Reduced-order modelling of equations of state using tensor decomposition for robust, accurate and efficient property calculation in high-pressure fluid flow simulations

Computationally efficient, accurate and robust Computational Fluid Dynamics (CFD) simulations involving thermodynamic properties from Equations of State (EOS) are hindered by limitations dictated by coupling strategies between EOS and CFD codes. This is a key aspect for a wide range of Chemical Engineering designs with special emphasis on those involving transcritical flows. We introduce a ROM approach based on a non-structured and sparse implementation of the Canonical Polyadic Decomposition of tensors that target abovementioned requirements. It reaches a similar speed with regards to direct use of the full equation of state and provides mean errors about 1 %-5 % without limiting accuracy. Its implementation is done in a standard and portable way, avoiding the need of additional implementation and an easy coupling with open and commercial CFD codes. The method is tested here for CFD but it can be directly applied in any process simulation tool. (C) 2020 Elsevier B.V. All rights reserved.