Final Project Topic
High-performance façade strategy for commercial buildings in India Delhi NCR (National Capital Region)
December 4, 2020 Prepared By
Kritika Kharbanda
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
2
‘Architecture of Impatient Capital’
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Precedent Study - Statistics
Contribution to energy consumption
Commercial Buildings Current EPI = 200 to 400 kWh/ sq m/ year Target EPI = 100 to 150 kWh/sq m/year
Building Typology Division in India
Building industry contributes almost 30%
Current Commercial = 659 million sqm Predicted Commercial = 1900 million sqm (by 2030)
Lighting (22%)
Agriculture (18%)
HV AC
Loa
d
Commercial (31%) Building (29%)
Industry (47%)
Other (7%)
Residential (69%)
Envelope (26%) Equipment (26%)
Infiltration (5%)
Occupancy (3%)
Equipment - Other (10%)
Climate Study
3 Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance:
Irradiation Map for India Solar Resource = 5.0 kWh/ m2/Day
A Deep Dive on Design Decisions
Location: Delhi NCR
Solar resource (kWh/m2/Day)
5.5-6.0 5.0-5.5 4.5-5.0 4.0-4.5 3.5-4.0 0
0.3
0.6
0.9
1.2
Land Area (Million km2)
Universal Thermal Comfort Index (UTCI) Chart - Annual Percentage of time feeling comfortable = 32%
UTCI (°C) - Monthly Analysis
In the Sun (Wind 100%) In the Shade (Wind 100%) In the Sun (Wind 50%) In the Shade (Wind 50%)
Source NBC 2005 NREL
4
Building Case
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Project Proposal
1. AEON Corporate Office, Noida
2. Tower 11, Brookfield Candor Tech Park Typology IT/ITES PARK Site Area 19.25 Acres Total Built-up 201,600 sqm Retail Size 3000 sqm (Total) Typical Floor Plate 2648 sqm Number of Floors G+10 Year Built 2011- Present(Phase Development)
Typology Office Building Site Area 0.24 Acres Total Built-up 1500 sqm Retail Size 400 sqm (GF) Typical Floor Plate 300 sqm Number of Floors G+5 Year Built -
N
N
5
Building Case
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Project Proposal
1. AEON Corporate Office, Noida S
Scale:
14 m
Scale:
2. Tower 11, Brookfield Candor Tech Park
Balcony (2.5m)
M
m 6 3
Building Core
Building Core
20 m Building Core
Atrium
Fire Staircase
Amenities Balcony (2.5m)
90
m
Building Core
6
Methodology
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Workflow Framework Step 1
Step 2
Baseline Study
Intervention
Building Geometry Centric
Additional Geometry Centric
Vertical Daylight Factor (VDF)
Shading Benefit Analysis
Rhino + Grasshopper (Ladybug)
Solar Irradiation Rhino + Grasshopper (Ladybug)
Rhino + Grasshopper (Ladybug+ Honeybee)
Step 3
Comparative Study
Previous Research + Experiments
Design Builder
Solar Irradiation Rhino + Grasshopper (Ladybug)
Solar Irradiation
Daylight Autonomy Rhino + Grasshopper (Ladybug+Honeybee)
Daylight Autonomy Window to Wall Ratio (WWR)
Optimisation
Rhino + Grasshopper (Ladybug+Honeybee)
Rhino + Grasshopper
Solar Heat Gain Coefficient (SHGC) U-Value (Assembly) Visual Light Transmittance (VLT)
End Result
Operational Energy Analysis
Rhino + Grasshopper (Ladybug+Honeybee)
Literature Study
Step 4
Life Cycle Assesment Shading Device (Geometry)
Athena
Proposal
7
Vertical Daylight Factor
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Baseline Study
The Vertical Daylight factor is measured at all building facades, and considers the daylight access of the facade based on CIE overcast sky conditions. This simulation has been used to identify the optimum values for Window to Wall Ratio for each respective facade. For this simulation, a reflectance material of 0.3 value was developed in Honeybee as the typical material for all conext objects, including parts of the building geometry as well that block the facades (like balconies)
1. AEON Corporate Office, Noida
N
2. Tower 11, Brookfield Candor Tech Park
Sunpath Diagram
37 %
52 %
of the simulated test points has a vertical daylight factor (VDF) above
of the simulated test points has a vertical daylight factor (VDF) above
25 %
25 %
The VDF Study highlights that for AEON Corporate Office, due to the mutual shading by neighbouring buildings, the WWR can be high comparatively.
