发表机构
Huaxin Consulting, Design, and Research Institute（华信咨询设计研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出EaC范式，构建ADL与ESA解决工程设计的可计算表示问题，原型在跨域样本上实现69条规则200ms内检查、100%检测率零误报的成果。
AI 中文摘要
大型语言模型在代码生成、芯片设计等可验证领域已取得显著进展，但在建筑、机械工程、HVAC等领域的工程设计任务上仍存在局限。本文认为根本原因并非模型能力，而是缺乏“设计即代码”的可计算基础：即机器可消费、可验证、可版本控制的设计表示。现有CAD/BIM系统将设计逻辑与几何耦合，导致质量保证向下游漂移；自动合规性检查（ACC）存在几何误报和依赖命名的模型重构开销。我们提出工程即代码（Engineering as Code, EaC）范式：将工程设计表达为原生文本的声明式语言，以自动化规则引擎、版本控制和包管理作为质量闸门。核心贡献包括：（1）信息表示假说，认为工程AI瓶颈源于缺失可计算设计表示而非模型能力；（2）部件定义语言（Assembly Definition Language, ADL），以部件为原子，组织为三个正交子语言——部件定义语言（Part Definition Language, PDL）、部件装配语言（Part Mating Language, PML）和部件布局语言（Part Layout Language, PLL）；（3）工程静态分析（Engineering Static Analysis, ESA），将合规性检查从下游审查转向设计阶段，基于语义类别（族类型、装配关系）而非几何运行，消除误报和命名依赖。原型通过三个跨域样本（电信机架扩展、模块化数据中心、机械键盘）验证了ADL的表达能力和ESA的检测能力，在200毫秒内检查了69条规则。受控违规注入实验达到100%检测率且零误报。SD-HWE-Bench基准设计作为该假说的经验测试平台已完成。
英文摘要
Large language models have made significant progress in verifiable domains such as code generation and chip design, yet remain limited on engineering design tasks in fields like architecture, mechanical engineering, and HVAC. This paper argues the root cause is not model capability but the absence of a "Design as Code" computable foundation: design representations that can be consumed, verified, and versioned by machines. Existing CAD/BIM systems couple design logic with geometry, causing quality assurance to drift downstream; Automated Compliance Checking (ACC) suffers from geometric false positives and naming-dependent model reconstruction overhead. We propose the Engineering as Code (EaC) paradigm: expressing engineering design as text-native declarative language with automated rule engines, version control, and package management as quality gates. Core contributions: (1) the Information Representation Hypothesis, arguing the engineering AI bottleneck stems from missing computable design representations rather than model capability; (2) ADL (Assembly Definition Language) with Part as atom, organized into three orthogonal sub-languages -- PDL (Part Definition), PML (Part Mating), and PLL (Part Layout); (3) ESA (Engineering Static Analysis), shifting compliance checking from downstream review to design-time, operating on semantic categories (Family types, Mate relations) rather than geometry, eliminating false positives and naming dependencies. A prototype validates ADL expressiveness and ESA detection across three cross-domain samples (telecom rack expansion, modular datacenter, mechanical keyboard), checking 69 rules in under 200ms. A controlled violation injection experiment achieves 100% detection rate with zero false positives. The SD-HWE-Bench benchmark design is complete as an empirical testbed for the hypothesis.
Comments27 pages, 3 tables, 1 figure
