The classical deviatoric hardening models are capable of characterizing the mechanical response of granular materials for a broad range of degrees of compaction.This work finds that it has limitations in accurately pr...The classical deviatoric hardening models are capable of characterizing the mechanical response of granular materials for a broad range of degrees of compaction.This work finds that it has limitations in accurately predicting the volumetric deformation characteristics under a wide range of confining/consolidation pressures.The issue stems from the pressure independent hardening law in the classical deviatoric hardening model.To overcome this problem,we propose a refined deviatoric hardening model in which a pressure-dependent hardening law is developed based on experimental observations.Comparisons between numerical results and laboratory triaxial tests indicate that the improved model succeeds in capturing the volumetric deformation behavior under various confining/consolidation pressure conditions for both dense and loose sands.Furthermore,to examine the importance of the improved deviatoric hardening model,it is combined with the bounding surface plasticity theory to investigate the mechanical response of loose sand under complex cyclic loadings and different initial consolidation pressures.It is proved that the proposed pressure-dependent deviatoric hardening law is capable of predicting the volumetric deformation characteristics to a satisfactory degree and plays an important role in the simulation of complex deformations for granular geomaterials.展开更多
First the deviator strain energy is introduced, then the problem of plane-crack critical growth was discussed, a path independent line integral J* was defined, furthermore its conservation was proved strictly. As appl...First the deviator strain energy is introduced, then the problem of plane-crack critical growth was discussed, a path independent line integral J* was defined, furthermore its conservation was proved strictly. As application examples, Mode-I stress intensity factors of cracked beams were obtained with present approach. The results are shown to agree well with those available in the open literature.展开更多
Pitch deviation at rack joints(PDRJ) is a common error in rack railways. It directly affects the contact characteristics between the rack and gear and leads to accelerated surface wear. This threatens the stability an...Pitch deviation at rack joints(PDRJ) is a common error in rack railways. It directly affects the contact characteristics between the rack and gear and leads to accelerated surface wear. This threatens the stability and service life of the rack system, and the theoretical understanding of this issue remains limited. To address this gap, this study develops an improved tooth wear model that simultaneously accounts for the instantaneous variations in meshing stiffness and dynamic transmission error(DTE) induced by PDRJ, as well as the real-time correlation between gear-rack contact position and meshing excitation. Subsequently, the rack tooth load and wear characteristics are evaluated through the rack vehicle-track coupled dynamics and gear-rack contact model. The model's reliability is verified through field measurements. Moreover, the influence of varying PDRJ levels on load sharing factors, surface wear depth, and rack displacement is investigated. The results show that PDRJ disrupts the theoretical gear-rack meshing process, resulting in non-uniform load distribution and accelerated wear, particularly in the addendum and dedendum regions of the rack teeth. This study provides valuable insights into the rack surface wear mechanism under PDRJ.展开更多
The deformation characteristics and thermal response of anchor rods are crucial for ensuring the stability and safety of surrounding rock support structures.However,existing research has predominantly concentrated on ...The deformation characteristics and thermal response of anchor rods are crucial for ensuring the stability and safety of surrounding rock support structures.However,existing research has predominantly concentrated on the mechanical performance of anchor rods,with limited attention to the coupled evolution of strain and temperature fields during tensile deformation.This knowledge gap hinders a comprehensive understanding of the synergistic mechanical-thermal response mechanisms in anchor rods under loading conditions.To address this limitation,the present study systematically investigated the evolution of strain and temperature fields,along with their correlation,during the test of micro-negative Poisson's ratio(NPR)and ordinary Poisson's ratio(PR)anchor rods.Digital image correlation(DIC)and infrared thermography(IRT)techniques were employed for this exploration.The uniaxial tensile tests were conducted at two different rates,and the ordinary PR anchor rod(Q235 anchor rod)was established as a control group for comparative analysis.The findings reveal that the micro-NPR anchor rod exhibit strain localization at multiple locations during the tensile process,whereas Q235 anchors show local strain concentration in only one region.The standard deviation evolution curves for both the strain and temperature field exhibit two distinct phases in the two anchor rods.The evolution patterns between these two types of curves are basically consistent.The two standard deviation curves for the micro-NPR anchor rod display a wavy increase in the second phase,while for the Q235 anchor rod,they increase steadily until the specimen is damaged.The correlation analysis reveals that the standard deviations of strain and temperature differences for both types of anchor rods are significantly correlated.These findings demonstrate the synergistic evolution mechanism of deformation and thermal response,providing a potential foundation for utilizing thermal monitoring to assess the stability of rock support structures.展开更多
