Decarbonizing maritime transport hinges on transitioning oil-fueled ships (98.4% of the fleet) to renewable and low-carbon fuel types. This shift is crucial for meeting the greenhouse gas (GHG) reduction targets set by the IMO and the EU, with the aim of achieving climate neutrality by 2050. Ammonia, which does not contain carbon atoms that generate CO2, is considered one of the effective solutions for decarbonization in the medium and long term. However, the concurrent increase in nitrogen oxide (NOx) emissions during the ammonia combustion cycle, subject to strict regulation by the MARPOL 73/78 convention, necessitates implementing solutions to reduce them through optimizing the combustion cycle. This publication presents a numerical study on the optimization of diesel and ammonia injection phases in a ship’s medium-speed engine, Wartsila 6L46. The study investigates the exhaust gas emissions and combustion cycle parameters through a high-pressure injection strategy. At an identified 7° CAD injection phase distance between diesel and ammonia, along with an optimal dual-fuel start of injection 10° CAD before TDC, a reduction of 47% in greenhouse gas emissions (GHG = CO2 + CH4 + N2O) was achieved compared to the diesel combustion cycle. This result aligns with the GHG reduction target set by both the IMO and the EU for 2030. Additionally, during the investigation of the thermodynamic combustion characteristics of the cycle, a comparative reduction in NOx of 4.6% was realized. This reduction is linked to the DeNOx process, where the decrease in NOx is offset by an increase in N2O. However, the optimized ammonia combustion cycle results in significant emissions of unburnt NH3, reaching 1.5 g/kWh. In summary, optimizing the combustion cycle of dual ammonia and diesel fuel is essential for achieving efficient and reliable engine performance. Balancing combustion efficiency with emission levels of greenhouse gases, unburned NH3, and NOx is crucial. For the Wartsila 6L46 marine diesel engine, the recommended injection phasing is A710/D717, with a 7° CAD between injection phases.
{"title":"Numerical Study on Optimization of Combustion Cycle Parameters and Exhaust Gas Emissions in Marine Dual-Fuel Engines by Adjusting Ammonia Injection Phases","authors":"Martynas Drazdauskas, Sergejus Lebedevas","doi":"10.3390/jmse12081340","DOIUrl":"https://doi.org/10.3390/jmse12081340","url":null,"abstract":"Decarbonizing maritime transport hinges on transitioning oil-fueled ships (98.4% of the fleet) to renewable and low-carbon fuel types. This shift is crucial for meeting the greenhouse gas (GHG) reduction targets set by the IMO and the EU, with the aim of achieving climate neutrality by 2050. Ammonia, which does not contain carbon atoms that generate CO2, is considered one of the effective solutions for decarbonization in the medium and long term. However, the concurrent increase in nitrogen oxide (NOx) emissions during the ammonia combustion cycle, subject to strict regulation by the MARPOL 73/78 convention, necessitates implementing solutions to reduce them through optimizing the combustion cycle. This publication presents a numerical study on the optimization of diesel and ammonia injection phases in a ship’s medium-speed engine, Wartsila 6L46. The study investigates the exhaust gas emissions and combustion cycle parameters through a high-pressure injection strategy. At an identified 7° CAD injection phase distance between diesel and ammonia, along with an optimal dual-fuel start of injection 10° CAD before TDC, a reduction of 47% in greenhouse gas emissions (GHG = CO2 + CH4 + N2O) was achieved compared to the diesel combustion cycle. This result aligns with the GHG reduction target set by both the IMO and the EU for 2030. Additionally, during the investigation of the thermodynamic combustion characteristics of the cycle, a comparative reduction in NOx of 4.6% was realized. This reduction is linked to the DeNOx process, where the decrease in NOx is offset by an increase in N2O. However, the optimized ammonia combustion cycle results in significant emissions of unburnt NH3, reaching 1.5 g/kWh. In summary, optimizing the combustion cycle of dual ammonia and diesel fuel is essential for achieving efficient and reliable engine performance. Balancing combustion efficiency with emission levels of greenhouse gases, unburned NH3, and NOx is crucial. For the Wartsila 6L46 marine diesel engine, the recommended injection phasing is A710/D717, with a 7° CAD between injection phases.","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":"141936715","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}
Nur Assani, Petar Matić, Danko Kezić, Nikolina Pleić
Flow processes onboard ships are common in order to transport fluids like oil, gas, and water. These processes are controlled by PID controllers, acting on the regulation valves as actuators. In case of a malfunction or refitting, a PID controller needs to be re-adjusted for the optimal control of the process. To avoid experimenting on operational real systems, models are convenient alternatives. When real-time information is needed, digital twin (DT) concepts become highly valuable. The aim of this paper is to analyze and determine the optimal NARX model architecture in order to achieve a higher-accuracy model of a ship’s flow process. An artificial neural network (ANN) was used to model the process in MATLAB. The experiments were performed using a multi-start approach to prevent overtraining. To prove the thesis, statistical analysis of the experimental results was performed. Models were evaluated for generalization using mean squared error (MSE), best fit, and goodness of fit (GoF) measures on two independent datasets. The results indicate the correlation between the number of input delays and the performance of the model. A permuted k-fold cross-validation analysis was used to determine the optimal number of voltage and flow delays, thus defining the number of model inputs. Permutations of training, test, and validation datasets were applied to examine bias due to the data arrangement during training.
