The main aim of this course is the exploration of systems of emergence as a design strategy for urban design. Instead of using tools of composition we will use tools of behaviour in order to scrutinize the selforganization of entities within an urban scheme. Thus creating patterns of materialization, densification and voids, striving for minimal energy consumption in correlation with the topography of the site and the various constraints applied to the structure. The constraints, the rules applied to the design, create variations in the resulting condition.
Complex populations
All of the above phenomena can be observed in organic systems of various levels, from very primitive lifeforms to higher level entities, as well as in anorganic entities. In this case intensive forces create emergent behavior such as hurricans or patterns formed in sand by waves crashing on the beach, and thus creating a constant flow of infinetly different patterns. Emergent properties can also be defined and discribed by stochastic(2) systems, as for example the behaviour of gas under pressure. The example of gas under pressure shows that the individual molecules are moving in deterministic paths, but that the paths of a population of molecules is computationaly, and practically, unpredictable. A huge population of molecules will behave in stochastic characteristics; filling the container, striving for equal pressure, diffusing along concentration gradients and so on. All of this behaviours can be tagged as emergent properties of a system.
stochastic behaviour within an atmospheric cloudfield
(www.met.rdg.ac.uk/ clouds/research.html)
Propable Cities
Why is this important? Genetic Algorithms, Neural Networks and artificial intelligence, all of this fields rely on stochastics in order to solve problems by using probabilistic methods. In Architecture this notion can lead us to novel approaches where the notion is that a problem itself may be stochastic, as in planning under uncertainty, resulting in emergent urban conditions.
Branching
Evolutionary algorithm creating a branching condition in 2D, created with Mathematica
Emergent structures are patterns not created by a single event or rule. There is nothing that commands the system to form a pattern, but instead the interactions of each part to its immediate surroundings causes a complex process which leads to order. One might conclude that emergent structures are more than the sum of their parts because the emergent order will not arise if the various parts are simply coexisting; the interaction of these parts is central. Emergent structures can be found in many natural phenomena, from the physical to the biological domain. For example, the shape of weather phenomena such as hurricanes are emergent structures.
It is useful to distinguish three forms of emergence structures. First-order emergence structures occurs as a result of shape interactions (for example, hydrogen bonds in water molecules lead to surface tension). Second-order emergence structures involves shape interactions played out sequentially over time (for example, changing atmospheric conditions as a snowflake falls to the ground build upon and alter its form). Finally, third-order emergence structures is a consequence of shape, time, and heritable instructions. For example, an organism's genetic code sets boundary conditions on the interaction of biological systems in space and time.
Algorithmic Botany: Branching structure in 3D
Raybranch288
For the creation of urban textures we will rely on the use of third-order emergence structures. The students will follow a set of rules that will create a complex entity evolving in four dimensions.
Rules:
Extensive vs Intensive (3)
Gradients
Stratification
Topology
Viscosity
This five issues will cover, in varying combinations of three, the student's projects and the scrutiny of the issue of emergence and complexity. The analysis of complex systems that are sensitive to its initial conditions differs from the issue of chaotic systems, as clearly stated by Colander(4) the study of complexity is the opposite of the study of chaos. Complexity is about how a huge number of extremely complicated and dynamic set of relationships can generate some simple behavioural patterns, whereas chaotic behaviour, in the sense of deterministic chaos, is the result of a relatively small number of non-linear interactions (Cilliers, 1998).
Complex systems may exhibit behaviors that are emergent, which is to say that while the results may be deterministic, they may have properties that can only be studied at a higher level. For example, the termites in a mound have physiology, biochemistry and biological development that are at one level of analysis, but their social behavior and mound building is a property that emerges from the collection of termites and needs to be analysed at a different level.
The rules will be applied in a twofold process:
First the creation of a material behaviour based model.
This models will explore the behavior of one material (plaster) in different levels of viscosity on a large scale model, bearing specific constraints eleborated by the students following the rules above (stratification, connectivity ea.) the results are shaped by various intensive forces (form in combination with gravity, flow forces, varying viscosity, friction..) The matter of emergence as a system for the generation of advanced behaviour in an urban texture.
Selforganization4
Analogue modeling of selforganizational patterns ©SPAN2006
The result of this models are further scrutinized by translating the selforganizational qualities into a machinic language. The analysis of the analogue model serves as a guideline for the development of digital design tactics. The models are moved into a machinic environment, wether this is by manual measurement, in an extensive process, or other measuring methods is up to the student. The importance of this step lies in the abbility of the student to interpret the intensive process applied to the first model in order to understand the potentials for an urban pattern (he density of the scaffold, variations in density and also behavioral densities). It is by no mean necessary to translate the analogue model in a literal way, but more important to understand the conceptual forces driving form, program, growth of urban patterns, textures, porosities, chromatics, gradients, and scale.
One of the main points withim this exploration will be the scrutiny of the models in terms of performance as an urban condition.
Pavilion2213
TopMod Models exploring various degrees of porosity (maxwellrender).©SPAN2006
In a further process the students have to find their own sets of rules based on the observations and conclusions from the physical model, this rules are the base for the projects development into a synthetic ecology by the use of a topological mesh modeling software. The problem of material behaviour and selforganization is interweaved with the problem of Topology and Selfconnectivity, thus the use of TopMod as a potential tool for the examination of the problem. The Software faccilitates the creation of digitally fabricated models that will buid one part of the final presentation.
Por6
3D printed model of one porous exploration. ©SPAN2006
The students are supposed to work an a single site in a communal effort. The site is divided among the students in order to create variaty within the site, constrains in form of the neccesary connectivity between the various projects have to be elaborated by the students.
Schedule:
1: Analogue Model, based on chickenwire and plaster, students have to follow varying agendas. The model has to measure a minimum of 1m x 1m
2: Translation of the model into TopMod & Maya
3: Abstract machines: explanatory maps and plans of the concepts and observation results out of both the analogue and the digital model.
In 1:500 scale.
4: 3D printed model of crucial points of the design, depicting the discovered framework based on the rules (Extensive vs Intensive, Stratification, Connectivity, etc) The models have to be nested within a milled base of the site.
5: Two A4 pages minimum TxT explaining the conceptual background as well as the exploration in terms of performance within an urban texture.
6: For the final presentation we will rely on a strict basic graphic and model representation for everyone. I.e.: Layout, font, model scales…
Acompaining workshops & lectures:
1: Introduction into TopMod
2: Lecture on Machine Learning
3: Troubleshooting in Zprint
Reading List for Students:
D´Arcy Thompson: On Growth and Form
Stephen Hyde: The Language of Shape
Ernst Haeckl: Artforms in Nature
Jaap A. Kaandorp: The Algorithmic Beauty of Seaweeds, Sponges and Corals
Przemyslaw Prusinkiewicz: The Algorithmic Beauty of Plants (The Virtual Laboratory)
Notes:
1: Goldstein, Jeffrey (1999): "Emergence as a Construct: History and Issues", Emergence: Complexity and Organization 1: 49-72
2: Stochastic, from the Greek word “Stochos” (Aim, Guess, means of, relating to) is characterised by conjecture and randomness. A stochastic process is one whose behaviour is non-deterministic in that a state does not fully determine its next state.
3: See also the paper “The machinic phylum” by Manuel de Landa, as well as :Manuel DeLanda & Peter Lamborn Wilson , 'Cities and Theories of Self Organization'
Manuel DeLanda: ‘Deleuze and the Use of the Genetic Algorithm in Architecture’
4: Colander, D. (2000): The Complexity Vision and the Teaching of Economics, E. Elgar, Northampton, MA.
