{"title":"选择性人工冻结地面运行条件的不确定性分析","authors":"Ahmad F. Zueter, Saad Akhtar, A. Sasmito","doi":"10.46873/2300-3960.1357","DOIUrl":null,"url":null,"abstract":"Abstract Artificial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective artificial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant flow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for field-scale applications is exploited to simulate a total of 5,000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on field observations of a field-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry. Abstract Arti fi cial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective arti fi cial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant fl ow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for fi eld-scale applications is exploited to simulate a total of 5000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on fi eld observations of a fi eld-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry.","PeriodicalId":37284,"journal":{"name":"Journal of Sustainable Mining","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Uncertainty analysis of operational conditions in selective artificial ground freezing applications\",\"authors\":\"Ahmad F. Zueter, Saad Akhtar, A. Sasmito\",\"doi\":\"10.46873/2300-3960.1357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Artificial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective artificial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant flow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for field-scale applications is exploited to simulate a total of 5,000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on field observations of a field-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry. Abstract Arti fi cial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective arti fi cial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant fl ow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for fi eld-scale applications is exploited to simulate a total of 5000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on fi eld observations of a fi eld-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry.\",\"PeriodicalId\":37284,\"journal\":{\"name\":\"Journal of Sustainable Mining\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Sustainable Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46873/2300-3960.1357\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sustainable Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46873/2300-3960.1357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Uncertainty analysis of operational conditions in selective artificial ground freezing applications
Abstract Artificial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective artificial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant flow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for field-scale applications is exploited to simulate a total of 5,000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on field observations of a field-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry. Abstract Arti fi cial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective arti fi cial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant fl ow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for fi eld-scale applications is exploited to simulate a total of 5000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on fi eld observations of a fi eld-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry.