Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8558886
A. Nagano, I. Ueki, T. Hasegawa, K. Ando
Offequatorial extension of equatorial buoy arrays such as Tropical Atmosphere and Ocean/Triangle Trans-Ocean Buoy Network (TAO/TRITON) buoy array is required to monitor global and regional climates. On December 3, 2016, Japan Agency for Marine-Earth Science and Technology (JAMSTEC) deployed a moored buoy (Ph buoy) at 13°N, 137° E in the Philippine Sea and are measuring temperature, salinity, and dissolved oxygen concentration from the sea surface to 300 m and atmospheric parameters. The Philippine Sea is located in the northern edge of the western Pacific warm pool, where atmospheric and oceanic disturbances on timescales from days to decades such as typhoons, cold surges, seasonal march of the East Asian monsoon, Madden-Julian Oscillation, El Niño and Southern Oscillation, and Pacific Decadal Oscillation occur. Global and regional climate changes possibly increase the frequency of occurrences of extreme weather events. Sensors installed on the buoy tower observed tropical depressions in the winter of 2016/2017. In addition, the development and annihilation of the barrier layer, which exists between the bases of the isothermal and mixed layers, were observed by the underwater sensors. The data collected at this mooring site serve to researches on extreme weather events.
{"title":"Ocean-Atmosphere Observations in Philippine Sea by Moored Buoy","authors":"A. Nagano, I. Ueki, T. Hasegawa, K. Ando","doi":"10.1109/OCEANSKOBE.2018.8558886","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8558886","url":null,"abstract":"Offequatorial extension of equatorial buoy arrays such as Tropical Atmosphere and Ocean/Triangle Trans-Ocean Buoy Network (TAO/TRITON) buoy array is required to monitor global and regional climates. On December 3, 2016, Japan Agency for Marine-Earth Science and Technology (JAMSTEC) deployed a moored buoy (Ph buoy) at 13°N, 137° E in the Philippine Sea and are measuring temperature, salinity, and dissolved oxygen concentration from the sea surface to 300 m and atmospheric parameters. The Philippine Sea is located in the northern edge of the western Pacific warm pool, where atmospheric and oceanic disturbances on timescales from days to decades such as typhoons, cold surges, seasonal march of the East Asian monsoon, Madden-Julian Oscillation, El Niño and Southern Oscillation, and Pacific Decadal Oscillation occur. Global and regional climate changes possibly increase the frequency of occurrences of extreme weather events. Sensors installed on the buoy tower observed tropical depressions in the winter of 2016/2017. In addition, the development and annihilation of the barrier layer, which exists between the bases of the isothermal and mixed layers, were observed by the underwater sensors. The data collected at this mooring site serve to researches on extreme weather events.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121617779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559459
K. Takizawa, T. Matsuda, F. Kojima, Ryotaro Suga, H. Yoshida
This paper shows a system configuration of underwater channel sounder (UCS), which enables us to characterize radio propagation in seawater through multi-antenna measurement with a vector network analyzer (VNA) even in the depth of up to 500 m. The UCS has capability of constructing multi-input/multi-output (MIMO) measurement in seawater by utilizing multiple receive antennas and a single transmit antenna that moves along with a 1D stage. Multiple sensors that include a CTD sensor, a tilt meter, and a video camera are also mounted on UCS to give a record on conditions of measurement site precisely. A test dive demonstrated that the UCS works as designed in seawater with depth of around 30 m.
