In this article, we propose that new architectural design practices might be based on machine learning approaches to better leverage data-rich environments and workflows. Through reference to recent architectural research, we describe how the application of machine learning can occur throughout the design and fabrication process, to develop varied relations between design, performance and learning. The impact of machine learning on architectural practices with performance-based design and fabrication is assessed in two cases by the authors. We then summarise what we perceive as current limits to a more widespread application and conclude by providing an outlook and direction for future research for machine learning in architectural design practice.

This paper aims to identify the current status of research in 3D concrete printing (3DCP), locate the sustainability considerations relevant to these trajectories, and to identify a gap in knowledge and future research challenge regarding the sustainability of 3DCP. To categorize the broad range of research topics within 3DCP, the paper introduces an assessment framework that subdivides this field into three sub-fields: material science, computational design, and structure and performance. Common sustainability considerations are identified for each of these sub-fields. As a result of this analysis, a lack of critical assessments on claims about the sustainability and environmental impacts of 3DCP is identified.Our survey of literature, and its analysis via this framework, finds that whilst certain sustainability aspects are highlighted, other measures and considerations are skimmed over, or omitted. It is found that whilst material optimization and the ability to create formwork-free, complex forms is noted as a main argument for the implementation of 3DCP, this claim is largely unsupported by reference or reported outcomes, and the environmental impacts are often only briefly discussed. There is a clear need for a holistic view on the sustainability issues which surround 3DCP.This paper further highlights the lack of comprehensive assessment tools and metrics for measuring the environmental impact of 3DCP and concludes that further research must be done to develop these tools, to allow architects to integrate 3DCP into sustainability-oriented design workflows. Our paper concludes that the development of these tools will lead to a more comprehensive understanding on the environmental sustainability of 3DCP, allowing research resources to be focused within each field to ensure 3DCP continues to develop in a sustainable way.

Active bending introduces a new level of integration into the design of architectural structures, and opens up new complexities for the architectural design process. In particular, the introduction of material variation reconfigures the design space. Through the precise specification of their stiffness, it is possible to control and pre-calibrate the bending behaviour of a composite element. This material capacity challenges architecture's existing methods for design, specification and prediction. In this paper, we demonstrate how architects might connect the designed nature of composites with the design of bending-active structures, through computational strategies. We report three built structures that develop architecturally oriented design methods for bending-active systems using composite materials. These projects demonstrate the application and limits of the introduction of advanced engineering simulation into an architectural workflow, and the extension of architecture's existing physics-based approaches.

Multiscale design and analysis models promise a robust, multimethod, multidisciplinary approach, but at present have limited application during the architectural design process. To explore the use of multiscale models in architecture, we develop a calibrated modeling and simulation platform for the design and analysis of a prototypical envelope made of phase change materials. The model is mechanistic in nature, incorporates material-scale and precinct scale-attributes, and supports the design of two- and three-dimensional phase change material geometries informed by heat transfer phenomena. Phase change material behavior, in solid and liquid states, dominates the visual and numerical evaluation of the multiscale model. Model calibration is demonstrated using real-time data gathered from the prototype. Model extensibility is demonstrated when it is used by designers to predict the behavior of alternate envelope options. Given the challenges of modeling phase change material behavior in this multiscale model, an additional multiple linear regression model is applied to data collected from the physical prototype in order to demonstrate an alternate method for predicting the melting and solidification of phase change materials.