液氢加注系统低温管道中的两相流仿真与分析

在液氢加注输送过程中,由于其具有低温和高压的特性,极易产生气液两相流,而使管道发生过压故障.因此,对液氢管道的仿真研究有着重要作用.文中对裸态和防护后的液氢管道进行建模计算,并通过AMESim软件的两相流库对氢物理属性和管道模型进行仿真分析,然后对系统的对液氢输送管道进行了应用改进与分析.仿真结果表明:液氢在裸管道中输...     

Magnetic resonance velocity imaging of liquid and gas two-phase flow in packed beds

Single-phase liquid flow in porous media such as bead packs and model fixed bed reactors has been well studied by MRI. To some extent this early work represents the necessary preliminary research to address the more challenging problem of two-phase flow of gas and liquid within these systems. In this paper, we present images of both the gas and liquid velocities during stable liquid–gas flow of water and SF₆ within a packing of 5 mm spheres contained within columns of diameter 40 and 27 mm; images being acquired using ¹H and ¹⁹F observation for the water and SF₆, respectively. Liquid and gas flow rates calculated from the velocity images are in agreement with macroscopic flow rate measurements to within 7% and 5%, respectively. In addition to the information obtained directly from these images, the ability to measure liquid and gas flow fields within the same sample environment will enable us to explore the validity of assumptions used in numerical modelling of two-phase flows.     

Effect of a uniform magnetic field on dielectric two-phase bubbly flows using the level set method

In this study, the behavior of a single bubble in a dielectric viscous fluid under a uniform magnetic field has been simulated numerically using the Level Set method in two-phase bubbly flow. The two-phase bubbly flow was considered to be laminar and homogeneous. Deformation of the bubble was considered to be due to buoyancy and magnetic forces induced from the external applied magnetic field. A computer code was developed to solve the problem using the flow field, the interface of two phases, and the magnetic field. The Finite Volume method was applied using the SIMPLE algorithm to discretize the governing equations. Using this algorithm enables us to calculate the pressure parameter, which has been eliminated by previous researchers because of the complexity of the two-phase flow. The finite difference method was used to solve the magnetic field equation. The results outlined in the present study agree well with the existing experimental data and numerical results. These results show that the magnetic field affects and controls the shape, size, velocity, and location of the bubble.     

小管径气液两相流空隙率波传播的多尺度相关性

空隙率波是气液两相流系统的特殊物理现象,理解空隙率波的传播特性对揭示两相流流型转变与流速测量物理机理具有重要意义.本文首先考察了典型非线性系统的多尺度互相关特性,发现去趋势互相关分析方法可有效揭示系统的多尺度非线性动力学特征;然后,通过采集垂直上升小管径气液两相流电导传感器阵列上下游空隙率波动数据,提出采用多尺度去趋势互相关分析方法探测空隙率波传播的多尺度互相关特性,并提取了低尺度空隙率波互相关水平增长率;另外,通过计算空隙率波空间衰减因子,考察了气液两相流空隙率波传播的结构不稳定行为.结果表明,空隙率波结构的多尺度互相关特性与其空间衰减特性具有较好的物理关联性:对于气液两相流过渡流型,低尺度空隙率波互相关水平增长率较高,且与较为稳定的空隙率波传播特性相对应;而当气液两相流空隙率波明显衰减或放大时,空隙率波互相关水平增长速率一般较低.     

A comparison in a back-bead prediction of gas metal arc welding using multiple regression analysis and artificial neural network

This research was done on the basis of prediction that there is a relationship between welding parameters and geometry of the back-bead in arc welding which is a gap. Multiple regression analysis and artificial neural network were used as methods for predicting the geometry of the back-bead. The multiple regression analysis and the artificial neural network were formed, and the analysis data or verification data which were used in the formation process of the multiple regression, and the training data or test data which were used in the formation process of the artificial neural network, were used to perform the prediction of the back-bead. Through this research, it was found that the error rate predicted by the artificial neural network was smaller than that predicted by the multiple regression analysis, in terms of the width and depth of the back-bead. It was also found that between the two predictions, the prediction of the width of the back-bead was superior to the prediction of the depth in both methods.     

竖直圆管内液氮流动沸腾流动压降的分析

文中对竖直圆管内液氮流动沸腾压降进行实验研究,分析热流密度、质量流量对液氮两相流动摩擦压降的影响以及热流密度对测试段总压降的影响.在本实验工况范围内,两相流摩擦压降随着热流密度和质量流速的增加而变大,且测试段总压降随着热流密度的增加而降低.分别利用均相模型、L-M模型和Chisholm B系数模型对实验结果进行预测,并比较了预测值与实验值,结果表明本实验工况下均相模型预测效果最好.     

The stabilization effect of the density difference in the modified lattice hydrodynamic model of traffic flow

A modified lattice hydrodynamic model of traffic flow is proposed by introducing the density difference between the leading and the following lattice. The stability condition of the modified model is obtained through the linear stability analysis. The results show that considering the density difference leads to the stabilization of the system. The Burgers equation and mKdV equation are derived to describe the density waves in the stable and unstable regions respectively. Numerical simulations show that considering the density difference not only could stabilize traffic flow but also makes the lattice hydrodynamic model more realistic.     

Simultaneous measurement of bubble size,velocity and void fraction in two‐phase bubbly flows with time‐resolved X‐ray imaging

Key parameters of two‐phase flows, such as void fraction and microscale bubble size, shape and velocity, were simultaneously measured using time‐resolved X‐ray imaging. X‐ray phase‐contrast imaging was employed to obtain those parameters on microbubbles. The void fraction was estimated from X‐ray absorption. The radii of the measured microbubbles were mostly smaller than 20 µm, and the maximum velocity was 39.442 mm s^?1, much higher than that in previous studies. The spatial variations of the void fraction were consecutively obtained with a small time interval. This technique would be useful in the experimental analysis of bubbly flows in which microbubbles move at high speed.     

虫草氨基酸的人工神经网络-近红外光谱快速测定方法

提出了用近红外漫反射光谱技术快速检测发酵冬虫夏草中氨基酸含量的新方法。采用比色法测定虫草菌粉中氨基酸含量。用BP神经网络建立了近红外光谱数据与氨基酸、精氨酸和总氨酸含量间的定量关联模型。通过比较不同的光谱预处理方法及光谱范围, 得到最优模型,即在7 501.7～6 097.8,5 453.7～4 246.5 cm-1区域内,近红外光谱的一阶微分光谱与其氨基酸含量之间建立模型。甘氨酸、精氨酸和总氨基酸的预测标准偏差分别为0.08,0.07和0.36,均优于主成分回归(PCR)和偏最小二乘回归(PLS)等线性模型的处理结果。结果表明,该方法是一种有效实用的非线性校正方法。为近红外光谱快速测定中药组分含量提供了一条新途径。     

Plasticity-induced characteristic changes of pattern dynamics and the related phase transitions in small-world neuronal networks

Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.