Mono-sized sphere packing algorithm development using optimized Monte Carlo technique

In this paper, fuel cell catalyst layer was developed using the optimized sphere packing algorithm. An optimization technique named adaptive random search technique (ARSET) was employed in this packing algorithm. The ARSET algorithm will generate the initial location of spheres and allow them to move in the random direction with the variable moving distance, randomly selected from the sampling range (α), based on the Lennard–Jones potential and Morse potential of the current and new configuration. The solid fraction values obtained from this developed algorithm are in the range of 0.610–0.624 while the actual processing time can significantly be reduced by 5.58–34% based on the number of spheres. The initial random number sampling range (α) was investigated and the appropriate α value is equal to 0.5.

[1]  David Pisinger,et al.  Heuristics for the container loading problem , 2002, Eur. J. Oper. Res..

[2]  L. Girifalco,et al.  Application of the Morse Potential Function to Cubic Metals , 1959 .

[3]  G. Androutsopoulos,et al.  Realistic random sphere pack model for the prediction of relative permeability curves , 2001 .

[4]  Enrique Iglesia,et al.  Monte carlo simulations of structural properties of packed beds , 1991 .

[5]  Yun Wang,et al.  A review of polymer electrolyte membrane fuel cells: Technology, applications,and needs on fundamental research , 2011 .

[6]  D. Stoyan,et al.  Optimisation of multi-component hard sphere liquids with respect to dense packing , 2007 .

[7]  E. Iglesia,et al.  Simulations of the structure and properties of amorphous silica surfaces , 2001 .

[8]  D. Stoyan,et al.  Computer simulated dense-random packing models as approach to the structure of porous low-k dielectrics , 2005 .

[9]  Coşkun Hamzaçebi,et al.  Continuous functions minimization by dynamic random search technique , 2007 .

[10]  Singiresu S. Rao Engineering Optimization : Theory and Practice , 2010 .

[11]  G. T. Nolan,et al.  Computer simulation of random packing of hard spheres , 1992 .

[12]  T. Nguyen,et al.  A liquid water management strategy for PEM fuel cell stacks , 2003 .

[13]  D. Wilkinson,et al.  Application of water barrier layers in a proton exchange membrane fuel cell for improved water manag , 2011 .

[14]  Pupong Pongcharoen,et al.  Development of a stochastic optimisation tool for solving the multiple container packing problems. , 2012 .

[15]  Joachim Scholta,et al.  Estimation of water distribution and degradation mechanisms in polymer electrolyte membrane fuel cel , 2011 .

[16]  Bryan Kok Ann Ngoi,et al.  Applying spatial representation techniques to the container packing problem , 1994 .

[17]  Jodrey,et al.  Computer simulation of close random packing of equal spheres. , 1985, Physical review. A, General physics.

[18]  Coskun Hamzaçebi,et al.  A heuristic approach for finding the global minimum: Adaptive random search technique , 2006, Appl. Math. Comput..

[19]  S. Reyes,et al.  Effective diffusivities in catalyst pellets: new model porous structures and transport simulation techniques , 1991 .

[20]  Tao Ye,et al.  Global optimization method for finding dense packings of equal circles in a circle , 2011, Eur. J. Oper. Res..

[21]  P. Achard,et al.  Highly porous PEM fuel cell cathodes based on low density carbon aerogels as Pt-support: Experimental study of the mass-transport losses , 2009 .