Paweł Unger's Master Thesis: Algorithmic Mumbai | PRESENTATION

Algorithmic Mumbai computational optimization of urban and architectural form on the example of the Eastern Waterfront transformation in Mumbai, India master’s thesis by Paweł Unger supervised by PhD Arch. Eng. Jan Cudzik and PhD Arch. Eng. Piotr Czyż reviewed by PhD Arch. Eng. Łukasz Pancewicz

5.11.2019

Mumbai, India

Eastern Waterfront, Mumbai

5km

population Mumbai

London

9 126 366 20 185 064

density

32 303 people/km²

6th the densest city

9 - 12 million live in slums depending on statistic

6% can afford housing

27. Singapore 29. Mumbai 36. Barcelona

29th wealthiest city in the world “Global city GDP rankings 2008-2025�. Pricewaterhouse Coopers. Archived from the original on 4 May 2011. Retrieved 16 December 2009.

$

40% of India’s foreign trade

500 000 imigrants a year

4 months of Monsoon rain

3.5h of commuting to job on average

Methodology XL scale strategic guidelines L scale urban guidelines

research

pedestrain corridors

geo-data

global influences

transportation nodes distribution

society

residential household to public transport distance

transportation nodes distribution

urban angle adjustment urban scale research

filter problems

environment

finding conotations

research and tools bank

XL scale (Estern Waterfron) 750ha

megalocalism

XL scale strategic guidelines

L scale (urban) 100ha

existing buildings use analysis

walkability mobility flooding predictions

algorithmic research

input

selection

analysis / simulation

scale

sun radiation simulation sun propoagation analysis

super services urban blocks widths

urban form

mobility analysis

proximity to the focal nodes

functions distribution in the urban scale

M scale (architecture)

Topology Optimization (TO)

pedestrian network

wind analysis

monsoon response typologies

output

environment

mobility

society

3 months of monsoon rain

long job distances

monsoon flooded public space

humid and hot climate

sinking metro system

0.5 to 4 hours job commuting

extreme air pollution

lack of water transport

6% of citizens can afford housing inefficient electricity

60% living in slums

analysis synthesis

Architectural Form cross ventilation analysis

pedestrian network pedestrian grid simulation

services

visual comfort simulation

quarter or full form builidng solar farms and roof urban farms distribution

offices

indoor farms

final output

XL scale strategic guidelines L scale urban guidelines M scale architecture

main problems

high tides and tsunamies

residential

services

heights of urban blocks

main urban grid solar radiation simulation

architectural scale research

M scale architecture

privacy and access simulation

functions distribution

XL scale: strategic guidelines

750ha

5km

XL

sea level

XL Top cities exposed to coastal flooding in the 2070s

Mumbai sea level prediction

2019

11,41mln (in 2070)

g n i d o o l f r o f d e s o p x e s n e z i t ci

~5m 2,78 mln

0m 0m

2119 ~6.5m e g n a r tide l e v e l sea

~1.5m

Hanson, S., Nicholls, R., Ranger, N., Hallegatte, S., Corfee-Morlot, J., Herweijer, C., & Chateau, J. (2011).

A global ranking of port cities with high exposure to climate extremes. Climatic change, 104(1), 89-111.

Deloitte City Mobility Index

XL sea range

1km

N

2 C warmer atmosphere in 2050 4 C warmer atmosphere in 2120 o

o

The Gate of India, Mumbai 2050

source: https://www.climatecentral.org

2120

XL

Learning from Chicago, 1850

“Chicago Tribune, February 7, 1866”. Retrieved July 21, 2019

“Chicago Tribune, February 7, 1866”. Retrieved July 21, 2019

XL

ground elevation

underground

on-ground

+3m 0m

initial ground level

infrastructure zone reservoir

XL

transportation and walkability

XL Statistic of mobility type usage in Mumbai:

55.5 % 21.9% 14.4% 3.1% 2.4% 1.6% 0.8% 0.3% walking train bus two rickshaw car bicycle taxi wheel-

XL walkability and train tranport

1km

20 minutes 10 minutes 5 minutes

N

XL Mumbai is a concentric mega-city

XL mega-local cluster parts: -focal point - residential - work - recreationial - services - health care - education

