Density Distribution Of Points Research Articles

Control parameter layout of compressor airfoils and adaptive optimization method for boundary extension

Parameterized optimization methods are effective approaches for achieving high aerodynamic performance in compressors. Traditional parameterized optimization methods rely on a designer's preselected control parameter layout (including control frame orientation, point density distribution, control point displacement direction, number of variables, and variable ranges), which are purely based on empirical knowledge without sufficient theoretical basis. This paper selects the free-form deformation (FFD) method and Bayesian algorithm as the parameterization method and optimization algorithm for compressor airfoil optimization and studies the influence of FFD control parameter layouts on aerodynamic optimization performance. Additionally, an adaptive optimization method for control parameters based on FFD is proposed, where the orientation and density of the control framework can be incorporated as variables into the control parameters. During the optimization process, the range of design variables is adaptively expanded. A comparison between FFD optimization results based on B-spline and Bernstein basis functions shows that the former achieves an average performance improvement of 4% relative to the latter. Furthermore, an optimization method with an infinitely expandable boundary based on Bernstein basis FFD is proposed, which improves the performance by 12% compared to general adaptive boundary expansion methods.

C-LFNet: Central-Local Feature 3D point cloud instance segmentation Network for robot bin-picking

We propose a novel instance segmentation algorithm called Central-Local Feature Network (C-LFNet) to address the low performance of point cloud segmentation in bin-picking. First, to address the issue of batch processing data, we propose a downsampling algorithm that can sample the number of target points while preserving the density distribution of points in space as much as possible both before and after sampling. Second, we design a dynamic graph convolution backbone to better extract the local geometric invariant features, referred to as Central-Local Feature Module (C-LFM). Finally, the results of each point estimate are clustered in order to enable instance segmentation of the point cloud. The proposed network is evaluated using the Fraunhofer IPA Bin-Picking dataset and compared to existing methods. Results demonstrate that the proposed network is effective and robust in bin-picking scenes to achieve the same category of point cloud instance segmentation, resulting in improved performance.

3D point cloud fusion from UAV and TLS to assess temperate managed forest structures

Light detection and ranging (LiDAR) technology has become one of the most dominant acquisition methods for modeling forest attributes, such as very accurate tree structure information, which is necessary for qualitative forest management and research activities. In this study, we evaluated the efficacy of standalone unmanned aerial vehicle-laser scanning (UAV-LS) and terrestrial laser scanning (TLS) data to accurately estimate forest tree metrics under differing management types. Furthermore, we combined the UAV-LS and TLS data to test whether fusion can improve the mapping of the three-dimensional (3D) structure of individual trees to favor accurate estimates of tree metrics. We initially calculated the percentage of point density per square meter aboveground in each height class at intervals of 1 m for the UAV-LS, TLS, and fusion datasets. This helped illustrate the vertical point density distribution that reflects the structural complexity between broadleaf and conifer trees. We then used tree-level point clouds to assess several tree metrics, such as diameter at breast height (DBH), total tree height (HT), crown projection area (PAC), crown width (WC), crown length (LC), 3D crown surface (SC), and 3D crown volume (VC). Our results indicated that LiDAR fusion can increase the estimation accuracy of DBH and HT, especially in broadleaves (97.8% accuracy). In addition, fusion significantly reshaped the modeled crown structures in both plots, which led to improved estimates for all crown metrics. The results show empirical evidence that LiDAR fusion can also have a determining role in supporting ecosystem services. For example, detailed 3D mapping of tree crowns can be used to assess the mitigation of rainfall`s kinetic energy by tree crowns concerning soil erosion and sedimentation near habitable zones.

