bluuebunny/crossref_metadata_2025 huggingface dataset:
Circular lattice benzene-core PCFs with flat near-zero dispersion for low-power broad-spectrum supercontinuum generation
Authors: Le Tran Bao Tran , Van Lanh Chu
Published: March 2024

A circular photonic crystal fiber infiltrated with benzene with different air-hole diameters is proposed as a new supercontinuum light source. Optical properties related to dispersion, effective mode area, nonlinear coefficient, and attenuation of the fundamental mode are investigated numerically. Two optimized structures are selected and verified against supercontinuum generation (SCG) in detail. The first structure (#F1) possesses all-normal dispersion, while the second (#F2) has a zero-dispersion wavelength. The possibility of coherent, octave-spanning SCG is proved by a 40 fs pulse, 1.064 μm wavelength, and 0.45 kW of power in-coupled into the core of #F1. Otherwise, injecting a 90 fs duration, 1.5 μm wavelength, and 0.555 kW peak power pump pulse into #F2 generates a broad SC spanning 0.76–4.23 μm. With the advantages of flat near-zero dispersion, high nonlinearity, low attenuation, and low input power used for SCG, the proposed fibers may lead to new low-cost all-fiber optical systems.
Renewed diffraction formula using reciprocity
Authors: Xia Yingjie , Feng Xuping
Published: March 2024

We present a new diffraction formula derived from the reciprocal theorem. This formula utilizes secondary waves generated from the unobstructed region of a plane near the diffraction object, with the plane’s normal vector aligned along the source-receiver axis. Importantly, our approach successfully mitigates the mathematical inconsistencies inherent in Kirchhoff’s diffraction formula and eliminates the inclination factor, resulting in a highly effective solution. This method is beneficial for scenarios involving irregularly shaped objects.
Solving the fractional Fornberg-Whitham equation within Caputo framework using the optimal auxiliary function method
Authors: Iqbal Naveed , Hussain Shah , Nazim Tufail Muhammad , Mohammed Wael W
Published: March 2024

In this work, we solve the fractional-order Fornberg-Whitham (FW) problem in the context of the Caputo operator by using the Optimal Auxiliary Function Method. Tables and figures showing full numerical findings indicate the correctness and efficacy of this strategy. The results provide insights into the solution behavior of the FW equation and demonstrate the applicability of the Optimal Auxiliary Function Method. By giving insight on the behavior of the FW equation in a fractional context, this research advances the use of fractional calculus techniques in the solution of complicated differential equations.
Criterion for ultra-fast bubble walls: the impact of hydrodynamic obstruction
Authors: Ai Wen-Yuan , Nagels Xander , Vanvlasselaer Miguel
Published: March 2024

The Bödeker-Moore thermal friction [1] is usually used to determine whether or not a bubble wall can run away. However, the friction on the wall is not necessarily a monotonous function of the wall velocity and could have a maximum before it reaches the Bödeker-Moore limit. In this paper, we compare the maximal hydrodynamic obstruction, a frictional force that exists in local thermal equilibrium, and the Bödeker-Moore thermal friction. We study the former in a fully analytical way, clarifying its physical origin and providing a simple expression for its corresponding critical phase transition strength above which the driving force cannot be balanced out by the maximal hydrodynamic obstruction. We find that for large parameter space, the maximal hydrodynamic obstruction is larger than the Bödeker-Moore thermal friction, indicating that the conventional criterion for the runaway behavior of the bubble wall may have to be modified. We also explain how to apply efficiently the modified criterion to particle physics models and discuss possible limitations of the analysis carried out in this paper.
An experimental and theoretical study on Dy3+-doped ZBLAN fiber laser, core-pumped at 1.1 μm
Authors: Jung Junha , Lee Kyungtaek , Kim Jeehwan , Kim Ingwon , Lee Ju Han
Published: March 2024

