This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging v...This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.展开更多
掘进机回转台在截割煤岩时承受偏载荷及强冲击作用,其性能影响掘进机的工作效率及安全性。为探究掘进机回转台疲劳寿命的影响因素及最佳服役参数,提出了一种基于Kriging代理模型和DEM-MFBD(discrete element model-multi flexible body ...掘进机回转台在截割煤岩时承受偏载荷及强冲击作用,其性能影响掘进机的工作效率及安全性。为探究掘进机回转台疲劳寿命的影响因素及最佳服役参数,提出了一种基于Kriging代理模型和DEM-MFBD(discrete element model-multi flexible body dynamics,离散单元法-多柔性体动力学)双向耦合技术的回转台疲劳寿命预测方法。首先,建立了掘进机截割部与回转台的空间受力模型,明确了截割部与回转台的受力规律。然后,联合RecurDyn与EDEM软件对回转台进行双向刚柔耦合动力学仿真分析,获得了回转台在工作状态下的应力分布。最后,利用拉丁超立方抽样法选取15组掘进机服役参数作为输入,以回转台疲劳寿命为响应,建立了对应的Kriging代理模型,并利用粒子群优化算法对代理模型进行寻优,得到了回转台在最佳服役参数下的疲劳寿命。结果表明,当掘进机的截割头转速为54 r/min、回转台横摆速度为1.003 m/min、截割臂垂直摆角为7°时,回转台的疲劳寿命最长。结合DEM-MFBD双向耦合技术、Kriging代理模型与粒子群优化算法来探究掘进机的最佳服役参数,可为回转类部件的优化设计提供新思路。展开更多
基金supported by the Doctoral Research Funds for Nanchang HangKong University,China(Grant No.EA202411211)support is gratefully acknowledged.
文摘This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.
文摘掘进机回转台在截割煤岩时承受偏载荷及强冲击作用,其性能影响掘进机的工作效率及安全性。为探究掘进机回转台疲劳寿命的影响因素及最佳服役参数,提出了一种基于Kriging代理模型和DEM-MFBD(discrete element model-multi flexible body dynamics,离散单元法-多柔性体动力学)双向耦合技术的回转台疲劳寿命预测方法。首先,建立了掘进机截割部与回转台的空间受力模型,明确了截割部与回转台的受力规律。然后,联合RecurDyn与EDEM软件对回转台进行双向刚柔耦合动力学仿真分析,获得了回转台在工作状态下的应力分布。最后,利用拉丁超立方抽样法选取15组掘进机服役参数作为输入,以回转台疲劳寿命为响应,建立了对应的Kriging代理模型,并利用粒子群优化算法对代理模型进行寻优,得到了回转台在最佳服役参数下的疲劳寿命。结果表明,当掘进机的截割头转速为54 r/min、回转台横摆速度为1.003 m/min、截割臂垂直摆角为7°时,回转台的疲劳寿命最长。结合DEM-MFBD双向耦合技术、Kriging代理模型与粒子群优化算法来探究掘进机的最佳服役参数,可为回转类部件的优化设计提供新思路。
