Intelligent pipeline inspection is necessary to operate submarine pipelines safely. At present, speed excursion and blockage are the challenges in the inspection of low-pressure gas pipelines. Accordingly, this study proposes a novel pneumo-electric hybrid-driven scheme to improve the traveling stability of inspection robots. To adapt to different working conditions, building blocks and CFD numerical simulation methods are used to study the throttling pressure control flow field of the robot. The results proved that the flow clearance had the most evident effect. The flow clearance was reduced from 30 to 5 mm, and the differential pressure of the prototype increased from 0.3 to 17 kPa. The skeleton diameter has a small effect on the differential pressure. The differential pressure increases as the gas velocity increases. By analyzing the prototype in different positions, it was found that the differential pressure of the prototype while passing the elbow decreased by 45% at 45°, which quantified the fluid-driven force gap of the prototype while passing through the elbow. Finally, by comparing the speed of prototype with that of fluid-driven pig, it is demonstrated that a pneumo-electric hybrid-driven scheme is an effective solution to the problem of unstable inspection operation of low-pressure gas pipelines.
{"title":"Numerical Simulation and Experimental Study of the Pneumo-Electric Hybrid-Driven Pipeline Inspection Robot in Low-Pressure Gas Pipeline","authors":"Yuming Su, Lijian Yang, Hao Geng, Ping Huang, Fuyin Zheng, Wenxue Zheng, Pengfei Gao","doi":"10.3390/jmse12081345","DOIUrl":"https://doi.org/10.3390/jmse12081345","url":null,"abstract":"Intelligent pipeline inspection is necessary to operate submarine pipelines safely. At present, speed excursion and blockage are the challenges in the inspection of low-pressure gas pipelines. Accordingly, this study proposes a novel pneumo-electric hybrid-driven scheme to improve the traveling stability of inspection robots. To adapt to different working conditions, building blocks and CFD numerical simulation methods are used to study the throttling pressure control flow field of the robot. The results proved that the flow clearance had the most evident effect. The flow clearance was reduced from 30 to 5 mm, and the differential pressure of the prototype increased from 0.3 to 17 kPa. The skeleton diameter has a small effect on the differential pressure. The differential pressure increases as the gas velocity increases. By analyzing the prototype in different positions, it was found that the differential pressure of the prototype while passing the elbow decreased by 45% at 45°, which quantified the fluid-driven force gap of the prototype while passing through the elbow. Finally, by comparing the speed of prototype with that of fluid-driven pig, it is demonstrated that a pneumo-electric hybrid-driven scheme is an effective solution to the problem of unstable inspection operation of low-pressure gas pipelines.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Formation testing is widely used in offshore oil and gas development, and predicting the sampling time of pure fluids during this process is very important. However, existing formation testing methods have problems such as long duration and low efficiency. To address these issues, this paper proposes a hybrid-driven method based on physical models and machine learning models to predict fluid sampling time in formation testing. In this hybrid-driven model, we establish a digital twin model to simulate a large amount of experimental data (6000 cases, totaling over 1 million data points) and significantly enhance the correlation between features using physical formulas. By applying advanced machine learning algorithms, we achieve real-time predictions of fluid sampling time with an accuracy of up to 92%. Additionally, we use optimizers to improve the model’s accuracy by 3%, ultimately reaching 95%. This model provides a novel approach for optimizing formation testing that is significant for the efficient development of offshore oil and gas.
