Molecular weight distribution dependent kernels in generalized mixing rules

Molecular Weight Dependent Kernels in Generalized Mixing Rules

In this paper, a model is proposed for the kernel in the generalized mixing rule recently formulated by Anderssen and Mead (1998). In order to derive such a model, it is necessary to take account of the rheological significance of the kernel in terms of the relaxation behaviour of the individual polymers involved. This leads naturally to consider a way how additional physical effects, which dep...

Rheological Method for Determining Molecular Weight and Molecular Weight Distribution

The molecular-weight distribution of glycosaminoglycans.

1. A rapid and sensitive method for the accurate estimation of the molecular-weight distribution of keratan sulphate and chondroitin sulphate isolated from adult bovine nasal septum and intervertebral disc is described. The method utilizes gel chromatography of reductively labelled glycosaminoglycan and end-group estimation of number-average molecular weight for each fraction across the peak of...

Calculation of Molecular Weight Distribution from Molecular Weight Moments in Free Radical Polymerization

A novel method is presented for the calculation of weight chain length distribution in free radical polymerization of vinyl monomers. In the proposed method, polymerization kinetic equations and molecular weight moment equations are used in conjunction with a function that defines the weight fraction of polymer in a finite chain length interval. The entire range of molecular weight is divided i...

Determination of Minimum Miscibility Pressure in Gas Injection Process by Using ANN with Various Mixing Rules

Miscible gas injection is one of the most effective enhanced oil recovery techniques and minimum miscibility pressure (MMP) is an important parameter in miscible gas injection processes. The accurate determination of this parameter is critical for an adequate design of injection equipment investment prospect. The purpose of this paper is to develop a new universal artificial neural network (U-A...