A General Frictional Pressure Drop Correlation for Condensation in Microfin Tubes

2017 ◽  
Author(s):  
Zhichuan Sun ◽  
Wei Li
Keyword(s):  
Pressure Drop ◽  
Reduced Pressure ◽  
Error Band ◽  
Frictional Pressure Drop ◽  
New Correlation ◽  
Data Points ◽  
Fin Tubes ◽  
Microfin Tubes ◽  
Experimental Pressure ◽  
Good Agreement

Experimental pressure drop data of condensation from the previous literature were collected to develop a general frictional pressure drop correlation for horizontal micro-fin tubes. The collected database contained 481 data points, covering nine working fluids at average saturated condensing temperatures ranging between 14 and 65°C, with mass velocities ranging from 50 to 800 kg/m2s, and average vapor qualities from 0.11 to 0.91. The hydraulic diameter of micro-fin tubes varied from 2.16 to 5.67 mm and was employed in the calculation of Reynolds number. The Fanning frictional factor was calculated by adopting the Churchill model with the empirically fitted relative roughness. Four existing pressure drop correlations developed for micro-fin tubes were evaluated by the database for condensation in micro-fin tubes. The correlation proposed by Cavallini et al. was the best prediction model among them, predicting 85.6% of the collected data points within the 30% error band. In addition, a new correlation based on the Martnelli parameter Xtt modified by incorporating the reduced pressure was proposed to predict the present database, which showed a good agreement.

Evaluation of Frictional Pressure Drop Correlations During Flow Boiling of Refrigerants in Micro-Fin Tubes

2020 ◽  
Author(s):  
Weiyu Tang ◽  
Wei Li ◽  
Jianxin Zhou
Keyword(s):  
Pressure Drop ◽  
Flow Boiling ◽  
Predictive Ability ◽  
Operating Conditions ◽  
Commercial Application ◽  
Equivalent Diameter ◽  
Specific Work ◽  
Frictional Pressure Drop ◽  
Data Points ◽  
Fin Tubes

Abstract Due to the widely commercial application of micro-fin tube and eco-friendly refrigerants, more general frictional pressure drop correlations is demanded for better prediction, and this study is aimed at compared existing correlations and provide guides for the furthermore improvement. Experimental data points for frictional pressure drop during flow boiling of refrigerants in horizontal micro-fin tubes were extracted from literature and our previous experimental work to evaluate numerous existing frictional pressure drop correlations and specify their applicability to meet the urgent demand of extensive application of eco-friendly refrigerants. The database consists of 949 data points covering eleven refrigerants (R1233zd(Z), R410A, R1234ze(E), R410A, R22, R32, R1234ze(Z), R22, R134a, R245fa and R1234yf included), and the involved operation conditions are as follows: mass velocity 94–888 kg m−2s−1, vapor quality 0.04–0.99, heat flux 3.9–85.2 kW m−2, and equivalent diameter 2.12–11.84mm. Eight existing general frictional pressure drop correlation including Cavallini et al., Kuo and Wang, Wongsangam et al. and Rollman and Spindler correlation were evaluated against the present database. In addition, the Churchill et al. model was employed in several correlation to improve their performance. It was found that none of these correlations was capable of providing a satisfactory prediction for a general operation condition. A detailed predictive ability of these correlation against specific work fluids were given for reference, and their individual parametric-trend predictive ability were also compared under varied operating conditions using several datasets.

Single Phase and Two Phase Flow Characteristics and Heat Transfer in Micro-Fin Tubes

2015 ◽  
Author(s):  
Jun-ye Li ◽  
Si-pu Guo ◽  
Jing Zhang ◽  
Wei Li ◽  
Jin-jia Wei ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Pressure Drop ◽  
Single Phase ◽  
Phase Flow ◽  
Single Phase Flow ◽  
Transfer Coefficients ◽  
Error Band ◽  
Heat Transfer Coefficients ◽  
New Correlation ◽  
Fin Tubes

An experimental investigation was performed with R22 and R410a for single-phase flow, evaporation and condensation inside five micro-fin tubes of various geometries to obtain pressure drop and heat transfer characteristics. The results suggest single-phase flow heat transfer coefficients are increased by 46% to 64% compared with smooth tubes values. Tube geometries that had higher evaporation heat transfer coefficients or higher condensation heat transfer coefficients were identified. Condensation pressure drop characteristics also varied with tube geometry. Based on experiment data, a new correlation which contains the characteristics of a liquid film in annular flow is established. The new correlation can predict the experimental data within an error band of 15% and, for 77% of the data from the literature, within an error band of 30%. The Choi et al. correlation can predict the present condensation pressure drop data within a 20% error band and the Yu and Koyama correlation can predict the present condensation heat transfer coefficient data within 25%.

