AbstractThe heating, ventilation, and air conditioning (HVAC) system is one of the most complex parts in a building design, which requires a high level of specialty to interpret and analyze during building energy modeling. From an energy simulation perspective, significant efforts are required in extracting HVAC information from the two-dimensional (2D) mechanical drawings or three-dimensional (3D) design models and manually inputting the data into the energy models. This tedious, error-prone, and time-consuming process has hindered high productivity in energy analysis. Automatically transforming HVAC data already contained in building information modeling (BIM) into building energy modeling (BEM) can significantly accelerate this process and improve efficiency during design iterations. To automate this process, the authors proposed a new algorithmic method by leveraging the state-of-the-art data-driven reverse engineering algorithm development (D-READ) method and the invariant signatures of HVAC objects. Following the proposed method, an algorithm was developed using a 2-story residential building model and a 2-story office building model. It successfully transformed HVAC data from BIM to EnergyPlus input file following the Industry Foundation Classes (IFC) standard. It was tested on two testing models with different HVAC systems [i.e., a 4-story office building model with a boiler radiator system and a 2-story clinic building with a variable air volume (VAV) system], which achieved 97.5% and 98.7% transformation accuracy compared with evaluation models manually created in commercially available software, respectively. Results also showed a satisfactory precision (<9.6% error) in total energy consumption by the algorithmically generated model when compared with the evaluation model. This work provides a new IFC-based approach to address the research gap of HVAC interoperability between BIM and BEM and supports better accessibility compared with a proprietary workflow. It builds a solid step for realizing seamless and fully-automated HVAC information transformation between BIM and BEM, for complete BIM-BEM interoperability.

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