Isabella Chow 833256
Studio Air. Part B.
Tutor: Isabelle Jooste
B.1 Research Field - Biomimicry
“A practice of ‘virtual industrial esp researcher and developer on Earth - Göran Pohl and Werner Nachtigall
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pionage’ of the most experienced h.”
4 Criteria Design ^ Figure 1 Chitosan based structural member 3D-printed with the water-based fabrication platform. Image: Markus Kayser
Material Ecology, Biomimetics and the work of Neri Oxman
1. De Paola, Pasquale, ‘Form Follows Structure: Biomimetic Emergent Models of Architectural Production’, Offsite: Theory and practice of Architectural Production (2012), pp. 302-306, pg. 306 2. Pohl, Göran and Nachtigall, Werner Biomimetics for Architecture and Design (Stuttgart, Germany: Springer, 2015), pp. 1-3 3. ‘Mediated Matter: About’, Mediated Matter (Massachusetts: MIT Media Lab, 2018) <http://matter.media. mit.edu/about> [March 22 2018] 4. Mogas Soldevilaa, Laia, Duro Royoa, Jorge and Oxman, Neri, ‘FORM FOLLOWS FLOW: A Material-driven Computational Workflow For Digital Fabrication of Large-Scale Hierarchically Structured Objects’, in ACADIA 2015 – Computational Ecologies: Design in the Anthropocene, (Massachusetts: MIT, 2015), pp. 1-8 (pp. 1-4) 5. Mogas Soldevilaa, Laia and Oxman, Neri, ‘Water-based Engineering & Fabrication: Large-Scale Additive Manufacturing of Biomaterials’ in Materials Research Society MRS 2015 - Symposium NN - Adaptive Architecture and Programmable Matter: Next Generation Building Skins and Systems from Nano to Macro, (Massachusetts: MIT, 2015), pp. 1-8 (pp. 1-6)
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This approach to architecture goes beyond formal applications and the design of tangible structures, it can also be applied to fabrication systems and material development. The work of Neri Oxman and the Mediated Matter Group illustrates this broad consult of natural systems, learning from biological strategies and applying these learnt techniques to design3. Their work turned to an exploration of new additive fabrication methods for digital design. While computational design is increasingly focused towards sustainable solutions, digital fabrication methods lag behind in this domain4. 3D printing materials are characterised by plastics and other fuel-based composites; the Mediated Matter Group studied the role of water in the formation of natural materials to produce a water-based additive material system of digital fabrication5. Noted was the multifaceted role of water in natural materials - shape formation, chemical activation, sustenance requirement - and it’s ability to manipulate factors like material strength depending on region of the material (e.g. hard shells to flexible joints)5. Likewise the resulting additive fabrication system uses water based composites and biomaterials (chitosan, cellulose) to 3D print materials whose graded properties can be changed depending on regions (e.g. increased / decreased strength) and which are completely degradable in water.
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The relationship between architectural design genesis and biological systems dictating form and function in the natural is increasingly relevant. Evolution has culled the weak and impractical, leaving only the best informed solutions to biological problems. To adapt these solutions to architectural issues seems only reasonable, however it demands broad research of the systems at work. This requires more than just a superficial analysis resulting in similar looking forms. In the natural, beauty arises as a result of functionality, any adaption of biological systems to architecture must acknowledge this: “form must follow structure”1. For this reason the term ‘biomimicry’ is somewhat misleading as it suggests imitation of form. Rather it should emphasise the analysis of functioning biological principles and subsequent development of informed architectural systems, coined ‘biomimetics’2.
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B.2 Case
Aranda La Thyssen-B
< Figure 2 The Morning Seville, Spain
e Study 1.0
asch - The Morning Line Bornemisza Art Contemporary, 2008-2013
g Line commissioned by Thyssen-Bornemisza Art Contemporary and exhibited in n; Istanbul, Turkey; Vienna, Austria; Karlsruhe, Germany from 2008 to 2013.
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8 Criteria Design ^ Figure 3 The Morning Line commissioned by Thyssen-Bornemisza Art Contemporary and exhibited in Seville, Spain; Istanbul, Turkey; Vienna, Austria; Karlsruhe, Germany from 2008 to 2013.
