Viscosity-dependent enhancement of fluid resistance in water/glycerol micro fluid segments

The influence of the formation of micro fluid segments on the fluid resistance was studied in an example of water/glycerol mixture by pressure drop measurements in dependence on the flow rate and viscosity. Therefore, a micro fluidic arrangement consisting of two syringe pumps, a pressure sensor and an injector for segment generation was assembled. It was found that micro fluid segments generate a significant enhancement of flow-induced pressure drop. This enhancement depends on the flow rate as well as on the number of microfluid segments and viscosity. The resulting pressure drop can be described by an empirical equation reconsidering flow rate, viscosity, capillary size and number of segments.     

Highly resolved dose–response functions for drug-modulated bacteria cultivation obtained by fluorometric and photometric flow-through sensing in microsegmented flow

The application of the micro fluid segment technique for the investigation of highly resolved dose–response relationship at the physiological parameters segment–internal pH and growth of the cell culture is introduced. The method was used to study the concentration-dependent response of an Escherichia coli culture for the effectors 2,4-dinitrophenol (DNP) and an antibacterial peptide amide (KKVVFKVKFK-NH₂). Large sequences with up to 250 micro fluid segments containing gradually varying concentrations of the effectors were generated using a PTFE micro fluidic arrangement, including a 7-port-manifold and PC-controlled syringe pumps. The response of the cell culture was characterized by a double sensor system allowing for simultaneous read out of metabolism-related changes as well as changes in cell density. A twin arrangement of a micro flow-through photometer and a micro flow-through fluorometer based on LED devices in connection with the application of pH-sensitive polymer sensor particles was applied. This experimental setup allows a detailed determination of drug-related changes in fluorescence intensity by the E. coli culture and the polymer particles as a function of time by tracking changes in pH and cell density. The application of the segmented flow technique for multi-parameter drug screenings provides new insights into the biological answer of bacteria cultures cultivated at the nanoliter scale.     

超声波流量测量影响因素的研究

详细分析了温度对超声波传输速度的影响以及温度、管径、流体流速等因素对流体流动状态的影响。在此基础上,采用FluidFlow软件进行了必要的仿真,并在流量计检定装置上进行了相应的试验。仿真和试验结果验证了温度、管径、流体流速等因素的影响,在对上述影响因素进行相应的系数修正后,保证了超声波流量计的计量精确度。     

Image-based algorithm for analysis of transient trapping in single-particle trajectories

Particle tracking has become an increasingly useful tool in microfluidics and biophysics, allowing measurement of microrheology, local structure, and flow. We introduce a novel, automated approach to analyze single-particle trajectories with transient elements, based on image-processing approaches and physical analysis of probe motion. In many physical and active biological systems, such as living cells, probe particles experience thermally mediated Brownian motion combined with active transport processes that can lead to transient-trajectories of local diffusion and trapping, punctuated by segments of active transport. Analyzing such a trajectory as a single unit masks the intermittent nature of the motion. Moreover, directly applying the generalized Stokes–Einstein relation in out-of-equilibrium systems is incorrect and returns inaccurate rheological parameters. We present an automated image-processing-based method to identify and segment transient trap-escape trajectories, allowing quantitative analysis of each segment. We define and discuss effects of controlling parameters, such as particle size and camera frame rate. Our algorithm provides a general and automated method to segment and analyze transient elements in trajectories of single particles, which can be applied to many different experiments. Our image-based approach allows identification of trapping segments, unbiased by specific step sizes within those traps or the mechanism driving those steps. As an example, we successfully apply this method to experiments of laser tweezers trapped particles and show that trajectory segmentation allows us to calculate both trap and fluid parameters. We accurately identify a round trap, calculate the trap stiffness at 3.1?pN/μm, and find that significant local heating reduces fluid viscosity.     

Simulation of bubble-bubble interaction using a lattice Boltzmann method

This paper presents the results obtained from three-dimensional numerical simulations of multiple bubbles rising under buoyancy in a quiescent viscous incompressible fluid. A lattice Boltzmann method, based on the free-energy model, is developed to simulate the behavior of bubble-bubble interaction while rising in the fluid. A new scheme, which involves eighteen lattice points for the first and second derivative, is proposed to achieve stable computations at high fluid-to-bubble density ratio. The effects of the density ratio and the initial bubble configuration on the flow field induced by rising bubbles and on the evolution of bubble shape during their coalescence are investigated. It is found that for two rising bubbles with the same size, the leading bubble rises like an isolated bubble before coalescence. The trailing bubble is entrained by the leading one, and experiences obvious deformation when it enters the wake region of the leading bubble. The shape evolution of the trailing bubble is different at the high and low density ratios. However, for two rising bubbles with different sizes, the larger bubble always has strong effect on the smaller one in any initial configuration.     

