Thesis project Master’s degree in Building engineer-architecture A.A. 2018 - 2019
Design of an high performance mixed-use building in NYC Student Antonio Lorusso
Supervisor Prof. Ing. Francesco Iannone
Introduction
Building’s energy need reduction GlobalABC 2019 Report By International Energy Agency
Energy consumption growth in the construction sector of 30% in the last 10 years
Increase in consumption for space cooling Urbanization density in warm climatic zones of the world
Global temperature
Government intervention strategies
in different parts of the world
Introduction | Case of study, internship in NYC Internship at VV Patchouli LLC
Concept High-performance mixed-use building
PROBLEM Large glass surfaces Overheating of the interior space Visual discomfort
STRATEGIES Bioclimatic architecture
GOAL High energy efficiency
Complex glass systems hybrid air conditioning system
Work stages
Definition of the information framework for the project
Project with introduction of bioclimatic strategies Basic model for evaluation – Option 1
Implementation of complex glazed systems Option 2
|
mixed-mode plant system Option 3
Comparative performance evaluation | Option 1 - Option 2 - Option 3
Step 1 – Initial investigation Crown Heights district - 1512 Union Street
Urban context Stylistic archetypes
Climate zone 4a – Mixed-humid
Climatic context
Data sourse - JFK Airport
NYC Energy building code
Regulatory context
Ashrae Standards
Company’s related
Building usage definition
Commercial
Gentrification – Change in the district’s identity Residential buildings in sandstone – Brownstone Production buildings in exposed brick CDD: 713 | HDD: 2496 – tm,e: 18,3°C Climate file: TMY3
Tmin,avg: 0°C Tmax,avg: 25°C
Standard 90.1 – Building performace Standard 55 – Thermal comfort IES-LM-83-12 – Visual comfort Co-working area - Lounge Showroom – Exposition Restaurant – Cocktail bar Conference space
Connected to the start-up’s activity
economic sustainability of the investment
Step 1 – Performance level | Thermal comfort Acceptability conditions
Evaluation parameters
Ashrae standard 55-2017
Variables Static
Subjective Metabolismo
Abbigliamento [Clo]
[Met]
U.R. [%]
Metabolic rate
Fanger
Air speed
Tmr [°C] Va [m/s]
PMV: ±0,5 | PPD: 10%
Summer
Winter
Ta < 26°C
Ta > 20°C
U.R. 50 – 60 %
U.R. 35 – 45 %
Tmr = ta ± 4°C
Tmr = ta ± 4°C
Fixed set-point conditions
VS Adaptive
Objective
ta [°C]
approach
Limits to objective variables
approach
Metabolic rate Clothing
[tpma] [to]
Temp. prevailing external mean
Adaptive set-point conditions
Temp. Int. operative to,max [°C] = 0.31 tpma + 21.3
Temp. prevailing external mean
Freedom for users to adapt clothing and natural ventilation conditions
to,min [°C] = 0.31 tpma + 14,3
Step 1 â&#x20AC;&#x201C; Performance level | Visual comfort Norm: IES-LM-83-12
Evaluation of sDA & ASE example
Different solar angles during the year
Potential glare risk
Intensity and redirection of sunlight
Need to consider shaded parts
Dynamic evaluation of daylight
Annual sunlight exposure
Spatial daylight autonomy
ASE1000,250
sDA300,50
Glare risk Minimum illuminance : 1000 lux Occupancy hours > 250 h anno
Minimum illuminance: 300 lux Occupancy hours: 50% h anno
Acceptable values sDA300lux,50% > 55%
% surface above the minimum illumination for the hours considered
ASE1000lux,250h < 10%
% surface below the maximum illumination for the hours considered
Step 2 â&#x20AC;&#x201C; Design | Morphology definition Aspect ratio S/V Variation of heat losses through the external surfaces Solar energy collection through external surfaces with favorable orientation
Total area
34,50 x 14,50 m Footprint area 24,00 x 14,00 S/V : 0,28 mq/mc
bonded Completion lot High cost per building surface
Step 2 – Design | Morphology definition Olgyay’s climatic chart Stretching ratio
•
Passive heating with solar gain
•
Cooling by natural ventilation
•
Room overheating control
Stretching ratio Cold
DEFINITION OF THE DECOMPOSITION SUBMODULE Climate Summer: Hot-humid
tempered
Optimal ratio 1:1,7 Optimal orientation
Hot-dry
Est – West Ratio: a/b = 14 / 8 m