Fractal Growth and Aggregation
Chaos out of order. Nature is chaotic in appearance, however this chaos is governed by rules, simple rules that form complex results through the shear scale of their repetition. Fractals are rules of patterning - whereby one geometry is scaled and repeated and this scaled geometry is then scaled by the same fixed ratio and repeated again, this process is repeated over and over again producing exponential growth and complex patterns in natural systems1. Lindenmayer system algorithms, mimicking the growth patterns of trees are examples of fractal growth creating optimal natural structures.
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1. Tingley, Kim, ‘Design for Living: The Hidden Nature of Fractals’, Live Science (January 24 2014) <https://www.livescience. com/42843-fractals-and-design.html> [March 24 2018] 2. ’The Morning Line’, Aranda \ Lasch <http://arandalasch.com/works/the-morning-line/> [March 23 2018]
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An ‘imagined ruin from the future’, The Morning Line by Aranda Lasch is a complex geometry thats composition can be adapted to its setting via the arrangement of its components, “the bits”2. It has no sole beginning or end, rather it is a network of “bits” accumulated through a fractal growth algorithm, whereby one polyhedral geometry is scaled and aggregated, scaled and aggregated2. Scaling is fixed but repeated more in some areas and less in others and continuous patterning of the surfaces is created, resulting in the complex random-looking arrangement.
^ Figure 4 The Morning Line - illustrating areas of differing fractal growth, surface patterning and branching stratergies to create complexity.
_Matrix 1.0
_Species 1
Truncated Tetrahedra
Add fractal tetrahedra
Segments increased n=4
_Species 2
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Orient and copy tetrahedra
Aggregate n = 6 alternate orient surface
Aggregate n = 26 forms helix structure
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Add branch to aggregation
Increase aggregate iterations to n = 8
Increase aggregate iterations to n = 18
_Species 4
Change input geometry to icosahedron and add branching Iterations n = 8
Change branching stratergy (different target surfaces)
Change branching stratergy (di ent target surfaces)
iffer-
Fractal scale decreased
Changed input geometry to add fractal component
Increase scaling factor / increase number of segments = 5
Changed input geometry to open polyhedra with 4 segments
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Fractal scale increased
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Changed target surface for orient
Decrease #no. iterations to 3 repetitions Change surface to aggregate
Increase number of branches Branch 1 n = 3 Branch 2 n = 2
Changed input geometry to add fractal components
Increase number of branches Branch 1 n = 2 Branch 2 n = 2 Change target surfaces
Delete original tetrahedra leaving only fractal elements
Decrease number of branches Branch 1 n =2 Branch 2 n = 1 Decrease number of aggregation iternations n = 12
_Python Script BROKEN DOWN import rhinoscriptsyntax as rs def allPts(srf): border = (rs.DuplicateSurfaceBorder (srf)) lines = rs.ExplodeCurves (border) centre = rs.SurfaceAreaCentroid (srf) allPts = [] allPts.append (centre[0]) for line in lines: pt = rs.CurveEndPoint (line) allPts.append (pt) return allPts First aggregate target surface to copy to
12 Orient new object
def aggregate(obj, pointList, count): source = [pointList[0], pointList[1], pointList[2]] target1 = [pointList[0], pointList[1], pointList[2]] target2 = [pointList[0], pointList[2], pointList[1]] if(count % 3 == 0): newObject = rs.OrientObject (obj, source, target2) else: newObject = rs.OrientObject (obj, source, target1)
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return newObject def recursiveAggregation(obj, gens, objList, count): allSrf = rs.ExplodePolysurfaces (obj)
Points on each surface - changes with input geometry
Branching - add copies
pointSet1 = allPts (allSrf[0]) pointSet2 = allPts (allSrf[1]) pointSet3 = allPts (allSrf[2]) pointSet4 = allPts (allSrf[3]) pointSet5 = allPts (allSrf[4]) pointSet6 = allPts (allSrf[5]) pointSet7 = allPts (allSrf[6]) if(count % 2 == 0): newObject = aggregate(obj, pointSet1, count) else: newObject = aggregate(obj, pointSet2, count) copy = rs.CopyObject (newObject) objList.append(copy) if(gens > 0): recursiveAggregation(newObject, gens-1, objList, count+1) return objList
Call output - recursive aggregation
allNewObjs = [] count = 0 a = recursiveAggregation(brep, iterations, allNewObjs, count)
Defining Species _Species 1 Fractal growth within a single geometry - truncated tetrahedron geometry altering polygon segments, radius scale and fractal scales _Species 2 Fixed aggregation algorithm created using Python scripting component in Grasshopper. Orientating geometries with set number of elements (iterations) and surface face for aggregation to occur on. _Species 3 Editing aggregation algorithm to incorporate branching and produce recursive aggregation.
