Solving strategic IMO tasks for the decarbonization of maritime transport and the dynamics of its controlling indicators (EEDI, EEXI, CII) involves the comprehensive use of renewable and low-carbon fuels (LNG, biodiesel, methanol in the mid-term perspective of 2030, ammonia, and hydrogen to achieve zero emissions by 2050) and energy-saving technologies. The technology of regenerating secondary heat sources of the ship’s power plant WHR in the form of an Organic Rankine Cycle (ORC) is considered one of the most promising solutions. The attractiveness of the ORC is justified by the share of the energy potential of WHR at 45–50%, almost half of which are low-temperature WHR (80–90 °C and below). However, according to DNV GL, the widespread adoption of WHR-ORC technologies, especially on operating ships, is hindered by the statistical lack of system prototypes combined with the high cost of implementation. Developing methodological tools for justifying the energy efficiency indicators of WHR–ORC cycle implementation is relevant at all stages of design. The methodological solutions proposed in this article are focused on the initial stages of comparative evaluation of alternative structural solutions (without the need to use detailed technical data of the ship’s systems, power plant, and ORC nodes), expected indicators of energy efficiency, and cycle performance. The development is based on generalized results of variation studies of the ORC in the structure of the widely used main marine medium-speed diesel engine Wärtsilä 12V46F (14,400 kW, 500 min−1) in the operational load cycle range of 25–100% of nominal power. The algorithm of the proposed solutions is based on the established interrelationship of the components of the ORC energy balance in the P-h diagram field of thermodynamic indicators of the cycle working fluid (R134a was used). The implemented strategy does allow, in graphical form, for justifying the choice of working fluid and evaluating the energy performance and efficiency of alternative WHR sources for the main engine, taking into account the design solutions of the power turbine and the technological constraints of the ORC condensation system. The verification of the developed methodological solutions is served by the results of comprehensive variation studies of the ORC performed by the authors using the professionally oriented thermoengineering tool “Thermoflow” and the specification data of Wärtsilä 12V46F with an achieved increase in energy efficiency indicators by 21.4–7%.
{"title":"Methodological Solutions for Predicting Energy Efficiency of Organic Rankine Cycle Waste Heat Recovery Systems Considering Technological Constraints","authors":"Sergejus Lebedevas, Tomas Čepaitis","doi":"10.3390/jmse12081303","DOIUrl":"https://doi.org/10.3390/jmse12081303","url":null,"abstract":"Solving strategic IMO tasks for the decarbonization of maritime transport and the dynamics of its controlling indicators (EEDI, EEXI, CII) involves the comprehensive use of renewable and low-carbon fuels (LNG, biodiesel, methanol in the mid-term perspective of 2030, ammonia, and hydrogen to achieve zero emissions by 2050) and energy-saving technologies. The technology of regenerating secondary heat sources of the ship’s power plant WHR in the form of an Organic Rankine Cycle (ORC) is considered one of the most promising solutions. The attractiveness of the ORC is justified by the share of the energy potential of WHR at 45–50%, almost half of which are low-temperature WHR (80–90 °C and below). However, according to DNV GL, the widespread adoption of WHR-ORC technologies, especially on operating ships, is hindered by the statistical lack of system prototypes combined with the high cost of implementation. Developing methodological tools for justifying the energy efficiency indicators of WHR–ORC cycle implementation is relevant at all stages of design. The methodological solutions proposed in this article are focused on the initial stages of comparative evaluation of alternative structural solutions (without the need to use detailed technical data of the ship’s systems, power plant, and ORC nodes), expected indicators of energy efficiency, and cycle performance. The development is based on generalized results of variation studies of the ORC in the structure of the widely used main marine medium-speed diesel engine Wärtsilä 12V46F (14,400 kW, 500 min−1) in the operational load cycle range of 25–100% of nominal power. The algorithm of the proposed solutions is based on the established interrelationship of the components of the ORC energy balance in the P-h diagram field of thermodynamic indicators of the cycle working fluid (R134a was used). The implemented strategy does allow, in graphical form, for justifying the choice of working fluid and evaluating the energy performance and efficiency of alternative WHR sources for the main engine, taking into account the design solutions of the power turbine and the technological constraints of the ORC condensation system. The verification of the developed methodological solutions is served by the results of comprehensive variation studies of the ORC performed by the authors using the professionally oriented thermoengineering tool “Thermoflow” and the specification data of Wärtsilä 12V46F with an achieved increase in energy efficiency indicators by 21.4–7%.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885230","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}
More and more underwater robots are deployed to investigate marine biodiversity autonomously, and tools are needed by underwater robots to discover and acknowledge marine life. This paper has proposed a convolutional neural network-based method for intelligent fish detection and recognition with a dataset used for training and testing generated and augmented from an open-source Fish Database regarding 6 different types. Firstly, to improve image quality, a hybrid image enhancement algorithm is used to preprocess underwater images with a weighted fusion strategy of multiple traditional methodologies and comparisons have been made to prove the effectiveness according to various indexes. Secondly, to increase detection and recognition accuracy, different attention modules are integrated into the YOLOv5m network structure and the convolutional block attention module(CBAM) has outperformed other modules in recall rate and mAP while maintaining the capability of real-time processing. Lastly, to meet real-time requirements, lightweight adjustments have been made to CBAM-YOLOv5m with the GSConv module and C3Ghost module and a nearly 25% reduction in network parameters and a 20% reduction in computational consumption are obtained. Besides, the lightweight network has realized better accuracy than YOLOv5m. In conclusion, the method proposed in this paper is effective in real-time fish detection and recognition with practical application prospects.
