In open pit mining,uncontrolled block instabilities have serious social,economic and regulatory consequences,such as casualties,disruption of operation and increased regulation difficulties.For this reason,bench face ...In open pit mining,uncontrolled block instabilities have serious social,economic and regulatory consequences,such as casualties,disruption of operation and increased regulation difficulties.For this reason,bench face angle,as one of the controlling parameters associated with block instabilities,should be carefully designed for sustainable mining.This study introduces a discrete fracture network(DFN)-based probabilistic block theory approach for the fast design of the bench face angle.A major advantage is the explicit incorporation of discontinuity size and spatial distribution in the procedure of key blocks testing.The proposed approach was applied to a granite mine in China.First,DFN models were generated from a multi-step modeling procedure to simulate the complex structural characteristics of pit slopes.Then,a modified key blocks searching method was applied to the slope faces modeled,and a cumulative probability of failure was obtained for each sector.Finally,a bench face angle was determined commensurate with an acceptable risk level of stability.The simulation results have shown that the number of hazardous traces exposed on the slope face can be significantly reduced when the suggested bench face angle is adopted,indicating an extremely low risk of uncontrolled block instabilities.展开更多
Blasting is a cost-effective technique to break hard rock volumes by using explosives in the mining and civil engineering realms. Moreover, although blasting is a designed process and plays an indispensable role in th...Blasting is a cost-effective technique to break hard rock volumes by using explosives in the mining and civil engineering realms. Moreover, although blasting is a designed process and plays an indispensable role in these industries, it can also have multiple adverse environmental impacts. One such effect is flyrock, which poses risks to nearby machinery, and residential structures, and can even lead to injuries or fatalities. To optimize blasting efficiency as well as restrict side effects, prediction of the blast aftereffects is vital. Therefore, the present work focuses on using two machine learning methods to predict the velocity of flyrock in the open pit mine. To address this issue, a comprehensive dataset was gathered from the open pit mine. Then, Decision Tree and Random Forest algorithms were employed to predict flyrock velocity. The Random Forest model demonstrated superior performance compared to the Decision Tree model. Nonetheless, the performance of the Decision Tree model was deemed satisfactory, as evidenced by its coefficient of determination value of 0.83, mean squared error (MSE) of 4.2, and mean absolute percentage error (MAPE) of 5.6%. Considering these metrics, it is reasonable to conclude that tree-based algorithms can be effective in predicting flyrock velocity.展开更多
针对不同个性化需求的燃料电池测试台(fuel cell test bench,FCTB)难以评价和量化评估的问题,提出一种基于改进和声搜索算法的FCTB价值评估方法.针对不同FCTB的个性化需求,建立了FCTB综合评估指标体系;结合用户的个性化需求,采用模糊层...针对不同个性化需求的燃料电池测试台(fuel cell test bench,FCTB)难以评价和量化评估的问题,提出一种基于改进和声搜索算法的FCTB价值评估方法.针对不同FCTB的个性化需求,建立了FCTB综合评估指标体系;结合用户的个性化需求,采用模糊层次分析法分配指标权重,构建价值定量评估模型,将权重求取问题转换为约束优化问题;提出一种改进和声搜索算法对问题进行求解,通过设计解向量生成机制和参数自适应调整策略,用于提高传统和声搜索算法的求解效率和搜索能力.仿真结果表明,本文方法在计算效率和精度方面具有优势,并能够根据不同的需求特性实现对FCTB方案做出定量的价值评估.展开更多
为解决传统座舱试验台结构同质化及模块化设计不足等问题,采用亲和图法整理了汽车故障及用户初始需求;采用模糊Kano模型进行需求指标权重计算,并结合质量特性要素进行用户核心需求汇总;通过功能分析系统技术(Function Analysis System T...为解决传统座舱试验台结构同质化及模块化设计不足等问题,采用亲和图法整理了汽车故障及用户初始需求;采用模糊Kano模型进行需求指标权重计算,并结合质量特性要素进行用户核心需求汇总;通过功能分析系统技术(Function Analysis System Technique,FAST)黑箱模型将用户需求转化为功能需求,并引入公理设计(Axiomatic Design,AD)理论与功能-行为-结构(Function-Behavior-Structure,FBS)模型进行逐级映射,最终确定智能座舱柔性试验台的结构设计要素。该设计过程以用户核心需求为导向,通过FAST-AD-FBS集成方法的应用,克服了传统产品概念设计中用户需求与产品功能结构设计间存在矛盾的问题,为提高产品创新设计的完整性及准确性提供了理论参考。展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.42102313 and 52104125)the Fundamental Research Funds for the Central Universities(Grant No.B240201094).
