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A knowledge graph-based framework to automate the generation of building energy models using geometric relation checking and HVAC topology establishment
Energy and Buildings ( IF 6.6 ) Pub Date : 2024-11-14 , DOI: 10.1016/j.enbuild.2024.115035 Meng Wang, Georgios N. Lilis, Dimitris Mavrokapnidis, Kyriakos Katsigarakis, Ivan Korolija, Dimitrios Rovas
Energy and Buildings ( IF 6.6 ) Pub Date : 2024-11-14 , DOI: 10.1016/j.enbuild.2024.115035 Meng Wang, Georgios N. Lilis, Dimitris Mavrokapnidis, Kyriakos Katsigarakis, Ivan Korolija, Dimitrios Rovas
Building Energy Models (BEM) are widely utilized throughout all stages of a building's lifecycle to understand and enhance energy usage. However, creating these models demands significant effort, particularly for larger buildings or those with complex HVAC systems. While a substantial amount of information can be extracted from Building Information Models (BIM) — which are increasingly accessible and provide necessary data for geometric and HVAC contexts — this information is not readily usable in setting up BEM and typically requires manual translation. To address this challenge, this paper introduces a BIM-to-BEM (BIM2BEM) framework that focuses on automating the generation of HVAC parts of BEM models from BIM data. Core to the methodology is the extraction of HVAC system topologies from the BIM model and the creation of a knowledge graph with the HVAC topology. The topology transformation unfolds in three key stages: first, a geometry-induced knowledge graph is established by examining the geometric relationships among HVAC elements; second, this graph is converted into an informative HVAC topology with enhanced properties from additional data sources; and finally, the informative topology is simplified into a BEM-oriented HVAC topology compliant with BEM platforms such as EnergyPlus. A case study of a large university building with a complex HVAC system showcases that the proposed framework achieves automatic and precise generation of building performance simulation models. The model's predictions are then validated against actual measurements from the building.
中文翻译:
一个基于知识图谱的框架,用于使用几何关系检查和 HVAC 拓扑建立自动生成建筑能源模型
建筑能源模型 (BEM) 广泛用于建筑物生命周期的所有阶段,以了解和提高能源使用情况。但是,创建这些模型需要付出巨大的努力,特别是对于较大的建筑物或具有复杂 HVAC 系统的建筑物。虽然可以从建筑信息模型 (BIM) 中提取大量信息——这些信息越来越容易获得并为几何和 HVAC 环境提供必要的数据——但这些信息在设置 BEM 时并不容易使用,通常需要手动转换。为了应对这一挑战,本文介绍了一个 BIM 到 BEM (BIM2BEM) 框架,该框架专注于从 BIM 数据自动生成 BEM 模型的 HVAC 部分。该方法的核心是从 BIM 模型中提取 HVAC 系统拓扑,并使用 HVAC 拓扑创建知识图谱。拓扑变换分为三个关键阶段:首先,通过检查 HVAC 元素之间的几何关系来建立几何诱导的知识图谱;其次,此图形被转换为信息丰富的 HVAC 拓扑,该拓扑具有来自其他数据源的增强属性;最后,将信息拓扑简化为符合 EnergyPlus 等 BEM 平台的面向 BEM 的 HVAC 拓扑。具有复杂 HVAC 系统的大型大学建筑的案例研究表明,所提出的框架实现了建筑性能仿真模型的自动生成和精确。然后,根据建筑物的实际测量值验证模型的预测。
更新日期:2024-11-14
中文翻译:
一个基于知识图谱的框架,用于使用几何关系检查和 HVAC 拓扑建立自动生成建筑能源模型
建筑能源模型 (BEM) 广泛用于建筑物生命周期的所有阶段,以了解和提高能源使用情况。但是,创建这些模型需要付出巨大的努力,特别是对于较大的建筑物或具有复杂 HVAC 系统的建筑物。虽然可以从建筑信息模型 (BIM) 中提取大量信息——这些信息越来越容易获得并为几何和 HVAC 环境提供必要的数据——但这些信息在设置 BEM 时并不容易使用,通常需要手动转换。为了应对这一挑战,本文介绍了一个 BIM 到 BEM (BIM2BEM) 框架,该框架专注于从 BIM 数据自动生成 BEM 模型的 HVAC 部分。该方法的核心是从 BIM 模型中提取 HVAC 系统拓扑,并使用 HVAC 拓扑创建知识图谱。拓扑变换分为三个关键阶段:首先,通过检查 HVAC 元素之间的几何关系来建立几何诱导的知识图谱;其次,此图形被转换为信息丰富的 HVAC 拓扑,该拓扑具有来自其他数据源的增强属性;最后,将信息拓扑简化为符合 EnergyPlus 等 BEM 平台的面向 BEM 的 HVAC 拓扑。具有复杂 HVAC 系统的大型大学建筑的案例研究表明,所提出的框架实现了建筑性能仿真模型的自动生成和精确。然后,根据建筑物的实际测量值验证模型的预测。