实验研究了螺管内绝热和沸腾汽液两相流动时压力波动特性，分析了热流密度对压力波动的影响规律。结果表明沸腾时波动的均方根和分形参数（分维数、关联维数和Kolmogorov熵）与绝热两相流明显不同，加热热流密度的大小影响各特征参数的大小及其随干度的变化规律。未考虑流密度影响的流型图或流型转变准则只能在小热流密度时使用。

在线识别的关键问题在于如何利用最短时间历程的参数波动过程完成由参数波动的特征空间到流型空间的映射。 CPN神经网络能够对自组织映射的结果进行有导师的训练，因此可以为流型的自动、客观和在线识别提供有效的手段。文中结合压力波动过程的快速傅立叶变换系数，对U形管垂直上升段内空气-水两相流的流型进行自动识别，在线性指标达到了8.2s。对如何提高流型快速识别的在线性指标和识别率等作了相关的探讨。

基于油气水多相流混合物在管道内流动时的多传感器信号——压力和压差信号，建立特定流型的识别规则，采用学习矢量量化模式分类器作为未知流型的分类器，根据数据融合的技术思路获得了油气水多相流的流型在线识别技术。通过系统集成的手段，利用微处理装置研制出了流型识别系统。该识别技术具有置信度高、容错性好、性能稳定、降低了对单个传感器的性能要求等优点。该识别系统结构简单、无运动部件、不改变管道的截面结构，可以处理非快速变化的瞬态流动，测量误差小于10%，并具有连续工作、定时打印、信号输出等功能。

运用现代数字信号处理技术，对垂直上升管水/水蒸气两相流不同流型时的压美波动信号特性进行了分析研究，提出了基于压差波动特征的两相流型的客观识别方法。通过提取压差波动信号的功率谱分布特征，表明利用功率谱随频率的分布特性的均方根可客观识别的泡状流、间歇流和环状流。

从理想的单气泡运动物理模型和离散正交小波与统计相结合的信号处理技术研究了泡状流压力波动的机理与多尺度的频规律，得到以下结论：泡状流的压力波动主要来源于气泡的运动和诱导湍及液相湍流，其中在低流速下前者产生的压力波动幅度大于后两者；存在一个临界频率，低于该频率压力信号均方根随频率的增加面增加，高于该频率压力信号均方根随频率的增加而减少；发生流型转变时压力信号的时频特征发生明显改变，最大均方根出现在更低的频率区。

An experiment has been conducted in detail to study the turbulent heat transfer in horizontal helically coiled tubes over a wide range of experimental parameters. We found that the enhancement of heat transfer in the coils results from the effects of turbulent and secondary flows. With Reynolds number increasing to a high level, the contribution of the secondary flow becomes less to enhance heat transfer, and the average heat transfer coefficient of the coil is closer to that in straight tubes under the same conditions. The local heat transfer coefficients are not evenly distributed along both the tube axis and the periphery on the cross section. The local heat transfer coefficients on the outside are three or four times those on the inside, which is half of the average heat transfer. A correlation is proposed to describe the distribution of the heat transfer coefficients at a cross section. The average cross-section heat transfer coefficients are distributed along the tube axis. The average value at the outlet section should not be taken as the average heat transfer coefficient.

With the development of supercritical fluids technology, more and more attention is being paid to the study of flow and heat transfer under supercritical conditions. In order to better understand the influence of gravity on the flow and heat transfer of supercritical fluids, with the CFD software FLUENT 6.0, a numerical study has been conducted for the developing laminar flow and heat transfer of water in a smooth vertical tube under supercritical pressure. The flow and heat transfer have been studied with the inlet Reynolds number ranging from 500 to 2000, Grashof number er ranging from1

In the present investigation, both pressure fluctuations and differential pressure signals were measured for oil-gas-water multiphase piping flow in wide ranges of flow parameters in horizontal pipe. The signal features were extracted and analyzed, which included time domain features, frequency domain features and fractal features. Both liquid velocity and oil fraction have tremendous influence on the feature analysis, which all the feature have bad clustering and bad separability for the same flow pattern or different flow pattern respectively. It is proved that the recognition methods, RMS of the pressure, PDF or PSD of differential pressure fluctuation, are not able to be employed widely in the industrial applications. The pressure fluctuations exhibit chaotic characters and are influenced by flow patterns. The regulations to identify the special flow pattern are obtained basing on the joint feature analysis. The online intelligent recognition of flow patterns is proposed which is a fusion method combining the special regulations and the pattern recognition. The proposed method was examined in the oil-gas-water loop and the results showed that bubble flow, stratified flow, intermittent flow and annular flow could be identified with more than 90% accuracy.

A simple method is developed in this paper to solve two-dimensional nonlinear steady inverse heat conduction problems. The unknown boundary conditions can be numerically obtained by using the iteration and modification method. The effect of measurement errors of the wall temperature on the algorithm is numerically tested. The results prove that this method has the advantages of fast convergence, high precision, and good stability. The method is successfully applied to estimate the convective heat transfer coefficient in the case of a fluid flowing in an electrically heated helically coiled tube

Byu singa ne nsemble-avem gedt wo-fluid model, with validc losurec onditionso fin terfacialtu omenturne xchanged uet ovirtual mass force, visco us shears tressand dragf orce, amodelfo rp ressurew avep ropagation in a horizontal gas-liquid bubbly flow is proposed. Accordingt ot hes mallp erturbationt heorya nds olvablec onditiono fo eorderlinearu niform equations, ad spersione quationo fpressurew aveis in duced. The pressue wave speedc alculatedf rom the modelis compare danding oods greem entwithe xistingdata. According to the dispersion equation, the propagation and attenuation of pressure wave are investigated systemicaly. The factors affecting pressure wave, sucha sv oidf raction, pressure, wallsh ears tress, perturbationf requency, virtualm ass for ceandd ragforce, are analyzed. The result shows that the decrease in system pmmare, the increase in void fraction and the existence of wall shear stress, will cause a decre inp ressurew avesp eeda nda nIn eressein the a tenuationc oefficientin the horizontalga s-liquidb ubblyflow. Thee ffectso fp erturbstion frequency, virtual mess and drag force on pressure wave in the horizontal gas-liquid bubbly flow at low perturbation frequency are different from that at high perturbation frequency.