An experimental and theoretical investigation into a core-pumped Dy3+-doped ZBLAN fiber laser with 1.1 μm pumping was conducted to figure out a configuration for better slope efficiency. First, the laser was experimentally constructed with a simple Fabry–Pérot cavity incorporating AlF3 no-core fiber endcaps. The maximum output power of 607 mW was obtained readily with a slope efficiency of 25%. Next, a 5-energy level model was adopted for a numerical simulation to figure out the optimum output mirror reflectivity for the particular experimental laser setup in terms of slope efficiency. The best slope efficiency of 30% was shown to be obtainable with an output mirror of a 22% reflection.
Asymmetric nucleation processes in spontaneous mode switch of active matter
Authors: Yang 杨 Bing 冰 , Wang 王 Yanting 延颋
Published: March 2024

Flocking and vortical are two typical motion modes in active matter. Although it is known that the two modes can spontaneously switch between each other in a finite-size system, the switching dynamics remain elusive. In this work, by computer simulation of a two-dimensional Vicsek-like system with 1000 particles, we find from the perspective of the classical nucleation theory that the forward and backward switching dynamics are asymmetric: going from flocking to vortical is a one-step nucleation process, while the opposite is a two-step nucleation process, with the system staying in a metastable state before reaching the final flocking state.
Interplay between topology and localization on superconducting circuits
Authors: Guan 关 Xin 欣 , Huo 霍 Bingyan 炳燕 , Chen 陈 Gang 刚
Published: March 2024

Topological insulators occupy a prominent position in the realm of condensed matter physics. Nevertheless, the presence of strong disorder has the potential to disrupt the integrity of topological states, leading to the localization of all states. This study delves into the intricate interplay between topology and localization within the one-dimensional Su–Schrieffer–Heeger (SSH) model, which incorporates controllable off-diagonal quasi-periodic modulations on superconducting circuits. Through the application of external alternating current (ac) magnetic fluxes, each transmon undergoes controlled driving, enabling independent tuning of all coupling strengths. Within a framework of this model, we construct comprehensive phase diagrams delineating regions characterized by extended topologically nontrivial states, critical localization, and co-existing topological and critical localization phases. The paper also addresses the dynamics of qubit excitations, elucidating distinct quantum state transfers resulting from the intricate interplay between topology and localization. Additionally, we propose a method for detecting diverse quantum phases utilizing existing experimental setups.
Weak Merging Scenario of CLASH Cluster A209
Authors: Feng Wen-Cheng , Yu Heng , Zhao Hai-Hui , Hou Xiao-Lan , Jia Shu-Mei , Li Cheng-Kui , Cheng Yu-Lin , Tozzi Paolo , Sun Ming , Chen Yong
Published: March 2024

We study the structural and dynamical properties of A209 based on Chandra and XMM-Newton observations. We obtain detailed temperature, pressure, and entropy maps with the contour binning method, and find a hot region in the NW direction. The X-ray brightness residual map and corresponding temperature profiles reveal a possible shock front in the NW direction and a cold front feature in the SE direction. Combined with the galaxy luminosity density map we propose a weak merger scenario. A young sub-cluster passing from the SE to NW direction could explain the optical subpeak, the intracluster medium temperature map, the X-ray surface brightness excess, and the X-ray peak offset together.
Influence of spatio-temporal filtering on hand kinematics estimation from high-density EMG signals
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Authors: Sîmpetru Raul C , Cnejevici Vlad , Farina Dario , Del Vecchio Alessandro
Published: March 2024