The VDF Study highlights that for Brookfield, the WWR can lie in the range of 30 to 40, with 40 being the maximum allowed WWR also, according to ECBC.
NE
SE
NE
N
SE
WWR > 30%
WWR > 30%
WWR > 45%
SW
NW
SW
NW
WWR > 45% WWR > 35% WWR > 50%
WWR > 35%
WWR > 45%
8
Solar Irradiation
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Baseline Study
Irradiation Analysis gives us the annual solar radiation received on all the facade orientations. This study has been performed to get an understanding of the SHGC Values to be adopted based on the amount of irradiation received at each surface. Determining a glass with good SHGC (low values in this case is good) is difficult in order to counterbalance the architectural appeal and clear views.
1. AEON Corporate Office, Noida
N
2. Tower 11, Brookfield Candor Tech Park
Sunpath Diagram
Sunpath Jun 21, 12PM Radiation Annual Max 1100 kWh/sqm
Sunpath Jun 21, 12PM Radiation Annual Max 1200 kWh/sqm
The front facade (road-facing) receives 200-800 kWh/sqm of solar irradiation per year. The highest radiation received is on the South Western facade, due to surrounding blocks of lower height comparatively.
The front facade (road-facing) receives 200 -1000 kWh/sqm of solar irradiation per year. The variations n the massing allow for mutually shaded regions, thus lowering the total radiation received on all facades.
NE
SE
NE
N
SE
1000 kWh/m2
400 kWh/m2 600kWh/m2
1000 kWh/m2 400 kWh/m2
SW
NW
1200 kWh/m2
500 kWh/m2
SW
NW
600kWh/m2 600 kWh/m2
400 kWh/m2
1200 kWh/m2
9
Literature Study
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Key Takeaways (Detailed Study in Appendix)
Almost 60%, were constructed before 1980, resulting in them having very poor energy performance Hellenic Statistical Authority (ELSTAT). 2011 General Census of Buildings; ELSTAT: Piraeus, Greece, 2015.
In India, 80% of the total heat flow into buildings is by direct solar radiation on window glazing S.S. Kumar, Optimum Usage of Glass in Building, Asahi India Glass Limited, India, 2012.
Effective shading strategies showed reductions in cooling energy consumption of up to 22% S.Kumar, et al. Projecting National Energy Saving Estimate from the Adoption of High Performance Windows Glazing in 2030, 2018
10
Shading Benefit Analysis
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Shading Geometry (Optimised)
An energy based test was performed on a simple office massing with dimensions and orientation similar to the AEON Office. For this test, the WWR considered was from the previous VDF studies. Therefore, the WWR for NE, NW, SE and SW was 30, 45, 45 and 35 respectively. The glass specifications used for this study are: U-Value = 1.8, SHGC = 0.68, VLT = 0.6 Other Considerations for this analysis: 5 HB Zones, Window Height = 2.5m, Sill Height = 1.2m Following are the results:
1. AEON Corporate Office, Noida
2. Tower 11, Brookfield Candor Tech Park
Minimum Depth (meters) of shading elements: A = 2.0 m B = 1.7 m C = 1.2 m D = 2.0 m
Minimum Depth of shading elements: A = 3.0 m B = 2.7 m C = 0.0 m D = 2.8 m C
B
C
C
D
C
B B
D
A D
North
B
D A
A
North
A
11
Mood Board
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Shading Geometry 1
2
5
4
2
5
2
3
5
5
4
Source 1 National Library of France (Dominic Perrault) 2 Mokuzai Kaikan Building, Tokyo (Nikken Sekkei) 3 Sky Green Residential & Retail Tower(WOHA) 4 Helsinki Dreispitz, Basel (Herzog & DeMeuron) 5 Clay Tile Experimentation within Facade - India
12
Shading Iterations
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Irradiation & Daylight Autonomy
Iteration 2 Horizontal: 750mm thk; n = 2
Iteration 3 Horizontal: 375mm thk; n = 4
Irradiation(kWh/m2) Comparative Study
Typology Horizontal
Iteration 1 Horizontal:1000mm thk; n = 1
SW
SW
SW
NW
NW
NW
SE
SE
SE
Daylight Autonomy(lux) Comparative Study
NE