{"title":"Underwater Channel Sounder (UCS) for Characterizing Radio Propagation in Seawater","authors":"K. Takizawa, T. Matsuda, F. Kojima, Ryotaro Suga, H. Yoshida","doi":"10.1109/OCEANSKOBE.2018.8559459","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559459","url":null,"abstract":"This paper shows a system configuration of underwater channel sounder (UCS), which enables us to characterize radio propagation in seawater through multi-antenna measurement with a vector network analyzer (VNA) even in the depth of up to 500 m. The UCS has capability of constructing multi-input/multi-output (MIMO) measurement in seawater by utilizing multiple receive antennas and a single transmit antenna that moves along with a 1D stage. Multiple sensors that include a CTD sensor, a tilt meter, and a video camera are also mounted on UCS to give a record on conditions of measurement site precisely. A test dive demonstrated that the UCS works as designed in seawater with depth of around 30 m.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115101917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559247
Jin Wei Lim, A. Prügel-Bennett, B. Thornton
Scientific surveys using underwater robots can recover a huge volume of seafloor imagery. For mapping applications, these images can be packaged into vast, seamless and georeferenced seafloor visual reconstructions in a routine way, however interpreting this data to extract useful quantitative information typically relies on the manual effort of expert human annotators. This process is often slow and is a bottleneck in the flow of information. This work explores the feasibility of using Machine Learning tools, specifically Convolutional Neural Networks (CNNs) to at least partially automate the annotation process. A CNN was constructed to identify Shinkaia Crosnieri galetheid crabs and Bathymodiolus mussels, which are two distinct megabenthic taxa found in vast numbers in hydrothermally active regions of the seafloor. The CNN was trained with varying numbers of annotated data, where each annotation consisted of a small region surrounding a positive label at the centre of each individual within a seamless seafloor image reconstruction. The performance was assessed using an independent set of annotated data, taken from a separate reconstruction located approximately 500 m away. While the results show that the trained network can be used to classify new datasets at well characterized levels of uncertainty, the performance was found to vary between the different taxa and with a control dataset that showed only unpopulated regions of the seafloor. The analysis suggests that the number of training examples required to achieve a given level of accuracy is subject dependent, and this should be considered by humans when devising annotation strategies that make best use of their efforts to leverage the advantages offered by CNNs.
{"title":"Automated Interpretation of Seafloor Visual Maps Obtained Using Underwater Robots","authors":"Jin Wei Lim, A. Prügel-Bennett, B. Thornton","doi":"10.1109/OCEANSKOBE.2018.8559247","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559247","url":null,"abstract":"Scientific surveys using underwater robots can recover a huge volume of seafloor imagery. For mapping applications, these images can be packaged into vast, seamless and georeferenced seafloor visual reconstructions in a routine way, however interpreting this data to extract useful quantitative information typically relies on the manual effort of expert human annotators. This process is often slow and is a bottleneck in the flow of information. This work explores the feasibility of using Machine Learning tools, specifically Convolutional Neural Networks (CNNs) to at least partially automate the annotation process. A CNN was constructed to identify Shinkaia Crosnieri galetheid crabs and Bathymodiolus mussels, which are two distinct megabenthic taxa found in vast numbers in hydrothermally active regions of the seafloor. The CNN was trained with varying numbers of annotated data, where each annotation consisted of a small region surrounding a positive label at the centre of each individual within a seamless seafloor image reconstruction. The performance was assessed using an independent set of annotated data, taken from a separate reconstruction located approximately 500 m away. While the results show that the trained network can be used to classify new datasets at well characterized levels of uncertainty, the performance was found to vary between the different taxa and with a control dataset that showed only unpopulated regions of the seafloor. The analysis suggests that the number of training examples required to achieve a given level of accuracy is subject dependent, and this should be considered by humans when devising annotation strategies that make best use of their efforts to leverage the advantages offered by CNNs.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127249332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559054
Shuche Wang, Zhiqiang He, K. Niu, Peng Chen, Y. Rong
Impulsive noise can significantly affect the performance of underwater acoustic (UA) orthogonal frequency-division multiplexing (OFDM) systems. In this paper, by utilizing the pilot subcarriers, we propose a novel sparse Bayesian learning based expectation maximization algorithm for joint channel estimation and impulsive noise mitigation in UA OFDM systems. Moreover, an adaptive clipping threshold method together with a minimum mean-squared error estimator are developed to improve the estimation of the positions and amplitudes of impulsive noise. The performance of the proposed algorithm is verified both through numerical simulations and by data collected during a UA communication experiment conducted in December 2015 in the estuary of the Swan River, Western Australia. The results show that the proposed algorithm is more effective in mitigating impulsive noise than existing methods.
