Investigation on airflows in abnormal nasal cavity with adenoid vegetation by particle image velocimetry

Knowledge of airflow characteristics in nasal cavity is essential to understand the physiological and pathological aspects of nasal breathing. Several studies have utilizedphysical models of the healthy nasal cavity to investigate the relationship between nasal anatomy and airflow. Since the final goal of these works is their contribution to the diagnosisand treatment of nasal diseases, the next step on this topic is naturally studies for disordered nasal cavities. In this paper, as the first application, airflows in the normal and abnormal nasal cavities with adenoid vegetation are investigated experimentally by PIV, and comparisons of both cases are appreciated. Dense CT data and careful treatment of model surface under the ENT doctor’s advice provide more sophisticatedcavity model. The CBC PIV algorithm with window offset is used for PIV flow analysis. Average and RMS distributions are obtained for inspirational and expirational nasal airflows. Airflow characteristics that are related with the abnormalities in nasal cavity are presented.     

Analysis of flow distribution from high-speed flow actuator using particle image velocimetry and digital speckle tomography

A variety of active flow control (AFC) methods are typically used in low-speed applications; however, the AFC techniques that are available for high-speed, supersonic applications are very limited. Under AFOSR (Air Force Research Laboratory) sponsorship, The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is investigating a device that is intended for high-speed flow control; it is called the SparkJet actuator, which manipulates high-speed flows without active mechanical components. To date, actuator characterization has included computational and experimental techniques including parametric studies and flow visualization techniques to investigate the operation of the SparkJet device under various conditions. This paper focuses on the experimental flow measurement techniques that have been implemented. The results will be used for validating prospective computational studies that investigate the detailed characteristics of the SparkJet’s discharge and cooling stages after an energy deposition pulse. Current efforts include the use of high- resolution particle image velocimetry (PIV) to quantify the quiescent air operation of a single SparkJet pulse. However, the proper seeding of the SparkJet cavity continues to be challenging and has led to the use of digital speckle tomography (DST) to measure the temperature distribution in the core of the SparkJet plume. In this study, improved PIV techniques were used to acquire a higher-resolution image of the SparkJet-entrained flow. These PIV results show that the peak velocity in the entrained flow is around 53 m/s and the plume is sustained for 75–100 μs. Additionally, the DST data show a peak temperature of 1616.3 K at 75 μs and provide supporting information for interpreting the PIV data. These results are intended to calibrate and build confidence in a computational model.     

Particle image velocimetry of a flow at a vaulted wall

The assessment of flow along a vaulted wall (with two main finite radii of curvature) is of general interest; in biofluid mechanics, it is of special interest. Unlike the geometry of flows in engineering, flow geometry in nature is often determined by vaulted walls. Specifically the flow adjacent to the wall of blood vessels is particularly interesting since this is where either thrombi are formed or atherosclerosis develops. Current measurement methods have problems assessing the flow along vaulted walls. In contrast with conventional particle image velocimetry (PIV), this new method, called wall PIV, allows the investigation of a flow adjacent to transparent flexible surfaces with two finite radii of curvature. Using an optical method which allows the observation of particles up to a predefined depth enables the visualization solely of the boundary layer flow. This is accomplished by adding a specific dye to the fluid which absorbs the monochromatic light used to illuminate the region of observation. The obtained images can be analysed with the methods of conventional PIV and result in a vector field of the velocities along the wall. With wall PIV, the steady flow adjacent to the vaulted wall of a blood pump was investigated and the resulting velocity field as well as the velocity fluctuations were assessed.     

绕后台阶与准方腔耦合流道流场的数值计算与试验研究

用Galerkin有限元法对绕后台阶与准方腔耦合流道流场进行数值模拟。数学模型采用的是流函数—涡量形式的N-S方程,分别计算了雷诺数214.2、428.4和642.6三种情况下流场的结构,计算所得瞬态流场和稳态流场以直观速度矢量图和等值线图的形式给出,并绘出了部分纵截面上速度分布剖面图,分析了雷诺数对流场结构的影响。同时应用近年来发展起来的且获得广泛应用的全场瞬时速度测量技术,即粒子图像测速技术PIV)对流场进行了试验研究,所得速度矢量图与数值计算结果吻合较好。计算和试验结果表明:绕后台阶与准方腔流道流场比较复杂,同时具有后台阶流动和方腔流动的结构特征。研究结果对工程实际具有重要意义。     

