Research on the physical model of features of the behavior of a two-phase bath at top blowing through a tip with folded nozzles

2020 ◽  
pp. 129-138
Author(s):  
S.І. Semykin ◽  
Т.S. Golub ◽  
V.V. Vakulchuk
Keyword(s):  
Physical Model ◽  
Silicone Oil ◽  
Mixing Processes ◽  
Two Phase ◽  
Converter Bath ◽  
Slit Size ◽  
Phase Liquid ◽  
Two Phases ◽  
Active Mixing ◽  
Favorable Conditions

At the previous stage of research using a physical model of an oxygen converter, the results of studying the features of purging a single-phase liquid through a single composite nozzle were obtained. The aim of this work was to study the behavior of a two-phase bath using a multi-nozzle lance with folded nozzles. At this stage of the study, silicone oil was used to simulate the slag phase of a two-phase bath. The peculiarities of the influence of experimental nozzles on the processes of mixing and foaming of two phases were studied. Three variants of the experimental nozzle design were investigated: a combination of a conventional and a slit nozzle with a ratio of their areas of 1: 1, 1: 2 and 2: 1. It is established that the use of a tip with four nozzles during purging from above promotes the active formation of a two-layer foamed emulsion on the surface of the bath. Comparison of the operation of the tip with folded nozzles with a tip with a cylindrical indicates more active mixing of the two liquids and the formation of a more stable and much higher layer of foamed emulsion. The most favorable conditions for the organization of full mixing of the two phases in the converter bath are formed when using folded nozzles with a slit size of about 35% and a ratio of slot and nozzle area of 1: 2. To intensify the mixing processes in the upper zone of the unit, it is most expedient to use folded nozzles with a larger fraction of the slit (up to 65%) and the ratio of the areas of the components of the nozzle 2: 1. The use of nozzles with equal areas of components in the studied conditions does not have a positive effect on metabolic processes in the converter bath.

Effects of Viscosity and Two Phase Liquid–Gas Fluids on the Performance of Multi-Stage Centrifugal Pumps

2010 ◽  
Author(s):  
Brown ‘Lyle’ Wilson ◽  
Ketan Sheth ◽  
Donn Brown
Keyword(s):  
Test Facility ◽  
Centrifugal Pumps ◽  
Two Phase ◽  
Void Fractions ◽  
Multi Stage ◽  
Significant Difference ◽  
Phase Liquid ◽  
Intake Pressure ◽  
Two Phases ◽  
Safety Considerations

The paper reports on developmental research on the effects of viscosity and two phases, liquid–gas fluids on ESPs which are multi stage centrifugal pumps for deep bore holes. The test facility work was performed using pumps with ten or more stages moving fluids with viscosity from 2 to 2500 cP at various speed, intake pressure and Gas Void Fractions (GVF). For safety considerations the injected gas was restricted to nitrogen or air. The results are a series of curves representing the performance degradation of the pump. Note that in some cases the pump performances actually improved with increasing viscosity. The resulting information will allow a better understanding and more accurate prediction of performance than has been previously available. The data indicates a significant difference in performance correction when compared to the information available from the Hydraulics Institute.

scholarly journals Transient CFD simulations of turbulent liquid - liquid flow in a Kenics static mixer. Radial and tangential velocities

2009 ◽  
Vol 11 (2) ◽  
pp. 36-40 ◽  
Author(s):  
Halina Murasiewicz ◽  
Zdzislaw Jaworski
Keyword(s):  
Liquid Flow ◽  
Liquid Mixture ◽  
Static Mixer ◽  
Cfd Simulations ◽  
Two Phase ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Transient Simulations ◽  
Phase Liquid ◽  
Two Phases

Transient CFD simulations of turbulent liquid - liquid flow in a Kenics static mixer. Radial and tangential velocities The results of modelling of the two-phase turbulent flow of a two-phase, liquid-liquid mixture in a Kenics static mixer were reported. Advanced transient simulations were performed using the large eddy simulation (LES) approach and a broader analysis of the velocity field was carried out. The two-phase flow was modelled employing the Eulerian approach in the pseudo-homogeneous version of the mixture model. Three cases were again considered, which differed by the density of the two phases and the simulations were performed for Reynolds number of 10,000. The LES results for the tangential and radial components were compared with those obtained in the steady-state RANS approach.