微致动器在流动控制中的应用研究

基于MEMS技术,研制了一种微气泡型致动器.对前缘布置有微致动器的三角翼进行了数值模拟和风洞实验,结果表明:微致动器可以改变三角翼前缘的旋涡流状态,扰动边界层,改变三角翼前缘分离涡位置,合理布置微致动器可以获得一定的滚转力矩,利用微致动器可以进行流动控制,进而改变飞行器的动力性能.     

Efficient feedforward categorization of objects and human postures with address-event image sensors

This paper proposes an algorithm for feedforward categorization of objects and, in particular, human postures in real-time video sequences from address-event temporal-difference image sensors. The system employs an innovative combination of event based hardware and bio-inspired software architecture. An event-based temporal difference image sensor is used to provide input video sequences, while a software module extracts size and position invariant line features inspired by models of the primate visual cortex. The detected line features are organized into vectorial segments. After feature extraction, a modified line segment Hausdorff distance classifier combined with on-the-fly cluster-based size and position invariant categorization. The system can achieve about 90 percent average success rate in the categorization of human postures, while using only a small number of training samples. Compared to state-of-the-art bio-inspired categorization methods, the proposed algorithm requires less hardware resource, reduces the computation complexity by at least five times, and is an ideal candidate for hardware implementation with event-based circuits.     

多重约束条件下的LBD描述子与直线段匹配

目的 针对直线描述子匹配算法缺乏有效的几何约束,且易受弱纹理、尺度变化的影响,提出一种结合多重约束条件的LBD描述子的直线段匹配算法（LBDs）。方法 该算法以LSD算法提取的直线段作为匹配基元,利用SIFT匹配得到的同名点构建同名三角网约束确定候选直线;参考影像上以目标直线段为中心轴建立该直线段的矩形支撑域;根据目标直线段端点及其支撑域四角点在搜索影像上的核线约束建立候选直线段的对应支撑域;利用仿射变换统一目标直线段及候选直线段支撑域的大小;将直线段支撑域分解为大小相等的条形带,通过计算每个条形带的描述符得到该直线段的描述子,依次完成目标直线段与候选直线段LBD描述子的构建;分别计算目标直线段与每个候选直线段描述子向量间的欧氏距离,将满足最近邻距离比准则的候选直线段作为匹配结果;最后选取角度约束对匹配结果检核,确定同名直线。结果 实验选取网上公开的3组分别存在角度、旋转、尺度变换的近景影像对作为实验数据,采用LBDs分别对其进行直线段匹配实验,并与其他直线段匹配算法进行对比分析,实验结果表明,LBDs获取同名直线数目约为其他算法的1.061.41倍,匹配正确率也提高了2.411.6个百分点,从匹配效率上来看,LBDs更为耗时,但兼顾该算法匹配获得同名直线数目、匹配正确率及运行时间,LBDs的鲁棒性更强,匹配结果的准确性与可靠性较高。结论 结合多重约束条件构建的LBD描述子对于存在角度、旋转和尺度变化的影像进行直线匹配过程中具有稳定性。     

Investigation of viscosity effect on droplet formation in T-shaped microchannels by numerical and analytical methods

Both numerical and analytical models have been developed to explore the viscosity effect of the continuous phase on drop formation at a T-shaped junction in immiscible liquids. The effects of the generalized power law coefficient, the power law exponent and the yield stress on the mechanism of drop breakup, final drop size and frequency of drop formation are studied by using the numerical three-dimensional volume of fluid model. Droplets coalescence in Bingham fluids is observed in the beginning transient period. The effect of yield stress on drop extension is also discussed. Predictions of drop size by using an analytical force balance show satisfactory agreement with simulation results for Newtonian and power law fluids with different viscosity ratios. The approximation error associated with the analytical model for Bingham fluids is also acceptable. This analytical model can greatly shorten the prediction time as compared with the numerical model, which is helpful for on-line control.     

