Combining CFD and data-based mechanistic (DBM) modelling approaches

Abstract

This paper outlines a methodology for the reduction of a complex computational fluid dynamics (CFD) model using data-based mechanistic (DBM) modelling technique. For this study a full scale, adiabatic walled ventilated installation was used. Primarily, a CFD model that is three dimensional, transient and turbulent was proposed and solved by a commercial package CFX 4.3 in order to obtain informative data that will be used to build a DBM model. At the inlet a step rise in temperature was applied and the ventilation rate is kept steady. Turbulence is modelled by the widely used standard k– ϵ model. Temperature responses at 36 monitoring positions inside the installation were extracted out of the simulation. In the second stage of the work, for the same ventilation system, a DBM model was formulated from an energy balance equation. The simplified refined instrumental variable (SRIV) algorithm is employed as model parameter identification tool. The obtained highly accurate model parameters for all monitoring positions demonstrate the possibility of reducing complex CFD models using identification technique.