{"title":"Modeling Fluid Flow in Ship Systems for Controller Tuning Using an Artificial Neural Network","authors":"Nur Assani, Petar Matić, Danko Kezić, Nikolina Pleić","doi":"10.3390/jmse12081318","DOIUrl":"https://doi.org/10.3390/jmse12081318","url":null,"abstract":"Flow processes onboard ships are common in order to transport fluids like oil, gas, and water. These processes are controlled by PID controllers, acting on the regulation valves as actuators. In case of a malfunction or refitting, a PID controller needs to be re-adjusted for the optimal control of the process. To avoid experimenting on operational real systems, models are convenient alternatives. When real-time information is needed, digital twin (DT) concepts become highly valuable. The aim of this paper is to analyze and determine the optimal NARX model architecture in order to achieve a higher-accuracy model of a ship’s flow process. An artificial neural network (ANN) was used to model the process in MATLAB. The experiments were performed using a multi-start approach to prevent overtraining. To prove the thesis, statistical analysis of the experimental results was performed. Models were evaluated for generalization using mean squared error (MSE), best fit, and goodness of fit (GoF) measures on two independent datasets. The results indicate the correlation between the number of input delays and the performance of the model. A permuted k-fold cross-validation analysis was used to determine the optimal number of voltage and flow delays, thus defining the number of model inputs. Permutations of training, test, and validation datasets were applied to examine bias due to the data arrangement during training.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936721","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}
Chaojin Ding, Wei Su, Zehong Xu, Daqing Gao, En Cheng
Due to the lack of sufficient valid labeled data and severe channel fading, the recognition of various underwater acoustic (UWA) communication modulation types still faces significant challenges. In this paper, we propose a lightweight UWA communication type recognition network based on semi-supervised learning, named the SSL-LRN. In the SSL-LRN, a mean teacher–student mechanism is developed to improve learning performance by averaging the weights of multiple models, thereby improving recognition accuracy for insufficiently labeled data. The SSL-LRN employs techniques such as quantization and small convolutional kernels to reduce floating-point operations (FLOPs), enabling its deployment on underwater mobile nodes. To mitigate the performance loss caused by quantization, the SSL-LRN adopts a channel expansion module to optimize the neuron distribution. It also employs an attention mechanism to enhance the recognition robustness for frequency-selective-fading channels. Pool and lake experiments demonstrate that the framework effectively recognizes most modulation types, achieving a more than 5% increase in recognition accuracy at a 0 dB signal-to-noise ratio (SNRs) while reducing FLOPs by 84.9% compared with baseline algorithms. Even with only 10% labeled data, the performance of the SSL-LRN approaches that of the fully supervised LRN algorithm.