XL

multi-functional mega-local districs

XL

mega-localism High potential for the center of each Megalocal district:

Sassoon Dock Local Fish Market

The Gate of India

Horniman Circle Garden

Indira Dock

L scale Clock Tower

Silos park

Coal Burden

Hay Burden

Industrial Park

Vidyalankar Polytechnic Park

1km

N

XL

mega-localism High potential for the center of each Megalocal district:

Sassoon Dock Local Fish Market

The Gate of India

Horniman Circle Garden

Indira Dock

L scale Clock Tower

Silos park

Coal Burden

Hay Burden

Industrial Park

Vidyalankar Polytechnic Park

1km

N

L

L scale: urban guidelines

100ha

5km

L

L scale: urban guidelines 2D

L

grid setup

100x 50m urban block 15m offset for streets

100m N

L

W

main axis, the green corridors and tranportation

average wind direction

W S N

S E

train stations train connections with monsoon-proof areas water tram connections pedestrian green corridors with enhanced ventilation

100m N

L

inland green areas

100m N

vs

shortest path on Hippodamus grid

494.96m max distance 270.83m average distance

shortest path on high density grid

100m

100m

N

N

382.69m max distance 211.75m average distnace

27.9% shorter

L

L

N key: designed buildings existing buildings Eastern Waterfront parts outside of the study area Mangrove parks

L

L scale: urban guidelines 3D

L

density

Street widths

the furthest from train station

the closest to train station

150m height

buildings distnace

30m

Building’s height related to distance from public transport

15m the furthest from train station

the closest to train station

16m

urban ecology

generative roofs

urban farm

60m² of urban farm is enough to feed one person

solar farm

solar energy

L

urban ecology

L

solar radiation simulation

annual average of sun radiation

11 10 8.9 7.75 6.6 4.75 4.41 3.33 2.17 1.08 0

[hours]

L

urban ecology

key: solar farms urban farms

290 000 people powered by the roofs 25 000 people fed from roofs

mangroves

https://cms.qz.com/wp-content/uploads/2018/09/mangrove-Apple.jpg?quality=75&strip=all&w=1600&h=900

generates oxygen 1ha = 1760kg of CO2 less yearly 2m strip = 90% lower waves

L

mangroves

https://cms.qz.com/wp-content/uploads/2018/09/mangrove-Apple.jpg?quality=75&strip=all&w=1600&h=900

1ha = 1760kg of CO2 less yearly 2m strip = 90% lower waves

tetra-pods

https://alicegordenker.files.wordpress.com/2014/04/main-photo.jpg

1tone = 900kg of CO2 emmited 2m strip = 100% lower waves

L

urban ecology

mangrove parks

20 480kg of CO2 less a year

functions and focal points

buildings use proportion summary

residential 65%

services 25% super services 10%

range of groundfloors services 50m range from squares

high potential commercial zone 100m range from train station

L

low typologies elevated train platform

volume slider

checkerboard

motion

100% 100%

5% 33%

36% 37.5%

55% 54%

cross ventilation dry public space [% of a footprint]

high-rise typologies

volume slider cross ventilation dry public space [% of a footprint]

23% 92%

checkerboard

motion

random

80% 37.5%

59% 203%

48% 149%

L

M

M scale: architecture

M

?? ?? ?? ??

M Train station 70m

N key: designed buildings existing buildings Eastern Waterfront parts outside of the study area urban block chosen for the architectural development (M scale) Mangrove parks

Mangrove park 100m

Thane Creek 20m

M L scale to M scale: architecture based on the urban strategy

2D passage

from the train station to the bay

M

3D maximum volume

40x70x110m

generative roof type

functions

solar roof

1/3 residential 1/3 offices 1/3 services

M step 1 : form finding Sun radiation analysis of the maximum building’s volume to reduce sun exposition of the building

step 2 : structural optimization Finding optimal structural for with Topology Optimization for the given geometry from the setp 1

step 3 : programme optimization A set of simulations to discover the optimal function for each part of the building.

step 1 : sun forms geometry

sun radiation simulation process:

