BPro RC 1 2016/17_Modiform

Modiform

The Bartlett School of Architecture RC1 Wonderlab / Architectural Design 2016-2017

RC1 Tutors Alisa Andrasek / Daghan Cam Soomeen Hahm / Andy Lomas Members Yin Yuan / Paat Pimarnprom / Zaiguo Lin

Content / Introduction / / Research / Adaptive orientation Achieving high-resolution with voxelization Topology Optimization Lattice structure & Precedent study Lattice behaviour: Continuous Combination Subdivision Deformation / Experimentation/ Agent-based modeling High density cell Inside - Outside Count Agents Count Trailpoints Cell deformation Compression Offset High density cell + Cell Deformation

/ Design Method / Toolpath Combination Creating Depth / Thickness Cell Deformation & Toolpath Design

/ Design Implementation / Chair Design Wall Design Pavilion Design

/ Fabrication / Final Model for Exhibiton Toolpath Design & Printing Sequence End-Effector Design Printing Test

Introduction Mod[i]form

Modify + Deformation Modify - Adaptive orientation of voxels Deformation - Alteration and distortion of lattice cells

This research project focuses on the simulation and fabrication of lattice cells. The application of different subdivisions cell and cell deformation are used in the research in order to find the best possible way to capture the agent behaviours and translate it into a fabricatable model without losing its characteristic and directionality.

Due to the constraints in robotic fabrication, each lattice cell needs to have printable, continous components that will allow the printing to process in the most efficient way, both in terms of production time and material usage.

The team attempts to simulate and produce models in architectural scale, in which we first started with the simulations of chair, wall, and space (pavillion). In terms of fabrication, more experimentation will be tested in order to find the balance between simulated models and fabricated ones.

Research Focus High-Resolution Design Lattice Cell Simulation Porousity / Transparency Voxel Deformation

Transformation from a uniform voxel grid to a non-uniform, heterogenous pattern

/ Research /

Adaptive Orientation The research focuses on the possibility of using the method of adaptive orientation in the simulated models. By identifying the crucial parts that require more attention, the voxel grid can be shifted towards those specific parts, which generates a more robust and flexible design. This method also provides efficiency in terms of computer-modeling and materiality used in the actual fabrication. It is also beneficial for structural purposes, by adapting more resolution towards the parts that requires more attention, the simulated model can achieve high complexity without losing its strength.This ideology has the potential in creating intricate models in the scale of architecture, with the development of construction technology and Artificial Intelligence, it is possible to model and fabricate such high-resolution and complex design in the near future.

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Adaptive Orientation in Nature Adaptive orientation or adaptive organisation appear frequently in nature. Patterns found in sea shell or leaf are all parts of the result from adaptive orientation.

Figure 1.1 Close-up picture of a piece of the pelvic bone.

(Dr. Yebin Jiang)

Figure 1.2 the upper section of the femeur

Bone structure is the closest reference to this research. The bones in the skeleton are not all solid. The outside cortical(compact) bone is solid bone with only a few small canals. The insides of the bone contain trabecular(spongy) bone which is like scaffolding or a honey-comb. The space between the bone are filled with fluid bone marrow cells, which make the blood, and some fat cells.[Figure1.1].

Furthermore, in the upper section of the femeur[Figure1.2], the structure and distribution of trabecular and cortical bone efficiently reflected the stresses( both tensile and compressive) generated by the bending moment. The spony bone is composed of two systems of trabeculae. One follows curved paths from the inner side of the shaft and radiates outwards to the opposite side of the bones, following the lines of maximum compressive stress. The second system forms curved paths from the outer side of the shaft and intersects the first system at right angles. These trabeculae follow the lines of maximum tensile stress, and in general are lighter in structure than those of the compressive system. [Figure1.3].

In all, the bone structure is able to create a resilient yet efficient structure by combing various densities and adaptive cells.

Figure 1.3 This diagram shows computed lines of constant stress from the analysis of various transverse sections.

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On Growth and Form - Transformation D’Arcy Wentworth Thompson’s book, on Growth and Form, is our most important refercence. In this book, he conceived of form not as a given,but as a product of dynamic forces that are shaped by flows of energy and stages of growth. “He draws out the laws governing the dimension of orgnaism and their growth, the statics and dynamics at work in cells and tissues including the phenomena of geometrical packing, membranes under tension,symmetries,and cell division;as well as the engineering and geodesics of skeletons in simple organisms.”( Sarah Bnonnemasion and Philip Beesley,2008) Thompson pointed out correlations between biological forms and mechanical phenomena by showing the similarity between the internal supoorting structures in the hollow bones of birds and well-known engineering truss designs. He explores the degree to which differcences in the form of related animals could be described by means of realatively simple mathematical transformations.[Figure 1.4].

With the development of computer-driven design, morphology has once again appeared as a significant theme in contemporary architectural theory. New generations of buildings can accommodate shifting forces,distributing loads to better withstand undesirable deformation. The new design methodology is capturing the geometric relationships that form the foundation of architecture and can create a model enabling coordinate and update themselves. It is quite similar that mutations in nature generate biodiversity,individual variation in architecural components can be archeived economically.

Thompson’s way of seeing the world continue to inspire scientist, artists and architects.

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Figure 1.4 Transformation of Argyropelecus olfersi into Sternoptyx diaphana,Thompson.

Achieving high-resolution with voxelization Traditional brick based architecture can served as the basis theory of 3D voxel. The entire structure resolution is low by using voxel components of the same type and material.

Figure 1.5 This picture shows a character mesh voxelized at different resolutions.

Voxel computation [Figure 1.5] has been used in recent architectural research.[Figure 1.6]. This example was shortlisted for the UCD Image of Research Competition 2008. 3D voxels are created to encapsulate the input point set. So, for each cube there is one or more data points inside its volume. The cubes are in fact the bounding boxes of the points in the structure.

Data points are streamed, which means that there is no limit to the number of points being used in voxels. All the voxel elements are identically applied. However, the potential of the voxel which we can create new result by combing different data is rarely implemented.

This design research aims to capture the input data, in this case agent behaviour, by using the method of voxelization. By inserting different types and mutated voxels into the computer-simulated model, we are able to design a lattice structure in a much more intricate scale. The use of voxel also allows flexibility and adaptability since each cell can be adapted according to the input data.