Objective. Surface electromyography (sEMG) is a non-invasive technique that records the electrical signals generated by muscles through electrodes placed on the skin. sEMG is the state-of-the-art method used to control active upper limb prostheses because of the association between its amplitude and the neural drive sent from the spinal cord to muscles. However, accurately estimating the kinematics of a freely moving human hand using sEMG from extrinsic hand muscles remains a challenge. Deep learning has been recently successfully applied to this problem by mapping raw sEMG signals into kinematics. Nonetheless, the optimal number of EMG signals and the type of pre-processing that would maximize performance have not been investigated yet. Approach. Here, we analyze the impact of these factors on the accuracy in kinematics estimates. For this purpose, we processed monopolar sEMG signals that were originally recorded from 320 electrodes over the forearm muscles of 13 subjects. We used a previously published deep learning method that can map the kinematics of the human hand with real-time resolution. Main results. While myocontrol algorithms essentially use the temporal envelope of the EMG signal as the only EMG feature, we show that our approach requires the full bandwidth of the signal in the temporal domain for accurate estimates. Spatial filtering however, had a smaller impact and low-order spatial filters may be suitable. Moreover, reducing the number of channels by ablation resulted in large performance losses. The highest accuracy was reached with the highest number of available sensors (n = 320). Importantly and unexpected, our results suggest that increasing the number of channels above those used in this study may further enhance the accuracy in predicting the kinematics of the human hand. Significance. We conclude that full bandwidth high-density EMG systems of hundreds of electrodes are needed for accurate kinematic estimates of the human hand.
Effect of toroidal rotation on impurity transport in tokamak improved confinement
Authors: Mochinaga Shota , Kasuya Naohiro , Fukuyama Atsushi , Yagi Masatoshi
Published: March 2024

The centrifugal force effects from toroidal rotation in improved confinement plasmas are analyzed on high-Z impurities in tokamaks. Tungsten (W) transport simulations are performed using the impurity transport code developed in the integrated code TASK. The geometric factors PA
and PB
are introduced into the neoclassical transport coefficients to include the effects of the toroidal rotation, which come from poloidal asymmetry in the high-Z impurity profiles. Inward neoclassical particle pinch driven by the main ion density gradient is enhanced by the poloidal asymmetry to be the dominant mechanism for W accumulation in the plasma central region. Simulations with experimental plasma profiles show good agreement with the experimental results and first-principle simulation results in the H-mode. In the hybrid mode and advanced mode, the impurity accumulation is enhanced in the internal transport barrier (ITB) regions. The condition to suppress impurity accumulation is investigated by calculating dependencies on the toroidal rotation velocity and ITB position. The neoclassical transport is sufficiently small with the prospected ITER condition of the Mach number of main ions Mi
∼ 0.1. The impurity transport inside the ITB is strongly influenced by competition between the density peaking effect and the temperature screening effect, and the present simulations show suppression of the impurity accumulation with the outer ITB position to improve the plasma performance, due to the relatively larger temperature gradient of the main ion.
The influence of landfast ice on the navigation in the Arctic Northeast Passage
Authors: Liu Minjun , Zhao Jiechen , Zhao Jixiang , Gnatiuk Natalia , Shalina Elena , Chen Xuejing , Shao Zhiyuan , Xiao Jing , Chen Ziyi , Zhang Sihan , Zhao Dinglong , Mu Fangru
Published: March 2024

Landfast ice is one of the most important factors that affect the navigation safety of Arctic Northeast and Northwest Passages but usually is treated as drift ice in previous studies. This study focused on the situation of landfast ice in four key traits of the Arctic Northeast Passage from 2007 to 2021 and calculated the navigational windows for different ice-class vessels in the influence of landfast ice. The results show that the extent of landfast ice in these straits generally reaches its maximum from March to June, and decreases to a minimum or even disappears in July and August. The proportion of landfast ice extent in the four straits is quite different, such as Bering Strait (1.3%), De Long Strait (3.6%), Dmitry Laptev and Sannikov Strait (DLS Strait) (53.5%), and Vilkitsky Strait (27.8%). The average navigational windows range from 27 weeks (Bering Strait) to 8 weeks (Vilkitsky Strait) per year, and the Bering Strait showed the smallest increase trend (0.20 weeks per year), while the Vilkitsky Strait experienced the largest increase trend (0.62 weeks per year). The increasing navigational windows in the key straits are beneficial for future commercial and scientific expeditions of polar vessels in the Northeast Passage.
Sea ice drift vector extraction based on feature matching using CS-1 Images
Authors: Yang Y L , Xie T
Published: March 2024