Although machine learning models have achieved high enough accuracy in predicting shield position deviations,their“black box”nature makes the prediction mechanisms and decision-making processes opaque,leading to wea...Although machine learning models have achieved high enough accuracy in predicting shield position deviations,their“black box”nature makes the prediction mechanisms and decision-making processes opaque,leading to weaker explanations and practicability.This study introduces a novel explainable deep learning framework comprising the Informer model with enhanced attention mechanisms(EAMInfor)and deep learning important features(DeepLIFT),aimed at improving the prediction accuracy of shield position deviations and providing interpretability for predictive results.The EAMInfor model attempts to integrate channel attention,spatial attention,and simple attention modules to improve the Informer model's performance.The framework is tested with the four different geological conditions datasets generated from the Xiamen metro line 3,China.Results show that the EAMInfor model outperforms the traditional Informer and comparison models.The analysis with the DeepLIFT method indicates that the push thrust of push cylinder and the earth chamber pressure are the most significant features,while the stroke length of the push cylinder demonstrated lower importance.Furthermore,the variation trends in the significance of data points within input sequences exhibit substantial differences between single and composite strata.This framework not only improves predictive accuracy but also strengthens the credibility and reliability of the results.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimila...Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.展开更多
To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy...To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.展开更多
Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address th...Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.展开更多
基金the funding support from Basic Science Center Program for Multiphase Media Evolution in Hypergravity of the National Natural Science Foundation of China(Grant No.51988101).
文摘The classical deviatoric hardening models are capable of characterizing the mechanical response of granular materials for a broad range of degrees of compaction.This work finds that it has limitations in accurately predicting the volumetric deformation characteristics under a wide range of confining/consolidation pressures.The issue stems from the pressure independent hardening law in the classical deviatoric hardening model.To overcome this problem,we propose a refined deviatoric hardening model in which a pressure-dependent hardening law is developed based on experimental observations.Comparisons between numerical results and laboratory triaxial tests indicate that the improved model succeeds in capturing the volumetric deformation behavior under various confining/consolidation pressure conditions for both dense and loose sands.Furthermore,to examine the importance of the improved deviatoric hardening model,it is combined with the bounding surface plasticity theory to investigate the mechanical response of loose sand under complex cyclic loadings and different initial consolidation pressures.It is proved that the proposed pressure-dependent deviatoric hardening law is capable of predicting the volumetric deformation characteristics to a satisfactory degree and plays an important role in the simulation of complex deformations for granular geomaterials.
文摘First the deviator strain energy is introduced, then the problem of plane-crack critical growth was discussed, a path independent line integral J* was defined, furthermore its conservation was proved strictly. As application examples, Mode-I stress intensity factors of cracked beams were obtained with present approach. The results are shown to agree well with those available in the open literature.
基金supported by the National Natural Science Foundation of China (Grant No.52388102)the Sichuan Science and Technology Program (Grant No.2024NSFTD0011)the Fundamental Research Funds for the State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University (Grant No.2023TPL-T11)。
文摘Pitch deviation at rack joints(PDRJ) is a common error in rack railways. It directly affects the contact characteristics between the rack and gear and leads to accelerated surface wear. This threatens the stability and service life of the rack system, and the theoretical understanding of this issue remains limited. To address this gap, this study develops an improved tooth wear model that simultaneously accounts for the instantaneous variations in meshing stiffness and dynamic transmission error(DTE) induced by PDRJ, as well as the real-time correlation between gear-rack contact position and meshing excitation. Subsequently, the rack tooth load and wear characteristics are evaluated through the rack vehicle-track coupled dynamics and gear-rack contact model. The model's reliability is verified through field measurements. Moreover, the influence of varying PDRJ levels on load sharing factors, surface wear depth, and rack displacement is investigated. The results show that PDRJ disrupts the theoretical gear-rack meshing process, resulting in non-uniform load distribution and accelerated wear, particularly in the addendum and dedendum regions of the rack teeth. This study provides valuable insights into the rack surface wear mechanism under PDRJ.
