The destruction of concrete building materials in severely cold regions of the north is more severely affected by freeze-thaw cycles,and the relationship between the mechanical properties and pore structure of concret...The destruction of concrete building materials in severely cold regions of the north is more severely affected by freeze-thaw cycles,and the relationship between the mechanical properties and pore structure of concrete with fine aggregate from municipal solid waste(MSW)incineration bottom ash after freeze-thaw cycles is analyzed under the degree of freeze-thaw hazard variation.In this paper,the gray correlation method is used to calculate the correlation between the relative dynamic elastic modulus,compressive strength,and microscopic porosity parameters to speculate on the most important factors affecting their changes.The GM(1,1)model was established based on the compressive strength of the waste incineration ash aggregate concrete,the relative error between the simulated and actual values in the model was less than 5%,and the accuracy of the model was level 1,indicating that the GM(1,1)model can well reflect the change in the compressive strength of the MSW incineration bottom ash aggregate concrete during freeze-thaw cycles.Using the gray correlation method,the correlation between the relative dynamic elastic modulus,compressive strength,air content,specific surface area,pore spacing coefficient,and pore average chord length was calculated,and the pore spacing coefficient and pore average chord length were determined to be highly correlated with each other.This determination can help analyze and infer the deterioration mechanism of concrete subject to freeze-thaw cycles.These results can provide a theoretical basis for guiding the engineering practice of concrete with fine aggregates of household bottom ash in the northern cold region.展开更多
Vehicle information on high-speed trains can not only determine whether the various parts of the train are working normally,but also predict the train’s future operating status.How to obtain valuable information from...Vehicle information on high-speed trains can not only determine whether the various parts of the train are working normally,but also predict the train’s future operating status.How to obtain valuable information from massive vehicle data is a difficult point.First,we divide the vehicle data of a high-speed train into 13 subsystem datasets,according to the functions of the collection components.Then,according to the gray theory and the Granger causality test,we propose the Gray-Granger Causality(GGC)model,which can construct a vehicle information network on the basis of the correlation between the collection components.By using the complex network theory to mine vehicle information and its subsystem networks,we find that the vehicle information network and its subsystem networks have the characteristics of a scale-free network.In addition,the vehicle information network is weak against attacks,but the subsystem network is closely connected and strong against attacks.展开更多
基金supported by the National Natural Science Foundation of China Project 51868058,52068058Inner Mongolia Natural Science Foundation 2018MS05011Inner Mongolia“Grassland Talent”CYYC5039.
文摘The destruction of concrete building materials in severely cold regions of the north is more severely affected by freeze-thaw cycles,and the relationship between the mechanical properties and pore structure of concrete with fine aggregate from municipal solid waste(MSW)incineration bottom ash after freeze-thaw cycles is analyzed under the degree of freeze-thaw hazard variation.In this paper,the gray correlation method is used to calculate the correlation between the relative dynamic elastic modulus,compressive strength,and microscopic porosity parameters to speculate on the most important factors affecting their changes.The GM(1,1)model was established based on the compressive strength of the waste incineration ash aggregate concrete,the relative error between the simulated and actual values in the model was less than 5%,and the accuracy of the model was level 1,indicating that the GM(1,1)model can well reflect the change in the compressive strength of the MSW incineration bottom ash aggregate concrete during freeze-thaw cycles.Using the gray correlation method,the correlation between the relative dynamic elastic modulus,compressive strength,air content,specific surface area,pore spacing coefficient,and pore average chord length was calculated,and the pore spacing coefficient and pore average chord length were determined to be highly correlated with each other.This determination can help analyze and infer the deterioration mechanism of concrete subject to freeze-thaw cycles.These results can provide a theoretical basis for guiding the engineering practice of concrete with fine aggregates of household bottom ash in the northern cold region.
基金supported by the Graduate Innovation Project of Beijing Jiaotong University(No.2020YJS098)。
文摘Vehicle information on high-speed trains can not only determine whether the various parts of the train are working normally,but also predict the train’s future operating status.How to obtain valuable information from massive vehicle data is a difficult point.First,we divide the vehicle data of a high-speed train into 13 subsystem datasets,according to the functions of the collection components.Then,according to the gray theory and the Granger causality test,we propose the Gray-Granger Causality(GGC)model,which can construct a vehicle information network on the basis of the correlation between the collection components.By using the complex network theory to mine vehicle information and its subsystem networks,we find that the vehicle information network and its subsystem networks have the characteristics of a scale-free network.In addition,the vehicle information network is weak against attacks,but the subsystem network is closely connected and strong against attacks.