{"title":"A Sparse Bayesian Learning Based Joint Channel and Impulsive Noise Estimation Algorithm for Underwater Acoustic OFDM Systems","authors":"Shuche Wang, Zhiqiang He, K. Niu, Peng Chen, Y. Rong","doi":"10.1109/OCEANSKOBE.2018.8559054","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559054","url":null,"abstract":"Impulsive noise can significantly affect the performance of underwater acoustic (UA) orthogonal frequency-division multiplexing (OFDM) systems. In this paper, by utilizing the pilot subcarriers, we propose a novel sparse Bayesian learning based expectation maximization algorithm for joint channel estimation and impulsive noise mitigation in UA OFDM systems. Moreover, an adaptive clipping threshold method together with a minimum mean-squared error estimator are developed to improve the estimation of the positions and amplitudes of impulsive noise. The performance of the proposed algorithm is verified both through numerical simulations and by data collected during a UA communication experiment conducted in December 2015 in the estuary of the Swan River, Western Australia. The results show that the proposed algorithm is more effective in mitigating impulsive noise than existing methods.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128915422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559404
T. Ebihara, G. Leus, H. Ogasawara
In this paper, we propose a novel underwater acoustic communication scheme that achieves energy and spectrum efficiency simultaneously by combining Doppler-resilient orthogonal signal division multiplexing (D-OSDM) and multiple-input multiple-output (MIMO) signaling. We present both the transmitter and receiver processing for MIMO D-OSDM. We evaluate the performance of MIMO D-OSDM in simulations with a large inter-symbol interference (60 symbols) and Doppler spread (maximum Doppler shift of 15 Hz). The simulation results show that MIMO D-OSDM achieves almost the same energy efficiency as normal D-OSDM while doubling the spectrum efficiency. We conclude that MIMO D-OSDM can become a viable technique that achieves reliable and effective UWA communication.
{"title":"Underwater Acoustic Communication Using Multiple-Input Multiple-Output Doppler-Resilient Orthogonal Signal Division Multiplexing","authors":"T. Ebihara, G. Leus, H. Ogasawara","doi":"10.1109/OCEANSKOBE.2018.8559404","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559404","url":null,"abstract":"In this paper, we propose a novel underwater acoustic communication scheme that achieves energy and spectrum efficiency simultaneously by combining Doppler-resilient orthogonal signal division multiplexing (D-OSDM) and multiple-input multiple-output (MIMO) signaling. We present both the transmitter and receiver processing for MIMO D-OSDM. We evaluate the performance of MIMO D-OSDM in simulations with a large inter-symbol interference (60 symbols) and Doppler spread (maximum Doppler shift of 15 Hz). The simulation results show that MIMO D-OSDM achieves almost the same energy efficiency as normal D-OSDM while doubling the spectrum efficiency. We conclude that MIMO D-OSDM can become a viable technique that achieves reliable and effective UWA communication.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125737801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559146
Jitendra S. Sewada, C. Ioana, M. Geen, J. Mars
This research work deals with the resolution problem in Phase Differencing Bathymetric Sonar Systems (PDBS), also called interferometric sonars (“Interferometers”). Wideband signals are compared with the narrowband continuous wave (CW) pulses to assess the relative merits of signals to improve the range and angle resolution. The idea is inspired by the marine mammals, who use complex wideband signals for navigation and target detection. A set of waveforms e.g. CW Pulses, LFM (Linear Frequency Modulated) Pulses, EFM (Exponential Frequency Modulation) Pulses were used with Bathyswath-1 transducers for the experiment. A comparative study was done to assess the set of signals for range and angular resolution of Interferometers. Wideband signal processing techniques are used to solve the problem of trade-off between range and resolution. This paper gives an introduction to interferometry sonars, the major problems with them and the wideband processing approach to improving them.
