Acceleration feature points of unsteady shear flows

The rheological modeling of a polymer melt in the course of its extrusion through a circular cylindrical channel inside a shaping die equipped with a rotating mandrel and a rotating or stationary nozzle is investigated. This paper attempts to provide a detailed rheological description of the physical processes of a polymer melt based on Leonov model inside the channel of an extruder under its kinematic deformation upon two-dimensional shear flow. Based on the obtained rheological equations of state, the flow process can be described in a form of dependencies reflecting kinematics of complex polymer deformation in the die channel. These expressions allow estimation of the velocity distribution for the flow elements within the channel as well as of the flow-pressure characteristics of the process. A quantitative relation between flow characteristics, rheological properties of polymer, and technical parameters of the channel of an extruder was determined. Comparison of this theoretical model with experimental results validates the suggested model.

A computerized analysis of supersonic nonuniform flows over sharp and spherically blunted cones at angle of attack

A computational study of joint effects of transverse shear and streamwise acceleration on three-dimensional boundary layers

The feature extraction of a point cloud fragment model is the basis of fragment splicing, which provides the technical support for research on the segmentation, splicing, and restoration of fragment surfaces. High-quality feature extraction, however, is a complicated process due to the diversity of the surface information of a fragment model. For this subject, a high-efficient point cloud feature extraction method was proposed to address a new method for extracting feature lines. First, the projection distance feature of the point cloud model was calculated to identify the potential feature points. Furthermore, the local information of the possible feature points was used to construct the adaptive neighborhoods for identifying the feature points based on neighborhoods of the model. The clustering fusion of the feature points was proposed according to the discrimination threshold values of the feature points. Finally, the Laplace operator was utilized to refine and connect the feature points to form smooth feature lines. The experimental results showed that the proposed method was automatic, highly efficient, and with good adaptability that could effectively extract the detailed features and construct the complete feature lines. Moreover, results showed that the provided framework could extract the features of simple structure models and be feasible to a certain extent for fragment models with abundant features.

At present, in the application of feature-based medical 3D reconstruction technology, there are still problems such as low matching accuracy of feature points in endoscope images and slow processing speed of image data. Therefore, the feature-based 3D reconstruction theory is of great research value and has great application value. This paper proposed a new feature detection method to improve the problems. This paper divides feature detection into two parts for further improvements: feature extraction and feature description. For feature extraction, the FAST algorithm shows a poor classification effect, so this paper adds the decision tree based on the C4.5 algorithm into the traditional FAST. The original data are divided into two decision trees to make the feature extraction performance more stable and feature point extraction more efficient. For the feature description part, the FREAK descriptor is used, combined with this paper's improved feature extraction algorithm. The feature points are extracted in scale space. The second-order function fitting is carried out according to the feature points' response scores in different scales. The scale-invariant descriptor of sub-pixel precision is obtained. The experimental results on the endoscope image show that the feature extraction method has a higher extraction accuracy and faster extraction speed. In addition, the feature description algorithm has higher calculation efficiency.

This paper describes some laboratory and numerical experiments made on the longitudinal dispersion in an open channel flow. Particular attention has been paid to the initial stages of the process. Physical arguments suggest that the streamwise dispersion of a line of marked fluid elements across a two-dimensional turbulent shear flow occurs in three distinct stages. These stages are identified by a change in the form of the distribution of marked fluid elements in the flow direction. The skewed distribution of the first stage is readily identified by a constant value (approximately 1·1) for the ratio of the peak velocity (V1) of the distribution to the mean-flow velocity $\overline{U}$; experiments using dyed fluid, made at this stage of the process, have revealed six identifiable features of the suggested distribution. The distributions suggested for the second and the third stage are consistent with the experimental findings of Elder (1959) for the second stage and Taylor (1954) for the third stage. An attempt has been made to simulate the process numerically using a Markovian model. The results of the simulation confirm features suggested by physical arguments and are in agreement with the open channel experiments. The Lagrangian autocorrelation function is found to be related to the Lagrangian velocity-history of marked fluid released from extreme positions on the flow cross-section. The correlation function, as expressed in terms of the velocity-history function provided by the numerical simulation, is \begin{eqnarray*} && R(t^{\prime}) = \exp (-bt^{\prime})\int_0^{1}U^{+2}dy^{\prime};\\ && t^{\prime} = tu_{*}/d,\quad U^{+} = \frac{U(y^{\prime})-\overline{U}}{u_{*}}, \end{eqnarray*} where u* is the friction velocity and U(y′) is the temporal mean velocity at a (non-dimensionalized) distance y′ from the flow boundary. In an open channel flow at a Reynolds number (based on friction velocity and channel depth) of 500, the numerical simulation provides the value of b = 0·536. The results of an experiment, in which the three-dimensional motion of small neutrally buoyant spheres was recorded in many small discrete time intervals, corroborate the theoretical suggestions and simulation results.