{"title":"Real-Time Underwater Fish Detection and Recognition Based on CBAM-YOLO Network with Lightweight Design","authors":"Zheping Yan, Lichao Hao, Jianmin Yang, Jiajia Zhou","doi":"10.3390/jmse12081302","DOIUrl":"https://doi.org/10.3390/jmse12081302","url":null,"abstract":"More and more underwater robots are deployed to investigate marine biodiversity autonomously, and tools are needed by underwater robots to discover and acknowledge marine life. This paper has proposed a convolutional neural network-based method for intelligent fish detection and recognition with a dataset used for training and testing generated and augmented from an open-source Fish Database regarding 6 different types. Firstly, to improve image quality, a hybrid image enhancement algorithm is used to preprocess underwater images with a weighted fusion strategy of multiple traditional methodologies and comparisons have been made to prove the effectiveness according to various indexes. Secondly, to increase detection and recognition accuracy, different attention modules are integrated into the YOLOv5m network structure and the convolutional block attention module(CBAM) has outperformed other modules in recall rate and mAP while maintaining the capability of real-time processing. Lastly, to meet real-time requirements, lightweight adjustments have been made to CBAM-YOLOv5m with the GSConv module and C3Ghost module and a nearly 25% reduction in network parameters and a 20% reduction in computational consumption are obtained. Besides, the lightweight network has realized better accuracy than YOLOv5m. In conclusion, the method proposed in this paper is effective in real-time fish detection and recognition with practical application prospects.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885227","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}
Alexander Paluzzi, Geoffrey Swain, John DeFrancisci, Daniel Kuchma, Colleen M. Hansel
Steel monopile support structures for offshore wind turbines require protection from corrosion and consideration with respect to biofouling on their external and internal surfaces. Cathodic protection (CP) works effectively to protect the external surfaces of monopiles, but internally, byproducts from aluminum sacrificial anode CP (SACP) and impressed current CP (ICCP) induce acidification that accelerates steel corrosion. Through an 8-week sea water deployment of four steel pipes, this project investigated the effect of perforations on internal CP systems. Additionally, marine growth on the internal and external surfaces of the pipes was assessed. SACP and ICCP systems inside perforated pipes performed similarly to external systems at a lower current demand relative to internal systems in sealed pipes. The organisms that grew inside of the perforated SACP and ICCP pipes were similar, suggesting that the CP systems did not affect organism recruitment. The results of this study demonstrate the potential benefits of designing perforated monopiles to enable corrosion control while providing an artificial reef structure for marine organisms to develop healthy ecosystems.
