Understanding the relationship between awareness and energy-saving behavior is vital for implementing effective energy efficiency policies and interventions. This study specifically examines this connection within office buildings. Building upon the Theory of Planned Behavior (TPB), an extended model is employed as the theoretical framework. Structural equation modeling (SEM) is used to assess the strength of relationships between structures. This analysis showed that environmental awareness has a significant impact on individuals’ energy conservation awareness and behavior in office buildings, and that the impact of environmental awareness varies depending on the item of energy conservation behavior.

We verified the validity of using woven glass fabrics as ceiling materials by conducting experiments where participants performed visual target detections behind the glass fiber ceiling and evaluated the target appearance under various conditions. We found that occupants cannot detect the visual target through the glass fabric ceiling with a porosity of 30% if the ceiling is illuminated as high as 1000lx and that the higher the porosity, the higher the target illuminance, and the lower the ceiling illuminance, the more annoying the target appears. Finally, we proposed a design tool to determine appropriate lighting for the glass fabric ceiling.

In recent years, much attention has been focused on the psychological and visual effects of windows, such as view. The aim of this research is to make a new method for quantitatively evaluating the view. In a previous paper, we proposed a method for evaluating the view from windows with blinds. As the next step, we consider the view through roll screens. In this study, we incorporate texture perception mechanisms into existing algorithm. The results of the subject experiment conducted in a model space showed that the clarity could be well estimated by the algorithm proposed in the research.

This study aimed to examine the detailed workers’ adjustment behaviors during summer and the impact of the behaviors on thermal comfort. We investigated of thermal environment and thermal comfort in a newly constructed ZEB Ready government building in Taiki, Hokkaido during summer. The result that workers’ adjustment behaviors were implemented in 85.0%. In addition, workers’ adjustment behaviors improved thermal comfort, even in high performance buildings. However, it was also found that there are issues with the operational policies and how to implement workers’ adjustment behaviors. This suggested the importance of the building environment education to workers.

This study examines the peak wind speed statistics and their uncertainty at the pedestrian level around an isolated building model using Large-Eddy Simulation (LES). Understanding pedestrian-level wind conditions is crucial for building design focused on comfort and safety. Traditional methods, often limited by the inability to directly assess peak speeds through wind tunnel experiments or computational fluid dynamics, rely on lower-order statistical measures combined with gust and peak factors. Our approach allows for a more direct and reliable estimation of these wind statistics, providing insights into the complexities of building-induced winds and their impact on pedestrian-level environments.

In the prediction of non-isothermal field in urban district, it is an issue that the generation of inflow turbulence that reproduce velocity and temperature fluctuations in actual meteorological fields. In this study, we generated inflow turbulence considering the effects of atmospheric stability and meteorological disturbance based on a spatial filtering and rescaling method (Kawai, Tamura, 2020) using WRF-LES results. The inflow turbulence reproduced well the characteristics of convective boundary layer, vertical temperature flux and temperature fluctuation around the inversion layer.

This report examines a method for classifying building energy consumption and quantifying its characteristics using machine learning methods for a group of buildings with a mix of uses and multiple energy sources. As a result of this analysis, characteristic of building energy consumption could be distinguishable according to feature analysis based on the re-clustering method. Furthermore, the bubble chart diagram, which visually represents the building energy consumption efficiency and building energy consumption characteristics for each building, was shown to be effective for identifying priority countermeasure buildings in each cluster.