Figure 1.6 The input point set for this image was part of a high-grade aerial laser scan of the city of Dublin.

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Topology Optimisation Topology optimization is a method for optimizing the organisation of material, indicating the area with high and low stress, the direction of load, and stiffness of the model. This method is useful for calculating structural properties in order to generate a model with high structural performance and high material efficiency.

Specifically for this project, Millipede, a Grasshopper component focusing on the analysis and optimization of structures, is employed as a tool to identify the structural properties of a model. Millipede allows us to extract structural information such as stress, stiffness, and finite element model after analysing all the input settings. Since there are many different outputs from topology optimization, many experiments are conducted in order to find the best possible output that works well when used as an input in the simulations. Stress lines and principal stress color map from topology optimization shows high potential for further design development because they analyse the structural requirements of a model which can be used as a guideline for distributing material.

Stress lines comprise a list of numbers indicating the location of points and stress vectors showing the direction of stress forces.

Principal stress color map comprises a list of number indicating the location of points and the stress value of each point. Therefore, the lists of numbers from stress lines and principal stress color map are applied as an input for form finding, material organisation, voxel type activation, and voxel deformation.

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Support regions

Support regions

Loads regions

Loads regions

1 The input geometory: 2D target mesh, Loads and support regions

Support regions

2 The visualization of stress lines which shows how force along the design domain

Support regions

This diagram shows the way we combine the deformation strategy Loads regions 3 The color shows the stiffness of the design domain

Loads regions 4 The relationship between stress lines and stiffness

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with Topology Optimization to increase the structure performance and material distribution.

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Agent-based Simulation - Flocking Algorithm Our design research is mostly based on the Craig Reynold’s algorithms for biods [Figure 1.7] which are examples of Swarm distributed behaviour.

As Craig Reynold (1987) discussed, the simulation of a flock of birds is based on modelling the behaviour of each bird independently by regarding it as an agent. This approach assumes that a flock is simply the result of the interaction between the behaviours of individual birds. The birds try to stick together and avoid collisions with one another and with other obstacles in the environment . The beautiful complex behaviour of flocking birds can be stimulated in three principles:1.Collision Avoidance: avoid collisions with nearby flockmates. 2. Velocity Matching: attempt to match velocity with nearby flockmates 3. Flock Centering: attempt to stay close to nearby flockmates.(CW Reynolds,1987)

Figure 1.7 A school of fish

These forms are the result of the continuous multi-port data system, so they come with features of various types of input data, showing the unique transition into organic natural forms. This design system is flexible; they always show a mixed, fixed, occurrence and disappearance, dispersion and agglomeration of macroscopic effects.

In our case, voxels are activated by agents which are programmed through the features of cohesion, aligment and separation and variable values of their spring connections. The design result will be adapted to local environment, unique and finally achieve a more natural aesthetic simulation.

Separation

Alignment

Cohesion

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Lattice structure Lattice is commonly used in architectural design as it is one of the strongest types of structure and can be applied to different geometries. This structrue has several distinct advantages compared with other structures. By using only one cost-saving material, we can create a structure that is simultaneously dense and sturdy in parts (for load-bearing walls), lightweight and porous in others (for nonload bearing walls), and even near-translucent in others (to allow the inflow of natural lighting). It is mainly because of the fact that materials is distributed spatially in a quite efficient way that it reflect the load tranfer mechanism- tension or compresssion.

Figure 1.9 Gramazio Kohler’s Iridescence Print

In terms of digital fabrication, lattice structure posses a versatility of form and can utilize a standard module to produce. There are several projects exploring the use of lattice structure in 3D plastic extrusion using robotic arm for printing. For example, Gramazio Kohler’s Iridescence Print in Zurich [Figure1.9], Patrik Schumacher’s Puddle Chair in collaboration with AI Build, and AI Build’s Daudalus Pavilion. [Figure2.0] Our research will explore more into the application of lattice cells in computer modeling and the possibility of fabricating intricate lattice structure.

Figure 2.0 AI Build’s Daedalus Pavilion

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Lattice Behaviour 1.Continuity

4. Deformation

Limitation of robots should be considered so as to fabricate the complicated geometry with spatial extrusion. On summary, the whole design objects should be printed with one continuous line. Following are the some more detail rules : Firstly, basic geometry should be strong enough to support the structure. Secondly, the extrusion always strart from the ground level. Thirdly, the latter toolpath should not collide with former ones. On the forth hand, the extrusion always start at the lines of biggest angle from ground.

The ability to deform the regular voxel takes a leap to reveal the high performance of the lattice structure. In our project, we have developed two strategies to capture the vains of agent behavior. The first logic is what we called compression according the location of agents. From the beginning , we are able to set deform range. Inside the range we calculate every vertices of the voxels. If the distance to attractor agent is smaller, it deform more. To make each voxel printable preventing defrom too much, we also need to set the maximum deform value to be the half size of cell. Similarly, the second logic is so called orientation by capturing the direction of the agents. Each vertices of the voxels inside the deformation range move to the same direction of the attractor agents. The distance they move depends on their distance to attractor.

2.Combination After achieving one singal voxel, combining different types of voxel to meet with different surfaces or meet different function requirment is quite essential. These different types of voxels could be different density or different direction with same density. There is a need to set basic rules to differentiate the voxels using algorithm.

3.Subdivision One of the approaches in achieving high-precision design is to simulate low and high density cells created by the use of subdivision. The low-density cell contains one subdivision, while the high-density cell contains four subdivisions. The high-density cells are activated in accordance to the number of agents running through each particular voxel.

The use of cell subdivisions allows us to model very complex models with high strength in the necessary parts. Voxelization usually gives a very uniform and invariable result, however, the use of cell subdivision can generate variations and complexities while enhancing the ability to design with high precision.

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Regarding Thompson’s view of form as a product of dynamics forces that are shaped by flows of energy . With these two deformation logic, it is possible for us to achieve higher level intelligent structure by using 3D lattice printing.

Continuity

Combination

Subdivision

Deformation

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/ Experimentation /

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/ Agent based Modeling /

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Agent-based Modeling

Flocking algorithm is used here in order to imitate the behaviour of a flock of bird. This agentbased modeling, together with external forces (cohesion, separation, alignment), are used in the form finding proces of our design.