{"title":"SSL-LRN: A Lightweight Semi-Supervised-Learning-Based Approach for UWA Modulation Recognition","authors":"Chaojin Ding, Wei Su, Zehong Xu, Daqing Gao, En Cheng","doi":"10.3390/jmse12081317","DOIUrl":"https://doi.org/10.3390/jmse12081317","url":null,"abstract":"Due to the lack of sufficient valid labeled data and severe channel fading, the recognition of various underwater acoustic (UWA) communication modulation types still faces significant challenges. In this paper, we propose a lightweight UWA communication type recognition network based on semi-supervised learning, named the SSL-LRN. In the SSL-LRN, a mean teacher–student mechanism is developed to improve learning performance by averaging the weights of multiple models, thereby improving recognition accuracy for insufficiently labeled data. The SSL-LRN employs techniques such as quantization and small convolutional kernels to reduce floating-point operations (FLOPs), enabling its deployment on underwater mobile nodes. To mitigate the performance loss caused by quantization, the SSL-LRN adopts a channel expansion module to optimize the neuron distribution. It also employs an attention mechanism to enhance the recognition robustness for frequency-selective-fading channels. Pool and lake experiments demonstrate that the framework effectively recognizes most modulation types, achieving a more than 5% increase in recognition accuracy at a 0 dB signal-to-noise ratio (SNRs) while reducing FLOPs by 84.9% compared with baseline algorithms. Even with only 10% labeled data, the performance of the SSL-LRN approaches that of the fully supervised LRN algorithm.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936899","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}
In recent years, global trade volume has been increasing, and marine transportation plays a significant role here. In marine transportation, the choice of transportation route has been widely discussed. Minimizing fuel consumption, minimizing voyage time, and maximizing voyage security are concerns of the International Maritime Organization (IMO) regarding Maritime Autonomous Surface Ships (MASS). These goals are contradictory and have not yet been effectively resolved. This paper describes the ship path-planning problem as a multi-objective optimization problem that considers fuel consumption, voyage time, and voyage security. The model considers wind and waves as marine environmental factors. Furthermore, this paper uses an improved Whale Optimization Algorithm to solve multi-objective problems. At the same time, it is compared to three advanced algorithms. Through seven three-objective test functions, the performance of the algorithm is tested and applied in path planning. The results indicate that the algorithm can effectively balance the fuel consumption, voyage time, and voyage security of the ship, offering reasonable paths.
{"title":"Improved Whale Optimization Algorithm for Maritime Autonomous Surface Ships Using Three Objectives Path Planning Based on Meteorological Data","authors":"Gongxing Wu, Hongyang Li, Weimin Mo","doi":"10.3390/jmse12081313","DOIUrl":"https://doi.org/10.3390/jmse12081313","url":null,"abstract":"In recent years, global trade volume has been increasing, and marine transportation plays a significant role here. In marine transportation, the choice of transportation route has been widely discussed. Minimizing fuel consumption, minimizing voyage time, and maximizing voyage security are concerns of the International Maritime Organization (IMO) regarding Maritime Autonomous Surface Ships (MASS). These goals are contradictory and have not yet been effectively resolved. This paper describes the ship path-planning problem as a multi-objective optimization problem that considers fuel consumption, voyage time, and voyage security. The model considers wind and waves as marine environmental factors. Furthermore, this paper uses an improved Whale Optimization Algorithm to solve multi-objective problems. At the same time, it is compared to three advanced algorithms. Through seven three-objective test functions, the performance of the algorithm is tested and applied in path planning. The results indicate that the algorithm can effectively balance the fuel consumption, voyage time, and voyage security of the ship, offering reasonable paths.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885219","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}
In scenarios such as nearshore and inland waterways, the ship spots in a marine radar are easily confused with reefs and shorelines, leading to difficulties in ship identification. In such settings, the conventional ARPA method based on fractal detection and filter tracking performs relatively poorly. To accurately identify radar targets in such scenarios, a novel algorithm, namely YOSMR, based on the deep convolutional network, is proposed. The YOSMR uses the MobileNetV3(Large) network to extract ship imaging data of diverse depths and acquire feature data of various ships. Meanwhile, taking into account the issue of feature suppression for small-scale targets in algorithms composed of deep convolutional networks, the feature fusion module known as PANet has been subject to a lightweight reconstruction leveraging depthwise separable convolutions to enhance the extraction of salient features for small-scale ships while reducing model parameters and computational complexity to mitigate overfitting problems. To enhance the scale invariance of convolutional features, the feature extraction backbone is followed by an SPP module, which employs a design of four max-pooling constructs to preserve the prominent ship features within the feature representations. In the prediction head, the Cluster-NMS method and α-DIoU function are used to optimize non-maximum suppression (NMS) and positioning loss of prediction boxes, improving the accuracy and convergence speed of the algorithm. The experiments showed that the recall, accuracy, and precision of YOSMR reached 0.9308, 0.9204, and 0.9215, respectively. The identification efficacy of this algorithm exceeds that of various YOLO algorithms and other lightweight algorithms. In addition, the parameter size and calculational consumption were controlled to only 12.4 M and 8.63 G, respectively, exhibiting an 80.18% and 86.9% decrease compared to the standard YOLO model. As a result, the YOSMR displays a substantial advantage in terms of convolutional computation. Hence, the algorithm achieves an accurate identification of ships with different trail features and various scenes in marine radar images, especially in different interference and extreme scenarios, showing good robustness and applicability.
