Optimization of window-openings design for thermal comfort in naturally ventilated buildings

Stavrakakis, GM; Zervas, PL; Sarimveis, H; Markatos, NC

dc.contributor.author	Stavrakakis, GM	en
dc.contributor.author	Zervas, PL	en
dc.contributor.author	Sarimveis, H	en
dc.contributor.author	Markatos, NC	en
dc.date.accessioned	2014-03-01T01:37:35Z
dc.date.available	2014-03-01T01:37:35Z
dc.date.issued	2012	en
dc.identifier.issn	0307-904X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21567
dc.subject	Artificial Neural Networks	en
dc.subject	Computational Fluid Dynamics	en
dc.subject	Natural ventilation	en
dc.subject	Optimization	en
dc.subject	Thermal comfort	en
dc.subject	Window-openings design	en
dc.subject.classification	Engineering, Multidisciplinary	en
dc.subject.classification	Mathematics, Interdisciplinary Applications	en
dc.subject.classification	Mechanics	en
dc.subject.other	Activity levels	en
dc.subject.other	Airflow patterns	en
dc.subject.other	Artificial Neural Network	en
dc.subject.other	CFD models	en
dc.subject.other	Computational fluid	en
dc.subject.other	Computational fluid dynamics models	en
dc.subject.other	Design guidelines	en
dc.subject.other	Input-output	en
dc.subject.other	Input-output data	en
dc.subject.other	Local climate	en
dc.subject.other	Mean values	en
dc.subject.other	Meta model	en
dc.subject.other	Natural ventilation	en
dc.subject.other	Naturally ventilated buildings	en
dc.subject.other	Optimization problems	en
dc.subject.other	Radial basis functions	en
dc.subject.other	Thermal comfort index	en
dc.subject.other	Weather stations	en
dc.subject.other	Window designs	en
dc.subject.other	Window-openings design	en
dc.subject.other	Buildings	en
dc.subject.other	Climate models	en
dc.subject.other	Computational fluid dynamics	en
dc.subject.other	Computer simulation	en
dc.subject.other	Design	en
dc.subject.other	Neural networks	en
dc.subject.other	Optimization	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Ventilation	en
dc.subject.other	Thermal comfort	en
dc.title	Optimization of window-openings design for thermal comfort in naturally ventilated buildings	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.apm.2011.05.052	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.apm.2011.05.052	en
heal.language	English	en
heal.publicationDate	2012	en
heal.abstract	In the present study, a novel computational method to optimize window design for thermal comfort in naturally ventilated buildings is described. The methodology is demonstrated by means of a prototype case, which corresponds to a single-room, rural-type building. Initially, the airflow in and around the building is simulated using a Computational Fluid Dynamics model. Local climate data are recorded by a weather station and the prevailing conditions are imposed in the CFD model as inlet boundary conditions. The produced airflow patterns are utilized to predict thermal comfort indices, i.e. the PMV and its modifications for non-air-conditioned buildings, with respect to various occupant activities. Mean values of these indices (output/objective variables) within the occupied zone are calculated for different window-to-door configurations and building directions (input/design variables), to generate a database of input-output data pairs. The database is then used to train and validate Radial Basis Function Artificial Neural Network (RBF ANN) input-output "meta-models". The produced meta-models are used to formulate an optimization problem, which takes into account thermal comfort constraints recommended by design guidelines. It is concluded that the proposed methodology provides the optimal window designs, which correspond to the best objective variables for both single and several activity levels. (C) 2011 Elsevier Inc. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE INC	en
heal.journalName	Applied Mathematical Modelling	en
dc.identifier.doi	10.1016/j.apm.2011.05.052	en
dc.identifier.isi	ISI:000296113400016	en
dc.identifier.volume	36	en
dc.identifier.issue	1	en
dc.identifier.spage	193	en
dc.identifier.epage	211	en