A new approach in evaluation of thermal contact conductance of tube–fin heat exchanger

This paper presents a new method in evaluating the thermal contact conductance (TCC) of tube–fin heat exchanger, which makes it possible to improve the tube–fin TCC performance at the stage of forming process design. Firstly, the tube–fin contact status is studied with a finite element (FE) model of tube expansion process. The simulation result shows that the tube–fin joining is far form full contact and a gap exists at the interface, which is confirmed by experimental observation. Distribution of the contact pressure along the tube–fin interface is obtained from the numerical results. Then, an experiment for the relationship between the contact pressure and the TCC is carried out. Combining the experiment result with the contact pressure distribution from the simulation, the tube–fin TCC can be evaluated. This evaluation results agree well with thermal measurement of the whole heat exchanger. Based on the method, effect of key factors of the expansion forming process, such as expanding ratio and die geometry, are optimized.     

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.     

Prediction of heat transfer due to presence of copper–water nanofluid using resilient-propagation neural network

Heat transfer due to laminar natural convection of copper–water nanofluid in a differentially heated square cavity has been predicted by Artificial Neural Network (ANN). The nanofluid has been considered as non-Newtonian. The ANN has been trained by a resilient-propagation (RPROP) algorithm. The required input and output data to train the ANN has been taken from the results of numerical simulation that was performed simultaneously where the transport equations has been solved numerically using finite volume approach incorporating SIMPLER algorithm. Results from simulation and resilient-propagation (RPROP) based ANN have been compared. It has been observed that the ANN predicts the heat transfer correctly within the given range of training data. It is further observed that resilient-propagation (RPROP) based ANN is an efficient tool to predict the heat transfer than simulation, which takes much longer time to compute.     

Analytical model of a solarium for cold climate—A new approach

In this present communication, a new approach has been evolved for analysing the thermal performance of a solarium useful in a cold climate. So as to trap the maximum solar radiation, the concept of glass windows (with movable insulation) in both the east and west walls of the sun space, besides in its south facing will and with the roof made of glass, has been introduced. Considering the ground temperature constant over a day, an overall heat transfer coefficient has been incorporated for the estimation of the heat flux transferred from the floor of the solarium to the ground. The introduction of this heat transfer coefficient eliminates the need of solving the conductivity equation for the heat flux conducted from the floor of the solarium to the ground. On account of the almost insulating behaviour of wood, an overall heat transfer coefficient has been taken for an all wooden structure of the solarium. Carrying out a transient analysis, explicit expressions for the temperatures of the sun space, the blackened absorbing surface of the water wall, the water itself, the living space and the isothermal masses have been developed as a function of time. These temperatures are required for the evaluation of the thermal energy taken in by the water wall, the heat flux entering the sun space and living space and the thermal energy distributed over the isothermal masses lying in the living space.     

A dispersion model for predicting the heat transfer performance of TiO2–water nanofluids under a laminar flow regime

Nanofluids are a suspension of particles with ultrafine size in a conventional base fluid that increases the heat transfer performance of the original base fluid. They show higher thermal performance than base fluids especially in terms of the thermal conductivity and heat transfer coefficient. During the last decade, many studies have been carried out on the heat transfer and flow characteristics of nanofluids, both experimentally and theoretically. The purpose of this article is to propose a dispersion model for predicting the heat transfer coefficient of nanofluids under laminar flow conditions. TiO₂ nanoparticles dispersed in water with various volume fractions and flowing in a horizontal straight tube under constant wall heat flux were used. In addition, the predicted values were compared with the experimental data from He et al. [14]. In the present study, the results show that the proposed model can be used to predict the heat transfer behaviour of nanofluids with reasonable accuracy. Moreover, the results also indicate that the predicted values of the heat transfer coefficient obtained from the present model differ from those obtained by using the Li and Xuan equation by about 3.5% at a particle volume fraction of 2.0%.     

A new algorithm for solving transient heat and mass transfer in metal–hydrogen reactor

A new algorithm based on the lattice Boltzmann method (LBM) is proposed as a potential solver for two-dimensional and dynamic heat and mass transfer in metal–hydrogen reactor. To check the validity of this algorithm, computational results have been compared with the experimental data and a good agreement is obtained. The advantages of the proposed numerical approach include, among others, simple implementation on a computer, accurate CPU time, and capability of stable simulation.     