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Chair Simulation The idea first come from single seat surface. We extract the data, in this case surface point. There is a need for optimization through analysis which is based on the stress points values. Then we let the points( agents) to fall down with gravity force, naturally forming the legs of the chair.

At the same time, we also apply flocking algorithm( cohesion, separation,alignment) to got the final shape. The diagram below show how we design the chair step by step. Also, the diagram on the right page reveals that the high performance of agent when we adjust the force values.

1

2

Modeling a surface suitable for a chair

Extract point (agents) from surface

3

4

The form of a chair is generated according to the

Using flocking algorithm to shape the final ge-

force parameters

ometry.

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Agent-based Chair Simulation Each model has different characteristics due to various approaches used in the simulation. The team attempted to find the form that is unique, functional, and aestheticly attractive.

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Wall Simulation The agents are organised from points extracted from a surface.

Another group of agents acts as a leader to attract the agents to a certain direction, creating directionality and transparency to the model. This strategy shows some potentials for further steps in voxelization.

1 Extract points (agents) from a surface

2 Introduce another group of agents (attractors)

3 Agents interact with the attractors under various parameters, creating different results

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int numAgents = 200;

float alignmentStrength = 0.05;

float maxSpeed = 0.3;

int numAgentsB = 500;

float cohesionRangeB = 10;

float maxSpeedB = 0.2;

float cohesionRange = 10;

float cohesionStrengthB = 0.0000003;

float predatorRange = 10;

float cohesionStrength = 0.0001;

float separationRangeB =2;

float predatorStrength = 0.9;

float separationRange = 8;

float separationStrengthB = 0.03;

int maxAgeTrailPoint = 100;

float separationStrength = 0.05;

float alignmentRangeB = 20;

float alignmentRange = 20;

float alignmentStrengthB = 0.09;

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/ High Density Cells /

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Voxel Activation 1. The logic we activate the voxels.

As the diagram showed on the right page, we use the Trail points of the agents to activate the voxels. Once an trailPoint can be found in an voxel, it activate the cube. Apart from this, we can also activate the neighbours of voxels which the trail points passed by to make the whole structure strong enough. With this logic we start to capture the random movement of the agents.

ArrayList getClosestVoxels(int d) { int idX = int((loc.x + cellSize/2) / cellSize); int idY = int((loc.y + cellSize/2) / cellSize); int idZ = int((loc.z + cellSize/2) / cellSize); if (idX>resX-1) idX = resX-1; if (idY>resY-1) idY = resY-1; if (idZ>resZ-1) idZ = resZ-1; if (idX<0) idX = 0; if (idY<0) idY = 0; if (idZ<0) idZ = 0;

ArrayList result = new ArrayList(); for (int i=idX-d; i<=idX+d; i++) { for (int j=idY-d; j<=idY+d; j++) { for (int k=idZ-d; k<=idZ+d; k++) { if (i>=0 && j>=0 && k>=0 && i<resX && j<resY && k<resZ) {

}

}

}

}

}

result.add(voxels[i][j][k]);

Trailpoints of Agents

return result;

Agentsâ&#x20AC;&#x2122;s path Voxel field( unactivated) Activated Voxels

1.1 GetClosestVoxels(0) voxels only be activated by the trail points of agents passed by.

1.2 GetClosestVoxels(1) activate one neighbour of voxels which the trail points passed by.

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1.2 GetClosestVoxels(2) activate two neighbours of voxels which the trail points passed by.

Voxel Type Differentiation 1. Differentiat the type of voxels(inside - outside) Combining different types of voxel to meet with different surfaces or meet different function requirment is quite essential. There is a need to set basic rules to differentiate the voxels using algorithm. In this logic, we check each activated voxels and count each neighbours( every voxel has 27 neighbours in 3 dimension environment, set boundary value to differentiat the type.

Apart from this, the different types of voxels could be different density or different direction with same density.

Belows are the code part.

void calculateType() { int count=0; for (int i=idX-1; i<=idX+1; i++) { for (int j=idY-1; j<=idY+1; j++) { for (int k=idZ-1; k<=idZ+1; k++) {

}

}

}

}

if (i>0 && i<resX && j>0 && j<resY && k>0 && k<resZ) { if (!(i==idX && j==idY && k==idZ)) { if ( voxels[i][j][k].isActive) count ++; } }

if (count>25 ) type = 1; if (count<=25 && count>18) type = 2; if (count<=18 && count>1) type = 3;

Trail points of Agents Voxel field( unactivated) Activated Voxels

1.1 Activate Voxels voxels are activated by the trail points of agents passed by.

1.2 Change voxel type Check the whole shape and count each neighbours, set rules to differentiat the type.

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1.3 Change voxel type with hierarchy Use the same logic to apply more types of voxels to the structure.

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Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

Cell Density Activation / Inside - outside /

Front Elevation

Voxel activation system

Inside = Low Density Outside = High Density

Low Density

Section

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High Density

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Cell Density Activation / Inside - outside / High density cells are activated on the shell while low density cells are activated on the inside, making the shell stronger to support the structure as a whole.

Voxel activation system

Inside = Low Density Outside = High Density

A Front

A Section 1

A Section 2

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B Front

B Section 1

B Section 2

Low Density

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High Density

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Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

Cell Density Activation / Count Agents / The strategy of counting agents gives the best result as it captures the movement of agents very well without losing its complexity.

Low Density

Low Density

High Density

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High Density

Low Density

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Cell Density Activation

Agent simulation

/ Count Agents / Different density cells are activated in accordance to the number of agent counted in each voxel.

int numLeaders=100;

float cohesionStrength = 0.0001;

float maxSpeed = 0.3;

float separationRange = 8;

float predatorRange = 10;

float separationStrength = 0.05;

float predatorStrength = 0.9;

float alignmentRange = 20;

float cohesionRange = 10;

float alignmentStrength = 0.05;

void createLeaders() { for (int i=0; i<numLeaders; i++) { Vec3D t = new Vec3D(random(40, 140), random(10, 70), random(10, 20)); Leader b = new Leader(t); arrayOfLeaders.add(b); }

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Voxel cell activation

if (countAgents>1) type=1; if (countAgents>=30) type=2;

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Cell Density Activation / Count Agents / Different density cells are activated in accourding to the number of agent counted in each voxel. This table shows various results acheived by different parameters, from 10 to 60, which assists in making decisions during the simulation on a bigger scale.

