Water-weakening presents a promising strategy for the in-situ improvement of rock cuttability.This study unveils the influences of water saturation on the mechanical response and fragmentation characteristics of rock ...Water-weakening presents a promising strategy for the in-situ improvement of rock cuttability.This study unveils the influences of water saturation on the mechanical response and fragmentation characteristics of rock samples.A series of rock-cutting tests using conical pick indentation was conducted on three types of sandstone samples under both dry and water-saturated conditions.The relationships between cutting force and indentation depth,as well as typical cuttability indices are determined and compared for dry and water-saturated samples.The experimental results reveal that the presence of water facilitates shearing failure in rock samples,as well as alleviates the fluctuations in the cutting force-indentation depth curve Furthermore,the peak cutting force(F_(p)),cutting work(W_(p)),and specific energy(SE)undergo apparent decrease after water saturation,whereas the trend in the indentation depth at rock failure(D_(f))varies across different rock types.Additionally,the water-induced percentage reductions in F_(p)and SE correlate positively with the quartz and swelling clay content within the rocks,suggesting that the cuttability improvement due to water saturation is attributed to the combined effects of stress corrosion and frictional reduction.These findings carry significant implications for improving rock cuttability in mechanized excavation of hard rock formations.展开更多
Real-time identification of rock strength and cuttability based on monitoring while cutting during excavation is essential for key procedures such as the precise adjustment of excavation parameters and the in-situ mod...Real-time identification of rock strength and cuttability based on monitoring while cutting during excavation is essential for key procedures such as the precise adjustment of excavation parameters and the in-situ modification of hard rocks.This study proposes an in-telligent approach for predicting rock strength and cuttability.A database comprising 132 data sets is established,containing cutting para-meters(such as cutting depth and pick angle),cutting responses(such as specific energy and instantaneous cutting rate),and rock mech-anical parameters collected from conical pick-cutting experiments.These parameters serve as input features for predicting the uniaxial compressive strength and tensile strength of rocks using regression fitting and machine learning methodologies.In addition,rock cuttabil-ity is classified using a combination of the analytic hierarchy process and fuzzy comprehensive evaluation method,and subsequently iden-tified through machine learning approaches.Various models are compared to determine the optimal predictive and classification models.The results indicate that the optimal model for uniaxial compressive strength and tensile strength prediction is the genetic algorithm-optimized backpropagation neural network model,and the optimal model for rock cuttability classification is the radial basis neural network model.展开更多
In order to understand the influence of brittleness and confining stress on rock cuttability,the indentation tests were carried out by a conical pick on the four types of rocks.Then,the experimental results were utili...In order to understand the influence of brittleness and confining stress on rock cuttability,the indentation tests were carried out by a conical pick on the four types of rocks.Then,the experimental results were utilized to take regression analysis.The eight sets of normalized regression models were established for reflecting the relationships of peak indentation force(PIF)and specific energy(SE)with brittleness index and uniaxial confining stress.The regression analyses present that these regression models have good prediction performance.The regressive results indicate that brittleness indices and uniaxial confining stress conditions have non-linear effects on the rock cuttability that is determined by PIF and SE.Finally,the multilayer perceptual neural network was used to measure the importance weights of brittleness index and uniaxial confining stress upon the influence for rock cuttability.The results indicate that the uniaxial confining stress is more significant than brittleness index for influencing the rock cuttability.展开更多
The rock indentation tests by a conical pick were conducted to investigate the rock cuttability correlated to confining stress conditions and rock strength.Based on the test results,the regression analyses,support vec...The rock indentation tests by a conical pick were conducted to investigate the rock cuttability correlated to confining stress conditions and rock strength.Based on the test results,the regression analyses,support vector machine(SVM)and generalized regression neural network(GRNN)were used to find the relationship among rock cuttability,uniaxial confining stress applied to rock,uniaxial compressive strength(UCS)and tensile strength of rock material.It was found that the regression and SVM-based models can accurately reflect the variation law of rock cuttability,which presented decreases followed by increases with the increase in uniaxial confining stress and the negative correlation to UCS and tensile strength of rock material.Based on prediction models for revealing the optimal stress condition and determining the cutting parameters,the axial boom roadheader with many conical picks mounted was satisfactorily utilized to perform rock cutting in hard phosphate rock around pillar.展开更多
