It is important to analyze the damage evolution process of surrounding rock under different water content for the stability of engineering rock mass.Based on digital speckle correlation(DSCM),acoustic emission(AE)and ...It is important to analyze the damage evolution process of surrounding rock under different water content for the stability of engineering rock mass.Based on digital speckle correlation(DSCM),acoustic emission(AE)and electromagnetic radiation(EMR),uniaxial hierarchical cyclic loading and unloading tests were carried out on sandstones with different fracture numbers under dry,natural and saturated water content,to explore the fracture propagation,failure precursor characteristics and damage response mechanism under the influence of water content effect.The results show that with the increase of water content,the peak stress and crack initiation stress decrease gradually,and the decreases are 15.28%-21.11%and 17.64%-23.04%,respectively.The peak strain and crack initiation strain increase gradually,and the increases are 19.85%-44.53%and 19.15%-41.94%,respectively.The precracked rock with different water content is mainly characterized by tensile failure at different loading stages.However,with the increase of water content,the proportion of shear cracks gradually increases,while acoustic emission events gradually decrease,the dissipative energy and energy storage limits of the rock under peak load gradually decrease,and the charge signal increases significantly,which is because the lubrication effect of water reduces the friction coefficient between crack surfaces.展开更多
To further investigate the forming mechanism and springback characteristics of strips under multi-square punch forming (MSPF) considering partial-unloading effects, a series of concave form ing tests of strips are con...To further investigate the forming mechanism and springback characteristics of strips under multi-square punch forming (MSPF) considering partial-unloading effects, a series of concave form ing tests of strips are conducted on the MSPF machine. This paper aims to reveal the physical mecha nism of the elastic-plastic deformation in the MSPF process considering the effect of the forming ap proaches, and derive appropriate mathematical interpretations. The theoretical model is firstly estab lished to analyse the concave forming mechanism and springback characteristics of the strip, and its accuracy is then validated by experimental data. The forming history and load evolutions are depicted to explore the required forming capacity through the proposed analytical method. Besides, the paramet ric studies are carried out to discuss their effects on the springback of the strip. The results suggest that the deformation paths of the strip are influenced by the forming approach, and the springback of the strip in convex forming is larger than that in concave forming.展开更多
With the increase of underground engineering construction depth,the phenomenon of surrounding rock sudden failure caused by supporting structure failure occurs frequently.The conventional unloading con-fining pressure...With the increase of underground engineering construction depth,the phenomenon of surrounding rock sudden failure caused by supporting structure failure occurs frequently.The conventional unloading con-fining pressure(CUCP)test cannot simulate the plastic yielding and instantaneous unloading process of supporting structure to rock.Thus,a high stress loading-instantaneous unloading confining pressure(HSL-IUCP)test method was proposed and applied by considering bolt’s fracture under stress.The wall thickness of confining pressure plates and the material of bolts were changed to realize different confin-ing pressure loading stiffness(CPLS)and lateral maximum allowable deformation(LMAD).The superio-rity of HSL-ICPU method is verified compared with CUCP.The rock failure mechanism caused by sudden failure of supporting structure is obtained.The results show that when CPLS increases from 1.35 to 2.33 GN/m,rock’s peak strength and elastic modulus increase by 25.18%and 23.70%,respectively.The fracture characteristics change from tensile failure to tensile-shear mixed failure.When LMAD decreases from 0.40 to 0.16 mm,rock’s residual strength,peak strain,and residual strain decrease by 91.80%,16.94%,and 21.92%,respectively,and post-peak drop modulus increases by 140.47%.The test results obtained by this method are closer to rock’s real mechanical response characteristics compared with CUCP.展开更多