Low Density

Low Density

High Density

countAgents>=10

countAgents>=20

countAgents>=30

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countAgents>=40

countAgents>=50

countAgents>=60

Low Density

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High Density

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Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

Cell Density Activation /Count Trailpoints / Different density cells are activated in accourding to the number of trailpoints counted in each voxel.

Low Density

High Density

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High Density

Low Density

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/ Cell Deformation /

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Cell Deformation

No deformation

In order to go beyond the uniform grid in the method of voxelization, the team applies the idea of deformation into our simulations.

The way the cells are deformed is based on two strategies, ‘Offset’ and ‘Compression’.

These strategies help us define the best method of deformation that would best capture the agent’s behaviours and produce the best possible result.

All voxels deformed

d<1.5 deformed

d

d

d Trailpoints Distance

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d

No morph

All morph

d<1.5 morph

d

d

d

d Trailpoints

d

d

Distance

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Cell Deformation

Compression

/ Compression / Offset / Simulations of cell deformation in relation to trailpoints using two strategies, compression and offset.

void morphVertices() { float dist = t.loc.distanceTo(v_original); deformation *= deformScale; for (int i=0; i<arrayOfControlPointsOriginal.size(); i++) { if (dist<minDist) { Vec3D dir = closestAttractor.sub(v_original); Vec3D v_original = (Vec3D) arrayOfControlPointsOriginal.get(i); minDist = dist; dir.normalize(); Vec3D v_morphed = (Vec3D) arrayOfControlPointsMorphed.get(i); closestAttractor = t.loc.copy(); dir.scaleSelf(deformation); Vec3D closestAttractor = new Vec3D(); } v_morphed.addSelf(dir); float minDist = 999999999; } } for (int k=0; k<arrayOfAgents.size(); k++) { } } Agent b = (Agent) arrayOfAgents.get(k); for (int j=0; j< b.arrayOfTrailPoints.size(); j++) { float deformation = constrain(map(minDist, 0, TrailPoint t = (TrailPoint) b.arrayOfTrailPoints.get(j); attractorRange, cellSize/2, 0), 0, cellSize/2);

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Offset

void morphVertices() { Vec3D velTrailPoint = new Vec3D(); for (int i=0; i<arrayOfControlPointsOriginal. size(); i++) { Vec3D v_original = (Vec3D) arrayOfControlPointsOriginal.get(i); Vec3D v_morphed = (Vec3D) arrayOfControlPointsMorphed.get(i); float minDist = 999999999; for (int k=0; k<arrayOfAgents.size(); k++) {

Agent b = (Agent) arrayOfAgents.get(k); for (int j=0; j< b.arrayOfTrailPoints.size(); j++) { TrailPoint t = (TrailPoint) b.arrayOfTrailPoints.get(j); float dist = t.loc.distanceTo(v_original); if (dist<minDist) { minDist = dist; velTrailPoint = t.vel.copy(); } } }

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float deformation = constrain(map(minDist, 0, attractorRange, cellSize/2, 0), 0, cellSize/2); deformation *= deformScale; Vec3D dir = velTrailPoint.copy(); dir.normalize(); dir.scaleSelf(deformation); v_morphed.addSelf(dir); } }

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Cell Deformation Documentation of different deform scale used in the process of deforming lattice cells. The cells are deformed and shift the vertices towards the velocity of trailpoints generated by the movement of agents.

deformScale = 0.1

deformScale = 0.6

deformScale = 0.7

deformScale = 0.2

deformScale = 0.3

deformScale = 0.8

deformScale = 0.9

deformScale = 0.4

deformScale = 0.5

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Testing Parameters Documentation of non-deformed cells in comparison with deformed cells in relation to agent behaviours.

DistanceToTrailPoint<0.1 float attractorRange =50; float deformScale = 0.7; CountTrailPoints:500

DistanceToTrailPoint<0.8 float attractorRange =30; float deformScale = 0.7; CountTrailPoints:500

DsitanceToTrailPoint<1.2 float attractorRange =30; float deformScale = 0.7; CountTrailPoints:500

DistanceToTrailPoint<0.5 float attractorRange =20; float deformScale = 0.7; CountTrailPoints:500

DistanceToTrailPoint<0.8 float attractorRange =5; float deformScale = 0.7; CountTrailPoints:500

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Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

Cell Deformation / Compression / The cells with close distance to trailpoints will get compressed closer to the trailpoints, making the vertices deformed and condense. In this experimentation, one model has all cells compressed, and another model with only some cells compressed.

All cells compressed Trailpoints compress all voxels

Part 1 Compression of voxels

Partly compressed Only the voxels with close distance to trailpoints get compressed

0.1 The range of deformation 2D Diagram

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0.9

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3D Diagram

Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

Cell Deformation / Offset / The cells with close distance to trailpoints will get offset to the velocity of trailpoints. All the vertices in each cell will move towards a certain direction, creating directionality that capture the agentâ&#x20AC;&#x2122;s behaviour very well.

do v

v

d

d

d

do

d

do

do

OFFSET

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Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

High Density and Cell Deformation / Count Trailpoints / Compression / These models show the steps of simulating agent behaviour, activating different density voxels, and applying deformation.

Agent behaviour

High density

Cell deformation 63

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/ High Density / Cell Deformation /

Deformation

High Density

No Deformation

One Density

Inside - Outside

Count Agents

Count Trailpoints

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Offset

Compression

Wall Simulation / Count Agents / Offset / The wall model generated from agent behaviour, with different density cells and the method of cell deformation. The combination of these two strategies provide good result in capturing agent behaviour and create complex, heterogenous model.

High Density

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Low Density

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/ High Wall Simulation Density / Cell / Deformation /

/ Design Method /

Design Method After many experimentations, the design method that the group follows is to extract the stress lines from topology optimization and use them to simulate the design.

Combining toolpath types by checking the distance to stress line.

The regions closer to stress lines will be one toolpath type, the regions further away will be toolpath type two and three.

Creating depth / thickness by checking the distance to stress lines.

The regions close to stress lines have thicker layers of voxel and more structural support.

Deforming voxels by checking the vector direction of stress lines.

The voxel vertices will be deformed towards that direction, creating denser material, which potentially generate more structural support.