迷宫型灌水器水沙两相流场分析及结构改进

为了解决迷宫型灌水器微细流道容易堵塞的问题,针对其复杂的微细流道结构(实际尺寸在0.8～1.2 mm之间),根据灌水器工作时灌溉水中存在过滤不掉的沙粒的实际情况,首先应用计算流体力学(Computational fluid dynamics, CFD)数值计算的方法,进行灌水器整体迷宫流道水砂两相流数值模拟,根据其流动场分析其堵塞的结构因素。同时应用粒子图像测速(Particle image velocimetry, PIV)技术,搭建灌水器流道流动场微PIV测试台,测量实际尺寸大小的微流道中流动场和粒子运动状况,得到其流动场流线图和粒子运动轨迹图,并通过灌水器的抗堵塞性能试验,验证了迷宫型灌水器微流道中流动场和粒子状况分析计算的正确性。针对流道中存在的容易引起堵塞的流动滞止区进行结构优化改进,试验结果表明,应用改进的结构可提高迷宫型灌水器的抗堵塞性能。     

An experimental study of developing and fully developed flows in a wavy channel by PIV

An experimental study is presented for a flow field in a two dimensional wavy channels by PIV. This flow has two major applications such as a blood flow simulation and the enhancement of heat transfer in a heat exchanger. While the numerical flow visualization results have been limited to the fully developed cases, existing experimental results of this flow were simple qualitative ones by smoke or dye streak test. Therefore, the main purpose of this study is to produce quantitative flow data for fully developed and developing flow regimes by the Correlation Based Correction PIV (CBC PIV) and to conjecture the analogy between flow characteristics and heat transfer enhancement with low pumping power. Another purpose of this paper is to examine the onset position of the transition and the global mixing, which results in transfer enhancement. PIV results on the Fully developed and developing flow in a wavy channel at Re=500, 1000 and 2000 are obtained. For the case Reynolds Number equals 500, the PIV results are compared with the finite difference numerical solution.     

某双阀芯电液比例多路阀主阀进口节流流场及阀口压降特性研究

以某系列双阀芯电液比例多路阀为研究对象,采用CFD流场仿真技术和PIV可视化测速技术对不同阀口开度和流量下的主阀沿进口流道、节流口、阀腔的流场进行了流体仿真和试验可视化研究。应用Fluent软件仿真研究了主阀进口节流流场分布并得出阀口压降特性;采用PIV试验研究的手段对流场分析结果加以验证,应用2D-PIV技术获得主阀腔内部一个截面上的流场分布,并通过相似理论计算得出阀口压降特性。CFD流场仿真和PIV试验结果表明：该双阀芯电液比例多路阀主阀出油环形腔内会形成较大旋涡,且阀口开度和流量对主阀进口节流内部流场结构和阀口压降特性有重要的影响。研究结果对定性分析双阀芯电液比例多路阀主阀内能量损失和噪声、主阀的结构和流道的设计以及优化具有重要实际意义,为CFD技术和PIV技术在双阀芯多路阀领域的应用研究提供了参考。     

A modified optical flow algorithm based on bilateral-filter and multi-resolution analysis for PIV image processing

Particle Image Velocimetry (PIV) technology is an efficient and powerful testing method to investigate the characteristics of flow field. The topic of PIV post-processing techniques has roused researchers׳ wide concern for its great influence on the success of flow field measurement. The traditional correlation algorithms have their innate defects. In the present study, a modified optical flow algorithm is proposed to overcome these deficiencies based on bilateral-filter and multi-resolution analysis of PIV image processing. The algorithm is designed based on the principle of multilayer segments, in which the isotropic diffusion method is employed to calculate the low-resolution layer of the image and the nonlinear filtering method is used to process the high-resolution layer. This new algorithm can reduce image noise effectively and maintain the details of the image boundary. In addition, the design of nonlinear filter makes the optical flow equation simpler, and the optimal velocity mapping factor method needs less iteration and reduces the computational load. The algorithm is first tested on synthetic time-resolved channel flow images, and the computational results from the simulated particle images are found to be in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual up-channel flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images.     

Experimental Study of Lubricating Grease Flow inside the Gap of a Labyrinth Seal Using Microparticle Image Velocimetry

In this study, the flow of lubricating greases in a labyrinth seal geometry is studied using microparticle image velocimetry (µPIV). The aim is to evaluate the grease velocity distribution inside the gap of a labyrinth seal and to find a relationship between the grease consistency and the transferred speed from the rotating ring in order to choose the correct grease as a sealing medium. In addition, the grease flow characteristics are important for the understanding of fracture due to grease layer displacement. For these purposes, four greases with different rheological properties were used in µPIV experiments. It was found that the grease consistency plays a crucial role in speed development as well as the grease composition and presence of a slip effect at the grease–rotating wall interface.     