SW NW SE NE
NE
SW NW SE NE
NE
SW NW SE NE
13
Shading Iterations
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Irradiation & Daylight Autonomy
Iteration 5 Vertical: 400mm thk; n = 4
Iteration 6 Vertical: 375mm thk; n = 12
Irradiation(kWh/m2) Comparative Study
Typology Vertical
Iteration 4 Vertical : 750mm thk; n = 4
SW
SW
SW
NW
NW
NW
SE
SE
SE
Daylight Autonomy(lux) Comparative Study
NE
SW NW SE NE
NE
SW NW SE NE
NE
SW NW SE NE
14
Shading Iterations
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Irradiation & Daylight Autonomy
Typology Vertical Irradiation(kWh/m2) Comparative Study
SW
SW
SW
NW
NW
NW
SE
SE
SE
NE
Daylight Autonomy(lux) Comparative Study
Iteration 9 (Grid 2) Vertical 1(large): 50 mm wide, 300mm thk, n = 12 Vertical 2(small): 25 mm wide, 150mm thk, n = 42 Horizontal: 50 mm wide, 150mm thk, n = 18
Iteration 8 (Grid 1) Vertical: 50 mm wide, 300mm thk, n = 12 Horizontal: 50 mm wide, 150mm thk, n = 18
Iteration 7 Diagonal : 300mm thk; Angle = 60°; dis = 750mm c/c
SW NW SE NE
NE
SW NW SE NE
NE
SW NW SE NE
15
Shading Iterations
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Irradiation(kWh/m2) Comparative Study
Typology Vertical
Irradiation & Daylight Autonomy Iteration 10 (Grid 5) Vertical 1(large): 50 mm wide, 300mm thk, n = 12 Vertical 2(small): 25 mm wide, 150mm thk, n = 42 Horizontal: 50 mm wide, 150mm thk, n = 18
Iteration 12 (Grid 5) Vertical 1(large): 50 mm wide, 300mm thk, n = 12 Vertical 2(small): 25 mm wide, 150mm thk, n = 42 Horizontal: 50 mm wide, 150mm thk, n = 18
SW
SW
SW
NW
NW
NW
SE
SE
SE
NE
Daylight Autonomy(lux) Comparative Study
Iteration 11 (Grid 5) Vertical 1(large): 50 mm wide, 300mm thk, n = 12 Vertical 2(small): 25 mm wide, 150mm thk, n = 42 Horizontal: 50 mm wide, 150mm thk, n = 18
SW NW SE NE
NE
SW NW SE NE
NE
SW NW SE NE
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Design Proposal Based on Precedent Study
Proposed Facade
17 Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
AEON Corporate Office
SW Facade
N
NW Facade
Proposed Facade
18 Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
AEON Corporate Office
SW Facade
N
NW Facade
Visualization
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
AEON Office
55mm thk.
Composite Wood (gloss finish)
150mm thk.
Composite Wood (gloss finish)
DGU
Low-e(6) + Air Gap(12) + Clear(6) (0.22 SHGC, 45% VLT, 3 U-Value)
75mm thk.
Composite Wood (gloss finish)
DGU
Low-e(6) + Air Gap(12) + Clear(6) (0.22 SHGC, 45% VLT, 3 U-Value)
35mm thk. Trellis Treated Wood
Green Climber Tempered Glass
Proposed Facade
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Tower 11, Brookfield Candor Tech Park
East Facade
N
West Facade
Proposed Facade
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Tower 11, Brookfield Candor Tech Park
South Facade
N
North Facade
Visualization
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Tower 11, Brookfield Candor Tech Park 1000mm thk. Steel Louvre
500mm thk. Steel Louvre
350mm thk. Steel Louvre
250mm thk. Steel Louvre
DGU Dark Blue Tinted(6) + Air Gap(12) + Tinted(6) (0.22 SHGC, 45% VLT, 3 U-Value)
DGU Low-e1(6) + Air Gap(12) + Clear(6) (0.68 SHGC, 76% VLT, 1.8 U-Value)
250mm thk. Steel Louvre
DGU Solar Control(6) + Air Gap(12) + Clear(6) (0.24 SHGC, 60% VLT, 2.8 U-Value)
Facade Details
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Typical: Blow Up Sections
1. AEON Corporate Office, Noida
Stick Construction
2. Tower 11, Brookfield Candor Tech Park
Unitised Facade System 500 thk. reinforced concrete beam
300 thk.
reinforced concrete slab
200 thk.
75 thk.
55 thk.
WPC false ceiling
Anodised Aluminium Sheet (Spandrel Panel)
500 thk.
DGU Dark Blue Tinted(6) + Air
reinforced concrete slab
reinforced concrete beam
DGU
Low-e(6) + Air Gap(12) + Clear(6)(0.22 SHGC, 45% VLT, 3 U-Value)
Composite Wood (150mm thk.)
