基于HHT的两相流动态信号提取与滤波的研究

为了去除气液两相流差压信号中的噪声成分,并提取差压波动信号,提出了一种基于Hilbert-Huang Transform(HHT)的气液两相流信号处理方法.对不同流型下的差压信号进行固有模态分解,分析不同模态的边际谱,利用HHT的多尺度滤波特性除去噪声,进一步得到差压波动信号.实验结果表明,该方法可以有效去除高频噪声,得到的差压波动信号又很好地保持了信号的局部特性.该方法原理简练、物理意义明确,是处理非线性信号的优良方法.     

基于环形管差压波动信号测量气液两相流气相含率的研究

设计了一种新型多圈环形管用于气液两相流参数的测量,对环形管上升段水平方向内外侧差压波动信号进行了分析,采用无因次分析方法获得与差压波动信号均方根相关的特征量,建立了此特征量与容积含气率的关系模型,并在此基础上进行了实验.实验结果表明与差压波动信号均方根有关的特征量和容积含气率存在一定的关系,在考虑到气体密度的影响之后,引入气体密度对关系模型进行修正,建立了差压波动信号均方根和容积含气率量纲1的线性关系模型.在容积含气率小于0.65时,气液两相流的容积含气率测量误差小于5%,为气液两相流的容积含气率测量提供了一种方法.     

泡罩塔板上差压波动信号的R/S分析

采用域重新标度(R/S)分析方法研究了泡罩塔板上的差压波动信号,得出泡罩塔板上差压波动信号的Hurst指数在0.33～0.49之间,<0.5说明差压波动信号具有“反持久性”。发现泡罩塔板上不同操作条件下,差压波动信号分形维数变化范围为1.51～1.67,且不同气液两相流型分形维数D存在差异:喷溅流型1.50相似文献   

基于文丘里流量传感器的湿气两相流量模型研究

研究旨在通过计算流体动力学(CFD)仿真技术预测的湿气气、液两相流量.以双差压长喉颈文丘里流量传感器为测量手段.模拟压力范围0.4,0.6,0.8,1.0,1.2 MPa,气相体积流量范围为140～283 m3/h,温度范围23 ～30℃,含液率范围0.5％～1.5％.文丘里流量传感器口径为DN100,节流比为0.55.多相流模型采用离散相模型(DPM),利用欧拉壁面(EWF)模型以模拟管壁上的薄液膜.分析得出压力、气相流速和液相体积含率(LVF)对液膜厚度的影响规律.根据仿真结果建立基于双差压比值法的气、液两相流量预测模型.将仿真值与实验值进行比较,气相流量模型预测的均方根误差为1.8％,且液相流量模型预测的均方根误差为6.1％.     

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。     

控压钻井井下气侵工况的自适应参数及状态估计

针对控压钻井过程中井下可能发生气侵的特殊工况,提出一种可在异常工况下估计井底压力,并借此判断异常工况的方法.首先,基于简化的漂移通量模型,在传统控压钻井水力学模型中添加气体膨胀项,建立控压钻井气液两相流模型;其次,将井下环空摩擦积分和井底气侵量视为未知参数,将井底流量视为未知状态,设计一种可对未知参数以及未知状态进行联合估计的自适应观测器,并以此为基础估计井底压力;最后,通过仿真实验验证所提方法的有效性.仿真结果表明,所建气液两相流模型可在井下发生气侵时模拟井底压力变化,且所提观测器能实时准确地跟踪井底流量及压力变化.     

LV型气体流量计

在工业管道上测量气体时,特别在高温、高压工况下,一般都用孔板流量计.不锈钢制成的孔板,其结构简单,制造和使用都方便,在一些不太清洁的气体管道上能长期使用.按规定在孔板二侧的取压孔上分别取出压力,与差压计(变送器)相连接,根据此差压的开方值计算出流量.一般情况下,气体通过孔板孔径的流速都处在亚临界流状态,此时在工况下的流量与各种可变参量相互都有影响,要得到准确的流量值不得不考虑这些参量,这些量的补偿就比较麻烦,用一般仪表不能很好解决.     

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.     