Evaluation Analysis of Prediction Methods for Two-Phase Flow Pressure Drop in Mini-Channels

2008 ◽  
Author(s):  
Licheng Sun ◽  
Kaichiro Mishima
Keyword(s):  
Pressure Drop ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Turbulent Region ◽  
Frictional Pressure Drop ◽  
New Correlation ◽  
Mini Channels ◽  
Flow Pressure ◽  
Better Than

2092 data of two-phase flow pressure drop were collected from 18 published papers of which the working fluids include R123, R134a, R22, R236ea, R245fa, R404a, R407C, R410a, R507, CO2, water and air. The hydraulic diameter ranges from 0.506 to 12mm; Relo from 10 to 37000, and Rego from 3 to 4×105. 11 correlations and models for calculating the two-phase frictional pressure drop were evaluated based upon these data. The results show that the accuracy of the Lockhart-Martinelli method, Mishima and Hibiki correlation, Zhang and Mishima correlation and Lee and Mudawar correalion in the laminar region is very close to each other, while the Muller-Steinhagen and Heck correlation is the best among the evaluated correlations in the turbulent region. A modified Chisholm correlation was proposed, which is better than all of the evaluated correlations in the turbulent region and its mean relative error is about 29%. For refrigerants only, the new correlation and Muller-Steinhagen and Heck correlation are very close to each other and give better agreement than the other evaluated correlations.

Prediction of Pressure Drop of Various Refrigerants During Condensation in Horizontal Smooth and Micro-Fin Tubes by Means of Artificial Neural Networks

2012 ◽  
Author(s):  
Muhammet Balcilar ◽  
Ahmet Selim Dalkiliç ◽  
Şevket Özgür Atayılmaz ◽  
Hakan Demir ◽  
Somchai Wongwises
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Pressure Drop ◽  
Tube Length ◽  
Two Phase ◽  
Pressure Drops ◽  
Data Points ◽  
Artificial Neural ◽  
Fin Tubes ◽  
Liquid And Vapor Phases

The predictions of condensation pressure drops of R12, R22, R32, R125, R410A, R134a, R22, R502 and R507a flowing inside various horizontal smooth and micro-fin tubes are made using the numerical techniques of Artificial Neural Networks (ANNs) and non-linear least squares (NLS). The National Institute of Standards and Technology’s (NIST) experimental data and, Eckels’ and Pate’s experimental data, as presented in Choi et al.’s study provided by NIST, are used in our analyses. In their experimental setups, the horizontal test sections have 1.587 m, 3.78 m, 3.81 m and 3.97 m long countercurrent flow double tube heat exchangers with refrigerant flowing in the inner smooth (8 mm, 8.01 mm and 11.1 mm i.d.) and micro-fin (5.45 mm and 7.43 mm i.d.) copper tubes as cooling water flows in the annulus. Their test runs cover a wide range of saturation pressures from 0.9 MPa to 2.9 MPa, inlet vapor qualities range from 0.19 to 1.0 and mass fluxes are from 8 kg m−2s−1 to 791 kg m−2s−1. The condensation pressure drops are predicted using 673 measured data points, together with numerical analyses of artificial neural networks and non-linear least squares. The input of the ANNs for the best correlation are the measured and the values of the test sections are calculated, such as mass flux, tube length, inlet and outlet vapor qualities, critical pressure, latent heat of condensation, mass fraction of liquid and vapor phases, dynamic viscosities of liquid and vapor phases, hydraulic diameter, two-phase density, and the outputs of the ANNs as the experimental total pressure drops in the condensation data from independent laboratories. The total pressure drops of in-tube condensation tests are modeled using the artificial neural networks (ANNs) method of multi-layer perceptron (MLP) with a 12-40-1 architecture. The average error rate is 7.085%, considering the cross validation tests of the 867 condensation data points. A detailed model of f(MLP) is given for direct use in MATLAB. This explanation will enable users to predict the two-phase pressure drop with high accuracy. As a result of the dependency analyses, dependency of the output of the ANNs from 12 sets of input values is shown in detail, and the pressure drops of condensation in smooth and micro-fin tubes are found to be highly dependent on mass flux, all liquid Reynolds numbers, the latent heat of condensation, outlet vapor quality, critical pressure of the refrigerant, liquid dynamic viscosity, and tube length. New ANNs based empirical pressure drop correlations are developed separately for the conditions of condensation in smooth and micro-fin tubes as a result of the analyses.

Pressure Drop Correlations of Single-Phase and Two-Phase Flow in Rolling Tubes

2006 ◽  
Author(s):  
Xia-Xin Cao ◽  
Chang-Qi Yan ◽  
Pu-Zhen Gao ◽  
Zhong-Ning Sun
Keyword(s):  
Experimental Data ◽  
Pressure Drop ◽  
Single Phase ◽  
Experimental Studies ◽  
Frictional Coefficient ◽  
Bubble Flow ◽  
Two Phase ◽  
Frictional Pressure Drop ◽  
Rolling Condition ◽  
New Correlation

A series of experimental studies of frictional pressure drop for single phase and two-phase bubble flow in smooth rolling tubes were carried out. The tube inside diameters were 15mm, 25mm and 34.5mm respectively, the rolling angles of tubes could be set as 10° and 20°, and the rolling periods could be set as 5s, 10s and 15s. Combining with the analysis of single-phase water motion, it was found that the traditional correlations for calculating single-phase frictional coefficient were not suitable for the rolling condition. Based on the experimental data, a new correlation for calculating single-phase frictional coefficient under rolling condition was presented, and the calculations not only agreed well with the experimental data, but also could display the periodically dynamic characteristics of frictional coefficients. Applying the new correlation to homogeneous flow model, two-phase frictional pressure drop of bubble flow in rolling tubes could be calculated, the results showed that the relative error between calculation and experimental data was less than ± 25%.