{"title":"Effects of Perforations on Internal Cathodic Protection and Recruitment of Marine Organisms to Steel Pipes","authors":"Alexander Paluzzi, Geoffrey Swain, John DeFrancisci, Daniel Kuchma, Colleen M. Hansel","doi":"10.3390/jmse12081299","DOIUrl":"https://doi.org/10.3390/jmse12081299","url":null,"abstract":"Steel monopile support structures for offshore wind turbines require protection from corrosion and consideration with respect to biofouling on their external and internal surfaces. Cathodic protection (CP) works effectively to protect the external surfaces of monopiles, but internally, byproducts from aluminum sacrificial anode CP (SACP) and impressed current CP (ICCP) induce acidification that accelerates steel corrosion. Through an 8-week sea water deployment of four steel pipes, this project investigated the effect of perforations on internal CP systems. Additionally, marine growth on the internal and external surfaces of the pipes was assessed. SACP and ICCP systems inside perforated pipes performed similarly to external systems at a lower current demand relative to internal systems in sealed pipes. The organisms that grew inside of the perforated SACP and ICCP pipes were similar, suggesting that the CP systems did not affect organism recruitment. The results of this study demonstrate the potential benefits of designing perforated monopiles to enable corrosion control while providing an artificial reef structure for marine organisms to develop healthy ecosystems.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885224","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}
Accurate habitat prediction of Bigeye Tuna, the main fishing target of tuna pelagic fishery, is of great significance to the fishing operation. In response to the fact that most of the current studies use single-source data for habitat prediction, and the association between spatiotemporal features and habitat distribution is not fully explored and that this has limited the further improvement of prediction accuracy, this paper analyzes the spatiotemporal distribution of the characteristics of Bigeye Tuna’s highly migratory nature. Additionally, it puts forward a method of habitat prediction that utilizes heterosource remote-sensing data for the four-dimensional time–space–environment–spectrum (TSES) for deep-level feature extraction. First, a multi-source heterogeneous dataset was constructed by combining the spatiotemporal distribution characteristics of the product-level environmental remote-sensing data and the L1B-level original spectral remote-sensing data, and then a multi-branch, dynamic spatiotemporal feature extraction, Long Short-Term Memory Network (LSTM) time-series model was constructed to extract the characteristics of the heterogeneous data. This model was constructed to fully explore and utilize the multidimensional deep-level TSES distribution features affecting the habitat prediction. Finally, the two types of heterogeneous data were subjected to the weighted average-based decision-level fusion to obtain the final prediction results. The experimental results show that compared with other methods, the proposed method in this paper outperforms traditional machine-learning models and other single-source, data-based time-series models, with R2 reaching 0.96278 and RMSE decreasing to 0.031361 in the validation experiments of these models. In contrast, the method in this paper demonstrates good generalization ability and achieves accurate prediction of future fishery distribution.
{"title":"Habitat Prediction of Bigeye Tuna Based on Multi-Feature Fusion of Heterogenous Remote-Sensing Data","authors":"Yanling Han, Xiaotong Wang, Haiyang He, Jing Wang, Yun Zhang","doi":"10.3390/jmse12081294","DOIUrl":"https://doi.org/10.3390/jmse12081294","url":null,"abstract":"Accurate habitat prediction of Bigeye Tuna, the main fishing target of tuna pelagic fishery, is of great significance to the fishing operation. In response to the fact that most of the current studies use single-source data for habitat prediction, and the association between spatiotemporal features and habitat distribution is not fully explored and that this has limited the further improvement of prediction accuracy, this paper analyzes the spatiotemporal distribution of the characteristics of Bigeye Tuna’s highly migratory nature. Additionally, it puts forward a method of habitat prediction that utilizes heterosource remote-sensing data for the four-dimensional time–space–environment–spectrum (TSES) for deep-level feature extraction. First, a multi-source heterogeneous dataset was constructed by combining the spatiotemporal distribution characteristics of the product-level environmental remote-sensing data and the L1B-level original spectral remote-sensing data, and then a multi-branch, dynamic spatiotemporal feature extraction, Long Short-Term Memory Network (LSTM) time-series model was constructed to extract the characteristics of the heterogeneous data. This model was constructed to fully explore and utilize the multidimensional deep-level TSES distribution features affecting the habitat prediction. Finally, the two types of heterogeneous data were subjected to the weighted average-based decision-level fusion to obtain the final prediction results. The experimental results show that compared with other methods, the proposed method in this paper outperforms traditional machine-learning models and other single-source, data-based time-series models, with R2 reaching 0.96278 and RMSE decreasing to 0.031361 in the validation experiments of these models. In contrast, the method in this paper demonstrates good generalization ability and achieves accurate prediction of future fishery distribution.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862715","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}
This research investigates the integration of Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs) to enhance sustainable energy generation, focusing on addressing dynamic complexities and uncertainties inherent in such systems. The novelty of this study lies in its dual approach, which integrates regressive modeling with an aero-hydro-elasto-servo-mooring coupled system with a deep data-driven network and implements a proportional-integral-derivative (PID) control mechanism to improve system stability. By employing Artificial Neural Networks (ANNs), the study circumvents the challenges of real-time closed-loop control on FOWT structures using the OpenFAST simulation tool. Data-driven models, trained on OpenFAST datasets, facilitate real-time predictive behavior analysis and decision-making. Advanced computational learning techniques, particularly ANNs, accurately replicate the dynamics of FOWT-OWC numerical models. An intelligent PID control mechanism is subsequently applied to mitigate structural vibrations, ensuring effective control. A comparative analysis with traditional barge-based FOWT systems underscores the enhanced modeling and control methodologies’ effectiveness. In this sense, the experimental results demonstrate substantial reductions in the mean oscillation amplitude, with reductions from 5% to 35% observed across various scenarios. Specifically, at a wave period from 20 s and a wind speed of 5 m/s, the fore-aft displacement was reduced by 35%, exemplifying the PID control system’s robustness and efficacy under diverse conditions. This study highlights the potential of ANN-driven modeling as an alternative to managing the complex non-linear dynamics of NREL 5 MW FOWT models and underscores the significant improvements in system stability through tailored PID gain scheduling across various operational scenarios.
