High performance facade strategy for commercial buildings in India

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