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_Species 4 Changing input geometry to a more complex icosahedron with twenty faces available to aggregation and branching strategies.
Each condition to receive a score out of five; one being poor and five being exceptional. 1.0 Algorithmic control Amount of control over the algorithm to produce generated geometry; can the placement of a single element be altered if need be, was the form preconceived or predicted, is the outcome ordered chaos or just chaos? 2.0 Continuity How well the generated geometry can be defined by a single continuous curve; could the discrete elements become a single continuous geometry easily, is there an identifiable beginning and an end point or any at all? 3.0 Proximity of elements How close each individual element / geometry is to its adjacent elements; is there any overlapping, is there empty space or gaps between elements? 4.0 Complexity How well the produced geometry illustrates its aggregation strategy; is branching easily identifiable, is there a pattern being produced; can order be deciphered from the chaos? 5.0 Input geometry How effectively does the input geometry work with the definition; did the definition require altering to accommodate the new input geometry, how does the geometry change the resulting form?
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Selection Criteria and Speculation
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Algorithmic control Continuity Proximity of elements Complexity Input geometry
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Algorithmic control Continuity Proximity of elements Complexity Input geometry
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Algorithmic control Continuity Proximity of elements Complexity Input geometry
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Algorithmic control Continuity Proximity of elements Complexity Input geometry
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B.3 Case Study 2.0 Iwamoto Scott - MoMA / PS1 Reef Finalist entry in MoMA PS1 Young Architects Program, 2007
^ Figure 5 Iwamoto Scott MoMA / PS1 Reef visualisation - ‘Anemone Clouds’
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Iwamoto Scott MoMA / PS1 Reef
Iwamoto Scott’s MoMA / PS1 Reef is an attempt at creating an underwater atmosphere on land, ‘reef mounds’ provide seating while ‘anemone clouds’ hang overheard billowing in the wind. The design focuses on the combined affect on numerous discrete elements - each ‘cloud’ element differs from the adjacent however this is easily controlled in the parametric model. The depth of the cloud elements varies depending on their position on the input surface, altering levels of shade and the way each reacts to the wind. These elements are tensile rings of fabric and all hang from a timber grid - the entire structure is lightweight and mostly pre-fabricated for ease of construction on site1.
1. ’MoMA / PS1 Reef’, Iwamoto Scott <https://iwamotoscott.com/projects/moma-ps1-reef> [March 29 2018]
20 Criteria Design ^ Figure 6 Iwamoto Scott MoMA / PS1 Reef visualisation - ‘Anemone Clouds’
Reverse Engineering
_Step 1 Create surface from input curves
_Step 4 Create attractor points (closest point)
_Step 5 Remap closest point list and use as surface box height input
_Step 6 Create box morph using geometry generated to act in tension with Kangaroo physics simulation
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_Step 3 Create surface boxes [variables: height and vector direction]
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_Step 2 Divide surface [variables: U and V count]
Process Documentation
Surface
Input Curves
U Value count V Value count
Divide Surface and IsoTrim
_Surface Analysis
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Area
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Attractor Point #1 Attractor Point #2 _Attractor Points
Rectangle Circle
Loft
_Geometry with Kangaroo Tensile Simulation
WeaverBird Mesh Edges
Kangaroo Springs Force
Surface Box
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Remap Values
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New Domain
Closest Point
Bounding Box Kangaroo Physics Simulation
Output: Geometry
_Box Morph
Box Morph
Comparison Reverse Engineering - Similarities and Differences While the reverse engineered outcome looks quite similar to the original Iwamoto Scott MoMA PS1 Reef there are many differences outlined below:
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FRAMING STRUCTURE - The original MoMA PS1 Reef is made up of two main components, a timber framing structure and fabric ‘anemone clouds’ - the framing structure supports the clouds however the reverse engineered result was created from a box morph technique, hence there is no framework but rather a continuous surface above the elements.
