Biomimetics - Cellular Automata

Course director : Dr.Elif Erdine

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Emergent Technologies and Design

Founding director : Dr.Michael Weinstock

Studio Tutors : Abhinav Chaudhary, Alican Sungur, Eleana Polychronaki, Lorenzo santelli

Cellular Automata Group 02 Dhwani Bisani Devaiah Ponnimada Emergent Technologies and Design - Natural systems and Biomimetics

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Emergent Technologies and Design - Natural systems and Biomimetics

Contents

CONTENTS

Emergent Technologies and Design - Natural systems and Biomimetics

Abstract

1.0

About wasps Wasps and life cycle Types of wasps Construction strategy

2.0 2.1 2.2 2.3

Natural System Abstraction Cellular automata System logic

3.0 3.1 3.2 3.3

Stage I - Tests 1D cellular automata 2D cellular automata 3D cellular automata

4.0 4.1 4.2 4.3

Stage II - Tests Different initial position of origin cells Different repelling geometries

5.0 5.1 5.2

Stage III - Analysis Radiation analysis

6.0 6.1

Conclusion

7.0

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Emergent Technologies and Design - Natural systems and Biomimetics

Abstract

ABSTRACT The domain of the project investigates the nest construction activity of social wasps and to derive an algorithm which could generate possible solutions for designing a pavilion. The focus is to study the highly ordered building strategy of wasps and how local stimuli and environmental cues influence the nest construction. To create a system which works under the similar rules.

This report makes use of Cellular Automata (CA). Multiplicity of the cells is based on Cellular Automata, different cell states were programmed to mimic the construction process of that of wasps an in turn lead to generation of our global geometry.

Section lV consists of our initial experiments of understanding how cellular automata works in one, two and three dimensional grid. To define cell states and rulesets which govern the transition from one cell state to another.

Section V we explored CA further by varying the point of origin and introducing various repelling geometries.

Section Vl consists of radiation analysis of the geometry generated in the earlier sections Finally, the report concludes in with reflections on the whole process and recommendations on future research and application.

Emergent Technologies and Design - Natural systems and Biomimetics

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2.0. Wasps

Fig 2.1 - Life- cycle of waps

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Emergent Technologies and Design - Natural systems and Biomimetics

2.0. Wasps

2.0. About Wasps 2.1. Wasps and their life-cycle Queen emerges in the early spring, and finds suitable place to build a nest. The queen starts laying eggs as she builds each cell. The queen becomes a full time egg layer.

Towards the end of summer, the colony growth is peak and the queen produces eggs that develop into new queens and fertile males wasps.

As it grows colder, the colony productivity declines , the existing queen reaches the end of her life. And the other wasps starts abandoning the nest. Towards the end of winter the colony dies.

2.2. Types of wasps Among the numerous wasp species, we investigate the most commonly found species of wasps and their nest construction stratergies Paper wasp

Umbrella shaped

Yellow jacket wasp

Balloon shaped

Hornet

Balloon shaped

Mud Dauber

Mud mound

1. Umbrella shaped - Single uncovered comb, attached to the substratum by a petiole. Nest is constructed in an umbrella shaped geometry to protect the swarm and the cells from rain as these types of nests do not have an external protective envelope.

2 . Balloon shaped - Multiple combs covered by an envelope and attached to the substratum without a petiole Emergent Technologies and Design - Natural systems and Biomimetics

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2.0. Wasps

2.3. Nest construction strategies Nest construction occurs in three phases : 1. Pre - Emergence - Colony initiation to initial eclosion ( Founding )

2 . Ergonomic

- Period of growth of number of workers

3 . Reproductive

- Production of drones and gynes

2.3.1. Independent founders

One cell per day

Ovipositing

Worker population ecloses

Continuous nest-construction

Certain species of wasps like the paper wasp engage in continuous nest construction. This type of nest is usually started by a single queen. The queen builds one cell per day, ovipositing in the cell once its constructed. The queen forages and feeds the larvae untill they hatch.