M

M

step 1 : sun forms geometry

analysis results

annual sunlight average

4h

5h

6h

7h

8h

9h

10h

M

step 1 : sun forms geometry

analysis results

annual sunlight average

4h

5h

6h

7h

8h

9h

10h

M

step 1 : sun forms geometry sun optimized geoemtry

final geometry with the passage

k e e r C e Than n o i t a t s train

M

step 2 : structural optimization

Morphogenesis of flux structure with Topology Optimization

M 1914 LeCorbusier - architectural perspective

Opposite approaches. Le Corbusier’s Mansion Domino 1914 (left) structural sub-rationalism

M 1914 LeCorbusier - architectural perspective

Opposite approaches. Le Corbusier’s Mansion Domino 1914 (left) structural sub-rationalism

vs 1904 George Mitchell - mathematical perspective

M 1914 LeCorbusier - architectural perspective

vs 2011 A. Isozaki, M. Sasaki, Convention Center, Qatar- architectural perspective

Opposite approaches. Le Corbusier’s Mansion Domino 1914 (left) structural sub-rationalism, Topology Optimized structure by Sebastian Białkowski 2018 (right) structural rationalism

M 1914 LeCorbusier - architectural perspective

n o i

l a

t a r ri

vs 2011 A. Isozaki, M. Sasaki, Convention Center, Qatar- architectural perspective

l a

t a r

n o i

Opposite approaches. Le Corbusier’s Mansion Domino 1914 (left) structural sub-rationalism, Topology Optimized structure by Sebastian Białkowski 2018 (right) structural rationalism

Example of a TO implementation: Initial design configuration of the L-bracket optimization case and the solution by R. Picelli et al

step 1 : TO algorithm initial conditions

step 2 : calculations

material: stainless steel

load:

algorithm setup:

Density Value [%] 3.5 Young Modulus [GPa] 210.0 Poisson Factor [v] 0.3

class C5 regarding norm PN-EN 1991-1-1

resolution [pts/m2] 100.0 iterations [int] 60

volume for structure

Load Value 7.5 [kN/m2]

initial conditions

boundin g box

step 3 : results

run iterative optimization process topology optimized geometry [mesh]

optimized structure

diagonal prestressing rod ring steel pipe

loads

main steel pipe

aluminum coating

suppor ts locat ion

TOPOLOGY OPTIMIZATION

axonometry

northern view

eastern view

southern view

western view

eastern view

sounthern view

western view

M

ground floor

SOLAR OPTIMIZATION

northern view

roof top

annual average of sun radiation 10 9 8 7 6 5 4 3 2 1 0

[hours]

M

step 3 : programmatic optimization

functions distribution in the given volume

M functions:

parameters for the functions distribution optimization:

1. residential 3. services 2. offices 4. urban farms

1. visual comfort 3. cross ventilation abilities 2. sun radiation analysis 4. privacy rate

analysis of visual comfort and cross-ventilation abilities

M

sun radiation simulation

M

privacy rate simulation

M

M

programme distribution

farms

75 modules = 8.8% of all modules

housing

363 modules = 42.9% of all modules

services

222 modules = 26.2% of all modules

offices

187 modules = 22.1% of all modules

section variation

M

ground floor variation

2 045m² of monsoon - proof public space

15x17 26.5

15x17 26.5

15x17 26.5

15x17 26.5

M

M

9th floor variation D 10x17 27.5

15x17 26.5

7x17 27.5

15x17 26.5

15x17 26.5

15x17 28

15x17 26.5

15x17 26.5

C

15x17 26.5

15x17 26.5

15x17 26.5

15x17 26.5

15x17 26.5

D

C

monsoon-proof public space

M

view from the bay

M

general performance

L scale

M scale

urban scale:

architecture:

73 000 people to inhabit 57m to sustainable transport

up to 40% less construction material most exposed to sun areas eliminated

25 000 people fed from roofs

36.5% of cross ventilated space

290 000 powered from roofs

2 045m² monsoon-proof public space

flood areas eliminated

21 475m² for rent

49.97% covered with greenery

1900m² of low sun exposed terraces

20 480 kg less CO2 annually monsoon-proof public spaces

790MW of power generated per year 1 875m² or 9 375m³ of urban farms

fresh air with urban ventilation

160people feed from the solar farms

Algorithmic Mumbai thank you for your attention