Hot-humid
Depending on space’s depth Ratio between confined volume and absorbing surfaces Breakdown of the initial volume based on the sub-module
Step 2 – Design | Volume subdivision by uses Start-up related uses
Coworking
Showroom
Start-up + commercial usages Optimal climatic exposures
Filter effect
Commercially valuable positions
Unfavorable climatic exposures
Lounge
Commercial uses
Restaurant
Conference area
Service spaces
3° & 4° Story
Exposition/conference area 1° & 2° Story Distribution
Warehouse
WC
Kitchen
| Service spaces
Lounge 1° & 2° Story
Coworking/restaurant
Step 2 – Design | Volume subdivision by uses Start-up related uses
Coworking
Showroom
| Service spaces
Start-up + commercial usages Optimal climatic exposures
Filter effect
Commercially valuable positions
Unfavorable climatic exposures
Lounge
Commercial uses
Coworking/restaurant
Lounge
Exposition/Conference
Restaurant
Conference area
1° Floor
2° Floor
Service spaces
Kitchen
Distribution
WC
Distribution
Warehouse
WC
Kitchen
3° Floor
4° Floor
Step 2 – Design | Passive heating strategies Transparent surface calculation for solar absorption - HDD NYC: 713 [Nov – Feb.]
833
0,27 – 0,42
750
0,24 – 0,38
668
0,21 – 0,33
583
0,19 – 0,29
1° 2° 3° 4°
Phase displacement of the thermal flow
279 208 216 105
Window surface placed [mq]
161 71 35
93,4
Window surface placed [mq]
Window surface placed [mq]
49,6 49,6
120,1 33,8 0
213,5 83,4 49,6
Dimensionamento massa di accumulo
Radiazione solare (Wh/mqgiorno)
accumulation mass
Floor
Floor surface Window surface [mq] per HDD [mq]
Total
Transparent surface
West
HDD
South
Absorption surface
Solar gain
Direct solar gain system
Phase displacement choice
Definition of the ratio: Sw/Sa
Low attenuation: Δtdaily = 22°C
b.a.:
1:1.5
Medium attenuation: Δtdaily = 15°C
m.a.:
1:3
High attenuation:
a.a.:
1:9
Floor
Δtdaily = 7°C
Window surface placed [mq]
Surface window Accumulation surface
Accumulation surface needed [mq] Low attenuation
Medium attenuation
High attenuation
213,5
320
961
8647
3°
83,4
125
375
3376
4°
49,6
74
223
2008
1° 2°
Step 2 â&#x20AC;&#x201C; Design | Passive heating/cooling Direct solar gain system
Structure Mass
Absorbtion Protection
Introduction of solar absorption system
Glased surfaces & Massive envelope components
Overheating protection for south-oriented facades
Horizontal lug & green roof
Lounge area overheating protection
Filter space above the greenhouse space
Step 2 – Design | Overheating protection Pre-definition of south-oriented lug
Design of external shading system for souther facades Stereoschopical shading mask Location: New York City Latitude: 40,5° N Longitude: -73.0° W Building orientation (α): 185°
•
Hwindow = 3,00 m
•
α 12.00,21/06= 70°
Llug = B Sin(90 - α)= 1,73 m
Solar tool Shading masks Avarage monthly shading coefficient
Souther shading Verification
Western shading Design
Design of external shading system for wouther facades
Step 2 – Design | Raffrescamento passivo Wind’s effect •
Velocità
•
Direzione
•
Coefficiente di pressione
Natural ventilation of spaces Wind’s effect
Buoyancy effect
Impossibility of exploiting the wind due to lack of climatic measurements in the place of interest
Buoyancy effect contribution •
ΔT : Int – Ext
•
Δρ: Cold air– Hot air
•
Δp: Int - Ext
Cross-ventilation through spaces
Hypothesis of passive cooling natural ventilation by buoyancy effect from check during computer simulation
Cross ventilation Windows placed on opposite facades
Vertical ventilation Multi-levels skylights
Step 2 â&#x20AC;&#x201C; Design | Opaque components Detailing of envelopeâ&#x20AC;&#x2122;s components
Transmittance verification by norm | Ashrae standard 90.1
Slabe-on-grade floor
Above-grade external wall
Roof
U norm: 0,32 W/mqK
U norm: 0,59 W/mqK
U norm: 0,18 W/mqK
U project: 0,26 W/mqK
U project: 0,42 W/mqK
U project: 0,16 W/mqK
Step 3 â&#x20AC;&#x201C; Optimization | Complex glazed system Angular selectivity glazed system
Traditional glazed system
Dynamic behavior
Solar control glass
Energetic
Optic
Dynamic reduction
Refraction coefficients
Specular behavior between int.
