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  • SYSID18_0041_FI_CFD

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Computational Fluid Dynamics and Data-Based Mechanistic Modelling of a Forced Ventilation Chamber

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>2018
Issue number15
Number of pages6
Pages (from-to)263-268
Publication StatusPublished
Early online date8/10/18
<mark>Original language</mark>English
Event18th IFAC Symposium on System Identification - Stockholm, Sweden
Duration: 9/07/201811/07/2018


Symposium18th IFAC Symposium on System Identification


The research behind this article ultimately concerns control system robustness and optimisation for the regulation of temperatures in multiple buildings that are linked to a controllable external heating supply network. Lancaster University campus is being used as a case study, for which the building management system provides data. Nonetheless, situations arise when it is difficult or expensive to obtain suitable data for specific rooms or buildings and, in such cases, computational fluid dynamics (CFD) models are utilised to investigate relevant heat transfer phenomena. Such models can be limited by their complexity and they are inappropriate for model-based control design. Hence, the present article investigates a hybrid approach based on both CFD and data-based mechanistic (DBM) models. DBM models are obtained initially from statistical analysis of observational time-series but are only considered credible if they can be interpreted in physically meaningful terms. A laboratory forced ventilation chamber is used to investigate the modelling issues arising and to make recommendations relating to the wider project. The chamber is first discretised into finite volumes and the associated Navier--Stokes equations are solved to determine the physical properties of each zone. The model responses are compared with experimental data and analysed using the DBM approach.