{"title":"Advancing Offshore Renewable Energy: Integrative Approaches in Floating Offshore Wind Turbine-Oscillating Water Column Systems Using Artificial Intelligence-Driven Regressive Modeling and Proportional-Integral-Derivative Control","authors":"Irfan Ahmad, Fares M’zoughi, Payam Aboutalebi, Aitor J. Garrido, Izaskun Garrido","doi":"10.3390/jmse12081292","DOIUrl":"https://doi.org/10.3390/jmse12081292","url":null,"abstract":"This research investigates the integration of Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs) to enhance sustainable energy generation, focusing on addressing dynamic complexities and uncertainties inherent in such systems. The novelty of this study lies in its dual approach, which integrates regressive modeling with an aero-hydro-elasto-servo-mooring coupled system with a deep data-driven network and implements a proportional-integral-derivative (PID) control mechanism to improve system stability. By employing Artificial Neural Networks (ANNs), the study circumvents the challenges of real-time closed-loop control on FOWT structures using the OpenFAST simulation tool. Data-driven models, trained on OpenFAST datasets, facilitate real-time predictive behavior analysis and decision-making. Advanced computational learning techniques, particularly ANNs, accurately replicate the dynamics of FOWT-OWC numerical models. An intelligent PID control mechanism is subsequently applied to mitigate structural vibrations, ensuring effective control. A comparative analysis with traditional barge-based FOWT systems underscores the enhanced modeling and control methodologies’ effectiveness. In this sense, the experimental results demonstrate substantial reductions in the mean oscillation amplitude, with reductions from 5% to 35% observed across various scenarios. Specifically, at a wave period from 20 s and a wind speed of 5 m/s, the fore-aft displacement was reduced by 35%, exemplifying the PID control system’s robustness and efficacy under diverse conditions. This study highlights the potential of ANN-driven modeling as an alternative to managing the complex non-linear dynamics of NREL 5 MW FOWT models and underscores the significant improvements in system stability through tailored PID gain scheduling across various operational scenarios.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862714","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}
Alexander Deen, Shu Kitajima, Waka Sato-Okoshi, Toyonobu Fujii
Coastal shellfish aquaculture can influence benthic–pelagic-coupled systems because cultured species consume phytoplankton in the water column and return the captured organic matter and nutrients to the environment as biodeposits, which fall to the seafloor, affecting local sediment characteristics and the benthic community. In 2023, we conducted monthly field surveys to characterize the relationships between shellfish aquaculture and the surrounding environment by examining a range of physical and biological variables along the benthic–pelagic gradient at multiple sampling locations in relation to their distances from the aquaculture facilities in Onagawa Bay, Japan. The abundances of benthic macrofauna were dominated by polychaetes (86.3%), followed by gastropods (4.7%), malacostracans (2.7%), ophiuroids (2.1%), and bivalves (1.5%). Both benthic biomass and biodiversity were markedly higher, but the chlorophyll-a concentration of the water column and the sediment organic matter content were significantly lower at the closest proximity to the aquaculture facilities. Although the physical presence of shellfish aquaculture may effectively enhance pelagic–benthic energy fluxes, such processes may also pose a new challenge under the influence of recent global warming, causing widespread hypoxic conditions due to increased stratification in the water column accompanied by excess organic inputs from the aquaculture.
