Flow state monitoring of gas-water two-phase flow using multi-Gaussian mixture model based on canonical variate analysis

As a highly complex and time-varying process, gas-water two-phase flow is commonly encountered in industries. It has a variety of typical flow states and transition flow states. Accurate identification and monitoring of flow states is not only beneficial to further study of two-phase flow but also helpful for stable operation and economic efficiency of process industry. Combining canonical variate analysis (CVA) and Gaussian mixture model (GMM), a strategy called multi-CVA-GMM is proposed for flow state monitoring in gas-water two-phase flow. CVA is used to extract flow state features from the perspective of correlation between historical data and future data, which solves the cross correlation and temporal correlation of multi-sensor measurement data. GMM calculates the possibility that the current flow state belongs to each typical flow pattern and judges the current flow state by probability indicators. It is conducive to follow-up use of Bayesian inference probability and Mahalanobis distance-based (BID) indicator for flow state monitoring, which avoids repeated traversal of multiple CVA-GMM models and improves the efficiency of the monitoring process. The probability indicators can also be used to analyze transition flow states. The method combining the probabilistic idea of GMM with the deterministic idea of multimodal modeling can accurately identify the current flow state and effectively monitor the evolution of flow state. The multi-CVA-GMM method is validated by using the measured data of the horizontal flow loop of gas-water two-phase flow experimental facility, and its effectiveness is proved.     

高熔体流动速率薄壁注塑聚丙烯专用料的结构与性能分析

采用多种分析测试方法，对3类高熔体流动速率薄壁注塑聚丙烯（PP）专用料的熔融结晶性能、光学性能、分子量分布、力学性能、毛细管流变性能、热收缩性能进行了分析研究。结果表明，K1860与2种市售主流PP1、PP2各项性能相当，其中K1860分子量分布相对PP1、PP2较窄，弯曲性能、拉伸性能更优，可满足大型薄壁注塑制品的生产要求。     

Flow regime recognition in a long pipeline-riser system based on signals at the top of the riser

To identify conveniently multiphase flow regimes in subsea pipeline-risers, we study in this paper experimentally two-phase flows in a 1657 m long pipeline with an S-shaped riser to simulate field experiment, within a wide range of gas and liquid velocities. Three flow regimes, namely severe slugging, transitional flows, and stable flows, are analyzed based on three differential pressure and one pressure signals at the top of the riser; comparatively speaking, the positions of these signals in the experimental system are similar to those of the sea level signals in industrial fields, which are easy and less expensive to obtain. The obtained signals are decomposed into six scales via a multi-scale wavelet analysis, and further four statistical parameters on each scale are extracted, including mean values, standard deviations, ranges, and mean values of absolute. We compared the effects of six SVM classifiers with different kernel functions on the recognition rate of flow regimes, and it is found the recognition rates of SVM classifier with quadratic and cubic kernel functions are the highest. Further, the principal component analysis is employed to reduce the dimension of statistical parameters and it indicates that the recognition rate tends to increase with the rising number of principal components from 1 to 6, and it remains constant if the principal component number is further increased. Moreover, The results suggest that the recognition rate obtained from the pressure difference between the top of the riser and the separator peaks, and then it comes that from the pressure signal at the top of the riser, and that for the pressure difference signal at the top of the riser is the least satisfying one. As for the optimal differential pressure signals between the top of the riser and the separator, the results show that the recognition rate increases rapidly from 70.2% to 90.4% when the sample duration rising from 2.3 s to 18.6 s, and when the sample duration exceeds 74.4 s, the recognition rate exceeds 92.9% and remains unchanged.     

Computational modelling of water flow inside laboratory Knelson concentrator bowl

Enhanced gravity concentrators such as Knelson concentrator (KC) are extensively used in the mineral processing industry. The complexities of KC bowl geometry and variation of feed characteristics have forced process engineers to design empirically new units using laboratory and pilot-scale Knelson concentrators. However, numerical modelling methods such as computational fluid dynamics (CFD) and discrete element method (DEM) provide a better insight of flow behaviour of fluid and particulate solid phases inside these processing units. This article reports findings of CFD simulations for single-phase water flow inside the laboratory KC. An available standard 7.5-cm laboratory KC bowl was numerically simulated using realisable k-ε turbulence model to resolve the turbulence dispersion of existing transitional flow regime. The effects of relative centrifugal force (RCF) intensity and bed fluidisation water flow rate on the water velocity and pressure distributions were studied. Simulations confirmed the swirling flow pattern governing inside the bowl. The results revealed that the impact of RCF intensity on the water field values is greater than that of bed fluidisation water flow rate. Both velocity and pressure variations inside the bowl rings followed a linear trend.     

