Macro Thinking & Micro actionSimulation Algorithm of

Thesis by Haidong MaMentor:Benjamin DillenburgerMichael Hansmeyer

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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

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4

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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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penetrate into city

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Weekly Life

CORE AREA

Monthly Life

penetrate into city

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MALL

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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

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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