Prediction Of Heat Transfer Rate Research Articles

Predicting heat transfer rate and system entropy based on combining artificial neural network with numerical simulation

PurposeThe purpose of this paper is to present numerical simulations for magnetohydrodynamics natural convection of a nanofluid flow inside a cavity with an H-shaped obstacle based on combining artificial neural network (ANN) with the finite element method (FEM), and predict the heat transfer rate and system entropy.Design/methodology/approachThe enclosure is assumed to be inclined. Changing the inclination angle results in a different obstacle shape, which affects the buoyancy force. Hence, different configurations of the contours of the fluid flow, isotherms and the entropy of the system are obtained. The outer walls of the cavity as well as the central part of the obstacle are kept adiabatic. The left vertical portion of the hindrance is cooled, whereas the right vertical part of the obstacle is a heated wall. Using dimensionless variables allows obtaining a dimensionless version of the governing system of equations that is solved via the consistency FEM. The coupled problem of pressure and velocity is overcome via the Increment Pressure Correction Scheme, which is known for its accuracy and stability for similar simple problems. A numerical computation is performed across a broad range of the governing parameters. A total of 304 data sets were used in the development of an ANN model. That data set was conducted from the numerical simulations. The data set underwent optimization, with 70% sets used for training the model, 15% for validation and another 15% for the testing phase. The training of the network model used the Levenberg–Marquardt training algorithm.FindingsFrom the numerical simulations, it is concluded that the H-shaped obstacle boosts heat transfer rate in comparison with the I-shaped case. Also, raising the value of the inclination angle improves the entropy of the system presented by the Bejen number. Furthermore, strength heat transfer rate is obtained via decreasing the Hartmann number while this decrease decays the values of the Bejen number for both positive and negative amounts of the nonlinear Boussinesq parameter. Slower velocity and a better heat transfer rate characterize nanofluid compared with pure fluid. Leveraging the capabilities of the ANN, the developed model adeptly forecasts the values of both the average Nusselt and Bejen numbers with a high degree of accuracy.Originality/valueA novel fusion of FEM and ANN has been tailored to forecast the heat transfer rate and system entropy of MHD natural convective flow within an inclined cavity containing an H-shaped obstacle, amid various physical influences.

Investigation of Hydrodynamics Characteristics of Fluidized Bed with back propagation Artificial Neural Network (BPANN)

Correlations have also been developed with system parameters by using dimensional analysis and an artificial neural network approach. The paper describes an investigation for the thermal design of a fluidized bed cooler and prediction of heat transfer rate among the media categories. It is devoted to the thermal design of such equipment and their application in the industrial fields. In the present work, an extensive ANN by using back propagation (BP) has been carried out to correlate the expansion ratio, fluctuation ratio in gas-solid fluidized bed. Back propagation network is the most well-known and widely used among the current types of neural network system, several applications of ANN for modeling of nonlinear process systems and subsequent control were reported. In back-propagation, different ANN structures (I×H×O) with varying number of neurons in the hidden layer were used as a tool for training input and output data for prediction value of hydrodynamic characteristics of the bed system. It was noted that ring models are the best ones in reducing bed expansion ratio and fluctuation ratio around (25%) and (23.22%).

Effect of soil moisture content on thermal performance of ground source heat exchangers: An electromagnetism topology-based analysis

Ground source heat pump (GSHP) technology has gained significant attention as a viable solution for the heating, ventilation, and air conditioning (HVAC) of buildings. One of the factors that can impact the performance of GSHP systems is the soil moisture content. In this study, an innovative approach, referred to as soil impedance topology, is introduced as an alternative to traditional methods for measuring soil moisture content in geothermal heat pump systems. This method is inspired by pipeline grid utilizes impedance measurement, which provides a direct measurement of soil moisture content without the need for sensors. The study also proposes a changing rule of impedance with varying moisture content, where capacitance increases and resistance decreases when the soil moisture content is less than 20% but stabilizes beyond a water content of 20%. The accuracy of the topological mechanism prediction method is high, as demonstrated through the verification of the Smith circle and measured data. However, it is noted that the performance may be insufficient in the high frequency band and high soil moisture content. The use of impedance topology provides a more accurate and reliable method for measuring soil moisture content as well as for modeling and predicting heat transfer rates and system performance. This technology has strong potential to improve efficiency, reduce energy costs, and enhance the environmental sustainability of geothermal heat pump systems.

