Performance predictions of laminar and turbulent heat transfer and fluid flow of heat exchangers having large tube-diameter and large tube-row by artificial neural networks

In this work an artificial neural network (ANN) is used to correlate experimentally determined and numerically computed Nusselt numbers and friction factors of three kinds of fin-and-tube heat exchangers having plain fins, slit fins and fins with longitudinal delta-winglet vortex generators with large tube-diameter and large the number of tube rows. First the experimental data for training the network was picked up from the database of nine samples with tube outside diameter of 18 mm, number of tube rows of six, nine, twelve, and Reynolds number between 4000 and 10,000. The artificial neural network configuration under consideration has twelve inputs of geometrical parameters and two outputs of heat transfer Nusselt number and fluid flow friction factor. The commonly-implemented feed-forward back propagation algorithm was used to train the neural network and modify weights. Different networks with various numbers of hidden neurons and layers were assessed to find the best architecture for predicting heat transfer and flow friction. The deviation between the predictions and experimental data was less than 4%. Compared to correlations for prediction, the performance of the ANN-based prediction exhibits ANN superiority. Then the ANN training database was expanded to include experimental data and numerical data of other similar geometries by computational fluid dynamics (CFD) for turbulent and laminar cases with the Reynolds number of 1000–10,000. This in turn indicated the prediction has a good agreement with the combined database. The satisfactory results suggest that the developed ANN model is generalized to predict the turbulent or/and laminar heat transfer and fluid flow of such three kinds of heat exchangers with large tube-diameter and large number of tube rows. Also in this paper the weights and biases corresponding to the neural network architecture are provided so that future research can be carried out. It is recommended that ANNs might be used to predict the performances of thermal systems in engineering applications, especially to model heat exchangers for heat transfer analysis.     

椭圆管与扁管管板式换热器换热性能的分析比较

本文对椭圆管与扁管管板式换热器的充分发展的周期性层流流动与换热特性进行了数值计算分析,给出了在400相似文献   

Numerical study of turbulent heat transfer in 3D pin-fin channels: Validation of a quick procedure to estimate mean values in quasi-periodic flows

Pin-fin heat exchangers are widely used and there is an increasing interest in the design of compact units. This work investigated the prediction of the heat transfer rate in pin-fin channel flows using numerical simulation, considering pins of cylindrical geometry in aligned and staggered arrangements. The simulations were performed using the Reynolds-averaged Navier–Stokes equations together with the shear stress transport turbulence model. The main purpose of this work was to develop and validate a quick numerical procedure to evaluate the heat transfer rate in pin-fin channel flows using their quasi-steady behavior. The procedure was validated by comparing the mean Nusselt number results with time-averaged Nusselt numbers obtained from transient simulations. It was also shown that these values are in good agreement with available experimental data. This procedure could determine the overall mean Nusselt number up to 25 times faster. The importance of the quasi-steady flow behavior on the heat transfer was also quantified.     

Prediction of convection heat transfer in converging–diverging tube for laminar air flowing using back-propagation neural network

The ability of an artificial neural network (ANN) model for heat transfer analysis in a converging–diverging tube is studied. Back propagation learning algorithm, the most common method for ANNs, was used in training and testing/validation the network. It is trained with selected values of the Reynolds numbers (Re), Prandtl numbers (Pr), half taper angle (θ), aspect ratio (L_cyc/D_max), and Nusselt number (Nu). The trained network is the used to make predictions of the Nusselt numbers. The accuracy between selected data and ANNs results was achieved with a mean absolute relative error less than 1.5%. This shows that well trained neural network model provided fast, accurate and consistent results.     

Heat Transfer Augmentation in Developing Flow Through a Ribbed Square Duct

An experimental study is conducted to investigate the heat transfer augmentation in developing turbulent flowthrough a ribbed square duct.The duct is made of 16mm thick bakelite sheet.The bottom surface of the ribbedwall having rib pitch to height ratio of 10 is heated by passing a c current to the heater placed under it.Theuniform heating is controlled using a digital temperature controller and a variac.The results of ribbed duct arecompared with the results of a smooth duct under the same experimental conditions.It is observed that the heattransfer augmentation in ribbed duct is better than that of the smooth duct.At Re=5.0×10~4,the meantemperature of air flowing through the ribbed duct increases by 2.45 percent over the smooth duct,whereas in theribbed duct Nusselt number increases by 15.14 percent than that of the smooth duct with a 6 percent increase inpressure drop.     

