Mihir Sen

Neural network analysis of fin-tube refrigerating heat exchanger with limited experimental data

We consider the problem of accuracy in heat rate estimations from artificial neural network (ANN) models of heat exchangers used for refrigeration applications. Limited experimental measurements from a manufacturer are used to show the capability of the neural network technique in modeling the heat transfer phenomena in these systems. A well-trained network correlates the data with errors of the same order as the uncertainty of the measurements. It is also shown that the number and distribution of the training data are linked to the performance of the network when estimating the heat rates under different operating conditions, and that networks trained from few tests may give large errors. A methodology based on the cross-validation technique is presented to find regions where not enough data are available to construct a reliable neural network. The results from three tests show that the proposed methodology gives an upper bound of the estimated error in the heat rates. The procedure outlined here can also help the manufacturer to find where new measurements are needed.

Numerical study of natural convection in a tilted rectangular porous material

Abstract Two-dimensional natural convective flow in a tilted rectangular porous material saturated with fluid is analyzed by solving numerically the mass, momentum and energy balance equations, using Darcys law and the Boussinesq approximation. Isothermal boundary conditions are considered, where two opposite walls are kept at constant but different temperatures and the other two are thermally insulated. The external parameters considered are the tilt angle, the aspect ratio and the Darcy-Rayleigh number. Three main convective modes are found: conduction, single and multiple cell convection and their features described in detail. Local and global Nusselt numbers are presented as functions of the external parameters. Multiplicity of solutions is explored for aspect ratio unity. The existence of more than one solution is found when the bottom wall is at a higher temperature and in a horizontal or close to horizontal position.

Simulation of heat exchanger performance by artificial neural networks

The artificial neural network technique was applied to heat transfer through a series of problems of increasing complexity. For the simplest problem of one-dimensional heat conduction with linear activation function, it is possible to give physical meaning to the synaptic weights of the network. A network with sigmoid activation function was used for non-linear representation of convection problems where identification of the weights with physical variables was not possible. Two cases of convective heat transfer with one and two heat transfer coefficients and artificially generated data were examined. Finally, the method was applied to the analysis of data obtained in the laboratory for a single-row, fin-tube heat exchanger. It is shown that a better prediction with smaller scatter is obtained in comparison to a conventional power-law correlation for the heat transfer coefficients.

Dynamic prediction and control of heat exchangers using artificial neural networks

We extend the artificial neural network (ANN) technique to the simulation of the time-dependent behavior of a heat exchanger (HX) and use it to control the temperature of air passing over it. The experiments are carried out in a open loop test facility. First a methodology is proposed for the training and prediction of the dynamic behavior of thermal systems with heat exchangers. Then an internal model scheme is developed for the control of the over-tube air temperature with two artificial neural networks, one to simulate the heat exchanger and another as controller. An integral control is implemented in parallel with the filter of the neural network controller to eliminate a steady-state offset. The results are compared with those of standard PI and PID controller. There is less oscillatory behavior with the neural network controller, which allows the system to reach steady-state operating conditions in regions where the PI and PID controllers are not able to perform as well.

Effect of fin spacing on convection in a plate fin and tube heat exchanger

Abstract We examine the influence of fin spacing on the over-tube side of a single-row fin-tube heat exchanger through flow visualization and numerical computation. The distance between fins is nondimensionalized by the tube diameter. If this parameter is small, the flow is Hele-Shaw; as it is increased, a horseshoe vortex is formed just upstream of the tube; a separated region is then developed behind the tube; this becomes larger and eventually communicates with the fluid downstream of the heat exchanger. A peak in the Nusselt number occurs at the horseshoe vortex. In the wake region the Nusselt number is very small but increases when there is fluid exchange with that downstream. The ratio of the overall Nusselt number per unit length to the nondimensional pressure drop is found to show a maximum.

