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Proceedings of CAD'17, 2017, 288-292
STG-framework: A Pattern-Based Algorithmic Framework for Developing Generative Model of Parametric Architectural Design at Conceptual Design Stage
Abstract. Confusion concerning methods, thinking, and techniques among parametric, generative, and algorithmic approaches has emerged with the appearance of more new digital design tools like Grasshopper and Dynamo. Leach claims that one reason for this confusion is that the architectural domain were unfamiliar with the computer science, and alludes to the differences between parametric and algorithmic design, where parametric techniques are based on the manipulation of geometric forms, while algorithmic design is based on the use of programming codes. But regardless of whether through the manipulation of forms or the use of code, architects should be able to use digital architectural design tools to solve architectural design problems. Kotnik proposed that digital architectural design involves "exploring computable functions," which should take design information as input parameters and buildings’ properties as output variables. Literally, parametric design implies that the algorithm is fixed, and that output variables are consequently predictable from parameters. Generative modeling implies that output variables are not only controlled by input parameters, but also by flexible and adjustable functions. However, the computable functions of various architectural disciplines, in another word, the algorithms for solving various architectural design problems, should be the key to many digital architectural design issues.
Keywords. Design Intention, Parametric Design, Generative Modeling, Design Pattern