{"title":"Intelligent Prediction of Sampling Time for Offshore Formation Testing Based on Hybrid-Driven Methods","authors":"Yiying Nie, Caoxiong Li, Yanmin Zhou, Qiang Yu, Youxiang Zuo, Yuexin Meng, Chenggang Xian","doi":"10.3390/jmse12081348","DOIUrl":"https://doi.org/10.3390/jmse12081348","url":null,"abstract":"Formation testing is widely used in offshore oil and gas development, and predicting the sampling time of pure fluids during this process is very important. However, existing formation testing methods have problems such as long duration and low efficiency. To address these issues, this paper proposes a hybrid-driven method based on physical models and machine learning models to predict fluid sampling time in formation testing. In this hybrid-driven model, we establish a digital twin model to simulate a large amount of experimental data (6000 cases, totaling over 1 million data points) and significantly enhance the correlation between features using physical formulas. By applying advanced machine learning algorithms, we achieve real-time predictions of fluid sampling time with an accuracy of up to 92%. Additionally, we use optimizers to improve the model’s accuracy by 3%, ultimately reaching 95%. This model provides a novel approach for optimizing formation testing that is significant for the efficient development of offshore oil and gas.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Automatic Identification System (AIS) utilizes base stations to manage vessel traffic and disseminate waterway information. These stations broadcast maritime safety data to vessels within their service radius using VHF signals. However, the emergence of “spoofing base stations” poses a significant threat to maritime safety. These impostors mimic legitimate AIS base stations by appropriating their Maritime Mobile Service Identity (MMSI) information, interacting with vessels, potentially leading to erroneous decisions, or guiding vessels into hazardous areas. Therefore, ensuring the credibility of AIS base stations is critical for safe vessel navigation. It is essential to distinguish between genuine AIS base stations and “spoofing base stations” to achieve this goal. One criterion for identifying AIS spoofing involves detecting signals beyond the expected service radius of AIS base stations. This paper proposes a method to monitor the credibility of AIS base stations through a service radius detection pattern. Furthermore, the method analyzes the impact of hydrological and meteorological factors on AIS signal propagation in complex sea surface environments. By integrating empirical data, it accurately describes the mathematical relationship and calculates the service radius of AIS base station signals. Analyzing vessel position coordinates, decoding base station position messages, and computing distances between vessels and AIS base stations allows for matching with the AIS base station’s designated service radius and propagation distance. This approach enables precise identification of AIS spoofing base stations, thereby facilitating robust monitoring of AIS base station credibility. The research outcomes provide a foundational framework for developing high-credibility AIS base station services within integrated maritime navigation and information systems.
{"title":"An AIS Base Station Credibility Monitoring Method Based on Service Radius Detection Patterns in Complex Sea Surface Environments","authors":"Xiaoye Wang, Yalan Wang, Leyun Fu, Qing Hu","doi":"10.3390/jmse12081352","DOIUrl":"https://doi.org/10.3390/jmse12081352","url":null,"abstract":"The Automatic Identification System (AIS) utilizes base stations to manage vessel traffic and disseminate waterway information. These stations broadcast maritime safety data to vessels within their service radius using VHF signals. However, the emergence of “spoofing base stations” poses a significant threat to maritime safety. These impostors mimic legitimate AIS base stations by appropriating their Maritime Mobile Service Identity (MMSI) information, interacting with vessels, potentially leading to erroneous decisions, or guiding vessels into hazardous areas. Therefore, ensuring the credibility of AIS base stations is critical for safe vessel navigation. It is essential to distinguish between genuine AIS base stations and “spoofing base stations” to achieve this goal. One criterion for identifying AIS spoofing involves detecting signals beyond the expected service radius of AIS base stations. This paper proposes a method to monitor the credibility of AIS base stations through a service radius detection pattern. Furthermore, the method analyzes the impact of hydrological and meteorological factors on AIS signal propagation in complex sea surface environments. By integrating empirical data, it accurately describes the mathematical relationship and calculates the service radius of AIS base station signals. Analyzing vessel position coordinates, decoding base station position messages, and computing distances between vessels and AIS base stations allows for matching with the AIS base station’s designated service radius and propagation distance. This approach enables precise identification of AIS spoofing base stations, thereby facilitating robust monitoring of AIS base station credibility. The research outcomes provide a foundational framework for developing high-credibility AIS base station services within integrated maritime navigation and information systems.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiangming Dai, Zhigang Li, Litian Hu, Peizhen Zhang, Xiaoqiang Yang, Rafael Almeida, Guanhua Li
Over the past 424 years, the Littoral Fault Zone (LFZ), located offshore of the South China coast, has experienced four destructive earthquakes (M ≥ 7). These events have resulted in an approximately 700 km seismic gap centered on the Greater Bay Area of China, home to over 70 million people. Despite previous studies on deeper crustal structures and geodynamic processes, the shallow structural architecture and recent tectonic activity of the LFZ within the seismic gap remain poorly understood due to limited offshore geophysical investigations. Here, we present new offshore geophysical data to explore the shallow crustal architecture and Holocene activity of the LFZ within this seismic gap. Multichannel seismic data reveal that the LFZ comprises a high-angle listric main normal fault along with several secondary normal faults. The main fault trends northeast and dips southeast in the shallow crustal architecture, serving as the basin-controlling fault in the north of the Pearl River Mouth Basin, with accumulated displacements ranging from 1.5 to 1.8 km. Furthermore, analysis of single-channel seismic data, and 14C dating results from the borehole, indicate that the most recent movement of the main fault occurred within the last ~10,000 years, with minimum vertical offsets of 1.2 m. Based on these findings, we emphasize the LFZ’s potential to generate a significant earthquake, estimated at Mw 7.0–7.5, within the inferred seismic gap. Our study highlights the potential earthquake hazard posed by the LFZ to the Greater Bay Area of China, while also providing valuable insights for the assessment of active submarine faults worldwide.