Frictional Pressure Drop Correlations for Single-Phase Flow, Condensation, and Evaporation in Microfin Tubes

2015 ◽  
Vol 138 (2) ◽  
Author(s):  
Zan Wu ◽  
Bengt Sundén
Keyword(s):  
Reynolds Number ◽  
Pressure Drop ◽  
Single Phase ◽  
Flow Boiling ◽  
Phase Flow ◽  
Single Phase Flow ◽  
Frictional Pressure Drop ◽  
Friction Factors ◽  
Flow Condensation ◽  
Microfin Tubes

Experimental single-phase, condensation, and evaporation (flow boiling) pressure drop data from the literature and our previous studies were collected to evaluate previous frictional pressure drop correlations for horizontal microfin tubes of different geometries. The modified Ravigururajan and Bergles correlation, by adopting the Churchill model to calculate the smooth-tube friction factor and by using the hydraulic diameter in the Reynolds number, can predict single-phase turbulent frictional pressure drop data relatively well. Eleven pressure drop correlations were evaluated by the collected database for condensation and evaporation. Correlations originally developed for condensation and evaporation in smooth tubes can be suitable for microfin tubes if the friction factors in the correlations were calculated by the Churchill model to include microfin effects. The three most accurate correlations were recommended for condensation and evaporation in microfin tubes. The Cavallini et al. correlation and the modified Friedel correlation can give good predictions for both condensation and evaporation. However, some inconsistencies were found, even for the recommended correlations.

PRESSURE DROP CHARACTERISTICS OF R410A-OIL MIXTURE FLOW BOILING IN SMALL SMOOTH TUBES

2010 ◽  
Vol 18 (02) ◽  
pp. 109-116 ◽  
Author(s):  
YIFENG GAO ◽  
BIN DENG ◽  
GUOLIANG DING ◽  
HAITAO HU ◽  
XIANGCHAO HUANG
Keyword(s):  
Pressure Drop ◽  
Flow Boiling ◽  
Smooth Tube ◽  
Two Phase ◽  
Experimental Conditions ◽  
Mixture Flow ◽  
Frictional Pressure Drop ◽  
New Correlation ◽  
Smooth Tubes ◽  
Local Properties

This study presents experimental frictional pressure drop for R410A/oil mixture flow boiling in small horizontal smooth tubes with inside diameters of 4.18 mm and 2.0 mm. Experimental conditions cover nominal oil concentrations from 0 to 5%. The test results show that the presence of oil enhances two-phase frictional pressure drop about 0–120% and 0–90% at present test conditions for 4.18 mm I.D. smooth tube and 2.0 mm I.D. smooth tube, respectively, and the enhanced effect is more evident at higher vapor qualities where the local oil concentrations are higher. A new correlation to predict the local frictional pressure drop of R410A/oil mixture flow boiling inside conventional size and small smooth tubes is developed based on local properties of refrigerant–oil mixture, and the experimental data of 4.18 mm I.D. and 2.0 mm I.D. smooth tubes and that of 6.34 mm I.D. smooth tube (Hu et al., 2008) are well-correlated with the new correlation.

scholarly journals Robust and universal predictive models for frictional pressure drop during two-phase flow in smooth helically coiled tube heat exchangers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. A. Moradkhani ◽  
Seyyed Hossein Hosseini ◽  
M. Mansouri ◽  
G. Ahmadi ◽  
Mengjie Song
Keyword(s):  
Pressure Drop ◽  
Sensitivity Analyses ◽  
Two Phase ◽  
Neural Network Approach ◽  
Frictional Pressure Drop ◽  
Mass Fluxes ◽  
The Neural Network ◽  
Coil Axis ◽  
Data Points ◽  
Intelligent Models

AbstractThere is a lack of well-verified models in the literature for the prediction of the frictional pressure drop (FPD) in the helically coiled tubes at different conditions/orientations. In this study, the robust and universal models for estimating two-phase FPD in smooth coiled tubes with different orientations were developed using several intelligent approaches. For this reason, a databank comprising 1267 experimental data samples was collected from 12 independent studies, which covers a broad range of fluids, tube diameters, coil diameters, coil axis inclinations, mass fluxes, saturation temperatures, and vapor qualities. The earlier models for straight and coiled tubes were examined using the collected database, which showed absolute average relative error (AARE) higher than 21%. The most relevant dimensionless groups were used as models’ inputs, and the neural network approach of multilayer perceptron and radial basis functions (RBF) were developed based on the homogenous equilibrium method. Although both intelligent models exhibited excellent accuracy, the RBF model predicted the best results with AARE 4.73% for the testing process. In addition, an explicit FPD model was developed by the genetic programming (GP), which showed the AARE of 14.97% for all data points. Capabilities of the proposed models under different conditions were described and, the sensitivity analyses were performed.

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