Journal of Ocean Engineering and Science最新文献

{"title":"Is a direct numerical simulation (DNS) of Navier-Stokes equations with small enough grid spacing and time-step definitely reliable/correct?","authors":"Shijie Qin ,&nbsp;Yu Yang ,&nbsp;Yongxiang Huang ,&nbsp;Xinyu Mei ,&nbsp;Lipo Wang ,&nbsp;Shijun Liao","doi":"10.1016/j.joes.2024.04.002","DOIUrl":"https://doi.org/10.1016/j.joes.2024.04.002","url":null,"abstract":"<div><p>Turbulence is strongly associated with the vast majority of fluid flows in nature and industry. Traditionally, results given by the direct numerical simulation (DNS) of Navier-Stokes (NS) equations that relate to a famous millennium problem are widely regarded as ‘reliable’ benchmark solutions of turbulence, as long as grid spacing is fine enough (i.e. less than the minimum Kolmogorov scale) and time-step is small enough, say, satisfying the Courant-Friedrichs-Lewy condition (Courant number <span><math><mo>&lt;</mo></math></span> 1). Is this really true? In this paper a two-dimensional sustained turbulent Kolmogorov flow driven by an external body force governed by the NS equations under an initial condition with a spatial symmetry is investigated numerically by the two numerical methods with detailed comparisons: one is the traditional DNS, the other is the ‘clean numerical simulation’ (CNS). In theory, the exact solution must have a kind of spatial symmetry since its initial condition is spatially symmetric. However, it is found that numerical noises of the DNS are quickly enlarged to the same level as the ‘true’ physical solution, which finally destroy the spatial symmetry of the flow field. In other words, the DNS results of the turbulent Kolmogorov flow governed by the NS equations are badly polluted mostly. On the contrary, the numerical noise of the CNS is much smaller than the ‘true’ physical solution of turbulence in a long enough interval of time so that the CNS result is very close to the ‘true’ physical solution and thus can remain symmetric, which can be used as a benchmark solution for comparison. Besides, it is found that numerical noise as a kind of artificial tiny disturbances can lead to huge deviations at large scale on the two-dimensional Kolmogorov turbulence governed by the NS equations, not only quantitatively (even in statistics) but also qualitatively (such as spatial symmetry of flow). This highly suggests that fine enough spatial grid spacing with small enough time-step alone could not guarantee the validity of the DNS of the NS equations: it is only a necessary condition but not sufficient. All of these findings might challenge some of our general beliefs in turbulence: for example, it might be wrong in physics to neglect the influences of small disturbances to NS equations. Our results suggest that, from physical point of view, it should be better to use the Landau-Lifshitz-Navier-Stokes (LLNS) equations, which consider the influence of unavoidable thermal fluctuations, instead of the NS equations, to model turbulent flows.</p></div>","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"9 3","pages":"Pages 293-310"},"PeriodicalIF":7.1,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468013324000214/pdfft?md5=05f9e31d26b4448a68efd583d1819189&pid=1-s2.0-S2468013324000214-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141164449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cooperative control for automatic towing operation by multiple DP tugboats with fully unknown model parameters","authors":"Xu Jiang, Yiming Zhu, Lei Wang, Yiting Wang","doi":"10.1016/j.joes.2023.12.005","DOIUrl":"https://doi.org/10.1016/j.joes.2023.12.005","url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"28 1-2","pages":""},"PeriodicalIF":7.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139194492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A transfer learning-based method for marine machinery diagnosis with small samples in noisy environments","authors":"Yongjin Guo, Chao Gao, Yang Jin, Yintao Li, Jianyao Wang, Qing Li, Hongdong Wang","doi":"10.1016/j.joes.2023.12.004","DOIUrl":"https://doi.org/10.1016/j.joes.2023.12.004","url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"60 5-6","pages":""},"PeriodicalIF":7.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139190660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Message from the head, State Key Laboratory of Ocean Engineering","authors":"","doi":"10.1016/S2468-0133(23)00083-9","DOIUrl":"https://doi.org/10.1016/S2468-0133(23)00083-9","url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"8 6","pages":"Page iv"},"PeriodicalIF":7.1,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468013323000839/pdfft?md5=0c4bd9cec787c566deaf6415bacc2368&pid=1-s2.0-S2468013323000839-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138335387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introduction to the discipline of Naval Architecture and Ocean Engineering, Shanghai Jiao Tong University","authors":"","doi":"10.1016/S2468-0133(23)00082-7","DOIUrl":"https://doi.org/10.1016/S2468-0133(23)00082-7","url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"8 6","pages":"Page iii"},"PeriodicalIF":7.1,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468013323000827/pdfft?md5=7af20a1be10bb317cc526d2967429681&pid=1-s2.0-S2468013323000827-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138335386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eight Key Open Questions in Ocean Engineering","authors":"","doi":"10.1016/S2468-0133(23)00084-0","DOIUrl":"https://doi.org/10.1016/S2468-0133(23)00084-0","url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"8 6","pages":"Pages