{"title":"YOSMR: A Ship Detection Method for Marine Radar Based on Customized Lightweight Convolutional Networks","authors":"Zhe Kang, Feng Ma, Chen Chen, Jie Sun","doi":"10.3390/jmse12081316","DOIUrl":"https://doi.org/10.3390/jmse12081316","url":null,"abstract":"In scenarios such as nearshore and inland waterways, the ship spots in a marine radar are easily confused with reefs and shorelines, leading to difficulties in ship identification. In such settings, the conventional ARPA method based on fractal detection and filter tracking performs relatively poorly. To accurately identify radar targets in such scenarios, a novel algorithm, namely YOSMR, based on the deep convolutional network, is proposed. The YOSMR uses the MobileNetV3(Large) network to extract ship imaging data of diverse depths and acquire feature data of various ships. Meanwhile, taking into account the issue of feature suppression for small-scale targets in algorithms composed of deep convolutional networks, the feature fusion module known as PANet has been subject to a lightweight reconstruction leveraging depthwise separable convolutions to enhance the extraction of salient features for small-scale ships while reducing model parameters and computational complexity to mitigate overfitting problems. To enhance the scale invariance of convolutional features, the feature extraction backbone is followed by an SPP module, which employs a design of four max-pooling constructs to preserve the prominent ship features within the feature representations. In the prediction head, the Cluster-NMS method and α-DIoU function are used to optimize non-maximum suppression (NMS) and positioning loss of prediction boxes, improving the accuracy and convergence speed of the algorithm. The experiments showed that the recall, accuracy, and precision of YOSMR reached 0.9308, 0.9204, and 0.9215, respectively. The identification efficacy of this algorithm exceeds that of various YOLO algorithms and other lightweight algorithms. In addition, the parameter size and calculational consumption were controlled to only 12.4 M and 8.63 G, respectively, exhibiting an 80.18% and 86.9% decrease compared to the standard YOLO model. As a result, the YOSMR displays a substantial advantage in terms of convolutional computation. Hence, the algorithm achieves an accurate identification of ships with different trail features and various scenes in marine radar images, especially in different interference and extreme scenarios, showing good robustness and applicability.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885221","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 cruise industry is obliged by economic and environmental initiatives to pursue fuel-efficient solutions and lower ship exhaust emissions. The medium voltage DC (MVDC) distribution with intelligent power management has become a concept for next-generation onboard power systems as its energy-saving feature is to eliminate the frequency constraint and simultaneously optimize engine loads and speed in response to load variations. The incentive for this transition lies on one hand in the fuel efficiency consideration and the reduction of power losses from serial conversion stages. On the other hand, the DC-based technology has been conceived as high-power density design, thus significantly increasing the payload. This study investigates such potential benefits focusing exclusively on large cruise vessels. A highly representative model of the integrated power platform that incorporates all dynamic interactions from the ship hull and essential machinery typically installed on board cruise ships is proposed. The power management strategy also takes account of actual sea conditions and real-time operation requirements. The simulation results demonstrate that the optimization-based MVDC system is able to maximize the opportunity of search agents in finding optimum fuel efficiency areas throughout the scenario time. An analysis of the system structure weight and space reduction of the MVDC architecture is also performed through the utilization of more compact electrical distribution devices and very high power-dense combustion turbines.