Estimation of methane production for batch technology – A new approach

In the case of agricultural biogas plants it is the living microorganisms (mainly archaea) that determine the amount of methane produced. If the conditions in the digester are not adequate or the substrates are selected incorrectly, the microorganisms will not be able to develop properly and methane production will also be low or none. Therefore, in the first place the influence of individual factors on the production of methane was analysed. Next, based on the conclusions drawn from the analysis of the factors, a mathematical model was developed that will facilitate the selection of appropriate substrates and process parameters by future investors building agricultural biogas plants. The aim of the study was to demonstrate the impact of the factors on the production of methane and to present a mathematical model for estimating methane production for batch technology used in agricultural biogas plants (this kind of production is also used in laboratories for testing specific substrates). The model presented in the paper has been developed and tested on a group of over seventy substrates of agricultural origin. The inclusion of many factors determining methane production in the model is not complicated as each of the factors is easy to measure.     

On an acoustics–thermal–fluid coupling model for the prediction of temperature elevation in liver tumor

The present study is aimed at predicting liver tumor temperature during a high-intensity focused ultrasound (HIFU) thermal ablation using the proposed acoustics–thermal–fluid coupling model. The linear Westervelt equation is adopted for modeling the incident finite-amplitude wave propagation. The nonlinear hemodynamic equations are also taken into account in the simulation domain that contains a hepatic tissue domain, where homogenization dominates perfusion, and a vascular domain, where blood convective cooling may be essential in determining the success of HIFU. Energy equation for thermal conduction involves two heat sinks to account for tissue perfusion and forced convection-induced cooling. The effect of acoustic streaming is also included in the development of the current HIFU simulation study. Convective cooling in large blood vessel and acoustic streaming were shown to change the temperature near blood vessel. It was shown that acoustic streaming effect can affect the blood flow distribution in hepatic arterial branches and leads to the mass flux redistribution.     

Numerical study on the convective heat transfer of nanofluid in a triangular minichannel heat sink using the Eulerian–Eulerian two-phase model

In this paper, the laminar forced convection heat transfer of the water-based nanofluid inside a minichannel heat sink is studied numerically. An Eulerian two-fluid model is considered to simulate the nanofluid flow inside the triangular heat sink and the governing continuity, momentum, and energy equations for both phases are solved using the finite volume method. Comparisons of the Nusselt number predicted by the Eulerian–Eulerian model with the experimental data available in the literature demonstrate that the simulation results are in excellent agreement with the experimental data and the maximum deviation from experimental data is 5%. The results show that the heat sink with nanofluid has a better heat transfer rate in comparison with the water-cooled heat sink. Also, the heat transfer enhancement increases with an increase in Reynolds number and nanoparticle volume concentration. In addition, the friction factor increases slightly for nanofluid-cooled minichannel heat sink.     

Numerical prediction of turbulent plane jets and forced plumes by use of the k-ε model of turbulence

A buoyancy-extended k-ε model of turbulence has been developed for calculating the dynamical and thermal fields in plane turbulent jets and forced plumes in a uniform stagnant environment. The governing partial differential equations (continuity, lateral and longitudinal momentum, thermal energy, turbulent kinetic energy k and its dissipation rate ε) are solved by means of an efficient computer program (called JEPHTE) for elliptic unsteady differential equations. A version assuming C_μ to be an empirical function of the densimetric Froude number at the source has been tested. The predictions are compared with experimental data and/or computed results obtained with more complex modellings of the buoyancy effects.     

Experimental study of an ammonia–water bubble absorber using a plate heat exchanger for absorption refrigeration machines

The development of absorption chillers activated by renewable heat sources has increased due mainly to the increase in primary energy consumption that causes problems such as greenhouse gases and air pollution among others. These machines, which could be a good substitute for compression systems, could be used in the residential and food sectors which require a great variety of refrigeration conditions. Nevertheless, the low efficiency of these machines makes it necessary to enhance heat and mass transfer processes in the critical components, mainly the absorber, in order to reduce their large size.This study used ammonia–water as the working fluid to look at how absorption takes place in a plate heat exchanger operating under typical conditions of absorption chillers, driven by low temperature heat sources. Experiments were carried out using a corrugated plate heat exchanger model NB51, with three channels, where ammonia vapor was injected in bubble mode into the solution in the central channel. The results achieved for the absorption flux were in the range of 0.0025–0.0063 kg m^?2 s^?1, the solution heat transfer coefficient varied between 2.7 and 5.4 kW m^?2 K^?1, the absorber thermal load from 0.5 to 1.3 kW. In addition, the effect of the absorber operating conditions on the most significant efficiency parameters was analyzed. The increase in pressure, solution and cooling flow rates positively affect the absorber performance, on the other hand an increase in the concentration, cooling, and solution temperature negatively affects the absorber performance.     

