Based on the steady-state seepage method, we used the Mechanical Testing and Simulation 815.02 System and a self-designed seepage instrument for over-broken stone to measure seepage properties of water flows in three ...Based on the steady-state seepage method, we used the Mechanical Testing and Simulation 815.02 System and a self-designed seepage instrument for over-broken stone to measure seepage properties of water flows in three types of crushed rock samples. Three methods of confidence interval in describing permeability coefficients are presented: the secure interval, the calculated interval and the systemic interval. The lower bound of the secure interval can be applied to water-inrush and the upper bound can solve the problem of connectivity. For the calculated interval, as the axial pressure increases, the length of confidence interval is shortened and the upper and lower bounds are reduced. For the systemic interval, the length of its confidence interval, as well as the upper and lower bounds, clearly vary under low axial pressure but are fairly similar under high axial pressure. These three methods provide useful information and references for analyzing the permeability coefficient of over-broken rock.展开更多
In pumped storage projects,the permeability of rock masses is a crucial parameter in engineering design and construction.The rock mass permeability coefficient(K)is influenced by various geological parameters,and prev...In pumped storage projects,the permeability of rock masses is a crucial parameter in engineering design and construction.The rock mass permeability coefficient(K)is influenced by various geological parameters,and previous studies aimed to establish an accurate relationship between K and geological parameters.This study uses the improved sparrow search algorithm(ISSA)to optimize the parameter settings of the deep extreme learning machine(DELM),constructing a prediction model with flexible parameter selection and high accuracy.First,the Spearman method is applied to analyze the correlation between geological parameters.A sample database is built by comprehensively selecting four geological indexes:burial depth,rock quality designation(RQD),fracture density characteristic index(FD),and rock mass integrity designation(RID).Hence,the defects of the sparrow search algorithm(SSA)are enhanced using the improved strategy,and the initial input weights of the DELM are optimized.Finally,the proposed ISSA–DELM model is employed to predict the permeability coefficient of rock mass in the entire study area.The results showed that the predictive performance of the model is superior to that of the DELM and SSA–DELM.Therefore,this model successfully provides insights into the distribution characteristics of rock mass permeability at engineering sites.展开更多
Using an MTS816.03 test system and self-designed seepage apparatus, seepage tests of saturated broken rocks were conducted, and the influence of lithology, axial stress, grain size distribution and loading rate on see...Using an MTS816.03 test system and self-designed seepage apparatus, seepage tests of saturated broken rocks were conducted, and the influence of lithology, axial stress, grain size distribution and loading rate on seepage characteristics was analyzed. The results show that： （1） Under the same axial stress （12 MPa）, the permeability of different lithologic samples increases in the order： gangue 〈 mudstone 〈 sandstone 〈 limestone. The permeability of gangue is 3 magnitudes lower than that of limestone. The absolute value of the non-Darcy coefficient β increases in the order： limestone 〈 sandstone 〈 mudstone 〈 gangue. The non-Darcy coefficient β of limestone, which is positive, is 5 magnitudes lower than that of gangue. （2） With increasing axial stress, the permeability of saturated broken sandstone decreases, and the absolute value of the non-Darcy coefficient β increases. After the axial stress exceeds 12 MPa, the curves of permeability and non-Darcy coefficient β all tend to be stable. （3） With increasing Talbol power exponent, the permeability increases, and the absolute value of the non-Darcy coefficient β decreases. （4） With increasing loading, the permeability increases, and the absolute value of the non-Darcy coefficient β decreases. When the loading rate is 0.5 kN/s, the non-Darcy coefficient β is positive.展开更多
基金Financial support for this work, provided by the National Natural Science Foundation of China (Nos. 50774083 and 41074040)the Program for New Century Excellent Talents in University (No. NCET-07-0803)the National Key Basic Research Program (No. 2009CB219605)
文摘Based on the steady-state seepage method, we used the Mechanical Testing and Simulation 815.02 System and a self-designed seepage instrument for over-broken stone to measure seepage properties of water flows in three types of crushed rock samples. Three methods of confidence interval in describing permeability coefficients are presented: the secure interval, the calculated interval and the systemic interval. The lower bound of the secure interval can be applied to water-inrush and the upper bound can solve the problem of connectivity. For the calculated interval, as the axial pressure increases, the length of confidence interval is shortened and the upper and lower bounds are reduced. For the systemic interval, the length of its confidence interval, as well as the upper and lower bounds, clearly vary under low axial pressure but are fairly similar under high axial pressure. These three methods provide useful information and references for analyzing the permeability coefficient of over-broken rock.
文摘In pumped storage projects,the permeability of rock masses is a crucial parameter in engineering design and construction.The rock mass permeability coefficient(K)is influenced by various geological parameters,and previous studies aimed to establish an accurate relationship between K and geological parameters.This study uses the improved sparrow search algorithm(ISSA)to optimize the parameter settings of the deep extreme learning machine(DELM),constructing a prediction model with flexible parameter selection and high accuracy.First,the Spearman method is applied to analyze the correlation between geological parameters.A sample database is built by comprehensively selecting four geological indexes:burial depth,rock quality designation(RQD),fracture density characteristic index(FD),and rock mass integrity designation(RID).Hence,the defects of the sparrow search algorithm(SSA)are enhanced using the improved strategy,and the initial input weights of the DELM are optimized.Finally,the proposed ISSA–DELM model is employed to predict the permeability coefficient of rock mass in the entire study area.The results showed that the predictive performance of the model is superior to that of the DELM and SSA–DELM.Therefore,this model successfully provides insights into the distribution characteristics of rock mass permeability at engineering sites.
基金provided by the National Basic Research Program of China (No.2013CB227900)the Ordinary University Graduate Student Research Innovation Project in Jiangsu Province for 2014 (No.KYLX_1370)the National Natural Science Foundation of China (Nos.11502229 and 51404266)
文摘Using an MTS816.03 test system and self-designed seepage apparatus, seepage tests of saturated broken rocks were conducted, and the influence of lithology, axial stress, grain size distribution and loading rate on seepage characteristics was analyzed. The results show that： （1） Under the same axial stress （12 MPa）, the permeability of different lithologic samples increases in the order： gangue 〈 mudstone 〈 sandstone 〈 limestone. The permeability of gangue is 3 magnitudes lower than that of limestone. The absolute value of the non-Darcy coefficient β increases in the order： limestone 〈 sandstone 〈 mudstone 〈 gangue. The non-Darcy coefficient β of limestone, which is positive, is 5 magnitudes lower than that of gangue. （2） With increasing axial stress, the permeability of saturated broken sandstone decreases, and the absolute value of the non-Darcy coefficient β increases. After the axial stress exceeds 12 MPa, the curves of permeability and non-Darcy coefficient β all tend to be stable. （3） With increasing Talbol power exponent, the permeability increases, and the absolute value of the non-Darcy coefficient β decreases. （4） With increasing loading, the permeability increases, and the absolute value of the non-Darcy coefficient β decreases. When the loading rate is 0.5 kN/s, the non-Darcy coefficient β is positive.
