Computational exploration of the structural design spaceCaitlin Mueller, MIT PhD Dissertation, 2014
This dissertation focuses on computational strategies for incorporating structural considerations into the earliest stages of the architectural design process. Because structural behavior is most affected by geometric form, the greatest potential for structural efficiency and a harmony of design goals occurs when global formal design decisions are made, in conceptual design. However, most existing computational tools and approaches lack the features necessary to take advantage of this potential: architectural modeling tools address geometry in absence of performance, and structural analysis tools require an already determined geometrical form. There is a need for new computational approaches that allow designers to explore the structural design space, which links geometric variation and performance, in a free and interactive manner. The dissertation addresses this need by proposing three new design space strategies. The first strategy, an interactive evolutionary framework, balances creative navigation of the design space with a focus on performance. The original contributions of this strategy center on enhanced opportunities for designer interaction and control. The second strategy introduces structural grammars, which allow for the formulation of broad and diverse design spaces that span across typologies. This strategy extends existing work in geometry-based shape grammars by incorporating structural behavior in novel ways. Finally, the third strategy is a surrogate modeling approach that approximates the design space to enable fast and responsive design environments. This strategy contributes new ways for non-experts to use this machine-learning-based methodology in conceptual design. These three complementary strategies can be applied independently or in combination, and the dissertation includes a discussion about possibilities and techniques for integrating them. Finally, the dissertation concludes by reflecting on its potential impact on design in practice, and by outlining important areas for future work. Key words: conceptual structural design, design space exploration, structural optimization, interactive evolutionary algorithm, structural grammar, surrogate modeling, structural design tools
An integrated computational approach for creative conceptual structural designCaitlin Mueller and John Ochsendorf, Proceedings of the International Association for Shell and Spatial Structures (IASS) Symposium 2013, 2013
This paper introduces a new computational approach for creative conceptual structural design, synthesizing an interactive evolutionary framework, a structural grammar strategy for trans-typological design, and a performance-focused surrogate modelling technique. By developing and integrating these three strategies into a unified design approach, this research enables architects and structural designers to explore broad ranges of conceptual design alternatives in an interactive way.
Modelling with forces: grammar-based graphic statics for diverse architectural structuresJuney Lee, Corentin Fivet, and Caitlin Mueller, Modelling Behaviour: Proceedings of the Design Modelling Symposium, Copenhagen 2015, 2015
Most architectural modelling software provides the user with geometric freedom in absence of performance, while most engineering software mandates pre-determined forms before it can perform any numerical analysis. This trial-and-error process is not only time intensive, but it also hinders free exploration beyond standard designs. This paper proposes a new structural design methodology that integrates the generative (architectural) and the analytical (engineering) procedures into a simultaneous design process, by combining shape grammars and graphic statics. Design tests presented will demonstrate the applicability of this new methodology to various engineering design problems, and demonstrate how the user can explore diverse and unexpected structural alternatives to conventional solutions.
Grammatical design with graphic statics: rule-based generation of diverse equilibrium structuresJuney Lee, MIT MEng Thesis, 2015
During early stages of design, an architect tries to control space by “finding a form” among countless possible forms, while an engineer tries to control forces by “form-finding” an optimized solution of that particular form. Most commonly used parametric tools in architectural design provide the user with extensive geometric freedom in absence of performance, while engineering analysis software mandates pre-determined forms before it can perform any numerical analysis. This trial-and-error process is not only time intensive, but it also prohibits exploration beyond the design space filled with already known, conventional solutions. There is a need for new design methods that combine form generation with structural performance.
This thesis addresses this need, by proposing a grammar-based structural design methodology using graphic statics. By combining shape grammars with graphic statics, the generative (architectural) and the analytical (engineering) procedures are seamlessly integrated into a simultaneous design process. Instead of manipulating forms with multiple variables as one would in the conventional parametric design paradigm, this approach defines rules of allowable geometric generations and transformations. Computationally automated random generator is used to iteratively apply various rules to generate unexpected, interesting and yet structural feasible designs. Because graphic statics is used to embed structural logic and behavior into the rules, the resulting structures are always guaranteed to be in equilibrium, and do not need any further numerical analysis. The effectiveness of this new methodology will be demonstrated through design tests of a variety of discrete, planar structures.
Grammatical Design with Graphic Statics (GDGS) contributes new ways of controlling both form and forces during early stages of design, by enabling the designer to: 1) rapidly generate unique, yet functional structures that fall outside of the expected solution space, 2) explore various design spaces unbiasedly, and 3) customize the combination of grammar rules or design objectives for unique formulation of the problem. Design tests presented in this thesis will show the powerful new potential of combining computational graphic statics with shape grammars, and demonstrate the possibility for richer and broader design spaces with much more trial, and less error.