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ANGLE OF CUT - MoMA PS1 Reef looks as though the ‘anemone clouds’ are cross sectioned at varying angles, almost like they have been the result of a boolean subtraction process. However in my reverse engineered result each element is cut planar on the xy axis. WIND - While the MoMA PS1 Reef displays a response to lateral wind loads, the reverse engineered result is completely static.
25 Criteria Design ^^ Figure 7 Image of reverse Iwamoto Scott MoMA / PS1 Reef engineered result ^ Figure 8 Iwamoto Scott MoMA / PS1 Reef model - â&#x20AC;&#x2DC;Anemone Cloudsâ&#x20AC;&#x2122;
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B.4 Technique - Development
_Matrix B
_Species 1
Increase z value of height vector
Increase domain of z value of height vector to incorporate negative and positive values
Increase U and V values of surfac mapping
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_Species 2
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Change input geometry Change input geometry
Change input geometry Decrease z value for height vec
_Species 3
Weaverbird mesh smoothing input box morph geometry
Weaverbird mesh smoothing input box morph geometry Increase U and V values
Weaverbird mesh smoothing in box morph geometry Move attractor points
ctor
nput
Decrease U and V values of surface mapping
Decrease U and V values of surface mapping
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Increase U values of surface mapping, leave V values
Change input geometry
Weaverbird mesh smoothing input box morph geometry Decrease domain size for z value of height vector
Change input geometry Increase U and V value Move attractor points
Weaverbird mesh smoothing input box morph geometry Add framework around weaverbird smoothed geometry
Change input geometry Decrease U and V value Move attractor points
Weaverbird mesh smoothing input box morph geometry Add framework around weaverbird smoothed geometry Increase z value of height vector
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ce
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Speculation Having developed the Iwamoto Scott ‘MoMA PS1 Reef’ reverse engineered definition and explored the possibilities of surface analysis and morphing geometries only differing surfaces I would now like to return to analyse systems of growth and the use of simple discrete elements to form complex geometries. While there is opportunity to explore discrete systems within the reverse engineered Iwamoto Scott ‘MoMA PS1 Reef’ definition I believe there is more room to understand and extend my knowledge of discrete systems through a further exploration of Case Study 1.0 the Aranda Lasch ‘Morning Line’ project. For the remaining portion of B.4 development phase I wish to experiment with different ways to aggregate parametrically in order to gain greater algorithmic control over resulting geometries.
_Matrix C
_Species 1 Altering number of tiling (aggregation) planes referenced, number of elements increases as number of planes availiable for aggregation increases
Referenced tiling planes n = 4 Bounding brep = box Iterations n = 3
Referenced tiling planes n = 7 Bounding brep = box Iterations n = 3
Referenced tiling planes n = 12 Bounding brep = box Iterations n = 3
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_Species 2
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Rotating tiling (aggregation) planes, was hoping to see patterns forming but there was no such patterns formed.
Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3 Number of planes rotated = 19 Rotation angle = 68 degrees
Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3 Number of planes rotated = 7 Rotation angle = 68 degrees
Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3 Number of planes rotated = 19 Rotation angle = alternating 45 degrees, 90 degrees
_Species 3 NEW INPUT GEOMETRY. Rotating tiling (aggregation) planes, new geometry has less faces and hence there is more control over the outcome, subtle patterns of aggregation forming.
