AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Article Link
Collect
Submit Manuscript
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article

Daylighting and visual comfort of oriental sun responsive skins: A parametric analysis

Amir Tabadkani1( )Saeed Banihashemi2M. Reza Hosseini3
Department of Building and Architectural Engineering, Politecnico di Milano, Milano, Italy
School of Built Environment and Design, University of Canberra, Australia
School of Architecture and Built Environment, Deakin University, Australia
Show Author Information

Abstract

This study reports on developing an innovative approach for the parametric analysis of daylighting and visual comfort, through a sun responsive shading system. The objective is estimating the annual daylight metrics and indoor glare discomfort. To this end, a review of the literature was carried out on three key concepts: smart facades, visual comfort, and parametric design, in order to develop a dynamic pattern of an oriental system for enhancing the daylight and visual performance. Afterwards, two geometrical components (Rosette modules and louvers) were applied, using Grasshopper plug-in for Rhino and daylighting plug-in DIVA, to investigate the indoor daylight quality through different geometrical and physical properties. This resulted in generating 6480 design variants, when several variables (rotation, distance to facade, time hours, transmittance properties and colors) that affect incoming daylight as well as visual comfort performance in a single office space in the hot-arid climate of Tehran were taken into account. Interactive correlations between the overall performance of kinetic patterns and visual performance were investigated through an optimization process. Analyses showed that the proposed approach is capable of significantly improving the shading flexibility to control daylight metrics and glare, via a full potential adaptive pattern to achieve the maximum visual comfort level based on LEEDv4 certificate.

Electronic Supplementary Material

Download File(s)
12273_2018_433_MOESM1_ESM.pdf (444.9 KB)

References

 
Y Abdullahi, MRB Embi (2013). Evolution of Islamic geometric patterns. Frontiers of Architectural Research, 2: 243–251.
 
S Banihashemi, MS Hassanabadi, AN Sadeghifam (2012). Analysis of behavior of windows in terms of saving energy in extreme cold weather climes of Iran. International Journal of Engineering and Technology, 4: 676–679.
 
S Banihashemi, H Golizadeh, MR Hosseini, M Shakouri (2015). Climatic, parametric and non-parametric analysis of energy performance of double-glazed windows in different climates. International Journal of Sustainable Built Environment, 4: 307–322.
 
S Banihashemi, A Tabadkani, MR Hosseini (2017). Modular coordination-based generative algorithm to optimize construction waste. Procedia Engineering, 180: 631–639.
 
Bank World (2014). World Development Indicators 1960–2013. Washington DC: World Bank.
 
L Bellia, F Fragliasso, E Stefanizzi (2017). Daylit offices: A comparison between measured parameters assessing light quality and users’ opinions. Building and Environment, 113: 92–106.
 
M Bodart, C Cauwerts (2017). Assessing daylight luminance values and daylight glare probability in scale models. Building and Environment, 113: 210–219.
 
P Boyce, C Hunter, O Howlett (2003). The benefits of daylight through windows. Rensselaer Polytechnic Institute.
 
S Carlucci, F Causone, F De Rosa, L Pagliano (2015). A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design. Renewable and Sustainable Energy Reviews, 47: 1016–1033.
 
A Costa, MM Keane, JI Torrens, E Corry (2013). Building operation and energy performance: Monitoring, analysis and optimisation toolkit. Applied Energy, 101: 310–316.
 
USGBC (2015). Leadership in Energy and Environmental Design (LEED). U.S. Green Building Council.
 
JF Duffy, CA Czeisler (2009). Effect of light on human circadian physiology. Sleep Medicine Clinics, 4: 165–177.
 
ECS (2011a.) EN 12464-1. Light and lighting—Lighting of work places—Indoor work places. Brussels: European Committee for Standardization.
 
ECS (2011b). EN 12665. Light and lighting—Basic terms and criteria for specifying lighting requirements. Brussels: European Committee for Standardization.
 
A El ouaazizi, A Nasri, R Benslimane (2015). A rotation symmetry group detection technique for the characterization of Islamic Rosette Patterns. Pattern Recognition Letters, 68: 111–117.
 
F Favoino, F Fioritio, A Cannavale, G Ranzi, M Overend (2016). Optimal control and performance of photovoltachromic switchable glazing for building integration in temperate climates. Applied Energy, 178: 943–961.
 
D Greenberg, K Pratt, B Hencey, N Jones, L Schumann, J Dobbs, Z Dong, D Bosworth, B Walter (2013). Sustain: An experimental test bed for building energy simulation. Energy and Buildings, 58: 44–57.
 
HB Gunay, W O’Brien, I Beausoleil-Morrison, S Gilani (2017). Development and implementation of an adaptive lighting and blinds control algorithm. Building and Environment, 113: 185–199.
 
İ Gürsel Dino (2012). Creative design exploration by parametric generative systems in architecture. METU Journal of Faculty of the Architecture, 29(1): 207–224.
 
MS Hassanabadi, S Banihashemi (2012). Developing an empirical predictive energy-rating model for windows by using Artificial Neural Network. International Journal of Green Energy, .
 
MS Hassanabadi, S Banihashemi, AR Javaheri (2012). Analysis and comparison of impacts of design optimization approaches with occupant behavior on energy consumption reduction in residential buildings. International Journal of Engineering and Technology, 4: 680–683.
 