An improved particle image velocimetry method for efficient flow analyses

This study proposes a spatiotemporally Adaptive Search Area (SA) size selecting algorithm for Particle image velocimetry (PIV), ASAPiv. The presented method releases the constraint of conventionally used static SAs, offering a significant computational performance increase through optimizing the dimensions of the SA according to the local flow conditions in a transient manner. The algorithm is implemented as a part of a new PIV framework, developed within the MATLAB environment. The most relevant steps of PIV and the related methods are reviewed, starting from image pre-processing up to the post-processing of raw PIV results. The performance of the proposed algorithm and the PIV tool in general is demonstrated through three examples of different nature, including a synthetic image sequence, a conventional, laser illuminated PIV case and a large-scale, field application. The dynamic alteration of the SAs is found to be consistent with the prevailing flow conditions, while the accuracy of PIV in general is maintained. Total calculation times with static and dynamic SAs are compared. The benchmark cases highlight the relevance of adaptive SAs in cases of spatiotemporally varied flow conditions, where significant (up to 900%) computational performance increase is achieved. In case of unidirectional, steady flow conditions the method offers moderate speed-up compared to the employment of static SA sizes.     

The development of an automated PIV image processing software—SmartPIV

Since the popularity of digital particle image velocimetry technique (DPIV), many PIV image processing algorithms have been proposed. Amongst them, fast Fourier transform (FFT) Cross Correlation, Discrete Window Offset Cross Correlation, Iterative Multigrid Cross Correlation, Iterative Image Deformation Cross Correlation and cross correlation based particle tracking methods are widely used algorithms and have been extensively studied by researchers. All of these algorithms have their advantages and disadvantages in terms of computational load and measurement accuracy. To choose a suitable algorithm, researchers not only need to understand the complex principles of these algorithms, but also need to find out their applicable flow conditions. This could greatly increase work load for PIV users who focus more on flow structure itself instead of PIV algorithms. It is therefore necessary to develop a method which can choose PIV algorithms wisely according to the input PIV images. This paper firstly reviews the development of PIV algorithm with mainly focus on analysing advantages and disadvantages of six widely used algorithms. By using both synthetic and real PIV images, comparative studies are then carried out among these algorithms. The tests give a rate for the performance of the algorithms and provide a parameter to automatically separate pattern match and particle tracking algorithms. Based on qualitative and quantitative analysis, an automated PIV image processing method—SmartPIV is proposed and tested by both synthetic and real PIV images. For all the three test cases, the SmartPIV successfully picks the most suitable algorithm and gives very promising results.     

Deep particle image velocimetry supervised learning under light conditions

Particle image velocimetry (PIV) is an important fluid visualization technology which extracts the velocity field from two successive particle images. Recently, some researchers have begun to use convolutional neural network (CNN) to tackle the PIV problem successfully. Some supervised learning methods make use of the PIV dataset with ground truth for network training. However, the existing dataset is composed of pairs of particle images under ideal light conditions and does not take into account the changes in actual experimental conditions. In this paper, we firstly generated a new and more challenging dataset called Light-PIV which fully simulates the change of the brightness of particle images in the real PIV experiment. Secondly, we present here a novel approach for fluid motion estimation which is based on an optical flow network LiteFlowNet. The proposed approach is verified by the application to a diversity of synthetic and experimental PIV images. We not only improve the structure, but also combine the traditional prior assumptions knowledge with the loss function to better guide the network training. The proposed approach is verified by the application to a diversity of synthetic and experimental PIV images. The experimental results show that our proposed method has advantages of high accuracy, obtaining detailed information and strong robustness in our PIV dataset compared with classical PIV methods such as HS optical flow and WIDIM, and even outperforms these existing approaches in some flow cases.     

Development of a realistic human airway model

Numerous models of human lungs with various levels of idealization have been reported in the literature; consequently, results acquired using these models are difficult to compare to in vivo measurements. We have developed a set of model components based on realistic geometries, which permits the analysis of the effects of subsequent model simplification. A realistic digital upper airway geometry except for the lack of an oral cavity has been created which proved suitable both for computational fluid dynamics (CFD) simulations and for the fabrication of physical models. Subsequently, an oral cavity was added to the tracheobronchial geometry. The airway geometry including the oral cavity was adjusted to enable fabrication of a semi-realistic model. Five physical models were created based on these three digital geometries. Two optically transparent models, one with and one without the oral cavity, were constructed for flow velocity measurements, two realistic segmented models, one with and one without the oral cavity, were constructed for particle deposition measurements, and a semi-realistic model with glass cylindrical airways was developed for optical measurements of flow velocity and in situ particle size measurements. One-dimensional phase doppler anemometry measurements were made and compared to the CFD calculations for this model and good agreement was obtained.     