基于流网络的流式计算动态任务调度策略

针对大数据流式计算平台中输入数据流速急剧上升所导致的计算延迟升高问题,提出了基于流网络模型的动态调度策略,并将其应用于Flink数据流计算平台。首先,通过定义有向无环图（DAG）中每条边的容量和流量将其转化为流网络模型,并通过容量检测算法确定每条边的容量值;然后,通过最大流算法计算对应的增进网络和优化路径,从而在输入速率上升阶段提升集群的吞吐量,并通过评估时空代价论证了算法的可行性;最后,讨论了重要参数对算法执行效果的影响,并通过实验得出了在不同类型的作业中推荐的参数取值。经实验验证得出：所提算法与Flink平台现有的任务调度策略相比,在输入速率上升阶段对不同作业类型中集群吞吐量的优化比均高于16.12%。实验结果表明动态调度策略在满足任务延迟约束的前提下有效提高了集群的吞吐量。     

应用神经网络测量凝析天然气流量

为了精确测量凝析天然气的气液相流量,研究了将神经网络用于气液两相流流量测量的方法。以中国石油大学自动化系试制的流量检测仪表样机为硬件基础,分析了仪表的差压波动信号,并通过比较F比值确定了特征提取方法。根据多相流存在多种流型的特点,采用了首先识别流体流型再计算其流量的方法。研究表明:神经网络在凝析天然气流量测量中具有较大的应用潜力。但要获得较高的层量精度,还需要更为准确的信号特征提取方法以及更加合理的网络结构。     

带有关节权重的DTW 动作识别算法研究

大多数动作仅包含部分关节的运动,现有方法未对运动剧烈的关节与几乎不参与运 动的关节进行区分,一定程度上降低了动作识别精度。针对这个问题,提出一种自适应关节权重 计算方法。结合动态时间规整(DTW)方法,利用获得的关节权重进行动作识别。首先对分类动作 序列进行分段,每段动作序列中运动较剧烈的关节选择分配更高权重,其余关节平均分配权重; 然后提取特征向量,计算两段动作序列的DTW 距离;最后采用K 近邻方法进行动作识别。实验 结果表明,该算法的总体分类识别准确率较高,且对于较相似的动作也能获得较好的识别结果。     

低液位非满管流量校准及其测量影响因素分析

管道粗糙度和流体黏度对流量测量有一定影响,为校准流量并分析其影响因素,运用FLUENT仿真软件对管道粗糙度、流体黏度进行模拟.建立粗糙度-平均流速、黏度-平均流速模型,搭建实验平台,验证模型建立的准确性,即外置U形连通管结合高精度激光测距仪精确测量管道内流体液位高度,管道上方通气管结合流速仪精确测量管道内流体平均流速,...     

Transient response analysis and modeling of near wall flow conditions in a micro channel: evidence of slip flow

An experimental tool for determination of the near wall transport parameters in a micro channel, supported by flow simulation, is presented. The method is based on the transient flow response due to convective diffusion, in absence of specific adsorption. An approximately step-function type temporal solute concentration variation serves as the input signal. The associated response signal of a surface plasmon resonance sensor, acting as an integral part of a micro channel, has been taken as the output signal. It provides the flow-dependent change of the NaOH solute concentration in the channel within the optical detection and near wall distance interval 0 < d < 0.5 μm. The temporal signal evolution and response time, until an initially plain aqueous solution is replaced by the solute, varies inversely with solute concentration and flow rate. In the asymptotic limits, the near wall forced convective and diffusive channel transit times, along with the associated velocities, can be extracted and separated. A low convective near wall flow speed would account for 100% adsorption efficiency. The validity of the scaling relation for Fickian diffusive transport has been confirmed by experiments. Convective near wall flow reveals a distorted parabolic flow profile. This indicates relaxation of the no-slip condition, and presence of slip flow. Neither boundary layer formation, nor near wall micro turbulences have been observed. Eventually, a compact mathematical transient flow model, outlined in the Laplace domain for the electrical equivalent analogue circuit and applicable to the convective diffusion equation, has been developed for the flow transients.     