IESNA (2012). LM-83-12 IES. Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE). New York, NY: IESNA Lighting Measurement.
 
A Jacobs (2012). Radiance Cookbook. Available at http://www.radiance-online.org.
 
JA Jakubiec, CF Reinhart (2011). DIVA 2.0: Integrating daylight and thermal simulations using Rhinoceros 3D, Daysim and EnergyPlus. In: Proceedings of the 12th International IBPSA Building Simulation Conference, Sydney, Australia, pp. 2202–2209.
 
A Karanouh, E Kerber (2015). Innovations in dynamic architecture. Journal of Facade Design and Engineering, 3: 185–221.
 
NE Klepeis, WC Nelson, WR Ott, JP Robinson, AM Tsang, P Switzer, JV Behar, SC Hern, WH Engelmann (2001). The National Human Activity Pattern Survey (NHAPS): A resource for assessing exposure to environmental pollutants. Journal of Exposure Science and Environmental Epidemiology, 11: 231–252.
 
K Konis (2017). A novel circadian daylight metric for building design and evaluation. Building and Environment, 113: 22–38.
 
I Konstantzos, A Tzempelikos (2017). Daylight glare evaluation with the sun in the field of view through window shades. Building and Environment, 113: 65–77.
 
C Lavin, F Fiorito (2017). Optimization of an external perforated screen for improved daylighting and thermal performance of an office space. Procedia Engineering, 180: 571–581.
 
N Leach (2009). Digital morphogenesis. Architectural Design, 79: 32–37.
 
RCGM Loonen, M Trčka, D Cóstola, JLM Hensen (2013). Climate adaptive building shells: State-of-the-art and future challenges. Renewable and Sustainable Energy Reviews, 25: 483–493.
 
M López, R Rubio, S Martín, B Croxford, R Jackson (2015). Active materials for adaptive architectural envelopes based on plant adaptation principles. Journal of Facade Design and Engineering, 3: 27–38.
 
AHA Mahmoud, Y Elghazi (2016). Parametric-based designs for kinetic facades to optimize daylight performance: Comparing rotation and translation kinetic motion for hexagonal facade patterns. Solar Energy, 126: 111–127.
 
A Narangerel, J-H Lee, R Stouffs (2016). Daylighting Based Parametric Design Exploration of 3D Facade Patterns. In: Proceedings of the 34th eCAADe Conference, At Oulu, Finland,
 
SM Pauley (2004). Lighting for the human circadian clock: Recent research indicates that lighting has become a public health issue. Medical Hypotheses, 63: 588–596.
 
A Pellegrino, S Cammarano, VRM Lo Verso, V Corrado (2017). Impact of daylighting on total energy use in offices of varying architectural features in Italy: Results from a parametric study. Building and Environment, 113: 151–162.
 
M Pesenti, G Masera, F Fiorito (2015). Shaping an Origami shading device through visual and thermal simulations. Energy Procedia, 78: 346–351.
 
CF Reinhart (2004). Lightswitch-2002: A model for manual and automated control of electric lighting and blinds. Solar Energy, 77: 15–28.
 
CF Reinhart, J Mardaljevic, Z Rogers (2006). Dynamic daylight performance metrics for sustainable building design. Leukos, 3: 7–31.
 
CF Reinhart, J Wienold (2011). The daylighting dashboard—A simulation-based design analysis for daylit spaces. Building and Environment, 46: 386–396.
 
CF Reinhart (2014). Daylighting Handbook I: Fundamentals; Designing with the Sun.
 
Z Rogers (2006). Daylighting metric development using daylight autonomy calculations in the sensor placement optimization tool. Available at http://www. archenergy. com/SPOT/SPOT_Daylight% 20Autonomy% 20Report. pdf.
 
M Rubiño, A Cruz, JA Garcia, E Hita (1994). Discomfort glare indices: a comparative study. Applied Optics, 33: 8001–8008.
 
D Rutten (2013). Galapagos: On the logic and limitations of generic solvers. Architectural Design, 83: 132–135.
 
Tomasetti Thornton (2017). Design Explorer. Github. Available at http://tt-acm.github.io/DesignExplorer.
 
A Tzempelikos, AK Athienitis (2007). The impact of shading design and control on building cooling and lighting demand. Solar Energy, 81: 369–382.
 
GJ Ward (1994). The RADIANCE lighting simulation and rendering system. In: Proceedings of the 21st International ACM Conference on Computer Graphics and Interactive Techniques, Orlando, FL, USA, pp. 459–472.
 
J Wienold, J Christoffersen (2006). Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras. Energy and Buildings, 38: 743–757.
 
G Yun, DY Park, KS Kim (2017). Appropriate activation threshold of the external blind for visual comfort and lighting energy saving in different climate conditions. Building and Environment, 113: 247–266.
Building Simulation
Pages 663-676
Cite this article:
Tabadkani A, Banihashemi S, Hosseini MR. Daylighting and visual comfort of oriental sun responsive skins: A parametric analysis. Building Simulation, 2018, 11(4): 663-676. https://doi.org/10.1007/s12273-018-0433-0

643

Views

67

Crossref

N/A

Web of Science

74

Scopus

3

CSCD

Altmetrics

Received: 30 August 2017
Revised: 08 January 2018
Accepted: 17 January 2018
Published: 01 February 2018
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018
Return