Pub Date : 2023-05-01DOI: 10.3724/sp.j.1249.2023.03320
Shuxian HONG, Fan ZHENG, Feng XING, Biqin DONG
HONG Shuxian, ZHENG Fan, XING Feng, and DONG Biqin College of Civil and Transportation Engineering, Guangdong Province Key Laboratory of Durability for Marine Civil Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P. R. China Abstract: Rust penetration in pore structure of concrete cover happens after the reinforcement corrosion, which impedes the cracking development. To improve the accuracy of deducing the corrosion level of reinforcement from the crack width, reinforcements are designed to be corroded with different corrosion rates using different impressed current densities. Based on an inverse modeling method that consists of a combination of X-ray micro-computed tomography and the finite element method, the development of the modification coefficient of the rust volume is calculated to quantify the rust penetration and the influence of the corrosion rates. The results indicate that as the corrosion rate increases, the rust penetration decreases, and the modification coefficient of the rust volume increases. As the corrosion process develops, a decrease in the modification coefficient of the rust volume is found, which is independent of the corrosion rate. The modification coefficient of the rust volume decreases exponentially with the increase of corrosion rate. This study could provide a basis for the evaluation of reinforcement corrosion of reinforced concrete structures.
{"title":"Influence of corrosion rate on rust penetration in concrete","authors":"Shuxian HONG, Fan ZHENG, Feng XING, Biqin DONG","doi":"10.3724/sp.j.1249.2023.03320","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03320","url":null,"abstract":"HONG Shuxian, ZHENG Fan, XING Feng, and DONG Biqin College of Civil and Transportation Engineering, Guangdong Province Key Laboratory of Durability for Marine Civil Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P. R. China Abstract: Rust penetration in pore structure of concrete cover happens after the reinforcement corrosion, which impedes the cracking development. To improve the accuracy of deducing the corrosion level of reinforcement from the crack width, reinforcements are designed to be corroded with different corrosion rates using different impressed current densities. Based on an inverse modeling method that consists of a combination of X-ray micro-computed tomography and the finite element method, the development of the modification coefficient of the rust volume is calculated to quantify the rust penetration and the influence of the corrosion rates. The results indicate that as the corrosion rate increases, the rust penetration decreases, and the modification coefficient of the rust volume increases. As the corrosion process develops, a decrease in the modification coefficient of the rust volume is found, which is independent of the corrosion rate. The modification coefficient of the rust volume decreases exponentially with the increase of corrosion rate. This study could provide a basis for the evaluation of reinforcement corrosion of reinforced concrete structures.","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.3724/sp.j.1249.2023.03284
Dexin CHE, Baoer LI, Hailing XIANG, Fei WU
{"title":"Application of big data technology in financing costs of enterprises","authors":"Dexin CHE, Baoer LI, Hailing XIANG, Fei WU","doi":"10.3724/sp.j.1249.2023.03284","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03284","url":null,"abstract":"","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.3724/sp.j.1249.2023.03361
Ji LU, Botao LIN, Can SHI, Jiahao ZHANG
LU Ji 1, , LIN Botao 1, , SHI Can 1, , and ZHANG Jiahao 1, 2 1) College of Petroleum Engineering, China University of Petroleum (Beijing), Beijing 102249, P. R. China 2) College of Artificial Intelligence, China University of Petroleum (Beijing), Beijing 102249, P. R. China Abstract: The sandy conglomerate reservoirs in Karamay are characterized by diverse lithology and interlayers. The cost of the conventional coring methods is high, and the identification accuracy in non-coring section is low, which leads to difficulty in reservoir classification. In order to achieve rapid and accurate identification of lithology, the lithology of the target area is classified into mudstone, coarse sandstone, medium-fine sandstone, coarse conglomerate, medium-fine conglomerate, and coal seam based on geological data. Firstly, the principal component analysis method is adopted to establish the lithology identification cross plot based on sensitivity analysis of well log data with an accuracy rate of 81. 37%. Secondly, a lithology identification model is proposed based on the combination of k-means synthetic minority oversampling technique (KMSMOTE) and random forest to improve minority identification accuracy. The model improves the identification accuracy to achieve the accuracy of about 92. 94% for oversampling minority samples. The two methods are applied to adjacent wells for comparative analysis of lithology identification. The accuracy of the KMSMOTE random forest is 95. 71%, better than that of the cross plot method of 82. 91%. The accuracy of minority sample identification is higher than that of the traditional random forest