The study emphasizes the crucial role of sea ice drift in Arctic climate research and the protection of human activities. Employing C-SAR/01 (CS-1) imagery as the primary data source, the study assesses the effectiveness of the ORB feature matching algorithm for extracting Arctic Sea ice drift vectors. Additionally, it investigates the spatial distribution variations in the drift vectors extracted from the HH and HV polarization channels. The accuracy of the extracted drift vectors is validated using manually extracted sea ice drift data. Experimental results reveal a significant disparity in the number of drift vectors extracted from CS-1 HV polarization images compared to HH polarization images. The sea ice drift vectors extracted using the Oriented fast and Roasted Bried (ORB) operator demonstrate an average velocity error of less than 0.27 cm/s (0.31 km/d) and an average direction error of less than 5.66° in HV polarization images.
An Elevation Editing Method for Water Bodies in InSAR derived DSM
Authors: Yuan Yibo , Hu Jun , Gui Rong
Published: March 2024

In the InSAR-DSM, which is the Digital Surface Model (DSM) acquired through Interferometric Synthetic Aperture Radar (InSAR), the presence of significant noise, voids, and elevation anomalies in water bodies is pervasive. These disparities arise from factors such as diminished backscattering due to electromagnetic wave absorption by water, surface-based specular reflection, and the impact of temporal decorrelation. To tackle this challenge, an automated elevation editing method for water bodies based on InSAR-DSM is introduced. Water bodies are automatically categorized as oceans, lakes, or rivers based on their morphological characteristics and location criteria. Distinct algorithms are subsequently deployed for elevation editing within each category. Results demonstrate that after editing water body elevations, all missing values within the original InSAR-DSM for water bodies are effectively addressed. Elevation anomalous pixels within water bodies are reduced by 68.5%, and the elevation standard deviation, which reflects elevation variability in water bodies, is decreased by 47.31%. This process effectively rectifies water body elevations within InSAR-DSM.
Extracting shallow water depth from the fusion of multi-temporal ICESat-2 data and multi-spectral imageries
Authors: Zhang Yunsheng , Zuo Longjiao , Zhao Yan , Zhao Le , Liu Yixuan
Published: March 2024

With the development of satellite remote sensing and laser altimetry data, the fusion of laser altimetry data and multi-spectral images for shallow water depth inversion has become an economically convenient way. However, there are few methods that take into account the temporal dimension of data to integrate the results of water depth inversion in multiple temporal phases. In response to this issue, this article proposed a shallow water depth inversion method that integrates multi-source and multi-temporal remote sensing data. This method utilized the random forest (RF) algorithm to estimate the water depth values at different time, taking into account the contextual information of Sentinel-2 imagery and using the overall least squares as the theoretical model to fuse the multi-temporal water depth inversion results. This article took the Yongle Islands in the South China Sea as the research area and conducted the shallow water inversion experiments using ICESat-2 (Ice, Cloud and Land Elevation Satellite 2) data from 5 temporal phases and one Sentinel-2 imagery. The results show that the mean value of RMSE (root mean square error) and R2 (determination coefficient) of the proposed method using single temporal imagery was 1.53m and 0.7610, which outperformed the inversion accuracy of traditional methods that ignore image context information. The RMSE and R2 of the multi-temporal fusion model was 1.15m and 0.8622, which was 0.08m and 0.0199m higher than existing median filtering fusion method.
Interpolation of China’s Nearshore Sea Surface Temperature Based on Information Diffusion with Small Sample Sizes
Authors: Wang Min , Shi Minghang , Xu Yongqi , Cao Xiaomeng , Gu Wenjie
Published: March 2024