{"title":"Seasonal Variability in the Influence of Coastal Aquaculture Operation on Benthic–Pelagic Coupling Processes in Shallow Aquatic Ecosystems","authors":"Alexander Deen, Shu Kitajima, Waka Sato-Okoshi, Toyonobu Fujii","doi":"10.3390/jmse12081293","DOIUrl":"https://doi.org/10.3390/jmse12081293","url":null,"abstract":"Coastal shellfish aquaculture can influence benthic–pelagic-coupled systems because cultured species consume phytoplankton in the water column and return the captured organic matter and nutrients to the environment as biodeposits, which fall to the seafloor, affecting local sediment characteristics and the benthic community. In 2023, we conducted monthly field surveys to characterize the relationships between shellfish aquaculture and the surrounding environment by examining a range of physical and biological variables along the benthic–pelagic gradient at multiple sampling locations in relation to their distances from the aquaculture facilities in Onagawa Bay, Japan. The abundances of benthic macrofauna were dominated by polychaetes (86.3%), followed by gastropods (4.7%), malacostracans (2.7%), ophiuroids (2.1%), and bivalves (1.5%). Both benthic biomass and biodiversity were markedly higher, but the chlorophyll-a concentration of the water column and the sediment organic matter content were significantly lower at the closest proximity to the aquaculture facilities. Although the physical presence of shellfish aquaculture may effectively enhance pelagic–benthic energy fluxes, such processes may also pose a new challenge under the influence of recent global warming, causing widespread hypoxic conditions due to increased stratification in the water column accompanied by excess organic inputs from the aquaculture.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141873424","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}
Yue Wu, Yang Wang, Kai Zhang, Shanfeng Zhang, Ying Wu
This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, a new H∞/H_ performance index, which depends on the membership functions, is defined. Then, based on the membership-function-dependent H∞/H_ performance index, a new fuzzy FD observer strategy, where the fuzzy submodels are not all required to be with the same H_ performance index, is developed to detect the sensor fault in UMVs; the corresponding synthesis conditions of the FD observer are derived based on the Lyapunov theory. Different from the conventional FD strategies, in the proposed membership-function-dependent FD method, the fuzzy submodels—which the system always works on—can have a larger H_ performance index, such that the performance of the FD can be improved. In the end, an example is given to show the effectiveness of the presented method.
{"title":"Fuzzy Fault Detection Observer Design for Unmanned Marine Vehicles Based on Membership-Function-Dependent H∞/H_ Performance","authors":"Yue Wu, Yang Wang, Kai Zhang, Shanfeng Zhang, Ying Wu","doi":"10.3390/jmse12081288","DOIUrl":"https://doi.org/10.3390/jmse12081288","url":null,"abstract":"This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, a new H∞/H_ performance index, which depends on the membership functions, is defined. Then, based on the membership-function-dependent H∞/H_ performance index, a new fuzzy FD observer strategy, where the fuzzy submodels are not all required to be with the same H_ performance index, is developed to detect the sensor fault in UMVs; the corresponding synthesis conditions of the FD observer are derived based on the Lyapunov theory. Different from the conventional FD strategies, in the proposed membership-function-dependent FD method, the fuzzy submodels—which the system always works on—can have a larger H_ performance index, such that the performance of the FD can be improved. In the end, an example is given to show the effectiveness of the presented method.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862796","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}
Stiffened caissons are a new kind of offshore platform foundation which has been widely used in recent years. Stiffeners are employed to avoid buckling during the installation process. However, they also create a significant challenge in terms of understating the soil-flow patterns and corresponding installation resistance prediction. Although centrifuge and in situ tests can simulate the caisson installation process very well, their high costs prevent their widespread application. Model tests have been widely used in research on caisson behavior during installation, as they are convenient and cost less compared to centrifuge and prototype tests. However, the quantitative conclusions of the resulting predictions of installation resistance have some uncertainties because it is quite hard to strictly follow the similarity principle in 1 g model tests. Therefore, it is important to establish a method to calibrate the data from model tests, providing better estimates of caisson behavior in field tests. In our research, large deformation finite element (LDFE) analyses were conducted to provide insights into differences in the outcomes of caisson installation approaches between prototype tests and 1 g model tests. Prior to carrying out parametric studies, validations were conducted with good results. The results show that normalized soil strength significantly influences the behavior of caissons of various dimensions in 1 g model tests. In uniform clay, caissons exhibit consistent installation behavior; otherwise, they show significant differences. Based on systematic research, this paper reveals the mechanisms of the difference between model tests and prototype tests with different sizes of caissons and identifies the factors influencing these differences.
