Modelling naturally ventilated double skin facade in Modelica

Autor: Alessandro Dama, Jaime Varas del Ser, Ettore Zanetti, Francesco Casella, Olena Kalyanova Larsen
Přispěvatelé: Saelens, Dirk, Laverge, Jelle, Boydens, Wim, Helsen, Lieve
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Dama, A, del Ser, J V, Zanetti, E, Casella, F & Larsen, O K 2022, Modelling naturally ventilated double skin facade in Modelica . in D Saelens, J Laverge, W Boydens & L Helsen (eds), Proceedings of Building Simulation 2021 : 17th Conference of IBPSA ., 30335, International Building Performance Simulation Association, Building Simulation Conference proceedings, vol. 2021, pp. 1429-1436, 17th IBPSA Conference on Building Simulation, BS 2021, Bruges, Belgium, 01/09/2021 . https://doi.org/10.26868/25222708.2021.30335
DOI: 10.26868/25222708.2021.30335
Popis: In recent decades, Double Skin Facades (DSF) and their thermal performance have been subject of numerous studies in literature. Despite this, the availability of rapid, robust, and accurate tools for evaluating the performance of naturally ventilated double skin facades is still very limited, since only few published models have been accompanied by a complete experimental validation. Furthermore, the integration and coupling of such models within building energy simulation tools remains a complex task due to the multiple functionalities of the transparent and ventilated façade interacting with the building environment. To this purpose this paper presents the implementation in Modelica of a model for naturally ventilated DSF and its validation against the dataset of an experimental campaign carried out in Aalborg, Denmark. The aim is to provide an open and robust tool easily integrable in the recent development of Modelica building libraries under the umbrella of the IBPSA project 1. Moreover, in this study a sensitivity analysis has been carried out on the selection of the surface convective heat transfer inside the ventilated channel according to different correlations, which gives insight on the relevance of this choice.
Databáze: OpenAIRE