ODFNet: Using orientation distribution functions to characterize 3D point clouds

Learning new representations of 3D point clouds is an active research area in 3D vision, as the order-invariant point cloud structure still presents challenges for the design of neural network architectures. Recent work explored learning global, local, or multi-scale features for point clouds. However, none of the earlier methods focused on capturing contextual shape information by analyzing local orientation distributions of points. In this paper, we use point orientation distributions around a point in order to obtain an expressive local neighborhood representation for point clouds. We achieve this by dividing the spherical neighborhood of a given point into predefined cone volumes, and statistics inside each volume are used as point features. In this way, a local patch can be represented not only by the selected point’s nearest neighbors, but also by considering a point density distribution defined along multiple orientations around the point. We are then able to construct an orientation distribution function (ODF) neural network that makes use of an ODFBlock which relies on MLP (multi-layer perceptron) layers. The new ODFNet model achieves state-of-the-art accuracy for object classification on ModelNet40 and ScanObjectNN datasets, and segmentation on ShapeNet and S3DIS datasets.

The Development and Evaluation of a Backpack LiDAR System for Accurate and Efficient Forest Inventory

Forest inventory holds an essential role in forest management and research, but the existing field inventory methods are highly time-consuming and labor-intensive. Here, we developed a simultaneous localization and mapping-based backpack light detection and ranging (LiDAR) system with dual orthogonal laser scanners and an open-source Python package called Forest3D for efficient and accurate forest inventory applications. Two key forest inventory variables, tree height and diameter at breast height (DBH), were extracted at six study sites with different tree species compositions. In addition, the vertical point density distribution and leaf area density (LAD) were calculated for two complex natural forest sites. The results showed that the backpack LiDAR system together with the Forest3D package accurately estimated the tree height ( R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.65, RMSE = 1.90 m) and DBH ( R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.95, RMSE = 0.02 m), which were equivalent to those derived from terrestrial laser scanning (TLS), but with much higher efficiency. The point density of the backpack LiDAR data was higher than or the same as that of the TLS data across all height strata, and the estimated LAD fit well with the TLS estimates ( R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> > 0.92, RMSE = 0.01 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ). The backpack LiDAR system, along with the Forest3D package, provides an efficient and accurate solution for extracting forest inventory variables, which should be of great interests to forest managers and researchers.

Investigation on Material Removal Uniformity in Electrochemical Mechanical Polishing by Polishing Pad with Holes

Owing to the low polishing pressure and high removal rate, electrochemical mechanical polishing (ECMP) is a good candidate to process thin copper substrates. However, ECMP pads require punching holes to ensure electrochemical effects on substrate surface during polishing, and difference in the arrangement of holes on polishing pad leads to uneven distribution of electrochemical action on substrate, which results in different material removal rates. This paper presents a new model to investigate non-uniformity of material removal in ECMP by using track point density distribution. The coefficient of variation of track point density and density distribution of two polishing pads at different speed ratios were simulated to represent the uniformity of electrochemical action across substrate, and experiments were designed to verify the results of simulation. The simulation and experimental results show that substrate after polished by the concentric circular arrangement pad has an annular corrugation and its flatness is deteriorated. The phyllotactic arrangement pad has a more uniform polishing effect, and the flatness error of substrate which has a diameter of 100 mm is reduced from 9.7 μm PV to 4.5 μm PV after polished by this pad.

Mesoscopic simulations of hydrophilic cross-linked polycarbonate polyurethane networks: structure and morphology.

Polyurethane (PU) cross-linked networks are frequently used in biomedical and marine applications, e.g., as hydrophilic polymer coatings with antifouling or low-friction properties and have been reported to exhibit characteristic phase separation between soft and hard segments. Understanding this phase-separation behavior is critical to design novel hydrophilic polymer coatings. However, most of the studies on the structure and morphology of cross-linked coatings are experimental, which only assess the phase separation via indirect methods. Herein we present a mesoscopic simulation study of the network characteristics of model hydrophilic polymer networks, consisting of PU with and without methyl-polyethylene glycol (mPEG) dangling chains. The systems are analyzed using a number of tools, such as the radial distribution function, the cross-link point density distribution and the Voronoi volume distribution (of the cross-linking points). The combined results show that the cross-linked networks without dangling chains are rather homogeneous but contain a small amount of clustering of cross-linker molecules. A clear phase separation is observed when introducing the dangling chains. In spite of that, the amount of cross-linker molecules connected to dangling chains only, i.e., not connected to the main network, is relatively small, leading to about 3 wt% extractables. Thus, these cross-linked polymers consist of a phase-separated, yet highly connected network. This study provides valuable guidelines towards new self-healing hydrophilic coatings based on the molecular design of cross-linked networks in direct contact with water or aqueous fluids, e.g., as anti-fouling self-repairing coatings for marine applications.