Multiple filling of gobs will lead to a layered structure of the backfill.To explore the influence of layering structure on the mechanical properties and failure modes of backfill,different backfill specimens were pre...Multiple filling of gobs will lead to a layered structure of the backfill.To explore the influence of layering structure on the mechanical properties and failure modes of backfill,different backfill specimens were prepared with a cement/sand ratio of 1:4,a slurry concentration of 75%,and backfilling times of 1,2,3 and 4,separately.Triaxial cyclic loading and unloading experiments were carried out.The results show that with an increase in backfilling time,the peak strength of backfill decreases as a polynomial function and the peak strain increases as an exponential function.The cyclic load enhances the linear characteristic of backfill deformation.The loading and unloading deformation moduli have a linear negative correlation with the backfilling time.The unloading deformation modulus is always slightly higher than the loading deformation modulus.The failure modes of stratified backfill are mainly characterized by conjugate shear failure at the upper layer and tensile failure across the layer plane,and there is usually no damage in the lower layer away from the loading area.展开更多
This paper investigates mechanical behaviours of sandstone during post-peak cyclic loading and unloading subjected to hydromechanical coupling effect, confirming the peak and residual strengths reduction laws of sands...This paper investigates mechanical behaviours of sandstone during post-peak cyclic loading and unloading subjected to hydromechanical coupling effect, confirming the peak and residual strengths reduction laws of sandstone with water pressure, and revealing the influence of water pressure on the upper limit stress and deformation characteristics of sandstone during post-peak cyclic loading and unloading.Regarding the rock strength, the experimental study confirms that the peak strength σ_(p) and residual strength σ_(r) decrease as water pressure P increases. Especially, the normalized strength parameters σ_(p)/σ_(pk) and σ_(r)/σ_(re) was negatively and linearly correlated with the P/σ_(3). Moreover, the Hoek-Brown strength criterion can be applied to describe the relationship between effective peak strength and effective confining stress. During post-peak cyclic loading and unloading, both the upper limit stress σ_(p(i)) and crack damage threshold stress σ_(cd(i)) of each cycle tend to decrease with the increasing cycle number. A hysteresis loop exists among the loading and unloading stress–strain curves, indicating the unloading deformation modulus E_(unload) is larger than the loading deformation modulus E_(load). Based on experimental results,a post-peak strength prediction model related to water pressure and plastic shear strain is established.展开更多
In coal mining,rock strata are fractured under cyclic loading and unloading to form fracture channels.Fracture channels are the main flow narrows for gas.Therefore,expounding the flow conductivity of fracture channels...In coal mining,rock strata are fractured under cyclic loading and unloading to form fracture channels.Fracture channels are the main flow narrows for gas.Therefore,expounding the flow conductivity of fracture channels in rocks on fluids is significant for gas flow in rock strata.In this regard,graded incremental cyclic loading and unloading experiments were conducted on sandstones with different initial stress levels.Then,the three-dimensional models for fracture channels in sandstones were established.Finally,the fracture channel percentages were used to reflect the flow conductivity of fracture channels.The study revealed how the particle size distribution of fractured sandstone affects the formation and expansion of fracture channels.It was found that a smaller proportion of large blocks and a higher proportion of small blocks after sandstone fails contribute more to the formation of fracture channels.The proportion of fracture channels in fractured rock can indicate the flow conductivity of those channels.When the proportion of fracture channels varies gently,fluids flow evenly through those channels.However,if the proportion of fracture channels varies significantly,it can greatly affect the flow rate of fluids.The research results contribute to revealing the morphological evolution and flow conductivity of fracture channels in sandstone and then provide a theoretical basis for clarifying the gas flow pattern in the rock strata of coal mines.展开更多
The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mech...The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.展开更多
By using MTS815 rock mechanics test system,a series of acoustic emission(AE) location experiments were performed under unloading confining pressure,increasing the axial stress.The AE space-time evolution regularities ...By using MTS815 rock mechanics test system,a series of acoustic emission(AE) location experiments were performed under unloading confining pressure,increasing the axial stress.The AE space-time evolution regularities and energy releasing characteristics during deformation and failure process of coal of different loading rates are compared,the influence mechanism of loading rates on the microscopic crack evolution were studied,combining the AE characteristics and the macroscopic failure modes of the specimens,and the precursory characteristics of coal failure were also analyzed quantitatively.The results indicate that as the loading rate is higher,the AE activity and the main fracture will begin earlier.The destruction of coal body is mainly the function of shear strain at lower loading rate and tension strain at higher rate,and will transform from brittleness to ductility at critical velocities.When the deformation of the coal is mainly plasticity,the amplitude of the AE ringing counting rate increases largely and the AE energy curves appear an obvious ''step'',which can be defined as the first failure precursor point.Statics of AE information shows that the strongest AE activity begins when the axial stress level was 92-98%,which can be defined as the other failure precursor point.As the loading rate is smaller,the coal more easily reaches the latter precursor point after the first one,so attention should be aroused to prevent dynamic disaster in coal mining when the AE activity reaches the first precursor point.展开更多