{"title":"Exploring Fault Geometry and Holocene Deformation of the Littoral Fault Zone within the Seismic Gap South of Greater Bay Area, China","authors":"Xiangming Dai, Zhigang Li, Litian Hu, Peizhen Zhang, Xiaoqiang Yang, Rafael Almeida, Guanhua Li","doi":"10.3390/jmse12081350","DOIUrl":"https://doi.org/10.3390/jmse12081350","url":null,"abstract":"Over the past 424 years, the Littoral Fault Zone (LFZ), located offshore of the South China coast, has experienced four destructive earthquakes (M ≥ 7). These events have resulted in an approximately 700 km seismic gap centered on the Greater Bay Area of China, home to over 70 million people. Despite previous studies on deeper crustal structures and geodynamic processes, the shallow structural architecture and recent tectonic activity of the LFZ within the seismic gap remain poorly understood due to limited offshore geophysical investigations. Here, we present new offshore geophysical data to explore the shallow crustal architecture and Holocene activity of the LFZ within this seismic gap. Multichannel seismic data reveal that the LFZ comprises a high-angle listric main normal fault along with several secondary normal faults. The main fault trends northeast and dips southeast in the shallow crustal architecture, serving as the basin-controlling fault in the north of the Pearl River Mouth Basin, with accumulated displacements ranging from 1.5 to 1.8 km. Furthermore, analysis of single-channel seismic data, and 14C dating results from the borehole, indicate that the most recent movement of the main fault occurred within the last ~10,000 years, with minimum vertical offsets of 1.2 m. Based on these findings, we emphasize the LFZ’s potential to generate a significant earthquake, estimated at Mw 7.0–7.5, within the inferred seismic gap. Our study highlights the potential earthquake hazard posed by the LFZ to the Greater Bay Area of China, while also providing valuable insights for the assessment of active submarine faults worldwide.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141925811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marisa A. Gomes, Catarina M. Alves, Fábio Faria, R. Neto, Edgar Fernandes, Jesús S. Troncoso, Pedro T. Gomes
Coastal ecosystems are vital for numerous demersal and benthopelagic species, offering critical habitats throughout their life cycles. Effective monitoring of these species in complex coastal environments is essential, yet traditional survey methodologies are often impractical due to environmental constraints like strong currents and high wave regimes. This study introduces a new cost-effective Baited Remote Underwater Video System (BRUVS) design featuring a vertical structure and 360° cameras developed to overcome limitations of traditional BRUVS, such as system anchoring, overturning, and restricted frame view. The new design was compared against a previous one used on the northwest Iberian coast. Key performance metrics included species detection, habitat identification, and operational efficiency under complex hydrodynamic conditions. Findings reveal that the two designs can effectively identify the common species typically observed in the study area. However, the new design outperformed the previous by significantly reducing equipment losses and anchoring issues. This enhancement in field operations’ simplicity, operability, portability, and resiliency underscores the new system’s potential as a cost-effective and efficient tool for demersal and benthopelagic ecological surveys in challenging coastal seascapes. This innovative BRUVS design offers advanced monitoring solutions, improving habitat assessment accuracy and responsiveness.