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Cell Deformation & Toolpath Design Toolpath design is very essential for capturing the best deformation effect, transparency, and structural performance. From this study, three simple vectors are used as a sample of stress lines, guiding the voxel to deform following the vectorâ&#x20AC;&#x2122;s direction. Three toolpath design with pronouced directionality are selected for further design development.

Input Vector

Toolpath 1

Toolpath 2

Toolpath 3

Toolpath 4

Toolpath 5

Toolpath 6

Toolpath 7

Toolpath 8

Toolpath 9

Toolpath 10

Toolpath 11

Toolpath 12

Toolpath 13 (Selected)

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

Toolpath 14 (Selected)

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Toolpath 15 (Selected)

Toolpath Combination A combination of three toopath is simulated by checking the distance to stress lines derived from topology optimization Voxel type activation parameters: if (dist>0 && dist<=3) type = 1; if (dist>3 && dist<=5) type = 2; if (dist>5) type = 3;

Input Vector

Toolpath Type 1

Toolpath Type 2

Toolpath Type 3

Type 1

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Type 2

Type 3

RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Deformation Strategy 1: This strategy can be called compression. Inside the influence domain which can be set by the designer, each vertices find the location of the closesest attractor and move toward it. The closer ones move more, and the farthest ones didn’t move at all. The closer voxels deform too much and make it impossible to fabricate.

1) Calculating the vector field

3) Iteration

2) Moving along the direction.

Iteration 1

4) Extreme conditions. Iteration 6

Strategy 2: This strategy can be called compression. Inside the influence domain which can be set by the designer, each vertices find the location of the closesest attractor and move toward it. The distance they move is oppsite to above.

1) Calculating the vector field

2) Moving along the direction.

Iteration 1

3) Iteration 3

4) Extreme conditions. Iteration 6

Strategy 3: This strategy is capturing the attractor’s direction. Inside the influence domain which can be set by the designer, each vertices find the location of the closesest attractor and copy its velocity. The closer ones move more, and the farthest ones didn’t move at all.

1) Calculating the vector field

2) Moving along the direction.

Iteration 1

3) Iteration 3

4) Extreme conditions. Iteration 6

Strategy 4: This strategy is capturing the attractor’s direction. Inside the influence domain which can be set by the designer, each vertices find the location of the closesest attractor and copy its velocity. The distance they move is not linearly.

1) Calculating the vector field

2) Moving along the direction.

Iteration 1

3) Iteration 3 76

4) Extreme conditions. Iteration 6

Strategy 5: This strategy introduced the magnetic field according to the attractors. The direction of each voxel vertices is more smooth than the strategies above.

1) Calculating the vector field

Strategy 6:

2) Moving along the direction.

Iteration 1

3) Iteration 3

4) Extreme conditions. Iteration 6

This strategy introduced the magnetic field according to the attractors. The direction of each voxel vertices is more smooth than the strategies above. But the distance they move is not good, especially the boundaries.

1) Calculating the vector field

2) Moving along the direction.

Iteration 1

3) Iteration 3

4) Extreme conditions. Iteration 6

Strategy 7: This strategy improve the vector filed logic, the distance each voxel vertices moves is depend on their distance to their closest attractors. But the the closest vertices will deform too much to make it impossible to fabricate.

1) Calculating the vector field

2) Moving along the direction.

Iteration 1

3) Iteration 3

4) Extreme conditions. Iteration 6

Strategy 8:

This strategy is nearly the same above. But the distance they move is hyperbolicly to make it printable.

1) Calculating the vector field

2) Moving along the direction.

Iteration 1 77

3) Iteration 3

4) Extreme conditions. Iteration 6 RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

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Creating Depth / Thickness Thickness of the wall is activated by the distance to stress lines: the areas closer to stress lines will be thicker than the areas further away from stress lines.

Input : Stress Lines

Input: Stress Color Map

if (dist>=0 && dist<=5) type =1; getClosestVoxels(8); if (dist>5 && dist <= 8) type =2; getClosestVoxels(6); if (dist > 8) type =3; getClosestVoxels(3);

if ( value <= 0.1) nearVoxels = getClosestVoxel().increaseThickness(5); if ( value > 0.3) nearVoxels = getClosestVoxel().increaseThickness(9); if ( value > 0.4) nearVoxels = getClosestVoxel().increaseThickness(12);

if (dist>=0 && dist<=3) type =1; getClosestVoxels(8); if (dist>3 && dist <= 5) type =2; getClosestVoxels(4); if (dist > 5) type =3; getClosestVoxels(3);

if ( value <= 0.1) nearVoxels = getClosestVoxel().increaseThickness(3); if ( value > 0.3) nearVoxels = getClosestVoxel().increaseThickness(4); if ( value > 0.5) nearVoxels = getClosestVoxel().increaseThickness(5);

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Simulation Process The simulation is determined by the output from topology optimization.

In this case, stress lines and stiffness color map are used in order to create different thickness and deforming the voxel vertices

1 Voxelization the design domain with regular grid

2 Selecting the compression stress lines. The number we cull the lines depends on the density of voxels.

3 Translating the stiffness values from grasshopper files.

4 Activate more voxel layers according to the stiffness value.

5 Creating the vector field according to the stress lines we selected.

6 Each vertices of the voxels deform by the vector field

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Simulation Process This simulation shows the simulation process using a more complex stress lines. Intricate stress lines give more complex result when combining toolpath types, creating thickness, and deforming voxel vertices

1 Stress lines and voxel field

2 Combination of three toolpath types, represented by different colors. The distance closer to stress lines will be one type, while the distance further away will be the second and third type

3 Creating thickness by checking the distance to stress lines. The regions closer to stress lines have thicker layer of voxels

4 Deforming voxel vertices according to the direction of stress lines

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Design Results Wall simulations resulted from different design strategies: combining different toolpaths, creating depth/thickness, and deforming the cells.

These design stages show how the three strategies are able to turn a uniform voxel grid into a non-uniform, heterogenous model. These strategies create a design with high complexity, diversity, and potentially higher structural performance.

