scholarly journals Algorithm Scheme to Simulate the Distortions during Gas Quenching in a Single-Piece Flow Technology

Coatings ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 694 ◽  
Author(s):  
Jacek Sawicki ◽  
Krzysztof Krupanek ◽  
Wojciech Stachurski ◽  
Victoria Buzalski
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
High Pressure ◽  
Heat Transfer Coefficient ◽  
Fluid Flow ◽  
Transfer Coefficient ◽  
Single Piece ◽  
Gas Quenching ◽  
Complex Fluid ◽  
Algorithm Scheme

Low-pressure carburizing followed by high-pressure quenching in single-piece flow technology has shown good results in avoiding distortions. For better control of specimen quality in these processes, developing numerical simulations can be beneficial. However, there is no commercial software able to simulate distortion formation during gas quenching that considers the complex fluid flow field and heat transfer coefficient as a function of space and time. For this reason, this paper proposes an algorithm scheme that aims for more refined results. Based on the physical phenomena involved, a numerical scheme was divided into five modules: diffusion module, fluid module, thermal module, phase transformation module, and mechanical module. In order to validate the simulation, the results were compared with the experimental data. The outcomes showed that the average difference between the numerical and experimental data for distortions was 1.7% for the outer diameter and 12% for the inner diameter of the steel element. Numerical simulation also showed the differences between deformations in the inner and outer diameters as they appear in the experimental data. Therefore, a numerical model capable of simulating distortions in the steel elements during high-pressure gas quenching after low-pressure carburizing using a single-piece flow technology was obtained, whereupon the complex fluid flow and variation of the heat transfer coefficient was considered.

Assessment of the Impact of Laminar-Turbulent Transition on the Accuracy of Heat Transfer Coefficient Prediction in High Pressure Turbines

2006 ◽  
Author(s):  
Mahmoud L. Mansour ◽  
Khosro Molla Hosseini ◽  
Jong S. Liu ◽  
Shraman Goswami
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
High Pressure ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Test Cases ◽  
Turbine Cascade ◽  
High Pressure Turbine ◽  
Turbulent Transition ◽  
Laminar Turbulent Transition

This paper presents a thorough assessment for two of the contemporary CFD programs available for modeling and predicting nonfilm-cooled surface heat transfer distributions on turbine airfoil surfaces. The CFD programs are capable of predicting laminar-turbulent transition and have been evaluated and validated against five test cases with experimental data. The suite of test cases considered for this study consists of two flat plat cases at zero and non-zero pressure gradient and three linear-turbine-cascade test cases that are representative of modern high pressure turbine designs. The flat plate test cases are the ERCOFTAC T3A and T3C2, while the linear turbine cascade cases are the MARKII, the Virginia Polytechnic Institute (VPI), and the Von Karman Institute (VKI) turbine cascades. The numerical tools assessed in this study are 3D viscous Reynolds Averaged-Navier-Stokes (RANS) equations programs that employ a variety of one-equation and two-equation models for turbulence closure. The assessment study focuses on the one-equation Spalart and Allmaras and the two-equation shear stress transport K-ω turbulence models with the ability of modeling and predicting laminar-turbulent transition. The RANS 3D viscous codes are Numeca’s Fine Turbo and ANSYS-CFX’ CFX5. Numerical results for skin friction, surface temperature distribution and heat transfer coefficient from the CFD programs are compared to measured experimental data. Sensitivity of the predictions to free stream turbulence and to inlet turbulence boundary conditions is also presented. The results of the study clearly illustrate the superiority of using the laminar-turbulent transition prediction in improving the accuracy of predicting the heat transfer coefficient on the surfaces of high pressure turbine airfoils.

Water Single-Phase Fluid Flow and Heat Transfer in Capillary Tubes

2003 ◽  
Author(s):  
A. Bucci ◽  
G. P. Celata ◽  
M. Cumo ◽  
E. Serra ◽  
G. Zummo
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Reynolds Number ◽  
Heat Transfer Coefficient ◽  
Fluid Flow ◽  
Laminar Flow ◽  
Transfer Coefficient ◽  
Single Phase ◽  
Heat Transfer Correlations ◽  
Good Agreement