Road Geometric Features Extraction based on Self-Organizing Map (SOM) Neural Network

Geometry is the key parameter when extracting road from high-resolution remote sensing imagery. We propose a method for road geometry parameter s extraction from high spatial resolution remote sensing imagery automatically based on self-organizing map (SOM) neural network algorithm. SOM is a no-tutor clustering segmentation method and the algorithm is the foundation of later road automatic extraction. Our approach may adjust cluster number and cluster center of the image through analyzing the point density distribution of self-organizing feature map neural network competition layer, which is good for flexible processing on the image excessive segmentation problem and succeed in accurate segmentation object. Then we can extract geometric features of the terrain target. The results are demonstrate d that the algorithm proposed is both accurate and effective.

Design and optimisation of laser scanning for tunnels geometry inspection

The use of terrestrial laser scanning technology in engineering surveys is gaining an increasing interest due to the very high spatial density of the acquired data. Recent improvements regarding the speed, accuracy, software algorithms and the fall in price have introduced a high potential for large scale applications of this technology in highly demanding engineering environments such as tunnels. Railway tunnels, in particular those of a long length, create challenges for surveyors due to their elongation to obtain satisfactory geometry of the scanned data. The purpose of this paper is to give an optimal solution for surveying tunnel geometry using laser scanning technology to reliably inspect railway tunnels and create “as-built” documentation.The proposed methodology provides optimisation of scanning parameters, scans registration, the georeferencing approach and the survey control network design. The maximal size of the scanner shifting along the tunnel alignment is primarily conditioned by factors including the incidence angle of the laser beam and the point density distribution. The authors introduce the so-called arbitrary georeferencing approach in long tunnel scanning that controls the point cloud geometric distortions to the required limits and contributes to time and material resources savings. Optimal design of the survey control network ensures the required positional accuracy and the reliability of the measurements, together with a cost effective approach to tunnels surveying.The proposed methodology is followed by the empirical results of the modelling and profiling of 12 tunnels in a single track railway. The lengths of these tunnels are from 60m to 1260m, with a total length of 3.5km. Due to the specific geometry of the case study tunnels, the maximal favourable laser incidence angle is 78° with a distance of 13m and consequently the optimal size of the scanner shifting along the tunnel alignment is 26m. The survey control network is designed with the condition that the optimal reliability factors are within the required limits for engineering networks. A priori estimation of the control network positional uncertainty and a posteriori adjustment results shows that the achieved positional accuracy of the control points is approximately five times better than the requested absolute accuracy of the tunnel model: σm=2cm. On the largest tunnel example it is shown that the arbitrary georeferencing approach assures that the optimal registration error size is within the requested limits.

Improved reliability analysis method based on the failure assessment diagram

With the uncertainties related to operating conditions, in-service non-destructive testing (NDT) measurements and material properties considered in the structural integrity assessment, probabilistic analysis based on the failure assessment diagram (FAD) approach has recently become an important concern. However, the point density revealing the probabilistic distribution characteristics of the assessment points is usually ignored. To obtain more detailed and direct knowledge from the reliability analysis, an improved probabilistic fracture mechanics (PFM) assessment method is proposed. By integrating 2D kernel density estimation (KDE) technology into the traditional probabilistic assessment, the probabilistic density of the randomly distributed assessment points is visualized in the assessment diagram. Moreover, a modified interval sensitivity analysis is implemented and compared with probabilistic sensitivity analysis. The improved reliability analysis method is applied to the assessment of a high pressure pipe containing an axial internal semi-elliptical surface crack. The results indicate that these two methods can give consistent sensitivities of input parameters, but the interval sensitivity analysis is computationally more efficient. Meanwhile, the point density distribution and its contour are plotted in the FAD, thereby better revealing the characteristics of PFM assessment. This study provides a powerful tool for the reliability analysis of critical structures.