Heat transfer rate prediction and performance optimization of CO2 air cooler in refrigeration system

In order to determine the heat transfer rate of CO2, heat transfer criterion equations were selected and validated using experiment data. The impacts of various operating conditions and structural parameters on CO2 air coolers were numerical simulation investigated. The results show that the inlet dryness and mass flow rate are proportional to heat transfer coefficient (HTC) and pressure drop (PD). When the mass flow reaches 240 kg/h, CO2 reaches the critical state, and further increasing the mass flow rate has little effect on the HTC. The HTC reaches its maximum value at a dryness of 0.2, after which, it decreases due to the flow pattern changing from wavy/intermittent flow to annular flow. Moreover, the tube spacing, tube diameter, and fin spacing affect the HTC, heat exchange area, and heat exchange capacity differently. Hence, a thoroughly consideration of the structural parameter design is crucial during the actual design process.

A new moving-boundary algorithm to predict heat transfer rate of counter-flow water-cooled transcritical CO2 gas cooler

A new moving-boundary model was proposed for predicting steady-state heat transfer rate of water-cooled transcritical CO2 gas cooler. The new model aims to separate the CO2 gas cooler into up to three zones depending on the local thermal capacitance rate, which is significantly different from the moving-boundary models used in subcritical region, which is based on fluid phase. The experimental data from the literature were used for model validation, and the results show that the prediction accuracy of the new moving-boundary model is comparable to that of the finite volume method. The deviations between predicted and measured heating capacities are within ±5%, and the predicted CO2 outlet temperatures are within ±4°C. The averaged computation time of the model is 22% of that of the finite volume model for the 45 data points in the present study. The proposed new model is suitable for steady-state simulation of transcritical CO2 water-cooled gas cooler, either standalone or integrated into overall CO2 heat pump water heater systems.

Simulation model of boiling heat transfer and flow maldistribution in parallel mini-channels heated unequally

• Focus on boiling flow in parallel mini-channels heated unequally. • Developed model predicts boiling heat transfer and flow maldistribution. • Unequal heating among channels causes deterioration of heat transfer rate. • Considering the wall temperature distribution across the channels is important. Heat exchangers using parallel refrigerant mini-channels have been developed recently to improve the performance of air conditioning systems. Due to the unequal heat loads among channels, the boiling flow is unevenly distributed across parallel mini-channels in evaporators. Because this phenomenon sometimes causes deterioration of the heat exchange performance and difficulty in performance prediction, thus, it is essential to understand the characteristics of boiling heat transfer under unequally heated conditions. In this study, a novel simulation model was developed to predict the heat transfer characteristics and flow maldistribution of refrigerants flowing in parallel mini-channels with different heat fluxes or wall temperatures among channels. The model predicted well the flow maldistribution and the local quality, heat transfer coefficient, and dryout region of the two parallel mini-channels heated unequally. The mean heat transfer rate of the channels decreased remarkably with the increasing difference in wall temperature between the channels. The validity of the model was confirmed by comparing the predicted heat transfer rate with the experimental results. Furthermore, for ten parallel mini-channels, the decrease in the channel-mean heat transfer rate was indicated by the model, and the rate of decline varied significantly depending on the wall temperature distribution across the channels.