of SGHC
For light radiation description
And ext. Glassâ&#x20AC;&#x2122;s surface
Computerized simulation
Descripted by static parameters SGHC: 0,30
Bi-directional scattering
Trasmission factors
function [BSDF]
As function of: solar angle and glazed surface orientation
File bsdf 145x145 coefficients from research
Light trasmission: 0,60
Microshade system
Step 3 – Optimization | Computer model definition Software
energetic & optical in
simulation
dynamic conditions
Model creation
Characterization of context and shading system
IES-VE | Simulation software
Characterization of opaque components CVE
COI
COB
COC
Geolocation Latitude: 40 ° N
Altitude: 3 m s.l.m.
Longitude: -73° W
Climatic file: NYC JFK TMY3
Step 3 – Optimization | Computer model definition Solar gain
Internal loads
Quantity
Insolation coefficients
Variation with time
App. Suncast
By Ashrae Standard 90.1
Facades insolation test Dynamic simulation for the typical year South facade | 3° floor | no shading
Occupancy
Scheduling
Computers Daily
Weekly
Annul
By Ashrae standard 90.1 P.R.M. South facade | 3° floor | with shading
Artificial light
Scheduling Domotic sensor of illuminance level Turning-on point: 300 lux
App. ApacheSim
Energy simulation in dynamic conditions
By Ashrae Handbook fundamentals Kitchen/bar appliance Qs = Qinput FU • Qs • Qinput • Fu
Sensible heat Plate energy consumtion Usage factor by expertimental research
Scheduling Daily
Weekly From in-site investigation
Annul
Step 3 – Optimization | Energy evaluation Glazed system evaluation Option 1
Base case | Project with bioclimatic strategies – Solar control glass – Static set-point air conditioning system
Trasmission factors for the Microshade system
Option 2
SHGC reduction related to solar angle
Glazed surface optimization | Angular selectivity glass - Static set-point air conditioning system
Building-Cooling system evaluation
Natural ventilation system
Option 3
Adaptive set-point implementation
Building automation system for windows Cooling/heating plant system
Plant optimization | Angular selectivity glass – Hybrid air conditioning system
Step 3 – Optimization | Visual comfort evaluation Case B – Angular selectivity glass
Case A – Solar control glass Triple glass system + solar control •
Solar control film on face 2
•
low-e on face 5
•
Triple glass system + Microshade
low-e on face 3
•
film Microshade type MS-A on face 2 •
film Microshade type MS-D on face 2 •
[Southern windows]
[Est/West windows]
Acceptability values Spatial daylight autonomy | sDA300,50% > 55 % Annual sunlight exposure | ASE1000,250 <10 %
Dynamic test sDA300,50 [%]
ASE1000,250 [%]
1° Floor
100
0
51,11
2° Floor
96,3
0
10,2
67,8
3° Floor
65,45
0
34,7
30,11
4° Floor
98,89
0
sDA300,50 [%]
ASE1000,250 [%]
1° Floor
50,5
36,99
2° Floor
33,6
3° Floor
4° Floor
low-e on face 5
Step 3 – Optimization | Glazed system energy evaluation Option 1
Base case | Project with bioclimatic strategies – Solar control glass
Option 2
Glazed surface optimization | Angular selectivity glass Solar gain
Glazed surface temperature variation
Solar gain (MWh) – Restaurant area, 1° floor Option 1
Option 2
Reduction %
Jenuary
0,5318
0,1491
-72%
February
0,862
0,2513
-71%
March
12,486
0,3014
-100%
April
10,477
0,2264
-100%
May
10,747
0,2391
-100%
June
11,393
0,2616
-100%
July
11,464
0,256
-100%
August
12,516
0,2935
-100%
September
12,043
0,2683
-100%
October
13.375
0,3743
-100%
November
0,6301
0,173
-73%
December
0,4686
0,1392
-70%
119,425
29,332
-75%
kW
°C
Month
Option 1
Option 2
Total
Step 3 – Optimization | Glazed system energy evaluation Option 1
