Automated Compliance Checking (ACC) techniques have advanced significantly, enabling designers to evaluate building designs against codes. However, architectural engineers have to improve the design by manually implementing the ACC results, which is laborious, iterative, and requires domain expertise. To address this challenge, this paper introduces a Design Healing framework that adapts the original design into code-compliant alternatives. By integrating design data and ACC results, the framework identifies critical non-compliant components through a graph-based topological algorithm and sensitivity analysis. A prior knowledge-informed design space exploration is conducted to find valid alternatives and quantify modifications using weighted Euclidean distances, allowing designers to select options closely aligned with the initial design. Multi-scenario experiments demonstrate the framework’s effectiveness in resolving architectural spatial design violations. By automating post-checking design adaptation, the framework reduces manual revisions and provides an efficient tool for achieving compliance while accommodating varying design constraints. This paper establishes a basis for advancing designer-centered automated design correction methods based on ACC techniques.

中文翻译：

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用于自动化代码合规性的设计修复框架


自动合规性检查 （ACC） 技术取得了显著进步，使设计人员能够根据规范评估建筑设计。但是，架构工程师必须通过手动实现 ACC 结果来改进设计，这很费力、迭代，并且需要领域专业知识。为了应对这一挑战，本文引入了一个 Design Healing 框架，该框架将原始设计调整为符合规范的替代方案。通过集成设计数据和 ACC 结果，该框架通过基于图形的拓扑算法和敏感性分析来识别关键的不合规组件。进行先验知识知情的设计空间探索，以找到有效的替代方案并使用加权欧几里得距离量化修改，使设计人员能够选择与初始设计密切相关的选项。多场景实验证明了该框架在解决建筑空间设计违规方面的有效性。通过自动进行检查后设计调整，该框架减少了手动修订，并为实现合规性提供了有效的工具，同时适应不同的设计约束。本文为推进基于 ACC 技术的以设计师为中心的自动化设计修正方法奠定了基础。