Rohit K. Singla

Application of artificial bee colony algorithm for inverse modelling of a solar collector

Abstract This paper deals with the inverse analysis of a double-glazed flat-plate solar collector using the artificial bee colony (ABC) optimization algorithm. In domestic water heating, both low and high heat output from the solar collector is undesirable, so the solar collector is required to supply the hot water at a particular temperature only, which in turn requires a given distribution of heat loss factor. With this criterion, the present analysis is aimed at predicting feasible dimensions and configurations of a solar collector satisfying a prescribed distribution of heat loss factor using ABC algorithm. It is observed that many feasible alternatives of unknowns exist which satisfy a prescribed requirement, and using the ABC algorithm, the size of the solar collector can be minimised by 6–32% with reference to the existing records. The effects of changing ambient conditions are also studied. Furthermore, a comparative study of the ABC algorithm against other heuristic algorithms reveals its suitability and efficacy for the present estimation problem.

Closed-form solution for a rectangular stepped fin involving all variable thermal parameters and nonlinear boundary conditions

In this paper, the implementation of the Adomian decomposition method is demonstrated to solve a nonlinear heat transfer problem for a stepped fin involving all temperature-dependent means of heat transfer and nonlinear boundary conditions. Unlike conventional insulated tip assumption, to make the present problem more practical, the fin tip is assumed to disperse heat by convection and radiation. Thermal parameters such as the thermal conductivity, the surface heat transfer coefficient and the surface emissivity are considered to be temperature-dependent. Adomian polynomials are first obtained and then a set of Adomian decomposition method results is validated with pertinent results of the differential transformation method reported in the literature. Effects of different thermo-physical parameters on the temperature distribution and the efficiency have been exemplified. The study reveals that for a given set of conditions, the stepped fin may perform better than the straight fin.

Adomian Decomposition Method for a stepped fin space radiator with internal heat generation

In the present study, the aim is to demonstrate the application of the Adomian Decomposition Method (ADM) to obtain a closed form solution of a stepped fin space radiator with temperature-dependent thermal parameters. The effect of internal heat generation is also considered. The thermal conductivity and surface emissivity are considered to be linearly-dependent on the temperature. For validating the employed methodology, the simplified ADM results from the present study have been compared with relevant results available in the literature, which are found to be in good agreement. The effect of pertinent performance parameters such as thickness reduction factor, step length ratio, aspect ratio, radiation-conduction, non-dimensional thermal conductivity and emissivity parameters along with heat generation number on the temperature distribution has been reported. Furthermore, the temperature distribution of the stepped fin space radiator has been compared against that of the straight fin space radiator. It has been found that the local temperature distribution in case of a stepped fin is less as compared to that of a straight fin space radiator. Thus, from enhanced heat transfer point of view as well as from less weight consideration, a stepped fin space radiator is concluded to perform better than a straight fin.

Inverse Heat Transfer Study of a Nonlinear Straight Porous Fin Using Hybrid Optimization

Gas turbine blades are subjected to excessive heating load and for safe operation they must be properly cooled for protecting the blade material from damage. This involves external film cooling and internal pin-fin cooling. Cooling using fins are used for gas turbine blades by passing cold air over small extended surfaces. However, it is found that compared to conventional solid fins, for same weight, the usage of porous fins gives better thermal performance. In order to satisfy a given temperature distribution, the fin designer needs to determine various important properties and parameters, which requires solution of inverse problems. These parameters are generally thermo-physical properties for selecting suitable material and dimensions. In this work, an inverse heat transfer study of a porous rectangular fin using a hybrid Differential Evolution (DE)-nonlinear programming (NLP) algorithm has been carried out. The energy exchange in the porous fin is governed by conductive, convective and radiative heat transfer alongwith mass diffusion through the porous media, which makes the problem nonlinear. The fluid medium is assumed to be air. Using DE-NLP algorithm, four important parameters such as porosity, thermal conductivity of solid, length and thickness of the porous fin have been estimated for satisfying a given temperature distribution. Initially, the prescribed temperature distribution is calculated by solving a forward problem based on an implicit Runge-Kutta method working on Lobatto technique. Effects of random measurement errors, comparison of number of iterations and reconstruction distributions for the hybrid DE-NLP and individual NLP, DE schemes are performed. It is observed that the hybrid DE-NLP method converges faster than other two methods working separately. For all measurement errors, a very good reconstruction of the temperature distribution is observed using DE-NLP algorithm. In addition to this, it is found that many feasible combinations of the parameters can satisfy a given temperature distribution, which offers flexibility in selecting various parameters by adjusting the fin size, solid thermal conductivity and porosity.© 2014 ASME

