Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation
Abstract
:1. Introduction
2. The Spandrel Panels
3. Methodology
3.1. Building Description
3.2. CFD Simulation
3.3. Thermal Comfort Assessment
4. Result
4.1. Grid Sensitivity Study
4.2. CFD Model Validation
4.3. Analysis of the Temperature Distribution by Different Heights of the Spandrel Panel
4.4. Effects on the PMV
5. Discussion
6. Conclusions
- When the spandrel panel height was 0 m, the highest temperature was observed in all cases, while the lowest temperature distribution was observed when spandrel panel height was 0.9 m. The temperature difference when the spandrel panel heights were from 0 m to 0.9 m was about 1–3 °C, which was caused by the variation of the glazing area. In addition, the cooling system could not effectively reduce heat gain when the spandrel panel height was zero. In addition, temperature distributions when spandrel panel heights were 0.6 m and 0.9, respectively, were close to or below the setpoint temperature.
- For thermal comfort evaluation, PMV values at 1.5 m from the floor in all cases were larger than zero. PMV values in all cases were within the range of slightly cool to warm. When spandrel panel height was 0 m, the highest thermal sensation (warm) among the cases was observed, which may cause thermal dissatisfaction for occupants. When the spandrel panel height was 0.3 m, the thermal sensation ranged from neutral to slightly warm. As for the spandrel panel height of 0.6 m, a slight decrease in the degree of thermal comfort was observed, when compared to that of the 0.3-m spandrel panel. For the case of 0.9 m of spandrel panel height, PMV values were below 0.5 and close to zero near the glazing, it had the smallest glazing area among the cases.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Oh, M.; Jang, K.M.; Kim, Y. Empirical analysis of building energy consumption and urban form in a large city: A case of seoul, south korea. Energy Build. 2021, 245, 111046. [Google Scholar] [CrossRef]
- Lei, L.; Chen, W.; Wu, B.; Chen, C.; Liu, W. A building energy consumption prediction model based on rough set theory and deep learning algorithms. Energy Build. 2021, 240, 110886. [Google Scholar] [CrossRef]
- Pi, Z.X.; Li, X.H.; Ding, Y.M.; Zhao, M.; Liu, Z.X. Demand response scheduling algorithm of the economic energy consumption in buildings for considering comfortable working time and user target price. Energy Build. 2021, 250, 111252. [Google Scholar] [CrossRef]
- Ding, Y.; Fan, L.; Liu, X. Analysis of feature matrix in machine learning algorithms to predict energy consumption of public buildings. Energy Build. 2021, 249, 111208. [Google Scholar] [CrossRef]
- Li, L.; Wang, Y.; Wang, M.; Hu, W.; Sun, Y. Impacts of multiple factors on energy consumption of aging residential buildings based on a system dynamics model--taking northwest china as an example. J. Build. Eng. 2021, 44, 102595. [Google Scholar] [CrossRef]
- The Annual Energy Consumption in 2017, Korea Energy Agency. Available online: https://www.Energy.Or.Kr/renew_eng/main/main.Aspx (accessed on 30 June 2022).
- Agency, K.E. Energy Statistics Handbook. 2020. Available online: https://www.Energy.Or.Kr/web/kem_home_new/new_main.Asp (accessed on 4 August 2022).