{"title":"Unleashing the Potential of the 360° Baited Remote Underwater Video System (BRUVS): An Innovative Design for Complex Habitats","authors":"Marisa A. Gomes, Catarina M. Alves, Fábio Faria, R. Neto, Edgar Fernandes, Jesús S. Troncoso, Pedro T. Gomes","doi":"10.3390/jmse12081346","DOIUrl":"https://doi.org/10.3390/jmse12081346","url":null,"abstract":"Coastal ecosystems are vital for numerous demersal and benthopelagic species, offering critical habitats throughout their life cycles. Effective monitoring of these species in complex coastal environments is essential, yet traditional survey methodologies are often impractical due to environmental constraints like strong currents and high wave regimes. This study introduces a new cost-effective Baited Remote Underwater Video System (BRUVS) design featuring a vertical structure and 360° cameras developed to overcome limitations of traditional BRUVS, such as system anchoring, overturning, and restricted frame view. The new design was compared against a previous one used on the northwest Iberian coast. Key performance metrics included species detection, habitat identification, and operational efficiency under complex hydrodynamic conditions. Findings reveal that the two designs can effectively identify the common species typically observed in the study area. However, the new design outperformed the previous by significantly reducing equipment losses and anchoring issues. This enhancement in field operations’ simplicity, operability, portability, and resiliency underscores the new system’s potential as a cost-effective and efficient tool for demersal and benthopelagic ecological surveys in challenging coastal seascapes. This innovative BRUVS design offers advanced monitoring solutions, improving habitat assessment accuracy and responsiveness.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rong Zheng, Zhilin Sun, Jiange Jiao, Qianqian Ma, Liqin Zhao
Accurate prediction of estuarine salinity can effectively mitigate the adverse effects of saltwater intrusion and help ensure the safety of water resources in estuarine regions. Presently, diverse data-driven models, mainly neural network models, have been employed to predict tidal estuarine salinity and obtained considerable achievements. Due to the nonlinear and nonstationary features of estuarine salinity sequences, this paper proposed a multi-factor salinity prediction model using an enhanced Long Short-Term Memory (LSTM) network. To improve prediction accuracy, input variables of the model were determined through Grey Relational Analysis (GRA) combined with estuarine dynamic analysis, and hyperparameters for the LSTM model were optimized using a multi-strategy Improved Sparrow Search Algorithm (ISSA). The proposed ISSA-LSTM model was applied to predict salinity at the Cangqian and Qibao stations in the Qiantang Estuary of China, based on measured data from 2011–2012. The model performance is evaluated by mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE). The results show that compared to other models including Back Propagation neural network (BP), Gate Recurrent Unit (GRU), and LSTM model, the new model has smaller errors and higher prediction accuracy, with NSE improved by 8–32% and other metrics (MAP, MAPE, RMSE) improved by 15–67%. Meanwhile, compared with LSTM optimized with the original SSA (SSA-LSTM), MAE, MAPE, and RMSE values of the new model decreased by 13–16%, 15–16%, and 11–13%, and NSE value increased by 5–6%, indicating that the ISSA has a better hyperparameter optimization ability than the original SSA. Thus, the model provides a practical solution for the rapid and precise prediction of estuarine salinity.