Once the first brood of workers have eclosed, they take over the responsibilities of construction and foraging. Then on, the queen is only responsible for ovipositing.

In some instances, independent founders comprise of the queen, one or two female co-founders who share the responsibility of construction and foraging.

2.3.2. Swarm founders

Build in modules

Multiplication of module

Explosive nest-construction

Species similar to the yellow jacket wasps engage in explosive nest construction in which the construction is initiated by a swarm. The swarm usually comprises of the queen, two or three co-founders and multiple workers.

Swarm founders build a cluster of cells as a module and multiply the module rapidly. Hence the rate of nest construction is higher compared to independent founders. However, there isnt a close relationship between the rate of oviposition and nest construction 7

Emergent Technologies and Design - Natural systems and Biomimetics

2.0. Wasps

Nest-building patterns of colonies, according to the orientation of the substratum and the angle formed between the substratum and petiole

Nest-building patterns of colonies, according to the orientation of the substratum and the angle formed between the substratum and petiole

Productive and reused cells in two nests of Mischocyttarus consimilis, monitored from foundation to abandonment: (A) colony 15; (B) colony

Journal of Insect Science: Vol. 10 | Article 191

Mean duration of colonies : 231.7 +- 25.3 days Mean of adults produced : 40.7 +- 14.0 Frequency of productive cells: 33.3 +- 4.9 % Frequency of reused cells: 19.4 +- 4.9 Maximum no. of generations: 2.7 +- 0.4 in most productive cells Emergent Technologies and Design - Natural systems and Biomimetics

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3.0. Natural System

3.1. Abstraction

1.Construction of initial cells

2. Locating the centre cell for the next row of cells

3.Construction of the next row of cells

4.Increase In the number of centre cells with increase in number of cells per row

Natural principle - Abstraction : Nest construction is initiated with the first set of initial cells being built. Once built, the centre cell for the next row of cells is located. The location of the centre cell is decided based on most available surface area of initial cell walls from which construction can commence.

Having located the centre cell, the respective row of cells are built.

Only once all the cells in the previous row have been built, construction of the next row of cells begin. As the nest grows bigger to accommodate growing population, the number of cells in each row increase. Therefore the number centre cells in each row increase in relation to the number of cells.

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Emergent Technologies and Design - Natural systems and Biomimetics

3.0. Natural system

3.2. Cellular Automata This project makes use of cellular automation to test the abstracted principle of nest construction by wasps. The decision to use cellular automation as opposed to agent based system was due to the need for a complex global system of elements, operating in parallel with local level relationships which enable emergent behaviour .

Cellular automation enabled us to understand how complex systems work with the use of simple elements, and learn how modification of local relationships between elements generated different resulting models for the same global system. .

What is Cellular Automata ?

Cellular automation ( CA ) is a model of a system made up of “cell� objects.

Cellular automation comprises of : 1.Grid - Cells live on a grid 2.Cell State

- Each cell on the grid has a state. There can be different types of states, simplest cell states being : ( 0 - Dead , 1 - Alive , 2 - Miscellaneous )

3.Neighbourhood - Each cell on the grid has a neighbourhood. ( Typically a list of adjacent cells ) 4.Ruleset

- Rules defining the change of state of cells with respect to the defined neighbourhood, resulting in emergent behaviour.

Grid of cells

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Emergent Technologies and Design - Natural systems and Biomimetics

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0

0

0

0

0

0

0

0

0

1

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0

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Cell states

Neighbourhood

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3.0. Natural System

3.3. System Logic

PAPER WASPS Nests Construction

Central cells

Wasps starts constructing each row from the central cells

CELLULAR AUTOMATA Random assignment of a cell state to type 2

PSEUDO CODE

00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 22 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00

As a result of a cell type 2, birth of initial set of type 1 cells.