This paper reports the results of an experimental investigation of fluid flow and single-phase heat transfer of water in stainless steel capillary tubes. Three tube diameters are tested: 172 μm, 290 μm and 520 μm, while the Reynolds number varying from 200 up to 6000. Fluid flow experimental results indicate that in laminar flow regime the friction factor is in good agreement with the Hagen-Poiseuille theory for Reynolds number below 800–1000. For higher values of Reynolds number, experimental data depart from the Hagen-Poiseuille law to the side of higher f values. The transition from laminar to turbulent regime occurs for Reynolds number in the range 1800–3000. This transition is found in good agreement with the well known flow transition for rough commercial tubes. Heat transfer experiments show that heat transfer correlations in laminar and turbulent regimes, developed for conventional size tubes, are not adequate for calculation of heat transfer coefficient in microtubes. In laminar flow the experimental values of heat transfer coefficient are generally higher than those calculated with the classical correlation, while in turbulent flow regime experimental data do not deviate significantly from classical heat transfer correlations. Deviation from classical heat transfer correlations increase as the channel diameter decrease.

A Critical Review on the Determination of Pressure Drop During Condensation in Smooth and Enhanced Tubes

2013 ◽  
Author(s):  
Ahmet Selim Dalkiliç ◽  
Ali Celen ◽  
Mohamed M. Awad ◽  
Somchai Wongwises
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Experimental Data ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Critical Review ◽  
Heat Exchangers ◽  
Numerical Analyses ◽  
Enhanced Tubes

Heat exchangers using in-tube condensation have great significance in the refrigeration, automotive and process industries. Effective heat exchangers have been rapidly developed due to the demand for more compact systems, higher energy efficiency, lower material costs and other economic incentives. Enhanced surfaces, displaced enhancement devices, swirl-flow devices and surface tension devices improve the heat transfer coefficients in these heat exchangers. This study is a critical review on the determination of the condensation heat transfer coefficient of pure refrigerants flowing in vertical and horizontal tubes. The authors’ previous publications on this issue, including the experimental, theoretical and numerical analyses are summarized here. The lengths of the vertical and horizontal test sections varied between 0.5 m and 4 m countercurrent flow double-tube heat exchangers with refrigerant flowing in the inner tube and cooling water flowing in the annulus. The measured data are compared to theoretical and numerical predictions based on the solution of the artificial intelligence methods and CFD analyses for the condensation process in the smooth and enhanced tubes. The theoretical solutions are related to the design of double tube heat exchangers in refrigeration, air conditioning and heat pump applications. Detailed information on the in-tube condensation studies of heat transfer coefficient in the literature is given. A genetic algorithm (GA), various artificial neural network models (ANN) such as multilayer perceptron (MLP), radial basis networks (RBFN), generalized regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS), and various optimization techniques such as unconstrained nonlinear minimization algorithm-Nelder-Mead method (NM), non-linear least squares error method (NLS), and Ansys CFD program are used in the numerical solutions. It is shown that the convective heat transfer coefficient of laminar and turbulent condensing film flows can be predicted by means of theoretical and numerical analyses reasonably well if there is a sufficient amount of reliable experimental data. Regression analysis gave convincing correlations, and the most suitable coefficients of the proposed correlations are depicted as compatible with the large number of experimental data by means of the computational numerical methods.

Experimental and theoretical investigation of heat transfer characteristics of cylindrical heat pipe using Al2O3–SiO2/W-EG hybrid nanofluids by RSM modeling approach

2021 ◽  
Vol 68 (1) ◽  
Author(s):  
R. Vidhya ◽  
T. Balakrishnan ◽  
B. Suresh Kumar
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Heat Transfer Coefficient ◽  
Thermal Resistance ◽  
Transfer Coefficient ◽  
Heat Pipe ◽  
Diffraction Spectrum ◽  
Step Method ◽  
Ceramic Nanoparticles ◽  
Transfer Mechanisms

AbstractNanofluids are emerging two-phase thermal fluids that play a vital part in heat exchangers owing to its heat transfer features. Ceramic nanoparticles aluminium oxide (Al2O3) and silicon dioxide (SiO2) were produced by the sol-gel technique. Characterizations have been done through powder X-ray diffraction spectrum and scanning electron microscopy analysis. Subsequently, few volume concentrations (0.0125–0.1%) of hybrid Al2O3–SiO2 nanofluids were formulated via dispersing both ceramic nanoparticles considered at 50:50 ratio into base fluid combination of 60% distilled water (W) with 40% ethylene glycol (EG) using an ultrasonic-assisted two-step method. Thermal resistance besides heat transfer coefficient have been examined with cylindrical mesh heat pipe reveals that the rise of power input decreases the thermal resistance and inversely increases heat transfer coefficient about 5.54% and 43.16% respectively. Response surface methodology (RSM) has been employed for the investigation of heat pipe experimental data. The significant factors on the various convective heat transfer mechanisms have been identified using the analysis of variance (ANOVA) tool. Finally, the empirical models were developed to forecast the heat transfer mechanisms by regression analysis and validated with experimental data which exposed the models have the best agreement with experimental results.