A new comprehensive set of data（n = 178） is compiled by adding a data set（n = 72） collected by Arioglu et al.（2007） to the data set（n = 106） presented in Rezazadeh and Eslami（2017）. Then, the compiled data s...A new comprehensive set of data（n = 178） is compiled by adding a data set（n = 72） collected by Arioglu et al.（2007） to the data set（n = 106） presented in Rezazadeh and Eslami（2017）. Then, the compiled data set is evaluated regardless of the variation in lithology/strength. The proposed empirical equation in this study comprises a wider range of uniaxial compressive strength（UCS）（0.15 MPa 〈 σ_（rc） 〈156 MPa） and various rock types. Rock mass cuttability index（RMCI） is correlated with shaft resistance（r_s） to predict the shaft resistance of rock-socketed piles. The prediction capacity of the RMCI versus r_s equation is also found to be in a fair good agreement with the presented data in Rezazadeh and Eslami（2017）. Since the RMCI is a promising parameter in the prediction of shaft resistance, the researchers in the rock-socketed pile design area should consider this parameter in the further investigations.展开更多
Semi-deep foundations socketed in rocks are considered to be a viable option for the foundations in the presence of heavy loads imposed by high-rise buildings and special structures, due to the low settlement and high...Semi-deep foundations socketed in rocks are considered to be a viable option for the foundations in the presence of heavy loads imposed by high-rise buildings and special structures, due to the low settlement and high bearing capacity. In this study, the unconfined compressive strength（UCS） and rock mass cuttability index（RMCI） have been applied to investigating the shaft bearing capacity. For this purpose, a comprehensive database of 178 full-scale load tests is compiled by adding a data set（n = 72）collected by Arioglu et al.（2007） to the data set（n = 106） presented in Rezazadeh and Eslami（2017）.Using the database, the applicability and accuracy of the existing empirical methods are evaluated and new relations are derived between the shaft bearing capacity and UCS/RMCI. Moreover, a general equation in case of unknown rock types is proposed and it is verified by another set of data（series 3 in Rezazadeh and Eslami（2017））. Since rock-socketed shafts are supported by rock mass（not intact rock）,a reduction factor for the compressive strength is suggested and verified in which the effect of discontinuities is considered using the modified UCS, based upon RMR and RQD to consider the effect of the rock mass properties.展开更多
基金supported by financial grants from the National Natural Science Foundation of China(Grant Nos.52334003 and 52104111)the National Key R&D Program of China(Grant No.2022YFC2905600)。
文摘Water-weakening presents a promising strategy for the in-situ improvement of rock cuttability.This study unveils the influences of water saturation on the mechanical response and fragmentation characteristics of rock samples.A series of rock-cutting tests using conical pick indentation was conducted on three types of sandstone samples under both dry and water-saturated conditions.The relationships between cutting force and indentation depth,as well as typical cuttability indices are determined and compared for dry and water-saturated samples.The experimental results reveal that the presence of water facilitates shearing failure in rock samples,as well as alleviates the fluctuations in the cutting force-indentation depth curve Furthermore,the peak cutting force(F_(p)),cutting work(W_(p)),and specific energy(SE)undergo apparent decrease after water saturation,whereas the trend in the indentation depth at rock failure(D_(f))varies across different rock types.Additionally,the water-induced percentage reductions in F_(p)and SE correlate positively with the quartz and swelling clay content within the rocks,suggesting that the cuttability improvement due to water saturation is attributed to the combined effects of stress corrosion and frictional reduction.These findings carry significant implications for improving rock cuttability in mechanized excavation of hard rock formations.
基金supported by the National Natural Science Foundation of China(Nos.52174099 and 52474168)the Science and Technology Innovation Program of Hunan Province,China(No.2023RC3050)+1 种基金the Natural Science Foundation of Hunan,China(No.2024JJ4064)the Open Fund of the State Key Laboratory of Safety Technology of Metal Mines(No.kfkt2023-01).