Numerical simulation of heat transfer and fluid flow past a rotating isothermal cylinder – A LBM approach

In this paper, a viscous fluid flowing past a rotating isothermal cylinder with heat transfer is studied and simulated numerically by the lattice Boltzmann method (LBM). A numerical strategy for dealing with curved and moving boundaries of second-order accuracy for both velocity and temperature fields is proposed and presented. The numerical strategy and method are validated by comparing the present numerical results of flow without heat transfer with those of available previous theoretical, experimental and numerical studies, showing good agreements. On this basis, the convective heat transfer performance in such rotational boundary environments is further studied and validated; the numerical results are reported in the first time. The effects of the peripheral-to-translating-speed ratio, Reynolds number and Prandtl number on flow and heat transfer are discussed in details.     

Life cycle assessment of nuclear-based hydrogen production via a copper–chlorine cycle: A neural network approach

A comparative environmental study is reported of nuclear-based hydrogen production using thermochemical water decomposition cycles. The investigation uses a life cycle assessment (LCA) as is an analytical tool to evaluate and reduce the environmental impact of the system or product. The LCA results are presented in terms of acidification potential and global warming potential. Since LCA often utilizes software to model and analyse the system, an artificial neural network (ANN) method can be advantageous. Here, an ANN method is applied to a nuclear-based hydrogen production system. Using an ANN method in this study eliminates the need to use LCA software separately and facilitates the determination of the impacts of altering input parameters of a system (e.g., heat, work, production capacity and plant lifetime). The neural network approach to identify the best system option, consistent with LCA software results, is developed here using ten neurons in the hidden layers.     

Assessment of Bejan’s heat exchanger allocation model under the influence of generalized thermal resistance,relaxation effect,bypass heat leak and internal irreversibility

This article reports an analytical investigation of the optimal heat exchanger allocation and the corresponding efficiency for maximum power output of a Carnot-like heat engine. To mimic a real engine, the generalized power law for the resistance in heat transfer external to the engine, relaxation effect in heat transfer, bypass heat leak and finally internal irreversibility of the power producing compartment of the engine is taken into consideration. From the engineering perspective the temperature ratio of the heat source and sink as well as to that of hot end and cold side of the working fluid is considered not to be the controllable parameters. A parametric study is presented for the other possible controllable variables. Selection of a power law over a linear model has a significant effect on the optimal heat exchanger allocation for maximum power output and the corresponding efficiency. For a higher degree of relaxation effect the drop in the maximum power efficiency is prominent along with the shift of equipartitioned allocation of heat exchanger inventory. Bypass heat leak and internal irreversibility exhibits relatively less pronounced effects on the maximum power efficiency and on the optimal heat exchanger allocation. Thus the endoreversible formulation of thermodynamic model is physically realistic. Strikingly when the optimal allocation of the heat exchanger inventory obeys the principle of equipartition in macroscopic organization for the linear law of the external heat resistance, the thermal efficiency appears to assume the representative documented value. Hence the linear model due to Bejan is also capable of capturing the essential features of a real power plant.     

Novel thermoelectric generator heat exchanger for indirect heat recovery from molten CuCl in the thermochemical Cu–Cl cycle of hydrogen production

The looming threat of global warming has elicited efforts to develop reliable sustainable energy resources. Hydrogen as a clean fuel is deemed a potential solution to the problem of storage of power from renewable energy technologies. Among current thermochemical hydrogen generation methods, the thermochemical copper-chlorine (Cu–Cl) cycle is of high interest owing to lower temperature requirements. Present study investigates a novel heat exchanger comprising a thermoelectric generator (TEG) to recover heat from high temperature molten CuCl exiting the thermolysis reactor. Employing casting/extrusion method, the performance of the proposed heat exchanger is numerically examined using COMSOL Multiphysics. Results indicate that maximum generated power could exceed 40 W at the matching current of 4.5 A. Maximum energy conversion efficiency yields to 7.1%. Results demonstrate that TEG performance boosts with increasing the inlet Re number, particularly at the hot end. For the molten CuCl chamber, findings denote that there is a 36% discrepancy between highest and lowest Re numbers. Similarly, the highest efficiency value pertains to the case with the highest inlet velocity. Moreover, the highest temperature difference between inlet and outlet of the cooling water is about 28 °C and 10 °C for the lowest and highest inlet Re numbers, respectively. Average deviation from anticipated friction factor and Nusselt number are 0.31% and 12.62%, respectively.     

