of geared-rotor, the AMB control the stiffness and damping to minimize the transmission of forced vibrations to the mountings by closed-loop feedback control system. For an accurate modelling the dynamic transmission error is taken in two orthogonal transverse directions, which has asymmetric transmission error characteristics. Full spectrum is used for frequency domain analysis with tilting phenomena of the gears at high spin speed. An identification algorithm is developed for fault detection and estimation of system parameters from vibration and current of the proposed geared-rotor-AMB system. The robustness of the proposed algorithm is verified with different added percentage of noise and modeling errors.

Design of a multi-sensor information acquisition system for mannequin reconstruction and human body size measurement under clothes

Although the measurement of human sizes and the reconstruction of mannequins have been extensively studied, there has been little research on systems applicable for measurement and reconstruction under clothes. This work presents a method for three-dimensional (3D) mannequin reconstruction and human body size measurement based on information fusion of multiple sensors. For this purpose, a multi-sensor information acquisition system (MIAS) is developed allowing one to acquire 11 key size data of the human body under clothes. The MIAS is based on the proposed parametric mannequin method and the Laplace mesh deformation technique, thus allowing one to reconstruct the mannequin conforming to the MIAS measurements. All mannequins reconstructed by this method have the same topology, which will greatly facilitate subsequent processing, such as garment design, customization and virtual fitting. The results of the reconstruction experiments show that our system can reconstruct a mannequin that matches the size of the feature parts very well. In addition, performed comparison experiments with manual and laser measurements shows that the measurement results of our system are close to those of manual and laser measurements. This provides a viable method for measuring key body sizes under clothes and reconstructing the corresponding 3D mannequin.

Bodies Uncovered: Learning to Manipulate Real Blankets Around People via Physics Simulations

While robots present an opportunity to provide physical assistance to older adults and people with mobility impairments in bed, people frequently rest in bed with blankets that cover the majority of their body. To provide assistance for many daily self-care tasks, such as bathing, dressing, or ambulating, a caregiver must first uncover blankets from part of a person’s body. In this work, we introduce a formulation for robotic bedding manipulation around people in which a robot uncovers a blanket from a target body part while ensuring the rest of the human body remains covered. We compare two approaches for optimizing policies which provide a robot with grasp and release points that uncover a target part of the body: 1) reinforcement learning and 2) self-supervised learning with optimization to generate training data. We trained and conducted evaluations of these policies in physics simulation environments that consist of a deformable cloth mesh covering a simulated human lying supine on a bed. In addition, we transfer simulation-trained policies to a real mobile manipulator and demonstrate that it can uncover a blanket from target body parts of a manikin lying in bed. Source code is available online <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula> .

Deep learning for biomechanical modeling of facial tissue deformation in orthognathic surgical planning.

Orthognathic surgery requires an accurate surgical plan of how bony segments are moved and how the face passively responds to the bony movement. Currently, finite element method (FEM) is the standard for predicting facial deformation. Deep learning models have recently been used to approximate FEM because of their faster simulation speed. However, current solutions are not compatible with detailed facial meshes and often do not explicitly provide the network with known boundary type information. Therefore, the purpose of this proof-of-concept study is to develop a biomechanics-informed deep neural network that accepts point cloud data and explicit boundary types as inputs to the network for fast prediction of soft-tissue deformation. A deep learning network was developed based on the PointNet++ architecture. The network accepts the starting facial mesh, input displacement, and explicit boundary type information and predicts the final facial mesh deformation. We trained and tested our deep learning model on datasets created from FEM simulations of facial meshes. Our model achieved a mean error between 0.159 and 0.642mm on five subjects. Including explicit boundary types had mixed results, improving performance in simulations with large deformations but decreasing performance in simulations with small deformations. These results suggest that including explicit boundary types may not be necessary to improve network performance. Our deep learning method can approximate FEM for facial change prediction in orthognathic surgical planning by accepting geometrically detailed meshes and explicit boundary types while significantly reducing simulation time.

Galerkin-based finite strain analysis with enriched radial basis interpolation

We present an enriched radial basis function (RBF) interpolation, which is combined with a symmetric Galerkin method to solve finite strain problems. Specifically, Wendland compact support radial basis functions (RBF) are enriched with a quadratic polynomial, whose parameters are condensed-out during the shape-function construction phase. A total Lagrangian technique is adopted and for finite strain plasticity the formalism with the Mandel stress is adopted. These recent developments are especially convenient from the implementation perspective, as RBF formulations for finite strain plasticity have been limited by interpolation updating. We also note that, although tetrahedra are adopted for quadrature in the undeformed configuration, mesh deformation is of no consequence for the results. Four benchmark tests are successfully solved, with extensive convergence studies and showing clear advantages with respect to finite-element in terms of robustness and with respect to classical Element-Free Galerkin (EFG) formulations in terms of efficiency.

