• Energy Research

The use of radiant panels in homes has increased recently because they do not cause a drafty feeling, unlike air conditioners. However, air conditioners are more power-efficient than radiant panels and have a higher coefficient of performance (COP). Therefore, combining radiant panels and air conditioning can provide an optimal solution for thermal control in residences. Energy simulation (ES) and computational fluid dynamics (CFD) can be used to simulate such environments. ES is suitable for non-steady state calculations, and combined with appropriate modeling, enables an accurate estimation of power consumption. Effective dehumidification becomes necessary, during summer as the relative humidity in a room increases. Both air conditioners and radiant panels can achieve this. This study developed a simulation tool that incorporates the effects of dehumidification. Based on a relative evaluation, a case was proposed where both energy efficiency and comfort were satisfied by jointly using air conditioners and radiant panels. The study found that a small number of panels could achieve the most balanced operation. The results of this study can serve as a reference for general housing, and the developed simulation tool can be applied to product development and building material design.

The use of radiant panels in homes has increased recently because they do not cause a drafty feeling, unlike air conditioners. However, air conditioners are more power-efficient than radiant panels and have a higher coefficient of performance (COP). Therefore, combining radiant panels and air conditioning can provide an optimal solution for thermal control in residences. Energy simulation (ES) and computational fluid dynamics (CFD) can be used to simulate such environments. ES is suitable for non-steady state calculations, and combined with appropriate modeling, enables an accurate estimation of power consumption. Effective dehumidification becomes necessary, during summer as the relative humidity in a room increases. Both air conditioners and radiant panels can achieve this. This study developed a simulation tool that incorporates the effects of dehumidification. Based on a relative evaluation, a case was proposed where both energy efficiency and comfort were satisfied by jointly using air conditioners and radiant panels. The study found that a small number of panels could achieve the most balanced operation. The results of this study can serve as a reference for general housing, and the developed simulation tool can be applied to product development and building material design.

The number of houses with large, continuous spaces has increased recently. With improvements in insulation performance, it has become possible to efficiently air condition such spaces using a single air conditioner. However, the air conditioning efficiency depends on the placement of the air conditioner. The only way to determine the optimal placement of such air conditioners is to conduct an experiment or use computational fluid dynamic analysis. However, because the analysis is performed over a limited period, it is difficult to consider non-stationarity effects without using an energy simulation. Therefore, in this study, energy simulations and computational fluid dynamics analyses were coupled to develop a thermal environment analysis method that considers non-stationarity effects, and various air conditioner arrangements were investigated to demonstrate the applicability of the proposed method. The accuracy verification results generally followed the experimental results. A case study was conducted using the calculated boundary conditions, and the results showed that the placement of two air conditioners in the target experimental house could provide sufficient air conditioning during both winter and summer. Our results suggest that this method can be used to conduct preliminary studies if the necessary data are available during design or if an experimental house is used.

The number of houses with large, continuous spaces has increased recently. With improvements in insulation performance, it has become possible to efficiently air condition such spaces using a single air conditioner. However, the air conditioning efficiency depends on the placement of the air conditioner. The only way to determine the optimal placement of such air conditioners is to conduct an experiment or use computational fluid dynamic analysis. However, because the analysis is performed over a limited period, it is difficult to consider non-stationarity effects without using an energy simulation. Therefore, in this study, energy simulations and computational fluid dynamics analyses were coupled to develop a thermal environment analysis method that considers non-stationarity effects, and various air conditioner arrangements were investigated to demonstrate the applicability of the proposed method. The accuracy verification results generally followed the experimental results. A case study was conducted using the calculated boundary conditions, and the results showed that the placement of two air conditioners in the target experimental house could provide sufficient air conditioning during both winter and summer. Our results suggest that this method can be used to conduct preliminary studies if the necessary data are available during design or if an experimental house is used.