- Kim, D.-B.; Kim, D.D.; Kim, T. Energy performance assessment of hvac commissioning using long-term monitoring data: A case study of the newly built office building in south korea. Energy Build. 2019, 204, 109465. [Google Scholar] [CrossRef]
- Leung, C.K.; Lu, L.; Liu, Y.; Cheng, H.S.; Tse, J.H. Optical and thermal performance analysis of aerogel glazing technology in a commercial building of hong kong. Energy Built Environ. 2020, 1, 215–223. [Google Scholar] [CrossRef]
- Kiran Kumar, G.; Saboor, S.; Ashok Babu, T.P. Investigation of various wall and window glass material buildings in different climatic zones of india for energy efficient building construction. Mater. Today Proc. 2018, 5, 23224–23234. [Google Scholar] [CrossRef]
- Lu, S.; Li, Z.; Zhao, Q.; Jiang, F. Modified calculation of solar heat gain coefficient in glazing façade buildings. Energy Procedia 2017, 122, 151–156. [Google Scholar] [CrossRef]
- Zhang, Y.; Tennakoon, T.; Chan, Y.H.; Chan, K.C.; Fu, S.C.; Tso, C.Y.; Yu, K.M.; Huang, B.L.; Yao, S.H.; Qiu, H.H.; et al. Energy consumption modelling of a passive hybrid system for office buildings in different climates. Energy 2022, 239, 121914. [Google Scholar] [CrossRef]
- Lim, T.; Yim, W.-S.; Kim, D.-D. Analysis of the thermal and cooling energy performance of the perimeter zones in an office building. Buildings 2022, 12, 141. [Google Scholar] [CrossRef]
- Berardi, U.; Kisilewicz, T.; Kim, S.; Lechowska, A.; Paulos, J.; Schnotale, J. Experimental and numerical investigation of the thermal transmittance of pvc window frames with silica aerogel. J. Build. Eng. 2020, 32, 101665. [Google Scholar] [CrossRef]
- Paulos, J.; Berardi, U. Optimizing the thermal performance of window frames through aerogel-enhancements. Applied Energy 2020, 266, 114776. [Google Scholar] [CrossRef]
- Sghiouri, H.; Mezrhab, A.; Karkri, M.; Naji, H. Shading devices optimization to enhance thermal comfort and energy performance of a residential building in morocco. J. Build. Eng. 2018, 18, 292–302. [Google Scholar] [CrossRef]
- Huang, Y.; Niu, J.-L.; Chung, T.-M. Comprehensive analysis on thermal and daylighting performance of glazing and shading designs on office building envelope in cooling-dominant climates. Appl. Energy 2014, 134, 215–228. [Google Scholar] [CrossRef]
- Liu, S.; Kwok, Y.T.; Lau, K.K.-L.; Chan, P.W.; Ng, E. Investigating the energy saving potential of applying shading panels on opaque façades: A case study for residential buildings in hong kong. Energy Build. 2019, 193, 78–91. [Google Scholar] [CrossRef]
- Alhuwayil, W.K.; Abdul Mujeebu, M.; Algarny, A.M.M. Impact of external shading strategy on energy performance of multi-story hotel building in hot-humid climate. Energy 2019, 169, 1166–1174. [Google Scholar] [CrossRef]
- Huo, H.; Xu, W.; Li, A.; Cui, G.; Wu, Y.; Liu, C. Field comparison test study of external shading effect on thermal-optical performance of ultralow-energy buildings in cold regions of china. Build. Environ. 2020, 180, 106926. [Google Scholar] [CrossRef]
- Chan, A.L.S. Effect of adjacent shading on the energy and environmental performance of photovoltaic glazing system in building application. Energy 2019, 187, 115939. [Google Scholar] [CrossRef]
- La Ferla, G.; Acha Román, C.A.; Roset Calzada, J. Radiant glass façade technology: Thermal and comfort performance based on experimental monitoring of outdoor test cells. Build. Environ. 2020, 182, 107075. [Google Scholar] [CrossRef]
- Danis, J.; Mishra, S.; Rempel, A.R. Direct heat flux sensing for window shading control in passive cooling systems. Energy Build. 2022, 261, 111950. [Google Scholar] [CrossRef]
- Pereira Tavares, M.C.; Perdigão Gonçalves, H.J.; de Faria Corrêa Bastos, J.N.T. The glazing area in residential buildings in temperate climate: The thermal-energetic performance of housing units in lisbon. Energy Build. 2017, 140, 280–294. [Google Scholar] [CrossRef]
- Lau, A.K.K.; Salleh, E.; Lim, C.H.; Sulaiman, M.Y. Potential of shading devices and glazing configurations on cooling energy savings for high-rise office buildings in hot-humid climates: The case of malaysia. Int. J. Sustain. Built Environ. 2016, 5, 387–399. [Google Scholar] [CrossRef] [Green Version]
