Challenges arise in automate design with building information modeling(BIM)in underground space.Industry foundation classes(IFC)standard lacks detailed entity objects for describing excavation retaining structures and...Challenges arise in automate design with building information modeling(BIM)in underground space.Industry foundation classes(IFC)standard lacks detailed entity objects for describing excavation retaining structures and geological information,and automated design based on BIM models is not yet for practical application.This study presents a novel automated framework.It integrates the extended IFC standard with mechanical analysis and BIM modeling,significantly advancing structural optimization and rebar detailing.Direct 3D model generation streamlines complex excavation projects,aligning with the trend towards automated,precision-driven design.Key contributions include:(1)the extension of the IFC standard to support excavation retaining structures with objects like IfcBracedPit and IfcPitWall,improving interoperability between geotechnical models and BIM systems;(2)the integration of heuristic algorithms for automated optimization of deformation control parameters,reducing manual intervention;and(3)the promotion of design methodology that bypasses two-dimensional modeling and directly generates three-dimensional models,enhancing efficiency and allowing engineers to focus on high-level decision-making.However,the framework is primarily suited for standard cross-section projects like subway stations and tunnels.Future work will focus on refining the framework for more complex geotechnical projects,addressing software independence and improving design robustness and independence.展开更多
Honeycomb metastructures are widely used in electromagnetic wave absorption applications due to their lightweight and high-strength properties.While geometric modifications can further enhance microwave absorption,the...Honeycomb metastructures are widely used in electromagnetic wave absorption applications due to their lightweight and high-strength properties.While geometric modifications can further enhance microwave absorption,the unclear relationships between structural parameters,electromagnetic response,and mechanical performance present challenges for optimizing these structures to achieve both absorption and mechanical performance.This study introduces an automated framework for the bi-objective optimization of hybrid geometry honeycomb metastructures(HGHMs),fabricated with a graphene conductive coating and photosensitive resin for the honeycomb substrate,designed to improve both microwave absorption and mechanical resistance.By integrating artificial intelligence(AI),parametric modeling,and finite element analysis,a robust system was developed to explore the design space.Two optimized HGHM configurations were identified:One prioritizes microwave absorption with a-10 dB bandwidth of 6.1–18.0 GHz,a-15 dB bandwidth of 6.9–16.3 GHz,and a compressive Young's modulus of E=123 MPa,while the other balances absorption performance(-10 dB bandwidth:5.7–18.0 GHz)and mechanical robustness with E=638 MPa.Experimental validation confirmed the simulation results,and sensitivity analysis revealed the relationship between structural design,absorption,and deformation resistance.Based on a highaccuracy neural network surrogate model for the prediction of reflection loss curves,differential evolution was employed to suggest geometric parameters that lead to desired reflection loss curves.These results underscore the transformative potential of AI-based optimization for the rapid,automated,and customized design of multifunctional metastructures.展开更多
基金supported by the National Key R&D Program of China(Grant No.2023YFC3009400)National Natural Science Foundation of China(Grant Nos.52238009,52208344,and 52278350)+1 种基金Natural Science Foundation of Jiangxi Province(Grant No.20223BBG71018)the Innovation Fund of Jiangxi Province for Postgraduate(Grant No.YC2024-B196).
文摘Challenges arise in automate design with building information modeling(BIM)in underground space.Industry foundation classes(IFC)standard lacks detailed entity objects for describing excavation retaining structures and geological information,and automated design based on BIM models is not yet for practical application.This study presents a novel automated framework.It integrates the extended IFC standard with mechanical analysis and BIM modeling,significantly advancing structural optimization and rebar detailing.Direct 3D model generation streamlines complex excavation projects,aligning with the trend towards automated,precision-driven design.Key contributions include:(1)the extension of the IFC standard to support excavation retaining structures with objects like IfcBracedPit and IfcPitWall,improving interoperability between geotechnical models and BIM systems;(2)the integration of heuristic algorithms for automated optimization of deformation control parameters,reducing manual intervention;and(3)the promotion of design methodology that bypasses two-dimensional modeling and directly generates three-dimensional models,enhancing efficiency and allowing engineers to focus on high-level decision-making.However,the framework is primarily suited for standard cross-section projects like subway stations and tunnels.Future work will focus on refining the framework for more complex geotechnical projects,addressing software independence and improving design robustness and independence.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFB3707800)the“Artificial Intelligence Empowering Scientific Research Plan”initiative of the Shanghai Municipal Education Commissionthe National Natural Science Foundation of China(Grant Nos.12072179,12421002,52231007,12327804)。
文摘Honeycomb metastructures are widely used in electromagnetic wave absorption applications due to their lightweight and high-strength properties.While geometric modifications can further enhance microwave absorption,the unclear relationships between structural parameters,electromagnetic response,and mechanical performance present challenges for optimizing these structures to achieve both absorption and mechanical performance.This study introduces an automated framework for the bi-objective optimization of hybrid geometry honeycomb metastructures(HGHMs),fabricated with a graphene conductive coating and photosensitive resin for the honeycomb substrate,designed to improve both microwave absorption and mechanical resistance.By integrating artificial intelligence(AI),parametric modeling,and finite element analysis,a robust system was developed to explore the design space.Two optimized HGHM configurations were identified:One prioritizes microwave absorption with a-10 dB bandwidth of 6.1–18.0 GHz,a-15 dB bandwidth of 6.9–16.3 GHz,and a compressive Young's modulus of E=123 MPa,while the other balances absorption performance(-10 dB bandwidth:5.7–18.0 GHz)and mechanical robustness with E=638 MPa.Experimental validation confirmed the simulation results,and sensitivity analysis revealed the relationship between structural design,absorption,and deformation resistance.Based on a highaccuracy neural network surrogate model for the prediction of reflection loss curves,differential evolution was employed to suggest geometric parameters that lead to desired reflection loss curves.These results underscore the transformative potential of AI-based optimization for the rapid,automated,and customized design of multifunctional metastructures.