An alternative illumination source based on LEDs for PIV measurements on human swimmers—A feasibility study

Methods for flow visualization help to investigate the motion of fluids that are normally invisible. Especially, Particle Image Velocimetry (PIV) – with a laser as light source – has been established in the field of engineering and partly in biology. Since the standard measuring equipment applying a laser system is very sensitive with respect to transport, temperature, humidity as well as laser safety requirements have to be adhered, the observation and classification of flow pattern around human swimmers in swimming pools has been rarely applied. There is a need for a simple, powerful, affordable, robust, and portable illumination source which shall not harm the swimmer by exceeding the permitted maximum radiation for human skin and eyes. As a result, this technical note demonstrates an alternative light source system based on LEDs which enables PIV measurements around human swimmers similar to experiments with a (traditional) laser system. As an example, the flow fields of two different swimmers with a similar movement and phase are compared using both illumination methods laser and LED. Furthermore, a series of sequential velocity fields, produced by the motion of a monofin swimmer, generate a vortex pair with an inverse Karman vortex street which is typically seen in fish and marine mammal locomotion. Consequently, this LED illumination source is show to provide a sufficient suitable light intensity as well as light quality enabling the measurement of the flow field around swimmers.     

Application of video imagery techniques for low cost measurement of water surface velocity in open channels

Developments in digital video recording technology make the video imagery tools more popular for velocity measurement in water flows. This has especially been of large interest due to its inherent advantage of non-contact nature which is quite handy in extreme flow conditions. Particle Image Velocimetry (PIV), Particle Tracking Velocimetry (PTV) and Large Scale Particle Tracking Velocimetry (LSPTV) are applied to free surface channel flow for water surface velocity measurement. Experiments are conducted to measure either a single point velocity applying PTV or velocity profiles across the channel width applying PIV on the water surface in a rectang typical velocities of nearly 1 andular tilting flume for various flow conditions. Technical issues regarding tracer particle size and type, travel distance, lighting, recording speed, camera position, image distortion and state of flow are discussed. Measured data is compared to computational results obtained from a numerical model involving a non-linear turbulence model capable of predicting turbulence driven secondary flows. Confirmation of reasonable match between computational and experimental results whereby applying mutual collaboration of them for discharge measurement has been attested. In addition to discharge, boundary roughness has also been predicted as an outcome of the numerical solution.     

Experimental investigation of particle distribution in a flow through a stenosed artery

The particle distribution of a dilute solid-liquid suspension through a stenosed arterial geometry was investigated. Particle image velocimetry (PIV) was used to determine the velocity as well as to acquire the flow images. The light intensity scattered by particles was evaluated to determine the particle distribution. Flow separation exists where the flow emerges from the stenosis throat. From the PIV images, the particle density distribution exhibited differing non-uniform characteristics which vary with flow rate, particle size and particle concentration. At low flow rates, a particle-free layer is formed. As the flow rate is increased, particles accumulate in concentric recirculation orbits within the downstream vortex. Particles with larger size and higher concentration tend to accumulate more towards the center of the vortex.     

基于样条曲面描述的大变形有限元数值模拟关键技术探索

模具型腔描述、锻件有限元网格划分、界面接触约束是制约三维复杂体成形有限元数值模拟技术应用的3个关键性问题。以3次B样条曲面描述为基础,对三维复杂工具表面离散、变形体三维网格自动划分、变形体边界节点与模具接触状态判断的一体化技术进行了研究。利用B样条曲面的直观性、局部性、通用性、造型灵活性等特点,构造复杂模具型腔曲面及变形体边界,提出三维网格样条生成法、改进的分块样条生成法及接触判断的区域层次搜索技术。     

A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.     

Real-time simulation and visualization of robotic belt grinding processes

Real time simulation and visualization are important for robot programmers to verify and optimize the path planning for the robotic belt grinding process. A new free-form surface representation based on discrete surfel element is developed to facilitate the system implementation, which exploits the advantage of the new development of point-based rendering technology in computer graphics. A local process model is integrated to calculate the material removal rate by considering the local geometry information and non-uniform force distribution. The final surface grinding error is easy to be assessed and visualized for quality evaluation. The experiments show that the simulation error is below 15%, even for a non-uniform contact under stable cutting conditions.     

A particle-image velocimetry system for measurement of velocity flow fields for investigations of thermohydraulic processes on the large-scale benchmark of a promising fast-neutron reactor

The use of visualization techniques in the research on thermohydraulic processes using large-scale models of nuclear power plants is discussed. In particular, the original particle-image velocimetry (PIV) measurement system at the TISEI test bench was presented, which is a model of a proposed fast-neutron reactor. Illumination and video-filming systems with the simultaneous use of several lasers and camcorders, as well as image-processing algorithms that make it possible to carry out field measurements with high precision in a complex configuration of the reactor model, reflections and distortions of the laser knife section, and shadowing by obstacles are described. The developed methodology of conversion of the image coordinates and velocity field into the reference system of the reactor model using a virtual 3D simulation made it possible to significantly simplify the experiments.