Application of control logic for optimum indoor thermal environment in buildings with double skin envelope systems

2014 ◽  
Vol 85 ◽  
pp. 59-71 ◽  
Author(s):  
Jin Woo Moon ◽  
Ji-Hyun Lee ◽  
Sooyoung Kim
Keyword(s):  
Thermal Environment ◽  
Control Logic ◽  
Indoor Thermal Environment ◽  
Skin Envelope ◽  
Double Skin

Numerical Simulation of Indoor Thermal Environment of a Double-Skin Facade Office with Different Shutter Angles

2014 ◽  
Vol 694 ◽  
pp. 256-259
Author(s):  
Xin Zhan ◽  
Hua Yang ◽  
Feng Yun Jin
Keyword(s):  
Heat Transfer ◽  
Thermal Environment ◽  
Ventilation Rate ◽  
Air Distribution ◽  
Indoor Thermal Environment ◽  
Double Skin ◽  
Computational Fluid Dynamics Cfd ◽  
Heat Transfer Simulation ◽  
Shading Devices ◽  
Rng Turbulence Model

Airflow and heat transfer simulation was conducted for a double-skin façade (DSF) system equipped with shading devices in the cavity, using computational fluid dynamics (CFD) with RNG turbulence model and PISO algorithm, for five conditions of slat angles (θ=0°, 30°, 45°, 60°, 90°). The present study indicates that the presence of shading devices influences the temperatures, the ventilation rate and the air distribution in the DSF system. Besides, the different angles will make different influences.

Artificial Neural Network for the Control of the Openings and Cooling Systems of the Double Skin Envelope Buildings

2012 ◽  
Vol 610-613 ◽  
pp. 2859-2865
Author(s):  
Jin Woo Moon ◽  
Soo Young Kim
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Control Method ◽  
Mean Square ◽  
Ann Model ◽  
Control Logic ◽  
Skin Envelope ◽  
Double Skin ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

This study aimed at developing an artificial neural network (ANN)-based temperature control method for the double skin envelope buildings. For this, control logic for opening conditions of the inner and outer surfaces’ openings as well as for cooling system’s operation was developed based on the predictive and adaptive ANN model. The parametrical optimization process for the structure and learning methods of the ANN model was conducted in terms of the number of hidden layers, the number of neurons in the hidden layers, learning rate, and moment. Then, the performance of this optimized model was tested using the similarity analysis between the predicted values from the ANN model and the measured values from the actual double skin envelope building. Analysis revealed that the developed ANN model proved its prediction accuracy and adaptability in terms of stable Root Mean Square (RMS) and Mean Square Error (MSE) values. Based on this finding, it can be concluded that the developed ANN model showed potentials to be successfully applied to the temperature controls for the double skin envelope buildings.

Optimal Design of the External Respiration Double Skin Facade

2011 ◽  
Vol 374-377 ◽  
pp. 257-262
Author(s):  
Shi Feng ◽  
Wang Wei
Keyword(s):  
Optimal Design ◽  
Natural Ventilation ◽  
Thermal Environment ◽  
External Respiration ◽  
Indoor Temperature ◽  
Temperature Changes ◽  
Indoor Thermal Environment ◽  
Double Skin ◽  
Computational Fluid Dynamics Cfd ◽  
Cfd Method

An optimal design is taken on the external respiration double skin facade (DSF) of a office building in Wuhan. The indoor thermal environment of the office units in the building have been simulated by taken computational fluid dynamics (CFD) method, and then the paper analyzes the indoor temperature changes under the condition that the internal airflow status of the DSF for natural ventilation, without shade, vents closed and other cases, discusses the influences of different inner glazed skin’s thermal properties, DSF for active ventilation and different wind speed on indoor thermal environment, according to the simulation results we obtain parameters of relevant optimal design.

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