Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this cha...Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.展开更多
Spatial performance measures the space usage of each underground segment in metro-led urban underground public space(UUPS).It usually varies in different UUPS segments and at different periods.Many environmental facto...Spatial performance measures the space usage of each underground segment in metro-led urban underground public space(UUPS).It usually varies in different UUPS segments and at different periods.Many environmental factors and space attractors can influence spatial performance in UUPS including spatial configurations,transportation facilities,space design characteristics,and commercial and work-ing facilities.This study intends to figure out the temporal and spatial distribution patterns of spatial performance in UUPS and then reveal the main influential factors and their impact mechanisms.The UUPS in Jiangwan–Wujiaochang Sub-center was selected as the study case.Cordon counting methods and multiple regression models were employed to collect the pedestrian data and quantitatively analyze the correlations between pedestrian flows and candidate influential factors.The study verified that spatial configurations were the most important factors instead of underground or surface attractors.There existed an interactive effect among pedestrian move-ments,spatial configurations,and commerce distribution in metro-led UUPS.Walkway width and the distribution of metro stations could partly affect spatial performance.The influential mechanisms of metro stations were different on weekdays and at weekends.Underground segments belonging to shopping malls in UUPS had a negative impact on spatial performance only on weekdays.Results of this study can provide insights for more efficient layout planning and design of metro-led UUPS in Chinese metropolitan cities.展开更多
基金funded by the National Key R&D Program of China(Grant No.2022YFC2903904)the National Natural Science Foundation of China(Grant Nos.51904057 and U1906208).
文摘Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.
基金supported by the National Natural ScienceFoundation of China(NSFC)(Grant number 42071251).
文摘Spatial performance measures the space usage of each underground segment in metro-led urban underground public space(UUPS).It usually varies in different UUPS segments and at different periods.Many environmental factors and space attractors can influence spatial performance in UUPS including spatial configurations,transportation facilities,space design characteristics,and commercial and work-ing facilities.This study intends to figure out the temporal and spatial distribution patterns of spatial performance in UUPS and then reveal the main influential factors and their impact mechanisms.The UUPS in Jiangwan–Wujiaochang Sub-center was selected as the study case.Cordon counting methods and multiple regression models were employed to collect the pedestrian data and quantitatively analyze the correlations between pedestrian flows and candidate influential factors.The study verified that spatial configurations were the most important factors instead of underground or surface attractors.There existed an interactive effect among pedestrian move-ments,spatial configurations,and commerce distribution in metro-led UUPS.Walkway width and the distribution of metro stations could partly affect spatial performance.The influential mechanisms of metro stations were different on weekdays and at weekends.Underground segments belonging to shopping malls in UUPS had a negative impact on spatial performance only on weekdays.Results of this study can provide insights for more efficient layout planning and design of metro-led UUPS in Chinese metropolitan cities.
