Generating random media from limited microstructural information via stochastic optimization

Random media abound in nature and in manmade situations. Examples include porous media, biological materials, and composite materials. A stochastic optimization technique that we have recently developed to reconstruct realizations of random media (given limited microstructural information in the form of correlation functions) is investigated further, critically assessed, and refined. The reconstruction method is based on the minimization of the sum of squared differences between the calculated and reference correlation functions. We examine several examples, including one that has appreciable short-range order, and focus more closely on the kinetics of the evolution process. The method is generally successful in reconstructing or constructing random media with target correlation functions, but one must be careful in implementing an earlier proposed time-saving step when treating random media possessing significant short-range order. The issue of the uniqueness of the obtained solutions is also discussed.