Base case | Project with bioclimatic strategies – Solar control glass
Option 2
Glazed surface optimization | Angular selectivity glass Monthly energy need for cooling and heating
140,000
Space heating energy need [MWh]
Space cooling energy need [MWh]
120,000
Month 100,000
MWh
80,000
60,000
40,000
20,000
Option 2
Option 1
Option 2
Option 1
Jenuary
120,045
110,817
0,0000
0,0000
February
119,121
105,858
0,0000
0,0000
March
68,245
55,077
0,0000
0,0126
April
0,0789
0,0611
0,0857
0,5071
May
0,0029
0,0014
14,184
26,777
June
0,0000
0,0000
66,830
86,083
July
0,0000
0,0000
107,179
127,690
August
0,0000
0,0000
107,585
129,442
September
0,0000
0,0000
51,424
70,183
October
0,0066
0,0030
0,7479
20,666
November
50,313
42,762
0,0000
0,0119
December
94,776
86,327
0,0000
0,0000
453,384
401,495
355,539
466,157
TOTAL
Δseasonal
0,000
Jenuary Gennaio February Febbraio
March Marzo
Option 1 heating Riscaldamento Opzione 1
April Aprile
May Maggio
June Giugno
Option 2 heating Riscaldamento Opzione 2
July Luglio
August Agosto
September Ottobre October Novembre November December Settembre Dicembre
Option 1 cooling Raffrescamento Opzione 1
OPTION 2
Opt.2 - Opt.1
+51,889
- 110,618
Option 2 cooling Raffrescamento Opzione 2
Greater reduction of the energy requirement for cooling compared to the increase for heating
Step 3 â&#x20AC;&#x201C; Optimization | Cooling System Option 2
Static set-point temperature cooling system
Option 3
Hybrid cooling system with adaptive set-point temperature
Adaptive set-point temperature calculation Ashrae standard 55 - 2017 Mean prevailing outdoor temperature
đ?&#x2018;Ąđ?&#x2018;?đ?&#x2018;&#x161;đ?&#x2018;&#x153; = 1 â&#x2C6;&#x2019; đ?&#x203A;ź [đ?&#x2018;Ąđ?&#x2018;&#x2019;
đ?&#x2018;&#x2018;â&#x2C6;&#x2019;1
+ đ?&#x203A;ź 2 đ?&#x2018;Ąđ?&#x2018;&#x2019;
đ?&#x2018;&#x2018;â&#x2C6;&#x2019;2
+ â&#x2039;Ż + đ?&#x203A;ź đ?&#x2018;&#x203A; đ?&#x2018;Ąđ?&#x2018;&#x2019;
đ?&#x2018;&#x2018;â&#x2C6;&#x2019;đ?&#x2018;&#x203A;
â&#x20AC;˘
Îą [0 ; 1] â&#x20AC;&#x201C; Outdoor temperature respose factor
â&#x20AC;˘
(Îą = 0,9 hot-humide climatic zone. Slow response)
â&#x20AC;˘
d â&#x20AC;&#x201C; considered day
â&#x20AC;˘
n â&#x20AC;&#x201C; previous day
Calculated as an exponential weighted average on the tpmo in the n days preceding that of interest
Comfort operative temperature
ྦྷ
tpmo [°C]
to [°C]
to [°C]
Superior limit 80%
Inferior limit 80%
Adaotive set-point
Jenuary
1,26
to,max [°C] = 0.31 tpma + 21.3
February
-0,20
March
4,79
to,min [°C] = 0.31 tpma + 14,3
April
10,00
24,40
17,40
May
14,18
25,70
18,70
Aceptability limits
June
21,27
27,89
20,89
10°C < tpmo < 33,5°C
July
24,70
28,96
21,96
August
24,90
29,02
22,02
September
21,06
27,83
20,83
October
14,90
25,92
18,92
November
8,35
December
3,86
Where tpmo not verified
Static set-point â&#x20AC;&#x201C; Winter/Summer
ta: 20°C | ta: 26°C
Step 3 – Optimization | Cooling System Option 2
Static set-point temperature cooling system
Option 3
Hybrid cooling system with adaptive set-point temperature
Natural ventilation automatic schedule definition Adaptive set-point operative temperature to [°C]
to [°C]
Superior limit 80%
Inferior limit 80%
Daytime schedule | Mixed-mode
text < tset-point
Jenuary
February
ta,int < tset-point
March April
24,40
17,40
May
25,70
18,70
June
27,89
20,89
July
28,96
21,96
August
29,02
22,02
September
27,83
20,83
October
25,92
18,92
November December
Night-time schedule | night purge
text > tset-point ta,int > tset-point
Windows opening
text < ta,int
Cooling system activation
Preventing risk of interference 0.5 ° C hysteresis between system activation and window closure