00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 11 00 11 00 00 00 00 00 00 00 00 22 00 00 00 00 00 00 00 00 11 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00

Cell states :

Proximity rules :

0 : Not built

If a cell 0 has a cell 2 in its defined proximity, There is a 40% probability to generate a cell 1

1 : Built 2 : Centre cell

Threshold : 40% probability

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Emergent Technologies and Design - Natural systems and Biomimetics

3.0. Natural system

Subsequent addition of the cells to finish a row of cells.

Intiating new rows and increase in number of central cells.

Abandonment of cells as the colony productivity decreases

+VE FEEDBACK

Subsequent addition type 1 cells

0 00 000 00 00 00 00 00 00 0 00 000 00 00 00 00 00 00 0 00 00 000 00 00 00 00 00 11 0 01 00 010 0 00 0001 0 00 11 0 111 01 0 00 000 001 01 0 10 2 1 0 00 000 00 00 201 021 0 10011000 1 0 00 000 001 0 00 11 0 01 00 010 0 00 0001 0 00 0 00 000000 00 00 00 00 00 0 00 000 00 00 00 00 00 00

0 0 0 0 10 10 0 0 0 0

0 0 0 0 1 1 1 0 0 0

00 00 00 00 00 00 00 00 00 00

-VE FEEDBACK

When it reaches a threshold and then one of the cells convert to cell type 2

0 00 000 00 00 00 00 00 00 0 00 000 00 00000000 00 00 0 00 000 00 00 00 00 00 00 2010 01 021 00 0 00 0001 0 01 11 1 01 1 01 0 00 000 001 01 0 1012 0 00 000 00 00 201 021 0 0 0011001 0 0 00 000 001 0 01 01 0 01 00 010 0 00 0001 0 01 0 00 000 00 00 00 00 00 00 0 00 000 00 00 00 00 00 00

0 0 0 20 10 10 0 0 0 0

As a result of less cells in the neighbourhood or overpopulation, a cell changes to type 0

0 0 0 0 1 1 1 0 0 0

00 00 00 01 01 00 00 00 00 00

0 00 000 00 00 00 00 00 00 0 01 000100 0 1000 00 00 00 1 00 100 0 1000 00 00 00 00 110221 0 2110 0 10 00 1010 20 21 0111 0 1 0 10 0 2100021 0 1 1 11 20 0 00 000 00 00 201 0200 10 10110101 0 00 000 101 0100 0010 0 00 000 10 2011020 1 0 2 0 00 000 00 00 00 00 00 00 0 00 000 00 00 00 00 00 00

Global rule :

Global rule :

If there are more than 5 cells in cell state 1 in proximity.

One of them is selected randomly and becomes cell state 2

If a cell has 2 or less cells in cell state 1 or more than 6 cells in the proximity. It changes to cell state 0

0 0 0 2 1 10 11 01 0 0 0

Threshold : 5 cells

Emergent Technologies and Design - Natural systems and Biomimetics

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0 0 0 0 1 0 1 0 0 0

4.0. Stage I - Tests

4.1. One dimensional cellular automata 1.Define initial population

2.Define cell states - Unbuilt - Built 3. Define neighbourhood

Neighbourhood of 3 cells 4. Define neighbourhood rules

Test 1 - Following the parameters, we test elementary CA for a one dimensional grid for an initial population of eleven cells. For this test, we considered two cell states, built and unbuilt.

At time interval T = 0, all cell states but one random cell are unbuilt.

We define neighbourhood rules to generate new cell states for every next time interval and test the resulting behaviour of the system for a time interval of T = 10.