- de Almeida Rocha, A.P.; Reynoso-Meza, G.; Oliveira, R.C.L.F.; Mendes, N. A pixel counting based method for designing shading devices in buildings considering energy efficiency, daylight use and fading protection. Appl. Energy 2020, 262, 114497. [Google Scholar] [CrossRef]
- Luo, Z.; Sun, C.; Dong, Q.; Yu, J. An innovative shading controller for blinds in an open-plan office using machine learning. Build. Environ. 2021, 189, 107529. [Google Scholar] [CrossRef]
- Atzeri, A.; Cappelletti, F.; Gasparella, A. Internal versus external shading devices performance in office buildings. Energy Procedia 2014, 45, 463–472. [Google Scholar] [CrossRef] [Green Version]
- Bunning, M.E.; Crawford, R.H. Directionally selective shading control in maritime sub-tropical and temperate climates: Life cycle energy implications for office buildings. Build. Environ. 2016, 104, 275–285. [Google Scholar] [CrossRef]
- Khidmat, R.P.; Fukuda, H.; Kustiani; Paramita, B.; Qingsong, M.; Hariyadi, A. Investigation into the daylight performance of expanded-metal shading through parametric design and multi-objective optimisation in japan. J. Build. Eng. 2022, 51, 104241. [Google Scholar] [CrossRef]
- de Vries, S.B.; Loonen, R.C.G.M.; Hensen, J.L.M. Multi-state vertical-blinds solar shading—Performance assessment and recommended development directions. J. Build. Eng. 2021, 40, 102743. [Google Scholar] [CrossRef]
- Khamma, T.R.; Zhang, Y.; Guerrier, S.; Boubekri, M. Generalized additive models: An efficient method for short-term energy prediction in office buildings. Energy 2020, 213, 118834. [Google Scholar] [CrossRef]
- Kapsis, K.; Dermardiros, V.; Athienitis, A.K. Daylight performance of perimeter office façades utilizing semi-transparent photovoltaic windows: A simulation study. Energy Procedia 2015, 78, 334–339. [Google Scholar] [CrossRef] [Green Version]
- Assem, E.O.; Al-Mumin, A.A. Code compliance of fully glazed tall office buildings in hot climate. Energy Build. 2010, 42, 1100–1105. [Google Scholar] [CrossRef]
- Mu, D.; Gao, N.; Zhu, T. Cfd investigation on the effects of wind and thermal wall-flow on pollutant transmission in a high-rise building. Build. Environ. 2018, 137, 185–197. [Google Scholar] [CrossRef]
- Li, A.; Zhang, W.; Gao, M. Field test and cfd modeling for flow characteristics in central cooking exhaust shaft of a high-rise residential building. Energy Build. 2017, 147, 210–223. [Google Scholar] [CrossRef]
- Ascione, F.; De Masi, R.F.; Mastellone, M.; Vanoli, G.P. The design of safe classrooms of educational buildings for facing contagions and transmission of diseases: A novel approach combining audits, calibrated energy models, building performance (bps) and computational fluid dynamic (cfd) simulations. Energy Build. 2021, 230, 110533. [Google Scholar] [CrossRef]
- Lam, T.C.; Ge, H.; Fazio, P. Impact of curtain wall configurations on building energy performance in the perimeter zone for a cold climate. Energy Procedia 2015, 78, 352–357. [Google Scholar] [CrossRef] [Green Version]
- Poirazis, H.; Blomsterberg, Å.; Wall, M. Energy simulations for glazed office buildings in sweden. Energy Build. 2008, 40, 1161–1170. [Google Scholar] [CrossRef]
- Konis, K. Evaluating daylighting effectiveness and occupant visual comfort in a side-lit open-plan office building in san francisco, california. Build. Environ. 2013, 59, 662–677. [Google Scholar] [CrossRef] [Green Version]
- Zhang, S.; Fine, J.P.; Touchie, M.F.; O’Brien, W. A simulation framework for predicting occupant thermal sensation in perimeter zones of buildings considering direct solar radiation and ankle draft. Build. Environ. 2020, 183, 107096. [Google Scholar] [CrossRef]
- Schiavon, S.; Webster, T.; Dickerhoff, D.; Bauman, F. Stratification prediction model for perimeter zone ufad diffusers based on laboratory testing with solar simulator. Energy Build. 2014, 82, 786–794. [Google Scholar] [CrossRef]
- Sadeghi, S.A.; Lee, S.; Karava, P.; Bilionis, I.; Tzempelikos, A. Bayesian classification and inference of occupant visual preferences in daylit perimeter private offices. Energy Build. 2018, 166, 505–524. [Google Scholar] [CrossRef]
