macro thinking & micro action
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Macro Thinking & Micro actionSimulation Algorithm of
Thesis by Haidong MaMentor:Benjamin DillenburgerMichael Hansmeyer
MALL MALL
MALL
GG
G
B
B
B
P
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P
P
Thanks
This thesis is based on my Master of Advanced Studiesfinal work at the ETH Zurich CAAD in 2009/2010.
This thesis would not exist without the support of:Ludger Hoverstadt who made this project possible.Benjamin Dillenburger, Michael Hansmeye who are my mentors from the Chair. Xiaofan Deng, who offer the site material and context.
Thanks also to our MAS colleagues for their support and friendship.
Content
1. Context & proposal
2. Site & parameterization
3. Simulation software3.1. algorithm-macro thinking 3.2. algorithm-micro action3.3. software output
4. Conclusion & feedback
5. Reference
AbstractThis thesis aims to provide alternative and innovative plan models for Chinese cities that are currently under rapid development. Using digital technology, the author strive to integrate the diverse local structure in social and spatial aspects with the ambition and demands of city’s expansion. Firstly, though parameterization, the local infrastructure, industry chain and living patterns were diagrammatized, quantized and input as reference database. Secondly, digital sequence simulation is used as an innovative tool to promote interventions among above elements and generate emergent process of living activities which interact to each other base on cellular automata theory. Finally, building behaviors of this area were predicted and outputted possible master plan in desirable future. This study arrives at an open scenario the feasible prospect. A conclusion is drawn to reflect the process, achievement and weakness of the research.
1950
15% 20%40%
60%
19701990
20102030
China’s Urbanization Process
professional designer
Monotonous
top down
1.1. Context“China is undergoing a process of unprecedented urbanization, with cities often being built from scratch in just three to five years. Four hundred new cites will be built over the next 20years with newly urbanized populations of over 240 million. So rapid and intense is this process that consumption of energy and natural resources is outstripping supply, posing unique challenges for the creation of sustainable cities.”1
Proposal output: integrate the diverse local structure in social and spatial aspects with the ambition and demands of city’s expansion.2
1.2. Proposal
designerstake holderresident
Diverse
intervention
self-organization
top downbottom up
1. Context & Proposal
Current output: To achieve the fast development, cities are considered as machines which are centrally operated by the forces of politics and economics in China.
China
Sequence Programs
1 Designcreative
school, studio, exhibition, gallery, salon, showcase…2 Production Research workshop, studio, headquarter, gallery…3 Module Making
production
workshop, factories…4 Parts Manufacturing workshop, factories, logistics…5 Assembling workshop, factories, logistics…6 Wholesale wholesale market, mall, sale agent, logistics...7 Retail
consumption-
vertisement...8 After Service
2.2. ParameterizationInfrastructures & facilities
Industry Chain
Social demandThere are six individual social demand have been parameterized in this site: 1) wholesale merchant, 2) rich wholesale businessman, 3) immigrant worker, 4) jobless immigrant, 5) local villager and 6) urban citizens.
2.1. Site descriptionThe southern districts in Beijing are selected as a research site. Formed by the process of self-organization, this area shows strong internal power to grow; however, as the expansion of the city has reached here, it brought intensive external development pressure to the area.
L, M FacilitiesS,XS Facilities
2. Site & Parameterization
This site has concentrated more than 460 clothing factories, ranging from parts manufacturing, module production to assembling. Furthermore, there are 39 big wholesale malls and market for garments, clothing materials and accessories.
XL,L,M Roads S,XS Roads
Site in Beijing
infrasturcturebuilding behavior
social demand
addingdeleting
adapting
macro thinking micro action
industry chain
3. Simulation Software
AlgorithmBy the influence of industry chain, infrastructures and social demand, building behaviors try to be stable by adapting, adding or deleting.
input: rules output: masterplan
3.1 Algorithm - macro thinking
(0,0)
(-600,-2000) (1200,-2000)
(-600,1000) (1200,1000)
define a rectangle of site area
2010.01 2020.01
DHM Develop Sequence
integration isolation 1 2 3 4
timeline
define a time scope of site development to simplify calculation.
software initialization
Define space & timeTo simplify calculation, before inputting parameter and starting simulation, software initialize site area by rectangle ABCD and dividing time scope as four phase from 2010 to 2020.
