Detection of Multiple Blockages in Parallelized Microreactors

In a plant consisting of parallelized microreactors (MRs), the product quality is lowered because of a lack of flow uniformity among them when blockage occurs. It is not practical to install sensors in every MR from the viewpoint of cost when detecting the blocked MRs. In the previous study, the multiple blockage detection (MBD) method using a small number of sensors was proposed, but its performance became low when the number of sensors decreased. Here, the conventional algorithm for MBD is improved by considering the process behavior on blockage occurrence, and the effectiveness of the improved algorithm is demonstrated through a numerical case study. The effects of flow distributor types and sensor types on the MBD performance are numerically investigated.     

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.     

Development and validation of a micro-fin tubes evaporator model using R134a and R1234yf as working fluids

This paper presents a model of shell and tube evaporator with micro-fin tubes using R1234yf and R134a. The model developed for this evaporator uses the ε-NTU method to predict the evaporating pressure, the refrigerant outlet enthalpy and the outlet temperature of the secondary fluid. The model accuracy is evaluated using different two-phase flow boiling correlations for micro-fin tubes and comparing predicted and experimental data. The experimental tests were carried out for a wide range of operating conditions using R134a and R1234yf as working fluids. The predicted parameter with maximum deviations, between the predicted and experimental data, is the evaporating pressure. The correlation of Akhavan– Behabadi et al. was used to predict flow boiling heat transfer, with an error on cooling capacity prediction below 5%. Simulations, carried out with this validated model, show that the overall heat transfer coefficient of R1234yf has a maximum decrease of 10% compared with R134a.     

Models for solar radiation prediction based on different measurement sites

The modeling of solar radiation for forecasting its availability is a key tool for managing photovoltaic (PV) plants and, hence, is of primary importance for energy production in a smart grid scenario. However, the variability of the weather phenomena is an unavoidable obstacle in the prediction of the energy produced by the solar radiation conversion. The use of the data collected in the past can be useful to capture the daily and seasonal variability, while measurement of the recent past can be exploited to provide a short term prediction. It is well known that a good measurement of the solar radiation requires not only a high class radiometer, but also a correct management of the instrument. In order to reduce the cost related to the management of the monitoring apparatus, a solution could be to evaluate the PV plant performance using data collected by public weather station installed near the plant. In this paper, two experiments are conducted. In the first, the plausibility of the short term prediction of the solar radiation, based on data collected in the near past on the same site is investigated. In the second experiment, the same prediction is operated using data collected by a public weather station located at ten kilometers from the solar plant. Several prediction techniques belonging from both computational intelligence and statistical fields have been challenged in this task. In particular, Support Vector Machine for Regression, Extreme Learning Machine and Autoregressive models have been used and compared with the persistence and the k-NN predictors. The prediction accuracy achieved in the two experimental conditions are then compared and the results are discussed.     

Flow pattern identification and measurement techniques in gas-liquid-liquid three-phase flow: A review

The simultaneous flow of gas, oil, and water forms various flow patterns due to the complex interfacial relationships. Three-phase flow patterns are classified as the gas-liquid and liquid-liquid flow patterns. Pressure drop, void fraction, liquid holdup, and phase distribution are important characteristics of the three-phase flow. These characteristics are generally associated with the three-phase flow patterns. Hence, the knowledge about flow patterns can help to predict the overall behavior of the three-phase flow. Studies have been conducted to identify three-phase flow pattern and their characteristics at various superficial velocities of gas, oil, and water. The major purpose of the studies is to gather information about the three-phase co-current flow and use it for improvement of the efficiency of the flow systems. Therefore, the accuracy of the measurement technique is critical. Several types of flow pattern identification and measurement techniques have been developed to improve accuracy and provide high-quality results. In this article, classical and advanced techniques used for the three-phase flow identification and measurement have been reviewed. The survey will help the researchers working in the area of multiphase flow to choose the right technique based on the objectives of the studies.     

Design and Fabrication of Concentration‐Gradient Generators with Two and Three Inlets in Microfluidic Chips

A simple and low‐cost method for designing and fabricating concentration‐gradient generators with two and three inlets is proposed which can generate different concentration gradients at varying flow velocities. The microchannel structure was designed in S‐shape and left‐right symmetry. The concentration‐gradient generator was simulated based on the finite element method. The microchannels were processed on a computer numerical control (CNC) engraving and milling machine on poly(methylmethacrylate) substrate, and then two concentration‐gradient generators were fabricated by hot bonding technology. The results of experiment and simulation were compared to prove the feasibility of the method. Flow velocity was an important factor for generating different concentration gradients. The concentration‐gradient profiles of the generators with two and three inlets present approximately linear and quadratic curves.     

基于感知评价的Internet语音终端流量控制

分析了影响因特网语音通信质量的主要因素，根据实时传输控制协议计算延迟、丢包率等网络参数，并利用RBF神经网络将参数映射为语音质量评分，根据评分值的变化动态地调整语音终端的编码速率，在保证一定语音质量的同时，缓解网络拥塞。实验证明了该方法的有效性。     

基于射频技术的无刷同步电机励磁电流的检测

无刷同步电机的励磁系统对励磁电流的测量是制约该励磁方式发展的一大障碍。设计了一个射频系统可以用来解决同步电机的励磁电流的测量问题。该系统可以方便地检测到同步电机励磁机的整流二极管的工作状态并且可以动态地显示励磁电流，极大地方便了运行人员做出判断，而且结构简单、方便实用。     

Flow Reaction Forces upon Blowdown of Safety Valves

The activation of safety valves causes the development of flow reaction forces that have to be transferred in an adequate way via the piping to the steel structure or via the connected vessel into the foundation. If the safety valve outlet piping is connected to a blowdown system or, in case of blowing off into the atmosphere, are equipped with a T‐piece at the outlet, the stationary reaction forces are compensated completely. The transient opening process, however, develops flow reaction forces which culminate in peaks of short duration. In this article, a simple method will be proposed for the estimation of the resulting reaction forces as a function of the length of the pipe at the safety valve outlet. CFD calculations and blowdown tests executed with a full‐lift safety valve have confirmed this method on principle. Special importance is attributed to the short duration of the effect of the reaction forces which seems to have only a negligible impact on the supporting steel structure.