Assessment of condensation models for moist air transonic flow prediction

2021 ◽  
Vol 345 ◽  
pp. 00033
Author(s):  
Piotr Wiśniewski ◽  
Mirosław Majkut ◽  
Sławomir Dykas ◽  
Krystian Smołka ◽  
Guojie Zhang ◽  
...  
Keyword(s):  
Numerical Modelling ◽  
Nucleation Rate ◽  
Transonic Flow ◽  
Nozzle Flow ◽  
Growth Equation ◽  
Nucleation Process ◽  
Moist Air ◽  
Ansys Fluent ◽  
Flow Prediction ◽  
Condensation Model

The aim of this article is to thoroughly analyse the influence of condensation models on the modelling of condensation phenomena in transonic flow of moist air. The reason for the study was the fact that different condensation models are used by researchers to obtain satisfactory results of numerical modelling. The condensation models tested herein differ in the nucleation rate formula and the droplets growth equation. Four most often used condensation models were selected for detailed investigations. The results obtained from each model were compared with experiments for the nozzle flow. The main focus was on the location of the onset of the nucleation process. Moreover, the droplets growth intensity was compared and discussed. The nozzle flow CFD calculations were performed using the ANSYS Fluent commercial tool. Finally, the condensation model which is the most suitable for the moist air transonic flow was recommended.

Selection of a steam condensation model for atmospheric air transonic flow prediction

2021 ◽  
pp. 117922
Author(s):  
Piotr Wiśniewski ◽  
Mirosław Majkut ◽  
Sławomir Dykas ◽  
Krystian Smołka ◽  
Guojie Zhang ◽  
...  
Keyword(s):  
Transonic Flow ◽  
Steam Condensation ◽  
Atmospheric Air ◽  
Flow Prediction ◽  
Condensation Model ◽  
Selection Of

scholarly journals A Study of Moist Air Condensation Characteristics in a Transonic Flow System

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 4052
Author(s):  
Jie Wang ◽  
Hongfang Gu
Keyword(s):  
Mach Number ◽  
Relative Humidity ◽  
Transonic Flow ◽  
Flow System ◽  
Plane Surface ◽  
Droplet Growth ◽  
Moist Air ◽  
Dry Air ◽  
Hydraulic Equipment ◽  
Non Equilibrium

When water vapor in moist air reaches supersaturation in a transonic flow system, non-equilibrium condensation forms a large number of droplets which may adversely affect the operation of some thermal-hydraulic equipment. For a better understanding of this non-equilibrium condensing phenomenon, a numerical model is applied to analyze moist air condensation in a transonic flow system by using the theory of nucleation and droplet growth. The Benson model is adopted to correct the liquid-plane surface tension equation for realistic results. The results show that the distributions of pressure, temperature and Mach number in moist air are significantly different from those in dry air. The dry air model exaggerates the Mach number by 19% and reduces both the pressure and the temperature by 34% at the nozzle exit as compared with the moist air model. At a Laval nozzle, for example, the nucleation rate, droplet number and condensation rate increase significantly with increasing relative humidity. The results also reveal the fact that the number of condensate droplets increases rapidly when moist air reaches 60% relative humidity. These findings provide a fundamental approach to account for the effect of condensate droplet formation on moist gas in a transonic flow system.

scholarly journals Numerical Modelling Of Humid Air Flow Around A Porous Body

2015 ◽  
Vol 9 (3) ◽  
pp. 161-166
Author(s):  
Aneta Bohojło-Wiśniewska
Keyword(s):  
Heat Transfer ◽  
Numerical Simulation ◽  
Porous Medium ◽  
Numerical Modelling ◽  
Chinese Cabbage ◽  
Air Flow ◽  
Transfer Model ◽  
Humid Air ◽  
Ansys Fluent ◽  
Complex Heat Transfer

Summary This paper presents an example of humid air flow around a single head of Chinese cabbage under conditions of complex heat transfer. This kind of numerical simulation allows us to create a heat and humidity transfer model between the Chinese cabbage and the flowing humid air. The calculations utilize the heat transfer model in porous medium, which includes the temperature difference between the solid (vegetable tissue) and fluid (air) phases of the porous medium. Modelling and calculations were performed in ANSYS Fluent 14.5 software.