{"title":"Power Generation Optimization for Next-Generation Cruise Ships with MVDC Architecture: A Dynamic Modeling and Simulation Approach","authors":"Chalermkiat Nuchturee, Tie Li, Xinyi Zhou","doi":"10.3390/jmse12081315","DOIUrl":"https://doi.org/10.3390/jmse12081315","url":null,"abstract":"The cruise industry is obliged by economic and environmental initiatives to pursue fuel-efficient solutions and lower ship exhaust emissions. The medium voltage DC (MVDC) distribution with intelligent power management has become a concept for next-generation onboard power systems as its energy-saving feature is to eliminate the frequency constraint and simultaneously optimize engine loads and speed in response to load variations. The incentive for this transition lies on one hand in the fuel efficiency consideration and the reduction of power losses from serial conversion stages. On the other hand, the DC-based technology has been conceived as high-power density design, thus significantly increasing the payload. This study investigates such potential benefits focusing exclusively on large cruise vessels. A highly representative model of the integrated power platform that incorporates all dynamic interactions from the ship hull and essential machinery typically installed on board cruise ships is proposed. The power management strategy also takes account of actual sea conditions and real-time operation requirements. The simulation results demonstrate that the optimization-based MVDC system is able to maximize the opportunity of search agents in finding optimum fuel efficiency areas throughout the scenario time. An analysis of the system structure weight and space reduction of the MVDC architecture is also performed through the utilization of more compact electrical distribution devices and very high power-dense combustion turbines.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936720","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}
Bo Wang, Lin Wu, Pengfei Wu, Qianqian Li, Lifeng Bao, Yong Wang
With the development of satellite altimetry technology and the application of new altimetry satellites, the accuracy and resolution of altimeter-derived gravity field models have improved over the last decades. Nowadays, they are close enough to shipborne gravimetry. In this paper, multi-source shipborne gravity data in the South China Sea were taken to evaluate the accuracies of two high-precision altimeter-derived marine gravity field models (SS V30.1, DTU17). In these shipborne gravity data, there are dozens of routes’ ship gravimetry data, obtained from the National Geophysical Data Center (NGDC); data were tracked from a marine survey with a commercial marine gravimeter (type KSS31M), and data were tracked from a marine gravimetry campaign that was conducted with a newly developed platform gravimeter (type JMG) in the South China Sea in September 2020. After various data filtering, processing, and calibrations, the shipborne gravity data were validated with crossover points analysis. Then, the processed shipborne data were employed to evaluate the accuracy of the altimeter-derived marine gravity field models. During this procedure, the quality of JMG shipborne gravity data was compared with the results of KSS31M and NGDC data. Analysis and evaluation results show that the crossover points verification accuracies of KSS31M and JMG are 0.70 mGal and 1.61 mGal, which are much better than the accuracy of NGDC, which is larger than 8.0 mGal. In the area where the bathymetry changes slowly, the root mean square error values between altimetry gravity models and KSS31M data are respectively 3.28 mGal and 4.54 mGal, and those of the JMG data are respectively 2.94 mGal and 2.60 mGal. According to the above results, we can conclude that the JMG has the same 1–2 mGal accuracy level as KSS31M and can meet the measurement requirements of marine gravity.
