Underground engineering,including shield tunnel construction,is a significant contributor to carbon dioxide emissions in infrastructure engineering projects.To better predict and control the carbon emissions associate...Underground engineering,including shield tunnel construction,is a significant contributor to carbon dioxide emissions in infrastructure engineering projects.To better predict and control the carbon emissions associated with shield tunnel construction,this paper presents a novel calculation method:the modified process analysis method based on inputoutput and process analysis methods.To evaluate the effectiveness of the proposed method,a specific shield tunnel construction project was selected as a case study.The modified process analysis method was used to analyze the various factors that influence carbon emissions during the project’s construction phase.In addition,a neural network approach was applied to validate the accuracy of the calculation using the LSTM and BP neural network.The results demonstrate that the proposed method not only combines the strengths of traditional methods but also offers high accuracy and acceptable error rates.Based on these findings,several measures to reduce carbon emissions during shield tunnel construction are suggested,providing valuable insights for reducing CO_(2) emissions associated with infrastructure engineering projects.This study highlights the importance of adopting innovative approaches to reduce carbon emissions and promotes the implementation of sustainable practices in the construction industry.Through the use of advanced analytical methods,such as the proposed modified process analysis method,we can effectively mitigate the environmental impact of construction activities and make significant contributions to the global effort to combat climate change.展开更多
A total of 80 weathering pits （gnammas）, located on granite surfaces of Qing Mountain （青山）, Hexigten （克什克腾） Global Geopark, Inner Mongolia, were identified and measured in terms of dimensional and orientat...A total of 80 weathering pits （gnammas）, located on granite surfaces of Qing Mountain （青山）, Hexigten （克什克腾） Global Geopark, Inner Mongolia, were identified and measured in terms of dimensional and orientational features. This article attempts to extract characteristics of the weathering pits by descriptive statistics and orientation rose diagrams, investigate the multi-phase evolution by the modified gnamma morphological analysis （GMA） method, and shed new light on the possible genesis and the influencing factors. Following the modified GMA method, weathering pits in Qing Mountain have been divided into six groups and compared with analogous sites to deduce their approximate age, which might be no older than 30 ka B.P., and explore the possibility that the multi-phase evolution of weathering pits may arise from responses to climate change. In consequence, we suggest that the combination of weathering, especially salt weathering, and wind erosion, both of which are closely related to climatic variation, take the main responsibility for the formation and development of weathering pits in Qing Mountain.展开更多
This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum...This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum and reflected coefficient of phase-locked wave field overlapped by multi directional irregular incident and reflected waves. The numerical test verifies the results under different wave conditions, different measurement systems, and different reflection features. The computation speed and stability of the two methods is also compared. The analysis addresses that the MBDM is better than the MMLM for directional spectrum estimating, while the MMLM is better than the MBDM for reflected coefficient estimation and calculating speed and stability.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52079128)Anhui province university discipline(professional)top talents academic funding project,project number:gxbjZD2022085.
文摘Underground engineering,including shield tunnel construction,is a significant contributor to carbon dioxide emissions in infrastructure engineering projects.To better predict and control the carbon emissions associated with shield tunnel construction,this paper presents a novel calculation method:the modified process analysis method based on inputoutput and process analysis methods.To evaluate the effectiveness of the proposed method,a specific shield tunnel construction project was selected as a case study.The modified process analysis method was used to analyze the various factors that influence carbon emissions during the project’s construction phase.In addition,a neural network approach was applied to validate the accuracy of the calculation using the LSTM and BP neural network.The results demonstrate that the proposed method not only combines the strengths of traditional methods but also offers high accuracy and acceptable error rates.Based on these findings,several measures to reduce carbon emissions during shield tunnel construction are suggested,providing valuable insights for reducing CO_(2) emissions associated with infrastructure engineering projects.This study highlights the importance of adopting innovative approaches to reduce carbon emissions and promotes the implementation of sustainable practices in the construction industry.Through the use of advanced analytical methods,such as the proposed modified process analysis method,we can effectively mitigate the environmental impact of construction activities and make significant contributions to the global effort to combat climate change.
基金supported by China Geological Survey(No.11212011120118)the Fundamental Research Projects of China University of Geosciences,Beijing,China(No.2011YYL016)
文摘A total of 80 weathering pits （gnammas）, located on granite surfaces of Qing Mountain （青山）, Hexigten （克什克腾） Global Geopark, Inner Mongolia, were identified and measured in terms of dimensional and orientational features. This article attempts to extract characteristics of the weathering pits by descriptive statistics and orientation rose diagrams, investigate the multi-phase evolution by the modified gnamma morphological analysis （GMA） method, and shed new light on the possible genesis and the influencing factors. Following the modified GMA method, weathering pits in Qing Mountain have been divided into six groups and compared with analogous sites to deduce their approximate age, which might be no older than 30 ka B.P., and explore the possibility that the multi-phase evolution of weathering pits may arise from responses to climate change. In consequence, we suggest that the combination of weathering, especially salt weathering, and wind erosion, both of which are closely related to climatic variation, take the main responsibility for the formation and development of weathering pits in Qing Mountain.
文摘This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum and reflected coefficient of phase-locked wave field overlapped by multi directional irregular incident and reflected waves. The numerical test verifies the results under different wave conditions, different measurement systems, and different reflection features. The computation speed and stability of the two methods is also compared. The analysis addresses that the MBDM is better than the MMLM for directional spectrum estimating, while the MMLM is better than the MBDM for reflected coefficient estimation and calculating speed and stability.