Optimization of Viscous Mixing in a Two-Dimensional Cavity Transfer Mixer

Following up ideas put forward by J.M. Ottino and colleagues, the possibility of designing a computational tool to optimize the mixing of viscous fluids in industrial devices is studied. It is shown that an efficient method to characterize and quantify a mixing process is to apply the statistical measures introduced by Danckwerts (e.g., intensity of segregation and scale of segregation) on the coarse-grained density distribution of points in Poincare sections and advection patterns, that can be obtained by tracking the positions of marked fluid elements numerically. This method is not computationally excessively costly and, as is demonstrated here, can be applied easily to experimental dye advection studies. The model system used is the Stokes flow in a two-dimensional cavity transfer mixer: two rectangular cavities which are periodically driven by a solid wall and by the passage of the cavities over each other. This system shares with many industrial devices the complexity that the geometry of the flow is time-dependent. These changes in the geometry of the flow impose difficulties on the techniques of calculating the fluid velocity field (a boundary element method) and the advection of marked fluid elements. Ways of overcoming these difficulties are described.

A Comparison of Two Approaches to Beta-Flexible Clustering.

We introduce a UPGMA based counterpart to the Lance and Williams (1966) p-flexible clustering strategy. This new method is compared with the original p-flexible technique based on WPGMA for a range of fl values from -0.8 to +0.1. Recovery of the known cluster structure from simulated data was evaluated using the Hubert and Arabie (1985) version of the Rand statistic. The algorithm used to generate the simulated clusters in the study included error-free data as well as three other error conditions. The simulated data also varied the number of clusters, the underlying dimensionality, and the density distribution of points to the clusters. Results showed that the flexible UPGMA gives the best recovery for all generated data configurations. Further, the flexible UPGMA method with a small negative β value performed better than the standard UPGMA method where β is set equal to zero. The flexible UPGMA strategy, employed with a narrow β range, is recommended based upon its ability to recover cluster structure over all error conditions.

Multifractality of space-filling bearings and Apollonian packings

We study the structure of space-filling bearings (SFB) and Apollonian packings (AP) by determining the scaling behavior of the density distribution of points where the circles touch each other. Application of the sand box method to the average of theqth power of the number of touching points reveals the multifractal aspects of the structure of SFB and AP.

Filtered bessel functions in computerized tomography

Computer Aided Tomography (CAT) is widely used in the medical imaging area for the detection of cancerous tissues. It has also proved to be a good technique for measuring point-density (void-fraction) in two-phase flow systems. The present day CAT-scanners employ alogorithms which are essentially a discrete implementation of the Radon Inversion Formulae. These methods of reconstructing density distributions are fast and easy to implement. The present work is an attempt to simplify (and consequently to speed-up) the existing algorithms for the cases of radially symmetric density distribution. The method uses Radon Inversion Formulae and involves Bessel's Function of Fourier frequency. The algorithm was tested on some known distributions and the reconstruction is excellent. Data for bubbly-flow was also processed to obtain a point density distribution. The range of investigation was 0.6 ≤ 〈ϱ〉 ≤ 0.9 g/cm 3 , where “〈 〉” denotes average cross-sectional value. The values of 〈ϱ CT 〉 are within ±0.03 g/cm 3 of the true values, 〈ϱ〉, for the data sets considered. The results are comparable with another simple method involving radial polynominals. It is observed that the simplified Radon Inversion Formulae for the radially symmetric case gives good results and can be implemented with ease.