{"title":"Intelligent lithologic identification of sandy conglomerate reservoirs in District No.7 of Karamay oilfield","authors":"Ji LU, Botao LIN, Can SHI, Jiahao ZHANG","doi":"10.3724/sp.j.1249.2023.03361","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03361","url":null,"abstract":"LU Ji 1, , LIN Botao 1, , SHI Can 1, , and ZHANG Jiahao 1, 2 1) College of Petroleum Engineering, China University of Petroleum (Beijing), Beijing 102249, P. R. China 2) College of Artificial Intelligence, China University of Petroleum (Beijing), Beijing 102249, P. R. China Abstract: The sandy conglomerate reservoirs in Karamay are characterized by diverse lithology and interlayers. The cost of the conventional coring methods is high, and the identification accuracy in non-coring section is low, which leads to difficulty in reservoir classification. In order to achieve rapid and accurate identification of lithology, the lithology of the target area is classified into mudstone, coarse sandstone, medium-fine sandstone, coarse conglomerate, medium-fine conglomerate, and coal seam based on geological data. Firstly, the principal component analysis method is adopted to establish the lithology identification cross plot based on sensitivity analysis of well log data with an accuracy rate of 81. 37%. Secondly, a lithology identification model is proposed based on the combination of k-means synthetic minority oversampling technique (KMSMOTE) and random forest to improve minority identification accuracy. The model improves the identification accuracy to achieve the accuracy of about 92. 94% for oversampling minority samples. The two methods are applied to adjacent wells for comparative analysis of lithology identification. The accuracy of the KMSMOTE random forest is 95. 71%, better than that of the cross plot method of 82. 91%. The accuracy of minority sample identification is higher than that of the traditional random forest","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.3724/sp.j.1249.2023.03296
Yang LE, Dongxi GAO, Yi ZHANG, Wei GUO, Yi CHEN
: Coordinated development is an important embodiment of high - quality development. The urban - rural income distribution is the main aspect of coordinated development. Reinterpreting the income distribution effect of the development of digital economy from the perspective of
{"title":"The impact of digital economy on urban-rural income gap under government intervention","authors":"Yang LE, Dongxi GAO, Yi ZHANG, Wei GUO, Yi CHEN","doi":"10.3724/sp.j.1249.2023.03296","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03296","url":null,"abstract":": Coordinated development is an important embodiment of high - quality development. The urban - rural income distribution is the main aspect of coordinated development. Reinterpreting the income distribution effect of the development of digital economy from the perspective of","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.3724/sp.j.1249.2023.03370
Kun TIAN, Yongwei GONG, Shijie CHEN, Xinxin REN, Junqi LI, Wenliang WANG
TIAN Kun , GONG Yongwei , CHEN Shijie , REN Xinxin , LI Junqi , and WANG Wenliang 2 1) Key Laboratory of Urban Stormwater System and Water Environment (Ministry of Education), Beijing University of Civil Engineering and Architecture, Beijing 100044, P. R. China 2) Institute of Sponge City, Beijing University of Civil Engineering and Architecture, Beijing 100044, P. R. China 3) Shenzhen Urban Planning and Design Institute Co. Ltd. , Shenzhen 518049, Guangdong Province, P. R. China