A B
CD
3.1 Algorithm - macro thinkinginfrasturcture input & output
input: streets & date (defined by urban designer)
output: blocks (calculated by software)
20122015
2020
By input of infrastructure development strategy which is defined by urban designer in different phase, this software will output blocks which is calculated by GIS spatial algorithm.
3.1 Algorithm - macro thinkingblock input & facilities output
input output
1
L street
p0
p1p2
p3L street
p0
p1p2
p3
formulafacilities’ number=(5~10)/100 X street lengthfacilites’ size=?{if (area< 500,000sqm)?=1;if(area<1000,000sqm)?=2;if(area>1000sqm)?=3;}ratio of L, M, S facilites’ scale=?{firstly, calculate the location. then calculate the distance to main streets.if (distance<10m)L=0%M=5%if (distance<100m)L=5%M=10%if(distance>100m)L=0%M=20%}
block
length:
area: 250,000sqm
400m
location: 30% nearby main street
facilities
numbers:
size list
35
ratio list
According to blocks’ property, software will generate facilities which are based on access abilities. field research and urban designer’s knowledge provided the formulas for software calculation. a) facilities’ numbers=formula(street length) b) ratio of L, M, S facilities’ scale=formula(distance to main streets).
industry chain input & programs output
programs output (software)
1
Des
ign
Production
Research
Module Making
Parts
ManufactureA
ssem
bleWholesale
Retail
After-
Service
23
4567
8
CREATIVE
CO
NSU
MPTION
SchoolStudio
Exhibition
Studio
Studio
WorkshopHeadquater
ResearchLab
Exhibition
Exhibition
Workshop
Factory
Workshop
FactoryLogistics
Workshop
Factory
Logistics
Logistics
Mall
Wholesalemarket
Shopping mall
Flagshipshops
Flagshipshops
Logistics
Boutique
headquater
flagship
PRODOCUTION
. . . . . .............
school.number
school.size
research studio.number
research studio.size
exhibition.number
exhibition.size
conference.number
conference.size
workshop.number
workshop.size
headquater.number
headquater.size
factory.number
factory.size
logistics.number
logistics.size
wholesale.number
wholesale.size
mall.number
mall.size
flagship.number
flagship.size
boutique.number
boutique.size
3.1 Algorithm - macro thinking
Industry Chain
industry sequence0
1
2
3
4
5
6
7
8
prod
uctio
n re
asea
ch
part
s m
anuf
actu
ring
mod
ul p
arts
man
ufac
turi
ng
ass
embl
y sale
aft
er s
ervi
ce
econ
omic
ben
efit
industry chain phase input (urban designer)
1 2 3 4
According to industry chain phase which is based on industry development discipline and inputted by urban designer, this software will output programs which is calculated by industry-related database.
output: anchors location and identity(programs and intensity)
LOG.
When the interventional simulation starts, all anchors strive for optimization in their built-in demands. After a certain amount of time, equilibrium is achieved and the process stops. Triggered by the anchors, spatial properties are generated automatically based on the influence from the anchors. The closer to the anchor, the greater influence it has. Gradient color is used to display spatial properties, where a darker color indicates a greater influence and vice versa.Through this method, software can generate various distribution patterns. Then, designers can select one for further processing.
3.1 Algorithm - macro thinking
anchors input (urban designer)
output (software)
schoolresearch/studio
exhibitionconference
workshop
headquater
factory
logistics
wholesale
mall
flagship
boutique
1logisticsanchor
2educationanchor
3fashionanchor
4conferenceanchor
related building programs output
village buildings
merchant familystudio/workereducation/researcher
local urban villagerlogistics serverfactory/worker
In this area, there are six living patterns. During the step of intervention, the anchors create environment to attract new groups of people, such as designers, researchers, and so on. To simulate this process, we adopt the concept of tolerance value from Micromotives and Macrobehavious3 by Thomas Schelling (1978). The principle is that people select where they live and work depending on similarities in neighborhood (including cultural and social quality). The tolerance value is introduced to the new comers and is defined as the number of similar neighborhoods in the vicinity. For example, if there is no similar neighborhood, the value will be zero; if there is one, the value should be one and so on and so forth. Before starting this simulation step, the designer should set up the tolerant value.
social demand3.2 Algorithm - macro thinking
rules: neighbors/living cost/facilities/anchors1) neighbor.numbers: 8 neighbor.radious: 80m2) facilities distrubtion. S facilities >= 10(distance <80m) M facilities L facilites3) anchors sequence.
