Matching Algorithm for 3D Point Cloud Recognition and Registration Based on Multi-Statistics Histogram Descriptors

Establishing an effective local feature descriptor and using an accurate key point matching algorithm are two crucial tasks in recognizing and registering on the 3D point cloud. Because the descriptors need to keep enough descriptive ability against the effect of noise, occlusion, and incomplete regions in the point cloud, a suitable key point matching algorithm can get more precise matched pairs. To obtain an effective descriptor, this paper proposes a Multi-Statistics Histogram Descriptor (MSHD) that combines spatial distribution and geometric attributes features. Furthermore, based on deep learning, we developed a new key point matching algorithm that could identify more corresponding point pairs than the existing methods. Our method is evaluated based on Stanford 3D dataset and four real component point cloud dataset from the train bottom. The experimental results demonstrate the superiority of MSHD because its descriptive ability and robustness to noise and mesh resolution are greater than those of carefully selected baselines (e.g., FPFH, SHOT, RoPS, and SpinImage descriptors). Importantly, it has been confirmed that the error of rotation and translation matrix is much smaller based on our key point matching algorithm, and the precise corresponding point pairs can be captured, resulting in enhanced recognition and registration for three-dimensional surface matching.

Double shear layer evolution on the non-uniform computational mesh

This paper considers the canonical problem of a thin shear layer evolution at Reynolds number Re = 400000 using the novel Compact Accurately Boundary Adjusting high-Resolution Technique (CABARET). The study is focused on the effect of the specific mesh refinement in the high shear rate areas on the flow properties under the influence of the developing instability. The original sequence of computational meshes (256^2, 512^2, 1024^2, 2048^2 cells) is modified using an iterative refinement algorithm based on the hyperbolic tangent. The properties of the solutions obtained are discussed in terms of the initial momentum thickness and the initial vorticity thickness, viscous and dilatational dissipation rates and also integral enstrophy. The growth rate for the most unstable mode depending on the mesh resolution is considered. In conclusion the accuracy of calculated mesh functions is estimated via L1, L2, L∞ norms.

CFD-based curved tip shape design for wind turbine blades

This work presents a high-fidelity shape optimization framework based on computational fluid dynamics (CFD). The presented work is the first comprehensive curved tip shape study of a wind turbine rotor to date using a direct CFD-based approach. Preceeding the study is a thorough literature survey particularly focused on wind turbine blade tips in order to place the present work in its context. Then follows a comprehensive analysis to quantify mesh dependency and to present needed mesh modifications ensuring a deep convergence of the flow field at each design iteration. The presented modifications allow the framework to produce up to 6 digit accurate finite difference gradients which are verified using the machine accurate Complex-Step method. The accurate gradients result in a tightly converged design optimization problem where the studied problem is to maximize power using 12 design variables while satisfying constraints on geometry as well as on the bending moment at 90 % blade length. The optimized shape has about 1 % r/R blade extension, 2 % r/R flapwise displacement, and slightly below 2 % r/R edgewise displacement resulting in a 1.12 % increase in power. Importantly, the inboard part of the tip is de-loaded using twist and chord design variables as the blade is extended ensuring that the baseline steady-state loads are not exceeded. For both analysis and optimization an industrial scale mesh resolution of above 14 · 106 cells is used which underlines the maturity of the framework.

A 2D Numerical Simulation of Binary Alloy Solidification: Effect of Mesh Resolution on Formation of Channel Segregates

Mesh refinement is crucial for capturing the complex phenomena that governs the formation of channel segregates during binary alloy solidification. In this article, the influence of mesh size on the formation of channel segregates during the solidification of Sn-5wt%Pb alloy is numerically investigated. A solver is developed in OpenFOAM for solving the coupled transport equations of mass, momentum, energy and species. Subsequently, the simulations are performed for different mesh sizes to predict the flow field, temperature, species and solid fraction distribution including the morphology of channel segregates. From this study, it is observed that the mesh size significantly affects the morphology and the strength of channel segregates. For very fine mesh size, having sufficient number of grid point along their width, the formed channels are more continuous and the flow inside channels is resolved.

