Design Space Exploration
2018/2019, Semester 2
School of Design and Environment (Architecture)
Modular Credits: 4
You will gain an understanding of design space exploration as a paradigm for design and the computational support of the design process. You will gain insight into
the characteristics of the design space and its structure.
You will gain some familiarity with the computational techniques of algorithmic design, including rule-based generation, and with
parametric/associative modelling. You will be able to apply one of these computational techniques
to the definition and investigation of a family or language of designs.
There are no specific prerequisites for this module, other than some affinity with design, some understanding of geometric modelling and, preferably, some famility with CAD modelling.
Fundamental notions of design space exploration and related topics will be transferred through lectures and discussions.
Computational skills of algorithmic design and parametric/associative modelling will be developed through tutorials and assignments.
The application of these skills to (architectural) design and reflection on the theoretic notions will come together in a (small) project.
Non-parametric spatial search
Associative-parametric spatial search
Non-parametric spatial generation
Languages of design
Associative-parametric spatial generation
Computational design has grown in importance and is fundamentally changing the nature of the design process in architectural practice. This module focuses on the ability to explore alternative design solutions as a means to inform the design and decision-making process. Without computational means, it is generally infeasible to consider more than a few design alternatives, even if the design solution space is uncountably large. Design space exploration is the idea that computers can be used to help designers by representing many designs, organizing them in a network structure that forms the space, and by assisting designers to explore this space: that is, to make new designs and to move among previously discovered designs in the network. Using techniques such as parametric/associative modelling, rule-based generation and more general algorithmic design generation allows defining and investigating a family or language of designs. Besides investigating one or more such techniques, we will also investigate the main characteristics of the design space and its structure.
The lecture topics will cover some of the following aspects related to design space exploration:
- computational structures and techniques to support design space exploration
- parametric/associative modelling
- rule-based/rewriting systems
- grammatical expressions of languages of designs
- algorithmic design and scripting
Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week