A NEW CLASS OF STOCHASTIC SIMULATION-MODELS FOR POLYMER STRESS CALCULATION

We introduce a new class of stochastic models for polymer stresses whi ch offers a blending of continuum mechanics, network theory and reptat ion theory. The stochastic dynamics of the model involve two independe nt Gaussian stochastic processes, Q(1) and Q(2). Associated with each random vector, ei, is a random variable, Si, that describes the vector 's survival time during which it evolves according to a deterministic equation of motion. The expression for the stress tensor is an ensembl e average of f(1)(Q(1)(2),Q(2)(2))Q(1)Q(1) + f(2) (Q(1)(2), Q(2)(2))1Q (2)Q(2,) where the f(i) are scalar functions of Q(1)(2) = Q(1).Q(1) an d Q(2)(2) = Q(2).Q(2). The relationship between this new class of mode ls and the class of factorized Rivlin-Sawyers integral models is indic ated, and simulation models from this new class are used to predict th eological behavior of three low-density-polyethylene melts. We find th at the steady-state sheat data of all three melts, and the time-depend ent elongational viscosity of one of the melts, can be predicted well by models with the same f(i), but different probability densities for S-i which are obtained from the different relaxation spectra. (C) 1998 American Institute of Physics.