基金supported by State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining&Technology,Beijing(Grant No.SKLGDUEK2120)。
文摘The deformation characteristics and thermal response of anchor rods are crucial for ensuring the stability and safety of surrounding rock support structures.However,existing research has predominantly concentrated on the mechanical performance of anchor rods,with limited attention to the coupled evolution of strain and temperature fields during tensile deformation.This knowledge gap hinders a comprehensive understanding of the synergistic mechanical-thermal response mechanisms in anchor rods under loading conditions.To address this limitation,the present study systematically investigated the evolution of strain and temperature fields,along with their correlation,during the test of micro-negative Poisson's ratio(NPR)and ordinary Poisson's ratio(PR)anchor rods.Digital image correlation(DIC)and infrared thermography(IRT)techniques were employed for this exploration.The uniaxial tensile tests were conducted at two different rates,and the ordinary PR anchor rod(Q235 anchor rod)was established as a control group for comparative analysis.The findings reveal that the micro-NPR anchor rod exhibit strain localization at multiple locations during the tensile process,whereas Q235 anchors show local strain concentration in only one region.The standard deviation evolution curves for both the strain and temperature field exhibit two distinct phases in the two anchor rods.The evolution patterns between these two types of curves are basically consistent.The two standard deviation curves for the micro-NPR anchor rod display a wavy increase in the second phase,while for the Q235 anchor rod,they increase steadily until the specimen is damaged.The correlation analysis reveals that the standard deviations of strain and temperature differences for both types of anchor rods are significantly correlated.These findings demonstrate the synergistic evolution mechanism of deformation and thermal response,providing a potential foundation for utilizing thermal monitoring to assess the stability of rock support structures.
基金supported by the National Natural Science Foundation of China(Grant Nos.52378392,52408356)the Foal Eagle Program Youth Top-notch Talent Project of Fujian Province,China(Grant No.00387088).
文摘Although machine learning models have achieved high enough accuracy in predicting shield position deviations,their“black box”nature makes the prediction mechanisms and decision-making processes opaque,leading to weaker explanations and practicability.This study introduces a novel explainable deep learning framework comprising the Informer model with enhanced attention mechanisms(EAMInfor)and deep learning important features(DeepLIFT),aimed at improving the prediction accuracy of shield position deviations and providing interpretability for predictive results.The EAMInfor model attempts to integrate channel attention,spatial attention,and simple attention modules to improve the Informer model's performance.The framework is tested with the four different geological conditions datasets generated from the Xiamen metro line 3,China.Results show that the EAMInfor model outperforms the traditional Informer and comparison models.The analysis with the DeepLIFT method indicates that the push thrust of push cylinder and the earth chamber pressure are the most significant features,while the stroke length of the push cylinder demonstrated lower importance.Furthermore,the variation trends in the significance of data points within input sequences exhibit substantial differences between single and composite strata.This framework not only improves predictive accuracy but also strengthens the credibility and reliability of the results.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
基金sponsored by the National Natural Science Foundation of China[grant number U2442218]。
文摘Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.
基金Supported by State Grid Zhejiang Electric Power Co.,Ltd.Science and Technology Project Funding(No.B311DS230005).
文摘To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.
基金supported by the Key R&D Program of Zhejiang Province(Nos.2023C01166 and 2024SJCZX0046)the Zhejiang Provincial Natural Science Foundation of China(Nos.LDT23E05013E05 and LD24E050009)the Natural Science Foundation of Ningbo(No.2021J150),China.
文摘Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.