Structural health monitoring(SHM)in service has attracted increasing attention for years.Load localization on a structure is studied hereby.Two algorithms,i.e.,support vector machine(SVM)method and back propagation ne...Structural health monitoring(SHM)in service has attracted increasing attention for years.Load localization on a structure is studied hereby.Two algorithms,i.e.,support vector machine(SVM)method and back propagation neural network(BPNN)algorithm,are proposed to identify the loading positions individually.The feasibility of the suggested methods is evaluated through an experimental program on a carbon fiber reinforced plastic laminate.The experimental tests involve in application of four optical fiber-based sensors for strain measurement at discrete points.The sensors are specially designed fiber Bragg grating(FBG)in small diameter.The small-diameter FBG sensors are arrayed in 2-D on the laminate surface.The testing results indicate that the loading position could be detected by the proposed method.Using SVM method,the 2-D FBG sensors can approximate the loading location with maximum error less than 14 mm.However,the maximum localization error could be limited to about 1 mm by applying the BPNN algorithm.It is mainly because the convergence conditions(mean square error)can be set in advance,while SVM cannot.展开更多
In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous network...In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth.To address this problem,a network-aware adaptive PS load distribution scheme is proposed,which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states.We evaluate the proposed scheme on MXNet,known as a realworld distributed training platform,and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.展开更多
基金financially supported by National Natural Science Foundation of China(No.52304136)Young Talent of Lifting Engineering for Science and Technology in Shandong,China(No.SDAST2024QTA060)Key Project of Research and Development in Liaocheng(No.2023YD02)。
文摘It is important to analyze the damage evolution process of surrounding rock under different water content for the stability of engineering rock mass.Based on digital speckle correlation(DSCM),acoustic emission(AE)and electromagnetic radiation(EMR),uniaxial hierarchical cyclic loading and unloading tests were carried out on sandstones with different fracture numbers under dry,natural and saturated water content,to explore the fracture propagation,failure precursor characteristics and damage response mechanism under the influence of water content effect.The results show that with the increase of water content,the peak stress and crack initiation stress decrease gradually,and the decreases are 15.28%-21.11%and 17.64%-23.04%,respectively.The peak strain and crack initiation strain increase gradually,and the increases are 19.85%-44.53%and 19.15%-41.94%,respectively.The precracked rock with different water content is mainly characterized by tensile failure at different loading stages.However,with the increase of water content,the proportion of shear cracks gradually increases,while acoustic emission events gradually decrease,the dissipative energy and energy storage limits of the rock under peak load gradually decrease,and the charge signal increases significantly,which is because the lubrication effect of water reduces the friction coefficient between crack surfaces.
文摘To further investigate the forming mechanism and springback characteristics of strips under multi-square punch forming (MSPF) considering partial-unloading effects, a series of concave form ing tests of strips are conducted on the MSPF machine. This paper aims to reveal the physical mecha nism of the elastic-plastic deformation in the MSPF process considering the effect of the forming ap proaches, and derive appropriate mathematical interpretations. The theoretical model is firstly estab lished to analyse the concave forming mechanism and springback characteristics of the strip, and its accuracy is then validated by experimental data. The forming history and load evolutions are depicted to explore the required forming capacity through the proposed analytical method. Besides, the paramet ric studies are carried out to discuss their effects on the springback of the strip. The results suggest that the deformation paths of the strip are influenced by the forming approach, and the springback of the strip in convex forming is larger than that in concave forming.
