Spring 2017|Coding Density|Workshop|Day 1

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//multi-

PERFORMATIVE URBANSCAPES //14st- 25th August//C o m p u t a t i o n a l D e s i g n W o r k s h o p

//CODING DENSITY STUDIO//UTS 2017


//workshop agenda

A

B

C

each group will select and study 1 area //Deliverables: -3 Infrastructure studies -3 Function allocation options with different degrees of density and mixture between different functions -Show how the model evolves in time (when more transportation nodes will be added etc)


//multi-agent computational systems //Swarm algorithms

a flock of birds=a swarm=a multi-agent system


//multi-agent computational systems //Swarm algorithms so what is swarm intelligence? //agent A


a glimpse of agent A in very crucial negotiations with the flock

//agent A

//agent B

//agent C


[agent direction]

[agent distance]

RULE A

RULE B

RULE C

cohesion

separation

alignment

//each agent behaves according to certain rules SELF-ORGANIZATION “the spontaneous appearance of order out of local level interactions”




//multi-agent computational systems //Physarealm

//Imitates the behaviour of Physarum Polycephalum


//multi-agent computational systems //Open the file “1. Introduction to Physarealm� Plug-in the terrain for the simulation

The Physarealm machine

select the starting points of the simulation

select the attractor nodes [f.i. the new infrastructure nodes]

//Physarealm


//multi-agent computational systems //Open the file “1. Introduction to Physarealm�

//Physarealm


//multi-agent computational systems //How to start the simulation

//Physarealm

Double-click the Boolean Toggle to turn it from True to False If the timer looks like this

double-click on it to activate it

After you start the simulation, double-click this to turn it to false, in order to visualize the agent trails


//multi-agent computational systems //What you should see

//Physarealm


//multi-agent computational systems //Let’s go through the plug-in tabs

Different kinds of emitters

Different kinds of environments

//Physarealm

And the mysterious settings


//multi-agent computational systems //Case application: our site

//Physarealm

//Open the file “2. Introduction to Physarealm_Case application� For the Environment we need a surface/ brep, but we have a mesh, so this part converts it to the desired geometry type

The Environment/Emitter/Food as usual

The Physarealm machine

Visualisation techniques

The Settings are not connected yet// connect them to see how it will affect the simulation


//multi-agent computational systems //How to visualize the agent field

//Physarealm

!!!!AFTER YOU START THE SIMULATION

Visualizes the history of the agent movement as points Increase this number to get longer agent trails

Visualizes the history of the agent movement as curves


//multi-agent computational systems //What you should see- with point set 1

//Physarealm


//multi-agent computational systems //What you should see- with point set 2

//Physarealm


//multi-agent computational systems //What if we use curves as emitters instead of points?

//Physarealm

//Open the file: “ 2. Introduction to Physarealm_Case application_curve as emitter�

Right-click on the Curve component and select Set Multiple Curves, then select your curves from the Rhino interface

Select the Curve Emitter component instead of the Point Emitter (you will find it under the Emitter tab). If you have many curves, right-click and select Flatten.


//multi-agent computational systems //What you should see

ITERATION A

//Physarealm

ITERATION B

ITERATION C


//multi-agent computational systems //What if we want to use both curves and points as emitters? //Open the file: “ 2a.Introduction to Physarealm_Case application_curve as emitter_2�

If you want to use point and curve emitters together, Physarealm does not accept that. You can though divide the curves and get the points in this way.

Remember to right-click and flatten the Points (same in the case of curves etc)

//Physarealm


//multi-agent computational systems //What you should see

ITERATION A

//Physarealm

ITERATION B

ITERATION C


//multi-agent computational systems //A more advanced example

//Physarealm

//Open the file “3. Introduction to Physarealm_Case application�

Mesh-to-Brep conversion-same as before

Surface split following the pattern of the hydrological network

Same as before


//multi-agent computational systems //Physarealm

The part of the algorithm that splits the surface

The surface is split in 3 areas


Area populated with 21 nodes

Change the number of points (21 and 17) in the Population components and plug the points in the POINT FOOD or POINT EMITTER component

Area populated with 17 nodes


//Also very popular for 3D micro-scale experimentations

//How to interpret this? -As infrastructure networks -Set different gradients of points in each district in order to examine the density of the transportation network -Alternatively: The paths can be interpreted as parts of the city with denser functional grid -To create branching water management networks


YOUR TURN!

Experiment with: -the settings -different emitters and food points -what if you use curves from the water network as emitters and work with a branching system for water management?


