Numerical analysis of cavitation shedding flow around a three-dimensional hydrofoil using an improved filter-based model

The cavitation shedding flow around a 3-D Clark-Y hydrofoil is simulated by using an improved filter-based model （FBM） and a mass transfer cavitation model with the consideration of the maximum density ratio effect between the liquid and the vapor. The unsteady cloud cavity shedding features around the Clark-Y hydrofoil are accurately captured based on an improved FBM model and a suitable maximum density ratio. Numerical results show that the predicted cavitation patterns and evolutions compare well with the experimental visualizations, and the prediction errors of the time-averaged lift coefficient, drag coefficient and Strouhal number St for the cavitation number o- = 0.8, the angle of attack a= 8°at a Reynolds number Re = 7 x 10^5 are only 3.29%, 2.36% and 9.58%, respectively. It is observed that the cavitation shedding flow patterns are closely associated with the vortex structures identified by the Q- criterion method. The predicted cloud cavitation shedding flow shows clearly three typical stages： （1） Initiation of the attached sheet cavity, the growth toward the trailing edge. （2） The formation and development of the re-entrant jet flow. （3） Large scale cloud cavity sheds downstream. Numerical results also indicate that the non-uniform adverse pressure gradient is the main driving force of the re-entrant jet, which results in the U-shaped cavity and the 3-D bubbly structure during the cloud cavity shedding.

Numerical analysis of the unsteady behavior of cloud cavitation around a hydrofoil based on an improved filter-based model

The unsteady cavitation evolution around the Clark-Y hydrofoil is investigated in this paper, by using an improved filter-base model（FBM） with the density correction method（DCM）. To improve the prediction accuracy, the filter scale is adjusted based on the grid size. The numerical results show that a small filter scale is crucial for the unsteady simulations of the cavity shedding flow. The hybrid method that combines the FBM and the DCM could help to limit the overprediction of the turbulent viscosity in the cavitation region on the wall of the hydrofoil and in the wake. The large value of the maximum density ratio ρ1 /ρv, clip promotes the mass transfer rate between the liquid phase and the vapor phase, which results in a large sheet cavity length and the vapor fraction rise inside the cavity. The cavity patterns predicted by the improved method are verified by the experimental visualizations. The time-average lift, the drag coefficient and the primary oscillating frequency St for the cavitation number σ= 0.8, the angle of attack, α= 8°, at a Reynolds number Re= 7×10^5 are 0.735, 0.115 and 0.183, respectively, and the predicted errors are 3.29%, 3.36% and 8.93%. The typical three stages in one revolution are well-captured, including the initiation of the sheet/attached cavity, the growth toward the trailing edge（TE） with the development of the re-entrant jet flow, and the large scale cloud cavity shedding. It is observed that the cloud cavity shedding flow induces the vortex pairs of the TE vortices in the wake and the shedding vortices. The positive vorticity vortex of the re-entrant jet and the TE vortices interacts and merges with the negative vorticity vortex of the leading edge（LE） cavity to produce the shedding flow.

Multiscale Hessian filter-based segmentation and quantification method for photoacoustic microangiography

The appearanee of blood vessels is an important biomarker to distinguish diseased from healthy tissues in several fields of medical applications. Photoacoustie microangiography has the advantage of directly visualizing blood vessel networks within mierocireulatory tissue. Usually these images are interpreted qualitatively. However, a quantitative analysis is needed to better describe the characteristics of the blood vessels. This Letter addresses this problem by leveraging an efficient multiscale Hessian filter-based segmentation method, and four measure- ment parameters are acquired. The feasibility of our approach is demonstrated on experimental data and we expect the proposed method to be beneficial for several microcireulatory disease studies.

传感器网络中过滤机制下高效top-k查询处理技术

如何能量高效的进行top-k查询处理是无线传感器网络领域中的一个重要课题.节点设置过滤窗口可以避免与top-k查询无关的数据上传到汇聚节点或者基站,因而大大减少传感器网络的通信量,节省传感器节点能量.然而,已有算法如FILA、DAFM,基站到传感器节点的过滤窗口更新中仍然存在很大开销.提出一种基于预测信息更新窗口的top-k查询算法FAPU,该算法根据历史数据采用ARIMA时间序列预测模型对接下来s个时刻的传感器数据进行预测,根据预测信息进行多步窗口更新的代价评估,避免不必要的窗口更新,从而减小窗口更新的能量消耗.实验结果表明在确保top-k查询准确性的同时,本文所提出的FAPU算法与已有算法相比更加能量有效.

