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.

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.

Numerical investigations of unsteady passing wake effects on turbine blade tip aerothermal performance with different tip clearances

2019 ◽  
Vol 30 (2) ◽  
pp. 792-817
Author(s):  
Bo Zhang ◽  
Xiaoqing Qiang ◽  
Shaopeng Lu ◽  
Jinfang Teng
Keyword(s):  
Heat Transfer ◽  
High Pressure ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Rotor Blade ◽  
Guide Vane ◽  
Heat Transfer Characteristics ◽  
High Pressure Turbine ◽  
Content Type ◽  
Blade Tip

Purpose The purpose of this paper is to numerically investigate the effect of guide vane unsteady passing wake on the rotor blade tip aerothermal performance with different tip clearances. Design/methodology/approach The geometry and flow conditions of the first stage of GE-E3 high-pressure turbine have been used to obtain the blade tip three-dimensional heat transfer characteristics. The first stage of GE-E3 high-pressure turbine has 46 guide vanes and 76 rotor blades, and the ratio of the vane to the blade is simplified to 38:76 to compromise the computational resources and accuracy. Namely, each computational domain comprises of one guide vane passage and two rotor blade passages. The investigations are conducted at three different tip gaps of 1.0, 1.5 and 2.0 per cent of the average blade span. Findings The results show that the overall discrepancy of the heat transfer coefficient between steady results and unsteady time-averaged results is quite small, but the dramatic growth of the instantaneous heat transfer coefficient along the pressure side is in excess of 20 per cent. The change of the aerothermal performance is mainly driven by turbulence-level fluctuations of the unsteady flow field within gap regions. In addition, the gap size expansion has a marginal impact on the variation ratio of tip unsteady aerothermal performances, even though it has a huge influence on the leakage flow state within the tip region. Originality/value This paper emphasizes the change ratio of unsteady instantaneous heat transfer characteristics and detailed the mechanism of blade tip unsteady heat transfer coefficient fluctuations, which provide some guidance for the future blade tip design and optimization.

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.

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.

Forced Convection Heat Transfer of Nanofluids: A Review

2017 ◽  
Author(s):  
Aditya Kuchibhotla ◽  
Debjyoti Banerjee
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Thermal Conductivity ◽  
Heat Capacity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Specific Heat ◽  
Forced Convection ◽  
Convection Heat Transfer ◽  
Convection Heat

Stable homogeneous colloidal suspensions of nanoparticles in a liquid solvents are termed as nanofluids. In this review the results for the forced convection heat transfer of nanofluids are gleaned from the literature reports. This study attempts to evaluate the experimental data in the literature for the efficacy of employing nanofluids as heat transfer fluids (HTF) and for Thermal Energy Storage (TES). The efficacy of nanofluids for improving the performance of compact heat exchangers were also explored. In addition to thermal conductivity and specific heat capacity the rheological behavior of nanofluids also play a significant role for various applications. The material properties of nanofluids are highly sensitive to small variations in synthesis protocols. Hence the scope of this review encompassed various sub-topics including: synthesis protocols for nanofluids, materials characterization, thermo-physical properties (thermal conductivity, viscosity, specific heat capacity), pressure drop and heat transfer coefficients under forced convection conditions. The measured values of heat transfer coefficient of the nanofluids varies with testing configuration i.e. flow regime, boundary condition and geometry. Furthermore, a review of the reported results on the effects of particle concentration, size, temperature is presented in this study. A brief discussion on the pros and cons of various models in the literature is also performed — especially pertaining to the reports on the anomalous enhancement in heat transfer coefficient of nanofluids. Furthermore, the experimental data in the literature indicate that the enhancement observed in heat transfer coefficient is incongruous compared to the level of thermal conductivity enhancement obtained in these studies. Plausible explanations for this incongruous behavior is explored in this review. A brief discussion on the applicability of conventional single phase convection correlations based on Newtonian rheological models for predicting the heat transfer characteristics of the nanofluids is also explored in this review (especially considering that nanofluids often display non-Newtonian rheology). Validity of various correlations reported in the literature that were developed from experiments, is also explored in this review. These comparisons were performed as a function of various parameters, such as, for the same mass flow rate, Reynolds number, mass averaged velocity and pumping power.

Leading-Edge Film-Cooling Physics: Part II — Heat Transfer Coefficient

2002 ◽  
Author(s):  
William D. York ◽  
James H. Leylek
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Film Cooling ◽  
Leading Edge ◽  
Numerical Predictions ◽  
Validation Experiment ◽  
Computational Methodology ◽  
Near Wall

A comprehensive study of film cooling on a turbine airfoil leading edge was performed with a documented, well-tested computational methodology. In this paper, numerically predicted heat transfer coefficients on the film-cooled leading edge are compared with experimental data from the open literature. The results are presented as the ratio of heat transfer coefficient with film cooling to that without film cooling, and the physics behind the surface results are discussed. The leading edge model was a half-cylinder in shape with a bluff afterbody to match the validation experiment, and other geometric parameters matched those of Part I of this study. Coolant at a density equal to that of the mainstream flow was injected through three rows of cylindrical film-cooling holes. One row of holes was centered on the stagnation line of the cylinder, and the other two rows were located ±3.5 hole diameters off stagnation. The downstream rows were staggered such that they were centered laterally between holes in the stagnation row. The holes were inclined at 20° with the surface, and made a 90° angle with the streamwise direction (radial injection). Four average blowing ratios were simulated in the range of 0.75 to 1.9, corresponding to the same momentum flux ratios as in Part I of this work. The multi-block, unstructured numerical grid was characterized by high quality and density, especially in the near wall region, in order to minimize error in predictions of the heat transfer. A fully-implicit scheme was used to solve the steady Reynolds-averaged Navier-Stokes equations, and a realizable k-ε model provided turbulence closure. A two-layer near-wall treatment allowed the resolution of the viscous sublayer for maximum accuracy in the prediction of the wall heat transfer coefficient. The numerical predictions exhibited generally good agreement with experimental data. The heat transfer coefficient was observed to increase sharply aft of the holes in the downstream rows. When coupled with the adiabatic effectiveness results of the first paper in this series, it is evident that a systematic computational methodology may be effectively applied to investigate and understand the complicated leading edge film-cooling problem.

A Critical Review on the Determination of Convective Heat Transfer Coefficient 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 ◽  
Convective Heat Transfer Coefficient ◽  
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.

Sign in / Sign up

Export Citation Format

Share Document