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<p>This study presents a comprehensive comparative analysis of flat slab systems with and without shear walls in reinforced concrete (RCC) multi-storey buildings under seismic loading. Using STAAD.Pro, structural models were developed for 10-, 20-, and 30-storey buildings with constant plan dimensions (20&#xa0;m × 30&#xa0;m). The study evaluates the influence of shear walls on key structural responses, including lateral displacement, storey drift, principal stresses, Von Mises and Tresca stresses, and stress concentration at slab corners. The presence of shear walls significantly reduces displacement and stress values, enhancing overall structural stability. To advance prediction capabilities, machine learning models—ANN, SVR, and XGBoost—were trained to estimate maximum principal stress using 500 simulated data points. Among them, XGBoost achieved the highest accuracy (R² = 0.948). Furthermore, an advanced Non-dominated Sorting Genetic Algorithm III (NSGA-III) was applied to perform multi-objective optimization targeting minimization of lateral displacement, principal stress, storey drift, and Von Mises stress. The optimization yielded Pareto-optimal solutions satisfying IS 456:2000 and IS 1893:2016 constraints. The findings offer valuable insights for structural engineers and designers to adopt efficient, earthquake-resistant configurations. The integration of AI and NSGA-III provides a robust framework for future seismic design and optimization of high-rise flat slab systems.</p>

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AI-augmented multi-objective structural optimization and statistical evaluation of flat slab systems with and without shear walls in high-rise RCC buildings under seismic loads

  • 期刊论文

  • 发表日期：

    2026年3月23日

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  • Rashtra Gaurav Singh Chauhan,
  • Yash Mothe,
  • Chayan Gupta

摘要

This study presents a comprehensive comparative analysis of flat slab systems with and without shear walls in reinforced concrete (RCC) multi-storey buildings under seismic loading. Using STAAD.Pro, structural models were developed for 10-, 20-, and 30-storey buildings with constant plan dimensions (20 m × 30 m). The study evaluates the influence of shear walls on key structural responses, including lateral displacement, storey drift, principal stresses, Von Mises and Tresca stresses, and stress concentration at slab corners. The presence of shear walls significantly reduces displacement and stress values, enhancing overall structural stability. To advance prediction capabilities, machine learning models—ANN, SVR, and XGBoost—were trained to estimate maximum principal stress using 500 simulated data points. Among them, XGBoost achieved the highest accuracy (R² = 0.948). Furthermore, an advanced Non-dominated Sorting Genetic Algorithm III (NSGA-III) was applied to perform multi-objective optimization targeting minimization of lateral displacement, principal stress, storey drift, and Von Mises stress. The optimization yielded Pareto-optimal solutions satisfying IS 456:2000 and IS 1893:2016 constraints. The findings offer valuable insights for structural engineers and designers to adopt efficient, earthquake-resistant configurations. The integration of AI and NSGA-III provides a robust framework for future seismic design and optimization of high-rise flat slab systems.