To determine the influence of key blasthole parameters on tunnel overbreak during blasting construction,an intelligent detection sys-tem for tunnel blasting construction is independently developed.And the key blasthol...To determine the influence of key blasthole parameters on tunnel overbreak during blasting construction,an intelligent detection sys-tem for tunnel blasting construction is independently developed.And the key blasthole parameters and overbreak of a typical section of a single line tunnel under the condition of Class V surrounding rock are analyzed and detected.The actual data obtained is compared with the results of numerical simulations and theoretical calculations.The results are as follows:(1)Quantitative analysis is performed based on the blasthole angle,opening position,and charge mass by the self-developed intelligent detection equipment for blasthole parameters,which can be used to guide the drilling construction.Intelligent scanning equipment for outline excavation can be used to image the actual excavation section in real-time and has the advantages of high precision and fast speed;(2)Tunnel overbreak can be regarded as consisting of two parts:the surrounding rock damage caused by the blasting load,and the collapse of the surrounding rock caused by the blasthole opening position.Every parameter of the peripheral hole will affect the tunnel overbreak;however,the key parameter is the blasthole opening position;(3)The distributions of the tunnel overbreak volume obtained with the theoretical analysis,finite element simulation,and measurements are basically consistent.Under the condition of Class V surrounding rock,the overbreak of this single line tunnel can reach 14.1–78.2 cm.To meet the specification requirements,the opening position and construction accuracy of the peripheral hole should be strictly controlled.展开更多
In order to increase the safety of working environment and decrease the unwanted costs related to overbreak in tunnel excavation projects, it is necessary to minimize overbreak percentage. Thus, based on regression an...In order to increase the safety of working environment and decrease the unwanted costs related to overbreak in tunnel excavation projects, it is necessary to minimize overbreak percentage. Thus, based on regression analysis and fuzzy inference system, this paper tries to develop predictive models to estimate overbreak caused by blasting at the Alborz Tunnel. To develop the models, 202 datasets were utilized, out of which 182 were used for constructing the models. To validate and compare the obtained results,determination coefficient(R2) and root mean square error(RMSE) indexes were chosen. For the fuzzy model, R2 and RMSE are equal to 0.96 and 0.55 respectively, whereas for regression model, they are 0.41 and 1.75 respectively, proving that the fuzzy predictor performs, significantly, better than the statistical method. Using the developed fuzzy model, the percentage of overbreak was minimized in the Alborz Tunnel.展开更多
基金supported by the Open-end Fund of Key Laboratory of New Technology for Construction of Cities in Mountain Area(LNTCCMA-20210108)the National Natural Science Foundation of China(5108098,51908387)+6 种基金the Chongqing Municipal Construction Investment(Group)Co.,Ltd.Joint Technical Issues(CQCT-JSA-GC-2021-0138)the Chongqing Natural Science Fund General Project(cstc2020jcyj-msxmX0904)the Chongqing Talents:Exceptional Young Talents Project(cstc2021ycjh-bgzxm0246)the China Postdoctoral Science Foundation-General Project(2021M693739)the Chongqing Outstanding Youth Science Fund Project(2022NSCQ-JQX1224)the Chongqing University of Science&Technology Graduate Innovation Program Project(YKJCX2120613)the Special Funding for Postdoctoral Research Projects in Chongqing(2021XM2019).
文摘To determine the influence of key blasthole parameters on tunnel overbreak during blasting construction,an intelligent detection sys-tem for tunnel blasting construction is independently developed.And the key blasthole parameters and overbreak of a typical section of a single line tunnel under the condition of Class V surrounding rock are analyzed and detected.The actual data obtained is compared with the results of numerical simulations and theoretical calculations.The results are as follows:(1)Quantitative analysis is performed based on the blasthole angle,opening position,and charge mass by the self-developed intelligent detection equipment for blasthole parameters,which can be used to guide the drilling construction.Intelligent scanning equipment for outline excavation can be used to image the actual excavation section in real-time and has the advantages of high precision and fast speed;(2)Tunnel overbreak can be regarded as consisting of two parts:the surrounding rock damage caused by the blasting load,and the collapse of the surrounding rock caused by the blasthole opening position.Every parameter of the peripheral hole will affect the tunnel overbreak;however,the key parameter is the blasthole opening position;(3)The distributions of the tunnel overbreak volume obtained with the theoretical analysis,finite element simulation,and measurements are basically consistent.Under the condition of Class V surrounding rock,the overbreak of this single line tunnel can reach 14.1–78.2 cm.To meet the specification requirements,the opening position and construction accuracy of the peripheral hole should be strictly controlled.
文摘In order to increase the safety of working environment and decrease the unwanted costs related to overbreak in tunnel excavation projects, it is necessary to minimize overbreak percentage. Thus, based on regression analysis and fuzzy inference system, this paper tries to develop predictive models to estimate overbreak caused by blasting at the Alborz Tunnel. To develop the models, 202 datasets were utilized, out of which 182 were used for constructing the models. To validate and compare the obtained results,determination coefficient(R2) and root mean square error(RMSE) indexes were chosen. For the fuzzy model, R2 and RMSE are equal to 0.96 and 0.55 respectively, whereas for regression model, they are 0.41 and 1.75 respectively, proving that the fuzzy predictor performs, significantly, better than the statistical method. Using the developed fuzzy model, the percentage of overbreak was minimized in the Alborz Tunnel.