基金the National Natural Science Foundation of China(Nos.52374218,52174122 and 52374094)Outstanding Youth Fund of Shandong Natural Science Foundation(No.ZR2022YQ49)Taishan Scholar Project in Shandong Province(Nos.tspd20210313 and tsqn202211150).
文摘With the increase of underground engineering construction depth,the phenomenon of surrounding rock sudden failure caused by supporting structure failure occurs frequently.The conventional unloading con-fining pressure(CUCP)test cannot simulate the plastic yielding and instantaneous unloading process of supporting structure to rock.Thus,a high stress loading-instantaneous unloading confining pressure(HSL-IUCP)test method was proposed and applied by considering bolt’s fracture under stress.The wall thickness of confining pressure plates and the material of bolts were changed to realize different confin-ing pressure loading stiffness(CPLS)and lateral maximum allowable deformation(LMAD).The superio-rity of HSL-ICPU method is verified compared with CUCP.The rock failure mechanism caused by sudden failure of supporting structure is obtained.The results show that when CPLS increases from 1.35 to 2.33 GN/m,rock’s peak strength and elastic modulus increase by 25.18%and 23.70%,respectively.The fracture characteristics change from tensile failure to tensile-shear mixed failure.When LMAD decreases from 0.40 to 0.16 mm,rock’s residual strength,peak strain,and residual strain decrease by 91.80%,16.94%,and 21.92%,respectively,and post-peak drop modulus increases by 140.47%.The test results obtained by this method are closer to rock’s real mechanical response characteristics compared with CUCP.
基金the National Natural Science Foundation of China(No.51374033)the Key Projects of the National Key Research and Development Program(No.YS2017YFSF040004).
文摘Multiple filling of gobs will lead to a layered structure of the backfill.To explore the influence of layering structure on the mechanical properties and failure modes of backfill,different backfill specimens were prepared with a cement/sand ratio of 1:4,a slurry concentration of 75%,and backfilling times of 1,2,3 and 4,separately.Triaxial cyclic loading and unloading experiments were carried out.The results show that with an increase in backfilling time,the peak strength of backfill decreases as a polynomial function and the peak strain increases as an exponential function.The cyclic load enhances the linear characteristic of backfill deformation.The loading and unloading deformation moduli have a linear negative correlation with the backfilling time.The unloading deformation modulus is always slightly higher than the loading deformation modulus.The failure modes of stratified backfill are mainly characterized by conjugate shear failure at the upper layer and tensile failure across the layer plane,and there is usually no damage in the lower layer away from the loading area.
基金supported by the National Natural Science Foundation of China(Nos.52274118 and 52274145)the Construction Project of Chenzhou National Sustainable Development Agenda Innovation Demonstration Zone(No.2021sfQ18).
文摘This paper investigates mechanical behaviours of sandstone during post-peak cyclic loading and unloading subjected to hydromechanical coupling effect, confirming the peak and residual strengths reduction laws of sandstone with water pressure, and revealing the influence of water pressure on the upper limit stress and deformation characteristics of sandstone during post-peak cyclic loading and unloading.Regarding the rock strength, the experimental study confirms that the peak strength σ_(p) and residual strength σ_(r) decrease as water pressure P increases. Especially, the normalized strength parameters σ_(p)/σ_(pk) and σ_(r)/σ_(re) was negatively and linearly correlated with the P/σ_(3). Moreover, the Hoek-Brown strength criterion can be applied to describe the relationship between effective peak strength and effective confining stress. During post-peak cyclic loading and unloading, both the upper limit stress σ_(p(i)) and crack damage threshold stress σ_(cd(i)) of each cycle tend to decrease with the increasing cycle number. A hysteresis loop exists among the loading and unloading stress–strain curves, indicating the unloading deformation modulus E_(unload) is larger than the loading deformation modulus E_(load). Based on experimental results,a post-peak strength prediction model related to water pressure and plastic shear strain is established.
基金This work was financially supported by the National Natural Science Foundation of China(No.52074041)the Chongqing Talent Program(No.cstc2022ycjh-bgzxm0077)the Postgraduate Research and Innovation Foundation of Chongqing,China(No.CYS23060).
