In extreme cold regions,a thermal insulation layer(TIL)is commonly employed to mitigate the detrimental effects of frost heaving forces in tunnels.Optimizing the laying scheme of TIL,specifically minimizing frost heav...In extreme cold regions,a thermal insulation layer(TIL)is commonly employed to mitigate the detrimental effects of frost heaving forces in tunnels.Optimizing the laying scheme of TIL,specifically minimizing frost heaving forces,holds considerable importance in the prevention of frost damage.This research developed a two-dimensional unsteady temperature field of circular tunnels by using the difference method(taking the off-wall laying method as an example)based on the law of conservation of energy.Then,the frozen circle and water migration coefficient were introduced to establish the relationship between the temperature field and frost heaving forces,and a reliable methodology for calculating these forces under the specific conditions of TIL installation was developed.Then(i)the influence of the air layer thickness of the off-wall laying method,(ii)different laying methods of TIL,(iii)the TIL thickness,(iv)the thermal conductivity of the TIL,and(v)the freeze-thaw cycles on the frost heaving force were investigated.The results showed that the frost heaving force served as a reliable and effective metric for evaluating the insulation effect in tunnels.In order to avoid frost damage in compliance with the design requirements,the insulation effects from various laying methods were established,in descending efficacy order as follows:off-wall laying,double layer laying,surface laying,and sandwich laying.Our findings revealed that the optimal thickness for the air layer in the offwall laying method was 0.10 m.The insulation effect of materials with a thermal conductivity below 0.047 W/(m·℃)was furthermore found to be good.Under freeze-thaw cycle conditions,it is concluded that to prevent frost damage,the TIL thickness should be the sum of the thickness r1 of the first freeze-thaw cycle without frost heaving forces and an additional reserve value 0.06r1 of the TIL thickness.展开更多
Soil background contents of a number of elements of different soil groups, sub-groups and genus on Liaohe River Plain were investigated. It appeared that: the background levels for most elements studied were around th...Soil background contents of a number of elements of different soil groups, sub-groups and genus on Liaohe River Plain were investigated. It appeared that: the background levels for most elements studied were around the lower limits of the world's averages, variation coefficients of the background content values were from 0.3-0.5 and the element migration coefficients were between 0.9 and 1.0. It was found that the element background contents in soils of eastern and southern parts of the area were generally higher than that of western and northern parts.展开更多
The mechanical and durability characteristics of concrete are crucial for designing and evaluating concrete structures throughout their entire operational lifespan.The main objective of this research is to use the dee...The mechanical and durability characteristics of concrete are crucial for designing and evaluating concrete structures throughout their entire operational lifespan.The main objective of this research is to use the deep learning(DL)method along with an artificial neural network(ANN)to predict the chloride migration coefficient and concrete compressive strength.An expansive experimental database of nearly 1100 data points was gathered from existing scientific literature.Four forecast models were created,utilizing between 10 and 12 input features.The ANN was used to address the missing data gaps in the literature.A comprehensive pre-processing approach was then implemented to identify outliers and encode data attributes.The use of mean absolute error(MAE)as an evaluation metric for regression tasks and the employment of a confusion matrix for classification tasks were found to produce accurate results.Additionally,both the compressive strength and chloride migration coefficient exhibit a high level of accuracy,above 0.85,in both regression and classification tasks.Moreover,a user-friendly web application was successfully developed in the present study using the Python programming language,improving the ability to integrate smoothly with the user’s device.展开更多
基金the financial support provided by the National Natural Science Foundation of China(Nos.52078061,51878074)the Huaihua University Scientific Research Project,China(No.HHUY 2022-26)+1 种基金the Postgraduate Research and Innovation-funded Project of Hunan Province,China(No.CX20220885)。
文摘In extreme cold regions,a thermal insulation layer(TIL)is commonly employed to mitigate the detrimental effects of frost heaving forces in tunnels.Optimizing the laying scheme of TIL,specifically minimizing frost heaving forces,holds considerable importance in the prevention of frost damage.This research developed a two-dimensional unsteady temperature field of circular tunnels by using the difference method(taking the off-wall laying method as an example)based on the law of conservation of energy.Then,the frozen circle and water migration coefficient were introduced to establish the relationship between the temperature field and frost heaving forces,and a reliable methodology for calculating these forces under the specific conditions of TIL installation was developed.Then(i)the influence of the air layer thickness of the off-wall laying method,(ii)different laying methods of TIL,(iii)the TIL thickness,(iv)the thermal conductivity of the TIL,and(v)the freeze-thaw cycles on the frost heaving force were investigated.The results showed that the frost heaving force served as a reliable and effective metric for evaluating the insulation effect in tunnels.In order to avoid frost damage in compliance with the design requirements,the insulation effects from various laying methods were established,in descending efficacy order as follows:off-wall laying,double layer laying,surface laying,and sandwich laying.Our findings revealed that the optimal thickness for the air layer in the offwall laying method was 0.10 m.The insulation effect of materials with a thermal conductivity below 0.047 W/(m·℃)was furthermore found to be good.Under freeze-thaw cycle conditions,it is concluded that to prevent frost damage,the TIL thickness should be the sum of the thickness r1 of the first freeze-thaw cycle without frost heaving forces and an additional reserve value 0.06r1 of the TIL thickness.
文摘Soil background contents of a number of elements of different soil groups, sub-groups and genus on Liaohe River Plain were investigated. It appeared that: the background levels for most elements studied were around the lower limits of the world's averages, variation coefficients of the background content values were from 0.3-0.5 and the element migration coefficients were between 0.9 and 1.0. It was found that the element background contents in soils of eastern and southern parts of the area were generally higher than that of western and northern parts.
文摘The mechanical and durability characteristics of concrete are crucial for designing and evaluating concrete structures throughout their entire operational lifespan.The main objective of this research is to use the deep learning(DL)method along with an artificial neural network(ANN)to predict the chloride migration coefficient and concrete compressive strength.An expansive experimental database of nearly 1100 data points was gathered from existing scientific literature.Four forecast models were created,utilizing between 10 and 12 input features.The ANN was used to address the missing data gaps in the literature.A comprehensive pre-processing approach was then implemented to identify outliers and encode data attributes.The use of mean absolute error(MAE)as an evaluation metric for regression tasks and the employment of a confusion matrix for classification tasks were found to produce accurate results.Additionally,both the compressive strength and chloride migration coefficient exhibit a high level of accuracy,above 0.85,in both regression and classification tasks.Moreover,a user-friendly web application was successfully developed in the present study using the Python programming language,improving the ability to integrate smoothly with the user’s device.
