Methods for Selecting Design Alternatives through Integrated Analysis of Energy Performance of Buildings and the Physiological Responses of Occupants
Abstract
:1. Introduction
1.1. Research Background and Objectives
1.2. Scope and Procedure of the Research
- 1.
- VR-EEG experiment and data analysis stage
- 2.
- DesignBuilder simulation experiment and analysis stage
- 3.
- Selection of design alternatives stage
2. Methods
2.1. Architectural Design Alternatives
2.1.1. Selection of Architectural Design Elements
2.1.2. Design Alternative Modeling
2.2. VR-EEG Experiment
2.2.1. Participants
2.2.2. EEG Analysis Metrics
2.2.3. Experimental Environment and Procedures
2.2.4. Experimental Tools
2.2.5. Data Preprocessing and Statistical Analysis
2.3. Energy Performance Simulation
2.3.1. DesignBuilder Software
2.3.2. Evaluation of Model Input Conditions
3. Analysis Results
3.1. Analysis of the EEG Responses of the Participants
3.1.1. Analysis of RAB Indicator Values for Design Alternatives
3.1.2. Selection of EEG Analysis Channels
3.1.3. Setting Arousal Level Ranges
3.2. Results of Energy Performance Analysis
3.2.1. Analysis of Primary Energy Consumption per Unit Area
3.2.2. K-Means Clustering Analysis
3.3. Selection of Design Alternatives
4. Discussion
Limitations and Future Research
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AD | Analog-to-digital |
ASHRAE | American Society of Heating, Refrigerating & Air Conditioning Engineers |
BEMS | Building energy management system |
BIM | Building information modeling |
EEG | Electroencephalography |
FFT | Fast Fourier transform |
HMD | Head-mounted display |
HTC | High-tech computer |
LEED | Leadership in Energy and Environmental Design |
PWI-SF | Psychosocial Well-Being Index—Short Form |
RAB | Ratio of alpha waves to beta waves |
SHGC | Solar heat gain coefficient |
STPV | Semi-transparent photovoltaics |
TMY | Typical meteorological year |
TRNSYS | Transient system simulation |
VLT | Visible light transmittance |
VR | Virtual reality |
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Experimental Group | Block 1 | Block 2 | Block 6 | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Stimulus no. | S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | S9 | S10 | … | S26 | S27 | S28 | S29 | S30 |
Aspect ratio | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1:1.6 | 1.6:1 | 1.6:1 | 1.6:1 | 1.6:1 | 1.6:1 | |
Ceiling height (m) | 2.3 | 2.3 | 2.3 | 2.3 | 2.3 | 2.7 | 2.7 | 2.7 | 2.7 | 2.7 | 3.0 | 3.0 | 3.0 | 3.0 | 3.0 | |
Window-to-wall ratio (%) | 20 | 40 | 60 | 80 | 100 | 20 | 40 | 60 | 80 | 100 | 20 | 40 | 60 | 80 | 100 |
Input Category | Input Values | ||
---|---|---|---|
Location site | Seoul | ||
dimension | Unit room: 3.4 × 5.2 × 4.0 m | ||
Construction | U-Value | Wall | 0.24 W/m2-K |
Slab | 1.52 W/m2-K | ||
Window | 1.50 W/m2-K | ||
Indoor Condition | Temperature | Heating | 20 °C |
Cooling | 22 °C | ||
Occupancy density | 0.0588 people/m2 | ||
Metabolic factor | 0.85 | ||
Power density | 3.58 W/m2 | ||
Light | 300 lux | ||
Operation Schedule | Weekdays | 0:00–24:00 h | |
Weekends | 0:00–24:00 h |
Ranking | Stimulus No. | Architectural Design Elements | Standardized RAB Indicator Value | Median | Deviation Rate | Arousal Level | ||
---|---|---|---|---|---|---|---|---|
Aspect Ratio | Ceiling Height (m) | Window-to-Wall Ratio (%) | ||||||
1 | 20 | 1.6:1 | 2.3 | 100 | −0.059 | −0.181 | 12.2 | Very low level |
2 | 3 | 1:1.6 | 2.3 | 60 | −0.080 | −0.181 | 10.1 | |
3 | 9 | 1:1.6 | 2.7 | 80 | −0.106 | −0.181 | 7.5 | |
4 | 19 | 1.6:1 | 2.3 | 80 | −0.118 | −0.181 | 6.3 | |
5 | 30 | 1.6:1 | 3.0 | 100 | −0.132 | −0.181 | 4.9 | |
6 | 27 | 1.6:1 | 3.0 | 40 | −0.134 | −0.181 | 4.7 | |
6 | 28 | 1.6:1 | 3.0 | 60 | −0.134 | −0.181 | 4.7 | |
7 | 4 | 1:1.6 | 2.3 | 80 | −0.142 | −0.181 | 3.9 | |
8 | 14 | 1:1.6 | 3.0 | 80 | −0.152 | −0.181 | 2.9 | Low level |
