Taki Eddine Seghier

Reverberation time (RT) measures how long sound takes to decay in a space, affecting speech intelligibility and sound quality. Calculating RT using Sabine’s formula is time-consuming and error-prone due to manual extraction of room volume and material surface areas. Balancing RT and cost further complicates material selection. This paper automates RT calculation and optimization using Building Information Modeling (BIM) and generative design (GD). Sound absorption coefficients are input into a BIM model’s material properties, and visual programming (VP) extracts room geometries, materials, and absorption coefficients to compute RT and material costs. A multi-objective optimization algorithm in Autodesk GD identifies the best material and room height combination for cost-effective RT. A classroom case study validates the method. This approach enables fast RT calculation and helps designers select cost-efficient materials with optimal RT, aiding acoustic analysis in concert halls, auditoriums, and classrooms while supporting targeted acoustic design.

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Concrete Usage Index (CUI) is one of the very used sustainability criteria related to building materials available in the Malaysian and Singaporean building standards. Often, CUI assessment is achieved either by manual calculation or semi-automated methods based on Material Take-off functionalities provided by the BIM tools. Both of these methods are relatively time-consuming, error-prone, and require much human intervention. The purpose of this paper is to develop a computational BIM-based tool for the automation of Concrete Usage Index (CUI) assessment and rating. This developed tool takes advantage of the data embedded in the BIM model and the automated CUI compliance-checking which is developed using a Visual Programing Language (Dynamo for Revit). For validation purpose, this tool has been tested on a BIM model of an existing building and the results were compared with Revit Material Take-off method. Thus, Auto-CUI tool automates the process of data collection, calculation and the generation of the CUI report. In addition to that, the generated results are as accurate as the material take-off method. Auto-CUI will support design decision-making during the design stage by providing an interactive feedback of CUI actual score and rating. Thus, the project team will be able to compare different design options according to concrete usage. Furthermore, it will allow designers to avoid CUI’s cumbersome calculations and inaccurate outputs. Even though, the usage of this tool does not require programming skills, developing this tool further as a plug-in for Revit would be helpful in reducing computation time as well as enhancing the generation of CUI report.