Windows opening
Step 3 – Optimization | Cooling System Option 2
Static set-point temperature cooling system
Option 3
Hybrid cooling system with adaptive set-point temperature
Natural ventilation flow verification Ashrae standard 62.1 - 2017 Ventilation flow-rate definition Users x Rp
Ventilation flow-rate
Floor surface x Ra
Window’s surface per floor area calculation Ventilation flow rate Floor area
[l/s] Windows height Windows total leights
Verified
Window’s surface per floor to verify
Comparation with windows area design Area
V bz / A z
H s/W s (design)
Aw [%Az]
A w,norm
A w,design
1° floor restaurant
1,425
0,15
5
13,95
28,08
2° floor restaurant
1,425
0,28
5
10,4
38,36
Kitchen
2,61
0,14
6,9
2,415
2,55
2° floor exposition area
1,668
0,12
5
10,8
31,68
3° floor Exposition area
1,668
0,05
5
5,25
5,62
[mq]
[mq]
This verification is defined in the regulations for natural ventilation for IAQ For this reason, the opening surfaces have been increased compared to the regulatory values
Step 3 – Optimization | Cooling System Option 2
Static set-point temperature cooling system
Option 3
Hybrid cooling system with adaptive set-point temperature
Introduction in the model of the hybrid system Fluid dynamic model App. MacroFlo
Dynamic energy simulation
App. ApacheSim
Option 2 – Static set-point | 1° Floor | July
Option 3 – Adaptive set-point | 1° Floor | July
Cooling energy need
Natural ventilation flow
Operative temperature
Step 3 – Optimization | Cooling System Option 2
Option 3
Cooling system with static set-point
Hybrid system with adaptive set-point temperature
Space cooling energy need 120
100
MWh
80
60
40
20
Month
Option 3
Option 2
Jenuary
0,0000
0,0000
February
0,0000
0,0000
March
0,0000
0,0000
April
0,0515
0,0857
May
0,0796
14,184
June
0,4351
66,830
July
16,681
107,179
August
20,061
107,585
September
0,2857
51,424
October
0,0123
0,7479
November
0,0000
0.0000
December
0,0000
0.0000
TOTAL
45,384
355,539
Δ 0
Opt. 3 – Opt. 2 Jenuary Gennaio
February Febbraio
March Marzo
Option 2 heating Riscaldamento Opzione 2
April Aprile
May Maggio
June Giugno
Option 3 heating Riscaldamento Opzione 3
July Luglio
August Agosto
September Settembre
Option 2 cooling Raffrescamento Opzione 2
October Ottobre
November Novembre
December Dicembre
Option 3 cooling Raffrescamento Opzione 3
-310,155
Step 4 – Comparative performance evaluation Option 3
Option 1 Base case – Solar control glass – Static set-point temperature cooling system
Angular selectivity glass – Adaptive set-point temperature hybrid cooling system
Space cooling energy need [MWh] 140
sDA300,50
Implementazione sistema mixed
120
MWh
100
Spatial daylight autonomy Option 1
Option 2/3
1° Floor
50,5
100
2° Floor
33,6
96,3
3° Floor
10,2
65,45
4° Floor
34,7
98,89
80
60
ASE1000,250 40
20
0
April Aprile
May Maggio
June Giugno Option 11 Opzione
July Luglio Option 22 Opzione
August Agosto
September Settembre Option 3 3 Opzione
Δseasonal Opt.1 – Opt. 3: -420 MWh | -90,3 %
October Ottobre
Annual sunlight exposure Option 1
Option 2/3
1° Floor
36,99
0
2° Floor
51,11
0
3° Floor
67,8
0
4° Floor
30,11
0
Conclusions Better daylight control and solar gain thanks to complex glass systems useful for hot climates / buildings with large glass surfaces Need to introduce a regulatory method for assessing comfort in a mixed-mode cooling system Reduction of energy needs with the adoption of the mixed-method cooling system that could respond to the problems that emerged from the GlobalABC report regarding the increase of energy for cooling
90% Energy need reduction for cooling
Concept
Base project
Optimized project