Numerical study of nanofluid heat transfer for different tube geometries – A comprehensive review on performance

The heat transfer performance of a system can be improved using a combination of passive methods, namely nanofluids and various types of tube geometries. These methods can help enhance the heat transfer coefficient and consequently reduce the weight of the system. In this paper, the effect of tube geometry and nanofluids towards the heat transfer performance in the numerical system is reviewed. The forced convective heat transfer performance, friction factor and wall shear stress are studied for nanofluid flow in different tube geometries. The thermo-physical properties such as density, specific heat, viscosity and thermal conductivity are reviewed for the determination of nanofluid heat transfer numerically. Various researchers had measured and modelled for the determination of thermal conductivity and viscosity of nanofluids. However, the density and specific heat of nanofluids can be estimated with the mixture relations. The different tube geometries in simulation work are analyzed namely circular tube, circular tube with insert, flat tube and horizontal tube. It was observed that the circular tube with insert provides the highest heat transfer coefficient and wall shear stress. Meanwhile, the flat tube has greater heat transfer coefficient with a higher friction factor compared to the circular tube.     

Pressure corrections for the potential flow analysis of Kelvin–Helmholtz instability with heat and mass transfer

Pressure corrections for the viscous potential flow analysis of Kelvin–Helmholtz instability at the interface of two viscous fluids have been carried out when there is heat and mass transfer across the interface. Both fluids are taken as incompressible and viscous with different kinematic viscosities. In viscous potential flow theory, viscosity enters through normal stress balance and effect of shearing stresses is completely neglected. We include the viscous pressure in the normal stress balance along with irrotational pressure and it is assumed that this viscous pressure will resolve the discontinuity of the tangential stresses at the interface for two fluids. It has been observed that heat and mass transfer has destabilizing effect on the stability of the system. A comparison between viscous potential flow (VPF) solution and viscous contribution to the pressure for potential flow (VCVPF) solution has been made and it is found that the effect of irrotational shearing stresses stabilizes the system.     

New prediction methods for CO2 evaporation inside tubes: Part II—An updated general flow boiling heat transfer model based on flow patterns

Corresponding to the updated flow pattern map presented in Part I of this study, an updated general flow pattern based flow boiling heat transfer model was developed for CO₂ using the Cheng–Ribatski–Wojtan–Thome [L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside horizontal tubes, Int. J. Heat Mass Transfer 49 (2006) 4082–4094; L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, Erratum to: “New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside tubes” [Heat Mass Transfer 49 (21–22) (2006) 4082–4094], Int. J. Heat Mass Transfer 50 (2007) 391] flow boiling heat transfer model as the starting basis. The flow boiling heat transfer correlation in the dryout region was updated. In addition, a new mist flow heat transfer correlation for CO₂ was developed based on the CO₂ data and a heat transfer method for bubbly flow was proposed for completeness sake. The updated general flow boiling heat transfer model for CO₂ covers all flow regimes and is applicable to a wider range of conditions for horizontal tubes: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m² s, heat fluxes from 1.8 to 46 kW/m² and saturation temperatures from ?28 to 25 °C (reduced pressures from 0.21 to 0.87). The updated general flow boiling heat transfer model was compared to a new experimental database which contains 1124 data points (790 more than that in the previous model [Cheng et al., 2006, 2007]) in this study. Good agreement between the predicted and experimental data was found in general with 71.4% of the entire database and 83.2% of the database without the dryout and mist flow data predicted within ±30%. However, the predictions for the dryout and mist flow regions were less satisfactory due to the limited number of data points, the higher inaccuracy in such data, scatter in some data sets ranging up to 40%, significant discrepancies from one experimental study to another and the difficulties associated with predicting the inception and completion of dryout around the perimeter of the horizontal tubes.     

An enhanced thermal conduction model for the prediction of convection dominated solid–liquid phase change

An enhanced thermal conduction model for predicting convection dominated solid–liquid phase change is presented. The main feature of the model is to predict (1) the overall thermal behavior of the system and (2) the phase front position without recurring to the full solution of the Navier–Stokes equations. The model rests entirely on the conduction equation for both the solid and liquid phases. The effect of convection in the melt is mimicked via an enhanced thermal conductivity that depends on the dimensionless numbers and the geometry of the flow. The model is tested and confronted to full CFD solutions for a freezing duct flow problem and for buoyancy driven melting in an enclosure. In both cases, the predictions of the enhanced thermal conduction model show excellent agreement with that of the CFD model. Not only is the enhanced thermal conduction model simpler to implement but its simulations run at least ten times as fast as those of the CFD model. Consequently, the enhanced thermal conduction model is well suited for controlling real-time solid–liquid phase change processes that occur in industrial applications as well as in latent heat thermal energy storage systems.