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Emergent Technologies and Design - Natural systems and Biomimetics

4.0. Stage I - Tests

Time based iterations :

T=0

T=1

T=2

T=3

T=4

T=5 T=6

T=7

T=8

T=9

T = 10

Observations : • Using the given ruleset, the resulting overall geometry is Sierpinski trianle • Cell states repeats itself in a fractal pattern, which we would like to experiment with 2D and 3D CA

Emergent Technologies and Design - Natural systems and Biomimetics

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4.0. Stage I - Tests

4.2. Two dimensional cellular automata 1.Define initial population

2.Define cell states

3. Define neighbourhood rules

- Unbuilt - Built

Neighbourhood of 6 cells 4. Define neighbourhood rules Born rule : if a cell is has 3 built cells in its neighbourhood, its cell state changes to built.

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Survive rule : if a built cell is has 5 built cells in its neighbourhood, its cell state remains the same.

Emergent Technologies and Design - Natural systems and Biomimetics

4.0. Stage I - Tests

T=9

T=8

T=7

T=6

T=5

T=4

T=3

T=2

Observations : • The results of 2D CA can be stacked in the z-axis in order to achieve a 3D geometry. But the resulting geometry was less intuitive. • Thus we decided to test the code to develop 3D CA Emergent Technologies and Design - Natural systems and Biomimetics

T=1

T=0 16

4.0. Stage I - Tests

4.3. Three dimensional cellular automata 1.Define initial population

2.Define cell states - Unbuilt cells - Built cells - Origin cells 3. Define neighbourhood rules

4. Define neighbourhood rules

• Rule 1 : If a cell has a cell type 2 in the neighbourhood, it changes to 1 • Rule 2: If a cell has more than three 1s, it changes to 1 (only If it does not have 2 in the neighbourhood) • Rule 3: If a cell has more than 18 1s in the neighbourhood, it changes to 2. A cell can’t change to 2 if it has two in the neighbourhood.

• Rule 4: If a cell state is 1 and the value of neighbours is more than 8 or less than 2, the cell state changes to 0 17

Emergent Technologies and Design - Natural systems and Biomimetics

4.0. Stage I - Tests

T=0

T=5

T = 10

T = 15

Observation : • The resulting geometry shows cells sharing edge conditions with neighbour cells and some cells that are independent of any connections • The code for 3D CA can be continuously modified to adapt to different tests.

Emergent Technologies and Design - Natural systems and Biomimetics

T = 20

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5.0. Stage II - Tests

5.1. Different initial position of origin cells In the second stage of testing , we tested 3D CA from different initial positions of origin cells in every iteration .

No. of iterations : 1 No. of type 1 cell : 1 No. of type 2 cell : 847

No. of iterations : 5 No. of type 1 cell : 186 No. of type 2 cell : 1705

No. of iterations : 1 No. of type 1 cell : 1 No. of type 2 cell : 3180

No. of iterations : 3 No. of type 1 cell : 83 No. of type 2 cell : 1663 22

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No. of iterations : 1 No. of type 1 cell : 1 No. of type 2 cell : 4

No. of iterations : 5 No. of type 1 cell : 61 No. of type 2 cell : 828

Emergent Technologies and Design - Natural systems and Biomimetics

5.0. Stage II - Tests

No. of iterations : 10 No. of type 1 cell : 258 No. of type 2 cell : 2048

No. of iterations : 15 No. of type 1 cell : 278 No. of type 2 cell : 2001

No. of iterations : 6 No. of type 1 cell : 145 No. of type 2 cell : 4168

No. of iterations : 9 No. of type 1 cell : 172 No. of type 2 cell : 2283

No. of iterations : 10 No. of type 1 cell : 147 No. of type 2 cell : 1658

Emergent Technologies and Design - Natural systems and Biomimetics

No. of iterations : 15 No. of type 1 cell : 159 No. of type 2 cell : 2671

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5.0. Stage II - Tests

5.2. Repelling geometries

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No. of iterations : 1 No. of type 1 cell : 1 No. of type 2 cell : 4266

