Roof and rib instability is an important issue in underground mining. To optimize ground support design,enhance ground stability, and reduce the possibility of roof or rib failure with minimal use of artificial ground...Roof and rib instability is an important issue in underground mining. To optimize ground support design,enhance ground stability, and reduce the possibility of roof or rib failure with minimal use of artificial ground support, it is essential to have an accurate understanding of ground conditions. This includes the location of voids, cracks, and discontinuities, as well as information about the different strata in the immediate roof. This paper briefly introduces ongoing research on void detection by using the roof bolter feed and rotation pressure. The goal of this project is to improve the sensitivity of detection programs to locate smaller joints and reduce the number of false alarms. This paper presents a brief review of the testing procedures, data analysis, logic, and algorithms used for void detection. In addition, this paper discusses the results of preliminary laboratory tests and statistical analysis of the data from these two drilling parameters used for void detection.展开更多
Variable-fidelity(VF)surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity(HF)simulations with reduced computational power.A key challen...Variable-fidelity(VF)surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity(HF)simulations with reduced computational power.A key challenge to building a VF model is devising an adaptive model updating strategy that jointly selects additional low-fidelity(LF)and/or HF samples.The additional samples must enhance the model accuracy while maximizing the computational efficiency.We propose ISMA-VFEEI,a global optimization framework that integrates an Improved Slime-Mould Algorithm(ISMA)and a Variable-Fidelity Expected Extension Improvement(VFEEI)learning function to construct a VF surrogate model efficiently.First,A cost-aware VFEEI function guides the adaptive LF/HF sampling by explicitly incorporating evaluation cost and existing sample proximity.Second,ISMA is employed to solve the resulting non-convex optimization problem and identify global optimal infill points for model enhancement.The efficacy of ISMA-VFEEI is demonstrated through six numerical benchmarks and one real-world engineering case study.The engineering case study of a high-speed railway Electric Multiple Unit(EMU),the optimization objective of a sanding device attained a minimum value of 1.546 using only 20 HF evaluations,outperforming all the compared methods.展开更多
Spares inventory configuration optimization is an effective way to improve readiness and reduce life cycle cost of equipment.Through analyzing two-echelon spares support system,the METRIC model basic theory was used.A...Spares inventory configuration optimization is an effective way to improve readiness and reduce life cycle cost of equipment.Through analyzing two-echelon spares support system,the METRIC model basic theory was used.An inventory configuration optimization model of two-echelon spares support system was proposed which took the spares expected shortfall as the object and made the minimum repairable parts expected shortfall instead of the maximum spares supportability as the objective function.Marginal efficiency analysis algorithm was applied to optimizing the spares configuration and generating a rational spares inventory configuration.Finally,several examples are given to verify the model.展开更多
针对EGO(Efficient Global Optimization)算法在求解昂贵优化问题中需要大量真实评价获得最优解的问题,提出一种基于并行填充准则的EGO算法。首先,设置了离群度量因子,提高分布稀疏区域样本点被选择的几率,从而提高算法优化效率;其次,...针对EGO(Efficient Global Optimization)算法在求解昂贵优化问题中需要大量真实评价获得最优解的问题,提出一种基于并行填充准则的EGO算法。首先,设置了离群度量因子,提高分布稀疏区域样本点被选择的几率,从而提高算法优化效率;其次,引入了影响函数,依据已选择填充点对后续待选填充点的影响,构造新的EI(Expected Improvement,简称EI)函数依次选择多个填充点,并对这些点并行计算,从而减少了计算成本。在14个测试函数上对所提算法进行仿真实验,与其它典型代理模型辅助的优化算法进行测试对比,实验结果表明所提算法在有限的的评价次数下拥有更快的收敛速度。展开更多
文摘Roof and rib instability is an important issue in underground mining. To optimize ground support design,enhance ground stability, and reduce the possibility of roof or rib failure with minimal use of artificial ground support, it is essential to have an accurate understanding of ground conditions. This includes the location of voids, cracks, and discontinuities, as well as information about the different strata in the immediate roof. This paper briefly introduces ongoing research on void detection by using the roof bolter feed and rotation pressure. The goal of this project is to improve the sensitivity of detection programs to locate smaller joints and reduce the number of false alarms. This paper presents a brief review of the testing procedures, data analysis, logic, and algorithms used for void detection. In addition, this paper discusses the results of preliminary laboratory tests and statistical analysis of the data from these two drilling parameters used for void detection.
基金funded by National Natural Science Foundation of China(grant No.52405255)Special Program of Huzhou(grant No.2023GZ05)+1 种基金Projects of Huzhou Science and Technology Correspondent(grant No.2023KT76)Guangdong Basic and Applied Basic Research Foundation(grant No.2025A1515010487)。
文摘Variable-fidelity(VF)surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity(HF)simulations with reduced computational power.A key challenge to building a VF model is devising an adaptive model updating strategy that jointly selects additional low-fidelity(LF)and/or HF samples.The additional samples must enhance the model accuracy while maximizing the computational efficiency.We propose ISMA-VFEEI,a global optimization framework that integrates an Improved Slime-Mould Algorithm(ISMA)and a Variable-Fidelity Expected Extension Improvement(VFEEI)learning function to construct a VF surrogate model efficiently.First,A cost-aware VFEEI function guides the adaptive LF/HF sampling by explicitly incorporating evaluation cost and existing sample proximity.Second,ISMA is employed to solve the resulting non-convex optimization problem and identify global optimal infill points for model enhancement.The efficacy of ISMA-VFEEI is demonstrated through six numerical benchmarks and one real-world engineering case study.The engineering case study of a high-speed railway Electric Multiple Unit(EMU),the optimization objective of a sanding device attained a minimum value of 1.546 using only 20 HF evaluations,outperforming all the compared methods.
文摘Spares inventory configuration optimization is an effective way to improve readiness and reduce life cycle cost of equipment.Through analyzing two-echelon spares support system,the METRIC model basic theory was used.An inventory configuration optimization model of two-echelon spares support system was proposed which took the spares expected shortfall as the object and made the minimum repairable parts expected shortfall instead of the maximum spares supportability as the objective function.Marginal efficiency analysis algorithm was applied to optimizing the spares configuration and generating a rational spares inventory configuration.Finally,several examples are given to verify the model.
文摘针对EGO(Efficient Global Optimization)算法在求解昂贵优化问题中需要大量真实评价获得最优解的问题,提出一种基于并行填充准则的EGO算法。首先,设置了离群度量因子,提高分布稀疏区域样本点被选择的几率,从而提高算法优化效率;其次,引入了影响函数,依据已选择填充点对后续待选填充点的影响,构造新的EI(Expected Improvement,简称EI)函数依次选择多个填充点,并对这些点并行计算,从而减少了计算成本。在14个测试函数上对所提算法进行仿真实验,与其它典型代理模型辅助的优化算法进行测试对比,实验结果表明所提算法在有限的的评价次数下拥有更快的收敛速度。