Experimental study of impinging heat transfer along rib-roughened walls by using transient liquid crystal technique

The objective of this work is to examine the detailed heat transfer coefficient distributions over a ribbed surface under impingement of in-line and staggered jet arrays by using a liquid crystal thermograph technique. In-line and staggered jet arrays with different exit flow orientations were considered. Three jet-to-target spacing Z of 3, 6 and 9 with in-line and staggered jet arrays were considered at jet Reynolds numbers of Re = 1500, 3000 and 4500 with three different exit flow orientations. In addition, the effects of rib configuration on the heat transfer distributions were discussed in detail. Results show that the local heat transfer rates over the ribbed surface are characterized by obvious periodic-type variation of Nusselt number distributions. The downstream peaks are diminished for increasing cross flow effect. Compared to the results without ribs, the heat transfer over the ribbed surface may be enhanced or retarded. Whereas, among the test angled-rib arrangements, the best heat transfer performance is obtained with a surface with 45° angled ribs.     

Conjugate heat transfer characterization in cooling channels

Cooling technology of gas turbine blades,primarily ensured via internal forced convection,is aimed towards withdrawing thermal energy from the airfoil.To promote heat exchange,the walls of internal cooling passages are lined with repeated geometrical flow disturbance elements and surface non-uniformities.Raising the heat transfer at the expense of increased pressure loss;the goal is to obtain the highest possible cooling effectiveness at the lowest possible pressure drop penalty.The cooling channel heat transfer problem involves convection in the fluid domain and conduction in the solid.This coupled behavior is known as conjugate heat transfer.This experimental study models the effects of conduction coupling on convective heat transfer by applying iso-heat-flux boundary condition at the external side of a scaled serpentine passage.Investigations involve local temperature measurements performed by Infrared Thermography over flat and ribbed slab configurations.Nusselt number distributions along the wetted surface are obtained by means of heat flux distributions,computed from an energy balance within the metal domain.For the flat plate experiments,the effect of conjugate boundary condition on heat transfer is estimated to be in the order of 3%.In the ribbed channel case,the normalized Nusselt number distributions are compared with the basic flow features.Contrasting the findings with other conjugate and convective iso-heat-flux literature,a high degree of overall correlation is evident.     

不同螺旋角螺旋折流板换热器传热性能对比实验

对螺旋角为8°、12°、18°、30°、40°的螺旋折流板换热器进行了壳程传热性能和压力降测试,得到了相应结构下的总传热系数和压力降。然后通过对试验数据的整理分析,并进行曲线回归,得到了不同螺旋角的螺旋折流板换热器换热系数和压降经验计算公式。研究表明,实验条件下,30°螺旋角的螺旋折流板换热器的单位压降传热系数要优于8°、12°、18°、40°螺旋角的螺旋折流板换热器的传热系数。     

Convective Heat Transfer and Pressure Drop over Elliptical and Flattened Tube

A numerical study on the effect of the effect of elliptical and flattened tube bundle geometry on the convective heat transfer and pressure drop is presented in this article. The analysis has been carried out to evaluate the performance of these bundle geometries in the design of a compact and effective single phase shell and tube heat exchanger. The temperature, velocity, and pressure drop profiles are obtained from solving the mass, momentum, and energy conservation equations. The comparison is made for inline and staggered bundle with different pitch to diameter ratio and inlet velocity for elliptical and flattened tubes. The pitch to diameter ratio is varied from 1.25 to 2.5 for Reynolds number ranging from 200 to 2000 which is in the laminar flow region. The heat transfer coefficient over the staggered and inline tube bundle decrease with an increase in pitch. The same kind of variation is also observed for the pressure drop in the case of both elliptical and flattened tube bundle. The study shows that the transverse pitch with respect to cross flow affects more than the longitudinal pitch.     

Prediction of Heat Transfer Rates for Shell-and-Tube Heat Exchangers by Artificial Neural Networks Approach

This work used artificial neural network(ANN)to predict the heat transfer rates of shell-and-tube heatexchangers with segmental baffles or continuous helical baffles,based on limited experimental data.The BackPropagation (BP) algorithm was used in training the networks.Different network configurations were alsostudied.The deviation between the predicted results and experimental data was less than 2%.Comparison withcorrelation for prediction shows ANN superiority.It is recommended that ANN can be easily used to predict theperformances of thermal systems in engineering applications,especially to model heat exchangers for heattransfer analysis.     

Investigation of heat transfer and pressure drop in a concentric heat exchanger with snail entrance

In this study, in order to increase heat transfer in concentric double-pipe heat exchangers by passive method, snail which is mounted at inlet of the inner pipe and assumed as a swirl generator was used. In the experimental set-up, cold air in ambient conditions was passed through the inner pipe while hot water was flowing through the annulus. The effects of a snail on the heat transfer and pressure drop were investigated for parallel and counter-flow, and obtained Nusselt numbers (Nu) were compared with those found, using a standard correlation such as Dittus–Boelter equation given for axial flows in smooth pipes. The results were correlated in the form of Nusselt number as a function of Reynolds number, Prandtl number and the swirling angle. An augmentation of up to 120% in Nusselt number was obtained in the swirl flow for counter-flow and 45° swirling angle. Though the swirl flow effect of the snail caused some increase in pressure drop, this effect was unimportant compared with the improvement in heat transfer capacity.     