Heat transfer enhancement in coiled tubes by chaotic mixing

Abstract The present work examines chaotic mixing as a means of enhancing the in-tube convection heat transfer in helical coils. It is shown that simple modifications of coil geometry can be made to take advantage of this phenomenon. The study focuses on a geometry with the axis of the coil being turned through 90° in a periodic manner, and comparisons are made with a coil without this change in axis. Particle paths are calculated using the classical perturbation solution of Dean for the secondary flow. Chaotic mixing is confirmed by a positive Lyapunov exponent. The temperature field is calculated numerically showing that chaotic mixing is responsible for considerable flattening of the temperature profile and an increase in conveetive heat transfer. Experiments are conducted with water on two coiled tube geometries over a Reynolds number range of 3000–10000. The coils are identical in every respect except that one is conventional with constant axis, while the other is with alternating axis. The latter shows a 6–8% higher in-tube heat transfer coefficient due to chaotic mixing, with a corresponding pressure drop increase of 1.5–2.5%.

Heat rate predictions in humid air-water heat exchangers using correlations and neural networks

We consider the flow of humid air over fin-tube multi-row multi-column compact heat exchangers with possible condensation. Previously published experimental data are used to show that a regression analysis for the best-fit correlation of a prescribed form does not provide an unique answer, and that there are small but significant differences between the predictions of the different correlations thus obtained. It is also shown that it is more accurate to predict the heat rate directly rather than through intermediate quantities like the j-factors. The artificial neural network technique is offered as an alternative technique. It is trained with experimental values of the humid-air flow rates, dry-bulb and wet-bulb inlet temperatures, fin spacing, and heat transfer rates. The trained network is then used to make predictions of the heat transfer. Comparison of the results demonstrates that the neural network is more accurate than conventional correlations. @DOI: 10.1115/1.1351167#

Analysis of heat transfer enhancement in coiled-tube heat exchangers

We analyze the phenomenon of steady heat transfer enhancement due to chaotic particle paths in steady, laminar flow through a tube. The performances of two different coils, one with regular mixing and the other with chaotic mixing, are numerically analyzed and compared. For the latter case, axially periodic boundary conditions over a unit cell are used. Velocity vectors and temperature fields are computed. Poincare maps of fluid particles being repeatedly mapped from inlet to outlet of this cell are presented as function of system geometry. Point and periodic attractors with chaotic windows are found. Lyapunov exponents are used to establish the presence of chaotic mixing. Flow fields and isotherms are examined to reveal the mechanisms of enhanced heat and momentum transfer through modification of the wall and internal boundary layers. Spatially varying local and constant bulk Nusselt numbers and bulk friction factors are determined for a range of governing parameters.

Topology Optimization Using a Hybrid Cellular Automaton Method With Local Control Rules

The hybrid cellular automaton (HCA) algorithm is a methodology developed to simulate the process of structural adaptation in bones. This methodology incorporates a distributed control loop within a structure in which ideally localized sensor cells activate local processes of the formation and resorption of material. With a proper control strategy, this process drives the overall structure to an optimal configuration. The controllers developed in this investigation include two-position, proportional, integral and derivative strategies. The HCA algorithm combines elements of the cellular automaton (CA) paradigm with finite element analysis (FEA). This methodology has proved to be computationally efficient to solve topology optimization problems. The resulting optimal structures are free of numerical instabilities such as the checkerboarding effect. This investigation presents the main features of the HCA algorithm and the influence of different parameters applied during the iterative optimization process. DOI: 10.1115/1.2336251

Multiple steady states for unicellular natural convection in an inclined porous layer

Abstract Multiplicity of steady states in natural convection within an inclined porous material with parallel conductive isotherms is investigated. The different steady states are obtained analytically for unicellular convection in thin rectangular porous layers with uniform heating and cooling through opposite walls. The basis of the analytical approximation is an assumption of parallel flow over a large portion of the layer. The two cases of heat fluxes through side and end walls are both calculated and are seen to share some qualitatively similar features. At sub-critical Rayleigh numbers only one steady state exists for any tilt angle. For higher Rayleigh numbers and for small enough inclinations around bottom heating, however, multiple steady states exist, some of which are unstable. Numerical confirmation of the stable analytical results is also presented.