Stress Lines (Input data)

1 Combination of three toolpath Voxel combination parameters: if (dist>0 && dist<=3) type = 1; if (dist>3 && dist<=5) type = 2; if (dist>5) type = 3;

2 Combination of three toolpath + Voxel deformation Voxel deformation parameters: float attractorR1 =20; float attractorR2 =8; float attractorRange = 10;

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3 Combination of three toolpath + Activating depth Depth activation parameters: if (dist>0 && dist<=3) getClosestVoxels(8); if (dist>3 && dist<=5) getClosestVoxels(6); if (dist>5) getClosestVoxels(3);

4 Combination of three toolpath + Activating depth + Voxel deformation Voxel deformation parameters: float attractorR1 =20; float attractorR2 =8; float attractorRange = 10;

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/ Design Implementation /

Chair Design Model 1

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Chair Design

Model 1 - Section

Voxel activation system: Inside = Low Density Outside = High Density

Low Density

Medium Density

High Density

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Chair Design Model 1 - Detail

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Voxel activation system: Inside = Low Density Outside = High Density 91

Low Density

Medium Density

High Density

RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Chair Design Model 2

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

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Chair Design

Model 1 - Section

Voxel activation system: High density close to surface

High Density

Low Density

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Chair Design Model 2 - Detail

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Voxel activation system: High density close to surface 95

High Density

Low Density

RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Chair Design The chair design uses the output from topology optimisation in order to identify the regions which require more structural support (more material) in order to make use the material as efficient as possible.

Design References The chair design uses the output from topology optimisation in order to identify the regions which require more structural support (more material) in order to make use the material as efficient as possible.

3D Printed Chair

By Zaha Hadid Architects

Bone Chair

By Joris Laarman

The goal of this design is to design a relatively lightweight chair that made use of its geometry, detailing and manufacture to highlight and improve its performance. Printing in different densities allowed designers to optimise the performance of key structural areas, which are visualised as blue veins across the surface.

The chair design is based on the generative process of bones. When bones grow, areas not exposed to high stress develop less mass while sectors that bear more stress develop added mass for strength. The working principle of the chair is likewise.

1) Settings

Design domain prototype The chair model used as a massing prototype / Research / Design Method / Design Implementation / Experimentation / Fabrication /

Loads and support conditions settings Loads and supports used as input for topology optimisation 96

2) Topology Optimization Output

(1) 3D ISO Mesh

(2) 3D Mesh Results

(3) 3D Node Results

(4) 3D Cell Results

(4) Stress Lines

(4.1) Stress Lines 1

(4.2) Stress Lines 2

(4.3) Stress Lines 3

3) Output for Processing

(1) Initial stress lines

(2) Cleaned stress lines

(3) Cleaned stress lines and the input mesh which genterates the agents

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Chair Simulation Different chair simulations resulted from different parameters and settings. The overall geometry of the chair is simulated by using agents to follow stress lines.

Design Exploration 1

Design Exploration 2

Design Exploration 6

Design Exploration 5

Design Exploration 3

Design Exploration 7

Design Exploration 4

Design Exploration 8

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Vector Field Parameters: float attractorR1 =30; float attractorR2 =6;

Vector Field Parameters: float attractorR1 =6; float attractorR2 =4;

Agent Behavior Parameters: float maxSpeed = 0.2; alignment(); float alignmentRangeA = 2; float alignmentStrengthA = 0.006; followField(0.3);

Vector Field Parameters: float attractorR1 =10; float attractorR2 =6; Agent Behavior Parameters: float maxSpeed = 0.2; alignment(); float alignmentRangeA = 10; float alignmentStrengthA = 0.06; followField(0.3);

Agent Behavior Parameters: float maxSpeed = 0.2; alignment(); float alignmentRangeA = 5; float alignmentStrengthA = 0.8; followField(0.3);

Vector Field Parameters: float attractorR1 =20; float attractorR2 =6;

Perlin Noise: float n = noise(originalCenter.x* 0.1, originalCenter.y * 0.1, originalCenter.z * 0.1) *360; pNoiseField.rotateX(radians(n)); pNoiseField.rotateY(radians(n)); pNoiseField.rotateZ(radians(n));

Agent1 Behavior Parameters: float maxSpeed = 0.2; cohesion(); separation(); alignment(); followField(0.3); Agent2 Behavior Parameters: Attractrion to Agent1

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Chair Parameters Test Different agents density and voxel activation methods are tested in order to get the best chair design with the best material distribution, structural performance, and directionality.

Agents Density: 3 Voxel activation: trailPoints

Agents Density: 1.5 Voxel activation: trailPoints

Agents Density: 1.5 Voxel activation: trailPoints and stress lines

Agents Density: 1 Voxel activation: trailPoints and its neighbours

Agents Density: 1 Agents Density: 1 Agents Density: 1 Agents Density: 1 Voxel activation:count the trailPoints in each voxel. Voxel activation:1 trailPoints and make the seperate in Voxel activation: count the trailPoints in each voxel. Voxel activation: each trailPoints and its neighbours 2 a constant region

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Chair Design the voxelized geometry depends on the numbers and behaviors of the agents: their density, speed,velocity, etc.

As seen in these renders, the parameterbalance is found to achieve a continuous structure without losing the information from the agent behaviour

Transparency

Porousity

Directionality

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Chair Design The final chair shows the dynamic of behavior that is obtainable with this design method. The model shows the possibility of generating very rich and heterogenous lattice cells that is transformed from a uniform grid to the non-uniform one

Uniform Lattice Cell

HeterogenouscLattice Cell

Porousity

Transparency

Before Deformation

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After Deformation

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Wall Design Stress lines from topology optimization is applied as an input for differentiate voxel type, creating depth, and deform by following the direction of stress lines

Design Strategies

2) Differentiate voxel type Distance to stress lines determines the type of voxel

1) Input Stress lines from topology optimization

3) Creating Depth/Thickness The region close to stress lines has thicker layer of voxels to strenghthen the structural performance of the model

Wall Parameters test

4) Voxel Deformation The vertices of voxel close to stress lines will be deformed following the direction of stress lines, creating more material concentration at the region where stress lines are

Different parameters of voxel activation and the range of deformation provide different results and effects to the simulation. Our objective is to find the right parameter that gives interesting result, high potential for structure performance, and fabricatable.