Numerical investigation of fluid flow and heat transfer over louvered fins in compact heat exchanger

Numerical investigation of fluid flow and heat transfer characteristics over louvered fins and flat tube in compact heat exchangers is presented in this study. Three-dimensional simulations of single and double row tubes with louvered fins have been conducted. Simulations are performed for different geometries with varying louver pitch, louver angle, fin pitch and tube pitch and for different Reynolds number. Conjugate heat transfer and conduction through the fins are considered. The air-side performance of heat exchanger is evaluated by calculating Stanton number and friction factor. The results are compared with experiment and a good agreement is observed. The local Nusselt number variation along the top surface of the louver is calculated and effects of geometrical parameters on the average heat transfer coefficient is computed. Design curves are obtained which can used to predict the heat transfer and the pressure drop for a given louver geometry.     

Artificial neural network modeling of nanofluid flow in a microchannel heat sink using experimental data

The present paper deals with the artificial neural network modeling (ANN) of heat transfer coefficient and Nusselt number in TiO₂/water nanofluid flow in a microchannel heat sink. The microchannel comprises of 40 channels; each channel has a length of 4 cm, a width of 500 μm, and a height of 800 μm. In the ANN modeling of heat transfer coefficient and Nusselt number 23 and 72 datasets have been used, respectively. The experimental Nusselt number has been calculated based on three different thermal conductivity models, four volume fractions of 0, 0.5, 1, and 2%, two values of Reynolds number i.e. 400 and 1200 and three different heating rates including 50.6, 60.7, and 69.1 W. Therefore, the inputs that are introduced to the neural network are volume fraction of nanoparticles, Reynolds number, heating rate, and model number while the output of network is the Nusselt number. It is elucidated that an appropriately trained network can act as a good alternative for costly and time-consuming experiments on the nanofluid flow in microchannels. The average relative errors in the prediction of Nusselt number and heat transfer coefficients were 0.3% and 0.2%, respectively.     

Experiments on the characteristics of evaporation of R410A in brazed plate heat exchangers with different geometric configurations

Experiments on the evaporative heat transfer and pressure drop in the brazed plate heat exchangers were performed with refrigerants R410A and R22. The plate heat exchangers with different 45°, 35°, and 20° chevron angles are used. Varying the mass flux of refrigerant (13–34 kg/m² s), the evaporating temperature (5, 10 and 15 °C), the vapor quality (0.9–0.15) and heat flux (2.5, 5.5 and 8.5 kW/m²), the evaporation heat transfer coefficients and pressure drops were measured. The heat transfer coefficient increases with increasing vapor quality and decreasing evaporating temperature at a given mass flux in all plate heat exchangers. The pressure drop increases with increasing mass flux and quality and with decreasing evaporating temperature and chevron angle. It is found that the heat transfer coefficients of R410A are larger than those of R22 and the pressure drops of R410A are less than those of R22. The empirical correlations of Nusselt number and friction factor are suggested for the tested PHEs. The deviations between correlations and experimental data are within ±25% for Nusselt number and ±15% for friction factor.     

Numerical evaluation and the effects of geometrical and operational parameters on thermal performance of the shell and double coil tube heat exchanger

Heat exchangers are extensively used in various industries. In this study, the impact of geometric and flow parameters on the performance of a shell and double helical coil heat exchanger is studied numerically. The investigated geometric parameters include external coil pitch, internal coil pitch, internal coil diameter, and coil diameter. The influences of considered geometrical parameters are analyzed on the output temperature of the hot and cold fluid, convective heat transfer coefficient, pressure drop, and average Nusselt number. Water is considered as working fluid in both shell and tube. As an innovation, double helical coils are used instead of one in the heat exchanger. To compare the obtained results accurately, in each section, the heat transfer area (coil outer surface) is kept constant in all models. The results show that the geometrical parameters of double helical coils significantly affect the heat transfer rate.     

Heat transfer,pressure drop,and fluid flow patterns in yawed tube banks

Complementary heat transfer, pressure distribution, and flow visualization experiments were performed to investigate the effect of yaw on both staggered and in-line tube tanks. The heat transfer measurements were carried out on a row-by-row basis, and pressures were measured internal to the tube banks as well as upstream and downstream. Air was the heat transfer fluid. The visualization experiments revealed that yaw markedly affected the manner in which the flow impinged on the tubes of the in-line array, with a lesser effect of yaw on the flow field in the staggered array. At a given freestream Reynolds number, the Nusselt number generally decreased as the angle of yaw increased. The yaw effect was well correlated for the staggered array, but not so well for the in-line array because of the aforementioned flow field modifications. The in-line-array Nusselt numbers generally exceeded those for the staggered array, a trend which was accentuated at larger yaw. The pressure drop decreased with increasing yaw. In the present operating range, the in-line-array pressure drops were smaller than the corresponding staggered-array values.     