{"title":"Effect of low impact development retrofitting in Shenzhen Xincheng Park","authors":"Kun TIAN, Yongwei GONG, Shijie CHEN, Xinxin REN, Junqi LI, Wenliang WANG","doi":"10.3724/sp.j.1249.2023.03370","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03370","url":null,"abstract":"TIAN Kun , GONG Yongwei , CHEN Shijie , REN Xinxin , LI Junqi , and WANG Wenliang 2 1) Key Laboratory of Urban Stormwater System and Water Environment (Ministry of Education), Beijing University of Civil Engineering and Architecture, Beijing 100044, P. R. China 2) Institute of Sponge City, Beijing University of Civil Engineering and Architecture, Beijing 100044, P. R. China 3) Shenzhen Urban Planning and Design Institute Co. Ltd. , Shenzhen 518049, Guangdong Province, P. R. China","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.3724/sp.j.1249.2023.03353
Gulei SUI, Yujiang FU, Hongxiang ZHU, Zunzhao LI, Xiaolin WANG
SUI Gulei 1, , FU Yujiang 1, , ZHU Hongxiang 1, , LI Zunzhao , and WANG Xiaolin 1, 2 1) SINOPEC Dalian Research Institute of Petroleum & Petrochemicals Co. Ltd. , Dalian 116045, Liaoning Province, P. R. China 2) Artificial Intelligence Innovation Center, SINOPEC, Dalian 116045, Liaoning Province, P. R. China Abstract: Formation pressure is a significant parameter for establishing the working system of injector-producer well and monitoring the operation of underground gas storage (UGS). In view of the complex geological modeling and highquality historical fitting involved in numerical simulation to understand the change of formation pressure, a datadriven method for forecasting formation pressure of UGS is proposed. The optimal warping path is weighted by the proportion of gas injection-production to screen pressure monitoring wells. The supervised learning model of forma⁃ tion pressure forecasting is established by three kinds of machine learning algorithms including extreme gradient boosting (XGBoost), support vector regression (SVR), and long short-term memory network (LSTM). The experimen⁃ tal results show that predictive performances of three predictive models are ranked from high to low: SVR, XGBoost, LSTM, among which the predictive performance of SVR is the most stable. Introducing the proportion of gas injection-production to screen pressure monitoring wells can improve the predictive performance of the data-driven model. Research shows that the purely data-driven method can directly interpret routine surface measurements to intuitive subsurface pressure parameters of UGS, which is very suitable for the field application of UGS.
{"title":"Prediction of formation pressure in underground gas storage based on data-driven method","authors":"Gulei SUI, Yujiang FU, Hongxiang ZHU, Zunzhao LI, Xiaolin WANG","doi":"10.3724/sp.j.1249.2023.03353","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03353","url":null,"abstract":"SUI Gulei 1, , FU Yujiang 1, , ZHU Hongxiang 1, , LI Zunzhao , and WANG Xiaolin 1, 2 1) SINOPEC Dalian Research Institute of Petroleum & Petrochemicals Co. Ltd. , Dalian 116045, Liaoning Province, P. R. China 2) Artificial Intelligence Innovation Center, SINOPEC, Dalian 116045, Liaoning Province, P. R. China Abstract: Formation pressure is a significant parameter for establishing the working system of injector-producer well and monitoring the operation of underground gas storage (UGS). In view of the complex geological modeling and highquality historical fitting involved in numerical simulation to understand the change of formation pressure, a datadriven method for forecasting formation pressure of UGS is proposed. The optimal warping path is weighted by the proportion of gas injection-production to screen pressure monitoring wells. The supervised learning model of forma⁃ tion pressure forecasting is established by three kinds of machine learning algorithms including extreme gradient boosting (XGBoost), support vector regression (SVR), and long short-term memory network (LSTM). The experimen⁃ tal results show that predictive performances of three predictive models are ranked from high to low: SVR, XGBoost, LSTM, among which the predictive performance of SVR is the most stable. Introducing the proportion of gas injection-production to screen pressure monitoring wells can improve the predictive performance of the data-driven model. Research shows that the purely data-driven method can directly interpret routine surface measurements to intuitive subsurface pressure parameters of UGS, which is very suitable for the field application of UGS.","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research and performance evaluation of channeling-plugging agent under high temperature","authors":"Hongjie YUAN, Long HE, Zijia LI, Mingkai LI, Xueli HUANG, Wen ZHANG","doi":"10.3724/sp.j.1249.2023.03344","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2023.03344","url":null,"abstract":"","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135517083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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