By taking a rolling-spring isolation system as the study object, the effects of the non-uniform distribution of rolling friction coefficient on its isolation performance were analyzed by a compiled computer program. T...By taking a rolling-spring isolation system as the study object, the effects of the non-uniform distribution of rolling friction coefficient on its isolation performance were analyzed by a compiled computer program. The results show that the errors associated with the structural maximum relative displacement, acceleration and residual displacement due to ignoring the friction variability sequentially grow. This rule is weakened by the spring action, however, the unreasonable spring constant will cause sympathetic vibration. Under the condition of large friction variability, in the calculation of the structural maximum relative displacement and acceleration, the friction variability should be considered. When the structural residual displacement is concerned, the variability of rolling friction coefficient should be fully considered regardless of the friction variability.展开更多
Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displ...Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.展开更多
Based on the internal temperature variation of a dam lagging behind the ambient temperature variation,the ambient temperature of continuous variation is disctetized,and the functional expression of the thermal displac...Based on the internal temperature variation of a dam lagging behind the ambient temperature variation,the ambient temperature of continuous variation is disctetized,and the functional expression of the thermal displacement component of the dam caused by single instantaneous temperature variation is obtained.Considering the temporal and spatial distribution law of the ambient temperature and its relation with air and water temperature,the function is expanded into a Taylor series.As a result,the improved thermal displacement component expression for a dam monitoring model is obtained.展开更多
A discontinuous deformation and displacement(DDD) analysis method is proposed for modelling the rock failure process. This method combines the rock failure process analysis(RFPA) method(based on finite element method)...A discontinuous deformation and displacement(DDD) analysis method is proposed for modelling the rock failure process. This method combines the rock failure process analysis(RFPA) method(based on finite element method) and discontinuous deformation analysis(DDA) method. RFPA is used to simulate crack initiation, propagation and coalescence processes of rock during the small deformation state. The DDA method is used to simulate the movement of blocks created by the multiple cracks modelled by the RFPA. The newly developed DDD method is particularly suitable for modelling both crack propagation and block movement during the rock failure process because of the natural and convenient coupling of continuous and discontinuous deformation analyses. The proposed method has been used to simulate crack initiation, propagation and coalescence within a slope as well as the block movement during the landslide process. Numerical modelling results indicate that the proposed DDD method can automatically simulate crack propagation and block movement during the rock failure process without degrading accuracy.展开更多
The effect of Ag nanoislands on the Raman of graphene was investigated in this work.Compared with that on the bare silicon wafer,Raman enhancement was observed in the graphene film that covered on Ag/Si surface with n...The effect of Ag nanoislands on the Raman of graphene was investigated in this work.Compared with that on the bare silicon wafer,Raman enhancement was observed in the graphene film that covered on Ag/Si surface with nanoscale Ag islands,which would be induced by the localized plasmon resonance in Ag nanostructures.The interaction between the graphene sheet and Ag/Si substrate was further studied.The peak shift and line shape of Raman spectroscopy indicated a nonuniform strain distribution in the Ag/Si supported graphene film.展开更多
In this paper, the author at first develops a method to study convergence of the cascadealgorithm in a Banach space without stable assumption on the initial (see Theorem 2.1), andthen applies the previous result on th...In this paper, the author at first develops a method to study convergence of the cascadealgorithm in a Banach space without stable assumption on the initial (see Theorem 2.1), andthen applies the previous result on the convergence to characterizing compactly supportedrefinable distributions in fractional Sobolev spaces and Holder continuous spaces (see Theorems3.1, 3.3, and 3.4). Finally the author applies the above characterization to choosing appropriateinitial to guarantee the convergence of the cascade algorithm (see Theorem 4.2).展开更多
基金Projects(51308549,51378504,51478475) supported by the National Natural Science Foundation of ChinaProject(2015JJ3159) supported by the Natural Science Foundation of Hunan Province,ChinaProject(2015CX006) supported by the Innovation-driven Plan in Central South University,China
文摘By taking a rolling-spring isolation system as the study object, the effects of the non-uniform distribution of rolling friction coefficient on its isolation performance were analyzed by a compiled computer program. The results show that the errors associated with the structural maximum relative displacement, acceleration and residual displacement due to ignoring the friction variability sequentially grow. This rule is weakened by the spring action, however, the unreasonable spring constant will cause sympathetic vibration. Under the condition of large friction variability, in the calculation of the structural maximum relative displacement and acceleration, the friction variability should be considered. When the structural residual displacement is concerned, the variability of rolling friction coefficient should be fully considered regardless of the friction variability.