文摘Real-time identification of rock strength and cuttability based on monitoring while cutting during excavation is essential for key procedures such as the precise adjustment of excavation parameters and the in-situ modification of hard rocks.This study proposes an in-telligent approach for predicting rock strength and cuttability.A database comprising 132 data sets is established,containing cutting para-meters(such as cutting depth and pick angle),cutting responses(such as specific energy and instantaneous cutting rate),and rock mech-anical parameters collected from conical pick-cutting experiments.These parameters serve as input features for predicting the uniaxial compressive strength and tensile strength of rocks using regression fitting and machine learning methodologies.In addition,rock cuttabil-ity is classified using a combination of the analytic hierarchy process and fuzzy comprehensive evaluation method,and subsequently iden-tified through machine learning approaches.Various models are compared to determine the optimal predictive and classification models.The results indicate that the optimal model for uniaxial compressive strength and tensile strength prediction is the genetic algorithm-optimized backpropagation neural network model,and the optimal model for rock cuttability classification is the radial basis neural network model.
基金Project(51904333) supported by the National Natural Science Foundation of China。
文摘In order to understand the influence of brittleness and confining stress on rock cuttability,the indentation tests were carried out by a conical pick on the four types of rocks.Then,the experimental results were utilized to take regression analysis.The eight sets of normalized regression models were established for reflecting the relationships of peak indentation force(PIF)and specific energy(SE)with brittleness index and uniaxial confining stress.The regression analyses present that these regression models have good prediction performance.The regressive results indicate that brittleness indices and uniaxial confining stress conditions have non-linear effects on the rock cuttability that is determined by PIF and SE.Finally,the multilayer perceptual neural network was used to measure the importance weights of brittleness index and uniaxial confining stress upon the influence for rock cuttability.The results indicate that the uniaxial confining stress is more significant than brittleness index for influencing the rock cuttability.
基金financial supports from the National Natural Science Foundation of China(Nos.51904333,51774326)。
文摘The rock indentation tests by a conical pick were conducted to investigate the rock cuttability correlated to confining stress conditions and rock strength.Based on the test results,the regression analyses,support vector machine(SVM)and generalized regression neural network(GRNN)were used to find the relationship among rock cuttability,uniaxial confining stress applied to rock,uniaxial compressive strength(UCS)and tensile strength of rock material.It was found that the regression and SVM-based models can accurately reflect the variation law of rock cuttability,which presented decreases followed by increases with the increase in uniaxial confining stress and the negative correlation to UCS and tensile strength of rock material.Based on prediction models for revealing the optimal stress condition and determining the cutting parameters,the axial boom roadheader with many conical picks mounted was satisfactorily utilized to perform rock cutting in hard phosphate rock around pillar.
基金support of Yapi Merkezi Construction and Industry Inc.,Istanbul,Turkey
文摘A new comprehensive set of data（n = 178） is compiled by adding a data set（n = 72） collected by Arioglu et al.（2007） to the data set（n = 106） presented in Rezazadeh and Eslami（2017）. Then, the compiled data set is evaluated regardless of the variation in lithology/strength. The proposed empirical equation in this study comprises a wider range of uniaxial compressive strength（UCS）（0.15 MPa 〈 σ_（rc） 〈156 MPa） and various rock types. Rock mass cuttability index（RMCI） is correlated with shaft resistance（r_s） to predict the shaft resistance of rock-socketed piles. The prediction capacity of the RMCI versus r_s equation is also found to be in a fair good agreement with the presented data in Rezazadeh and Eslami（2017）. Since the RMCI is a promising parameter in the prediction of shaft resistance, the researchers in the rock-socketed pile design area should consider this parameter in the further investigations.
文摘Semi-deep foundations socketed in rocks are considered to be a viable option for the foundations in the presence of heavy loads imposed by high-rise buildings and special structures, due to the low settlement and high bearing capacity. In this study, the unconfined compressive strength（UCS） and rock mass cuttability index（RMCI） have been applied to investigating the shaft bearing capacity. For this purpose, a comprehensive database of 178 full-scale load tests is compiled by adding a data set（n = 72）collected by Arioglu et al.（2007） to the data set（n = 106） presented in Rezazadeh and Eslami（2017）.Using the database, the applicability and accuracy of the existing empirical methods are evaluated and new relations are derived between the shaft bearing capacity and UCS/RMCI. Moreover, a general equation in case of unknown rock types is proposed and it is verified by another set of data（series 3 in Rezazadeh and Eslami（2017））. Since rock-socketed shafts are supported by rock mass（not intact rock）,a reduction factor for the compressive strength is suggested and verified in which the effect of discontinuities is considered using the modified UCS, based upon RMR and RQD to consider the effect of the rock mass properties.
