This paper presents the shear performance analysis of a heavy-duty universal hinged cast steel support with the largest bearing capacity. The effect of 9 parameters ( 52 specimens) ,i. e. height of the upper support,d...This paper presents the shear performance analysis of a heavy-duty universal hinged cast steel support with the largest bearing capacity. The effect of 9 parameters ( 52 specimens) ,i. e. height of the upper support,depth of the ring of the upper support,depth of the top plate of the bottom support,height of the ribs of the bottom support,depth of the ribs of the bottom support,bolt hole diameter,number of the ribs of the bowl,depth of the ribs of the bowl,and yield strength of the material,were analyzed with a 3-dimensional elastic-plastic finite element model in which the nonlinearities of geometry,material and contact were all considered. Analysis shows that height of the upper support,depth of the ring of the upper support and yield strength of the material have a great effect on the mechanical performance of the support. Height of the upper support has the largest effect on performance price ratio of the support,and the maximum effect can be up to 160% . Depth of the top plate of the bottom support,height of the ribs of the bottom support and depth of the ribs of the bottom support have a medium effect on performance price ratio of the support,and the effect is within the limit of 15% 19% .展开更多
The application of steel strut force servo systems in deep excavation engineering is not widespread,and there is a notable scarcity of in-situ measured datasets.This presents a significant research gap in the field.Ad...The application of steel strut force servo systems in deep excavation engineering is not widespread,and there is a notable scarcity of in-situ measured datasets.This presents a significant research gap in the field.Addressing this,our study introduces a valuable dataset and application scenarios,serving as a reference point for future research.The main objective of this study is to use machine learning(ML)methods for accurately predicting strut forces in steel supporting structures,a crucial aspect for the safety and stability of deep excavation projects.We employed five different ML methods:radial basis function neural network(RBFNN),back propagation neural network(BPNN),K-Nearest Neighbor(KNN),support vector machine(SVM),and random forest(RF),utilizing a dataset of 2208 measured points.These points included one output parameter(strut forces)and seven input parameters(vertical position of strut,plane position of strut,time,temperature,unit weight,cohesion,and internal frictional angle).The effectiveness of these methods was assessed using root mean square error(RMSE),correlation coefficient(R),and mean absolute error(MAE).Our findings indicate that the BPNN method outperforms others,with RMSE,R,and MAE values of 72.1 kN,0.9931,and 57.4 kN,respectively,on the testing dataset.This study underscores the potential of ML methods in precisely predicting strut forces in deep excavation engineering,contributing to enhanced safety measures and project planning.展开更多
In order to access remote reserve areas, some U.S.coal mines have to maintain aged underground entries for a great distance.However, high humidity, warm temperature, and time dependent deterioration can cause progress...In order to access remote reserve areas, some U.S.coal mines have to maintain aged underground entries for a great distance.However, high humidity, warm temperature, and time dependent deterioration can cause progressive roof deterioration and unexpected roof falls, and pose a great challenge to ground control engineers.With an active belt structure in place and limited space, re-bolting becomes very costly, less effective,and, sometimes, impractical and unfeasible.To gain long-term entry stability and serviceability, operators typically rehabilitate the aged belt entries by installing standing steel set supports.In the last several years,Keystone Mining Services, LLC,(KMS) has assisted many coal mines with their belt entry rehabilitation projects, evaluated the ground condition of various aged belt entries, and designed different standing steel set support systems.This paper presents a case study of a large-scale roof fall that occurred at an aged belt entry in a mine located in an eastern coalfield, analyzes root causes of excessive deformation of square sets that were installed in an adjacent entry, evaluates the adequacy of an existing rehabilitation square set, and develops remedial recommendations for future rehabilitation practice.Based on the case study, the paper outlines design guidelines for rehabilitation steel sets that include field evaluation, engineering considerations, design assumptions, steel structural analysis, and field installation quality control.展开更多
基金Sponsored by the National Natural Science Foundation of China( Grant No. 50878066)the National Key Technology R&D Program during the 11th Five-Year Plan Period of China( Grant No. 2006BAJ01B02)
文摘This paper presents the shear performance analysis of a heavy-duty universal hinged cast steel support with the largest bearing capacity. The effect of 9 parameters ( 52 specimens) ,i. e. height of the upper support,depth of the ring of the upper support,depth of the top plate of the bottom support,height of the ribs of the bottom support,depth of the ribs of the bottom support,bolt hole diameter,number of the ribs of the bowl,depth of the ribs of the bowl,and yield strength of the material,were analyzed with a 3-dimensional elastic-plastic finite element model in which the nonlinearities of geometry,material and contact were all considered. Analysis shows that height of the upper support,depth of the ring of the upper support and yield strength of the material have a great effect on the mechanical performance of the support. Height of the upper support has the largest effect on performance price ratio of the support,and the maximum effect can be up to 160% . Depth of the top plate of the bottom support,height of the ribs of the bottom support and depth of the ribs of the bottom support have a medium effect on performance price ratio of the support,and the effect is within the limit of 15% 19% .
基金supported by the National Natural Science Foundation of China(Grant No.51778575).
文摘The application of steel strut force servo systems in deep excavation engineering is not widespread,and there is a notable scarcity of in-situ measured datasets.This presents a significant research gap in the field.Addressing this,our study introduces a valuable dataset and application scenarios,serving as a reference point for future research.The main objective of this study is to use machine learning(ML)methods for accurately predicting strut forces in steel supporting structures,a crucial aspect for the safety and stability of deep excavation projects.We employed five different ML methods:radial basis function neural network(RBFNN),back propagation neural network(BPNN),K-Nearest Neighbor(KNN),support vector machine(SVM),and random forest(RF),utilizing a dataset of 2208 measured points.These points included one output parameter(strut forces)and seven input parameters(vertical position of strut,plane position of strut,time,temperature,unit weight,cohesion,and internal frictional angle).The effectiveness of these methods was assessed using root mean square error(RMSE),correlation coefficient(R),and mean absolute error(MAE).Our findings indicate that the BPNN method outperforms others,with RMSE,R,and MAE values of 72.1 kN,0.9931,and 57.4 kN,respectively,on the testing dataset.This study underscores the potential of ML methods in precisely predicting strut forces in deep excavation engineering,contributing to enhanced safety measures and project planning.
文摘In order to access remote reserve areas, some U.S.coal mines have to maintain aged underground entries for a great distance.However, high humidity, warm temperature, and time dependent deterioration can cause progressive roof deterioration and unexpected roof falls, and pose a great challenge to ground control engineers.With an active belt structure in place and limited space, re-bolting becomes very costly, less effective,and, sometimes, impractical and unfeasible.To gain long-term entry stability and serviceability, operators typically rehabilitate the aged belt entries by installing standing steel set supports.In the last several years,Keystone Mining Services, LLC,(KMS) has assisted many coal mines with their belt entry rehabilitation projects, evaluated the ground condition of various aged belt entries, and designed different standing steel set support systems.This paper presents a case study of a large-scale roof fall that occurred at an aged belt entry in a mine located in an eastern coalfield, analyzes root causes of excessive deformation of square sets that were installed in an adjacent entry, evaluates the adequacy of an existing rehabilitation square set, and develops remedial recommendations for future rehabilitation practice.Based on the case study, the paper outlines design guidelines for rehabilitation steel sets that include field evaluation, engineering considerations, design assumptions, steel structural analysis, and field installation quality control.
