Design optimization of rotary regenerator using artificial bee colony algorithm

This study explores the use of artificial bee colony (ABC) algorithm for the design optimization of rotary regenerator. Maximization of regenerator effectiveness and minimization of regenerator pressure drop are considered as objective functions and are treated individually and then simultaneously for single-objective and multi-objective optimization, respectively. Seven design variables such as regenerator frontal area, matrix rotational speed, matrix rod diameter, matrix thickness, porosity, and split are considered for optimization. A case study is also presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization using ABC algorithm are validated by comparing with those obtained using genetic algorithm for the same case study. The effect of variation of ABC algorithm parameters on convergence and fitness value of the objective function has also been presented.

[1]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[2]  D. P. Sekulic,et al.  Fundamentals of Heat Exchanger Design , 2003 .

[3]  S. Sanaye,et al.  Multi-objective optimization of rotary regenerator using genetic algorithm , 2009 .

[4]  Dervis Karaboga,et al.  Artificial bee colony algorithm , 2010, Scholarpedia.

[5]  Geoffrey F. Hewitt.  Heat exchanger design handbook, 1998 , 1998 .

[6]  Zhenyu Liu,et al.  Multi-objective optimization design analysis of primary surface recuperator for microturbines , 2008 .

[7]  Hassan Hajabdollahi,et al.  Multi-objective optimization of shell and tube heat exchangers , 2010 .

[8]  Saeid Jafari,et al.  Optimum operational conditions of a rotary regenerator using genetic algorithm , 2008 .

[9]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[10]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[11]  Jamil A. Khan,et al.  Design and multi-objective optimization of heat exchangers for refrigerators , 2007 .

[12]  Ramesh K. Shah,et al.  A comparison of rotary regenerator theory and experimental results for an air preheater for a thermal power plant , 2004 .

[13]  N Ghodsipour,et al.  Experimental and sensitivity analysis of a rotary air preheater for the flue gas heat recovery , 2003 .

[14]  Yaochu Jin,et al.  Optimization of micro heat exchanger: CFD, analytical approach and multi-objective evolutionary algorithms , 2006 .

[15]  R. Hilbert,et al.  Multi-objective shape optimization of a heat exchanger using parallel genetic algorithms , 2006 .

[16]  R. V. Rao,et al.  A subjective and objective integrated multiple attribute decision making method for material selection , 2010 .

[17]  Zhuang Wu,et al.  Model-based analysis and simulation of regenerative heat wheel , 2006 .

[18]  Dervis Karaboga,et al.  Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems , 2007, IFSA.