Biphasic parameter identification of 3D scaffold-free cartilage transplants (SFCT) from stress relaxation compression tests using an optimized 3D FE-based method with tension-compression nonlinearity

Cartilage constructs produced by SFCTtechnology provide promising opportunities to restore cartilage defects. Mechanical parameters of soft tissues are explicit markers for quantitative tissue characterization. In this study, we present a biphasic 3D-FE-based method to determine the biomechanical properties of SFCT from stress relaxation compression tests (ε = 20 %, t = 3400 s) whereby cartilaginous tissue is modeled as a biphasic material with tension-compression nonlinearity (BMTCN). The FE-model computation was optimized by exploiting the axial symmetry and mesh resolution. The R² of the fit results varies between 0.970 and 0.983. The Young’s and fiber modulus determined from SFCT are 37-times and 5-times lower than from native articular cartilage, respectively. Permeability, on the other hand, is 11-times higher than from native articular cartilage.

Dam Break Simulation with HEC-RAS and OpenFOAM

A dam break is a natural disaster that can cause significant property damage and loss of life. It's useful to identify potential flooding areas downstream in the event of a dam break. In this study both HEC-RAS and OpenFOAM are set up to simulate the inundation map downstream of the Dworshak dam in Idaho. Using the same topographical data from satellite observations, similar computational meshes are set up in both HEC-RAS and OpenFOAM. Where possible, identical or similar conditions are set up in HEC-RAS and OpenFOAM to model flooding patterns due to a dam break. The velocity of the water before reaching Ahsahka, the town located at the junction downstream from the dam, is 11.5% slower in HEC-RAS compared to OpenFOAM. The average velocity of water before reaching the end of the computational domain at Big Canyon Creek is about 20% slower in HEC-RAS compared to OpenFOAM. One notable discovery is that the water flow velocity in OpenFOAM appears to depend on the mesh resolution used in the simulation. A significant velocity difference is observed when water flows from one mesh refinement region to another mesh refinement region with a different resolution.

Immersed boundary-conformal isogeometric method for linear elliptic problems

We present a novel isogeometric method, namely the Immersed Boundary-Conformal Method (IBCM), that features a layer of discretization conformal to the boundary while employing a simple background mesh for the remaining domain. In this manner, we leverage the geometric flexibility of the immersed boundary method with the advantages of a conformal discretization, such as intuitive control of mesh resolution around the boundary, higher accuracy per degree of freedom, automatic satisfaction of interface kinematic conditions, and the ability to strongly impose Dirichlet boundary conditions. In the proposed method, starting with a boundary representation of a geometric model, we extrude it to obtain a corresponding conformal layer. Next, a given background B-spline mesh is cut with the conformal layer, leading to two disconnected regions: an exterior region and an interior region. Depending on the problem of interest, one of the two regions is selected to be coupled with the conformal layer through Nitsche’s method. Such a construction involves Boolean operations such as difference and union, which therefore require proper stabilization to deal with arbitrarily cut elements. In this regard, we follow our precedent work called the minimal stabilization method (Antolin et al in SIAM J Sci Comput 43(1):A330–A354, 2021). In the end, we solve several 2D benchmark problems to demonstrate improved accuracy and expected convergence with IBCM. Two applications that involve complex geometries are also studied to show the potential of IBCM, including a spanner model and a fiber-reinforced composite model. Moreover, we demonstrate the effectiveness of IBCM in an application that exhibits boundary-layer phenomena.

A wall-adapted zonal URANS/LES methodology for the scale-resolving simulation of engine flows

In the present paper, a comprehensive, wall-adapted zonal URANS/LES methodology is shown for the multidimensional simulation of modern direct-injection engines. This work is the latest update of a zonal hybrid turbulence modeling approach, specifically developed by the authors for a flexible description of in-cylinder turbulent flow features with an optimal balance between computational costs and accuracy. Compared to the previous developments, a specific near-wall treatment is added, in order to preserve full-URANS behavior in the first near-wall cells, having in mind typically available mesh resolution in this part of the fluid domain. The updated methodology is applied to the multi-cycle simulation of a reference single-cylinder optical engine, which features a twin-cam, overhead-valve pent-roof cylinder head, and is representative of the current generation of spark-ignited direct-injection thermal power units. Results based on phase-specific flow field statistics and synthetic quality indices demonstrate the consistency and effectiveness of the proposed methodology, which is then qualified as a suitable candidate for affordable scale-resolving analyses of cycle to cycle variability (CCV) phenomena in direct-injection engines.