High-order implicit discontinuous Galerkin schemes for unsteady compressible Navier–Stokes equations

AbstractEfficient solution techniques for high-order temporal and spatial discontinuous Galerkin (DG) discretizations of the unsteady Navier–Stokes equations are developed. A fourth-order implicit Runge–Kutta (IRK) scheme is applied for the time integration and a multigrid preconditioned GMRES solver is extended to solve the nonlinear system arising from each IRK stage. Several modifications to the implicit solver have been considered to achieve the efficiency enhancement and meantime to reduce the memory requirement. A variety of time-accurate viscous flow simulations are performed to assess the resulting high-order implicit DG methods. The designed order of accuracy for temporal discretization scheme is validate and the present implicit solver shows the superior performance by allowing quite large time step to be used in solving time-implicit systems. Numerical results are in good agreement with the published data and demonstrate the potential advantages of the high-order scheme in gaining both the high accuracy and the high efficiency

Traffic Light Recognition for Real Scenes Based on Image Processing and Deep Learning

Traffic light recognition in urban environments is crucial for vehicle control. Many studies have been devoted to recognizing traffic lights. However, existing recognition methods still face many challenges in terms of accuracy, runtime and size. This paper presents a novel robust traffic light recognition approach that takes into account these three aspects based on image processing and deep learning. The proposed approach adopts a two-stage architecture, first performing detection and then classification. In the detection, the perspective relationship and the fractal dimension are both considered to dramatically reduce the number of invalid candidate boxes, i.e. region proposals. In the classification, the candidate boxes are classified by SqueezeNet. Finally, the recognized traffic light boxes are reshaped by postprocessing. Compared with several reference models, this approach is significantly competitive in terms of accuracy and runtime. We show that our approach is lightweight, easy to implement, and applicable to smart terminals, mobile devices or embedded devices in practice

Supervised descent method (SDM) applied to accurate pupil detection in off-the-shelf eye tracking systems

The precise detection of pupil/iris center is key to estimate gaze accurately. This fact becomes specially challenging in low cost frameworks in which the algorithms employed for high performance systems fail. In the last years an outstanding effort has been made in order to apply training-based methods to low resolution images. In this paper, Supervised Descent Method (SDM) is applied to GI4E database. The 2D landmarks employed for training are the corners of the eyes and the pupil centers. In order to validate the algorithm proposed, a cross validation procedure is performed. The strategy employed for the training allows us to affirm that our method can potentially outperform the state of the art algorithms applied to the same dataset in terms of 2D accuracy. The promising results encourage to carry on in the study of training-based methods for eye tracking.Spanish Ministry of Economy,Industry and Competitiveness, contracts TIN2014-52897-R and TIN2017-84388-

INFLUENCE OF PRESSURE FLUCTUATION ON REFLUX VALVE IN A SELF-PRIMING PUMP WITH OUTER RECIRCULATION

ABSTRACT The pressure fluctuation caused by impeller-volute interaction is one of the factors which affect the stability of self-priming pump with outer recirculation. Based on the RNG k ε − turbulence model, three-dimensional unsteady turbulence flow in a self-priming pump was simulated in this paper. Pressure fluctuations were obtained at 26 monitor points distributed at eight sections of the volute and on the reflux valve, and the influence on the valve was analyzed. The CFD results show that the main frequency of monitor points is blade passing frequency, and the pressure difference between maximum and average is minimal at the fifth section, which is 1.3%~2.4%. Using pressure sensors and LabVIEW system, the pressures at third, fifth and seventh sections were tested. The experimental results show that pressure fluctuation layouts are similar as those from CFD, and the pressure difference at the fifth section is 4%, also the minimum. The position also is found with minimal influence on reflux valve. Reflux hole should be placed at 200° ~ 220° from the tongue along the direction of the impeller rotation. Further, according to the CFD results, the Finite Element Analysis (FEA) of the reflux valve was carried out. FEA shows that the valve can close the reflux hole completely after self-priming process, which gets a good hydraulic performance when the pump runs normally