基于小波神经网络的气液两相流流型识别方法

为了克服传统流型识别方法的特点,采用小波分解和RBF神经网络技术来实现气液两相流流型的智能识别。首先测量了水平管内气液两相流的差压波动信号,其次应用小波分解对流型的动态差压波动信号进行了分析并提取流型特征,最后将小波能量特征作为RBF神经网络的输入,从而实现对流型的智能识别。仿真结果表明:该方法能够较好地识别出4种流型,从而为流型的在线识别提供了一种定量的流型识别方法。     

基于槽式孔板与神经网络的湿气流量计

在研究某湿气流量计样机的基础上,提出了一种应用槽式孔板与神经网络技术实现湿气流量计量的方法.简要介绍了槽式孔板的特点及流量计样机的结构,采用统计分析与相关分析相结合的方法对信号特征量进行筛选,并应用神经网络技术对数据处理、构建二级神经网络系统.此设计实现了流型识别和计量,利用网络集成技术进一步提高网络系统的计量精度和泛化能力.现场测试结果表明,应用该流量计进行湿气流量计量,其气相累积流量计量误差为3%,液相累积流量计量误差为6%,满足了生产计量的精度要求.     

Stochastic mixed multiscale finite element methods and their applications in random porous media

We present a framework for stochastic mixed multiscale finite element methods (mixed MsFEMs) for elliptic equations with heterogeneous random coefficients. The use of some global information is necessary in multiscale simulations when there is no scale separation for the heterogeneity. The methods in the proposed framework for the stochastic mixed MsFEMs use some global information. The media properties in a stochastic environment drastically vary among realizations and, thus, many global fields are needed for multiscale simulation. The computations of these global fields on a fine grid can be very expensive. One can utilize upscaling methods to compute the global information on an intermediate coarse grid that reduces the computational cost. We investigate two approaches of stochastic mixed MsFEMs in the framework. First approach entails no stochastic interpolation and the second approach uses stochastic interpolation. If the random media have deterministic features that play significant roles in the flow, we can use the deterministic features of the random media as the global information. This reduces the computational cost of the simulations. We make convergence analysis of the stochastic mixed MsFEMs and investigate their applications to incompressible two-phase flows in random porous media. The numerical results demonstrate the effectiveness of the proposed methods and confirm the convergence.     

气固两相流模拟的随机离散模型

§1.引言 气固两相流动形式是最复杂的两相流动实例,其系统中的颗粒浓度较高,颗粒间的碰撞经常发生,从而导致细观层次上的颗粒运动具有复杂性,对于两相流动系统,拟流体模型以其大规模模拟的可行性在数值模拟领域中居重要地位。但是,拟流体模型的连续性假设     

气液两相流电导传感器测量波动信号的Wigner-Ville分析

流型是两相流中非常重要的流动参量,不同流型下的两相流流动特性及传热传质性能有很大不同。流型也严重影响着两相流参数测量的准确性。利用新近研制的两相流电导传感器,在垂直上升气液两相流管中采集了不同流型下的电导波动信号,采用W igner-V ille分布(WVD)在时频域内处理了电导波动信号,观察到了WVD特征与流型之间的关系,取得了较好的气液两相流流型辨识效果。     

Exact and approximate Riemann solvers for compressible two-phase flows

Numerical methods for solving equations of two-phase hydrodynamics, which describe the flow of a dispersed solid and gas mixture are considered. The Godunov method is applied as the main approach to approximate numerical fluxes in solutions of the relevant Riemann problems. The formulations of these problems for the solid and gas phases are given, their exact analytical solution is described, and possible simplified approximate solutions are discussed. The obtained theoretical results are applied to the construction of a discrete model, which results in the generalization of the well-known Godunov-type and Rusanov-type methods to the case of nonequilibrium two-phase media. The numerical results involve the verification of the constructed methods on the analytical solutions of two-phase equations.     

Forecasting air passenger traffic flow based on the two-phase learning model

The future airports will head toward a highly intelligent direction, like the unmanned check-in services, while the scale and resources allocation of the ground service are tightly related to the air passenger flow. Therefore, forecasting passenger flow accurately will affect the development of future airports and the optimization of service of civil airlines significantly. As a kind of time series, air passenger flow is influenced by multiple factors, particularly, the stochastic part of seasonality, trend and volatility. These will ultimately affect the accuracy of the prediction. Therefore, this paper introduces a prediction model based on a two-phase learning framework. In phase one, various predictors cope with different features of time series in parallel and the prediction results are integrated in phase two. Furthermore, this paper has compared principal error indicators with actual data and results show that the two-phase learning model performs better than current fusion models and owns stable performance.

