Open AccessA systematic methodology for energy modeling improvement of cross-ventilated buildings in dense urban areas
Author(s) -
Mohammadreza Shirzadi,
Parham A. Mirzaei,
Mohammad Naghashzadegan
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/609/7/072014
Subject(s) - computational fluid dynamics , calibration , computer science , metric (unit) , ventilation (architecture) , energy consumption , closure (psychology) , indoor air quality , energy (signal processing) , building energy simulation , efficient energy use , environmental science , simulation , engineering , aerospace engineering , mechanical engineering , energy performance , mathematics , environmental engineering , operations management , statistics , electrical engineering , economics , market economy
Cross-ventilation strategy is an efficient and reliable method, which has been used in modern zero-energy buildings and traditional buildings for reducing building energy consumption and improving indoor air quality. The accuracy of current models based on building energy simulation (BES) and computational fluid dynamics (CFD) are questionable in dense urban areas. Hence, in this paper, a systematic methodology is introduced aiming to improve the energy modeling accuracy of cross-ventilated buildings in urban areas. The methodology comprises of three main steps for validation metric definition, CFD model calibration, and BES model calibration. The CFD model calibration is based on the stochastic optimization of the closure coefficients while BES model calibration is carried out by using results of the calibrated CFD model and approximation models. The proposed method was applied to a small multi-story building surrounded by eight buildings in a neutral atmospheric boundary layer (ABL) in Rasht city, Iran. According to the results, the accuracy of the modified BES model is 60% higher than the default BES model in prediction of the cross-ventilation energy-saving potential.