Addressing the issue of data sparsity and gaps caused by missing values, this study employs an information diffusion approach to effectively spread information from sparse sample points to monitoring locations. By thoroughly extracting insights from a limited dataset, it achieves more precise interpolation outcomes. To validate the superiority of the information diffusion interpolation technique under conditions of sparse samples, we utilize sea surface temperature (SST) data from the offshore waters of China as a case study. We compare three interpolation methods: Kriging, Gaussian information diffusion, and asymmetric information diffusion. The calculations and comparisons of interpolation results are conducted across varying sample sizes. The findings indicate that in situations with relatively sparse samples, asymmetric information diffusion yields the most favorable results, with Kriging and Gaussian diffusion exhibiting comparable performance. In cases of extremely sparse samples, asymmetric information diffusion yields the lowest interpolation error, followed by Gaussian diffusion, while Kriging performs the least effectively. Thus, when confronted with sample sparsity, the application of the information diffusion interpolation method can yield notably improved results.
Targeted observation for the climatology temperature in the Kuroshio region based on the CNOP approach
Authors: Liu Jingyi , Guo Wuhong , Cui Baolong
Published: March 2024

To reduce the cost of ocean observations and improve prediction accuracy of the Kuroshio region temperature, this study investigates the related targeted observation by using the conditional nonlinear optimal perturbation (CNOP) approach. Results show that the scheme of vertical-integrated energy is more suitable for the identification of sensitive area in the related targeted observation. By conducting a set of observation system simulation experiments (OSSEs), we discovered that the sensitive areas identified by the CNOP exert substantial influence on temperature predictions within the target area. The dynamic diagnosis further indicated that the pressure gradient and Coriolis force in the momentum equations greatly contribute the development of the prediction biases. These findings implied that the implement of CNOP-based targeted observation represents a cost-effective strategy for enhancing temperature predictions in the Kuroshio region.
A Global Coupled Atmosphere-Wave Model System Based on C-Coupler2. Part II: Preliminary Results
Authors: Peng Wei , Li Xiang , Hao Sai , Liu Xiaoyan
Published: March 2024

A global coupled atmosphere-wave model system (MPAS-NWW3) that consists of MPAS-A (Model for Prediction Across Scales-Atmosphere) and NWW3 (the Third Generation Wave Model, WAVEWATHCH III) with C-Coupler2 (the Community Coupler2) is demonstrated with a focus on the atmospheric results in global and the specific marine area in the year 2020. Results from the two-way coupled MPAS-NWW3 model and standalone MPAS-A are compared with reanalysis products. The coupled model performs better in terms of high wind speeds and long valid hours. This indicates that the coupled model has an obvious inhibitory effect on surface wind in areas with strong winds.
Analysis of Acoustic Elements in Northwest Pacific Ocean Based on Operational MODAS Data and Its Response to Kuroshio Seasonal Variation
Authors: Li Yang , Wu Xiangyu , Chen Zhiqiang , Wang Dakui , Wang Xidong , Kuang Xiaodi
Published: March 2024

This study utilized operational MODAS (Modular Ocean Data Assimilation System) data to analyze the seasonal variation of acoustic elements of Northwest Pacific Ocean (NWPO). Combining the seasonal variation of the Kuroshio, it further investigated the impact of the Kuroshio seasonal variation on acoustic properties. The results indicate that the distribution of acoustic elements have significant seasonal variation, with a strong correlation between sonic layer depth and mixed layer depth. The acoustic thermocline depth and thermocline depth show significant correlations in the whole area in winter and spring, while in the rest two seasons, it only occurs in low latitude, the southern part of South China Sea (SCS), and also the Kuroshio area.
Memory of HF radar surface-current assimilation on different forecasting variables of ocean circulation models
Authors: Wu Lunyu , Ning Jinjin , Jiao Yang
Published: March 2024

