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ONDŘEJ POKOJ WORKSHOP WITH SHOTA TSIKOLIA STUDIO A3 PROF. AK.ARCH. IMRICH VAŠKO MGA. MARTIN GSANDTNER M.SC. AAAD

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METABOLIMS 2.0 Shota Tsikolia The new understanding of the architecture as an open dynamic system follows the similar change of approach in other subjects, particularly natural sciences. Classical reduction-ist approach of the modern science has faced its limitations. The development in the fields of biology and studies of the living matter showed the necessity of the system thinking. Deductive methods and the attention to the isolated parts are not applicable nor to the biology neither to architecture, as no living matter can exist isolated of its environment. Architecture and biologi-cal organism can be described as a complex system of relations and interactions. The transition from reductionism to the system thinking is related to the term “emergency�. Emergency rep-resents a spontaneous appearance of new macroscopic qualities and complex structures, which cannot be simply deduced out of the qualities of its inner microscopic parts.1 Emergent system is a system, which contains many simple parts, behaving according to a simple rules, but which in result create complex patterns, which are more than a sum of the inner parts. It is relatively simple to simulate an emergent system, yet very challenging to predict its development. A part of the emergent system is often a system of positive and negative feedbacks, which regulate its behavior.

An application of the emergent systems in architecture presents an ultimate change of paradigm. The design of the emergent architecture is a design of its inner processes, behaviors, feedback mechanisms, therefore it is complicated to predict the exact shape of the designed structure. Emergent architecture cannot be properly represented in a notational way, therefore it is not defined by an elevation, a plan or a cross-section, but by rules and behaviors. The ap-plicable analogies include not a traditional architecture, but more often structure encountered in nature. Bird nests as well as nests of the social insects are based on the set of limited and simple behaviors, but can achieve high ranges of complexity.2 The resulting object is exceeding the sum of its inner components. Emergent architecture is unpredictable, yet variable, redun-dant yet adaptable, its advantages come out of its disadvantages.

Dynamic, alive, ever-changing, evolving, biological architecture can be traced to the utopian projects of sixties, the examples of those are Archigram, Superstudio or Cedric Price. It was developed even further in the projects of Japanese Metabolist architects. Over-popu-lated cities, mountainous terrain and a radioactive wasteland were the testing ground for the experiments with this new dynamic architecture.3 Bio-inspired structures speculated about the new utopia on the ground of apocalypse. However the technical equipment of the time limited the use of biological inspiration to a level of metaphor.

New technologies, tools, fabrication methods, material studies and computational sources provide an opportunity to reinvent and redefine metabolism in the paradigm of the emergent architecture. The fourth industrial revolution means the transition from the auto-mated robotics to the intelligent cyber-physical space.4 Metabolism 2.0 tests new utopia of self-regulation in the contemporary globalized apocalypse.

1 John H. Holland, Emergence: from Chaos to Order 2 Scott Camazine, Self-organisation in biological systems 3 Rem Koolhaas, Hans Ulrich Obrist, Project Japan 4 Achim Menges, The New Cyber-Physical Making in Architecture

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ARTHROPOD EXOSKELETON

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FIBROUS COMPOSITES

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FIBROUS ASSEMBLAGES

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SWARM AGENT BEHAVIOR

SEPARATION

FOLLOW BAIT AGENT

COHESION

FOLLOW CURVE

ALIGNMENT

FOLLOW MESH

STIGMERGY

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2D SWARM SYSTEMS SEPARATE_0.0 / 50.0 COHESION_0.0014 / 50.0 ALIGN_0.0438 / 50.0 ATTRACTOR_0A.0042 / 100.0

SEPARATE_2.0 / 50.0 COHESION_0.0014 / 50.0 COHESION_0.0014 / 50.0 ALIGN_0.0438 / 50.0

SEPARATE_4.0 / 50.0 COHESION_0.0014 / 50.0 ALIGN_0.0438 / 50.0 ATTRACTOR_0.0042 / 100.0

SEPARATE_2.0 / 50.0 COHESION_0.0 / 50.0 ALIGN_0.0438 / 50.0 ATTRACTOR_0.0042 / 100.0

SEPARATE_2.0 / 50.0 COHESION_0.003 / 50.0 ALIGN_0.0438 / 50.0 ATTRACTOR_0.0042 / 100.0

SEPARATE_2.0 / 50.0 COHESION_0.0015 / 50.0 ALIGN_0.0 / 50.0 ATTRACTOR_0.0042 / 100.0

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SEPARATE_2.0 / 50.0 COHESION_0.0015 / 50.0 ALIGN_0.1 / 50.0 ATTRACTOR_0.0042 / 100.0

SEPARATE_2.0 / 50.0 COHESION_0.0015 / 50.0 ALIGN_0.05 / 50.0 ATTRACTOR_0.0 / 100.0

SEPARATE_2.0 / 50.0 COHESION_0.0015 / 50.0 ALIGN_0.05 / 50.0 ATTRACTOR_0.0122 / 100.0

SEPARATE_2.0 / 10.0 COHESION_0.0015 / 10.0 ALIGN_0.05 / 10.0 ATTRACTOR_0.0046 / 100.0

SEPARATE_2.0 / 100.0 COHESION_0.0015 / 100.0 ALIGN_0.05 / 100.0 ATTRACTOR_0.0046 / 100.0

SEPARATE_2.0 / 25.0 COHESION_0.0015 / 50.0 ALIGN_0.05 / 85.0 ATTRACTOR_0.0046 / 246.0

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3D SWARM SYSTEMS

AXONOMETRY

PLAN

ELEVATION

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CURVE DISTRIBUTION RHOMBUS

PARABOLA

INTERPOLATE

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MESH GENERATING QUAD SUBDIVISION

FRAME SUBDIVISION

CURVE PIPES

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MESH SUBDIVISION

QUAD SUBDIVISION WITH ATTRACTOR

TUBULAR, LINEAR AND QUAD SUBDIVISION WITH ATTRACTOR

TUBULAR AND CATMULL-CLARK SUBDIVISION

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TUBULAR, LINEAR AND QUAD SUBDIVISION WITH ATTRACTOR

TUBULAR, LINEAR AND QUAD SUBDIVISION WITH ATTRACTOR ON FIBERS

FRACTAL QUAD SUBDIVISION

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PROTOTYPE

VIRTUAL MODEL

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PHYSICAL MOCKUP

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ONDŘEJ POKOJ 2016