{"title":"Salinity Prediction Based on Improved LSTM Model in the Qiantang Estuary, China","authors":"Rong Zheng, Zhilin Sun, Jiange Jiao, Qianqian Ma, Liqin Zhao","doi":"10.3390/jmse12081339","DOIUrl":"https://doi.org/10.3390/jmse12081339","url":null,"abstract":"Accurate prediction of estuarine salinity can effectively mitigate the adverse effects of saltwater intrusion and help ensure the safety of water resources in estuarine regions. Presently, diverse data-driven models, mainly neural network models, have been employed to predict tidal estuarine salinity and obtained considerable achievements. Due to the nonlinear and nonstationary features of estuarine salinity sequences, this paper proposed a multi-factor salinity prediction model using an enhanced Long Short-Term Memory (LSTM) network. To improve prediction accuracy, input variables of the model were determined through Grey Relational Analysis (GRA) combined with estuarine dynamic analysis, and hyperparameters for the LSTM model were optimized using a multi-strategy Improved Sparrow Search Algorithm (ISSA). The proposed ISSA-LSTM model was applied to predict salinity at the Cangqian and Qibao stations in the Qiantang Estuary of China, based on measured data from 2011–2012. The model performance is evaluated by mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE). The results show that compared to other models including Back Propagation neural network (BP), Gate Recurrent Unit (GRU), and LSTM model, the new model has smaller errors and higher prediction accuracy, with NSE improved by 8–32% and other metrics (MAP, MAPE, RMSE) improved by 15–67%. Meanwhile, compared with LSTM optimized with the original SSA (SSA-LSTM), MAE, MAPE, and RMSE values of the new model decreased by 13–16%, 15–16%, and 11–13%, and NSE value increased by 5–6%, indicating that the ISSA has a better hyperparameter optimization ability than the original SSA. Thus, the model provides a practical solution for the rapid and precise prediction of estuarine salinity.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hao Liu, Shenshen Yang, Lei Wang, Yulong Li, Lei Mi, Fangyang Yuan, Cong Ye
Numerical analysis of the sediment erosion of the balance valve in a buoyancy regulation system was performed. A numerical model for the two-phase flow inside the balance valve was constructed based on the discrete phase model. The sediment erosion rate on the balance valve was discussed, and the effects of five parameters were considered. The effects of the sediment concentration and valve opening were found to be significant, while the effects of the pressure difference, sediment density, and size were found to be moderate. The erosion rate, according to the numerical results, increased linearly with the sediment concentration, so long-term operation of a buoyancy regulation system in high-concentration areas should be avoided. The erosion rate was the highest when the valve opening was 46.3%, so half-open operating conditions are not recommended. The erosion rate was proportional to the square root of the pressure difference. However, adjusting the pressure difference may not be an effective method for regulating the total erosion. The superposition of the secondary flow and the main stream caused particles to spiral along with the fluid, resulting in asymmetric erosion at the working edge. The erosion rate on the working edge decreased with the increase in the sediment size. Conversely, the erosion rate on the valve ball surface increased with the sixth power of the sediment size. Considering that large particles are more likely to cause a blockage, it is recommended to install a seawater pretreatment device at the inlet to prevent large sediments from entering the valve and to improve the working life of the buoyancy regulation system.
{"title":"Numerical Analysis of the Sediment Erosion of the Balance Valve in a Buoyancy Regulation System","authors":"Hao Liu, Shenshen Yang, Lei Wang, Yulong Li, Lei Mi, Fangyang Yuan, Cong Ye","doi":"10.3390/jmse12081344","DOIUrl":"https://doi.org/10.3390/jmse12081344","url":null,"abstract":"Numerical analysis of the sediment erosion of the balance valve in a buoyancy regulation system was performed. A numerical model for the two-phase flow inside the balance valve was constructed based on the discrete phase model. The sediment erosion rate on the balance valve was discussed, and the effects of five parameters were considered. The effects of the sediment concentration and valve opening were found to be significant, while the effects of the pressure difference, sediment density, and size were found to be moderate. The erosion rate, according to the numerical results, increased linearly with the sediment concentration, so long-term operation of a buoyancy regulation system in high-concentration areas should be avoided. The erosion rate was the highest when the valve opening was 46.3%, so half-open operating conditions are not recommended. The erosion rate was proportional to the square root of the pressure difference. However, adjusting the pressure difference may not be an effective method for regulating the total erosion. The superposition of the secondary flow and the main stream caused particles to spiral along with the fluid, resulting in asymmetric erosion at the working edge. The erosion rate on the working edge decreased with the increase in the sediment size. Conversely, the erosion rate on the valve ball surface increased with the sixth power of the sediment size. Considering that large particles are more likely to cause a blockage, it is recommended to install a seawater pretreatment device at the inlet to prevent large sediments from entering the valve and to improve the working life of the buoyancy regulation system.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen Fu, Zhihao Zhang, Meixin Yu, Dai Zhou, Hongbo Zhu, Lei Duan, Jiahuang Tu, Zhaolong Han