In this study, using nudging method, the current data from a pair of HF radar along Jiangsu coast was assimilated to unstructured grid models based on FVCOM. Several experiments were conducted to examine the effect of radar data on surface velocity, elevation and sea surface salinity forecast. The results show that the gain of assimilation on surface velocity and elevation forecasts disappeared fast within a few hours, while salinity forecasts can be influenced for more than 10 days. This fast diminishing of the gain of data assimilation on current and elevation can be attributed to the fast wave propagation from elsewhere to the radar coverage area.
Research on underwater unmanned platform route planning based on marine environment constraints
Authors: Guo Zilong , Hong Mei , Zhang Yongchui , Shi Jian , Zhang Yunxiang , Wang Hongrui , Qian Longxia
Published: March 2024

Since the development of unmanned systems, autonomous underwater unmanned platforms have become an important facility for countries to explore the ocean field which play an important role in both military and civilian. In this paper, the route planning of underwater unmanned platform is carried out from three constraints: the risk that affects the operational effectiveness of the unmanned underwater platform, the navigation resistance and the navigation path length. The simulation results show that the model can deal with three constraints reasonably and plan a suitable route.
Risk assessment of ice-class-based navigation in Arctic: a case study in the Vilkitsky Strait
Authors: Chen Xuejing , Zhao Jiechen , Zhao Yiding , Liu Xueqin , Ma Linwei , Liu Minjun , Shao Zhiyuan , Xiao Jing , Chen Ziyi , Zhang Sihan , Zhao Dinglong , Mu Fangru
Published: March 2024

Over the past four decades, the decrease in Arctic sea ice has driven significant growth in vessel traffic through the Arctic passages. A precise and quantitative sea ice risk assessment would be the cornerstone of route planning for Arctic ships. Taking the chokepoint of Arctic Northeast Passage, the Vilkitsky Strait, as an example, the temporal and spatial characteristics of ice conditions in the strait were analyzed based on simulated ice thickness and observed sea ice concentration data from 2012 to 2021. Additionally, navigation risk in the strait was assessed based on the Polar Operational Limit Assessment Risk Indexing System (POLARIS). The results showed that the strait experienced 100% sea ice coverage from December to May, peaking in thickness of nearly 2 m in May, receding starting in June, and presenting ice-free passages by August and September. A significant interannual variability is evident in the timing of sea ice melting and freezing. Moreover, the average navigability of the strait was 365 days for vessels with an ice class of PC3, 72 days for PC6 and fewer than 64 days for those below B1. Remarkably, in 2013, 2014, and 2021, vessels below PC5 had less than 30 navigable days in the strait.
Spatiotemporal Characteristics of the Evaporation Duct in the Kuroshio Extension
Authors: Gao Yuan , Zhang Yongchui , Hong Mei , Wang Ning , Hu Wangjiang , Yan Hengqian , Chen Zhentao
Published: March 2024

The evaporation duct over the sea affects the propagation of electromagnetic waves, impacts the performance of electromagnetic systems accordingly, such as the shipborne radars. In order to reveal the spatiotemporal variations of the evaporation duct in the Kuroshio Extension (KE) region, where is one of the most intense air-sea interaction regions, the study utilized a 30-year ERA5 reanalysis dataset (from 1993 to 2022) and conducted statistical analysis on the monthly, seasonal variations and spatial distribution characteristics of the evaporation duct based on the NPS evaporation duct diagnostic model. The results enrich the database of maritime evaporation duct characteristics and improve the resolution and accuracy compared to previous studies.
Experimental Investigation on a convex Mode-2 internal solitary wave and its induced flow field
Authors: Wang Shaodong , Du Hui , Wei Gang , Xu Junnan , Peng Pai , Xuan Pu , Wang Guanjing
Published: March 2024

The second mode internal solitary wave (Mode-2 ISW) and its wave-induced flow field structure are investigated by conducted physical experiments in a large stratified fluid flume. The Mode-2 ISW is generated by the method of the gravity collapse of fluid, and the measurements of its wave-flow structure are obtained by the combined method of conductivity probe array and particle image velocimetry (PIV). The flow field structure and its influencing factors were analysed quantitatively. The results reveal the characteristic of the Mode-2 ISW waveform and density field and the effect of the wave amplitude on the flow and shear characteristics of induced flow field.
Risk assessment of wave hazard in Guangdong Province
Authors: Jiang Lifang , Xu Weiming , Luo Jun , Hu Jinlei , Yin Yi , Xu Boliang
Published: March 2024