文摘In open pit mining,uncontrolled block instabilities have serious social,economic and regulatory consequences,such as casualties,disruption of operation and increased regulation difficulties.For this reason,bench face angle,as one of the controlling parameters associated with block instabilities,should be carefully designed for sustainable mining.This study introduces a discrete fracture network(DFN)-based probabilistic block theory approach for the fast design of the bench face angle.A major advantage is the explicit incorporation of discontinuity size and spatial distribution in the procedure of key blocks testing.The proposed approach was applied to a granite mine in China.First,DFN models were generated from a multi-step modeling procedure to simulate the complex structural characteristics of pit slopes.Then,a modified key blocks searching method was applied to the slope faces modeled,and a cumulative probability of failure was obtained for each sector.Finally,a bench face angle was determined commensurate with an acceptable risk level of stability.The simulation results have shown that the number of hazardous traces exposed on the slope face can be significantly reduced when the suggested bench face angle is adopted,indicating an extremely low risk of uncontrolled block instabilities.
文摘Blasting is a cost-effective technique to break hard rock volumes by using explosives in the mining and civil engineering realms. Moreover, although blasting is a designed process and plays an indispensable role in these industries, it can also have multiple adverse environmental impacts. One such effect is flyrock, which poses risks to nearby machinery, and residential structures, and can even lead to injuries or fatalities. To optimize blasting efficiency as well as restrict side effects, prediction of the blast aftereffects is vital. Therefore, the present work focuses on using two machine learning methods to predict the velocity of flyrock in the open pit mine. To address this issue, a comprehensive dataset was gathered from the open pit mine. Then, Decision Tree and Random Forest algorithms were employed to predict flyrock velocity. The Random Forest model demonstrated superior performance compared to the Decision Tree model. Nonetheless, the performance of the Decision Tree model was deemed satisfactory, as evidenced by its coefficient of determination value of 0.83, mean squared error (MSE) of 4.2, and mean absolute percentage error (MAPE) of 5.6%. Considering these metrics, it is reasonable to conclude that tree-based algorithms can be effective in predicting flyrock velocity.
文摘针对不同个性化需求的燃料电池测试台(fuel cell test bench,FCTB)难以评价和量化评估的问题,提出一种基于改进和声搜索算法的FCTB价值评估方法.针对不同FCTB的个性化需求,建立了FCTB综合评估指标体系;结合用户的个性化需求,采用模糊层次分析法分配指标权重,构建价值定量评估模型,将权重求取问题转换为约束优化问题;提出一种改进和声搜索算法对问题进行求解,通过设计解向量生成机制和参数自适应调整策略,用于提高传统和声搜索算法的求解效率和搜索能力.仿真结果表明,本文方法在计算效率和精度方面具有优势,并能够根据不同的需求特性实现对FCTB方案做出定量的价值评估.
文摘为解决传统座舱试验台结构同质化及模块化设计不足等问题,采用亲和图法整理了汽车故障及用户初始需求;采用模糊Kano模型进行需求指标权重计算,并结合质量特性要素进行用户核心需求汇总;通过功能分析系统技术(Function Analysis System Technique,FAST)黑箱模型将用户需求转化为功能需求,并引入公理设计(Axiomatic Design,AD)理论与功能-行为-结构(Function-Behavior-Structure,FBS)模型进行逐级映射,最终确定智能座舱柔性试验台的结构设计要素。该设计过程以用户核心需求为导向,通过FAST-AD-FBS集成方法的应用,克服了传统产品概念设计中用户需求与产品功能结构设计间存在矛盾的问题,为提高产品创新设计的完整性及准确性提供了理论参考。