Inverse Heat Transfer Analysis of Porous Extended Surface Using Simplex Search Method

This work deals with the application of the Nelder-Mead simplex search method (SSM) to study a porous extended surface. At first, analytical expression for calculating the local temperature field has been derived using an implicit Runge-Kutta method. The heat transfer phenomenon is assumed to be governed by conductive, naturally convective and radiative heat transfer, whereas the diffusion of mass through the porous media is also taken into account. Then, using the SSM, critical parameters such as porosity, permeability, and thermal conductivities of the extended surface have been predicted for satisfying a prescribed temperature field. It is found that many alternative solutions can meet a given thermal requirement, which is proposed to offer the flexibility in selecting the material and regulating the thermal conditions. It is observed that the allowable error in the temperature measurement should be limited within 5%. It is also found that even with few temperature measurement points, very good reconstruction of the thermal field is possible using the SSM.Copyright

Multi-parameter Retrieval in a Porous Fin Using Binary-Coded Genetic Algorithm

In this paper, the implementation of the binary-coded Genetic Algorithm (GA) for multi-parameter retrieval through inverse analysis is demonstrated. A porous rectangular fin with constant thermo-physical parameters is investigated. The porous fin involves Fourier law of heat conduction along with natural convection and surface radiation phenomena. Due highly nonlinear phenomenon owing to the radiative effect and because of the associated complexity in the gradient evaluation, gradient-free method based on the GA has been used for unknown parameter retrieval. The analysis is done for satisfying a given temperature distribution on the fin surface generated using a well-validated forward solver based on the Runge-Kutta method. It is observed from the simulated experiments that for simultaneous multi-parameter retrieval, the GA yields multiple combinations of unknown parameters satisfying a particular distribution of temperature.

A differential evolution algorithm for maximizing heat dissipation in stepped fins

In this work, a differential evolution (DE)-based inverse analysis has been reported for maximizing the heat transfer rate from a rectangular stepped finned surface satisfying a given volume. The temperature dependency in all modes of heat transfer has been taken into the consideration, thereby making the problem highly nonlinear. In addition to conventional insulated tip assumption that signifies a linear case, nonlinear analysis with fin tip comprising simultaneous convection and radiation is also carried out. Furthermore, a numerical analysis of the transient behavior is done with the aid of the finite difference method. Due to unavailability of inverse analysis of stepped fins (literature supports this claim), for solving the problem using the DE, the concept of multiplicity of solutions satisfying a given criterion is used to search appropriate step configurations satisfying a fixed fin volume. Thereafter, step dimensions meeting the highest possible rate of heat transfer have been realized. During the DE-based optimization process, approximate analytical solutions formulated on the Adomian decomposition method (ADM) have been used for updating the pertinent fin temperature distribution. The proposed ADM-DE combination is observed to converge into a unique solution that yields the optimized design conditions under the imposed constraints.

Retrieval of controlling parameter in induced draft cooling tower using inverse method

In this work, application of the Golden Section Search Method (GSSM) is illustrated to inversely retrieve the controlling parameter meeting a desired performance requirement in an induced draft cooling tower. Merkel number is an important performance parameter because it involves various parameters such as global heat and mass transfer coefficient, water flow rate, dimensions (interfacial area per unit volume) and range within itself. At first, experiments have been performed to get accurate correlations for Merkel number against the controlling parameter that is required to be estimated, which is the air mass flow rate. Then, an inverse optimization technique involving GSSM has been used to estimate the required air flow rate in order to satisfy a given performance parameter. It is found from the present study that the controlling parameter estimated using GSSM yields a very good reconstruction of the Merkel number.