- Shen, H.; Tzempelikos, A. Sensitivity analysis on daylighting and energy performance of perimeter offices with automated shading. Build. Environ. 2013, 59, 303–314. [Google Scholar] [CrossRef]
- Dubois, M.-C.; Blomsterberg, Å. Energy saving potential and strategies for electric lighting in future north european, low energy office buildings: A literature review. Energy Build. 2011, 43, 2572–2582. [Google Scholar] [CrossRef]
- Chen, C. A study on the renewal construction of office building exterior. Procedia Eng. 2011, 21, 155–162. [Google Scholar] [CrossRef] [Green Version]
- Wong, S.L.; Wan, K.K.W.; Lam, T.N.T. Artificial neural networks for energy analysis of office buildings with daylighting. Appl. Energy 2010, 87, 551–557. [Google Scholar] [CrossRef]
- Boafo, F.E.; Kim, J.-H.; Ahn, J.-G.; Kim, S.-M.; Kim, J.-T. Slim curtain wall spandrel integrated with vacuum insulation panel: A state-of-the-art review and future opportunities. J. Build. Eng. 2021, 42, 102445. [Google Scholar] [CrossRef]
- Chan, Y.-C.; Tzempelikos, A. Daylighting and energy analysis of multi-sectional facades. Energy Procedia 2015, 78, 189–194. [Google Scholar] [CrossRef] [Green Version]
- Kassem, M.; Mitchell, D. Bridging the gap between selection decisions of facade systems at the early design phase: Issues, challenges and solutions. J. Facade Des. Eng. 2015, 3, 165–183. [Google Scholar] [CrossRef] [Green Version]
- Sanders, R.M. Curtain Walls: Not just another pretty façade. J. Archit. Technol. 2006, 23, 1–8. [Google Scholar]
- Jelle, B.P.; Hynd, A.; Gustavsen, A.; Arasteh, D.; Goudey, H.; Hart, R. Fenestration of today and tomorrow: A state-of-the-art review and future research opportunities. Sol. Energy Mater. Sol. Cells 2012, 96, 1–28. [Google Scholar] [CrossRef] [Green Version]
- Cuce, E.; Riffat, S.B. A state-of-the-art review on innovative glazing technologies. Renew. Sustain. Energy Rev. 2015, 41, 695–714. [Google Scholar] [CrossRef]
- Van Den Bergh, S.; Hart, R.; Jelle, B.P.; Gustavsen, A. Window spacers and edge seals in insulating glass units: A state-of-the-art review and future perspectives. Energy Build. 2013, 58, 263–280. [Google Scholar] [CrossRef]
- Rezaei, S.D.; Shannigrahi, S.; Ramakrishna, S. A review of conventional, advanced, and smart glazing technologies and materials for improving indoor environment. Sol. Energy Mater. Sol. Cells 2017, 159, 26–51. [Google Scholar] [CrossRef]
- Richman, R.C.; Pressnail, K.D. A more sustainable curtain wall system: Analytical modeling of the solar dynamic buffer zone (sdbz) curtain wall. Build. Environ. 2009, 44, 1–10. [Google Scholar] [CrossRef]
- Arnesano, M.; Pandarese, G.; Martarelli, M.; Naspi, F.; Gurunatha, K.L.; Sol, C.; Portnoi, M.; Ramirez, F.V.; Parkin, I.P.; Papakonstantinou, I.; et al. Optimization of the thermochromic glazing design for curtain wall buildings based on experimental measurements and dynamic simulation. Sol. Energy 2021, 216, 14–25. [Google Scholar] [CrossRef]
- Sayed, M.A.A.E.D.A.; Fikry, M.A. Impact of glass facades on internal environment of buildings in hot arid zone. Alex. Eng. J. 2019, 58, 1063–1075. [Google Scholar] [CrossRef]
- Song, J.-H.; Lim, J.-H.; Song, S.-Y. Evaluation of alternatives for reducing thermal bridges in metal panel curtain wall systems. Energy Build. 2016, 127, 138–158. [Google Scholar] [CrossRef]
- O’Brien, W.; Kapsis, K.; Athienitis, A.K. Manually-operated window shade patterns in office buildings: A critical review. Build. Environ. 2013, 60, 319–338. [Google Scholar] [CrossRef]
- Ihara, T.; Gao, T.; Grynning, S.; Jelle, B.P.; Gustavsen, A. Aerogel granulate glazing facades and their application potential from an energy saving perspective. Appl. Energy 2015, 142, 179–191. [Google Scholar] [CrossRef]
- Korea Meteorological Administration. Available online: https://www.Weather.Go.Kr/weather/main.Jsp (accessed on 8 August 2022).
- Korean Statistical Information Service. Available online: https://kosis.Kr/index/index.Do (accessed on 10 September 2022).