{"title":"Multidimensional Evaluation of Altimetry Marine Gravity Models with Shipborne Gravity Data from a New Platform Marine Gravimeter","authors":"Bo Wang, Lin Wu, Pengfei Wu, Qianqian Li, Lifeng Bao, Yong Wang","doi":"10.3390/jmse12081314","DOIUrl":"https://doi.org/10.3390/jmse12081314","url":null,"abstract":"With the development of satellite altimetry technology and the application of new altimetry satellites, the accuracy and resolution of altimeter-derived gravity field models have improved over the last decades. Nowadays, they are close enough to shipborne gravimetry. In this paper, multi-source shipborne gravity data in the South China Sea were taken to evaluate the accuracies of two high-precision altimeter-derived marine gravity field models (SS V30.1, DTU17). In these shipborne gravity data, there are dozens of routes’ ship gravimetry data, obtained from the National Geophysical Data Center (NGDC); data were tracked from a marine survey with a commercial marine gravimeter (type KSS31M), and data were tracked from a marine gravimetry campaign that was conducted with a newly developed platform gravimeter (type JMG) in the South China Sea in September 2020. After various data filtering, processing, and calibrations, the shipborne gravity data were validated with crossover points analysis. Then, the processed shipborne data were employed to evaluate the accuracy of the altimeter-derived marine gravity field models. During this procedure, the quality of JMG shipborne gravity data was compared with the results of KSS31M and NGDC data. Analysis and evaluation results show that the crossover points verification accuracies of KSS31M and JMG are 0.70 mGal and 1.61 mGal, which are much better than the accuracy of NGDC, which is larger than 8.0 mGal. In the area where the bathymetry changes slowly, the root mean square error values between altimetry gravity models and KSS31M data are respectively 3.28 mGal and 4.54 mGal, and those of the JMG data are respectively 2.94 mGal and 2.60 mGal. According to the above results, we can conclude that the JMG has the same 1–2 mGal accuracy level as KSS31M and can meet the measurement requirements of marine gravity.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885220","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}
Floating offshore wind turbines (FOWTs) experience unbalanced loads and platform motion due to the coupling of variable wind and wave loads, which leads to output power fluctuation and increased fatigue loads. This paper introduces a new blade pitch control strategy for FOWTs that combines fuzzy logic with a linear quadratic regulator (LQR) and a proportional-integral (PI) controller. The fuzzy PI controller dynamically adjusts the PI control gains to regulate rotor speed and stabilize output power. Fuzzy LQR is employed for individual pitch control, utilizing fuzzy logic to adaptively update feedback gains to achieve stable power output, suppress platform motion, and reduce fatigue load. Co-simulations conducted with OpenFAST (Fatigue, Aerodynamics, Structures, and Turbulence) and MATLAB/Simulink under diverse conditions demonstrate the superiority of the proposed method over traditional PI control. The results show significant reductions in platform pitch, roll, and heave motion by 17%, 27%, and 48%, respectively; blade out-of-plane, pitch, and flapwise bending moments are reduced by 38%, 44%, and 36%; and the tower base roll and pitch bending moments are reduced by up to 29% and 22%, respectively. The proposed control scheme exhibits exceptional environmental adaptability, enhancing FOWT’s power regulation, platform stability, and reliability in complex marine environments.
浮式海上风力涡轮机（FOWT）会因可变风力和波浪载荷的耦合而承受不平衡载荷和平台运动，从而导致输出功率波动和疲劳载荷增加。本文介绍了一种新的 FOWT 叶片俯仰控制策略，它将模糊逻辑与线性二次调节器（LQR）和比例积分（PI）控制器相结合。模糊 PI 控制器动态调整 PI 控制增益，以调节转子速度并稳定输出功率。模糊 LQR 用于单个螺距控制，利用模糊逻辑自适应地更新反馈增益，以实现稳定的功率输出、抑制平台运动并减少疲劳负荷。利用 OpenFAST（疲劳、空气动力学、结构和湍流）和 MATLAB/Simulink，在不同条件下进行了协同模拟，证明了所提出的方法优于传统的 PI 控制。结果表明，平台俯仰、滚动和翻滚运动分别大幅减少了 17%、27% 和 48%；叶片平面外、俯仰和襟翼弯矩分别减少了 38%、44% 和 36%；塔基滚动和俯仰弯矩分别减少了 29% 和 22%。所提出的控制方案具有出色的环境适应性，可提高 FOWT 在复杂海洋环境中的功率调节、平台稳定性和可靠性。