if (dist>0 && dist<=3) type = 1; getClosestVoxels(8); if (dist>3 && dist<=5) type = 2; getClosestVoxels(3); if (dist>5) type = 3; getClosestVoxels(3);

if (dist>0 && dist<=5) type = 1; getClosestVoxels(8); if (dist>5 && dist<=8) type = 2; getClosestVoxels(3); if (dist>8) type = 3; getClosestVoxels(3);

float attractorR1 =20; float attractorR2 =8; float attractorRange = 10;

float attractorR1 =20; float attractorR2 =8; float attractorRange = 10;

if (dist>0 && dist<=3 type = 1; getClosestVoxels(8); if (dist>3 && dist<=5) type = 2; getClosestVoxels(6); if (dist>5) type = 3; getClosestVoxels(4);

if (dist>0 && dist<=3) type = 1; getClosestVoxels(8); if (dist>3 && dist<=5) type = 2; getClosestVoxels(4); if (dist>5) type = 3; getClosestVoxels(3);

float attractorR1 =20; float attractorR2 =8; float attractorRange = 10;

if (dist>0 && dist<=6) type = 1; getClosestVoxels(8); if (dist>6 && dist<=8) type = 2; getClosestVoxels(6); if (dist>8) type = 3; getClosestVoxels(3);

if (dist>0 && dist<=5) type = 1; getClosestVoxels(8); if (dist>5 && dist<=8) type = 2; getClosestVoxels(4); if (dist>8) type = 3; getClosestVoxels(3);

float attractorR1 =20; float attractorR2 =8; float attractorRange = 20;

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float attractorR1 =20; float attractorR2 =8; float attractorRange =10;

float attractorR1 =20; float attractorR2 =8; float attractorRange = 10;

if (dist>0 && dist<=3) type = 1; getClosestVoxels(8); if (dist>3 && dist<=5) type = 2; getClosestVoxels(2); if (dist>5) type = 3; getClosestVoxels(2);

if (dist>0 && dist<=5) type = 1; getClosestVoxels(8); if (dist>5 && dist<=8) type = 2; getClosestVoxels(6); if (dist>8) type = 3; getClosestVoxels(3);

float attractorR1 =20; float attractorR2 =8; float attractorRange =12;

float attractorR1 =20; float attractorR2 =8; float attractorRange =10;

The result of a wall from combining different toolpath, creating thickness/depth, and deforming the voxel following the stress lines.

Different depth/ thickness Creating thicker layer at the part closed to stress lines potentially create stronger structural performance for the model.

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Directionality

Transparency

The voxels are deformed following the vector of stress lines. This create directionality and material distribution to the region that needs to have denser material.

Lattice voxel generates different transparency to the model, creating lightweight structure with strong structural performance

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Spatial Pavilion Design The overall geometry of the spatial pavilion design comes from the method of topology optimization. The finite element model from topology optimization provides the geometry, as well as stress lines that are later used in the simulation process

Form Finding (Topology Optimization) / Research / Design Method / Design Implementation / Experimentation / Fabrication /

Stress Lines (Output from topology optimization) 114

Pavilion Details 115

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This model shows the possibilities of using topology optimization in the form-finding process and the stress lines to activate and deform the voxels. This strategy provides good overall geometry, but does not give interesting voxel behaviour compared to the other strategies

Space Simulation with Cell Deformation

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Space Simulation with Cell Deformation One of the attempts in simulating lattice cell structure in an architectural scale. This model is a result of agent-based modeling and the application of deformed lattice cells.

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Part 1 Compression of voxels

0.1 The range of deformation 2D Diagram

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COMPRESSION

0.9

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Space Simulation with Cell Deformation

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Part 1 Compression of voxels

0.1 The range of deformation 2D Diagram

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COMPRESSION

0.9

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3D Diagram

Deformation range Large

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

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Habitable wall developed from the flat wall model. This design attempts to show how the design method can generate a wall model that is functional in architectural scale 127

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Shell Pavilion Design The pavilion model is used as a prototype for topology optimization.

The output from topology optimization composes of stress lines, vector field, and stiffness value are used as an input for the simulation.

1. Design prototype Curved surface used as a prototype for a pavilion

Vertical load frocce

Wind force

2. Load and support settings Load and support settings are set as an input for topology optimization

Support Regions

3. Topology optimization output: Stress lines Stress lines generated from the method of topology optimization. These stress lines vary according to the load, support, and geometry settings

4. Topology optimization output: Quad Results vector field Vector field indicates the force direction of the geometry

5. Topology optimization output: Stiffness Visualization Stiffness color map shows the high and low stress region evaluated from the geometry, load, and support setting

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

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Pavilion Details 129

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(1) Shell points with stiffness values. The points with orange color shows that the structure with high stiffness

(4) Voxelization according to the shell points. Use the stiffness to control the thickness of the structure.

(2) The blue lines shows that the normal direction of each shellpoints which will be used to activate more voxels

(5) Change the voxel patterns according to the distance to the principle stress lines.

(3) The way to cull the stresslines depends on the density and voxel sizes.

(6) Deformation according to the principle stress lines.

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Pavilion Simulation

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Different Resolution This test shows how the resolution affects the overall design and the behaviour of voxel (combination, layering, and deformation)

Voxel resolution: 20cm

Voxel resolution: 15cm

Voxel resolution: 10cm

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Deformation Test Different deformation parameters are tested in order to find a good result that shows prominent deformation result

No Deformation

Deformation Iteration:1

Deformation Iteration:4 133

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/ Fabrication /

Fabrication Different from convertional 3D printing which print layer by layer, our team managed to build a special extruder and printed lattice spacial structure successfully. We adapt voxeliazition to wall and pavillion, which make those sculpture more stable and transparent. Comparing with traditional layer-by-layer printing way that only heating extruder and melting materials. Our printing also need to use cooling system to ensure that the filament can cool immediately when printing lattice structure without other supporting sturcture.