A Router Based Packet Filtering Scheme for Defending Against DoS Attacks

The filter-based reactive packet filtering is a key technology in attack traffic filtering for defending against the Denial-of- Service （DOS） attacks. Two kinds of relevant schemes have been proposed as victim- end filtering and source-end filtering. The first scheme prevents attack traffic from reaching the victim, but causes the huge loss of legitimate flows due to the scarce filters （termed as collateral damages）; the other extreme scheme can obtain the sufficient filters, but severely degrades the network transmission performance due to the abused filtering routers. In this paper, we propose a router based packet filtering scheme, which provides relatively more filters while reducing the quantity of filtering touters. We implement this scheme on the emulated DoS scenarios based on the synthetic and real-world Internet topologies. Our evaluation results show that compared to the previous work, our scheme just uses 20% of its filtering routers, but only increasing less than 15 percent of its collateral damage.

Enhancing Parkinson’s Disease Prediction Using Machine Learning and Feature Selection Methods

Several millions of people suffer from Parkinson’s disease globally.Parkinson’s affects about 1%of people over 60 and its symptoms increase with age.The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners,but which could be analyzed using recorded speech signals.With the huge advancements of technology,the medical data has increased dramatically,and therefore,there is a need to apply data mining and machine learning methods to extract new knowledge from this data.Several classification methods were used to analyze medical data sets and diagnostic problems,such as Parkinson’s Disease(PD).In addition,to improve the performance of classification,feature selection methods have been extensively used in many fields.This paper aims to propose a comprehensive approach to enhance the prediction of PD using several machine learning methods with different feature selection methods such as filter-based and wrapper-based.The dataset includes 240 recodes with 46 acoustic features extracted from3 voice recording replications for 80 patients.The experimental results showed improvements when wrapper-based features selection method was used with K-NN classifier with accuracy of 88.33%.The best obtained results were compared with other studies and it was found that this study provides comparable and superior results.

Facies and Fracture Network Modeling by a Novel Image Processing Based Method

A wide range of methods for geological reservoir modeling has been offered from which a few can reproduce complex geological settings, especially different facies and fracture networks. Multi Point Statistic (MPS) algorithms by applying image processing techniques and Artificial Intelligence (AI) concepts proved successful to model high-order relations from a visually and statistically explicit model, a training image. In this approach, the patterns of the final image (geological model) are obtained from a training image that defines a conceptual geological scenario for the reservoir by depicting relevant geological patterns expected to be found in the subsurface. The aim is then to reproduce these training patterns within the final image. This work presents a multiple grid filter based MPS algorithm to facies and fracture network images reconstruction. Processor is trained by training images (TIs) which are representative of a spatial phenomenon (fracture network, facies...). Results shown in this paper give visual appealing results for the reconstruction of complex structures. Computationally, it is fast and parsimonious in memory needs.

Assessing the performance of urban heritage conservation projects-influencing factors,aspects and priority weights

Heritage conservation in urban areas involves complex systems often faced with the dilemmas of maintaining the built form's historical character,improving infrastructure,and managing development through stakeholder cooperation.At present,the performance of any conservation project is solely vested in conserving the built fabric.Evaluation tools for urban heritage conservation projects do not have provisions for measuring the subjective value of stakeholders who are part of the heritage setting.This study tries to identify and prioritise the factors that need to be considered when developing a conservation project performance assessment model for an urban heritage conservation project from the perspective of experts that can be further evaluated from the perspective of stakeholders.As these complex systems can be better viewed in the context of developing countries,the case of India is adopted.From a literature review,factors that contribute to the outcome of an urban heritage conservation project were identified and categorised into six aspects:the physical,social,economic,cultural,political,and continuity aspects.Through an expert survey,the factors that constituted each aspect were filtered using the feature selection method of correlation to avoid factors that may seem related.The factors under each aspect were ranked using a weighted average ranking method to identify the most prioritised factors determining the outcome of an urban heritage conservation project.The priority weights of the aspects were calculated using Saaty's analytic hierarchy process.The results show that the cultural aspect was the most important aspect,followed by the continuity aspect.The social and physical aspects were prioritised similarly,followed by the economic and political aspects.This study is distinctive because it identifies the influential factors that can help develop a conservation project performance assessment model for an urban heritage conservation project.

