民主化环境影响评估:人工智能增强的可持续建筑设计框架
1Department of Civil and Environmental Engineering and Earth Science, University of Notre Dame, Notre Dame, IN, USA.
iScience
|February 2, 2026
概括
本研究介绍了一个人工智能工具,用于在建筑设计中进行可访问的生命周期评估 (LCA). 它可以帮助设计师在过程的早期做出明智的,低碳的材料选择.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 建筑工程 建筑工程 工程
背景情况:
- 建筑行业是温室气体排放的主要贡献者.
- 在决策过程中,设计人员往往缺乏可访问的生命周期评估 (LCA) 工具.
- 将环境影响分析纳入早期设计是可持续建筑的关键.
研究的目的:
- 在建筑信息建模 (BIM) 中为自动化和可解释的LCA提供AI增强的框架.
- 为了使设计师和利益相关者能够探索环境权衡,并了解影响.
- 支持明智的材料选择,并简化绿色许可程序.
主要方法:
- 开发了一个AI框架,将LCA嵌入到Revit BIM环境中.
- 从Revit使用编程库存建模链接材料数量.
- 整合了用于用户交互和结果解释的对话界面,包括可调节的时间视界.
主要成果:
- 该框架复制了专家SimaPro的LCA输出,对于住宅建筑模型的变化不到2.1%.
- 证明了系统能够提供可解释的结果和可视化环境影响的能力.
- 验证了环境智能在早期设计工作流程中的整合.
结论:
- 人工智能增强的LCA框架使建筑设计师能够获得环境评估.
- 这种方法促进了更明智的材料选择,从而导致了低碳建筑.
- 该系统为促进可持续建筑实践的政策工具提供了基础.
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