     

一种气液两相流气相参数图像检测方法

介绍了一种运用图像处理技术检测气液两相流参数的新方法,针对气液两相中气泡目标对比度低的特点,提出先对待处理图像进行分形增强,运用改进的Canny算子检测出气泡目标边缘,在经过填充和标记后检测出两相流图像面积、圆形度、截面含气率等参数,为气液传质效率建模提供了基础;实践证明该方法抗干扰能力强,是一种实用可行的参数检测方法.     

Computational heat transfer and two-phase flow topology in miniature tubes

Detailed computational multi-fluid dynamics simulations have been performed to study the effect of two-phase flow regime on heat transfer in small diameter pipes. Overall the heat removal rate in two-phase flow is higher than in single phase. Subtle differences in thermal removal rates are revealed when the flow-regime transitions from bubbly to slug and slug-train configurations. It is found that the wall thermal layer is affected by two separate mechanisms: an early-stage compression due to gas-jet fragmentation into slugs or bubbles, and a background inclusion-induced flow superimposed on the equivalent single-phase fully developed flow far downstream. The first mechanism resembles a confinement or blockage effect, and is shown to directly influence radial temperature gradients. The downstream mechanism is a cell-based developed flow (rather than fully developed), and is shown here to increase the wall shear in the vicinity of the cell, leading to higher heat transfer rates. The mean Nusselt number distribution shows that the bubbly, slug and slug-train patterns transport as much as three to four times more heat from the tube wall to the bulk flow than pure water flow. A mechanistic heat transfer model is proposed, based on frequency and length scale of inclusions.     

基于弧状电极传感器的气/水两相流参数测量系统设计

气/水两相流流动参数的检测对工业过程的控制和优化有重要意义,相含率作为一个重要参数直接影响到两相流建模的精度。为测量两相流相含率参数设计了弧状电极电导传感器测量系统,通过对气/水两相流典型流型的物理模拟研究了相含率与测量电压之间的关系。实验结果表明:弧状电极电导传感器的液相相含率与测量电压存在很好的线性关系,为两相流动态实验参数测量提供了依据。     

Two-phase AC electrothermal fluidic pumping in a coplanar asymmetric electrode array

The ability to achieve fast fluid flow yet maintain a relatively low temperature rise is important for AC electrothermal (ACET) micropumping, especially in applications such as bioMEMS and lab-on-a-chip systems. In this paper, we propose a two-phase ACET fluidic micropump using a coplanar asymmetric electrode array. The proposed structure applies a two-phase AC voltage, i.e., voltage of phase 0°/180°, to the narrow electrodes while the wide electrodes are at ground potential. Numerical simulation demonstrates that this simple coplanar electrode configuration can achieve at least 25% faster fluid flow rates than using a single AC signal. By selecting certain design parameters, a two-phase ACET structure can achieve up to 50% faster fluid flow rates than a corresponding single-phase structure. The simple two-phase AC signal sources are easily produced by using inverter buffers, which is a considerable improvement compared to the multi-phase AC signals required by other electrokinetic micropumping methods, such as traveling wave structures.     

Gas�Cliquid flow stability and bubble formation in non-Newtonian fluids in microfluidic flow-focusing devices

This communication describes the gas–liquid two-phase flow patterns and the formation of bubbles in non-Newtonian fluids in microfluidic flow-focusing devices. Experiments were conducted in two different polymethyl methacrylate (PMMA) square microchannels of, respectively, 600 × 600 and 400 × 400 μm. N₂ bubbles were generated in non-Newtonian polyacrylamide (PAAm) solutions of different concentrations. Slug bubble, missile bubble, annular and intermittent flow patterns were observed at the cross-junction by varying gas and liquid flow rates. Gas and liquid flow rates, concentration of PAAm solutions, and channel size were varied to investigate their effect on the mechanism of bubble formation. The bubble size was proportional to the ratio of gas/liquid flow rate for slug bubbles and could be scaled with the ratio of gas/liquid flow rate as a power–law relationship for missile bubbles under wide experimental conditions.