Investigating the aerodynamic performance and wake characteristics of wind farms under different levels of wake effects is crucial for optimizing wind farm layouts and improving power generation efficiency. The Large Eddy Simulation (LES)–actuator line model (ALM) method is widely used to predict the power generation efficiency of wind farms composed of multiple turbines. This study employs the LES-ALM method to numerically investigate the aerodynamic performance and wake characteristics of a single NREL 5 MW horizontal-axis wind turbine and three such turbines under different wake interaction conditions. For the single turbine case, the results obtained using the LES-ALM method were compared with the existing literature, showing good agreement and confirming its reliability for single turbine scenarios. For the three-turbine wake field problem, considering the aerodynamic performance differences under three cases, the results indicate that spacing has a minor impact on the power coefficient and thrust coefficient of the middle turbine but a significant impact on the downstream turbine. For staggered three-turbine arrangements, unilateral turbulent inflow to the downstream turbine causes significant fluctuations in thrust and torque, while bilateral turbulent inflow leads to more stable thrust and torque. The presence of two upstream turbines causes an acceleration effect at the inflow region of the downstream single turbine, significantly increasing its power coefficient. The findings of this study can provide methodological references for reducing wake effects and optimizing the layout of wind farms.
{"title":"Research on Aerodynamic Characteristics of Three Offshore Wind Turbines Based on Large Eddy Simulation and Actuator Line Model","authors":"Chen Fu, Zhihao Zhang, Meixin Yu, Dai Zhou, Hongbo Zhu, Lei Duan, Jiahuang Tu, Zhaolong Han","doi":"10.3390/jmse12081341","DOIUrl":"https://doi.org/10.3390/jmse12081341","url":null,"abstract":"Investigating the aerodynamic performance and wake characteristics of wind farms under different levels of wake effects is crucial for optimizing wind farm layouts and improving power generation efficiency. The Large Eddy Simulation (LES)–actuator line model (ALM) method is widely used to predict the power generation efficiency of wind farms composed of multiple turbines. This study employs the LES-ALM method to numerically investigate the aerodynamic performance and wake characteristics of a single NREL 5 MW horizontal-axis wind turbine and three such turbines under different wake interaction conditions. For the single turbine case, the results obtained using the LES-ALM method were compared with the existing literature, showing good agreement and confirming its reliability for single turbine scenarios. For the three-turbine wake field problem, considering the aerodynamic performance differences under three cases, the results indicate that spacing has a minor impact on the power coefficient and thrust coefficient of the middle turbine but a significant impact on the downstream turbine. For staggered three-turbine arrangements, unilateral turbulent inflow to the downstream turbine causes significant fluctuations in thrust and torque, while bilateral turbulent inflow leads to more stable thrust and torque. The presence of two upstream turbines causes an acceleration effect at the inflow region of the downstream single turbine, significantly increasing its power coefficient. The findings of this study can provide methodological references for reducing wake effects and optimizing the layout of wind farms.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shenghong Li, Peiliang Li, Shuangyan He, Zhiyan Kuai, Yanzhen Gu, Haoyang Liu, Tao Liu, Yuan Lin
Computer vision in marine ranching enables real-time monitoring of underwater resources. Detecting fish presents challenges due to varying water turbidity and lighting, affecting color consistency. We propose a Foreground Region Convolutional Neural Network (FR-CNN) that combines unsupervised and supervised methods. It introduces an adaptive multiscale regression Gaussian background model to distinguish fish from noise at different scales. Probability density functions integrate spatiotemporal information for object detection, addressing illumination and water quality shifts. FR-CNN achieves 95% mAP with IoU of 0.5, reducing errors from open-source datasets. It updates anchor boxes automatically on local datasets, enhancing object detection accuracy in long-term monitoring. The results analyze fish species behaviors in relation to environmental conditions, validating the method’s practicality.