Referenced tiling planes n = 5 Bounding brep = box Iterations n = 3 Number of planes rotated = 0
Referenced tiling planes n = 5 Bounding brep = box Iterations n = 3 Number of planes rotated = 5 Rotation angle = 90 degree
Referenced tiling planes n = 5 Bounding brep = box Iterations n = 3 Number of planes rotated = 5 Rotation angle = alternating 4 degrees, 90 degrees
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Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3
Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3 Number of planes rotated = 19 Rotation angle = inverse alternating 90 degrees, 45 degrees
5
5 45
Referenced tiling planes n = 8 These tiling planes are randomly chosen and not according to adjacent planes like previous iterations Bounding brep = box Iterations n = 3
Referenced tiling planes n = 5 Bounding brep = box Iterations n = 3 Number of planes rotated = 5 Rotation angle = inverse alternating 90 degrees, 45 degrees
Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3 Number of planes rotated = 19 Rotation angle = alternating 0 degrees, 90 degrees
Referenced tiling planes n = 5 Bounding brep = box Iterations n = 3 Number of planes rotated = 5 Rotation angle = inverse alternating 90 degrees, 45 degrees WITH EXCEPTION TOP face plane rotational angle decreased to 62 (decreasing this angle increases vertical aggregation of elements)
Referenced tiling planes n = 19 Bounding brep = box Iterations n = 3 Number of planes rotated = 19 Rotation angle = 90 degrees
Referenced tiling planes n = 5 Bounding brep = box Iterations n = 3 Number of planes rotated = 5 Rotation angle = inverse alternating 90 degrees, 45 degrees WITH EXCEPTION SIDE face plane rotational angle decreased to 62 (decreasing this angle increases diagonal and sideward aggregation of elements)
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Referenced tiling planes n = 8 These tiling planes are randomly chosen and not according to adjacent planes like previous iterations Bounding brep = box Iterations n = 3
_Matrix C
_Bounding Geometry
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Aggregation of polyline elements with the addition of notches allowing fabricatable geometries. Basic tri-branch input geometry used.
Iterations n = 3 Greater resemblance of tree branching structures
Iterations n = 8 As the aggregation keeps running density and overlapping increase towards the edges within the boudning geometry
Iterations n = 8 Aggregation takes the shap of the continuous bounding geometry
pe g
35 Criteria Design Iterations n = 18 Once the aggregating elements fill the bounding geometry (reach the boundary edges) the algorithm keeps running, increasing density of the elements within the boundary, density increases outwards from the starting element
Iterations n = 8
Iterations n = 20
-3
_Matrix C
-3
_Fields
-3 3
-3 6
6
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_Species 5
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Aggregation of polyline elements with the addition of notches allowing fabricatable geometries. Basic tri-branch input geometry used. Aggregation occurs according to boundaries set by the charges of fields, these fields can be visually represented within a bounding geometry (in this case a simple bounding box)
Iterations n = 40 Point charges = 3 and -3 and -3 on interior point Negative charge on interior point allows for the creation of a hollow aggregated structure
Iterations n = 40 Point charges = 6 and -3 and -3 on interior point Increased charge on exterior point increases the volume of possible aggregated form
Iterations n = 10 Point charges = 6 and -3 on interior point Fewer number of iterations ( renders the continuous bou ary fields unidentifiable
-3
6
n
(n) und-
-4
-4
-3
4
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4
-4
Iterations n = 40 Point charges = 6 and -3 on interior point The greater the number of iterations the better the bounding fields are visible
Iterations n = 23 Point charges = 4 and -3 and -4 Proximity and magnitude of point charges creates a merging of fields
Iterations n = 23 Point charges = 4 and -4 and -4 Proximity and magnitude of point charges creates a merging of fields
Defining Species _Species 1 Altering number of tiling (aggregation) planes referenced, number of elements increases as number of planes available for aggregation increases _Species 2 Rotating tiling (aggregation) planes, was hoping to see patterns forming but there was no such patterns formed. _Species 3 NEW INPUT GEOMETRY. Rotating tiling (aggregation) planes, new geometry has less faces and hence there is more control over the outcome, subtle patterns of aggregation forming.
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_Species 4 Aggregation of polyline elements with the addition of notches allowing fabricatable geometries. Basic tri-branch input geometry used.
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_Species 5 Aggregation of polyline elements with the addition of notches allowing fabricatable geometries. Basic tri-branch input geometry used. Aggregation occurs according to boundaries set by the charges of fields, these fields can be visually represented within a bounding geometry (in this case a simple bounding box)
Selection Criteria and Speculation - addition of condition 6.0 Each condition to receive a score out of five; one being poor and five being exceptional. 1.0 Algorithmic control Amount of control over the algorithm to produce generated geometry; can the placement of a single element be altered if need be, was the form preconceived or predicted, is the outcome ordered chaos or just chaos?
