multiphase fluids
Recently Published Documents


TOTAL DOCUMENTS

66
(FIVE YEARS 14)

H-INDEX

12
(FIVE YEARS 1)

2021 ◽  
Vol 850 (1) ◽  
pp. 012022
Author(s):  
K Sowndarya ◽  
S Monica ◽  
M S Abhisheka ◽  
A K Pradikshan ◽  
M Venkatesan

Abstract Micromixers are used for mixing of multiphase fluids in microchannels. Passive micromixers help in mixing of fluids by having a designed periphery in their structure. In the current study, a Y micro-channel section of 25 mm length with an inlet diameter of 2 mm is considered. Vane shaped micromixers are placed inside the channel to mix fluids of two different concentrations. The vanes are positioned at specific places inside the channel to enhance mixing in the stratified flow stream. The presence of vanes during the flow induces mixing of the stratified fluids without requiring additional components. The study is carried out using COMSOL Multiphysics. The mixing index increases with increase in the number of vanes and no considerable change in velocity is observed downstream of the last vane. Further, when the thickness of the vane is increased, it is found that the mixing index also increases.


2021 ◽  
Vol 88 (s1) ◽  
pp. s107-s113
Author(s):  
Felipe d. A. Dias ◽  
Philipp Wiedemann ◽  
Marco J. da Silva ◽  
Eckhard Schleicher ◽  
Uwe Hampel

Abstract In this paper, the front-end circuit of a capacitance wire-mesh sensor (WMS) is analyzed in detail and a new methodology to tune its feedback gains is reported. This allows, for the first time, a capacitance WMS to be able to provide linear measurements of multiphase fluids with electrical conductivity greater than 100 𝜇S/cm, which is particularly important for tap water, where the conductivity is typically in between 100 S/cm and 500 𝜇S/cm. Experimental and numerical results show that the selected gains using the proposed methodology contribute to suppress cross-talk and energy losses, which in turn, reduces considerably the deviation of the conductivity measurement and the estimation of derived flow parameters, such as local and average phase fraction.


2021 ◽  
Author(s):  
Kieu Hiep Le

To preserve the product quality as well as to reduce the logistics and storage cost, drying process is widely applied in the processing of porous material. In consideration of transport phenomena that involve a porous medium during drying, the complex morphology of the medium, and its influences on the distribution, flow, displacement of multiphase fluids are encountered. In this chapter, the recent advanced mass and energy transport models of drying processes are summarized. These models which were developed based on both pore- and continuum-scales, may provide a better fundamental understanding of non-isothermal liquid–vapor transport at both the continuum scale and the pore scale, and to pave the way for designing, operating, and optimizing drying and relevant industrial processes.


2020 ◽  
Vol 39 (8) ◽  
pp. 69-77
Author(s):  
Y. Jiang ◽  
C. Li ◽  
S. Deng ◽  
S. M. Hu

2020 ◽  
Vol 34 (2) ◽  
pp. 334-341
Author(s):  
Taiki YOSHIDA ◽  
Yuji TASAKA ◽  
Kohei OHIE ◽  
Yuichi MURAI
Keyword(s):  

Fluids ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 4
Author(s):  
Shahriar Afkhami ◽  
Pengtao Yue

The presence of drops, bubbles, and particles affects the behavior and response of complex multiphase fluids [...]


2019 ◽  
Vol 16 (2) ◽  
pp. 77
Author(s):  
M Mohammadzaheri ◽  
Reza Tafreshi ◽  
Zurwa Khan ◽  
Hamidreza Ziaiefar ◽  
Mojataba Ghodsi ◽  
...  

This paper initially reviews existing empirical models which predict head or pressure increase of two-phase petroleum fluids in electrical submersible pumps (ESPs), then, proposes an alternative model, a fully connected cascade (FCC in short) artificial neural network to serve the same purpose. Empirical models of ESP are extensively in use; while analytical models are yet to be vastly employed in practice due to their complexity, reliance on over-simplified assumptions or lack of accuracy. The proposed FCC is trained and cross-validated with the same data used in developing a number of empirical models; however, the developed model presents higher accuracy than the aforementioned empirical models. The mean of absolute prediction error of the FCC for the experimental data not used in its training, is 68% less than the most accurate existing empirical model.


Sign in / Sign up

Export Citation Format

Share Document