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Ángeles, L., (2019). Estudio numérico de rejillas de sistema de aire acondicionado usados en ambientes interiores [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/17605
Ángeles, L., Estudio numérico de rejillas de sistema de aire acondicionado usados en ambientes interiores [Tesis]. : Universidad Nacional de Ingeniería; 2019. http://hdl.handle.net/20.500.14076/17605
@mastersthesis{renati/709974,
title = "Estudio numérico de rejillas de sistema de aire acondicionado usados en ambientes interiores",
author = "Ángeles Rodríguez, Luis Enrique",
publisher = "Universidad Nacional de Ingeniería",
year = "2019"
}
Title: Estudio numérico de rejillas de sistema de aire acondicionado usados en ambientes interiores
Authors(s): Ángeles Rodríguez, Luis Enrique
Advisor(s): Celis Pérez, César
Issue Date: 2019
Institution: Universidad Nacional de Ingeniería
Abstract: El acondicionamiento de ambientes interiores busca alcanzar el bienestar y las condiciones apropiadas para el trabajo de los ocupantes del ambiente mediante una adecuada distribución del flujo de aire en el ambiente interior. La distribución de flujo de aire obtenida siguiendo metodologías de diseño convencionales basadas en estándares como los de la ASHRAE no siempre garantiza el confort térmico y la calidad de aire interior para todos los ocupantes. Esto ocurre debido a que esta distribución de flujo de aire interior depende de las condiciones de entrada de aire, la posición y tamaño de las rejillas y difusores de aire, condiciones exteriores, forma del cuarto, mobiliario, entre otros. Este artículo tiene como objetivo estudiar numéricamente la influencia de las condiciones del aire de suministro y el posicionamiento y tamaño de rejillas de sistemas de aire acondicionado en el confort térmico y la calidad de aire en ambientes interiores. Para ello se ha desarrollado e implementado un esquema de optimización mediante algoritmos genéticos usando técnicas de dinámica de fluidos computacional (CFD) para mejorar el confort térmico y la calidad de aire interior. La función objetivo ha sido construido para cada uno de los tres índices que representan al confort térmico (porcentaje estimado de insatisfechos (PPD), porcentaje de insatisfacción debido a la corriente de aire (PD)) y a la calidad del aire interior (Efectividad del cambio de aire (ACE)). Los principales resultados muestran que la configuración optimizada según la función objetivo f1, que depende del PPD, es la que ofrece el mejor compromiso para los tres índices considerados, en comparación a las otras dos configuraciones óptimas y a la configuración de referencia. Por otro lado, la configuración optimizada para la función objetivo f3, que depende del ACE, tiene los valores de PMV y PD alejados de los criterios de aceptabilidad dados por los estándares. La configuración de referencia determinadas siguiendo el procedimiento de diseño convencional no ofrece el confort térmico adecuado para los ocupantes del ambiente interior. El mayor valor de la temperatura aire asociada a la configuración óptima según f1 (20.28°C) con respecto a la configuración de referencia (14°C), muestra que una menor cantidad de energía es requerida para enfriar al aire de suministro.
The conditioning of internal environments seeks to achieve the well-being and the appropriate conditions for the work of the occupants in the environment through an adequate distribution of the air flow in the interior environment. The distribution of air flow obtained following conventional design methodologies based on standards such as those of the ASHRAE does not always guarantee thermal comfort and indoor air quality for all occupants. This happens because this distribution of indoor air flow depends on the air intake conditions, the position and size of air grilles and diffusers, exterior conditions, room shape, furniture, among others. The purpose of this article is to numerically study the influence of air supply conditions and the positioning and geometry of diffusers and grilles of air conditioning systems on thermal comfort and air quality in indoor environments. To this end, an optimization scheme has been developed and implemented using genetic algorithms using computational fluid dynamics (CFD) techniques to improve thermal comfort and indoor air quality. The objective function has been built for each of the three indices that represent thermal comfort (estimated percentage of unsatisfied people (PPD), percentage of dissatisfaction due to draft (PD)) and indoor air quality (Effectiveness of change of air (ACE)). The main results show that the configuration optimized according to the objective function f1, which depends on PPD, is the one that offers the best compromise for the three considered indices, in comparison to the other two optimal configurations and the reference configuration. On the other hand, the optimized configuration for the objective function f3, which depends on the ACE, has PMV and PD values far from the acceptability criteria given by the standards. The reference configuration determined following the conventional design procedure does not offer adequate thermal comfort for occupants of the indoor environment. The high value of the air temperature associated with the optimal configuration according to f1 (20.28 ° C) with respect to the reference configuration (14 ° C), shows that a smaller amount of energy is required to cool the supply air.
The conditioning of internal environments seeks to achieve the well-being and the appropriate conditions for the work of the occupants in the environment through an adequate distribution of the air flow in the interior environment. The distribution of air flow obtained following conventional design methodologies based on standards such as those of the ASHRAE does not always guarantee thermal comfort and indoor air quality for all occupants. This happens because this distribution of indoor air flow depends on the air intake conditions, the position and size of air grilles and diffusers, exterior conditions, room shape, furniture, among others. The purpose of this article is to numerically study the influence of air supply conditions and the positioning and geometry of diffusers and grilles of air conditioning systems on thermal comfort and air quality in indoor environments. To this end, an optimization scheme has been developed and implemented using genetic algorithms using computational fluid dynamics (CFD) techniques to improve thermal comfort and indoor air quality. The objective function has been built for each of the three indices that represent thermal comfort (estimated percentage of unsatisfied people (PPD), percentage of dissatisfaction due to draft (PD)) and indoor air quality (Effectiveness of change of air (ACE)). The main results show that the configuration optimized according to the objective function f1, which depends on PPD, is the one that offers the best compromise for the three considered indices, in comparison to the other two optimal configurations and the reference configuration. On the other hand, the optimized configuration for the objective function f3, which depends on the ACE, has PMV and PD values far from the acceptability criteria given by the standards. The reference configuration determined following the conventional design procedure does not offer adequate thermal comfort for occupants of the indoor environment. The high value of the air temperature associated with the optimal configuration according to f1 (20.28 ° C) with respect to the reference configuration (14 ° C), shows that a smaller amount of energy is required to cool the supply air.
Link to repository: http://hdl.handle.net/20.500.14076/17605
Discipline: Maestría en Ciencias con Mención en Energética
Grade or title grantor: Universidad Nacional de Ingeniería. Facultad de Ingeniería Mecánica. Unidad de Posgrado
Grade or title: Maestro en Ciencias con Mención en Energética
Register date: 28-May-2019
This item is licensed under a Creative Commons License