Compact potential of exhaust heat exchangers for engine waste heat recovery using metal foams

To improve the practicability of the waste heat recovery system for internal combustion engines, the compact potential of exhaust heat exchangers using metal foams is investigated. In the present study, the performance of compact exhaust heat exchangers is compared with that of a conventional shell and tube heat exchanger in a real test bench. Both heat transfer and pressure drop performance are considered when assessing the performance of heat exchangers because these two factors normally show a trade‐off relationship when designing exhaust heat exchangers. Compared with the conventional heat exchanger, the compact heat exchanger can achieve a similar pressure drop, and at the same time the heat transfer is increased by 30%, whereas the volume and the weight are each reduced by 2/3. The performance of compact heat exchangers with six types of Ni metal foams is also investigated under different mass flow rates and thicknesses of the porous layer. Results show that the optimum compact heat exchanger enhances the comprehensive performance 1.9 times compared with original one. This study shows that metal foams have great potential in realizing a compact exhaust heat exchanger for engine waste heat recovery.     

Experimental investigation of the influence of the cross flow in the nozzle region on the shell-side heat transfer in double-pipe heat exchangers

In shell-and-tube heat exchangers, the shell-side fluid flow enters and leaves through nozzles which are mounted on the shell wall. The cross-flow in the nozzle region has an impact on the shell-side pressure drop and heat transfer. The influence on the heat transfer is investigated by means of experiments with four double-pipe heat exchangers.The results show that the influence is greater, the shorter the heat exchangers are, and the smaller the ratio of the free cross sectional areas of the nozzle to that of the shell-side. A correlation suitable for predicting the heat transfer coefficient is presented in this paper. The correlation consists of the Nusselt number for the flow in the nozzle region and that for the flow in the annulus.     

Experimental investigation of turbulent flow and convective heat transfer characteristics of alumina water nanofluids in fully developed flow regime

In this paper the convective heat transfer and friction factor of the nanofluids in a circular tube with constant wall temperature under turbulent flow conditions were investigated experimentally. Al₂O₃ nanoparticles with diameters of 40 nm dispersed in distilled water with volume concentrations of 0.1–2 vol.% were used as the test fluid. All physical properties of the Al₂O₃–water nanofluids needed to calculate the pressure drop and the convective heat transfer coefficient were measured. The results show that the heat transfer coefficient of nanofluid is higher than that of the base fluid and increased with increasing the particle concentrations. Moreover, the Reynolds number has a little effect on heat transfer enhancement. The experimental data were compared with traditional convective heat transfer and viscous pressure drop correlations for fully developed turbulent flow. It was found that if the measured thermal conductivities and viscosities of the nanofluids were used in calculating the Reynolds, Prandtl, and Nusselt numbers, the existing correlations perfectly predict the convective heat transfer and viscous pressure drop in tubes.     

Predicting and optimizing the heat transfer performance of radiator with functionalized graphene nanofluids

Accurately predicting the heat transfer characteristics of coolants used in thermal management of energy systems like heat exchangers, power electronics, and heating, ventilation, and air conditioning is indispensable in maintaining its operating conditions within safety limits. Apart from safety, factors such as power consumption and operating cost are the most important constraints to be considered in designing an energy-efficient and cost-effective cooling solution. In this study, the experimental data available from previous research on the use of functionalized graphene-based nanofluids in compact heat exchangers such as the automotive radiator is used to optimize the heat transfer performance parameters like Nusselt number of the nanofluid, the friction factor, and effectiveness of the heat exchanger. A supervised machine learning technique like the artificial neural network is used to obtain the objective functions of the response variables in terms of input features such as Reynolds number, Prandtl number, the volume concentration of nanoparticles in the base fluid, number of transfer units, heat capacity, the density of nanofluid, pressure drop and velocity. On the current dataset, it is found that by using the Bayesian regularization training algorithm and tangent sigmoidal activation function in the neural network, the best accuracies in the prediction can be achieved. Well-known nature-inspired optimization algorithms like genetic algorithms and simulated annealing are used in optimizing the above-mentioned response variables. Both algorithms converged to the same values of the objective functions. The optimum values of Nusselt number, effectiveness, and friction factor are 105.65, 0.506, and 0.0038, respectively, for the given composition of the nanofluid and radiator configuration.