基金supported by the National Natural Science Foundation of China(Grant No.51674169)Department of Education of Hebei Province of China(Grant No.ZD2019140)+1 种基金Natural Science Foundation of Hebei Province of China(Grant No.F2019210243)S&T Program of Hebei(Grant No.22375413D)School of Electrical and Electronics Engineering。
文摘Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51079046,50909041,51139001)the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cyclein River Basin (Grant No. IWHR-SKL-201108)+4 种基金the Special Fund of State Key Laboratory of China (Grant Nos. 2009586012,2009586912,201058-5212)the Fundamental Research Funds for the Central Universities(Grant Nos. 2009B08514,2010B20414,2010B01414,2010B14114)Jiangsu Province "333 High-Level Personnel Training Project" (Grant No.2017-B08037)Graduate Innovation Program of Universities in Jiangsu Province (Grant No. CX09B_163Z)the Science Foundation for the Excellent Youth Scholars of Ministry of Education of China (Grant No.20070294023)
文摘Based on the internal temperature variation of a dam lagging behind the ambient temperature variation,the ambient temperature of continuous variation is disctetized,and the functional expression of the thermal displacement component of the dam caused by single instantaneous temperature variation is obtained.Considering the temporal and spatial distribution law of the ambient temperature and its relation with air and water temperature,the function is expanded into a Taylor series.As a result,the improved thermal displacement component expression for a dam monitoring model is obtained.
基金supported by the National Basic Research Program of China("973"Project)(Grant No.2014CB047100)the National Natural Science Foundation of China(Grant Nos.51421064,51474046 & 51174039)the Fundamental Research Funds for the Central Universities(Grant No.DUT14LK21)
文摘A discontinuous deformation and displacement(DDD) analysis method is proposed for modelling the rock failure process. This method combines the rock failure process analysis(RFPA) method(based on finite element method) and discontinuous deformation analysis(DDA) method. RFPA is used to simulate crack initiation, propagation and coalescence processes of rock during the small deformation state. The DDA method is used to simulate the movement of blocks created by the multiple cracks modelled by the RFPA. The newly developed DDD method is particularly suitable for modelling both crack propagation and block movement during the rock failure process because of the natural and convenient coupling of continuous and discontinuous deformation analyses. The proposed method has been used to simulate crack initiation, propagation and coalescence within a slope as well as the block movement during the landslide process. Numerical modelling results indicate that the proposed DDD method can automatically simulate crack propagation and block movement during the rock failure process without degrading accuracy.
基金supported by the National Natural Science Foundation of China(Grant Nos.91123009,11104229 and 61227009)Xiamen University Start-up Funds
文摘The effect of Ag nanoislands on the Raman of graphene was investigated in this work.Compared with that on the bare silicon wafer,Raman enhancement was observed in the graphene film that covered on Ag/Si surface with nanoscale Ag islands,which would be induced by the localized plasmon resonance in Ag nanostructures.The interaction between the graphene sheet and Ag/Si substrate was further studied.The peak shift and line shape of Raman spectroscopy indicated a nonuniform strain distribution in the Ag/Si supported graphene film.
文摘In this paper, the author at first develops a method to study convergence of the cascadealgorithm in a Banach space without stable assumption on the initial (see Theorem 2.1), andthen applies the previous result on the convergence to characterizing compactly supportedrefinable distributions in fractional Sobolev spaces and Holder continuous spaces (see Theorems3.1, 3.3, and 3.4). Finally the author applies the above characterization to choosing appropriateinitial to guarantee the convergence of the cascade algorithm (see Theorem 4.2).