{"title":"A Hybrid Fuzzy LQR-PI Blade Pitch Control Scheme for Spar-Type Floating Offshore Wind Turbines","authors":"Ronglin Ma, Fei Lu Siaw, Tzer Hwai Gilbert Thio","doi":"10.3390/jmse12081306","DOIUrl":"https://doi.org/10.3390/jmse12081306","url":null,"abstract":"Floating offshore wind turbines (FOWTs) experience unbalanced loads and platform motion due to the coupling of variable wind and wave loads, which leads to output power fluctuation and increased fatigue loads. This paper introduces a new blade pitch control strategy for FOWTs that combines fuzzy logic with a linear quadratic regulator (LQR) and a proportional-integral (PI) controller. The fuzzy PI controller dynamically adjusts the PI control gains to regulate rotor speed and stabilize output power. Fuzzy LQR is employed for individual pitch control, utilizing fuzzy logic to adaptively update feedback gains to achieve stable power output, suppress platform motion, and reduce fatigue load. Co-simulations conducted with OpenFAST (Fatigue, Aerodynamics, Structures, and Turbulence) and MATLAB/Simulink under diverse conditions demonstrate the superiority of the proposed method over traditional PI control. The results show significant reductions in platform pitch, roll, and heave motion by 17%, 27%, and 48%, respectively; blade out-of-plane, pitch, and flapwise bending moments are reduced by 38%, 44%, and 36%; and the tower base roll and pitch bending moments are reduced by up to 29% and 22%, respectively. The proposed control scheme exhibits exceptional environmental adaptability, enhancing FOWT’s power regulation, platform stability, and reliability in complex marine environments.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885433","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}
In this research, two distinct designs of protective structures were developed to address structural damage caused by ships impacting the internal structures of floating docks during maintenance operations. The designed protective structures consist of support sections and load-bearing sections, with the load-bearing section comprising three frame sections. For ease of description, the front frame section, middle frame section, and rear frame section are referred to as Frame A, Frame B, and Frame C, respectively. A drop-weight test was conducted with a stern-shaped indenter impacting the structures at 3.89 m/s. This study also assessed varying impact speeds and positions. The results showed that Specimen 2 had localized indentations on Frame B, while Specimen 1 exhibited overall deformation of Frame B and additional deformations in Frame A. The simulations agreed with the experimental results, confirming the model’s accuracy. At speeds from 2.34 m/s to 5.45 m/s, Specimen 2 consistently showed localized deformations, while Specimen 1 showed comprehensive deformation of Frame B at 3.89 m/s due to lower rigidity. When the indenter impacted the specimens at different locations with a speed of 5.45 m/s, the two specimens exhibited varying degrees of damage. As the impact location shifted from the central area to the end, the maximum indentation depth of Specimen 1 decreased from 52.26 mm to 41.71 mm, while that of Specimen 2 decreased from 43.26 mm to 38.50 mm. The reduction in indentation depth and extent as the impact location approached the support frame can be attributed to the increasing involvement of the web plate beneath the frame in resisting the impact. Additionally, compared to Specimen 1, Specimen 2 exhibited a relatively smaller overall indentation depth, and the impact of location variation on indentation depth was also relatively minor.
在这项研究中，开发了两种不同设计的保护结构，以解决船舶在维护作业期间撞击浮动船坞内部结构造成的结构损坏问题。设计的保护结构由支撑部分和承重部分组成，其中承重部分由三个框架部分组成。为便于描述，前框架部分、中框架部分和后框架部分分别称为框架 A、框架 B 和框架 C。在进行落重试验时，使用了一个以 3.89 米/秒速度撞击结构的尾形压头。这项研究还评估了不同的冲击速度和位置。结果表明，试样 2 在框架 B 上有局部压痕，而试样 1 则表现出框架 B 的整体变形和框架 A 的额外变形。在速度为 2.34 米/秒至 5.45 米/秒时，试样 2 始终表现出局部变形，而试样 1 由于刚度较低，在速度为 3.89 米/秒时表现出框架 B 的全面变形。当压头以 5.45 米/秒的速度撞击试样的不同位置时，两个试样表现出不同程度的损坏。当冲击位置从中心区域转移到末端时，试样 1 的最大压痕深度从 52.26 毫米减小到 41.71 毫米，而试样 2 则从 43.26 毫米减小到 38.50 毫米。随着撞击位置接近支撑框架，压痕深度和范围都有所减小，这可能是因为框架下方的腹板越来越多地参与抵抗撞击。此外，与试样 1 相比，试样 2 的总体压痕深度相对较小，位置变化对压痕深度的影响也相对较小。
{"title":"Experimental and Simulation Studies on Protective Structures in Floating Dock","authors":"Zhengyao Wang, Kun Liu, Jingqiao Liu, Qingao Meng, Weijian Qiu, Shuai Zong","doi":"10.3390/jmse12081311","DOIUrl":"https://doi.org/10.3390/jmse12081311","url":null,"abstract":"In this research, two distinct designs of protective structures were developed to address structural damage caused by ships impacting the internal structures of floating docks during maintenance operations. The designed protective structures consist of support sections and load-bearing sections, with the load-bearing section comprising three frame sections. For ease of description, the front frame section, middle