This paper investigates ways in which weathering-related site conditions can be allowed to inform the design process in order to improve a building's geometry and performance. Providing a building design with the capacity to remember past experiences and anticipate future events can provide substantial gains to the architectural configuration and engineering of a timber façade. A new theory of architecture is outlined based on recent “teleodynamic” theories—a hypothesis about the way far-from-equilibrium systems interact and combine to produce emergent patterns. The proposed explanation considers nested levels of thermodynamic systems applied to an architectural context: “homeodynamic” operations that involve equilibration and dissipation of constraint combine to produce self-organising “morphodynamic” procedures that amplify and regularise site-specific constraining data streams. A teleodynamic design reconstitutes itself by combining morphodynamic processes so as to optimise its relationship to the past, present, and future. A novel teleodynamic design tool called Contextual Optimisation Workspace (COW) is assembled within the Grasshopper visual programming environment. The tool is used to carry out four experiments that combine to produce the teleodynamic design of an urban wooden façade, exemplifying an alternative framework for the design of wood-based structures. The first experiment investigates a variegated grid combining two distinct subdivision methods (an orthogonal grid and a Voronoi tessellation), transmuting one system into another. The second and third experiments focus on durability aspects of a wooden façade and devise strategies for how the effects of photochemical degradation and wetting due to driving rain might be minimised using the COW tool. The fourth experiment optimises the building for daylight based on an illuminance simulation. Using simulation and anticipation to add the advantages of site- and time-specific data streams as a design strategy can effectively suspend an algorithm-driven design iteration in time and space in order to allow it to be parametrically influenced by past or future events such as unique site and project conditions. The COW tool can be used to produce such teleodynamic designs.

This paper challenges an asserted artificial separation between architecture, engineering, and material design. Novel protocols for mass-customised building materials could make each material entity perform optimally at its given position within a geometry. The number of evaluated materials in an architectural surface should be expanded to become equal to its number of parts. This number should in turn be maximised given other constraints and objectives. The built environment’s restricted material palette provides a limited space of possible combinations of material properties. Evolutionary design procedures could expand this conservative range of materials to achieve additional performance targets. Contextual Optimisation Workspace (COW) is a design tool that promotes such novel processes. Fusing multiple-objective optimisation (MOO) strategies with genetic algorithms, the system allows for analytical comparisons between conflicting aspects of a design. An experiment is conducted to investigate and develop two specific parts of the system’s anatomy. New components add weights to objectives while punishing less favourable designs. The components guide the relative positioning of wood products within a single wall of an architectural structure, to achieve optimal performance given predefined targets. A path towards a “contextual materials engineering technology” is discussed, and suggestions for future studies provided.

Conventional phase diagrams plot differences in properties (e.g. volume) of a medium generated by changes in external conditions (e.g. temperature and/or pressure). This paper discusses how the logic of such diagrams can be applied to produce a new type of surface plot, material phase transition (MPT) diagrams, that chart not the conditions for chemical equilibrium but the relative benefits of a particular material system given a set of predefined objectives and a virtual search space of design solutions. Such diagrams can form an integral part of parametric design processes that use ‘auxiliary loads’ (e.g. LCA values) as variables to generate design iterations. A Grasshopper user object is created and used to design a box beam that yields a set of auxiliary loads charts and MPT diagrams. The anatomy of MPT diagrams is described, and areas for future studies discussed.

This quantitative/qualitative evaluation of meta-heuristic design processes being implemented in a real-life architecture project introduces the theoretical concept of anticipatory adaptive assemblages (AAA) and reports on tactics that were used to reduce the ‘curse of dimensionality’ associated with the mechanisms that produce such assemblages. It describes strategies to adopt ‘presilient’ methods to constrain a model’s design space before any evolutionary solving occurs, leverage the advantage in fenestration performance presumed to arise from explorations of non-periodic tessellations of the plane, and use benchmark models to optimise some material aspects of wall sections. These tactics all support a materiality-based approach to designing architecture using genetic algorithms. The experiments were designed in an attempt to begin to close the knowledge gap between on the one hand the existing praxis of LCA-based analyses, on the other simulations that use material properties to directly inform geometries associated with particular combinations of (for instance) site, weather, and material data. The hypothesis is that AAA’s can become an effective framework for design-based adaptation to site conditions and mitigation of climate change. The objectives of the study are a) to implicitly and qualitatively describe the trials and tribulations a commercial adaptation of alternative design processes may cause, while b) explicitly and quantitatively report on the results of the experiments, and how they relate to AAAs. After an introduction of the AAA concept, three design experiments are described and their outcomes analysed, followed by a concluding discussion including suggestions for future studies.