Ground penetrating radar(GPR)is a vital non-destructive testing(NDT)technology that can be employed for detecting the backfill grouting of shield tunnels.To achieve intelligent analysis of GPR data and overcome the su...Ground penetrating radar(GPR)is a vital non-destructive testing(NDT)technology that can be employed for detecting the backfill grouting of shield tunnels.To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods,the CatBoost&BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms.A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz,with known backfill grouting thickness.The model test helps address the limitation of not knowing the grout body condition in actual field detection.The data were then used to create machine learning datasets.The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic(EM)propagation law in mediums.The research shows that:(1)the CatBoost&BO-TPE model exhibited outstanding performance in both experimental and numerical data,achieving R^(2)values of 0.9760,0.8971,0.8808,and 0.5437 for numerical data and test data at 400 and 900 MHz.It outperformed extreme gradient boosting(XGBoost)and random forest(RF)in terms of performance in the backfill grouting thickness regression;(2)compared with the full-waveform GPR data,the feature selection method proposed in this paper can promote the performance of the model.The selected features within the 5–30 ns of the A-scan can yield the best performance for the model;(3)compared to GPR data at 900 MHz,GPR data at 400 MHz exhibited better performance in the CatBoost&BO-TPE model.This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters;(4)the application results of the trained CatBoost&BO-TPE model in engineering are in line with the patterns observed through traditional processing methods,yet they demonstrate a more quantitative and objective nature compared to the traditional method.展开更多
Backfill mining technology is the practice of returning waste materials underground for both disposal and geotechnical stability,however,a challenge with current technologies is that they commonly require cement-based...Backfill mining technology is the practice of returning waste materials underground for both disposal and geotechnical stability,however,a challenge with current technologies is that they commonly require cement-based binders which have a relatively high environmental impact.Finding alternatives to cement-based binders can improve environmental performance and this paper proposes microbial grouted backfill(MGB)as a potential solution.In this paper,the effects of the cementation solution concentration(CSC),volume ratio of bacterial solution to cementation solution(VRBC),particle sizes of the aggregates,and the number of grouting batches on the mechanical properties of MGB are studied.The experimental results show that MGB strength increased,up to a peak value,as CSC was increased,before decreasing as CSC was increased further.The results also show that MGB strength increased,up to a peak value,as VRBC decreased,before decreasing as the VRBC was decreased further.The peak strength was achieved at a CSC of 2 mol/L and a VRBC of 1:9.The strength of the MGB also increased as the number of grouting batches increased.Graded MGB samples showed the highest UCS,25.12 MPa,at particle sizes of 0.2 to 0.8 mm,while full(non-graded)MGB samples displayed mean UCS values ranging from1.56 MPa when the maximum particle size was 0.2 mm,up to 13 MPa when the maximum particle size was 1.2 mm.MGB samples are consolidated by the calcium carbonate that is precipitated during microbial metabolism,and the strength of MGB increases linearly as calcium carbonate content increases.The calcium carbonate minerals produced in MGB materials are primarily calcite,with secondary amounts of vaterite.展开更多
Shield tunnel backfill grouting is vital to stabilize tunnel settlement at a later stage;however,most shield tunnel backfill grouting designs lack a complete theoretical reference,and numerical simulations of the grou...Shield tunnel backfill grouting is vital to stabilize tunnel settlement at a later stage;however,most shield tunnel backfill grouting designs lack a complete theoretical reference,and numerical simulations of the grouting process are rarely conducted.This study presents the fundamental theories of grout diffusion and pressure variation for backfill grouting during shield construction.Moreover,the numerical simulation methods coupled with discrete element methods(DEM)and finite difference methods(FDM)are achieved to simulate the process of grout injection from the grouting hole into the shield tail gap and generate grout pressure on the surrounding rock.The diffusion state of the grout in the shield tail gap and the squeezing effect on the surrounding rock under two shield tail disengagement modes are analyzed,as well as the impact of various grouting pressure on the surface settlement.The results indicated that the grout diffusion in the shield tail gap can be divided into three stages:the stage of diffusion with each grouting hole as the starting point,the stage of interconnection and contact of the grout injected in each grouting hole,and the final gap filling stage.Each of the three stages can be described using the proposed equation.During the grouting process,the grout is injected into the shield tail gap at a certain pressure,but the grout diffuses slowly to both sides and upwards,which causes a rapid rise of the principal stresses in the soil around the tunnel.After grouting is complete,the grout pressure gradually dissipates and stabilizes,and the principal stress decreases.In addition,backfill grouting can reduce surface settlement,but it does not affect its distribution width.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52038008 and 52378408)the Science and Technology Innovation Plan of Shanghai Science and Technology Commission(Grant Nos.20DZ1202004 and 22DZ1203004)State Grid Shanghai Municipal Electric Power Company(Grant No.52090W220001).