- American Society of Heating, Refrigerating and Air Conditioning Engineers. Ashrae Handbook; ASHRAE: Atlanta, GA, USA, 2013; Chapter 4. [Google Scholar]
- Gavrilov, A.A.; Rudyak, V.Y. Reynolds-averaged modeling of turbulent flows of power-law fluids. J. Non-Newton. Fluid Mech. 2016, 227, 45–55. [Google Scholar] [CrossRef]
- Pasut, W.; De Carli, M. Evaluation of various cfd modelling strategies in predicting airflow and temperature in a naturally ventilated double skin façade. Appl. Therm. Eng. 2012, 37, 267–274. [Google Scholar] [CrossRef]
- Pei, G.; Rim, D. Quality control of computational fluid dynamics (cfd) model of ozone reaction with human surface: Effects of mesh size and turbulence model. Build. Environ. 2021, 189, 107513. [Google Scholar] [CrossRef]
- Shaw, E.W. Thermal comfort: Analysis and applications in environmental engineering, by p. O. Fanger. 244 pp. Danish technical press. Copenhagen, denmark, 1970. Danish kr. 76, 50. R. Soc. Health J. 1972, 92, 164. [Google Scholar] [CrossRef] [Green Version]
- Chen, Z.; Xin, J.; Liu, P. Air quality and thermal comfort analysis of kitchen environment with cfd simulation and experimental calibration. Build. Environ. 2020, 172, 106691. [Google Scholar] [CrossRef]
- The American Society of Mechanical Engineers, ASME. Procedure for estimation and reporting of uncertainty due to discretization in cfd applications. J. Fluids Eng. 2008, 130, 078001. [Google Scholar] [CrossRef] [Green Version]
- Convertino, F.; Vox, G.; Schettini, E. Evaluation of the cooling effect provided by a green façade as nature-based system for buildings. Build. Environ. 2021, 203, 108099. [Google Scholar] [CrossRef]
- Tong, S.; Wen, J.; Wong, N.H.; Tan, E. Impact of façade design on indoor air temperatures and cooling loads in residential buildings in the tropical climate. Energy Build. 2021, 243, 110972. [Google Scholar] [CrossRef]
- Standard 55-2017; Thermal Environmental Conditions for Human Occupancy. ASHRAE: Atlanta, GA, USA, 2017.
- Losi, G.; Bonzanini, A.; Aquino, A.; Poesio, P. Analysis of thermal comfort in a football stadium designed for hot and humid climates by cfd. J. Build. Eng. 2021, 33, 101599. [Google Scholar] [CrossRef]
- Dixit, A.; Gade, U. A case study on human bio-heat transfer and thermal comfort within cfd. Build. Environ. 2015, 94, 122–130. [Google Scholar] [CrossRef]
- Bay, E.; Martinez-Molina, A.; Dupont, W.A. Assessment of natural ventilation strategies in historical buildings in a hot and humid climate using energy and cfd simulations. J. Build. Eng. 2022, 51, 104287. [Google Scholar] [CrossRef]
Building | Description |
---|---|
Location | Seoul, Republic of Korea |
Floor | 21 floors above ground and 7 basement floors |
Usage | Office: 1st–21st floor, 2nd basement floor Parking: 1st basement floor, 4th–7th basement floor Exhibition: 3rd basement floor |
Year the building was built | 2007 |
Building envelopes and structure | Low-e double glazing with reinforced concrete & steel-framed structure |
Gross floor area | 72,718 m2 |
Heating, Ventilation, and Air-conditioning systems (HVAC) | Screw chillers, turbo refrigerators, steam boilers, packaged heat pump and air barrier systems |
Internal Heat Source | Heat Gain | |
---|---|---|
7 People | 785 W | |
Lighting | 13.33 W/m2 | |
Equipment | 2 Printers | 60 W |
7 Computers | 343 W | |
7 Monitors | 140 W |
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Lim, T.; Kim, D.D. Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation. Sustainability 2022, 14, 15647. https://doi.org/10.3390/su142315647
Lim T, Kim DD. Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation. Sustainability. 2022; 14(23):15647. https://doi.org/10.3390/su142315647
Chicago/Turabian StyleLim, Taesub, and Daeung Danny Kim. 2022. "Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation" Sustainability 14, no. 23: 15647. https://doi.org/10.3390/su142315647
APA StyleLim, T., & Kim, D. D. (2022). Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation. Sustainability, 14(23), 15647. https://doi.org/10.3390/su142315647