The classic feature point image stitching algorithm is time-consuming in feature extraction, and an image sparse matrix method is proposed to determine the feature points. This method first uses Laplace operator to extract the image gradient and set the threshold to obtain the sparse matrix of image segmentation, then using features from accelerated segment test (FAST) detection algorithm for feature point. Finally, the speeded-up robust features (SURF) descriptor is given to increase the stability of the feature points. This method solves the problem of time-consuming feature extraction, making the real-time image mosaic possible. In the process of image mosaic, this paper presents a method using Kalman filter to predict the overlap region, thus reducing the computational complexity. In addition, because there is always a mismatch between feature points matching, this paper proposes a method using perceptual hashing to refine the matching pair, which solves the error caused by mismatching for the next image registration and improves the registration accuracy. Experimental results show that the proposed algorithm improves the speed and precision of image mosaic.

The classic feature point image stitching algorithm is time-consuming in feature extraction, and an image sparse matrix method is proposed to determine the feature points. This method first uses Laplace operator to extract the image gradient and set the threshold to obtain the sparse matrix of image segmentation, then using features from accelerated segment test (FAST) detection algorithm for feature point. Finally, the speeded-up robust features (SURF) descriptor is given to increase the stability of the feature points. This method solves the problem of time-consuming feature extraction, making the real-time image mosaic possible. In the process of image mosaic, this paper presents a method using Kalman filter to predict the overlap region, thus reducing the computational complexity. In addition, because there is always a mismatch between feature points matching, this paper proposes a method using perceptual hashing to refine the matching pair, which solves the error caused by mismatching for the next image registration and improves the registration accuracy. Experimental results show that the proposed algorithm improves the speed and precision of image mosaic.

A one-dimensional model for the transition from periodic to chaotic motions in granular shear flows

Most of the existing visual SLAM schemes rely solely on point or line features to estimate camera trajectory. In some scenes such as texture missing or motion blurring, it’s difficult to find a sufficient number of reliable features, resulting in low positioning accuracy. To extract more features, an RPL-SLAM solution is proposed to extract point features and line features respectively. Ulteriorly, the depth information of RGBD image is used to restore the 3D information of point and line features, improving the accuracy of camera track positioning. RPL-SLAM scheme mainly includes three modules: tracking, local mapping and loop detection. Tracking module extends the application of line feature on the basis of point feature extraction and matching. A SLD line segment extraction algorithm which can eliminate the micro segments and a DBM segment matching algorithm based on word bag are proposed respectively. These two algorithms improve the matching efficiency while ensuring the matching accuracy, and effectively track and locate the camera of each frame. In the local mapping and loop detection module, the Plucker coordinates are applied to express the spatial line and define the re-projection error of the straight line, so that the back-end optimization error model of point-line fusion is unified to solve the instability problem in optimization. RPL-SLAM is tested on TUM RGBD and ICL-NUIM data set respectively, and compared with ORB-SLAM2. The result shows that RPL-SLAM can effectively improve the accuracy of pose estimation and map reconstruction while maintaining real-time performance by fusing point-line features with depth images.

Most mainstream visual-inertial SLAM systems rely on the point feature method of front-end images for motion estimation and localization. However, the SLAM system based on the point feature method, in the case of weakly textured environments, may not be able to estimate the motion due to the lack of point features. For this reason, the introduction of line features has received extensive attention. Line features in the environment can improve the localization accuracy of SLAM, but the extraction and matching of line features are relatively time-consuming and cannot satisfy real-time requirements. Based on the EDLines algorithm, we propose a fast visual-inertial odometry that fuses point and line features. The improved EDLines algorithm is used to process line features. By adjusting the internal parameters of the algorithm, the extraction time of line features is decreased while the extraction effect is the same. And the line features screening strategy is proposed to filter out invalid short line segments and merge adjacent line segments. We use the more effective line features after screening for graph matching and back-end optimization, which reduces the calculation amount of line features matching and ensures the accuracy. The proposed algorithm has been tested on the public datasets, and the comparison results with PL-VIO and VINS-Mono show that the algorithm in this paper improved real-time performance and localization accuracy.