frame section, and rear frame section are referred to as Frame A, Frame B, and Frame C, respectively. A drop-weight test was conducted with a stern-shaped indenter impacting the structures at 3.89 m/s. This study also assessed varying impact speeds and positions. The results showed that Specimen 2 had localized indentations on Frame B, while Specimen 1 exhibited overall deformation of Frame B and additional deformations in Frame A. The simulations agreed with the experimental results, confirming the model’s accuracy. At speeds from 2.34 m/s to 5.45 m/s, Specimen 2 consistently showed localized deformations, while Specimen 1 showed comprehensive deformation of Frame B at 3.89 m/s due to lower rigidity. When the indenter impacted the specimens at different locations with a speed of 5.45 m/s, the two specimens exhibited varying degrees of damage. As the impact location shifted from the central area to the end, the maximum indentation depth of Specimen 1 decreased from 52.26 mm to 41.71 mm, while that of Specimen 2 decreased from 43.26 mm to 38.50 mm. The reduction in indentation depth and extent as the impact location approached the support frame can be attributed to the increasing involvement of the web plate beneath the frame in resisting the impact. Additionally, compared to Specimen 1, Specimen 2 exhibited a relatively smaller overall indentation depth, and the impact of location variation on indentation depth was also relatively minor.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885437","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}
Yasi Ye, Xiaoping Liu, Yukang Ye, Anbin Li, Jiaqiang Zhang, Qijiang Ren
The hydrodynamics of the flow around piers affects the motion of ships navigating near these structures, while the motion of the ships, in turn, affects the distribution of the flow field near the piers. This study investigates the forces exerted on a ship in various ship–pier transverse distances using commercial computational fluid dynamics (CFD) software, Fluent 13.0, based on the RNG k-ε model, complemented by experiments with a physical model. The interaction between the ship’s motion and the flow field near the piers was considered. The results indicate that during the encounter between the ship and the pier, the boundary of the approaching ship affects the flow field near the pier, thereby affecting the generation and detachment of vortices behind the pier. The yaw moment of the ship demonstrates a marked “positive peak–negative peak–positive peak” pattern. Moreover, as the ship–pier transverse distance increases, the impact of the pier on the ship’s motion decreases, and it becomes negligible when the distance reaches 0.9 times the diameter of the pier (D), suggesting that the pier has a minimal impact on ship navigation if the ship–pier transverse distance exceeds this threshold.
{"title":"A Sensitivity Analysis of Ship–Bridge Spacing under the Coupling Effect of Turbulence and Ship Motion","authors":"Yasi Ye, Xiaoping Liu, Yukang Ye, Anbin Li, Jiaqiang Zhang, Qijiang Ren","doi":"10.3390/jmse12081308","DOIUrl":"https://doi.org/10.3390/jmse12081308","url":null,"abstract":"The hydrodynamics of the flow around piers affects the motion of ships navigating near these structures, while the motion of the ships, in turn, affects the distribution of the flow field near the piers. This study investigates the forces exerted on a ship in various ship–pier transverse distances using commercial computational fluid dynamics (CFD) software, Fluent 13.0, based on the RNG k-ε model, complemented by experiments with a physical model. The interaction between the ship’s motion and the flow field near the piers was considered. The results indicate that during the encounter between the ship and the pier, the boundary of the approaching ship affects the flow field near the pier, thereby affecting the generation and detachment of vortices behind the pier. The yaw moment of the ship demonstrates a marked “positive peak–negative peak–positive peak” pattern. Moreover, as the ship–pier transverse distance increases, the impact of the pier on the ship’s motion decreases, and it becomes negligible when the distance reaches 0.9 times the diameter of the pier (D), suggesting that the pier has a minimal impact on ship navigation if the ship–pier transverse distance exceeds this threshold.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885438","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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