{"title":"Wideband Signals for Phase Differencing Sonar Systems","authors":"Jitendra S. Sewada, C. Ioana, M. Geen, J. Mars","doi":"10.1109/OCEANSKOBE.2018.8559146","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559146","url":null,"abstract":"This research work deals with the resolution problem in Phase Differencing Bathymetric Sonar Systems (PDBS), also called interferometric sonars (“Interferometers”). Wideband signals are compared with the narrowband continuous wave (CW) pulses to assess the relative merits of signals to improve the range and angle resolution. The idea is inspired by the marine mammals, who use complex wideband signals for navigation and target detection. A set of waveforms e.g. CW Pulses, LFM (Linear Frequency Modulated) Pulses, EFM (Exponential Frequency Modulation) Pulses were used with Bathyswath-1 transducers for the experiment. A comparative study was done to assess the set of signals for range and angular resolution of Interferometers. Wideband signal processing techniques are used to solve the problem of trade-off between range and resolution. This paper gives an introduction to interferometry sonars, the major problems with them and the wideband processing approach to improving them.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127737414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559072
E. Zheldak, V. Petukhov, Kiseon Kim
Traditional way to estimate propagation losses in a region with no actual measures is to use oceanographic climatologies, built from archived data. Usually such statistical models have 0.25°-1° resolution. While it is enough for large-scale ocean acoustic simulation, higher-resolution climatology reflects regional ocean state better. With increasing of resolution, size of the models also increases, which makes it difficult to use them in small autonomous underwater systems, such as underwater sensor networks nodes, where space and power resources are limited. To minimize the size of a model the artificial neural network regression is proposed. To check applicability of method, shallow water area near Jeju island (East China Sea) was choosen. Set of neural networks was trained on data from World Ocean Database 2013. To estimate the error of sound speed profile reconstruction data from SAVEX15 shallow water acoustic experiment was used. Although the RMS error of prediction was high, vertical gradients of sound speed profile was reconstructed with good accuracy, which was shown using propagation loss calculations.
{"title":"Shallow Water Sound Speed Estimation with Neural Networks-Based Nonlinear Regression of Space-Time Variability","authors":"E. Zheldak, V. Petukhov, Kiseon Kim","doi":"10.1109/OCEANSKOBE.2018.8559072","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559072","url":null,"abstract":"Traditional way to estimate propagation losses in a region with no actual measures is to use oceanographic climatologies, built from archived data. Usually such statistical models have 0.25°-1° resolution. While it is enough for large-scale ocean acoustic simulation, higher-resolution climatology reflects regional ocean state better. With increasing of resolution, size of the models also increases, which makes it difficult to use them in small autonomous underwater systems, such as underwater sensor networks nodes, where space and power resources are limited. To minimize the size of a model the artificial neural network regression is proposed. To check applicability of method, shallow water area near Jeju island (East China Sea) was choosen. Set of neural networks was trained on data from World Ocean Database 2013. To estimate the error of sound speed profile reconstruction data from SAVEX15 shallow water acoustic experiment was used. Although the RMS error of prediction was high, vertical gradients of sound speed profile was reconstructed with good accuracy, which was shown using propagation loss calculations.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128651540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559266
Rui Duan, Kunde Yang
This paper presents a formula to calculate the source depth from the arrival angles and the time delay of the direct (D) and surface-reflected (SR) arrivals in the reliable acoustic path (RAP) environment. The formula is valid when the SR path is not significantly refracted. A model-free and real-time method for depth estimation is presented based on the formula and verified using three signals recorded in an experiment, namely, ship-radiated noise, pseudorandom noise, and continuous wave (CW). The estimated depths of the artificial source agree with the measurements using a pressure sensor.
