Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved]
Background Unexpected leakage accidents of the natural gas pipeline inside urban utility tunnels can pose great threats to public safety, property, and the environment. It highlights the modeling of natural gas leakage and dispersion dynamics, especially from a digital twin implementation perspectiv...
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| Format: | Article |
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F1000 Research Ltd
2024-12-01
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| Series: | Digital Twin |
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| Online Access: | https://digitaltwin1.org/articles/4-8/v2 |
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| author | Jiansong Wu Jitao Cai Ziqi Han Yanzhu Hu Ming Fu Yuefei Li Xin Wang Xiaofu Zou |
| author_facet | Jiansong Wu Jitao Cai Ziqi Han Yanzhu Hu Ming Fu Yuefei Li Xin Wang Xiaofu Zou |
| author_sort | Jiansong Wu |
| collection | DOAJ |
| description | Background Unexpected leakage accidents of the natural gas pipeline inside urban utility tunnels can pose great threats to public safety, property, and the environment. It highlights the modeling of natural gas leakage and dispersion dynamics, especially from a digital twin implementation perspective facilitating effective emergency response in a data-driven way. Methods In this study, a digital twin-based emergency response framework for gas leakage accidents in urban utility tunnels is proposed. Within this framework, the data-calibrated gas concentration prediction (DC-GCP) model is developed by integrating the Lattice Boltzmann Method (LBM) with data assimilation (DA) techniques. This combination enables accurate spatiotemporal predictions of gas concentrations, even with a prior or inaccurate gas leakage source term. Specifically, we develop a high-performance LBM-based gas concentration prediction model using the parallel programming language Taichi Lang. Based on this model, real-time integration of gas sensor data from utility tunnels is achieved through the DA algorithm. Therefore, the predicted results can be calibrated by the continuous data in the absence of complete source term information. Furthermore, a widely used twin experiment and statistical performance measures (SPMs) are used to evaluate and validate the effectiveness of the proposed approach. Results The results show that all SPMs progressively converge towards their ideal values as calibration progresses. And both the gas concentration predictions and the source term estimations can be calibrated effectively by the proposed approach, achieving a relative error of less than 5%. Conclusions This study helps for dynamic risk assessment and emergency response of natural gas leakage accidents, as well as facilitating the implementation of predictive digital twin in utility tunnels. |
| format | Article |
| id | doaj-art-461d0dd1c85c4736b3e9a979c18bbc45 |
| institution | Kabale University |
| issn | 2752-5783 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | Digital Twin |
| spelling | doaj-art-461d0dd1c85c4736b3e9a979c18bbc452025-01-09T01:00:02ZengF1000 Research LtdDigital Twin2752-57832024-12-01419409Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved]Jiansong Wu0Jitao Cai1https://orcid.org/0009-0001-6704-8872Ziqi Han2Yanzhu Hu3Ming Fu4Yuefei Li5Xin Wang6Xiaofu Zou7School of Emergency Management and Safety Engineering, China University of Mining and Technology, Beijing, Beijing, 100083, ChinaSchool of Emergency Management and Safety Engineering, China University of Mining and Technology, Beijing, Beijing, 100083, ChinaSchool of Emergency Management and Safety Engineering, China University of Mining and Technology, Beijing, Beijing, 100083, ChinaSchool of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, Beijing, 100876, ChinaHefei Institute for Public Safety Research, Tsinghua University, Anhui, Hefei, 230601, ChinaMaster Plan and Municipal Design Institute, China Architecture Design and Research Group, Beijing, Beijing, 100044, ChinaMaster Plan and Municipal Design Institute, China Architecture Design and Research Group, Beijing, Beijing, 100044, ChinaSchool of Artificial intelligence, Beihang University, Beijing, Beijing, 100191, ChinaBackground Unexpected leakage accidents of the natural gas pipeline inside urban utility tunnels can pose great threats to public safety, property, and the environment. It highlights the modeling of natural gas leakage and dispersion dynamics, especially from a digital twin implementation perspective facilitating effective emergency response in a data-driven way. Methods In this study, a digital twin-based emergency response framework for gas leakage accidents in urban utility tunnels is proposed. Within this framework, the data-calibrated gas concentration prediction (DC-GCP) model is developed by integrating the Lattice Boltzmann Method (LBM) with data assimilation (DA) techniques. This combination enables accurate spatiotemporal predictions of gas concentrations, even with a prior or inaccurate gas leakage source term. Specifically, we develop a high-performance LBM-based gas concentration prediction model using the parallel programming language Taichi Lang. Based on this model, real-time integration of gas sensor data from utility tunnels is achieved through the DA algorithm. Therefore, the predicted results can be calibrated by the continuous data in the absence of complete source term information. Furthermore, a widely used twin experiment and statistical performance measures (SPMs) are used to evaluate and validate the effectiveness of the proposed approach. Results The results show that all SPMs progressively converge towards their ideal values as calibration progresses. And both the gas concentration predictions and the source term estimations can be calibrated effectively by the proposed approach, achieving a relative error of less than 5%. Conclusions This study helps for dynamic risk assessment and emergency response of natural gas leakage accidents, as well as facilitating the implementation of predictive digital twin in utility tunnels.https://digitaltwin1.org/articles/4-8/v2Utility tunnels natural gas leakage emergency response lattice Boltzmann method data assimilationeng |
| spellingShingle | Jiansong Wu Jitao Cai Ziqi Han Yanzhu Hu Ming Fu Yuefei Li Xin Wang Xiaofu Zou Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] Digital Twin Utility tunnels natural gas leakage emergency response lattice Boltzmann method data assimilation eng |
| title | Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] |
| title_full | Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] |
| title_fullStr | Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] |
| title_full_unstemmed | Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] |
| title_short | Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] |
| title_sort | digital twin based modeling of natural gas leakage and dispersion in urban utility tunnels version 2 peer review 2 approved |
| topic | Utility tunnels natural gas leakage emergency response lattice Boltzmann method data assimilation eng |
| url | https://digitaltwin1.org/articles/4-8/v2 |
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