Vibratory Mobilization of Two-Phase Liquid Trapped in Capillary

2009 ◽  
Author(s):  
Gang Cheng ◽  
Liming Dai
Keyword(s):  
Porous Media ◽  
Physical Model ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Vibration Frequency ◽  
Experimental Tests ◽  
Two Phase ◽  
Phase Liquid

The newly developed Enhanced Oil Recovery technology implementing vibration and seismic stimulations relies on mobilization of oil trapped in pores of porous media of reservoir. This research indents to investigate the conditions for dynamically mobilizing an oil slug trapped in capillary with controlled vibration. An idealized physical model is established, on which series of experimental tests are performed for determining the conditions. Initiation of the mobilization and the effects of vibration frequency and duration of vibration on the mobilization are analyzed. The results of the research are significant for reveal the mechanism of Enhanced Oil Recovery technology with vibro-seismic stimulation.

Phase Inversion in Two-Phase Liquid Systems

1992 ◽  
Vol 57 (7) ◽  
pp. 1419-1423
Author(s):  
Jindřich Weiss
Keyword(s):  
Interfacial Tension ◽  
Phase Inversion ◽  
Continuous Phase ◽  
Considerable Effect ◽  
Weak Dependence ◽  
Dispersed Phase ◽  
Two Phase ◽  
Liquid Systems ◽  
Phase Liquid

New data on critical holdups of dispersed phase were measured at which the phase inversion took place. The systems studied differed in the ratio of phase viscosities and interfacial tension. A weak dependence was found of critical holdups on the impeller revolutions and on the material contactor; on the contrary, a considerable effect of viscosity was found out as far as the viscosity of continuous phase exceeded that of dispersed phase.

A Lightweight Formalism for Reference Lifetimes and Borrowing in Rust

2021 ◽  
Vol 43 (1) ◽  
pp. 1-73
Author(s):  
David J. Pearce
Keyword(s):  
Memory Management ◽  
Programming Model ◽  
Type System ◽  
Control Flow ◽  
Two Phase ◽  
Type Checking ◽  
Strong Focus ◽  
Reference Implementation ◽  
Two Phases ◽  
Complex Features

Rust is a relatively new programming language that has gained significant traction since its v1.0 release in 2015. Rust aims to be a systems language that competes with C/C++. A claimed advantage of Rust is a strong focus on memory safety without garbage collection. This is primarily achieved through two concepts, namely, reference lifetimes and borrowing . Both of these are well-known ideas stemming from the literature on region-based memory management and linearity / uniqueness . Rust brings both of these ideas together to form a coherent programming model. Furthermore, Rust has a strong focus on stack-allocated data and, like C/C++ but unlike Java, permits references to local variables. Type checking in Rust can be viewed as a two-phase process: First, a traditional type checker operates in a flow-insensitive fashion; second, a borrow checker enforces an ownership invariant using a flow-sensitive analysis. In this article, we present a lightweight formalism that captures these two phases using a flow-sensitive type system that enforces “ type and borrow safety .” In particular, programs that are type and borrow safe will not attempt to dereference dangling pointers. Our calculus core captures many aspects of Rust, including copy- and move-semantics, mutable borrowing, reborrowing, partial moves, and lifetimes. In particular, it remains sufficiently lightweight to be easily digested and understood and, we argue, still captures the salient aspects of reference lifetimes and borrowing. Furthermore, extensions to the core can easily add more complex features (e.g., control-flow, tuples, method invocation). We provide a soundness proof to verify our key claims of the calculus. We also provide a reference implementation in Java with which we have model checked our calculus using over 500B input programs. We have also fuzz tested the Rust compiler using our calculus against 2B programs and, to date, found one confirmed compiler bug and several other possible issues.

scholarly journals XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks

2021 ◽  
Author(s):  
Vishu Madaan ◽  
Aditya Roy ◽  
Charu Gupta ◽  
Prateek Agrawal ◽  
Anand Sharma ◽  
...  
Keyword(s):  
Image Classification ◽  
Second Phase ◽  
Two Phase ◽  
X Ray ◽  
The Neural Network ◽  
Rapid Spread ◽  
Chest X Ray ◽  
Polymerase Chain ◽  
Two Phases ◽  
Active Patients

AbstractCOVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is accelerating. More than 1.5 million patients (approximately 2.5% of total reported cases) across the world lost their life. In many places, the COVID-19 detection takes place through reverse transcription polymerase chain reaction (RT-PCR) tests which may take longer than 48 h. This is one major reason of its severity and rapid spread. We propose in this paper a two-phase X-ray image classification called XCOVNet for early COVID-19 detection using convolutional neural Networks model. XCOVNet detects COVID-19 infections in chest X-ray patient images in two phases. The first phase pre-processes a dataset of 392 chest X-ray images of which half are COVID-19 positive and half are negative. The second phase trains and tunes the neural network model to achieve a 98.44% accuracy in patient classification.

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