An investigation on dehumidification and heat transfer characteristics of a minichannel heat exchanger for heat pump system of electric vehicles

Heat pump systems for electric vehicles must assure the system's energy efficiency and the comfort and safety of the passenger cabin. This project aims to analyze the dehumidification and heat transfer characteristics of a heat exchanger through experiments and theoretical modeling. In this paper, a parallel flow minichannel heat exchanger was experimentally and theoretically studied under various operating conditions. A distributed parameter model considering heat and mass transfer was developed and utilized to predict the heat exchanger's dehumidification and heat transfer characteristics. The results reveal that, with a fixed inlet air relative humidity and a low refrigerant mass flow rate, the dehumidification rate (DHR) increases and subsequently declines with the increasing inlet airflow. When the inlet air relative humidity and inlet airflow are constant, the lower the refrigerant mass flow rate, the greater the enthalpy humidity ratio. As the inlet airflow increases, the refrigerant mass flow rate and inlet air relative humidity stay constant, and the enthalpy humidity ratio rises. The proposed model's predictions match the experimental data rather well. The predicted heat transfer rates (HTRs) and DHRs have absolute errors of less than 4% and 10%, respectively, compared with the experimental results. Under various airflows for the OM3 operating conditions, the distributions of HTR and DHR demonstrate that the HTR percentage is lowest in flow path IV, no dehumidification is conducted in flow path IV, and the DHR percentage is largest in flow path II. The proposed model may be employed to assess the dehumidification and heat transfer performance of heat exchangers and optimize the design of heat exchangers in similar heat pump systems. Highlights Construct a test bench for the dehumidification and heat transfer performance evaluation of a minichannel evaporator. Analyze and discuss the dehumidification and heat transfer characteristics of the evaporator under different operating conditions. Develop a distributed parameter model of dehumidification and heat transfer for the evaporator.

Out-of-sample validation of a general correlation for steam condensation in the presence of air over a vertical slender tube in turbulent free convection

In a previous work [Dehbi, 2015], a general correlation was proposed for the prediction of steam condensation rates in the presence of air over vertical flat surfaces in turbulent free convection. Because most of the heat transfer data were obtained from tube condenser tests, the Popiel [2008] correction for curvature was employed to transfer results to flat plate surfaces. Popiel’s correlation is valid for laminar flows, and hence, as shown in subsequent investigations [Dehbi, 2021], it predicts mostly lower values for the curvature correction factors if applied to turbulent flows. Hereafter, we first revisit the flat surface correlation presented in [Dehbi, 2015] and update its form based on the more accurate curvature correction given in [Dehbi, 2021]. The updated flat plate correlation, along with the curvature correction, is subsequently used to predict heat transfer rates in five experiments conducted recently on slender vertical tubes, covering tube diameters from 12 mm to 38.1 mm, steam mass fraction from 0.2 to 0.90, wall temperature subcooling from 4 K to 120 K, and pressures from 1 to 16 bars. It is demonstrated that the general correlation provides very good out-of-sample predictions of the data, with a standard deviation of 13.3 %, which is typical of experimental uncertainty.

Impact of Uncertainty on Prediction of Supercritical CO2 Properties and Nusselt Numbers

Abstract The impact of measurement uncertainty on Nusselt number correlations for supercritical CO2 is investigated. Selection of appropriate reference quantities for these correlations, such as thermal conductivity, appears to have a large effect on accurately predicting heat transfer rates. Supercritical CO2 work heavily depends on real fluid property data, which show that fluid properties have very large gradients with respect to temperature and pressure near the critical point. The sharp gradients imply heat transfer predictions are highly sensitive to the accuracy of temperature and pressure experimental measurements in this region. Root sum of squares uncertainties at various property values indicate predictably large (on the order of 1000%) uncertainties in calculated Reynolds, Prandtl, and Nusselt numbers near the critical point. Interestingly, uncertainties remain several times the calculated value for operating pressures between 7.5 and 8.5 MPa, which are common in the experimental literature—highlighting a need for careful application of correlations near the pseudocritical line and the benefits of presenting dimensional data in the literature.

