Optimizing Concrete Design in High-Rise Buildings Through Adaptive Parametric BIM: A Mixed Methods Framework

This paper presents an adaptive parametric Building Information Modeling (BIM) method for enhancing concrete design of tall buildings. Traditional BIM workflows are great at representing and coordinating but struggle to incorporate near real-time feedback and iterative performance-based design exercises. Our methodology fills this gap by implementing parametric control (Autodesk Revit), structural analysis (ETABS), interference detection (Navisworks), and statistical endorsement (SPSS) in a closed-loop process. The framework validation was conducted in two ways: a qualitative benchmark of Shanghai and Canton Towers and a quantitative simulation of a 30-story prototype model. Performance metrics volumetric coverage, seismic response, cost savings, and workflow efficiency were monitored between iterations. Results revealed that the required concrete volume was reduced by 14%, seismic performance was improved by 13%, and all design conflicts were resolved. What’s transformative of this research, is to show that adaptive BIM can go beyond a static design tool or a mechanism of design coordination, to become a facility to achieve dynamic optimization. By facilitating early design stage performance-based decision making, the framework provides a scalable and data-driven approach to sustainable and efficient high-rise construction. The originality of the study lies in combining simulation analytics with parametric modeling tools to return empirically validated and repeatable outcomes for the AEC sector.