Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney SystemSource: Journal of Solar Energy Engineering:;2017:;volume( 139 ):;issue: 003::page 31001DOI: 10.1115/1.4035516Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney.
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contributor author | Park, David | |
contributor author | Battaglia, Francine | |
date accessioned | 2017-11-25T07:19:17Z | |
date available | 2017-11-25T07:19:17Z | |
date copyright | 2017/16/1 | |
date issued | 2017 | |
identifier issn | 0199-6231 | |
identifier other | sol_139_03_031001.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4235711 | |
description abstract | A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney System | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 3 | |
journal title | Journal of Solar Energy Engineering | |
identifier doi | 10.1115/1.4035516 | |
journal fristpage | 31001 | |
journal lastpage | 031001-9 | |
tree | Journal of Solar Energy Engineering:;2017:;volume( 139 ):;issue: 003 | |
contenttype | Fulltext |