A comparative study of various machine learning methods for performance prediction of an evaporative condenser

Evaporative condensers are regarded as highly-efficient and eco-friendly heat exchangers in refrigeration systems. Data-driven methods can play a key role in performance prediction of evaporative condensers, conducted without the complexity of theoretical analysis. In this study, four machine learning models including multi-layer perceptron artificial neural network (ANNMLP), support vector regression (SVR), decision tree (DT), and random forest (RF) models have been employed to predict heat transfer rate and overall heat transfer coefficient of a small-scale evaporative condenser functioning under a wide range of working conditions. A set of experimental tests were conducted, where inlet air dry/wet-bulb temperatures, spraying water and condenser saturation temperatures, refrigerant, and air flow rates were considered as main influencing parameters. The results show that the ANNMLP followed by SVR, and RF models possess the best generalization capability. Further, the dataset size analysis indicates that SVR is the best model to predict heat transfer rate for small dataset sizes. Additionally, feature importance analysis by the RF model reveals that refrigerant flow rate is the most influencing parameter.

An Investigation on Dehumidification and Heat Transfer Characteristics of a Minichannel Heat Exchanger for Heat Pump System of Electric Vehicles

In this paper, a parallel flow minichannel heat exchanger was experimentally and theoretically studied under various operating conditions. A model of heat and mass transfer was developed and utilized to predict the dehumidification and heat transfer performance of the heat exchanger. The results show that under the operating condition of a low refrigerant mass flow rate, the dehumidification rate increases and then decreases with the increasing inlet airflow with a constant inlet air relative humidity. The lower the refrigerant mass flow rate, the higher the enthalpy humidity ratio when the inlet air humidity and inlet airflow are constant. As the refrigerant mass flow rate and the inlet air relative humidity remain unchanged, the enthalpy humidity ratio decreases as the inlet airflow increases. The results predicted by the proposed model agree well with the experimental results. The absolute errors of the predicted heat transfer rate and dehumidification rate concerning the experimental results are within ±4% and ±10%, respectively. The presented model can be employed for the evaluation of dehumidification and heat transfer performance of heat exchangers for the design and optimization of similar heat pump systems and their components.

Predicting heat transfer rate of a ribbed triple-tube heat exchanger working with nanofluid using neural network enhanced by advanced optimization algorithms

Eight optimizer methods are combined with a perceptron neural network to achieve an optimal network and minimize errors for predicting the heat transfer rate of a ribbed triple-tube heat exchanger operating with the graphene nanoplatelets-based nanofluid. The optimization techniques consist of Harris Hawks Optimizer (HHO), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Ant Lion Optimizer (ALO), Biogeography-Based Optimization (BBO), and Dragonfly Algorithm (DA). The required data are provided with the aid of numerical simulations. The structural parameters are considered using different rib pitches and heights. The ALO algorithm is the best method for estimating the output. The best performance of this algorithm is gained by population size of 350. By this method, the heat transfer rate is estimated with the Root Mean Square Error (RMSE) values of about 0.0310 and 0.0385 for the training and testing data samples, respectively.

Heat transfer characteristics of flame jet impingement with methane air reaction environment

Abstract The high heat transfer rate achieved in flame impingement technique makes it suitable for various industrial heating operations which demands rapid heating. The geometric parameters of flame jet impingement has significant effect on heat transfer rate. One of these parameters is h/d (h is distance between flame emission nozzle and base plate while d is diameter of nozzle) which has significant effect on heat transfer rate. The current research investigates the effect of this geometric parameter i.e., h/d using techniques of Computational Fluid Dynamics. The CAD model of flame jet computational domain of different h/d ratio (1.2, 1.6, 2, and 2.4) is developed in Creo design software and CFD analysis is conducted using ANSYS CFX software package. Eddy dissipation model is used for combustion modelling and RNG k-epsilon model is used for turbulence. The temperature plot and heat flux plot generated from analysis predicted heat transfer rate at stagnation point.