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TOOLPATH DESIGN RESEARCH The toolpath is really important for spatial lattice printing. It is the key to the success of printing results. One toolpath that can be printed completely, continuously and directly should be able to organise the whole structure of the physical model

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Three Types of Toolpath

Type 1

Type 2

Type 3

Printing Sequence Pattern Types Type 1

Printing Sequence Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Type 2

Type 3

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TOOLPATH COMBINATION The toolpath is really important for spatial lattice printing. It is the key to the success of printing results. One toolpath that can be printed completely, continuously and directly should be able to organise the whole structure of the physical model

Patterns

Connection between types

+

Type 1

Type 2

Type 2

Type 1

Type 2

Type 1

Type 1

Type 2

Type 2

Type 1

+

Type 3

Type 3

Type 2

Type 2

Type 3

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

Type 3

Type 2

Type 2

Type 3

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Perspective

Patterns

Transform

Perspective

+

Type 1

Type 1

Type 1

Type 1 Type 1

+

Type 3

Type 3

Type 1

Type 1

Type 3

Type 3

Type 1

Type 1

Type 3

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Toolpath design

2

5

×

1

3

4 2

5

√

1

2

3

×

1

3 2

4

1

√

Printing Constraint

Original Structure

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

Reinforced Structure

148

Toolpath Design

This computer simulation adopts the three types of toolpaths and connects these toolpaths in various combinations into one chunk. Those toolpaths can be arranged in different combination and various perspectives. When two voxels with the same anatomy are connected together, the toolpath will be changed fundamentally.

Toolpath Sections

Printing Sequence

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TOOLPATH COMBINATION

+

Type 1

+

Type 2

Type 3

Physical Model

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+

Type 1

Type 2

Physical Model

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HIGH-PRECISION PRINTING In order to achieve high-precision printing results, the motor and stopping time needs to be set properly according to the material behavior. Stopping the motor will stop the release of material which lets the material to harden before the nozzle moves to the next spot

waiting time 1 motor stops

waiting time : 1 with motor running

waiting time : 2 with motor running

waiting time 2 motor stops

Printing Speed: 5mm/second Waiting Time 1: 2 seconds Waiting Time 2: 1seconds

Printing Speed: 5mm/second Waiting Time 1: 4 seconds Waiting Time 2: 2seconds

Printing without stopping motor at the node

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Printing with motor stops at the node

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DEFORMATION SCALE Testing the scale of deformation is essential for the physical model printing because the size of extruder may be too big to print a very deformed lattice without collision. This study shows how the group calculate the rate of deformation that is suitable for printing

Type 3

Deformation Range

Direction

Top

25%

50%

75%

100%

25%

50%

75%

100%

25%

50%

75%

100%

25%

50%

75%

100%

Perspective

Top

Perspective

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Deformation Range

Direction

Front

25%

50%

75%

100%

25%

50%

75%

100%

25%

50%

75%

100%

25%

50%

75%

100%

25%

50%

75%

100%

25%

50%

75%

100%

Perspective

Top

Perspective

Top

Perspective

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Printing Sequence

Top surface

Diagonal

Wall

Basement

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Step 1 - Basement

Step 2 - Wall

Step 3 - Diagonal

Step 4 - Wall

Step 5 - Top surface

Step 6 - Diagonal

Step 7 - Wall

Step 8 - Top surface 157

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Arduino

Framwork of extruder system

Motor

Nozzle

Robot

Digital Output

Filament

End-Effector Design

Robotic Control System

Control system

End-effector

Cooling system

Heating system

Robotic End - Effector

Air Line Connector

PVC Pipe

Aluminium Disk

6mm Screw Gear Head Stepper Motor

3mm Screw

5mm Acrylic Aluminium Connector

Teflon Threaded rod

Nozzle Copper tube

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

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End Effector Design

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End-Effector Design

A

Diameter 2mm

/ Research / Design Method / Design Implementation / Experimentation / Fabrication /

Diameter 3mm

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Drill 9.5 Dia; tap M11

Section A-A 1.8mm Dia, 20mm Deep

4 holes 6mm Dia, 20mm Deep

Diameter 3.5mm

Diameter 3.5mm

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

End-Effector Design Extruding Angle

The maximum angle is 80 degrees, and the maximum voxel size is 30mm.

80째

The maximum angle is 70 degrees, and the maximum voxel size is 35mm.

70째

The maximum angle is 70 degrees, and the maximum voxel size is 25mm.

70째

80째

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The maximum angle is 80 degrees, and the maximum voxel size is 40mm.

Voxel Size

Extrudion Diameter

Voxel size: 30mm

Extrusion diameter: 2mm

Voxel size: 35mm

Extrusion diameter: 3mm

Voxel size: 25mm

Extrusion diameter: 3.5mm

Voxel size: 40mm

Extrusion diameter: 3.5mm

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Control System

1 Sensor

Tem

Tem

+

Heater System

-

Interface

5

Screen: - Temperature State - Heating State

1 Heater System

Arduino UNO 3 8 Reley Module

2 Motor Control System Arduino UNO 3 Big Easy Driver

3 Digital Out/In Put 8 High/Low Reley

4 Robotic End-Effector Nozzle Stepper Motor

5 Interface

LCD Screen

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b Ro

ic ot

En

d-

fe Ef

o ct

r Stepper Motor

4

mp↓

mp↑

+

-

2

Motor Control System

Hot ends

Digital Out/In Put

3

Digital Out/In Put

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Printing Test

Motor Speed: 300 Robot Speed: 5 Point stop time (second): 2

Motor Speed: 300 Robot Speed: 6 Point stop time (second): 2

Motor Speed: 300 Robot Speed: 8 Point stop time (second): 2

Motor Speed:400 Robot Speed: 8 Point stop time (second): 3

Motor Speed: 400 Robot Speed: 8 Point stop time (second): 4

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Motor Speed: 400 Robot Speed: 8 Point stop time (second): 3

Printing Jump Test Voxel size 5cm

Printing Deformed Lattice Test Voxel size 5cm

Perspective

Perspective

Top

Front

Motor Speed: 400 microseconds Robot Speed: 4seconds Waiting time: 5 seconds

Motor Speed: 350 microseconds Robot Speed: 4seconds Waiting time: 4 seconds

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Printing Test This model is used to test the printing limitations of a deformed model. The model is divided into four pieces, which the group decided to print only one piece that contains the most extreme deformation

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Printed Physical Model

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Model printed by 3D printer shows an intricate and dynamic behaviour of lattice cells with three types of toolpath combined and deformed

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Robotic Printing

Top Front

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Right Perspective

Printing Results

Perspective

Motor Speed: 400 microseconds Robot Speed: 8 seconds Waiting time: 3 seconds

Top

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Grasshopper Definition

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RC 1 MArch Architectural Design (B-Pro) The Bartlett School of Architecture, UCL

Modiform

The Bartlett School of Architecture RC1 Wonderlab / Architectural Design 2016-2017