加劲沉箱是近年来广泛使用的一种新型海上平台基础。采用加筋沉箱是为了避免在安装过程中发生屈曲。然而，加固沉箱也给了解土壤流动模式和相应的安装阻力预测带来了巨大挑战。尽管离心试验和现场试验可以很好地模拟沉箱安装过程，但其高昂的成本阻碍了它们的广泛应用。与离心机试验和原型试验相比，模型试验不仅方便，而且成本较低，因此在沉箱安装过程中的行为研究中得到了广泛应用。然而，由于在 1 g 模型试验中很难严格遵循相似性原则，因此得出的安装阻力预测定量结论具有一定的不确定性。因此，必须建立一种方法来校准模型试验的数据，从而更好地估计沉箱在现场试验中的行为。在我们的研究中，进行了大变形有限元（LDFE）分析，以深入了解沉箱安装方法在原型试验和 1 g 模型试验之间的结果差异。在进行参数研究之前，还进行了验证，结果良好。结果表明，在 1 g 模型试验中，归一化土体强度对不同尺寸沉箱的行为有显著影响。在均匀粘土中，沉箱表现出一致的安装行为；反之，则表现出明显的差异。在系统研究的基础上，本文揭示了不同尺寸沉箱的模型试验与原型试验之间存在差异的机理，并确定了影响这些差异的因素。
{"title":"Numerical Simulation of the Behavior of Caisson Based on Physical Modeling","authors":"Sifen Huang, Yuwei Han, Shuyi Li, Mi Zhou","doi":"10.3390/jmse12081284","DOIUrl":"https://doi.org/10.3390/jmse12081284","url":null,"abstract":"Stiffened caissons are a new kind of offshore platform foundation which has been widely used in recent years. Stiffeners are employed to avoid buckling during the installation process. However, they also create a significant challenge in terms of understating the soil-flow patterns and corresponding installation resistance prediction. Although centrifuge and in situ tests can simulate the caisson installation process very well, their high costs prevent their widespread application. Model tests have been widely used in research on caisson behavior during installation, as they are convenient and cost less compared to centrifuge and prototype tests. However, the quantitative conclusions of the resulting predictions of installation resistance have some uncertainties because it is quite hard to strictly follow the similarity principle in 1 g model tests. Therefore, it is important to establish a method to calibrate the data from model tests, providing better estimates of caisson behavior in field tests. In our research, large deformation finite element (LDFE) analyses were conducted to provide insights into differences in the outcomes of caisson installation approaches between prototype tests and 1 g model tests. Prior to carrying out parametric studies, validations were conducted with good results. The results show that normalized soil strength significantly influences the behavior of caissons of various dimensions in 1 g model tests. In uniform clay, caissons exhibit consistent installation behavior; otherwise, they show significant differences. Based on systematic research, this paper reveals the mechanisms of the difference between model tests and prototype tests with different sizes of caissons and identifies the factors influencing these differences.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885222","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}
Configuring green power transmissions for heavy-industry marines is treated as a crucial request in an era of global energy and pollution crises. Following up on this hotspot trend, this paper examines the effectiveness of a modified optimization-based energy management strategy (OpEMS) for a dual proton exchange membrane fuel cells (dPEMFCs)-battery-ultra-capacitors (UCs)-driven hybrid electric vessels (HEVs). At first, the summed power of the dual PEMFCs is defined by using the equivalent consumption minimum strategy (ECMS). Accordingly, a map search engine (MSE) is proposed to appropriately split power for each FC stack and maximize its total efficiency. The remaining power is then distributed to each battery and UC using an adaptive co-state, timely determined based on the state of charge (SOC) of each device. Due to the strict constraint of the energy storage devices’ (ESDs) SOC, one fine-corrected layer is suggested to enhance the SOC regulations. With the comparative simulations with a specific rule-based EMS and other approaches for splitting power to each PEMFC unit, the effectiveness of the proposed topology is eventually verified with the highest efficiency, approximately about 0.505, and well-regulated ESDs’ SOCs are obtained.