MALL
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MALL
MALLB
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penetrate into city
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GGBP
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Weekly Life
CORE AREA
Monthly Life
penetrate into city
P
P
MALL
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G
B
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Daiy LifeCORE AREA
distance
facilities
local urban villager education/reseacher
CORE AREA
distance
current point(Pn)
neighbor area(radius)
Software automatically generates three different building behaviors.
base on cellular automata theory
adapting
deleting
adding
1
0
2
Depending on spatial properties of site generated at the first step, the software strives to distribute and modify village living patterns (cells). Each cell tries to find their position in the site and meet their neighborhood within the tolerance value.When the simulation is started, the initial situation is determined by assigning a state (live pattern) for each cell from the intervention step. A new generation of cells is then created according to spatial properties of the site and the tolerance rule. The tolerance rule determines that the new state of each cell is based on their current states and the cells around. Eventually if all the cells meet the rules, they will be stable. It should take a finite amount of time to reach this stable state. Otherwise, designers should reduce tolerance value and modify the initial parameters in the intervention step to achieve convergence.4
self-organization building behaviors3.2 Algorithm - micro action
java simulation software/developer haidong ma
date: 2015ancher numbers: 4
develop levels: 2sum of buildings: 850
floor area ratio(FAR): 1.2
MALL
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3.3 Software Output
The complete simulation process is a sequence loop. At the first step (intervention), the processing is initialized and parametric rules considering the infrastructure and basic programs are set up. At the second step (self-organization), the villages reflect the parametric elements and start the process of self-organization. At the third step (auto-generation), local infrastructure and related facilities are generated automatically. When the three steps sequence accomplished, simulation process goes back to the first intervention step for the next computing circle. After several iterations of processing and intervention from designers, simulation process will arrive at the final development sequence. At this point, the whole scene of this site is generated.
Develop Sequence
integration isolation developed current 1 2 3 4
Infrastructure Upgradingauto generation by develop sequence
selected by manual
"Macro Thinking & Micro Action" has been selected as one of the 10 best papers of the eCAADe2010 conference.
4 conclusion & feedback
Software & Algorithm Support:Java, provided an object-oriented languageProcessing, provided a visual contextPostSQL & PostGIS, provided a related spatial database and algorithm
5 Reference
1. Laurence Liauw, 2008, ‘New Urban China’, Architectual Design, Profile No 195, Wiley2. Alexander, C 1965, ‘A city is not a tree’, Architectural Forum, Vol 122, No 1&2, April 1965, pp 58-62.3. Schelling, T. C 1978, Micromotives and macrobehavior, W. W. Norton, New York.4. Batty, M 2005, Cities and Complexity: Understand cities with cellular automata, agent-based models and fractals’, The MIT Press, Cambridge, Massachusetts.
[1] http://en.wikipedia.org/wiki/Computer_simulation.[2] http://en.wikipedia.org/wiki/Cellular_automaton.
4.1. ConclusionThe final version application still is on processing though, it is clear that digital parameterization and simulation can be considered as new possible urban tools to model the realities and generate solutions. In this case, by introducing anchor points urban design principle and cellular automata digital method. Computational simulation of urban developing can happen under the control of certain parametric rules and setting up people living behavior. Because this new tools embrace emerging process into strategy, one of the benefits of this new tools is that different users can be involved into the process. It helps to find a more adaptive proposal for cities. The critical issue of this method is to create a convergence programming sequence structure that has the ability to simulate a whole scene of urban develop procedure, otherwise simulation will be endless.
4.2. Feedback
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