The theories

Theory one – Cellular Automata

Origin of Cellular Automata

The cellular automata (CA) approach was introduced in the 1940s by John von Neumann and Stanislaw Ulam.
The determining properties of a CA are:
• A regular single or multi- dimensional lattice where
each cell has a discrete state.
• A dynamical behaviour, described by rules which
describe the state of a cell for the next time step, in
the neighbourhood of the cell.

Why Cellular Automata

Cellular Automata allows us to populate parts of the site automatically through a defined set of cell states. In the production of the AZCEG model, we use this to distribute the amenities within a specified location on the site. The amenities will be populated in response to the surrounding cell states – the typology types.

Theory two – Complex Adaptive Systems

Complex Adaptive Systems (CAS)

CA is based on complex adaptive systems where macro phenomena result from micro behaviour interactions among a heterogeneous set of interacting
cells. A complex adaptive system has many distributed, interacting parts with little obstruction to central control. Each rule participates in the influence of an outcome and the actions of other parts. CA utilises this understanding of complex adaptive systems to set rules for cells, which then interact with and respond to one another based on the rules governing the cell which, in turn, results in the behaviour of a larger system.

Theory three – Pattern Language

Pattern Language

Taking from Christopher Alexander’s Pattern Language, the implementation of different patterns at different scales and contexts, can enable minuscule adjustments at a micro scale to count towards significant changes at a macro scale. Taking from Dawes and Ostwald (2017), the theory informs a series of processes, that can be used in both computation and design, that fall under three categories: Conceptualisation, Development, and Implementation.

Application of Pattern Language

Using this in conjunction with cellular automata and circle packing, we can form our grid through focussing density at a point. The point will consist of a mix of amenities that cater for typologies serving either a healthcare, commercial, retail, leisure or civil purpose.

The point types will vary in the amenities included which can be input by the user at the starting point of the application’s use. The residential typologies will then be distributed with the option of either dense-sparse or sparse-dense, creating a cluster and ultimately determining accessibility within the ‘cluster’.

The cluster’s accessibility will be determined by the radial distance to these amenities either on foot, by bicycle or by motorised vehicle. This formation of clusters in their varying forms are what will act as points that will form a pattern across the site. The process of forming clusters and laying them out (circle packing), the process of filling out the site appropriately depending on proximity rules (CA).

Urban Metabolism

Urban Metabolism

Abel Wolman describes urban metabolism to be a process of exploring socio-political dimensions such as the governing of flows and production of spatial inequalities. ‘The term has expanded from its biological meaning to capture the metabolic processes by which cities transform materials and energy in order to sustain their functions’ (Bancheva, 2014)

The Hammarby Model

The Hammarby model is named after an ecological city district project in Sweden, aiming to provide housing for 25,000 people. The Hammarby model is particularly innovative as it loops and cascades resource flows. This is a closed cyclical urban metabolism system (wastes are recycled where possible).

Applying Urban Metabolism within A2ZCEG

In a similar manner we aim to apply the Hammarby Model to the Victoria North Site be optimising the use of renewable energy, waste and resource recycling. Renewable energy will be generated on-site via PV panels on typologies and potential hydro-power at the River Irk; surplus energy will be redirected. Accessibility measures encourage occupants to take more sustainable modes of transportation.