Numerical analysis of cavitation within slanted axial-flow pump

In this paper, the cavitating flow within a slanted axial-flow pump is numerically researched. The hydraulic and cavitation performance of the slanted axial-flow pump under different operation conditions are estimated. Compared with the experimental hydraulic performance curves, the numerical results show that the filter-based model is better than the standard k-ε model to predict the parameters of hydraulic performancE. In cavitation simulation, compared with the experimental results, the proposed numerical method has good predicting ability. Under different cavitation conditions, the internal cavitating flow fields within slanted axial-flow pump are investigated. Compared with flow visualization results, the major internal flow features can be effectively grasped. In order to explore the origin of the cavitation performance breakdown, the Boundary Vorticity Flux （BVF） is introduced to diagnose the cavitating flow fields. The analysis results indicate that the cavitation performance drop is relevant to the instability of cavitating flow on the blade suction surface.

Experimental investigation and numerical analysis of unsteady attached sheetcavitating flows in a centrifugal pump

This paper studies the attached sheet cavitation in centrifugal pumps. A pump casted from Perspex is used as the test subject. The cavitation bubbles were observed in the entrance of the impeller and the drops of the head coefficients were measured under different operating conditions. A Filter-Based Model （FBM）, derived from the RNG k-e model, and a modified Zwart model are adopted in the numerical predictions of the unsteady cavitating flows in the pump. The simulations are carded out and the results are compared with experimental results for 3 different flow coefficients, from 0.077 to 0.114. Under four operating conditions, qualitative comparisons are made between experimental and numerical cavitation patterns, as visualized by a high-speed camera and described as isosurfaces of the vapour volume fraction ctv = 0.1. It is shown that the simulation can truly represent the development of the attached sheet cavitation in the impeller. At the same time, the curves for the drops of the head coefficients obtained from experiments and calculations are also quantitatively compared, which shows that the decline of the head coefficients at every flow coefficient is correctly captured, and the prediction accuracy is high. In addition, the detailed analysis is made on the vapour volume fraction contours on the plane of span is 0.5 and the loading distributions around the blade section at the midspan. It is shown that the FBM model and the modified Zwart model are effective for the numerical simulation of the cavitating flow in centrifugal pumps. The analysis results can also be used as the basis for the further research of the attached sheet cavitation and the improvement of centrifugal pumps.

Numerical analyses of ventilated cavitation over a 2-D NACA0015 hydrofoil using two turbulence modeling methods

The present paper studies the ventilated cavitation over a NACA0015 hydrofoil by numerical methods. The corresponding cavity evolutions are obtained at three ventilation rates by using the level set method. To depict the complicated turbulent flow structure, the filter-based density corrected model（FBDCM） and the modified partially-averaged Navier-Stokes（MPANS） model are applied in the present numerical analyses. It is indicated that the predicted results of the cavitation shedding dynamics by both turbulence models agree fairly well with the experimental data. It is also noted that the shedding frequency and the super cavity length predicted by the MPANS method are closer to the experiment data as compared to that predicted by the FBDCM model. The simulation results show that in the ventilated cavitation, the vapor cavity and the air cavity have the same shedding frequency. As the ventilated rate increases, the vapor cavity is depressed rapidly. The cavitation-vortex interaction in the ventilated cavitation is studied based on the vorticity transport equation（VTE） and the Lagrangian coherent structure（LCS）. Those results demonstrate that the vortex dilatation and baroclinic torque terms are highly dependent on the evolution of the cavitation. In addition, from the LCSs and the tracer particles in the flow field, one may see the process from the attached cavity to the cloud cavity.