Thesis project

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