{"title":"Enhancing Efficiency in Hybrid Marine Vessels through a Multi-Layer Optimization Energy Management System","authors":"Hoai Vu Anh Truong, Tri Cuong Do, Tri Dung Dang","doi":"10.3390/jmse12081295","DOIUrl":"https://doi.org/10.3390/jmse12081295","url":null,"abstract":"Configuring green power transmissions for heavy-industry marines is treated as a crucial request in an era of global energy and pollution crises. Following up on this hotspot trend, this paper examines the effectiveness of a modified optimization-based energy management strategy (OpEMS) for a dual proton exchange membrane fuel cells (dPEMFCs)-battery-ultra-capacitors (UCs)-driven hybrid electric vessels (HEVs). At first, the summed power of the dual PEMFCs is defined by using the equivalent consumption minimum strategy (ECMS). Accordingly, a map search engine (MSE) is proposed to appropriately split power for each FC stack and maximize its total efficiency. The remaining power is then distributed to each battery and UC using an adaptive co-state, timely determined based on the state of charge (SOC) of each device. Due to the strict constraint of the energy storage devices’ (ESDs) SOC, one fine-corrected layer is suggested to enhance the SOC regulations. With the comparative simulations with a specific rule-based EMS and other approaches for splitting power to each PEMFC unit, the effectiveness of the proposed topology is eventually verified with the highest efficiency, approximately about 0.505, and well-regulated ESDs’ SOCs are obtained.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872651","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}
Aleix Maria-Arenas, Aitor J. Garrido, Izaskun Garrido
Wave energy conversion is a promising field of renewable energy, but it still faces several technological and economic challenges. One of these challenges is to improve the energy efficiency and adaptability of Wave Energy Converters to varying wave conditions. A technological approach to solve this efficiency challenge is the negative spring mechanisms illustrated in recent studies. This paper proposes and analyzes a novel negative spring technological concept that dynamically modifies the mass and inertia of a Wave Energy Converter by transferring seawater between its compartments. The added value of the presented technology relies on interoperability, ease of manufacturing and operating, and increased energy efficiency for heterogeneous sea states. The concept is presented in two analyzed alternatives: a passive one, which requires no electrical consumption and is purely based on the relative motion of the bodies, and an active one, which uses a controlled pump system to force the water transfer. The system is evaluated numerically using widely accepted simulation tools, such as WECSIM, and validated by physical testing in a wave flume using decay and regular test scenarios. Key findings include a relevant discussion about system limitations and a demonstrated increase in the extracted energy efficiency up to 12.7% while limiting the maximum power extraction for a singular wave frequency to 3.41%, indicating an increased adaptability to different wave frequencies because of the amplified range of near-resonance operation of the WEC up to 0.21 rad/s.
{"title":"Enhancing Wave Energy Converters: Dynamic Inertia Strategies for Efficiency Improvement","authors":"Aleix Maria-Arenas, Aitor J. Garrido, Izaskun Garrido","doi":"10.3390/jmse12081285","DOIUrl":"https://doi.org/10.3390/jmse12081285","url":null,"abstract":"Wave energy conversion is a promising field of renewable energy, but it still faces several technological and economic challenges. One of these challenges is to improve the energy efficiency and adaptability of Wave Energy Converters to varying wave conditions. A technological approach to solve this efficiency challenge is the negative spring mechanisms illustrated in recent studies. This paper proposes and analyzes a novel negative spring technological concept that dynamically modifies the mass and inertia of a Wave Energy Converter by transferring seawater between its compartments. The added value of the presented technology relies on interoperability, ease of manufacturing and operating, and increased energy efficiency for heterogeneous sea states. The concept is presented in two analyzed alternatives: a passive one, which requires no electrical consumption and is purely based on the relative motion of the bodies, and an active one, which uses a controlled pump system to force the water transfer. The system is evaluated numerically using widely accepted simulation tools, such as WECSIM, and validated by physical testing in a wave flume using decay and regular test scenarios. Key findings include a relevant discussion about system limitations and a demonstrated increase in the extracted energy efficiency up to 12.7% while limiting the maximum power extraction for a singular wave frequency to 3.41%, indicating an increased adaptability to different wave frequencies because of the amplified range of near-resonance operation of the WEC up to 0.21 rad/s.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862793","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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