Numerical investigation of laminar forced convection for a non-Newtonian nanofluids flowing inside an elliptical duct under convective boundary condition

2019 ◽  
Vol 29 (1) ◽  
pp. 334-364 ◽  
Author(s):  
Haroun Ragueb ◽  
Kacem Mansouri
Keyword(s):  
Heat Transfer ◽  
Boundary Condition ◽  
Heat Transfer Coefficient ◽  
Fluid Flow ◽  
Transfer Coefficient ◽  
Convective Boundary Condition ◽  
Bulk Temperature ◽  
Convective Boundary ◽  
Content Type ◽  
The Heat Transfer Coefficient

PurposeThe purpose of this study is to investigate the thermal response of the laminar non-Newtonian fluid flow in elliptical duct subjected to a third-kind boundary condition with a particular interest to a non-Newtonian nanofluid case. The effects of Biot number, aspect ratio and fluid flow behavior index on the heat transfer have been examined carefully.Design/methodology/approachFirst, the mathematical problem has been formulated in dimensionless form, and then the curvilinear elliptical coordinates transform is applied to transform the original elliptical shape of the duct to an equivalent rectangular numerical domain. This transformation has been adopted to overcome the inherent mathematical deficiency due to the dependence of the ellipsis contour on the variables x and y. The yielded problem has been successfully solved using the dynamic alternating direction implicit method. With the available temperature field, several parameters have been computed for the analysis purpose such as bulk temperature, Nusselt number and heat transfer coefficient.FindingsThe results showed that the use of elliptical duct enhances significantly the heat transfer coefficient and reduces the duct’s length needed to achieve the thermal equilibrium. For some cases, the reduction in the duct’s length can reach almost 50 per cent compared to the circular pipe. In addition, the analysis of the non-Newtonian nanofluid case showed that the addition of nanoparticles to the base fluid improves the heat transfer coefficient up to 25 per cent. The combination of using an elliptical duct and the addition of nanoparticles has a spectacular effect on the overall heat transfer coefficient with an enhancement of 50-70 per cent. From the engineering applications view, the results demonstrate the potential of elliptical duct in building light-weighted compact shell-and-tube heat exchangers.Originality/valueA complete investigation of the heat transfer of a fully developed laminar flow of power law fluids in elliptical ducts subject to the convective boundary condition with application to non-Newtonian nanofluids is addressed.

scholarly journals Using artificial neural network for predicting heat transfer coefficient during flow boiling in an inclined channel

2020 ◽  
pp. 238-238
Author(s):  
Adel Bouali ◽  
Salah Hanini ◽  
Brahim Mohammedi ◽  
Mouloud Boumahdi
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Experimental Data ◽  
Artificial Neural Network ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Flow Boiling ◽  
Low Flow ◽  
Inclined Channel ◽  
Artificial Neural

The flow and heat transfer characteristics in a nuclear power plant in the event of a serious accident are simulated by boiling water in an inclined rectangular channel. In this study an artificial neural network model was developed with the aim of predicting heat transfer coefficient (HTC) for flow boiling of water in inclined channel, the network was designed and trained by means of 520 experimental data points that were selected from within the literature. orientation ,mass flux, quality and heat flow which were employed to serve as variables of input of multiple layer perceptron (MLP) neural network, whereas the analogous HTC was selected to be its output. Via the method of trial-and-error, MLP network with 30 neurons in the hidden layer was attained as optimal ANN structure. The fact that is was enabled to predict accurately the HTC. For the training set, the mean relative absolute error (MRAE) is about 0.68 % and the correlation coefficient (R) is about 0.9997. As for the testing and validation set they are respectively about 0.60 % and 0.9998 and about 0.79 % and 0.9996. The comparison of the developed ANN model with experimental data and empirical correlations in vertical channel under the low flow rate and low quality shows a good agreement.

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