Numerical experiments on finite difference solutions of time dependent two-dimensional Navier-Stokes equations are used to study the transition triggering off in a mixing layer of initial tanh(y) profile. The inflow is excited by sinusoIdal waves resulting from the linear theory of hydrodynamic instability. Numerical realizations are compared, through streamwise growth of momentum thickness and vorticity plots, with Winant and Browand experiments.

We conduct a convergence analysis for the estimation of inertial lift force on a spherical particle suspended in flow through a straight square duct using the finite element method. Specifically, we consider the convergence of an inertial lift force approximation with respect to a range of factors including the truncation of the domain, the resolution of the tetrahedral mesh and the boundary conditions imposed at the (truncated) ends of the domain. Additionally, we compare estimates obtained via the Lorentz reciprocal theorem with those obtained via a direct integration of fluid stress over the particle surface. 
 
 References M. S. Alnaes, J. Blechta, J. Hake, A. Johansson, B. Kehlet, A. Logg, C. Richardson, J. Ring, M. E. Rognes, and G. N. Wells. The FEniCS project version 1.5. Arch. Numer. Software, 3(100):923, 2015. doi:10.11588/ans.2015.100.20553. D. Di Carlo. Inertial microfluidics. Lab Chip, 21:30383046, 2009. doi:10.1039/B912547G. C. Geuzaine and J.-F. Remacle. Gmsh: A 3-d finite element mesh generator with built-in pre- and post-processing facilities. Int. J. Numer. Meth. Eng., 79(11):13091331, 2009. doi:10.1002/nme.2579. B. Harding. A study of inertial particle focusing in curved microfluidic ducts with large bend radius and low flow rate. In Proc. 21st Australasian Fluid Mechanics Conference, number 603, 2018. URL https://people.eng.unimelb.edu.au/imarusic/proceedings/21/Contribution_603_final.pdf. B. Harding, Y. M. Stokes, and A. L. Bertozzi. Effect of inertial lift on a spherical particle suspended in flow through a curved duct. J. Fluid Mech., accepted, 2019. URL https://arxiv.org/abs/1902.06848. A. J. Hogg. The inertial migration of non-neutrally buoyant spherical particles in two-dimensional shear flows. J. Fluid Mech., 272:285318, 1994. doi:10.1017/S0022112094004477. K. Hood, S. Lee, and M. Roper. Inertial migration of a rigid sphere in three-dimensional Poiseuille flow. J. Fluid Mech., 765:452479, 2015. doi:10.1017/jfm.2014.739. N. Nakagawa, T. Yabu, R. Otomo, A. Kase, M. Makino, T. Itano, and M. Sugihara-Seki. Inertial migration of a spherical particle in laminar square channel flows from low to high reynolds numbers. J. Fluid Mech., 779:776793, 2015. doi:10.1017/jfm.2015.456. T.-W. Pan and R. Glowinski. Direct simulation of the motion of neutrally buoyant balls in a three-dimensional poiseuille flow. C. R. Mecanique, 333(12):884895, 2005. doi:10.1016/j.crme.2005.10.006. C. Taylor and P. Hood. A numerical solution of the navier-stokes equations using the finite element technique. Comput. Fluids, 1(1):73100, 1973. doi:10.1016/0045-7930(73)90027-3. M. E. Warkiani, G. Guan, K. B. Luan, W. C. Lee, A. A. S. Bhagat, P. Kant Chaudhuri, D. S.-W. Tan, W. T. Lim, S. C. Lee, P. C. Y. Chen, C. T. Lim, and J. Han. Slanted spiral microfluidics for the ultra-fast, label-free isolation of circulating tumor cells. Lab Chip, 1:128137, 2014. doi:10.1039/C3LC50617G. B. H. Yang, J. Wang, D. D. Joseph, H. H. Hu, T.-W. Pan, and R. Glowinski. Migration of a sphere in tube flow. J. Fluid Mech., 540:109131, 2005. doi:10.1017/S0022112005005677. L. Zeng, S. Balachandar, and P. Fischer. Wall-induced forces on a rigid sphere at finite reynolds number. J. Fluid Mech., 536:125, 2005. doi:10.1017/S0022112005004738.

Lattice Boltzmann study of effective viscosities of porous particle suspensions

Topological pattern discovery and feature extraction for fraudulent financial reporting