气瓶内部淬火过程的流动换热特性

 大直径厚壁气瓶内部淬火时的流动换热过程极其复杂，受到多种因素的影响，而研究气瓶内部压强和温度的变化规律对改善流动换热效果、提高产品组织性能具有重要的理论指导意义。以914 mm厚壁气瓶和瓶内流体为研究对象，建立了二维等效流 固耦合模型；采用多喷嘴系统对气瓶内外进行喷水淬火，研究了气瓶总长、喷水流速及淬火时间对瓶内压强及内壁温度的影响，通过间歇淬火试验验证了数学模型的正确性。结果发现，气瓶长度对瓶内压强和瓶壁温度的影响显著，喷水流速次之，当喷水流速大于8 m/s后，水量对瓶壁的冷却效果大大降低；气瓶内壁长度方向的温度梯度分别随气瓶总长的增加和淬火时间的延长而减小，但基本不受喷水量的影响。     

Mathematical model for coal conversion in supercritical water: reacting multiphase flow with conjugate heat transfer

Providing heat for supercritical water gasification (SCWG) of coal by coupling subsequent products oxidation in integrated supercritical water reactor (ISWR) provides an effective method for directional control of temperature field and avoids excessive hot spots caused by uniform heating. An exploratory numerical model incorporating particle-fluid flow dynamics, multispecies transport and thermal coupling between endothermic coal gasification and exothermic product oxidation was established to simulate the reacting multiphase flow process of coal conversion in a novel lab-scale ISWR. An eleven-lump kinetic model was proposed for the prediction of chemical reactions. And the thermal coupling relationship was described by conjugate heat transfer boundary conditions (BC). Detailed physical and chemical field distribution in ISWR were analyzed and influence factors were discussed. The results showed that oxidation of gas products as inner heat source could promote the gasification reaction with only slight or even little maximum temperature increase of the pressure-bearing wall. Coal feeding rate and oxygen supply method significantly affected the field distribution. The multi-injection compressed-air supply method provided a more uniform temperature field but would reduce heat transfer temperature difference. The carbon gasification efficiency (CGE) in the gasification zone could easily reach up to 97% under mild conditions (less than 650 °C).     

基于概要数据结构的全网络持续流检测方法

持续流是隐蔽的网络攻击过程中显现的一种重要特征，它不产生大量流量且在较长周期内有规律地发生，给传统的检测方法带来极大挑战。针对网络攻击的隐蔽性、单监测点的重负荷和信息有限的问题，提出全网络持续流检测方法。首先，设计一种概要数据结构，并将其部署在每个监测点；其次，当网络流到达监测点时，提取流的概要信息并更新概要数据结构的一位；然后，在测量周期结束时，主监测点将来自其他监测点的概要信息进行综合；最后，提出流持续性的近似估计，通过一些简单计算为每个流构建一个位向量，利用概率统计方法估计流持续性，使用修正后的持续性估计检测持续流。通过真实的网络流量进行实验，结果表明，与长持续时间流检测算法（TLF）相比，所提方法的准确性提高了50%，误报率和漏报率分别降低了22%和20%，说明全网络持续流检测方法能够有效监测高速网络流量。     

基于OpenFOAM的过冷流动沸腾数值模拟

过冷流动沸腾现象被广泛应用于工业生产和动力系统中，对该现象的准确预测是两相流CFD模拟的重要研究方向。本文详细阐述了该模拟过程中的欧拉两流体模型及相关辅助模型，基于开源CFD平台OpenFOAM，模拟了4.5 MPa下竖直圆管内的过冷流动沸腾，得到了截面空泡份额、液相平均温度及壁面温度沿轴向的分布。计算结果与实验值符合良好，说明了模型的有效性和程序的正确性。本文可为在OpenFOAM中添加新的模型及开发新的求解器以模拟过冷流动沸腾问题提供参考。