v-vi"},"PeriodicalIF":7.1,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468013323000840/pdfft?md5=72e18d53f89692bf051e9381e69cd361&pid=1-s2.0-S2468013323000840-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138404240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A machine learning based Bayesian decision support system for efficient navigation of double-ended ferries","authors":"Vergara Daniel ,&nbsp;Alexandersson Martin ,&nbsp;Lang Xiao ,&nbsp;Mao Wengang","doi":"10.1016/j.joes.2023.11.002","DOIUrl":"10.1016/j.joes.2023.11.002","url":null,"abstract":"<div><div>Ships can be operated more efficiently by utilizing intelligent decision support integrated with onboard data collection systems. In this study, a Bayesian optimization-based decision support system, which utilizes ship performance models built by machine learning methods, is proposed to help determine the operational set-points of two engines for double-ended ferries. By optimizing the ferries’ power allocation between the stern and bow engines, the Decision Support System (DSS) will simultaneously attempt to keep the ETA of the ferry fixed under a set of operational constraints using the Bayesian optimization. Its objective is to minimize fuel consumption along individual trips. Based on simulation environment, the DSS can reduce at maximum 40 % fuel consumption with no significant change of the ETA. Final full-scale experiments of a double-ended ferry demonstrated an average of 15 %, where at least half of this saving was achieved by the optimized power allocation between bow and stern engines.</div></div>","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"9 6","pages":"Pages 605-615"},"PeriodicalIF":13.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135615616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of the dynamic response of a floating wind-aquaculture platform under the combined actions of wind, waves and current","authors":"Qixiang Fan, Yuwang Xu, Qianhui Xie, Mengmeng Zhang, H. Ren, Tongxiao Sun","doi":"10.1016/j.joes.2023.11.003","DOIUrl":"https://doi.org/10.1016/j.joes.2023.11.003","url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"22 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139291521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2D CNN-based multi-feature fusion detection method for the magnetic anomaly generated by submarine wake","authors":"Ran Hui, Xiaofeng Liang, Chao Zuo, Zuoshuai Wang","doi":"10.1016/j.joes.2023.11.001","DOIUrl":"https://doi.org/10.1016/j.joes.2023.11.001","url":null,"abstract":"A Two-Dimensional Convolutional Neural Network (2D-CNN)-based multi-feature fusion detection method is proposed to improve the detection performance of the submarine wake magnetic anomaly in view of its characteristics of low frequency and low signal-to-noise ratio (SNR). The method involves pre-processing the original signal by using the Savitzky-Golay (S–G) filter, followed by Residual Structure processing to extract the time-domain information, FFT to extract the frequency domain information and Minimum-Entropy Filter (MEF) for noise analysis. The 2D-CNN model with three processing branches is utilised for further feature extraction and signal judgement. To train the method, Simulated target signal dataset is obtained through the submarine wake magnetic anomaly simulation model, and the simulated original signal is acquired by stacking measured noise. The proposed method exhibits great detection performance for signals with different Signal-to-Noise Ratios (SNRs) and various types of noise, achieving a recognition accuracy of 90 % for signals with SNRs above -10dB. The theoretical detection range of the submarine has been increased to over 1 km, outperforming similar neural networks based on magnetic dipole models.","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"153 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135509793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of enhancement for ocean thermal energy conversion system","authors":"Safaa Malik Abbas,&nbsp;Hend Dakhel Skhaal Alhassany,&nbsp;David Vera,&nbsp;Francisco Jurado","doi":"10.1016/j.joes.2022.03.008","DOIUrl":"10.1016/j.joes.2022.03.008","url":null,"abstract":"<div><p>Ocean thermal energy conversion (OTEC) is a renewable energy source that uses differences in ocean water temperature between warm surface and cold depth to generate electricity. It is an essential link in the carbon neutrality chain and one of the rising sectors of the ocean energy. This paper provides an overview of studies on closed thermodynamic cycles and the numerous difficulties that OTEC technology faces. A description of the thermodynamic cycles incorporating mixed or pure working fluids, as well as the implications of different working fluids on cycle efficiency were also studied. Changes in condensing and evaporating temperatures induced by variations in heat resources affect the efficiency of cycles with pure working fluids. Several strategies, such as intermediate extraction regeneration and heat recovery of ammonia-depleted solution can increase the thermal efficiency with mixed working fluids. In addition, the impact of the ejector on the cycle's performance is examined. Finally, the efficiency-improving strategies are described and summarized. Thermodynamic efficiency can increase using suitable working fluids and taking steps to maximize the rate of ocean thermal energy. To establish which approach is the most effective, different methods have been evaluated and compared under identical operating conditions.</p></div>","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":"8 5","pages":"Pages 533-545"},"PeriodicalIF":7.1,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43258426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}