文摘Ground penetrating radar(GPR)is a vital non-destructive testing(NDT)technology that can be employed for detecting the backfill grouting of shield tunnels.To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods,the CatBoost&BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms.A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz,with known backfill grouting thickness.The model test helps address the limitation of not knowing the grout body condition in actual field detection.The data were then used to create machine learning datasets.The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic(EM)propagation law in mediums.The research shows that:(1)the CatBoost&BO-TPE model exhibited outstanding performance in both experimental and numerical data,achieving R^(2)values of 0.9760,0.8971,0.8808,and 0.5437 for numerical data and test data at 400 and 900 MHz.It outperformed extreme gradient boosting(XGBoost)and random forest(RF)in terms of performance in the backfill grouting thickness regression;(2)compared with the full-waveform GPR data,the feature selection method proposed in this paper can promote the performance of the model.The selected features within the 5–30 ns of the A-scan can yield the best performance for the model;(3)compared to GPR data at 900 MHz,GPR data at 400 MHz exhibited better performance in the CatBoost&BO-TPE model.This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters;(4)the application results of the trained CatBoost&BO-TPE model in engineering are in line with the patterns observed through traditional processing methods,yet they demonstrate a more quantitative and objective nature compared to the traditional method.
基金supported by the National Natural Science Foundation of China(Nos.5180430852034009)+3 种基金the China Postdoctoral Science Foundation(Nos.2020T1302692020M670689)the Yue Qi Young Scholar Project(No.2020QN03)the Postdoctoral Research Project of Hebei Province(No.B2020003029)。
文摘Backfill mining technology is the practice of returning waste materials underground for both disposal and geotechnical stability,however,a challenge with current technologies is that they commonly require cement-based binders which have a relatively high environmental impact.Finding alternatives to cement-based binders can improve environmental performance and this paper proposes microbial grouted backfill(MGB)as a potential solution.In this paper,the effects of the cementation solution concentration(CSC),volume ratio of bacterial solution to cementation solution(VRBC),particle sizes of the aggregates,and the number of grouting batches on the mechanical properties of MGB are studied.The experimental results show that MGB strength increased,up to a peak value,as CSC was increased,before decreasing as CSC was increased further.The results also show that MGB strength increased,up to a peak value,as VRBC decreased,before decreasing as the VRBC was decreased further.The peak strength was achieved at a CSC of 2 mol/L and a VRBC of 1:9.The strength of the MGB also increased as the number of grouting batches increased.Graded MGB samples showed the highest UCS,25.12 MPa,at particle sizes of 0.2 to 0.8 mm,while full(non-graded)MGB samples displayed mean UCS values ranging from1.56 MPa when the maximum particle size was 0.2 mm,up to 13 MPa when the maximum particle size was 1.2 mm.MGB samples are consolidated by the calcium carbonate that is precipitated during microbial metabolism,and the strength of MGB increases linearly as calcium carbonate content increases.The calcium carbonate minerals produced in MGB materials are primarily calcite,with secondary amounts of vaterite.
基金supported by National Natural Science Foundation of China of China(Grant Nos.51778633 and 51308552)2020 Science and Technology Research and Development Plan Guiding Subjects of China Railway Corporation Ltd.(Grant Nos.41 and 243)2022 Annual Science and Technology Research and Development Plan and Funded Topics of China Railway Construction Corporation Ltd.(Grant No.2022-C1).
文摘Shield tunnel backfill grouting is vital to stabilize tunnel settlement at a later stage;however,most shield tunnel backfill grouting designs lack a complete theoretical reference,and numerical simulations of the grouting process are rarely conducted.This study presents the fundamental theories of grout diffusion and pressure variation for backfill grouting during shield construction.Moreover,the numerical simulation methods coupled with discrete element methods(DEM)and finite difference methods(FDM)are achieved to simulate the process of grout injection from the grouting hole into the shield tail gap and generate grout pressure on the surrounding rock.The diffusion state of the grout in the shield tail gap and the squeezing effect on the surrounding rock under two shield tail disengagement modes are analyzed,as well as the impact of various grouting pressure on the surface settlement.The results indicated that the grout diffusion in the shield tail gap can be divided into three stages:the stage of diffusion with each grouting hole as the starting point,the stage of interconnection and contact of the grout injected in each grouting hole,and the final gap filling stage.Each of the three stages can be described using the proposed equation.During the grouting process,the grout is injected into the shield tail gap at a certain pressure,but the grout diffuses slowly to both sides and upwards,which causes a rapid rise of the principal stresses in the soil around the tunnel.After grouting is complete,the grout pressure gradually dissipates and stabilizes,and the principal stress decreases.In addition,backfill grouting can reduce surface settlement,but it does not affect its distribution width.