Shape optimization method for axisymmetric disks based on mesh deformation and smoothing approaches

Axisymmetric disk structures with complex contour curves are widely used in aero-engines. The shape optimization is generally carried out to reduce the stress level of axisymmetric disks. In this article, a shape optimization method for axisymmetric disks based on radial basis function (RBF) mesh deformation and Laplace smoothing approaches is proposed. This method can obtain the optimized reduced control points selection of mesh deformation under the influence of design space based on greedy algorithm. RBF mesh deformation is used to change the axisymmetric contour shape. And after deformation, the local mesh quality is monitored and improved by Laplace smoothing. In this article, two illustrative examples used in aero-engines are carried out to validate the effectiveness of the proposed method, including an independent optimization of a turbine disk and a collaborative optimization of a turbine disk with a deflector for minimizing the maximum equivalent stress. To improve the computational efficiency, a two-dimensional (2D) axisymmetric FE model is established. Compared with initial results, optimized results in two examples obtained by the proposed optimization method reduce the maximum von Mises stress by 8.02% and 9.25%, respectively. It can be concluded that the proposed method has significant potential in the shape optimization design of axisymmetric disks.

High-performance 3D Unstructured Mesh Deformation Using Rank Structured Matrix Computations

The Radial Basis Function (RBF) technique is an interpolation method that produces high-quality unstructured adaptive meshes. However, the RBF-based boundary problem necessitates solving a large dense linear system with cubic arithmetic complexity that is computationally expensive and prohibitive in terms of memory footprint. In this article, we accelerate the computations of 3D unstructured mesh deformation based on RBF interpolations by exploiting the rank structured property of the matrix operator. The main idea consists in approximating the matrix off-diagonal tiles up to an application-dependent accuracy threshold. We highlight the robustness of our multiscale solver by assessing its numerical accuracy using realistic 3D geometries. In particular, we model the 3D mesh deformation on a population of the novel coronaviruses. We report and compare performance results on various parallel systems against existing state-of-the-art matrix solvers.

Moving least-squares in finite strain analysis with tetrahedra support

A finite strain finite element (FE)-based approach to element-free Galerkin (EFG) discretization is introduced, based on a number of simplifications and specialized techniques in the context of a Lagrangian kernel. In terms of discretization, a quadratic polynomial basis is used, support is determined from the number of pre-assigned nodes for each quadrature point and quadrature points coincide with the centroids of tetrahedra. Diffuse derivatives are adopted, which allow for the use of convenient non-differentiable weight functions which approximate the Dirac-Delta distribution. Due to the use of a Lagrangian kernel, recent finite strain elasto-plastic constitutive developments based on the Mandel stress are adopted in a direct form. These recent developments are especially convenient from the implementation perspective, as EFG formulations for finite strain plasticity have been limited by the previous requirement of updating the kernel. We also note that, although tetrahedra are only adopted for integration in the undeformed configuration, mesh deformation is of no consequence for the results. Four 3D benchmark tests are successfully solved.

Trailing Edge Flap Effects on Dynamic Stall Vortex and Unsteady Aerodynamic Forces on a Pitching Airfoil

This study focuses on the effect of the upward deflection of trailing edge flap (TEF) on the strength and trajectory of dynamic stall vortex (DSV) around a pitching airfoil by means of numerical simulations based on unsteady Reynolds-averaged Navier-Stokes (URANS). The effect of the upward deflection of the TEF on the unsteady aerodynamic forces due to DSV is analyzed. The numerical simulation method for large mesh deformation is constructed. Radial basis function- (RBF-) based mesh deformation algorithm, as well as Laplacian and optimization-based mesh smoothing algorithm, is adopted to ensure the mesh quality in flow field simulations. The results reveal that the upward deflection of the TEF can reduce the peaks of drag and pitching moment coefficients. Although the maximum lift coefficient of the airfoil is slightly reduced, its maximum drag and pitching moment coefficients are significantly reduced by up to 34.8% and 31.8%, respectively. The vorticity transport behavior in a planar control region during the DSV formation and detachment is analyzed. It is found that the TEF can change the development process of the DSV. The upward deflection of the TEF reduces the vorticity flux from the leading edge shear layer, which causes the circulation of the DSV and the translational velocity of the vortex center to decline. The peaks of the unsteady aerodynamic forces on the airfoil induced by the DSV are reduced. The upward deflection of the TEF plays the role of alleviating the pitching moment load. The longer TEF can result in a better control effect. The bigger the upward deflection angle of the TEF, the better its control effect.