4.0 Complexity How well the produced geometry illustrates its aggregation strategy; is branching easily identifiable, is there a pattern being produced; can order be deciphered from the chaos? 5.0 Input geometry How effectively does the input geometry work with the definition; did the definition require altering to accommodate the new input geometry, how does the geometry change the resulting form? 6.0 Fabrication Is fabrication of the geometry possible or impossible? If impossible can adjustments be made to allow for the geometry to be fabricated, how will these adjustments alter the geometry? What fabrication technique/techniques are required? How complex will this process be?
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3.0 Proximity of elements How close each individual element / geometry is to its adjacent elements; is there any overlapping, is there empty space or gaps between elements?
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2.0 Continuity How well the generated geometry can be defined by a single continuous curve; could the discrete elements become a single continuous geometry easily, is there an identifiable beginning and an end point or any at all?
40 Criteria Design _Species 3 _Iteration 5
Algorithmic control Continuity Proximity of elements Complexity Input geometry Fabrication
41 Criteria Design _Species 4 _Iteration 3
Algorithmic control Continuity Proximity of elements Complexity Input geometry Fabrication
42 Criteria Design _Species 5 _Iteration 6
Algorithmic control Continuity Proximity of elements Complexity Input geometry Fabrication
43 Criteria Design _Species 5 _Iteration 4
Algorithmic control Continuity Proximity of elements Complexity Input geometry Fabrication
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_Figure 9 Recursive aggregation of simple elements - growth from 1 element to 7448 elements within the bounds of a continuo
ous geometry Criteria Design
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Using discrete systems to gesture continuous geometries.
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HOMOGENEOUS DISCRETE ELEMENTS
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ARTIFICIAL BRANCHING
CENTRAL GROWTH
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INCREASED DENSITY TOWARDS STARTING POINT
AGGREGATION IN CONTINUOUS SILHOUETTE IMPERFECT BOUNDARIES CREATE UNPREDICTABLE AND CHAOTIC GEOMETRIES THAT GESTURE THE CONTINUOUS FORM THEY ARE CONFINED WITHIN
B.5 Prototypes MATERIAL CHOICE: 3MM MDF FABRICATION CHOICE: LASER CUTTING JOINTS: NOTCHES with non toxic adhesive
TWO THINGS TO KEEP IN MIND: 1. STRENGTH - each flying fox weighs up to 700 grams, these are large animals and the structure must support not one but many. 2. FLEXIBILITY - flying foxes are airborne animals, collisions are likely to occur often, the structure must not be too ridgid that it will snap with small amounts of lateral force.
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SUCCESS OF PROTOTYPE: While laser cutting proved an appropriate subtractive method of fabrication for the chosen xy oriented geometry, there were many issues with the prototype and its construction:
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1.0 JOINTS - notches were cut too wide for the 3MM thick material and so were useless in stabalising and holding elements together, therefore glue was used to bond the MDF in place, this was a fiddly process and not ideal.
2.0 LENGTH OF â&#x20AC;&#x2DC;BRANCHESâ&#x20AC;&#x2122; - the elongated branches created an element of fragility to the prototype, theres was quite a lot of flexibility due to these longer elements which while a positive in terms of collision resistance, a negative in terms of strength. This could also be to do with the width of branches, testing different width / height combinations is a wise step to clarifying this problem.
3.0 SPARSITY - will this prototype is only a portion of the entire structure it seems quite sparse and there are large gaps of free space for the flying foxes to become trapped in. Would an increase in the number of notches or branches change this sparsity and create a denser volume?
49 Criteria Design ^^ Figure 9 Close up of joint - intersecting notches ^ Figure 10 Aggregation 1:1 scale laser cut prototype
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B.6 Proposal - Synthetic Physics
^ Figure 11 Pre-roosting vs Post-roosting folliage patterns
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52 Criteria Design ^ Figure 12 Grey headed Flying Fox - a threatened species in Victoria
The Client - Identifying the problem The Grey Headed Flying Fox is a native species to Southern Victoria, currently it is listed as threatened however there is a large population in the Melbourne metropolitan area, peaking at 30 000 animals in 20031. Morphologically they are large animals, with wing spans reaching up to 1m and heights of roughly 250mm for this reason current bat box measures are completely unreasonable2. They populate dense tree canopies and vegetation of native Eucalyptus, Melaleuca and Banskia trees in large roosts of 5000 plus individuals3. Nocturnal, they roost in large trees during the day and awake at night to search for food. Grey Headed Flying Fox are also quite heat dependent animals and prefer to be higher up in trees, though generally no higher than 200m, in order to maximise on solar radiation. It is for this reason also that they migrate North to warmer climates during the cooler Southern winters3. Moreover in recent years they have been migrating increasingly towards metropolitan areas in search of warmth.