9 | 24 | 1.6:1 | 2.7 | 80 | −0.159 | −0.181 | 2.2 | |
10 | 10 | 1:1.6 | 2.7 | 100 | −0.166 | −0.181 | 1.5 | |
11 | 7 | 1:1.6 | 2.7 | 40 | −0.174 | −0.181 | 0.7 | |
12 | 1 | 1:1.6 | 2.3 | 20 | −0.175 | −0.181 | 0.6 | |
13 | 12 | 1:1.6 | 3.0 | 40 | −0.179 | −0.181 | 0.2 | |
14 | 17 | 1.6:1 | 2.3 | 40 | −0.180 | −0.181 | 0.1 | |
15 | 2 | 1:1.6 | 2.3 | 40% | −0.181 | −0.181 | 0 | Intermediate level |
15 | 25 | 1.6:1 | 2.7 | 100% | −0.181 | −0.181 | 0 | |
16 | 8 | 1:1.6 | 2.7 | 60% | −0.192 | −0.181 | −1.1 | High level |
17 | 11 | 1:1.6 | 3.0 | 20% | −0.193 | −0.181 | −1.2 | |
18 | 5 | 1:1.6 | 2.3 | 100% | −0.194 | −0.181 | −1.3 | |
19 | 6 | 1:1.6 | 2.7 | 20% | −0.196 | −0.181 | −1.5 | |
20 | 18 | 1.6:1 | 2.3 | 60% | −0.199 | −0.181 | −1.8 | |
21 | 15 | 1:1.6 | 3.0 | 100% | −0.200 | −0.181 | −1.9 | |
22 | 26 | 1.6:1 | 3.0 | 20% | −0.205 | −0.181 | −2.4 | |
23 | 16 | 1.6:1 | 2.3 | 20% | −0.206 | −0.181 | −2.5 | |
24 | 29 | 1.6:1 | 3.0 | 80% | −0.209 | −0.181 | −2.8 | |
25 | 21 | 1.6:1 | 2.7 | 20% | −0.217 | −0.181 | −3.6 | |
26 | 23 | 1.6:1 | 2.7 | 60% | −0.220 | −0.181 | −3.9 | |
27 | 22 | 1.6:1 | 2.7 | 40% | −0.235 | −0.181 | −5.4 | Very high level |
28 | 13 | 1:1.6 | 3.0 | 60% | −0.249 | −0.181 | −6.8 |
Ranking | Stimulus No. | Architectural Design Elements | Primary Energy Consumption per Unit Area | Cluster | ||
---|---|---|---|---|---|---|
Aspect Ratio | Ceiling Height (m) | Window-to-Wall Ratio (%) | ||||
1 | 1 | 1:1.6 | 2.3 | 20 | 333.3806 | 1 |
2 | 16 | 1.6:1 | 2.3 | 20 | 340.8252 | |
3 | 6 | 1:1.6 | 2.7 | 20 | 347.5869 | |
4 | 2 | 1:1.6 | 2.3 | 40 | 348.8503 | |
5 | 21 | 1.6:1 | 2.7 | 20 | 356.751 | |
6 | 11 | 1:1.6 | 3.0 | 20 | 358.2649 | |
7 | 3 | 1:1.6 | 2.3 | 60 | 364.228 | |
8 | 7 | 1:1.6 | 2.7 | 40 | 365.5719 | |
9 | 17 | 1.6:1 | 2.3 | 40 | 366.4862 | |
10 | 26 | 1.6:1 | 3.0 | 2 | 368.5466 | |
11 | 12 | 1:1.6 | 3.0 | 40 | 378.1458 | 3 |
12 | 4 | 1:1.6 | 2.3 | 80 | 379.7582 | |
13 | 8 | 1:1.6 | 2.7 | 60 | 383.4911 | |
14 | 22 | 1.6:1 | 2.7 | 40 | 386.6479 | |
15 | 18 | 1.6:1 | 2.3 | 60 | 392.7244 | |
16 | 5 | 1:1.6 | 2.3 | 100 | 394.5489 | |
17 | 13 | 1:1.6 | 3.0 | 60 | 397.9597 | |
18 | 27 | 1.6:1 | 3.0 | 40 | 401.5976 | |
19 | 9 | 1:1.6 | 2.7 | 80 | 401.6113 | |
20 | 23 | 1.6:1 | 2.7 | 60 | 417.3301 | |
21 | 14 | 1:1.6 | 3.0 | 80 | 418.0263 | |
22 | 10 | 1:1.6 | 2.7 | 100 | 418.9126 | |
23 | 19 | 1.6:1 | 2.3 | 80 | 419.6733 | |
24 | 28 | 1.6:1 | 3.0 | 60 | 435.5712 | 2 |
25 | 15 | 1:1.6 | 3.0 | 100 | 437.198 | |
26 | 20 | 1.6:1 | 2.3 | 100 | 445.4888 | |
27 | 24 | 1.6:1 | 2.7 | 80 | 448.7792 | |
28 | 29 | 1.6:1 | 3.0 | 80 | 470.3499 | |
29 | 25 | 1.6:1 | 2.7 | 100 | 478.9056 | |
30 | 30 | 1.6:1 | 3.0 | 100 | 503.6237 |
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Kim, S.; Ryu, J.; Lee, Y.; Park, H.; Lee, K. Methods for Selecting Design Alternatives through Integrated Analysis of Energy Performance of Buildings and the Physiological Responses of Occupants. Buildings 2024, 14, 237. https://doi.org/10.3390/buildings14010237
Kim S, Ryu J, Lee Y, Park H, Lee K. Methods for Selecting Design Alternatives through Integrated Analysis of Energy Performance of Buildings and the Physiological Responses of Occupants. Buildings. 2024; 14(1):237. https://doi.org/10.3390/buildings14010237
Chicago/Turabian StyleKim, Sanghee, Jihye Ryu, Yujeong Lee, Hyejin Park, and Kweonhyoung Lee. 2024. "Methods for Selecting Design Alternatives through Integrated Analysis of Energy Performance of Buildings and the Physiological Responses of Occupants" Buildings 14, no. 1: 237. https://doi.org/10.3390/buildings14010237
APA StyleKim, S., Ryu, J., Lee, Y., Park, H., & Lee, K. (2024). Methods for Selecting Design Alternatives through Integrated Analysis of Energy Performance of Buildings and the Physiological Responses of Occupants. Buildings, 14(1), 237. https://doi.org/10.3390/buildings14010237