systems up to high temperature and high pressure conditions

Thermodynamic and volumetric properties of polymeric systems play an important role in the polymer industry and are often a key factor in polymer production, processing, and material development, especially for the design of advanced polymeric materials [۱]. Predicting the thermodynamic properties of polymers especially at high temperature-high pressure (HTHP) conditions is of great importance in industry. An artificial neural network (ANN) can be a suitable alternative to model the different thermodynamic properties of chemical systems. ANN is a simple method for modeling, which does not need explicit formulation of exact mathematical or physical relations between input and output data. In this study, the applicability of ANN in predicting the specific volume of polymeric systems up to high temperature and high pressure conditions is investigated.

کلیدواژه ها:

Polymer ، ANN ، Group contribution method (GCM) ، Specific volume.