Metal Connection Steel Grail (Accessible) (400mm thk.)
Wood Trellis (65mm thk.)
Green Panel
mineral fiber false ceiling
Gap(12) + Tinted(6) (0.22 SHGC, 45% VLT, 3 U-Value) (INNER PANE)
DGU Low-e1(6) + Air Gap(12) + Clear(6) (0.68 SHGC, 76% VLT, 1.8 U-Value) (OUTER PANE)
Aluminium clad uPVC Mullions (600mm thk.)
24
Comparative Analysis
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
1 Daylight Study
1. AEON Corporate Office, Noida Baseline (DA > 300 lux) 106 % Overlit
Proposed (DA > 300 lux) 83 % Optimized
2. Tower 11, Brookfield Candor Tech Park Baseline (DA > 300 lux) 82 % Adequate
Proposed (DA > 300 lux) 52% Adequate
Comparative Analysis
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
2 Irradiation Study
1. AEON Corporate Office, Noida Baseline SE SW NW NE
SE
900 800 250 580
2. Tower 11, Brookfield Candor Tech Park Baseline E 900 S 1000 W 600 N 900
Proposed SE 625 SW 625 NW 250 NE 450
E S
SW
W N
NW
NE
Proposed E 500 S 750 W 500 N 600
26
Comparative Analysis
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
2 Operational Energy 2 Operational Energy
1. AEON Corporate Office, Noida Baseline (Zone = 3) Cooling (Electricity) > 3000 W/m2
12% Improvement ! Proposed (Zone = 3) Cooling (Electricity) ≈ 2650 W/m2
2. Tower 11, Brookfield Candor Tech Park Baseline (Zone = 5) Cooling (Electricity) > 55000 W/m2
14% Improvement ! Proposed (Zone = 5) Cooling (Electricity) ≈ 45000 W/m2
Fuel breakdown (W/m2)
50000
Fuel breakdown (W/m2)
25000
45000 40000
20000
35000 30000
15000
25000 20000
10000
15000 10000
5000
5000 Months
Baseline
Months
Proposed
Months
Baseline
Months
Proposed
Cooling Lighting Heating Room Electricity DHW
27
Conclusion
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Key Takeaways
Market Aanalysis Rs/USD
Embodied Energy kWh/m2
Operational Energy kWh/m2
Irradiation Study kWh/m2
Daylight Study DA > 300 lux
Baseline Case
(DA > 300 lux) 106 % Overlit SE SW NW NE
900 800 250 580
Baseline (Zone = 3) Cooling (Electricity) > 3000 W/m2
Proposed Design
(DA > 300 lux) 83 % Optimized SE SW NW NE
625 625 250 450
Proposed (Zone = 3) Cooling (Electricity) ≈ 2650 W/m2
Originally, high performance glazing with aluminium frame was used that has a higher GWP impact than timber
Baseline Case
(DA > 300 lux) 82 % Adequate E S W N
900 1000 600 900
Baseline (Zone = 5) Cooling (Electricity) > 50000 W/m2
Proposed Design
(DA > 300 lux) 52% Adequate E S W N
500 750 500 600
Proposed (Zone = 5) Cooling (Electricity) ≈ 45000 W/
Aluminium mullion was replaced by aluminium clad uPVC mulltion for window framing, that has lesser embodied energy comparatively.
M Asif et al, 2005
Arijit Sinha, 2012
Aluminium Frame 650-800 Rs/sq ft including cost of single glazing. (Rakesh Bhatia, 2019)
Wooden Frame 300 – 400 Rs/ sq ft including cost of single glazing. (Kumar.R, 2010)
High Performance Glazing Can go up to 800 Rs/sq ft without cost of frames
DGU (for glass provided) 450-550 Rs/sq ft without cost of frames (Rakesh Bhatia, 2019)
Acknowledgement Collaboration
1. AEON Integrated Building Design Consultants LLP, Noida, India Mr Arnab Saha, Mr Ashish Rakheja, Mr Ashish Jain 2. Brookfield Properties Mr Ashok Kumar 3. Prof Vivek Sabharwal Director, Apeejay School of Architecture & Planning, Greater Noida 4. Henning Larsen Architects Mr Mikkel Esrup Steenberg, Mr Jakob Stromann Andersen
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Appendix
Market Analysis & Literature Study
30
‘Architecture of Impatient Capital’
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Energy Consumption Pattern in India Current Commercial = 659 million sqm Predicted Commercial = 1900 million sqm (by 2030)
Precedent Study
Agriculture (18%)
Statistics 1. Buildings energy consumption in India is expected to increase faster than in other regions.1 Delivered energy consumption for residential and commercial buildings in India is expected to increase by an average of 2.7% per year between 2015 and 2040, more than twice the global average increase.2
Building (29%)
Industry (47%) Other (7%)
3. India is projected to account for about 19% of the increase in world population over the projection period, surpassing China as the world’s most populous country in 2023.3 Building Typology Division in India
4. Although EIA expects the rate of India’s commercial energy growth to be higher than its residential energy growth, the residential sector remains the greater consumer of buildings energy, representing more than 70% of the buildings total throughout the projection period.3 5. Currently, approximately 659 million m2 spaces is used as commercial space and in 2030, it is estimated that it would increase to 1,900 million m2 and by then more than 60% of the commercial built space would be air conditioned4.
