Passive ventilation control for cooling
The aim of this paper is to show the process of creating a prediction model for the control of passive ventilation system in a hot dry climate. The paper shows that, by the right manual control of passive ventilation systems, a lower indoor temperature can be achieved, compared with the temperature...
| Autores: | , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | México |
| Recursos: | UNIVERSIDAD DE GUADALAJARA |
| Repositorio: | Viviendas y Comunidades Sustentables |
| Idioma: | español |
| OAI Identifier: | oai:www.revistavivienda.cuaad.udg.mx:article/38 |
| Acesso em linha: | https://revistavivienda.cuaad.udg.mx/index.php/rv/article/view/38 |
| Access Level: | acceso abierto |
| Palavra-chave: | temperature prediction mathematical model control passive ventilation predicción temperaturas modelo matemático ventilación pasiva |
| Resumo: | The aim of this paper is to show the process of creating a prediction model for the control of passive ventilation system in a hot dry climate. The paper shows that, by the right manual control of passive ventilation systems, a lower indoor temperature can be achieved, compared with the temperature without ventilation, during transition seasons. The investigation was carried out in the frame of postgraduate studies at the University of Sonora. The main concepts are prediction and control. The prediction is the key of the control, even it can change the course of the events. A linear regression method was used, which is one of the most used scientific prediction methods due to its adaptability. This method is a statistical analysis for estimating the relationships among variables. The mathematical model focuses on predicting indoor temperatures, based on outdoor temperatures. It was developed starting from the characterization, by measurements, of the thermal behavior of the dwelling studied, and of the local climate characteristics. By linear and multiple correlation, formulas were developed to predict the hourly interior temperature, based on the most relevant exterior variables. The metho- dology followed in this research can be used for other studies and future applications with energy savings purposes. This research has the particularity that was carried out in a hot dry climate and in a full- scale housing prototype. Because of this, it can be useful for housing developers and researchers. |
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