The combined effects of color temperature and illuminance in a small office on visual response and mood under various lighting conditions were examined in this study. Visual annoyance tests were conducted using a sample of 20 subjects in a full-scale mock-up test space. Computer and paper-based reading tasks were conducted for 500 lx and 750 lx illuminance levels under 3,000 K, 4,000 K and 6,500 K conditions. Two hypotheses were considered for the test in this study. The primary hypothesis was that visual perception is affected by the color temperatures of light sources. The secondary hypothesis was that better moods, such as relaxed and cozy feelings, are associated with low color temperatures given equal illuminance levels. The visual environment under the 3,000 K condition was characterized by glare and brightness, resulting in visual discomfort when target illuminance was higher than 500 lx. Occupants preferred 500 lx under the 6,500 K condition, and 500 lx and 750 lx under the 4,000 K condition, reporting better visual satisfaction when performing office tasks. Prediction models for visual comfort suggest that the less that subjects are visually bothered by light during tasks, the more visual comfort they feel. User satisfaction with light source color is critical for the prediction of visual comfort under different lighting conditions. Visual comfort was the most influential factor on mood. Lower color temperature was associated with better mood at lower illuminance levels, while higher color temperature was preferred at higher illuminance levels.

This study examines the effect of interior design elements on prospective occupants’ perceptions of amenity and efficiency in a residential space. Thirty-one prospective occupants participated in a survey using virtual reality environments that consist of various combinations of interior design elements. In this study, occupants’ perceptions were discussed in terms of affordance and satisfaction, and the relationship between them is interpreted statistically. The spatial factors affecting overall satisfaction at a detailed level were discussed. The causal relationship between the interior design elements and space were determined under the elaboration of perception processing. Multiple linear relationships between a limited number of spatial factors and virtually created space were analyzed. The perceived affordance of interior design elements was influenced by priming and concrete behaviors in a space. The materials, surfaces, and colors were weak contributors to clear perceptions about space. The occupants’ evaluative perception processing elaborations were not effectively activated in the assessment of spatial design adequacy (SDA) in terms of materials, surfaces, and colors in a space.

This study examined the influence of heat recovery ventilators (HRVs) on energy savings and indoor air quality (IAQ) in high-rise residential buildings. Field measurements were performed in four residential units, which were validated by computer simulations and estimated the total annual energy consumption. The operation schedules for HRVs were determined by a survey of residents. Field measurement results indicate that HRVs could effectively improve IAQ and afford effective energy savings. The indoor concentrations of formaldehyde were reduced by 54.6% after HRVs were operated for 24 h. The initial concentration was reduced by 82% after 168 h. Toluene was the dominant volatile organic compounds (VOCs) in the indoor air. Its initial concentration was reduced by 50% and other VOCs were also reduced by 40.1% to 53.1% after HRVs were operated. Annual energy savings of up to 20.26% were predicted when HRVs were operated for 24 h continuously, exchanging sensible and latent heat. HRVs could save energy more effectively in winter than in summer due to the greater temperature difference between outdoor and indoor air. Based on the preferred operation schedules of homes surveyed, an annual energy savings could be as high as 8.52%.

This study examines the influence of illuminance variation on visual perception and mood in a small office. Field measurements and annoyance tests were performed in a full-scale mock-up office space. Subjects conducted paper-based and computer-based reading tasks when six instantaneous fluctuation ranges were given under 500 lx and 650 lx base level conditions. Results indicate that equal amounts of instantaneous illuminance fluctuation could influence visual perception differently under these two base level conditions. Visual annoyance under the 500 lx base level was more severe than that under the 650 lx base level. The acceptable illuminance fluctuation ranges that did not cause visual annoyance under 500 lx base level conditions were 141.3 lx for paper-based tasks and 187.3 lx for computer-based tasks. Under 650 lx base level conditions, the acceptable ranges were 200.3 lx and 252.4 lx for paper-based and computer-based tasks respectively. The mean mood and perception responses for visual thresholds under the 650 lx base level showed more positive feelings than those under the 500 lx base level. Multiple linear predictive models showed that feelings of visual sensitiveness to illuminance variation, visual distraction, and stimulation were significant contributors to visual annoyance under fluctuating illuminance conditions.

This study aims at developing an indoor temperature control method that could provide comfortable thermal conditions by integrating heating system control and the opening conditions of building envelopes. Artificial neural network (ANN)-based temperature control logic was developed for the control of heating systems and openings at the building envelopes in a predictive and adaptive manner. Numerical comparative performance tests for the ANN-based temperature control logic and conventional non-ANN-based counterpart were conducted for single skin enveloped and double skin enveloped buildings after the simulation program was validated by comparing the simulation and the field measurement results. Analysis results revealed that the ANN-based control logic improved the indoor temperature environment with an increased comfortable temperature period and decreased overshoot and undershoot of temperatures outside of the operating range. The proposed logic did not show significant superiority in energy efficiency over the conventional logic. The ANN-based temperature control logic was able to maintain the indoor temperature more comfortably and with more stability within the operating range due to the predictive and adaptive features of ANN models.

This study examines the performance and adaptability of Artificial Neural Network (ANN)-based thermal control strategies for diverse thermal properties of building envelope conditions applied to residential buildings. The thermal performance using two non-ANN-based control logics and two predictive ANN-based control logics was numerically tested using simulation software after validation. The performance tests were conducted for a two-story single-family house for various envelope insulation levels and window-to-wall ratios on the envelopes. The percentages of the period within the targeted ranges for air temperature, humidity and PMV, and the magnitudes of the overshoots and undershoots outside of the targeted comfort range were analyzed for each control logic scheme. The results revealed that the two predictive control logics that employed thermal predictions of the ANN models achieved longer periods of thermal comfort than the non-ANN-based models in terms of the comfort periods and the reductions of the magnitudes of the overshoots and undershoots. The ANN-based models proved their adaptability through accurate control of the thermal conditions in buildings with various architectural variables. The ANN-based predictive control methods demonstrated their potential to create more comfortable thermal conditions in single-family homes compared to non-ANN based control logics.