Flow and heat transfer of impinging jet array associated with entrained air ducts

The purpose of this research was to investigate experimentally and numerically the effects of an impinging jet array with entrained air ducts on heat transfer. Straight pipes with 17.2 mm inner diameter (d) and 300 mm length (l) were in a 5 × 5 nozzle array with in-line configuration. The length of air duct (L) was varied among L/d = 2, 4, or 6, and the diameter of the duct (D) satisfied D/d = 2, 4, or 6. The jet-to-surface distance (H) was tested at H/d = 4, 6, or 8; and the jet-to-jet spacing (S) was among S/d = 4, 6, or 8. Reynolds number (Re) in the jets was from 10,000 to 40,000. Conventional impinging jets were also examined for benchmarking. Flow characteristics obtained numerically from v2f turbulence model were also presented to explain the heat transfer mechanisms. The results indicated that heat transfer rates on the target surface became higher when the duct was elongated, and was more widely spread when the duct diameter was expanded. These effects were more marked in cases with narrow jet-to-jet spacing (S/d = 4) and with large jet-to-surface distance (H/d = 8). Moreover, a heat transfer correlation was constructed from the experimental results to predict heat transfer rates within the studied ranges of parameters.

An experiment and three-dimensional numerical simulation of pulsating heat pipes

An experimental and analytical study of pulsating heat pipe (PHP) has been carried out in order to develop a more reliable numerical simulation model. The test PHP was made of transparent Pyrex tubes with the inner diameter of 1.85mm and a total of sixteen tubes formed eight turns of PHP. Both heating and cooling were provided by water jackets in which inlet and outlet temperatures were precisely measured for estimating heat transfer rate. The working fluid was R123. Visualization using a high-speed camera showed various flow patterns as well as the fluid motions. The wall temperature measured at various locations revealed its relation to the fluid motion and the direction of circulation. The circulation motion was dominant in most tests. The heat transfer rate was measured and the difference for filling ratio of 50 and 60% was little. A three-dimensional computational fluid dynamics modeling has been developed for pulsating heat pipe using ANSYS Fluent. The VOF model with variable density and vapor pressure relation successfully simulated the circulating motions of PHP. The predicted wall temperatures showed the same indication of mode of flow motion and the flow direction as observed in the experiment. The predicted heat transfer rates agreed well with the experimental data within 5%. The success of the simulation of the experiment implies that the realizable k−ε turbulence model is appropriate to PHP simulation and the use of variable density for liquid and vapor and the vapor pressure equation is crucial.

Modelling of the cooling process of steel tubes in a rake type cooling bed

Despite the fact that production speed in a hot tube rolling facility is highly dependent on effective cooling of the output product, the mechanisms of the heat transfer in cooling beds are only addressed in few experimental and numerical studies. As a result, industry calls for a mathematical model, which is capable of predicting heat transfer rates and temperatures for the transient cooling process of steel tubes in a rake type cooling bed. Compared to current state-of-the-art approaches, the present work takes a major modification into account: Horizontal spacing between the tubes, Sh/D, was identified as having a significant impact on the heat transfer. Its influence on natural convection and radiation was investigated in CFD simulations on a horizontal cylinder array for Rayleigh numbers in the range of 104⩽Ra⩽108. Based on the results of the numerical investigation, correction functions for the heat transfer in existing correlation equations were introduced. In the range of 1.25⩽Sh/D⩽3.0, convective heat transfer in the tube array increases by up to 9.91% compared to an individual tube, while heat transfer due to radiation decreases by up to 25.39%.

Improving combustion chamber heat transfer correlation of an HCCI engine in order to achieve a more accurate thermodynamic model

An appropriate heat transfer rate prediction for an internal combustion engine is important from many perspectives. This study investigates the appropriate coefficients of heat transfer correlation and provides a new method for calculating the convective heat transfer coefficient of combustion chamber walls of an HCCI engine. Therefore, a thermodynamic code including the combustion and heat transfer processes, which are coupled with an optimization algorithm, is used to estimate P-θ behavior of an HCCI engine. Double-Wiebe function and Woschni correlations are applied for combustion and heat transfer respectively in a single-zone model. The results show that the use of heat transfer correlation without improvement in coefficients and exponents for different engines, leads to significant errors in the prediction of in-cylinder pressure. Comparison of computational results with the experimental data shows that original Woschni correlation in the single-zone model cannot predict in-cylinder pressure appropriately. Modifications made in this paper resulted in a change of more than 40% in some coefficients of the existing heat transfer correlation, to provide accurate prediction of the engine thermodynamic behavior of an HCCI engine.