Effect of nonequilibrium condensation of moist air on transonic flow fields

2000 ◽  
Vol 9 (1) ◽  
pp. 37-44 ◽  
Author(s):  
Katsumi Shimamoto ◽  
Shigeru Matsuo ◽  
Toshiaki Setoguchi
Keyword(s):  
Transonic Flow ◽  
Flow Fields ◽  
Moist Air ◽  
Nonequilibrium Condensation

scholarly journals Secondary Nucleation Kinetics of AIBN Crystallisation in Methanol: Online Imaging-Based Measurement and Modelling

Crystals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 506
Author(s):  
Yang Li ◽  
Yang Zhang ◽  
Xue Zhong Wang
Keyword(s):  
Nucleation Rate ◽  
Induction Time ◽  
Nucleation Process ◽  
Stirrer Speed ◽  
Seed Number ◽  
Nucleation Kinetics ◽  
Secondary Nucleation ◽  
On Line ◽  
Small Change ◽  
Crystal Seed

The secondary nucleation process of 2,2-azobisisobutyronitrile (AIBN) seeded crystallisation in methanol in a stirred tank reactor was studied at varying initial supersaturation levels, temperatures, crystal seed numbers, and stirrer speeds. The average secondary nucleation rate, induction time, and agglomeration ratio were measured using on-line microscopic imaging. The initial supersaturation level, temperature, and stirrer speed were found to be positively correlated with the secondary nucleation rate. A small change in the crystal seed number, i.e., 1-20, did not substantially affect the secondary nucleation rate throughout the secondary nucleation process. An increase in the initial supersaturation level and crystal seed number decreased the induction time, and an increase in the strength of agitation promoted the initiation of secondary nucleation at a stirring rate greater than 250 revolutions per minute (rpm). Temperature exerted a complex effect on the induction time. Regarding the agglomeration ratio, the initial supersaturation level positively correlated with the agglomeration ratio, while the stirrer speed negatively correlated with this parameter. Finally, based on the measured data, the average secondary nucleation rate, induction time, and final crystal suspension density were correlated. This study provides guidance for the control of supersaturation, induction time, stirring, and other factors in the crystal seed addition process in AIBN crystallisation.

Numerical Calculation of the Force Coefficient for Cylindrical Shape Smokestack Covered with Corrugated Iron

2016 ◽  
Vol 821 ◽  
pp. 79-84
Author(s):  
Vladimira Michalcova ◽  
Lenka Lausova
Keyword(s):  
Numerical Calculation ◽  
Circular Cylinder ◽  
Numerical Modelling ◽  
Aerodynamic Drag ◽  
Cylindrical Shape ◽  
Force Coefficient ◽  
Ansys Fluent ◽  
Aerodynamic Drag Coefficient ◽  
Aerodynamic Roughness ◽  
Des Model

The article deals with the influence of a shape of the smokestacks casing on the final load from wind effects. It describes possibilities of defining an equivalent aerodynamic roughness and aerodynamic drag coefficient for numerical modelling of the flow around a circular cylinder. The aim is to determine the force coefficient for a smokestack of a cylindrical shape, which is sheeted with corrugated sheet metal. The flow around a smokestack is solved in software Ansys Fluent using the DES model.

Transonic flow of moist air around a thin airfoil with non-equilibrium and homogeneous condensation

2000 ◽  
Vol 403 ◽  
pp. 173-199 ◽  
Author(s):  
ZVI RUSAK ◽  
JANG-CHANG LEE
Keyword(s):  
Transonic Flow ◽  
Droplet Growth ◽  
Inviscid Fluid ◽  
Small Disturbance ◽  
Moist Air ◽  
Integration Rule ◽  
Flow Equations ◽  
Homogeneous Condensation ◽  
Thin Airfoil ◽  
Non Equilibrium

A new small-disturbance model for a steady transonic flow of moist air with non-equilibrium and homogeneous condensation around a thin airfoil is presented. The model explores the nonlinear interactions among the near-sonic speed of the flow, the small thickness ratio and angle of attack of the airfoil, and the small amount of water vapour in the air. The condensation rate is calculated according to classical nucleation and droplet growth models. The asymptotic analysis gives the similarity parameters that govern the flow problem. Also, the flow field can be described by a non-homogeneous (extended) transonic small-disturbance (TSD) equation coupled with a set of four ordinary differential equations for the calculation of the condensate (or sublimate) mass fraction. An iterative numerical scheme which combines Murman & Cole's (1971) method for the solution of the TSD equation with Simpson's integration rule for the estimation of the condensate mass production is developed. The results show good agreement with available numerical simulations using the inviscid fluid flow equations. The model is used to study the effects of humidity and of energy supply from condensation on the aerodynamic performance of airfoils.

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