//multi-agent computational systems //Kangaroo


//multi-agent computational systems //Open the file “4. Introduction to Kangaroo_Particle attraction and repulsion�

//Kangaroo

all Kangaroo simulations need 3 things

the Kangaroo Physics machine: runs the simulation

Right-click here to select different points

Simulation reset button

Timer


//multi-agent computational systems //Kangaroo

the force object that we are going to use

the Kangaroo Physics machine: runs the simulation

PLUG-IN YOUR FORCE OBJECTS PLUG-IN YOUR GEOMETRY


//multi-agent computational systems The circle-packing algorithm

HOUSING

COMMERCE

BIOPHARMA

AGRICULTURE

//Kangaroo


//multi-agent computational systems //Open the file “4. Introduction to Kangaroo_Simple circle packing�

Plug-in the surface/mesh that you want to populate [in this case our site]

Defines the amount of agents [circles]

Defines the numerical domain of the circle sizes [smallest circle radius:2, largest circle radius:5] Double-click the reset button to execute the simulation

//Kangaroo


//multi-agent computational systems //What you should see

//Kangaroo

No control yet over the size/place of the functions


//multi-agent computational systems //Open the file “6. Kangaroo_Advanced circle packing�

forget the rest-just play with the settings here

This part retrieves from an excel file the sizes of each function and the number of units to be generated

//Kangaroo

This part populates the surface with the desired amount of particles, and then splits this amount to subgroups according to the units of each function the math jargon

Here you put the destination point for each function, and the land is divided to patches surrounding those points

Pulls the functions to a specific patch of land


//multi-agent computational systems //Script logic

//select the points that will attract the functions

//select the x number of Closest Points that surround them

//Kangaroo

//based on that, select the brep faces that are closest to these points =CREATE SUBDISTRICTS

//pull the spheres to the selected surfaces by using Pull to Surface



//multi-agent computational systems //How to connect the file with the excel sheet

STEP 1. !!Super important: Paste here the directory of the excel file in your computer!!

//Kangaroo


//multi-agent computational systems //How to connect the file with the excel sheet

STEP 2. Right-click the Spreadsheet Reader component, disable it and enable it again [otherwise the excel sheet will not be read and an error message will pop up] ,

//Kangaroo


//multi-agent computational systems //How to connect the file with the excel sheet FUNCTION NAME

FUNCTION TOTAL AREA

//Kangaroo

SUBDIVISION INDEX [how many units does each function contain: how many houses, schools etc

6

//Count the number of cells that each category occupies

8

7 4 STEP 3. Put these numbers [6,8,7,4] here as a list


//multi-agent computational systems //How to play with the script Just play with the settings here

Connect here the points that you want to use as attractors for the functions [it has to be 4 points,each representing 1 district] Connect this to the site brep

//Kangaroo


//multi-agent computational systems //How to play with the script

//Kangaroo

Also play with this

This number controls the size of each of the 4 subdistricts-play with it to see how it affects the density of the function distribution


Case A: N=10

Case B: N=20

Case C: N=200


what’s next? THE MEGA CROSSOVER

//Physarealm

VS

//Kangaroo


//what’s next? //Kangaroo vs Physarealm: The Great Crossover

DISTRICT 1 DISTRICT 2 DISTRICT 3 DISTRICT 4

//Run a simulation for the infrastructure in Physarealm

//Use it as input for selecting the attraction points in the Circle Packing algorithm


YOUR TURN!

Experiment with: -various areas and numbers of subfunctions in order to achieve different densities -Various distances between the starting points


once again//workshop agenda

A

B

C

each group will select and study 1 area //Deliverables: -3 Infrastructure studies -3 Function allocation options with different degrees of density and mixture between different functions -Show how the model evolves in time (when more transportation nodes will be added etc)

Physarealm Kangaroo


COFFEE BREAK


//branching techniques //Wooly Paths

Mimics the behaviour of wet wool threads Look for: Otto Frei-Wooly threads Edge bundling Kernel Density Estimation-based Edge bundling


//branching techniques //Wooly Paths

Physical vs Digital


//branching techniques //Open the file “7. Branching techniques_Wooly Paths_Start�

//Wooly Paths

Input: LINES

!!!!!!!!!First play with all the sliders etc on the left and then activate this component (right-click on it and then select ENABLE), otherwise it will crash!!!


//branching techniques //Wooly Paths

1. Divides the creek curves to create points

2. Interconnects the points

RIGHT-CLICK THIS AND SELECT “ENABLED”


//branching techniques //Wooly Paths

Kernel Size 5

Kernel Size 3


//branching techniques //How to create VARIOUS DENSITIES //Open the file “8. Branching techniques_Wooly Paths_Various densities�

We want District 1 to have a low density so we have just 15 interconnecting lines

We want District 1 to have a medium density so we have 66 interconnecting lines

We want District 1 to have high density so we have 120 interconnecting lines

//Wooly Paths


more interconnections

more density

District A: 15 Interconnecting lines

District B: 66 Interconnecting lines

District C: 120 Interconnecting lines


//branching techniques //How to use the curves as a pattern to split the surface

//Wooly Paths

//Open the file “9. Branching techniques_Wooly Paths_ Get surfaces from the curves and connect to Kangaroo�

1. Activate the Kernel Density component

2. Activate the Project component

3. Set the Boolean Toggle to TRUE 4. Activate the Project component 5. Activate the Patch Surface component


//branching techniques //Wooly Paths

The initial network

The subdistricts Notice how there is a gradient transitioning from larger to smaller subdistricts


what’s next? ANOTHER MEGA CROSSOVER

//Frei Otto and his wooly paths

VS

//Kangaroo


KANGAROO

DISTRICT 3 DISTRICT 2

DISTRICT 4

DISTRICT 1

//Create a curvilinear network with the Wooly Paths definition

//Use it as input for selecting the attraction points in the Circle Packing algorithm


COFFEE BREAK


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