Teaching learning optimization and neural network for the effective prediction of heat transfer rates in tube heat exchangers

Heat exchangers are widely used in many field for the purpose of heat from one medium to another. In heat exchanger one or more fluids are used, and which are various types based on its flow and construction. Design of heat exchanger is one of the important field, in the research due to its application. In recent decade the simulation is used in most of the engineering application. A proper simulation technique can effectively analysis the functionality and behavior of any machine before its construction or production. In this sense the machine learning techniques are used in some simulation analysis to model the machine or engine. In this work we used a hybrid neural network for the modeling of shell and tube type heat exchanger and its heat transfer rate is predicted effectively. The computational performance of the proposed technique is compared with the conventional technique and it is proved the effectiveness of the hybrid machine learning technique.

Simulation of Drop-Size Distribution During Dropwise and Jumping Drop Condensation on a Vertical Surface: Implications for Heat Transfer Modeling.

Accurate models for condensation heat transfer are necessary to improve condenser design. Drop-size distribution is an important aspect of heat transfer modeling that is difficult to measure for small drop sizes. The present work uses a numerical simulation of condensation which incorporates the possibility of coalescence and coalescence-induced jumping over a range of drop sizes. Results of the simulation are compared with previous theoretical models and the impact of the assumptions used in those models is explored. In particular, previous drop-size distribution models may predict heat transfer rates less accurately for high contact angles and for coalescence-induced jumping since coalescence occurs over a range of drop sizes and does not always result in departure. The influence of various input parameters (nucleation site distribution approach, nucleation site density, contact angle, maximum drop size, heat transfer modeling to individual drops, and minimum jumping size) on the drop-size distribution and overall heat transfer rate is explored. Assignment of the nucleation site spatial distribution and heat transfer model affect both the drop-size distribution and predicted overall heat transfer rate. Results from the simulation suggest that, when the contact angle is large (as on superhydrophobic surfaces) and no coalescence-induced jumping occurs, the heat transfer may not be as sensitive to the maximum drop-size as previously supposed. Furthermore, this work suggests that when coalescence-induced jumping occurs, reducing the maximum drop size may not always increase heat transfer since drops similar in size to those removed by coalescence-induced jumping can contribute significantly to the overall heat transfer rate.

Optimized heat exchanger integration within a TSA-process based on experimentally evaluated heat transfer correlations for finned-tubes in fluidized-beds

In terms of design optimization of a potential heat exchanger within a gas-solid contacting stage, its thermal behaviours (i.e. heat transfer) is the key influencing factor. The aim of the work is to realize an optimized temperature swing adsorption (TSA) process system by heat exchanger surface configurations with finned tubes for fluidized bed. In a first step, the heat transfer coefficient (HTC) of Lewatit® VP OC 1065 will be experimentally investigated in a fluidized bed test system for the simulation of process characteristics of TSA. The HTC of four tubes with different circular helical fins was experimentally characterized as a function of variable fluidization gas velocities. All measurements were performed for single tube configuration resp. and staggered as well as in-line tube bundle configuration, respectively. The data obtained were validated to meet the energy balance and further used to develop a dimensionless correlation. After analysis and evaluation of the data acquired, the two developed correlations (i.e. single and bundle correlations) are able to predict heat transfer rates of finned tubes within a fluidized bed. These correlations are valid within a certain parameter range. In a second step, the correlations are integrated into a process simulation environment for dimensioning TSA-process systems. The simulation tool enables the calculation of the heat transfer rates of a gas-solid contact stage for adsorption or desorption. Hence, optimized heat exchanger surface layouts with finned tubes for fluidized bed TSA process systems can be realized.