文摘In coal mining,rock strata are fractured under cyclic loading and unloading to form fracture channels.Fracture channels are the main flow narrows for gas.Therefore,expounding the flow conductivity of fracture channels in rocks on fluids is significant for gas flow in rock strata.In this regard,graded incremental cyclic loading and unloading experiments were conducted on sandstones with different initial stress levels.Then,the three-dimensional models for fracture channels in sandstones were established.Finally,the fracture channel percentages were used to reflect the flow conductivity of fracture channels.The study revealed how the particle size distribution of fractured sandstone affects the formation and expansion of fracture channels.It was found that a smaller proportion of large blocks and a higher proportion of small blocks after sandstone fails contribute more to the formation of fracture channels.The proportion of fracture channels in fractured rock can indicate the flow conductivity of those channels.When the proportion of fracture channels varies gently,fluids flow evenly through those channels.However,if the proportion of fracture channels varies significantly,it can greatly affect the flow rate of fluids.The research results contribute to revealing the morphological evolution and flow conductivity of fracture channels in sandstone and then provide a theoretical basis for clarifying the gas flow pattern in the rock strata of coal mines.
基金supported by the National Science and Technology Major Project of China(2016ZX05066005-001)Zhejiang Province Key Research and Development Plan(2021C03152)Zhoushan Science and Technology Project(2021C21011)
文摘The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.
文摘By using MTS815 rock mechanics test system,a series of acoustic emission(AE) location experiments were performed under unloading confining pressure,increasing the axial stress.The AE space-time evolution regularities and energy releasing characteristics during deformation and failure process of coal of different loading rates are compared,the influence mechanism of loading rates on the microscopic crack evolution were studied,combining the AE characteristics and the macroscopic failure modes of the specimens,and the precursory characteristics of coal failure were also analyzed quantitatively.The results indicate that as the loading rate is higher,the AE activity and the main fracture will begin earlier.The destruction of coal body is mainly the function of shear strain at lower loading rate and tension strain at higher rate,and will transform from brittleness to ductility at critical velocities.When the deformation of the coal is mainly plasticity,the amplitude of the AE ringing counting rate increases largely and the AE energy curves appear an obvious ''step'',which can be defined as the first failure precursor point.Statics of AE information shows that the strongest AE activity begins when the axial stress level was 92-98%,which can be defined as the other failure precursor point.As the loading rate is smaller,the coal more easily reaches the latter precursor point after the first one,so attention should be aroused to prevent dynamic disaster in coal mining when the AE activity reaches the first precursor point.
基金supported by the National Natural Science Foundation of China(Nos.11402112,51405223)
文摘Structural health monitoring(SHM)in service has attracted increasing attention for years.Load localization on a structure is studied hereby.Two algorithms,i.e.,support vector machine(SVM)method and back propagation neural network(BPNN)algorithm,are proposed to identify the loading positions individually.The feasibility of the suggested methods is evaluated through an experimental program on a carbon fiber reinforced plastic laminate.The experimental tests involve in application of four optical fiber-based sensors for strain measurement at discrete points.The sensors are specially designed fiber Bragg grating(FBG)in small diameter.The small-diameter FBG sensors are arrayed in 2-D on the laminate surface.The testing results indicate that the loading position could be detected by the proposed method.Using SVM method,the 2-D FBG sensors can approximate the loading location with maximum error less than 14 mm.However,the maximum localization error could be limited to about 1 mm by applying the BPNN algorithm.It is mainly because the convergence conditions(mean square error)can be set in advance,while SVM cannot.
基金partially supported by the computing power networks and new communication primitives project under Grant No. HC-CN-2020120001the National Natural Science Foundation of China under Grant No. 62102066Open Research Projects of Zhejiang Lab under Grant No. 2022QA0AB02
文摘In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth.To address this problem,a network-aware adaptive PS load distribution scheme is proposed,which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states.We evaluate the proposed scheme on MXNet,known as a realworld distributed training platform,and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.