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While implementations of the management plan may address problems with the health of surrounding vegetation, the problem remains however - the roosting habits of flying fox in the area are still causing damage and premature death of roosting trees.
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In the early 1980’s a small camp of Grey Headed Flying foxes established a roost in the Royal Botanic Gardens of Melbourne, within 20 years this camp had grown astronomically to approximately 30 000 individuals and greatly threatened the health of surrounding flora, particularly large roosting trees1. The size and number of flying foxes and their preference to roost in large camps puts substantial stress on roosting trees, inevitably causing a loss of foliage and sometimes resulting in the falling of large branches and death of roosting trees. In 2003, the camp was relocated to Yarra Bend Park and a management plan for the sustainment of the area was produced1.
Pre- roost foliage
Post- roost foliage ^ Figure 13 Grey headed flying fox prefer higher tree canopy however this results in declining foliage health and increased stress to roosting trees. The above diagram graphically depicts canopy coverage before and after roosting. 1. Victorian State Government: Department of Sustainability and Environment, ‘Yarra Bend Flying Fox Campsite: Review of the Management Plan’ (Victorian State Government, 2009), pp. 4-6. 2. NSW National Parks and Wildlife Service, ‘Grey Headed Flying Fox’, NSW National Parks and Wildlife Service <http://www.nationalparks.nsw.gov. au/plants-and-animals/grey-headed-flying-fox> [Accessed 23 March 2018] 3. Encyclopedia of Life, ‘Grey Headed Flying Fox’, Encyclopedia of Life <http://eol.org/pages/327288/details> [Accessed 23 March 2018]
Synthetic branching via aggregation lightweight, modular roosting structures
The Proposal.
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Interesting in this case is the almost parasitic relationship between the Grey Headed Flying Fox and its host, the tree. While the tree provides the flying fox with a habitat, the flying fox is severely detrimental to the health of the tree. Furthermore once the tree is no longer useful to the flying fox, that is it is dead or branchless due to stress, the flying fox will move on to another tree, just as a parasite would move on to its next host. In this situation the flying fox can be labeled self destructive, as it is detrimental to its own habitat.
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Our solution creates an alternative habitat for the flying fox - a modular agglomeration of â&#x20AC;&#x2DC;synthetic branchesâ&#x20AC;&#x2122; for roosting flying fox camps. The formation uses systems of recursive aggregation, discrete elements aggregate within the confines of a continuous field to create hollow (lightweight) structures. These structures, made of lightweight timber (namely plywood or MDF) can vary in scale depending on the size / bearing capacity of the tree and magnitude of flying fox camps. Their modularity allows them to be constructed on site or pre-fabricated and easily transported to site.
55 Criteria Design ^ Figure 14 Synthetic branching structures - made from aggregation of homogeneous discrete elements - can vary in scale according to roosting demands
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57 Criteria Design ^ Figure 15 Synthetic branching structures to be suspended from healthy trees as synthetic roosting habitats
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B.7 Learning Outcomes
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The past few weeks completing Part B have be extremely helpful in terms of improving my Grasshopper skills and gaining a deeper understanding of the way parametric modeling works, albeit frustrating at times. I feel increasingly confident in creating my own definitions and am slowly gaining more control over the definitions we are currently experimenting with. In terms of the design for our group assignment I believe we know have a driving theme of aggregation and the use of discrete elements to create synthetic habitats for our client, the flying fox. However there is much to improve and explore, the passing critique was great help in distilling what exactly it is we should aim to improve: complexity of the discrete element (from polyline geometry to notch placement and number of branches) and fabrication / assembly strategy (how can we reduce the number of elements or create a streamline simple construction without destroying the structures complexity or effectiveness). To do this I believe the fabrication of numerous and differing prototypes is essential.
