[KSCI] Korea Science Citation Index Service

Computation of viscoelastic flow using neural networks and stochastic simulation

Tran-Canh, D. (Faculty of Engineering and Surveying, University of Southern Queensland Toowoomba)
Tran-Cong, T. (Faculty of Engineering and Surveying, University of Southern Queensland)

Publication Information

Korea-Australia Rheology Journal / v.14, no.4, 2002 , pp. 161-174 More about this Journal

Abstract

A new technique for numerical calculation of viscoelastic flow based on the combination of Neural Net-works (NN) and Brownian Dynamics simulation or Stochastic Simulation Technique (SST) is presented in this paper. This method uses a "universal approximator" based on neural network methodology in combination with the kinetic theory of polymeric liquid in which the stress is computed from the molecular configuration rather than from closed form constitutive equations. Thus the new method obviates not only the need for a rheological constitutive equation to describe the fluid (as in the original Calculation Of Non-Newtonian Flows: Finite Elements St Stochastic Simulation Techniques (CONNFFESSIT) idea) but also any kind of finite element-type discretisation of the domain and its boundary for numerical solution of the governing PDE's. As an illustration of the method, the time development of the planar Couette flow is studied for two molecular kinetic models with finite extensibility, namely the Finitely Extensible Nonlinear Elastic (FENE) and FENE-Peterlin (FENE-P) models.P) models.

Keywords

Brownian dynamics; neural networks; molecular models; stochastic simulation; viscoelastic flow; diffusion equation; Fokker-Plank equation; Brownian simulation; CONNFFESSIT;

Citations & Related Records

Times Cited By KSCI : 1 (Citation Analysis)
Times Cited By Web Of Science : 8 (Related Records In Web of Science)

Reference
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