{"title":"An Arrival-Structure-Dependent Formula to Calculate Source Depth in Deep Water","authors":"Rui Duan, Kunde Yang","doi":"10.1109/OCEANSKOBE.2018.8559266","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559266","url":null,"abstract":"This paper presents a formula to calculate the source depth from the arrival angles and the time delay of the direct (D) and surface-reflected (SR) arrivals in the reliable acoustic path (RAP) environment. The formula is valid when the SR path is not significantly refracted. A model-free and real-time method for depth estimation is presented based on the formula and verified using three signals recorded in an experiment, namely, ship-radiated noise, pseudorandom noise, and continuous wave (CW). The estimated depths of the artificial source agree with the measurements using a pressure sensor.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127777290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559399
Zhen Wang, Yi Zheng, Qun Yang, Yue Zhang, Jin-yan Du
Floating underwater anchored platform can be utilized to measure the ocean physical parameters such as current velocity, sound velocity, temperature and salinity. In order to analyze the hydrodynamic interference of floating underwater anchored platform with airfoil section under different current conditions, the flow field distribution and acoustic analysis of the platform structure with four different airfoil sections are simulated and compared. The calculated results including flow velocity, dynamic pressure and flow noise varied around the buoy body are simulated with FLUENT software to obtain the optimized structure with the least disturbance on the flow field. It's concluded that increasing the axial length of platform body section in the same cross-sectional diameter will decrease the flow interference. Hence, the platform body with cross-section of NACA 2424 has the less interference caused by the surrounding current variant on the premise that the airfoil section can satisfy the structural and engineering requirements.1
{"title":"Hydrodynamic and Flow Noise Analysis of Floating Underwater Anchored Platform","authors":"Zhen Wang, Yi Zheng, Qun Yang, Yue Zhang, Jin-yan Du","doi":"10.1109/OCEANSKOBE.2018.8559399","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559399","url":null,"abstract":"Floating underwater anchored platform can be utilized to measure the ocean physical parameters such as current velocity, sound velocity, temperature and salinity. In order to analyze the hydrodynamic interference of floating underwater anchored platform with airfoil section under different current conditions, the flow field distribution and acoustic analysis of the platform structure with four different airfoil sections are simulated and compared. The calculated results including flow velocity, dynamic pressure and flow noise varied around the buoy body are simulated with FLUENT software to obtain the optimized structure with the least disturbance on the flow field. It's concluded that increasing the axial length of platform body section in the same cross-sectional diameter will decrease the flow interference. Hence, the platform body with cross-section of NACA 2424 has the less interference caused by the surrounding current variant on the premise that the airfoil section can satisfy the structural and engineering requirements.1","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133133070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-28DOI: 10.1109/OCEANSKOBE.2018.8559172
Y. Liu, Cheng Chen
SSP cluster analysis was performed in the region with water depth in the range 75 m ∼ 150 m in ECS. By assuming that the water density stratification follows that of the ‐ coordinate, and that the continental shelf region in ECS was a relatively flat one, the SSPs in this region were clustered with the -coordinate. Principle Component Analysis (PCA) method and the Self-Organizing Map (SOM) method were employed to cluster the SSPs calculated from the outputs of the regional FVCOM model. Results suggest the region north of Taiwan fluctuates most and that the region corresponding to each group stretches along the contour line, which agrees with the current system there. Acoustic propagation analysis show that acoustic propagation in different groups show different sensitivities to SSP fluctuation and the source depth could make a difference. The reason lies in the fact that amplitudes for the propagating modes would be excited in different degrees for different source depth so that effect of SSP fluctuation differs greatly.
在ECS中水深在75 m ~ 150 m范围内的区域进行了SSP聚类分析。假设水密度分层遵循-坐标，假设ECS大陆架区域是一个相对平坦的大陆架区域，该区域的ssp聚集在-坐标上。采用主成分分析(PCA)方法和自组织映射(SOM)方法对区域FVCOM模型输出计算的ssp进行聚类。结果表明，台湾北部地区波动最大，各类群对应的区域沿等高线延伸，与台湾北部地区的现行体系一致。声传播分析表明，不同群体的声传播对SSP波动的敏感性不同，且震源深度不同。其原因是由于不同的源深度会激发不同程度的传播模式振幅，因此SSP波动的影响差异很大。
{"title":"Clustering Sound Speed Profiles in East China Sea","authors":"Y. Liu, Cheng Chen","doi":"10.1109/OCEANSKOBE.2018.8559172","DOIUrl":"https://doi.org/10.1109/OCEANSKOBE.2018.8559172","url":null,"abstract":"SSP cluster analysis was performed in the region with water depth in the range 75 m ∼ 150 m in ECS. By assuming that the water density stratification follows that of the ‐ coordinate, and that the continental shelf region in ECS was a relatively flat one, the SSPs in this region were clustered with the -coordinate. Principle Component Analysis (PCA) method and the Self-Organizing Map (SOM) method were employed to cluster the SSPs calculated from the outputs of the regional FVCOM model. Results suggest the region north of Taiwan fluctuates most and that the region corresponding to each group stretches along the contour line, which agrees with the current system there. Acoustic propagation analysis show that acoustic propagation in different groups show different sensitivities to SSP fluctuation and the source depth could make a difference. The reason lies in the fact that amplitudes for the propagating modes would be excited in different degrees for different source depth so that effect of SSP fluctuation differs greatly.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132231934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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