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B.8 Appendix - Algorithmic Sketches
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^ Biothing pavillion tu Using fields and grap
utorial ph mapping components to produce linear outcomes
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64 Criteria Design ^ Particle trajectories Using anemone and fields to map the path of particles over a mesh
65 Criteria Design ^ Recursive Aggregation Using Fox plugin to aggregate a simple geometry in a continuous boundary
References De Paola, Pasquale, ‘Form Follows Structure: Biomimetic Emergent Models of Architectural Production’, Offsite: Theory and practice of Architectural Production (2012), pp. 302-306, pg. 306 Encyclopedia of Life, ‘Grey Headed Flying Fox’, Encyclopedia of Life <http://eol.org/pages/327288/details> [Accessed 23 March 2018] Pohl, Göran and Nachtigall, Werner Biomimetics for Architecture and Design (Stuttgart, Germany: Springer, 2015), pp. 1-3 ‘Mediated Matter: About’, Mediated Matter (Massachusetts: MIT Media Lab, 2018) <http://matter. media.mit.edu/about> [March 22 2018] ’MoMA / PS1 Reef’, Iwamoto Scott <https://iwamotoscott.com/projects/moma-ps1-reef> [March 29 2018] Mogas Soldevilaa, Laia, Duro Royoa, Jorge and Oxman, Neri, ‘FORM FOLLOWS FLOW: A Material-driven Computational Workflow For Digital Fabrication of Large-Scale Hierarchically Structured Objects’, in ACADIA 2015 – Computational Ecologies: Design in the Anthropocene, (Massachusetts: MIT, 2015), pp. 1-8 (pp. 1-4) 66
Mogas Soldevilaa, Laia and Oxman, Neri, ‘Water-based Engineering & Fabrication: Large-Scale Additive Manufacturing of Biomaterials’ in Materials Research Society MRS 2015 - Symposium NN - Adaptive Architecture and Programmable Matter: Next Generation Building Skins and Systems from Nano to Macro, (Massachusetts: MIT, 2015), pp. 1-8 (pp. 1-6)
Criteria Design
‘The Morning Line’, Aranda \ Lasch <http://arandalasch.com/works/the-morning-line/> [March 23 2018] Tingley, Kim, ‘Design for Living: The Hidden Nature of Fractals’, Live Science (January 24 2014) <https://www.livescience.com/42843-fractals-and-design.html> [March 24 2018] Victorian State Government: Department of Sustainability and Environment, ‘Yarra Bend Flying Fox Campsite: Review of the Management Plan’ (Victorian State Government, 2009), pp. 4-6. NSW National Parks and Wildlife Service, ‘Grey Headed Flying Fox’, NSW National Parks and Wildlife Service <http://www.nationalparks.nsw.gov.au/plants-and-animals/grey-headed-flyingfox> [Accessed 23 March 2018]
Image Credits Figure 1 Chitosan based structural member 3D-printed with the water-based fabrication platform. Image: Markus Kayser Figure 2 The Morning Line commissioned by Thyssen-Bornemisza Art Contemporary and exhibited in Seville, Spain; Istanbul, Turkey; Vienna, Austria; Karlsruhe, Germany from 2008 to 2013. <http:// arandalasch.com/works/the-morning-line/> Figure 3 The Morning Line commissioned by Thyssen-Bornemisza Art Contemporary and exhibited in Seville, Spain; Istanbul, Turkey; Vienna, Austria; Karlsruhe, Germany from 2008 to 2013. <http:// arandalasch.com/works/the-morning-line/>
Figure 5 Iwamoto Scott MoMA / PS1 Reef visualisation - ‘Anemone Clouds’ <https://iwamotoscott.com>
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Figure 4 The Morning Line - illustrating areas of differing fractal growth, surface patterning and branching stratergies to create complexity. <http://arandalasch.com/works/the-morning-line/>
Figure 8 Iwamoto Scott MoMA / PS1 Reef model - ‘Anemone Clouds’ <https://iwamotoscott.com> Figure 12 Grey headed Flying Fox - a threatened species in Victoria <http://www.nationalparks.nsw.gov. au/plants-and-animals/grey-headed-flying-fox>
Criteria Design
Figure 6 Iwamoto Scott MoMA / PS1 Reef visualisation - ‘Anemone Clouds’ <https://iwamotoscott.com>