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<p>This paper presents a procedural, AI-assisted workflow for translating the proportional and com-positional logic of classical architecture into a parametric modeling system based on shape grammar theory. Grounded in Scamozzi’s <i>L’Idea dell’architettura universale</i>, the research formalizes a corpus of architectural elements by encoding their geometric rules into modular, reproducible data structures. Leveraging Blender’s open-source Python API and large language models for natural-language-to-code generation, the method has shifted from primitive-based approximations to analytically defined Bezier and NURBS profiles, enabling accurate reconstruction of moldings, entasis, and proportional dependencies. The resulting Blender add-on, <i>Ars Modulandi</i> 2.0, provides an accessible tool for generating classical components while enhancing transparency and scientific traceability. Overall, the study demonstrates how AI-driven scripting can act as a mediator between textual description, mathematical reasoning, and architectural form, opening new avenues for procedural heritage reconstruction and computational design.</p>

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From Treatise’s Geometry to an AI-Driven Procedural Framework for Shape Grammars

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月6日

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  • Ramona Quattrini,
  • Paolo Pieruccini,
  • Mirco D’Alessio,
  • Paolo Clini

摘要

This paper presents a procedural, AI-assisted workflow for translating the proportional and com-positional logic of classical architecture into a parametric modeling system based on shape grammar theory. Grounded in Scamozzi’s L’Idea dell’architettura universale, the research formalizes a corpus of architectural elements by encoding their geometric rules into modular, reproducible data structures. Leveraging Blender’s open-source Python API and large language models for natural-language-to-code generation, the method has shifted from primitive-based approximations to analytically defined Bezier and NURBS profiles, enabling accurate reconstruction of moldings, entasis, and proportional dependencies. The resulting Blender add-on, Ars Modulandi 2.0, provides an accessible tool for generating classical components while enhancing transparency and scientific traceability. Overall, the study demonstrates how AI-driven scripting can act as a mediator between textual description, mathematical reasoning, and architectural form, opening new avenues for procedural heritage reconstruction and computational design.