Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model
To predict the drifting trajectories of bodies in the Pearl River Front Channel and assist local water police in locating the specific positions of drowning victims, this study uses Delft3D to construct a hydrodynamic model of the Pearl River Front Channel and conducts multiple on-site drifting test...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Pearl River
2024-05-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2024.05.008 |
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| _version_ | 1841530629130289152 |
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| author | CHENG Xiangju CHEN Zehai LI Bin LI Xu BI Jinjin WANG Longwei |
| author_facet | CHENG Xiangju CHEN Zehai LI Bin LI Xu BI Jinjin WANG Longwei |
| author_sort | CHENG Xiangju |
| collection | DOAJ |
| description | To predict the drifting trajectories of bodies in the Pearl River Front Channel and assist local water police in locating the specific positions of drowning victims, this study uses Delft3D to construct a hydrodynamic model of the Pearl River Front Channel and conducts multiple on-site drifting tests using a corpse model. By fitting the surface flow velocity of the Pearl River Front Channel, the paper builds a prediction model for corpse model drifting with an <italic>R</italic><sup>2</sup> of 0.88. The results show that the corpse model released in the Pearl River Front Channel undergoes back-and-forth motion along the river channel under the influence of tides and flows, gradually drifting downstream. In the drifting model validation, the drifting speed and direction of the corpse model are generally consistent with the tidal current, and the error in simulation results is within 1 km, with a final distance error rate of less than 15%. In a case study, the simulated results for an adult female corpse have an error of approximately 300 m. External forces such as wave force caused by boats result in a north-south directional deviation in the drifting trajectory, indicating the need to further improve the simulation effect. The derivation mode of the model is also applicable to other tidal rivers, making it possible to measure the drifting trajectories of bodies and providing convenience and reference for body recovery work and police case processing. |
| format | Article |
| id | doaj-art-ded3709daa23426da685c2869a90498e |
| institution | Kabale University |
| issn | 1001-9235 |
| language | zho |
| publishDate | 2024-05-01 |
| publisher | Editorial Office of Pearl River |
| record_format | Article |
| series | Renmin Zhujiang |
| spelling | doaj-art-ded3709daa23426da685c2869a90498e2025-01-15T03:00:55ZzhoEditorial Office of Pearl RiverRenmin Zhujiang1001-92352024-05-0145657459362597Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D ModelCHENG XiangjuCHEN ZehaiLI BinLI XuBI JinjinWANG LongweiTo predict the drifting trajectories of bodies in the Pearl River Front Channel and assist local water police in locating the specific positions of drowning victims, this study uses Delft3D to construct a hydrodynamic model of the Pearl River Front Channel and conducts multiple on-site drifting tests using a corpse model. By fitting the surface flow velocity of the Pearl River Front Channel, the paper builds a prediction model for corpse model drifting with an <italic>R</italic><sup>2</sup> of 0.88. The results show that the corpse model released in the Pearl River Front Channel undergoes back-and-forth motion along the river channel under the influence of tides and flows, gradually drifting downstream. In the drifting model validation, the drifting speed and direction of the corpse model are generally consistent with the tidal current, and the error in simulation results is within 1 km, with a final distance error rate of less than 15%. In a case study, the simulated results for an adult female corpse have an error of approximately 300 m. External forces such as wave force caused by boats result in a north-south directional deviation in the drifting trajectory, indicating the need to further improve the simulation effect. The derivation mode of the model is also applicable to other tidal rivers, making it possible to measure the drifting trajectories of bodies and providing convenience and reference for body recovery work and police case processing.http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2024.05.008Delft3Dtidal reachdrifting trajectoryprediction modelfitting |
| spellingShingle | CHENG Xiangju CHEN Zehai LI Bin LI Xu BI Jinjin WANG Longwei Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model Renmin Zhujiang Delft3D tidal reach drifting trajectory prediction model fitting |
| title | Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model |
| title_full | Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model |
| title_fullStr | Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model |
| title_full_unstemmed | Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model |
| title_short | Prediction of Corpse Model Drifting Trajectories in Pearl River Front Channel Based on Delft3D Model |
| title_sort | prediction of corpse model drifting trajectories in pearl river front channel based on delft3d model |
| topic | Delft3D tidal reach drifting trajectory prediction model fitting |
| url | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2024.05.008 |
| work_keys_str_mv | AT chengxiangju predictionofcorpsemodeldriftingtrajectoriesinpearlriverfrontchannelbasedondelft3dmodel AT chenzehai predictionofcorpsemodeldriftingtrajectoriesinpearlriverfrontchannelbasedondelft3dmodel AT libin predictionofcorpsemodeldriftingtrajectoriesinpearlriverfrontchannelbasedondelft3dmodel AT lixu predictionofcorpsemodeldriftingtrajectoriesinpearlriverfrontchannelbasedondelft3dmodel AT bijinjin predictionofcorpsemodeldriftingtrajectoriesinpearlriverfrontchannelbasedondelft3dmodel AT wanglongwei predictionofcorpsemodeldriftingtrajectoriesinpearlriverfrontchannelbasedondelft3dmodel |