Aerodynamic design optimization: Challenges and perspectives

Antony Jameson pioneered CFD-based aerodynamic design optimization in the late 1980s. In addition to developing the fundamental theory, Jameson implemented that theory in codes that were practical enough to be used in industry. As a result of Jameson’s seminal efforts, a research community has been established in aerodynamic design optimization. This research area has experienced sustained improvements in CFD solvers, mesh deformation, sensitivity computation, and optimization tools. We review recent developments for each of these components and present open-source tools available for aerodynamic shape optimization. A variety of applications is presented, including the optimization of a supercritical airfoil starting from a circle, a web application that optimizes airfoils within a few seconds, aircraft aerodynamic and aerostructural optimization, and aeropropulsive optimization. We also review the Aerodynamic Design Optimization Discussion Group (ADODG) benchmarks and other aerodynamic shape optimization problems. Among the ADODG benchmarks, we focus on the RANS-based problems and discuss some of the issues encountered, including comparing Euler and RANS results and design-space multimodality. The availability of these benchmarks and the open-source tools is expected to enable further studies and benchmarks in CFD-based aerodynamic design optimization and MDO.

Multi-objective aerodynamic optimization of two-dimensional hypersonic forebody-inlet based on the heuristic algorithm

Nowadays, the forebody-inlet integrated design optimization becomes more and more important in improving the performance of hypersonic vehicles. And several achievements have been made to improve the performance of the two-dimensional hypersonic forebody-inlet integrated vehicle. However, all these works are faced with many defects. For example, the work adopting the gradient algorithm is easy to be trapped in the local optimum solution. The data-driven optimization method is with a low level of accuracy. Moreover, the geometry parameterization methods adopted in those optimization procedures are hardly implemented to complex configurations. In this study, a global-searching multi-objective optimization framework is proposed to overcome these limitations and to carry out multi-objective optimization of the two-dimensional hypersonic forebody-inlet shape. The framework includes the Free-Form Deformation (FFD) method, the mesh deformation method, the high-accuracy Reynolds Averaged Navier-Stokes (RANS) solver, and the global-searching heuristic algorithm. Results obtained by this framework indicate that the total pressure recovery coefficient, the pressure rising ratio, and the mass flow coefficient are increased by 3.97%, 9% and 7.35%, respectively, which suggests that the optimization framework proposed in this study is promising to be widely used in practical engineering applications.

A General Inheritance Algorithm for Calculating of Arbitrary Moving Samples During Microwave Heating

Moving models, such as translation, rotation, and other motion modes, are widely applied to improve the microwave heating uniformity. However, due to a variety of motion modes, the deformation of mesh, including discontinuity, crossing, and winding, usually occurs in the process of microwave heating calculation. It is a great challenge to numerical simulation of moving samples because of the lack of a common calculation method. In this article, a novel inheritance algorithm, which inherits both the grid and temperature distribution of the sample, can be used to calculate arbitrary moving models of microwave heating process. It is adopted to inherit the grid and temperature distribution in the finite element method to ensure that each temperature calculation result can perfectly correspond to the temperature value of these mesh nodes. By building a 3-D mathematical model of translation, swing, and rotation, the coupling process of electromagnetic field and thermal phenomena in microwave heating was performed and the proposed method was clearly illustrated. Finally, the calculated results are consistent with the experimental results, confirming the accuracy of the algorithm. Compared with the conventional algorithm, the proposed algorithm has a higher precision and practically and can be used to simulate microwave heating of arbitrary motions.

Hybrid Mesh Deformation for Aerodynamic-Structural Coupled Adjoint Optimization

This paper demonstrates that a discrete coupled-adjoint aeroelastic shape optimization can be made more efficient with the use of different mesh-deformation algorithms for the fluid-structure interaction (FSI) simulations and the coupled-adjoint calculations within the optimization loop. Mesh deformation using radial basis functions (RBF) with only a subset of surface points is popular due to the efficiency and mesh quality produced by the technique. However, this technique can reduce the rate of convergence of the coupled-adjoint and even prevent the coupled-adjoint equations from converging. This paper proposes a hybrid mesh-deformation strategy to improve the efficiency of coupled-adjoint optimizations: use the RBF method with a data-reduction algorithm when deforming the mesh within FSI simulations but use the Delaunay graph mapping (DGM) method in the coupled-adjoint procedure. The DGM method increases the rate of convergence of the coupled-adjoint matrix, relative to the RBF approach with a data-reduction algorithm, with the additional benefit of being a faster method. Using this hybrid approach, an optimization in which lift and pitching-moment constraints are satisfied within the FSI simulation is performed. The results of the optimization, and the effects of the hybrid approach, are presented.

