露天矿工程项目具有设计复杂、生产环节多、工程动态发展和信息多源分布等特点,传统的项目管理模式因存在矿建项目信息难以共享的问题,导致设计变更、工程返工等诸多工程问题屡见不鲜。以建筑信息模型(Building Information Modeling,B...露天矿工程项目具有设计复杂、生产环节多、工程动态发展和信息多源分布等特点,传统的项目管理模式因存在矿建项目信息难以共享的问题,导致设计变更、工程返工等诸多工程问题屡见不鲜。以建筑信息模型(Building Information Modeling,BIM)技术为基础,针对露天矿建设工程设计领域,深入分析了其BIM设计内涵,研究了BIM矿建设计的框架,并以国能集团新疆矿业红沙泉二矿为例开展了应用探索。结果表明:(1)露天矿建设工程BIM设计内涵是以BIM技术为基础,融合协同设计和真三维信息十大关键技术,从安全管理、设计质量、工程建设、绿色智能、技术支撑等多角度开展露天矿工程设计;(2)通用软件端、专业软件端、三方软件端、应用端和数据交互平台共同组成了露天矿BIM设计框架,其功能架构遵循“自上而下逐级规划、自下而上分布实施”的金字塔结构,并由分类编码、数据模型及信息传递共同构成其设计数据标准;(3)红沙泉二矿BIM设计应用实践表明,该技术显著提升了设计质量、安全管理水平以及全过程智能管控和绿色开采水平。展开更多
This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material u...This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material usage,and costs.In the first stage,an extended key block analysis identifies key blocks and key block groups,accounting for progressive failure and force interactions.The second stage uses AI algorithms to optimise rockbolting design,balancing stability,cost,and material use.The most efficient algorithms include the multi-objective tree-structured Parzen estimator(MOTPE)and non-dominated sorting genetic algorithms(NSGA-II and NSGA-III).Applied to the Larvik rock slope,the optimised solution uses 18 pre-tensioned cablebolts,providing 13.2 MN of active force and achieving a factor of safety of 1.31 while reducing the average anchorage length by approximately 16%compared to traditional design.The AI-assisted approach also reduces computation time by over 90%compared to Quasi-Monte Carlo(QMC)methods,demonstrating its efficiency for small-scale civil engineering projects and large-scale mining operations.The developed tool is practical,compatible with Building Information Modelling(BIM),and ready for engineering implementation,supporting sustainable and cost-effective rock slope stabilisation.While the method is largely automated,professional judgement remains crucial for verifying ground conditions and selecting the final solution.Future work will focus on integrating data uncertainties,addressing complex block deformation mechanisms,refining optimisation objectives,and improving the performance of multi-objective optimisation for slope rockboling applications to further enhance the method's versatility.展开更多
文摘露天矿工程项目具有设计复杂、生产环节多、工程动态发展和信息多源分布等特点,传统的项目管理模式因存在矿建项目信息难以共享的问题,导致设计变更、工程返工等诸多工程问题屡见不鲜。以建筑信息模型(Building Information Modeling,BIM)技术为基础,针对露天矿建设工程设计领域,深入分析了其BIM设计内涵,研究了BIM矿建设计的框架,并以国能集团新疆矿业红沙泉二矿为例开展了应用探索。结果表明:(1)露天矿建设工程BIM设计内涵是以BIM技术为基础,融合协同设计和真三维信息十大关键技术,从安全管理、设计质量、工程建设、绿色智能、技术支撑等多角度开展露天矿工程设计;(2)通用软件端、专业软件端、三方软件端、应用端和数据交互平台共同组成了露天矿BIM设计框架,其功能架构遵循“自上而下逐级规划、自下而上分布实施”的金字塔结构,并由分类编码、数据模型及信息传递共同构成其设计数据标准;(3)红沙泉二矿BIM设计应用实践表明,该技术显著提升了设计质量、安全管理水平以及全过程智能管控和绿色开采水平。
基金support from Research Council of Norway via STIPINST PhD grant(Grant No.323307),Bever Control AS,and Bane NOR.
文摘This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material usage,and costs.In the first stage,an extended key block analysis identifies key blocks and key block groups,accounting for progressive failure and force interactions.The second stage uses AI algorithms to optimise rockbolting design,balancing stability,cost,and material use.The most efficient algorithms include the multi-objective tree-structured Parzen estimator(MOTPE)and non-dominated sorting genetic algorithms(NSGA-II and NSGA-III).Applied to the Larvik rock slope,the optimised solution uses 18 pre-tensioned cablebolts,providing 13.2 MN of active force and achieving a factor of safety of 1.31 while reducing the average anchorage length by approximately 16%compared to traditional design.The AI-assisted approach also reduces computation time by over 90%compared to Quasi-Monte Carlo(QMC)methods,demonstrating its efficiency for small-scale civil engineering projects and large-scale mining operations.The developed tool is practical,compatible with Building Information Modelling(BIM),and ready for engineering implementation,supporting sustainable and cost-effective rock slope stabilisation.While the method is largely automated,professional judgement remains crucial for verifying ground conditions and selecting the final solution.Future work will focus on integrating data uncertainties,addressing complex block deformation mechanisms,refining optimisation objectives,and improving the performance of multi-objective optimisation for slope rockboling applications to further enhance the method's versatility.