In order to improve the prediction ability of wave hazard levels in the ocean under the jurisdiction of Guangdong Province, this paper uses the wave simulation data to evaluate the wave hazard index of the ocean under the jurisdiction of Guangdong Province, and analyses the risk assessment analysis of wave hazards in the Guangdong Province, which provides data support for future wave disaster prevention and mitigation, coastal development, and spatial planning in Guangdong Province. The significant wave height of the 50-year return period in the coastal areas of Guangdong Province is generally distributed within 9 meters of the territorial sea baseline. The intensity of the return period gradually increases with the distance from the mainland and decreases with the decrease of water depth. In the past 30 years, the sea areas under the jurisdiction of the Guangdong Province are mainly dominated by class III and IV wave heights, with class IV being higher than class III. The frequency of Class IV wave heights in the mainly marine area is more than 90%. The risk level of wave disasters in the coastal waters of Guangdong Province is mainly level IV. However, the risk level of wave disasters in the waters under the jurisdiction of Guangdong Province is mainly Level I.
Response of tidal current to the construction of Yangshan Deepwater Harbor, Shanghai, China
Authors: Mao Wei , Ge Jianzhong , Guo Wenyun
Published: March 2024

A high-resolution ocean model for the Yangshan Deepwater Harbor (YDH), Shanghai, China was established based on FVCOM. Changes of tidal current and water fluxes due the construction of YDH was then investigated thoroughly. Results show that the construction of YDH reduced current velocities in the harbor basin, but led to significant increase of tidal current in the channels.
The Effect of Vehicles Attitude Angle Error on Magnetic Compass Heading Estimation
Authors: Li Ziyaun , Zhang Yanmin , Yang Wentie
Published: March 2024

The three-component magnetic sensor is used to measure the heading of the vehicle. Under working, the magnetic sensor be rotated to the horizontal plane according to the attitude angle of the vehicle, and then the heading estimation is performed. However, the vehicle’s attitude angle measurement errors affect the accuracy of the magnetic sensor measurement’s east and north components and then lead to a false heading result. Based on the relation of magnetic field measurement error and magnetic heading error, the effect model of geomagnetic measurement error on magnetic heading error is derived in this paper. Finally, the characteristics of attitude angle errors on magnetic heading are verified by experiments, and the results show that particular angles can avoid the magnetic compass’s effect by the vehicle’s attitude angle error.
Seawater Dual Parametric Fiber Optic Temperature and Pressure Sensors Demodulated by Machine Learning Method
Authors: Chen Yuren , Yu Yang , Xu Yan , Wang Zhencheng , Li Ning , Xu Wenjie , Zhang Zhenrong
Published: March 2024

By employing polydimethylsiloxane (PDMS) characterized by elevated thermo-optical and elastic-optical coefficients for encapsulating an optical microfiber coupler integrated with a sagnac loop (OMCSL) structure, which exhibits large abrupt field characteristics, a fiber optic sensor capable of simultaneously measuring seawater temperature and pressure can be created. Nevertheless, the utilization of the traditional sensitivity matrix method (SMM) for demodulating the sensor led to unstable and considerably erroneous demodulation results. To enhance the accuracy of the demodulation process, this paper investigates and employs a machine learning method (MLM) for sensor demodulation. This paper centers on the investigation and application of MLM for sensor demodulation. The experimental results exhibit a significant decrease in demodulation error attained via MLM when contrasted with the traditional SMM.
Marine Compass Data Quality Control Method Based on Robust Surface Fitting
Authors: Sang Kaiwei , Kuang Cuilin , Duan Chufeng , Zhang Haonan , Yang Baocai
Published: March 2024