自适应变步长高斯混合模型的工业烟尘目标分割方法

工业烟尘排放时的烟气黑度自动监测对提高环保质量和指导生产过程具有重要的应用价值, 针对传统的 高斯混合模型在进行背景建模时, 参数是在固定帧值的基础上进行参数更新, 导致烟尘检测不准确等问题, 提出一 种自适应变步长高斯混合模型的工业烟尘图像分割方法. 根据烟尘变化速度不均匀的特点, 通过分析检测出烟尘 与实际烟尘的检出率和检准率的和的最大值, 计算熵值差变化率对应的最佳步长, 得到熵值差变化率与最佳步长的 模型. 以熵值差变化率为依据, 确定最佳步长, 得到一个关于熵值差变化率与最佳步长的模型. 以熵值差变化率为 输入, 以最佳步长为输出, 在广义回归神经网络(GRNN)得到适用于本文工业烟尘图像分割的网络模型. 最后, 在多 个场景的烟尘视频中进行分割实验, 结果表明, 本文中方法能够有效的分割出视频中烟尘区域, 且具有一定的适用 性.     

基于流的P2P网络特性模型

利用从实际网络获得的数据,提出基于流的P2P网络特性模型。采用图形方法和概述统计识别样本所服从的分布族,使用可视化图形方法和假设检验方法对统计分布模型进行拟合优度检验。分析结果表明,流持续时间的分布模型可以用对数正态分布精确表示,混合对数正态分布可以有效拟合流长和流传输速率分布的分布模型,且P2P应用的流长和流持续时间没有高度相关的关系。     

Numerical study of the unsteady flow of non-Newtonian fluid through differently shaped arterial stenoses

The problem of non-Newtonian and nonlinear pulsatile flow through an irregularly stenosed arterial segment is solved numerically where the non-Newtonian rheology of the flowing blood is characterized by the generalized Power-law model where both the shear-thinning and shear-thickening models of the streaming blood are taken into account. The combined influence of an asymmetric shape and surface irregularities (roughness) of the constriction has been explored in a study of blood flow with 48% areal occlusion. The vascular wall deformability is taken to be anisotropic, linear, viscoelastic, incompressible circular cylindrical membrane shell. The effect of the surrounding connective tissues on the motion of the arterial wall is also paid due attention. Results are obtained for a smooth stenosis model and also for a stenosis model represented by the cosine curve. The present analytical treatment has the potential to calculate the rate of flow, the resistive impedance and the wall shear stress without excessive computational complexity by exploiting the appropriate physiologically realistic prescribed conditions in nonuniform nonstaggered grids, and to estimate the effects of surface roughness as well as asymmetry of stenosis shape for both shear-thinning and shear-thickening models of Power-law fluid, representing the streaming blood through graphical representations in order to validate the applicability of the present improved mathematical model.     

基于改进的CNN语音识别研究

针对卷积神经网络进行语音识别时识别率较低的问题,结合序列的最大子序列理论,把真实数据和预测数据看作两个序列并计算两者的最大子序列,再使用欧氏距离计算MSLoss损失函数.使用闵氏距离和神经网络反向更新时的参数,提出自适应卷积核ACKS算法,根据网络传播情况动态地改变卷积核大小,改善模型在不同阶段对数据特性的提取效果.设...     

基于狭缝文丘里管的气液两相流测量

提出了一种新的气液两相流测量系统-狭缝文丘里气液两相流测量系统.理论分析表明,狭缝文丘里管利用对称结构可以减小或消除摩阻压降的影响,中间狭缝处垂直于水平流向的重位压降的测量同样避免了沿程摩擦阻力的影响.提出了基于狭缝文丘里测量系统的气液两相流非分离测量方案,并进行了实验研究.利用狭缝文丘里重位压降信号在三类流动下的特性,可以直接识别流型,在不同的流型下用相应的测量模型求解气液两相的流量.结果表明该方法是可行的.     

Experimental study on hydrodynamic effect of orientation micro-pored surfaces

The orientation of the dimple increases the flow distance in the dimple and produces fluid cumulative effect in the dimple length direction, which leads to obvious hydrodynamic effect as a result. In order to investigate the hydrodynamic effect of orientation dimples, a series of experiments was carried out on a ring-on-ring test. Multi-pored faces were tested with different dimple inclination angles and slender ratios. Film thickness and frictional torque were measured under different conditions of load an...