Computational Morphogenesis of City Tissues

Farzaneh, Ali (2017). Computational Morphogenesis of City Tissues. PhD thesis The Open University.



Scientific discoveries of the 20th century had a profound impact not only on the study of the natural sciences but disciplines worldwide. The studies were rooted in understanding the complex process of organisation, development and evolution in natural systems before attempting to emulate the behaviours in artificial systems, leading to the emergence of new disciplines such as systems theory, complexity science, genetics, developmental and evolutionary biology. The discoveries had a profound impact in understanding the nature of cities as they develop over time. Once considered top-down models in equilibrium, the dynamic qualities of cities could be explained through the study of dynamic complex systems, exhibiting non-deterministic characteristics that over time emerge as organised structures. These characteristics are not exclusive to cities alone; they are inherent to all complex systems.

The understanding of cities as complex systems has stimulated a body of research through mathematical and scientific modelling in understanding the behaviour of cities over time. The studies have been strongly focused on the analytical performance of city morphologies and less on the relational qualities of how systems interact to produce functioning spatial configurations. With the rapid rate of urbanisation and the emergence of new cities around the world, the approach to the design of cities remains rooted in static, top-down models. The implications of such models have led to high energy consumption, lack of integration and poor performance. It is a contradiction to consider cities as complex systems but design them as simple systems.

The thesis explores principles of complex systems through the study of biological morphogenesis (the formation and development of organisms over time) for their implementation in formalising a design model for the formation, development and evolution of cities. The central contribution of the thesis lies in the computational modelling of cities in three main areas. The first is the co-evolution of networks and block systems towards the generation of differentiated spatial morphologies. Network systems are generated by coupling multi-agent systems and branching systems from the mathematics of natural systems, and the block systems are generated through procedural subdivision and volumetric modelling. The process involves substantial computational coding and the integration of knowledge from outside disciplines including biology, genetics, complexity theory and mathematics.

The second is the development of a unified computational model combining morphological, topological and analytical modelling. The integration of the models is contingent on the writing of classes including graph theory, centrality measures and environmental calculations - all classes were written in C#. The third area is the evolutionary modelling of urban systems. The process utilised the open-source evolutionary solver Octopus in evolving solutions. The advantage lay in the populace-based nature of the model in generating differentiated phenotypes - or geometries - as a response to multiple-objectives.

The model has been designed to enable the integration of systems of different types. Analytical data can be used as input to influence the model on the types of decisions it can make. The model has also been designed to enable the exploration of multiple design objectives at varying spatial and time scales. A significant part of the design model takes advantage of open source software including the open source language C#. The software have been extensively modified by hard coding. The model is mutable so that others may add new classes and procedures in the future.

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