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<p>Demand for economical reinforced concrete (RC) structures promote designing strategies to save material and reduce embodied CO₂ emissions while at the same time saving the structure’s functionality. Cost and emissions are treated as two distinct features, a factor that hampers them from integration in the process to critically address sustainability as a holistically defined goal. This work presents an integrated Bioinspired Morphogenetic Topology Optimization (BMTO) framework which models RC frames as bioinspired vascular structures projecting plant xylem–phloem adaptation to allow the evolution of non-prismatic beam–column geometries under combined gravity and lateral loads. Optimized geometries inform an Energy–Carbon Multiobjective Surrogate Model (ECMS) that enables the use of co-kriging to jointly predict cost and ECO₂, explicitly discriminating trade-offs with ~ 95% performance. As opposed to NSGA II, the Hybrid Quantum-Enhanced Multiobjective Optimizer (HQMO) works along these axes in quantum inspired superposition states, converging faster (by ~ 40–60% search time) and delivering better optimality. Selected geometries undertake Bio Inspired Multi-Scale Reinforcement Pattern Optimization (BMRPO), which imitates nacre microstructures to minimize steel ε by ~ 10–12% while raising the ductility. Finally, a Closed-Loop Digital Twin with Real-Time CO₂ Feedback (CDT-RCF) combines construction-phase monitoring with adjusting predicted improvements and gains, all but actualizing CO₂ estimation accuracy improvement from ~ 85% to ~ 97%. This design framework offers substantial environmental sustainability, from the savings of concrete mass by at least ~ 8–15% to possibly lowering the CO₂ of up to ~ 8%, along with cost savings, all set along the satisfactory line of stiffness and safety.</p>

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Multi-objective optimization for sustainability-based design of non-prismatic reinforced concrete structures

  • 期刊论文

  • 发表日期：

    2025年8月26日

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  • Vaishali Mendhe,
  • Shradhesh Marve,
  • Lowlesh N. Yadav,
  • Anuradha S. Bodhe,
  • Ramakant S. Ingole,
  • Tejas R. Patil,
  • Nischal Puri,
  • Rohit Pawar,
  • Manda Ukey,
  • Pranita S. Bhandari

摘要

Demand for economical reinforced concrete (RC) structures promote designing strategies to save material and reduce embodied CO₂ emissions while at the same time saving the structure’s functionality. Cost and emissions are treated as two distinct features, a factor that hampers them from integration in the process to critically address sustainability as a holistically defined goal. This work presents an integrated Bioinspired Morphogenetic Topology Optimization (BMTO) framework which models RC frames as bioinspired vascular structures projecting plant xylem–phloem adaptation to allow the evolution of non-prismatic beam–column geometries under combined gravity and lateral loads. Optimized geometries inform an Energy–Carbon Multiobjective Surrogate Model (ECMS) that enables the use of co-kriging to jointly predict cost and ECO₂, explicitly discriminating trade-offs with ~ 95% performance. As opposed to NSGA II, the Hybrid Quantum-Enhanced Multiobjective Optimizer (HQMO) works along these axes in quantum inspired superposition states, converging faster (by ~ 40–60% search time) and delivering better optimality. Selected geometries undertake Bio Inspired Multi-Scale Reinforcement Pattern Optimization (BMRPO), which imitates nacre microstructures to minimize steel ε by ~ 10–12% while raising the ductility. Finally, a Closed-Loop Digital Twin with Real-Time CO₂ Feedback (CDT-RCF) combines construction-phase monitoring with adjusting predicted improvements and gains, all but actualizing CO₂ estimation accuracy improvement from ~ 85% to ~ 97%. This design framework offers substantial environmental sustainability, from the savings of concrete mass by at least ~ 8–15% to possibly lowering the CO₂ of up to ~ 8%, along with cost savings, all set along the satisfactory line of stiffness and safety.