Shape variation in the carapace of Chinese mitten crabs (Eriocheir sinensis H. Milne Edwards, 1853) in Yangcheng Lake during the year-long culture period

To evaluate whether ontogenetic development over the grow-out culture period can cause geographical plasticity of carapace shape in a certain region, geometric morphometric analysis was used, in this study, to determine the ontogenetic changes in the carapace morphology of Chinese mitten crabs (Eriocheir sinensis) originating from Yangcheng Lake, China, during a year of growth from coin-sized juveniles to market-sized adults. The morphological differences in the carapace throughout the year of culture were characterized using a 35-landmark point system. We used principal component analysis and linear discriminant analysis to determine morphological variation using thin-plate spline analysis and mesh deformation. During the growth process, the changes in the carapace were mainly concentrated in the third and fourth anterolateral teeth and on the M-shaped pattern. During the growth of male and female crabs throughout the year, the shape of the carapace changed considerably over the first six months. Afterwards, the shape of the carapace began to stabilize and could not be differentiated through discriminant analysis. This study is the first to use geometric morphometrics to analyze the ontogenetic changes in the carapace shape of E. sinensis crabs native to Yangcheng Lake. The results demonstrate that it takes a long time for the carapace morphology of native crabs to stabilize.

Coupled particle and mesh method in an Euler frame for unsteady flows around the pitching airfoil

Finite difference method (FDM) is a grid-based method which is convenient for implementing multiple resolutions and has high computational efficiency. Smoothed particle hydrodynamics (SPH) is a meshless and particle method which has been widely applied into the fluid flows with free surfaces. In this study, a coupled SPH-FDM approach in an Euler frame is developed to simulate the unsteady flow around a pitching airfoil. In addition, an improved iterative shifting particle technology (IPST) is proposed to satisfy the movement of pitching airfoils. Steady flows around the static airfoils are simulated by SPH-FDM, and the results are compared with results of finite volume mothed (FVM) and literatures. The flows around the pitching airfoil with different conditions are simulated, and the results by coupled SPH-FDM are compared with the results by FVM which uses mesh deformation technology to control the movement of mesh. The numerical results by SPH-FDM in an Euler frame are agreement with the results of FVM or literatures, which verifies the effectiveness of the present method. The results of pithing airfoils show the direction of lift hysteresis loop changes from clockwise to counterclockwise as the pitching axis moves from the leading edge to the trailing edge, which can be well predicted by present SPH-FDM in the Euler frame. In addition, some parameters which may affect the lift hysteresis loop are discussed in this study. The results indicate that the acceleration of the airfoil surface has little effect on the lift hysteresis loop; the shape of airfoil has a weak effect on the lift hysteresis loop; the velocity of the airfoil surface, the position of the pitching axis and the free-stream velocity have predominant effect on the lift hysteresis loop.

Three-Dimensional Wheat Modelling Based on Leaf Morphological Features and Mesh Deformation

The three-dimensional (3D) morphological structure of wheat directly reflects the interrelationship among genetics, environments, and cropping systems. However, the morphological complexity of wheat limits its rapid and accurate 3D modelling. We have developed a 3D wheat modelling method that is based on the progression from skeletons to mesh models. Firstly, we identified five morphological parameters that describe the 3D leaf features of wheat from amounts of 3D leaf digitizing data at the grain filling stage. The template samples were selected based on the similarity between the input leaf skeleton and leaf templates in the constructed wheat leaf database. The leaf modelling was then performed using the as-rigid-as-possible (ARAP) mesh deformation method. We found that 3D wheat modelling at the individual leaf level, leaf group, and individual plant scales can be achieved. Compared with directly acquiring 3D digitizing data for 3D modelling, it saves 79.9% of the time. The minimum correlation R2 of the extracted morphological leaf parameters between using the measured data and 3D model by this method was 0.91 and the maximum RMSE was 0.03, implying that this method preserves the morphological leaf features. The proposed method provides a strong foundation for further morphological phenotype extraction, functional–structural analysis, and virtual reality applications in wheat plants. Overall, we provide a new 3D modelling method for complex plants.

Effect of the Computational Model and Mesh Strategy on the Springback Prediction of the Sandwich Material

The effect of the computational model and mesh strategy on the springback prediction of the thin sandwich material made of micro-alloyed steel was investigated in this paper. To verify the chosen computational strategy, a comparison of the experimentally obtained specimen (U-bending) with the FEA result was performed. The Vegter yield criterion combined both with the isotropic and kinematic hardening law was used for the calculation. In addition, the effect of the deformation mesh element (surface and volume) on the accuracy of the springback prediction was investigated. It was concluded that the choice of the volume deformation mesh does not significantly improve the accuracy of the results. Moreover, it is quite a time-consuming approach. The much greater influence was monitored by concerning the selection of hardening law, where the anisotropic one was more suitable to be used on the springback prediction of a given sandwich material.