{"title":"An Automatic Detection and Statistical Method for Underwater Fish Based on Foreground Region Convolution Network (FR-CNN)","authors":"Shenghong Li, Peiliang Li, Shuangyan He, Zhiyan Kuai, Yanzhen Gu, Haoyang Liu, Tao Liu, Yuan Lin","doi":"10.3390/jmse12081343","DOIUrl":"https://doi.org/10.3390/jmse12081343","url":null,"abstract":"Computer vision in marine ranching enables real-time monitoring of underwater resources. Detecting fish presents challenges due to varying water turbidity and lighting, affecting color consistency. We propose a Foreground Region Convolutional Neural Network (FR-CNN) that combines unsupervised and supervised methods. It introduces an adaptive multiscale regression Gaussian background model to distinguish fish from noise at different scales. Probability density functions integrate spatiotemporal information for object detection, addressing illumination and water quality shifts. FR-CNN achieves 95% mAP with IoU of 0.5, reducing errors from open-source datasets. It updates anchor boxes automatically on local datasets, enhancing object detection accuracy in long-term monitoring. The results analyze fish species behaviors in relation to environmental conditions, validating the method’s practicality.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cao Duc Sang, Ngo Van He, Ngo Van Hien, Nguyen Trong Khuyen
This article introduces a new design pattern that provides an optimal solution for the systematic development of AUV controllers. In this study, a hybrid control model is designed on the basis of the OOSEM (Object-Oriented Systems Engineering Method), combined with MDA (Model-Driven Architecture) concepts, real-time UML/SysML (Unified Modeling Language/Systems Modeling Language), and the UKF (unscented Kalman filter) algorithm. This hybrid model enables the implementation of the control elements of autonomous underwater vehicles (AUVs), which are considered HDSs (hybrid dynamic systems), and it can be adapted for reuse for most standard AUV platforms. To achieve this goal, a dynamic AUV model is integrated with the specializations of the OOSEM/MDA, in which an analysis model is clarified via a use-case model definition and then combined with HA (hybrid automata) to precisely define the control requirements. Next, the designed model is tailored via real-time UML/SysML to obtain the core control blocks, which describe the behaviors and structures of the control parts in detail. This design model is then transformed into an implementation model with the assistance of round-trip engineering to conveniently realize a controller for AUVs. Based on this new model, a feasible AUV controller for low-cost, turtle-shaped AUVs is implemented, and it is utilized to perform planar trajectory tracking.
{"title":"An OOSEM-Based Design Pattern for the Development of AUV Controllers","authors":"Cao Duc Sang, Ngo Van He, Ngo Van Hien, Nguyen Trong Khuyen","doi":"10.3390/jmse12081342","DOIUrl":"https://doi.org/10.3390/jmse12081342","url":null,"abstract":"This article introduces a new design pattern that provides an optimal solution for the systematic development of AUV controllers. In this study, a hybrid control model is designed on the basis of the OOSEM (Object-Oriented Systems Engineering Method), combined with MDA (Model-Driven Architecture) concepts, real-time UML/SysML (Unified Modeling Language/Systems Modeling Language), and the UKF (unscented Kalman filter) algorithm. This hybrid model enables the implementation of the control elements of autonomous underwater vehicles (AUVs), which are considered HDSs (hybrid dynamic systems), and it can be adapted for reuse for most standard AUV platforms. To achieve this goal, a dynamic AUV model is integrated with the specializations of the OOSEM/MDA, in which an analysis model is clarified via a use-case model definition and then combined with HA (hybrid automata) to precisely define the control requirements. Next, the designed model is tailored via real-time UML/SysML to obtain the core control blocks, which describe the behaviors and structures of the control parts in detail. This design model is then transformed into an implementation model with the assistance of round-trip engineering to conveniently realize a controller for AUVs. Based on this new model, a feasible AUV controller for low-cost, turtle-shaped AUVs is implemented, and it is utilized to perform planar trajectory tracking.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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