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Comfort Modeling in Semi-Outdoor Spaces
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Indoor comfort modelling is well known and mastered thanks to empirical indices or heat balance equations of the individual. In open buildings, called semi-outdoor spaces, assessing comfort is a considerable effort as rapid variations of ambient conditions require the transient modelling of human metabolism.
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... Nombre del modelo y tipos Referencia TEÓRICOS PMV (Predicted Mean Vote) [1,8,[9][10][11][12][13][14]] PPD (Predicted Percente Dissatisfied) [1,8] TSENS (Thermal Sensation) [1,5] DISC (Thermal Discomfort) [1,5] ET* (Effective Temperature) [1] SET* (Standard Effective Temperature) [1,15,16,17] PET (Physiological Equivalent Temperature) [18,19] EMPÍRICOS PD (Percent Dissatisfied) [1,5] ...
... Cabe resaltar que se han realizado adaptaciones de este indicador para espacios abiertos o semi-abiertos denominado en este caso Out_SET* [15]. Para calcular el SET* se emplea la expresión (43) [16]. ...
The main internationaly comfort, thermal stress and comfort zones models that have been developed are described in this work. These models are of interest as a theoretical reference for the development and understanding of a broader comfort zone model. In each one, the influence of factors and parameters, both environmental and personal, that affect the comfortable or not perception of the thermal environment is analyzed, emphasizing for each model its corresponding discomfort model. Visual informatic application was developed on Matlab® that grouped the different models studied. The application allowed comparisons to be made between them and to demonstrate that the single-variable control, systesms carried out in most buildings to guarantee comfort, giving importance only to the temperature variable, limit the influence of other variables that have an impact on customers’satisfaction. The pressure, relative humidity, and air speed also affects the comfort and energy consumption in a certain way in the building sector.
... Gagge's SET*, derived from this two-node model, is defined as the equivalent dry bulb temperature of an isothermal environment at 50% RH in which a subject, while wearing clothing standardized for activity concerned, would have the same heat stress (skin temperature) and thermo-regulatory strain (skin wettedness) as in the actual test environment [59,60]. Although SET* provides a tool for evaluating an environment it does not give a comfort scale [64]. In order to assess the degree of comfort in studied SOS Gagge's version of Fanger's PMV (called PMV*) was used as a counterpart for SET*, since it is a better index, in contrast to PMV, for measuring thermal stress of the environment caused by heat loads, as well as to the physiological heat strain caused by changing humidity of the environment and by changing vapor permeability properties of clothing worn [60]. ...
... Gagge's SET*, based on the two-node model of human thermal regulation, is one of the most common indices for evaluating thermal comfort in semi-outdoor environments [63,64,74,78,79,[86][87][88][89][90]. It is considered the best predictor of observed thermal sensation votes in semi-outdoor environments [87], as well as a very useful index for broadly explaining subject's thermal preferences concerning physical microclimatic parameters in outdoor and semi-outdoor environments [89]. ...
This study delved on the role of semi-outdoor spaces (SOS), as form-based strategies, in providing enhanced, thermally comfortable environments in highly dense urban contexts. A sample of sixty-three (63) SOS was studied, within four different mid-rise and high-rise buildings located in the warm-humid tropical city of Singapore. It was found: (i) that SOS may act as thermal buffer spaces; (ii) that microclimate creation in SOS is linked to form, specifically to geometrical variables such as void-to-solid ratio, height, height-to-depth ratio, height from ground level, green plot ratio and open space ratio, which influence significantly the environmental factors of air temperature, mean radiant temperature, air velocity and relative humidity; (iii) that some aforementioned geometrical variables (height-to-depth ratio and open space ratio) are linked to thermal comfort when estimated with SET* and PMV* thermal indices; (iv) and that thermal comfort (between −1 and +1 PMV*) can be achieved in SOS considering a typical Singaporean outdoor CLO of 0.3, especially for 1 MET (85.7% of SOS). In the context of Singapore, this study demonstrates that incorporating SOS to mid-rise and high-rise building forms promotes the creation of thermally comfortable microclimates suitable for human activity, even during the hottest hours.
... First, Gagge's SET* thermal comfort index, which is defined as the equivalent dry bulb temperature of an isothermal environment at 50% of RH in which a subject would have the same heat stress (skin temperature) and thermo-regulatory strain (skin wettedness) as in the actual environment while wearing clothing standardised for the activity concerned [43,44]. While the SET* thermal comfort index provides a tool to evaluate a semi-outdoor environment, it does not give the designer a comfort scale [73]. Therefore, and second, Gagge's PMV* thermal comfort index was used to provide designers with a comfort scale for Gagge's SET*, which calculates Fanger's PMV based on Gagge's two-node model of the human regulation system, with the exception that DRY is calculated using SET* rather than the operative temperature. ...