Abstract A thermal environment simulation method was developed for a structure with a thermally complex building envelope. The method used a heat transfer simulation (HTS), computational fluid dynamics (CFD), and a two-dimensional heat-flow calculation tool called Hygrabe2D. The general HTS does not support the modeling of buildings with a radial shape. Therefore, the building envelope was evaluated using a two-dimensional heat-flow computation tool coupled to the HTS. In the HTS, the amount of advection between zones for buildings with volumes that should be divided into multiple zones was unknown. The indoor surface temperature calculated by Hygrabe2D was coupled to the HTS, and the advection and convective heat transfer coefficients between zones were calculated via CFD, which were passed to the HTS. The accuracy of the proposed method was verified and validated. The influence of calculation accuracy was investigated by comparing the accuracies in the presence and absence of the coupling of the convective heat transfer coefficient. The initial conditional dependence of coupled advection between zones was confirmed, although it had no significant effect on the calculation accuracy. Through verification of the computational load reduction, we achieved computational accuracy with a small number of couplings. The proposed method was used to evaluate the thermal environment of a building by calculating the annual room temperature and temperature inside the building skin.

Abstract A thermal environment simulation method was developed for a structure with a thermally complex building envelope. The method used a heat transfer simulation (HTS), computational fluid dynamics (CFD), and a two-dimensional heat-flow calculation tool called Hygrabe2D. The general HTS does not support the modeling of buildings with a radial shape. Therefore, the building envelope was evaluated using a two-dimensional heat-flow computation tool coupled to the HTS. In the HTS, the amount of advection between zones for buildings with volumes that should be divided into multiple zones was unknown. The indoor surface temperature calculated by Hygrabe2D was coupled to the HTS, and the advection and convective heat transfer coefficients between zones were calculated via CFD, which were passed to the HTS. The accuracy of the proposed method was verified and validated. The influence of calculation accuracy was investigated by comparing the accuracies in the presence and absence of the coupling of the convective heat transfer coefficient. The initial conditional dependence of coupled advection between zones was confirmed, although it had no significant effect on the calculation accuracy. Through verification of the computational load reduction, we achieved computational accuracy with a small number of couplings. The proposed method was used to evaluate the thermal environment of a building by calculating the annual room temperature and temperature inside the building skin.

In building design, several approaches have been proposed for coupling computational fluid dynamics (CFD) and energy simulation (ES) to perform analyses of thermal environments. The unsteady analysis of thermal environments within buildings containing offices and colonnade spaces is difficult to perform using an ES that represents the space with a single mass point, owing to excessive predictive heat loss; therefore, CFD has typically been used instead. Although it is possible to divide the space into zones using ES, it leads to excessive predicted heat loss and the prediction of heat movement due to the influence of strong air currents, such as those associated with air conditioners. This behavior is observed because these zones are not detailed mesh divisions. To solve these problems, we proposed a method for calculating the ratio of heat contribution to zones that were pre-divided using CFD followed by the distribution of the total thermal load calculated by ES. In this study, we proposed a method for coupling ES and CFD, which enabled the unsteady analysis of a thermal environment in a large space and verified its accuracy.

In building design, several approaches have been proposed for coupling computational fluid dynamics (CFD) and energy simulation (ES) to perform analyses of thermal environments. The unsteady analysis of thermal environments within buildings containing offices and colonnade spaces is difficult to perform using an ES that represents the space with a single mass point, owing to excessive predictive heat loss; therefore, CFD has typically been used instead. Although it is possible to divide the space into zones using ES, it leads to excessive predicted heat loss and the prediction of heat movement due to the influence of strong air currents, such as those associated with air conditioners. This behavior is observed because these zones are not detailed mesh divisions. To solve these problems, we proposed a method for calculating the ratio of heat contribution to zones that were pre-divided using CFD followed by the distribution of the total thermal load calculated by ES. In this study, we proposed a method for coupling ES and CFD, which enabled the unsteady analysis of a thermal environment in a large space and verified its accuracy.