No. of iterations : 5 No. of type 1 cell : 354 No. of type 2 cell : 3421

No. of iterations : 1 No. of type 1 cell : 2 No. of type 2 cell : 8

No. of iterations : 7 No. of type 1 cell : 77 No. of type 2 cell : 2629

No. of iterations : 1 No. of type 1 cell : 1 No. of type 2 cell : 4

No. of iterations : 7 No. of type 1 cell : 235 No. of type 2 cell : 2248

Emergent Technologies and Design - Natural systems and Biomimetics

5.0. Stage II - Tests

No. of iterations : 15 No. of type 1 cell : 488 No. of type 2 cell : 4821

No. of iterations : 25 No. of type 1 cell : 651 No. of type 2 cell : 5582

No. of iterations : 14 No. of type 1 cell : 157 No. of type 2 cell : 8135

No. of iterations : 21 No. of type 1 cell : 240 No. of type 2 cell : 4331

No. of iterations : 14 No. of type 1 cell : 356 No. of type 2 cell : 3970

No. of iterations : 21 No. of type 1 cell : 514 No. of type 2 cell : 4729

Emergent Technologies and Design - Natural systems and Biomimetics

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5.0. Stage II - Tests

5.3. Repellor geometries Testing 3D cellular automata with repellor geometries.

Iteration 1

Iteration 2

Iteration 3

Repelling Geometries

Cellular Automation

Final Geometry

Cross Section

Observations : • The CA grows around the repelling geometries and only ends once the CA has checked all the cells in the bound box. • The CA is limited by the definition of the bounding box 23

Emergent Technologies and Design - Natural systems and Biomimetics

6.0. Stage III - Tests

6.0. Stage III - Tests

6.1. Radiation analysis We wanted to test two geometries with extreme conditions . Iterations 1 and 3 were futher tested for radiation.

Test 1 - Iteration 1

Test 2 - Iteration 3

Observations : • Iteration 1 is affected by relatively higher radiation, on the overall geometry • Iteration 3 is exhibits more desirable results as the internal spaces of the geometry are well protected from solar radiation.

Emergent Technologies and Design - Natural systems and Biomimetics

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7.0. Conclusion

CONCLUSION Cellular Automata is a rule based system, which can be used to understand emergent behaviour of biological systems in terms of self organization.

And this system can be further developed into a computational algorithms which can be tested to generate efficient sustainable, modular, flexible, and the system which has the ability to adapt and evolve.

The geometry generated by the CA results in rigid bodies that are connected to their neighbours by edges. As a result these rigid bodies behave as pin connections and are subject to rotational movement during deformation.

There also exist independent rigid bodies which share no connections and are freely suspended which cannot be accounted for while running structural analysis using Karamba.

This helped us conclude that 3D CA geometries are computationally programmable but for it to generate stable physical structures, the rulesets need to be developed based on multiple trial and error.

SCOPE - Cellular Automata is a rule based system, and further experiments can be carried out by setting different birth and survival rules.

- It would be interesting to experiment with different geometries like hexagon and see how it grows with different number neighbouring cells.

-While defining rulesets for CA, the thresholds can be varied through iterations to achieve more dense or porous structure as the structure progresses.

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Emergent Technologies and Design - Natural systems and Biomimetics

6.0. Stage III - Tests

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Start / End point Toolpath Toolpath of the layer above No. of layers : 18 Toolpath length : 205mm

No. of layers : 30 Toolpath length : 1475mm

No. of layers : 20 Toolpath length : 1540mm

Foam block - 75 x 50 x 50 (mm)

Emergent Technologies and Design - Natural systems and Biomimetics

No. of layers : 68 (50 + 18) Total toolpath length : 78740mm Amount of support materal : xx

Amount of clay : 2230 cm3 Printing time : 30 min Drying time : 2 days (approx.)

No. of blocks : 757 Total amount of clay : 1688110 cm3 Total printing time : 47 days (8 hours a day) Emergent Technologies and Design - Natural systems and Biomimetics

No. of blocks : 1055 Total amount of clay : 2352650 cm3 Total printing time : 66 days