The lack of green open spaces undermines the environmental and social quality of tropical highly-dense cities (i.e. raises urban temperatures, limits social interaction). The goal of this study, which focused on environmental aspects, was to identify underlying factors (i.e. hypothetical constructs) in semi-outdoor spaces within building forms that explain their microclimatic behaviour, thermal comfort levels, and clustering. Sixty-three semi-outdoor spaces in four high/mid-rise building forms of Singapore were studied using microclimatic data collected from field measurements and analysed via inferential statistical methods (e.g., exploratory factor analysis, multivariate regression analysis, and hierarchical clustering analysis). Findings demonstrate: (1) that spatial attributes (i.e. height, depth, void, solid, total frontage, open frontage, area, volume, perimeter, sky view factor, green plot ratio) are manifestations of three underlying factors: volume porosity (VP), perimeter openness (PO) and exposure to sky (ES); (2) that VP and PO are significantly associated with air velocity and predicted thermal comfort; and (3) that vertical breezeways appear to be the most thermally comfortable cluster due to high VP and low PO. This study sheds new light on the spatial nature of semi-outdoor spaces, which designers can consider in order to enhance wind movement for promoting thermally comfortable semi-outdoor environments in highly-dense Singapore.
... The coupled solving procedure for PET is provided in the appendix B.3 of the present work. It was shown that the heat and mass transfer dependency with ambient air velocity can cause an important shift of the comfort zone [18,23,27]. The heat and vapour transfer modelling in comfort indices should hence be improved after [18,23] to include wind effect on clothes properties. ...
[link to full text download on Elsevier https://authors.elsevier.com/a/1Wq~-1HudMvux8 (valid until May 25th 2018)]
This work is a first thorough presentation of the widely used PET (Physiological Equivalent Temperature) comfort index. It underlines the simplifications made in solving the equation system for the PET and proposes a correction of the errors in the widespread version of the PET calculation routine. A comparison of the corrected model with a stringent solving of the equation system is made: as a result, the PET calculated after the original method introduces a bias of − 0.5 to + 2.3 [K] in the studied conditions (operative temperature, high mean radiant temperature and windy environments). The original vapour diffusion model is also examined and shows no dependency to the clothing level. The comparison with a state-of-the-art vapour transfer model exhibits a significant − 7 to + 2.6 [K] discrepancy with the corrected PET model in the aforementioned studied conditions. Links to the two versions of the code are provided in the appendix.
In highly dense tropical cities, a semi-outdoor space (SOS) is frequently used as a social space within tall building forms where people can interact and connect. Thermal comfort in SOSs within tall buildings, however, may vary depending on the type and form attributes that define it. This study classifies 63 SOSs in four tall buildings of Singapore into five types based on literature review: perimeter buffers, sky terraces, horizontal breezeways, breezeway atria and vertical breezeways. Findings suggest that the five SOS types perform differently in terms of thermal comfort (based on PMV*), environmental parameters (air temperature, mean radiant temperature, relative humidity, and air velocity), and building form attributes (height-to-depth ratio, open space ratio, and green plot ratio). Of these five, vertical breezeways and horizontal breezeways are the most thermally comfortable for all activities during a typically warm hour. It is postulated that higher thermal comfort levels in these SOS types are linked to form attributes that enhance air velocity. This study examines the pros and cons of each SOS type in terms of thermal comfort in their role as communal spaces in tall buildings situated within a highly dense tropical city.
p>En este trabajo se reflejan los resultados obtenidos, vía simulación, del estudio de las restricciones de confort de un controlador predictivo basado en modelo (MPC) no lineal, para la gestión energética del sistema centralizado de climatización de una instalación hotelera. Con el objetivo de lograr eficiencia económica, el controlador empleado utiliza un modelo de predicción del comportamiento del consumo energético de las habitaciones a partir de los registros históricos del hotel. Para satisfacer el confort térmico requerido por los ocupantes, se considera un modelo de zona de confort más completo, que el modelo utilizado por (Acosta et al. , 2016), en una de las restricciones del problema de optimización. Esto permitió un mayor ahorro energético, siendo esta la principal contribución de esta investigación. Las simulaciones de los escenarios presentados fueron realizadas con MATLAB<sup>®</sup>.</p
As part of the research carried out in the field of thermal comfort, a visual application was developed on Matlab® that grouped the different existing models of thermal comfort and discomfort. For this, a visual programming environment available in this mathematical assistant was used. With this application, comparisons between them could be established and the possible dependencies between environmental and personal factors and parameters with the comfort or thermal stress index were analyzed. This allowed to demonstrate that the monovariable controls carried out in most of the buildings to guarantee comfort, giving importance only to the temperature variable, limits the influence of other variables that have an impact on customer satisfaction such as pressure, relative humidity, the speed of the air, among others, which also affects in a certain way the energy consumption in the field of the building because some of these determining variables in the same cease to be regulated.
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