The Experts below are selected from a list of 135180 Experts worldwide ranked by ideXlab platform
Miao Yi - One of the best experts on this subject based on the ideXlab platform.
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large eddy simulation of Mixing Process in stirred tank with rushton turbine
Journal of East China University of Science and Technology, 2006Co-Authors: Miao YiAbstract:Large eddy simulation(LES) of Mixing Process in a stirred tank of 0.476 m diameter with a standard Rushton turbine were reported.The turbulent flow field and Mixing time were calculated using LES with Smagorinsky-Lilly sub grid scale model.The impeller was modeled using the sliding mesh technique.Better agreement of Mixing time is obtained between the experimental results and prediction by LES than that by the traditional Reynolds-averaged Navier-Stokes(RANS) approach. The response curve of tracer predicted by LES is in a good agreement with the experimental results.The results show that LES is a good approach to investigate unsteady and quasi-periodic behavior of the turbulent flows in stirred tanks.
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Numerical Simulation of Mixing Process in Stirred Tanks with Dual Rushton Turbines
Journal of East China University of Science and Technology, 2006Co-Authors: Miao YiAbstract:The Mixing Process in a stirred tank of 0.476 m diameter with dual six-blade Rushton turbine(DT-6) was numerically simulated using computational fluid dynamics(CFD) package FLUENT(6.0).The RNG κ-e turbulent model and multi-reference frame were used in the simulation.By changing the meshing technology,increasing the number of mesh and decreasing the residual discrepancy,the(effects) of tracer feeding and detecting positions on Mixing time were investigated.The momentum and mass equations were computed separately.The shaft power predicted by CFD is in a good agreement with experimental results. Although the Mixing time predicted by CFD is better than that reported in literatures,it is still about two times higher than that obtained by experiment.
Yi Cheng - One of the best experts on this subject based on the ideXlab platform.
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study on the reactive Mixing Process in an unbaffled stirred tank using planar laser induced fluorescence plif technique
Chemical Engineering Science, 2010Co-Authors: Zhe Liu, Jichu Yang, Yong Jin, Yi ChengAbstract:Abstract The reactive Mixing Process in a stirred tank has drawn much attention due to the complex interplay between the hydrodynamics and the chemical kinetics. However, there is still a lack of effective measurement techniques to explore the detailed information. To quantify the reactive Mixing Process, a novel reactive planar laser-induced fluorescence (reactive-PLIF) technique was developed to visualize how the two liquids mixed and reacted with each other. The main principle was to capture the Process characterized by the fluorescence signal of the tracer dye (i.e., Rhodamine B), which varied in time and space because of being oxidized by the oxidant (i.e., the hydroxyl radical OH) generated between Fe2+ and H2O2 (i.e., a Fenton reaction). The behaviors were recorded by a high-speed digital camera and quantitatively analyzed. The influences of the impeller rotation speed, the impeller position and the liquid properties on the Processes were evaluated. The relationship between the reactive Mixing and the physical Mixing can be determined by the results from the (reactive-)PLIF measurements. This novel technique enabled the convenient measurement of liquid Mixing Process with reactions at a low cost.
Dongxiang Zhang - One of the best experts on this subject based on the ideXlab platform.
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soft sensor development for online quality prediction of industrial batch rubber Mixing Process using ensemble just in time gaussian Process regression models
Chemometrics and Intelligent Laboratory Systems, 2016Co-Authors: Kai Yang, Huaiping Jin, Xiangguang Chen, Jiayu Dai, Li Wang, Dongxiang ZhangAbstract:Abstract Rubber Mixing is a nonlinear batch Process that lasts for very a short time ( ca. 2–5 min). However, the lack of online sensors for quality variable ( e.g. , the Mooney viscosity) has become a main obstacle of controlling rubber Mixing accurately, automatically and optimally. This paper proposes a novel soft sensing method based on Gaussian Process regression (GPR) models fortified with both ensemble learning and just-in-time (JIT) learning, which ensures precision and robustness at the same time. More specifically, this method first builds multiple input variable sets from random local datasets, then uses the obtained input variable sets to establish local models and send them to ensemble learning with Bayesian inference and finite mixture mechanism before making the final prediction output. The superiority of the proposed method is demonstrated using an industrial rubber Mixing Process.
Xinping Long - One of the best experts on this subject based on the ideXlab platform.
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numerical investigation on the Mixing Process in a steam ejector with different nozzle structures
International Journal of Thermal Sciences, 2012Co-Authors: X Yang, Xinping LongAbstract:Abstract The effects of different nozzle structures on the performance of a steam ejector have been investigated numerically with the computational fluid dynamics (CFD) technique. The performance of the steam ejectors with five different nozzle structures, namely, conical, elliptical, square, rectangular and cross-shaped nozzles, have been compared under the same conditions. It is found that, compared with the CFD results of the ejector equipped with the conical nozzle, the entrainment ratio (ER) and critical back pressure (CBP) of the rectangular nozzle is 7.1% and 21.3% lower respectively; the ER and CBP of the elliptical nozzle is 7.9% and 21.3% lower respectively; the square nozzle has improved the ER by 2.0% and decreased the CBP by 2.1%; the ER and CBP of the ejector utilizing cross-shaped nozzle is 9.1% higher and 6.4% respectively lower. Based on the simulation results of the streamwise vortex and spanwise vortex distributions in the Mixing chamber and the internal energy variations along the streamwise distance, the characteristics of the Mixing Process and the main factors accounting for the ejector performance change are clarified. The ER increase can be achieved by efficient Mixing due to the interactions between the streamwise vortex and the spanwise vortex. The streamwise vortex helps to deform and rupture the spanwise vortex which has greater strength. Collides of the vortices to the Mixing chamber wall at early stage would increase mechanical energy loss and reduce “effective area” for secondary flow to pass through, resulting in great decrease of the ER and CBP. This scenario should be avoided in the design of nozzles.
Nan Yang - One of the best experts on this subject based on the ideXlab platform.
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visualization experimental study of the condensing flow regime in the transonic Mixing Process of desalination oriented steam ejector
Energy Conversion and Management, 2019Co-Authors: Yongzhi Tang, Hongqiang Wu, Yanxia Li, Xiaopeng Zhang, Nan YangAbstract:Abstract There are few available related studies about condensing flow regime in the transonic Mixing Process of steam ejector due to its extreme complexity, although it is of great importance for improving ejector entrainment performance and broadening its application. In this paper, a visualization experimental platform of desalination-oriented steam ejector is designed, and the condensing flow regimes under various entrainment pressures pH are captured from multiple perspectives, by means of direct photography approach. The results reveal that the supersonic jet flow is full with massive amounts of condensation droplets whose particle size distribution is not uniform at various vertical positions, and some easily lose their dynamic equilibrium. There exists a slant reverse condensing flow cross-section at the Mixing chamber end, which moves upstream as pH rises and where great numbers of condensation droplets constantly generate around. The condensate quantity of each observation surface is different and increases with pH. The reverse condensing flow regime formed is very complex and accompanied by flexible swirls, clockwise circumferential flow and condensate dynamic accumulation. Then the generated condensate significantly reduces after multiple evaporations downstream the reverse cross-section. It is also found that the flow regime is similar at a same field of view, but diverse at the different fields of view. These meaningful results could serve as a good start point for reducing internal irreversible losses and tailoring ejector design, as well as refining and evaluating physical and mathematical two-phase flow ejector models.