Commercial (31%)
Residential (69%)
6. India’s commercial sector accounted for nearly 69% of the country’s gross domestic product in 2015, and this share is expected to continue growing, leading to more energy demand in the commercial sector. EIA projects that total delivered commercial sector energy use in India will increase by an average of 3.4% per year, the fastest growth rate among IEO regions. India’s economic growth, rising income, and population growth are likely to increase the need for education, health care, leisure, recreation, and other services, which EIA expects will lead to an increase in demand for lighting, space cooling, and office equipment.1
Commercial Buildings Current EPI = 200 to 400 kWh/ sq m/ year Target EPI = 100 to 150 kWh/sq m/year Lighting (22%)
8. Commercial Buildings are divided into various sub categories. Among all, the office space demand is high due to increasing share of the services sector in the Indian economy as office space supply shifting from CBD to secondary centres (office and IT parks). Modern office buildings are coming up or likely to built in newly developed area for IT services. In India, 70% offices are of services companies (more than 7000 No.), 15% by financial and pharmaceutical sector and 15% by other sectors. Overall, demand for Grade A office space in the top seven cities of the country rose 18% to touch an all-time high 38 million square feet in 2015, compared to a year earlier.5
HV AC Loa d
7. EIA projects the electricity share of India’s total commercial energy consumption to continue increasing, from 59% in 2015 to 65% in 2040, displacing some coal consumption.1
Source Envelope (26%) Equipment (26%)
1. US Energy Information Administration (https://www.eia.gov/ todayinenergy/detail.php?id=33252#) 2. IEO2017 Reference case (https://www.eia.gov/outlooks/ieo/) 3. https://www.iea.org/ 4. ISA Vision Summit, Bangalore; Benchmarking Energy Use in Buildings and Cleanrooms; Dr. Satish Kumar
Infiltration (5%)
Occupancy (3%)
Equipment - Other (10%)
5.CBRE. CBRE: India Office Marketview - Q1 2015. CBRE India. [Online] April 2015. [Cited: september 5, 2016.] http://www.cbre. co.in/aboutus/mediacentre/mediaarchives/Pages/Office-space-takeup-witnesses-46-rise-in-Q2-2016-over-Q1-2016-.aspx.
31 Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance:
Compliance Local Regulations
A Deep Dive on Design Decisions
ECBC Commercial Buildings (Type D - Business) The three criteria that determine the thermal performance of the fenestration are explained below: (ISO - 15099) 1. Useful Daylight Illuminance (UDI) (table 4-1) - Meet the illuminance range of 100 – 2000 lux - Meeting UDI levels ranging from 10% to 40% of the gross floor area as per Table 4-1. - UDI levels should meet 90% of the potential daylit time in a year.
