Modeling of Distributions of Polymer Properties Using Parallel Computing in Matlab. I: Univariate Distributions

PINTOS, ESTEBAN; ASTEASUAIN, MARIANO

Cancún, México

Congreso; XV Simposio Latinoamericano de Polímeros - XIII Congreso Iberoamericano de Polímeros (SLAP 2016); 2016

Sociedad Polimérica de México

The operation of polymer processes aiming at achieving tight control of the molecular architecture of the polymer chains is very important for polymer manufacturers. Therefore, a significant effort has been devoted to the development of detailed predictive models of polymer processes. The calculation of the distribution of a single property, in most cases the MWD, has been extensively studied. The probability generating function (pgf) technique is a powerful method for modeling distributions of polymer properties.1,2 Models to be used for optimization and on-line control should require short running times. In this context, parallel computing offers a great possibility for the development of fast models of polymer processes. In this work, the performances of two variants of the pgf technique implemented in MATLAB® with parallel computing are studied in terms of accuracy and CPU time.