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<p>This study presents a comparative analysis of reinforced concrete (RC) buildings and composite (steel–concrete) structures subjected to blast loads. Structures were modelled and analysed using extended 3D Analysis of Building Systems (ETABS) 20.0.3 under uniform blast load intensities across varying building heights. Key performance indicators such as maximum storey displacement and overturning moment were evaluated. The results show that composite structures exhibit superior performance, with significantly lower maximum lateral displacements (6300&#xa0;mm) compared to RC structures (9800&#xa0;mm), indicating greater lateral stiffness. Storey drift was also notably lower in composite systems 0.09 versus 0.145 particularly in the mid-storey region, while overturning moments were slightly higher in composites due to their increased stiffness. These results demonstrate better deformation control and overall stability of composite structures under dynamic loading. Machine learning algorithms, including AdaBoost, CatBoost, and Random Forest, were applied to predict structural responses. All models performed well, achieving R2 values greater than 0.91.</p>

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Analysis of reinforced concrete building and composite structure building subjected to blast load using ETABS and machine learning

  • 期刊论文

  • 发表日期：

    2025年7月26日

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  • Akshay Saini,
  • Bheem Pratap,
  • Deepshikha Shukla

摘要

This study presents a comparative analysis of reinforced concrete (RC) buildings and composite (steel–concrete) structures subjected to blast loads. Structures were modelled and analysed using extended 3D Analysis of Building Systems (ETABS) 20.0.3 under uniform blast load intensities across varying building heights. Key performance indicators such as maximum storey displacement and overturning moment were evaluated. The results show that composite structures exhibit superior performance, with significantly lower maximum lateral displacements (6300 mm) compared to RC structures (9800 mm), indicating greater lateral stiffness. Storey drift was also notably lower in composite systems 0.09 versus 0.145 particularly in the mid-storey region, while overturning moments were slightly higher in composites due to their increased stiffness. These results demonstrate better deformation control and overall stability of composite structures under dynamic loading. Machine learning algorithms, including AdaBoost, CatBoost, and Random Forest, were applied to predict structural responses. All models performed well, achieving R2 values greater than 0.91.