Key Takeaways
WWR
VLT
40% Max
0.27 Min
2.EPI (Building Envelope Trade-Off Method) 1 or 0.75 (SuperECBC) Key Metrics in Daylighting Standards such as the NBC and ASHRAE 90.1 specify illuminance levels for various space types such as corridors, open office space, classroom and others. The National Building Code (NBC) specifies sky illuminance for different climate zones (table 4E) WWR: Maximum allowable Window Wall Ratio (WWR) is 40% (applicable to buildings showing compliance using Prescriptive Method, including Building Envelope Trade off Method)(Influenced by table 4E) VLT: Minimum allowable Visual Light Transmittance (VLT) is 0.27 U-Factor: Assembly U-factor shall be determined for the overall fenestration product (including the sash and frame) (table 4-7) SHGC: As determined in table 4-10. Eceptions are allowed when the fenestration is covered by a permanent shading devide. Equivalent SHGC: The maximum allowable SHGC of glazing shall be 0.9 (table 4-10) Building Envelope Trade Off Method: This is a systems-based approach, where the thermal performance of individual components can be reduced if compensated by higher efficiency in other building components. (table 4-16)
SHGC
U-Factor
0.97 Max
3.00 Max
Literature Study
Research Papers and Market Analysis Past Experiments It has been found that for an uninsulated building (no insulation in walls/roof), 30% glazed area of south wall is sufficient for Delhi’s composite climate. For insulated buildings, optimum glazed areas are: 10% for New Delhi. [Singh MC, Garg SN; Suitable Glazing Selection for Glass-CurtainWalls in Tropical Climates of India; 2011] Another study was carried out a study to investigate the cooling load reduction in tropical climates by means of HP glazing. They employed five leading window glazing units comprising both single and double-glazed units to quantify the decrease in energy consumption. Nano (double-glazing) which has a U value of 1.8 W/m2K and SHGC of 0.2 resulted in maximum reduction in energy consumption of up to 6.4%. Arindam Dutta⁎, Akash Samanta., Reducing cooling load of buildings in the tropical climate through window glazing: Anmodel to model comparison, Journal of Building engineering, 2018 vol 18, 318-327. Double-glazed windows have two panes of glass fitted into a window frame. An inert gas like argon is filled between the two panes to increase insulation. Double glazed glass is perfect for Indian weather conditions, especially in North India where there are scorching summers and moderate winters. Lohia S, Dixit S; Energy Conservation using Window Glazing in India, 2015
The most effective way to reduce the solar load on fenestration is to intercept direct radiation from the sun before it reaches the glass. There are various methods to shade windows – overhangs, awnings, louvres, vertical fins, lightn shelves and natural vegetation. These can reduce cooling energy consumption by 10-20%. NREL (2000) in their study, gauged the potential of effective shading strategies on cooling load reduction. The results showed reductions in cooling energy consumption of up to 22%. Md. Jahangir Alam and Mohammad Ariful., Islam Effect of external shading and window glazing on energy consumption of buildings in Bangladesh Advances in Building Energy Research, 2017 vol. 11, no. 2, 180–192
32
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
33
Glazing Type
Harvard GSD Fall 2020 SCI 6466 Optimizing Facade Performance: A Deep Dive on Design Decisions
Possible Iterations Case
1. AEON Corporate Office, Noida
2. Tower 11, Brookfield Candor Tech Park
*From Vertical Daylight Factor Study
Orientation
WWR
North-East
30%
South-East
45%
*The glass type selected are based on the Market Reseach (study zone: South Asia)
Glass Type
Glass Properties
U-Value
*From Irradiation Study
SHGC
ECBC Compliant
Shading Required
DGU
Low-e1(6) + Air Gap(12) + Clear(6)
1.80
0.68
Yes
No
DGU
Clear(6) + Air Gap(12) + Clear(6) Low-e1(6) + Air Gap(12) + Clear(6)
2.95
0.73
1.80
0.68
Yes Yes
Yes
1.80 1.74
0.68 0.54
Yes Yes
Yes
South-West
45%
DGU
Low-e1(6) + Air Gap(12) + Clear(6) Low-e2(6) + Air Gap(12) + Clear(6)
North-West
35%
DGU
Low-e1(6) + Air Gap(12) + Clear(6)
1.80
0.68
Yes
No
North-East
40%
DGU
Clear(6) + Air Gap(12) + Clear(6)
2.95
0.73
Yes
No
Low-e1(6) + Air Gap(12) + Clear(6) Low-e2(6) + Air Gap(12) + Clear(6) Solar Control(6) + Air Gap(12) + Clear(6) Clear(6) + Air Gap(12) + Clear(6)
1.80 1.74 2.80 2.95
0.68 0.54 0.24 0.73
Yes Yes
1.80 1.74 2.80 2.95
0.68 0.54 0.24 0.73
Yes Yes
2.95
0.73
Yes
South-East
40%
DGU
South-West
40%
DGU
Low-e1(6) + Air Gap(12) + Clear(6) Low-e2(6) + Air Gap(12) + Clear(6) Solar Control(6) + Air Gap(12) + Clear(6) Clear(6) + Air Gap(12) + Clear(6)
North-West
30%
DGU
Clear(6) + Air Gap(12) + Clear(6)
Yes Yes
Yes Yes
Yes
Yes
No