Towed streamer positioning is a key step in offshore seismic exploration, and its positioning accuracy directly affects the imaging quality of subsequent seismic data. Accurate and clean magnetic compass observations are an important guarantee for high-precision towed streamer positioning. However, the existing compass data quality control methods have the problem of insufficient utilization of spatial distribution prior information, which heavily relies on mathematical statistical characteristics of the data while neglecting the crucial factors of streamer shape, bringing about an inadequate elimination of gross errors. In this work, a compass data quality control algorithm based on robust surface fitting is proposed to improve the accuracy of positioning. Firstly, the towed streamer positioning algorithm and the prior information of the spatial structure distribution of the compass are introduced. Secondly, the robust surface fitting to control the quality of compass data is proposed, and the specific process of the algorithm is given. Lastly, the effectiveness of the algorithm is verified by simulation and measured data. The results of simulation experiments indicate that compared with the traditional single-streamer threshold robust algorithm, the new algorithm has a significant effect on the quality control of compass data, and the positioning accuracy of the towed streamer is significantly improved. The positioning precision of along-line direction is improved by 52.1%, and that of the across-line direction by 52.4%. These demonstrate that the proposed new algorithm is effective for detecting and eliminating gross errors in compass observations in real-time operation scenarios, improving the stability of towed streamer shape calculation, which can better ensure the smooth progress of offshore towed streamer seismic exploration operations.
Storm surge forecasting based on physics-informed neural networks in the Bohai Sea
Authors: Fu Cifu , Xiong Jie , Yu Fujiang
Published: March 2024

Physics-informed neural networks (PINN), as a new method of integrating artificial neural networks (ANN) and physical laws, have been considered and applied in the fields of ocean forecasting and ocean research. In this paper, the simplified two-dimensional (2D) storm surge governing equation is introduced into an ANN to establish a PINN-based storm surge forecast model. The numerical simulation results of 14 storm surge events in the Bohai Sea are selected as the PINN training set, and 6.3% of the training set data are randomly selected to reconstruct the storm surge field information. The storm surge reconstructed at each tide station is nearly identical to the storm surge curve simulated by the numerical model, with the root mean square error (RMSE) less than 0.12 m and absolute error of maximum storm surge less than 0.2 m. The analysis of the storm surge field at key moments (storm surge height lager than 1 m) shows that the difference in storm surge field between the PINN reconstruction and the numerical model is generally less than 0.4 m. Two storm surge events in the Bohai Sea are selected as forecast cases, and the same network structure, parameters, and storm surge data assimilation scheme are used for predictions by the ANN, PINN, and numerical model. The results show that compared to the ANN and numerical models, the average relative error of the maximum storm surge predicted by the PINN is reduced by approximately 25%, which significantly improves the forecast accuracy, therefore, the PINN is suitable for storm surge forecasting and research due to its advantages in small sample data training and strong physical meaning.
Research on Underdriven HOV Fault Diagnosis based on Physical Attention-Multidimensional Recurrent Neural Networks
Authors: Zhao Yuchen , Hu Haolong , Jiao Huifeng , Chu Zhenzhong
Published: March 2024

In recent years, underdriven human occupied vehicles (HOVs) have gained immense popularity due to their exceptional maneuverability and efficiency. However, the intricate nature of their propulsion systems, coupled with the harsh underwater environment, presents substantial challenges in terms of fault diagnosis. To address this issue, this study proposes a fault diagnosis approach that leverages the Physical Attention-Multidimensional Recurrent Neural Networks (PA-MDRNN) for underdriven HOV propulsion systems. The PA-MDRNN model is trained using a dataset comprising both normal and faulty HOV propulsion systems. Subsequently, the trained model is utilized for real-time identification and diagnosis of faults. Distinguishing itself from conventional data-driven models, our approach introduces a novel non-consistent attention mechanism based on fundamental computational physical properties. This mechanism operates within the framework of hybrid networks, where attention is computed on the multidimensional mapping results. This computation enhances the focus on desired features that adhere to traditional physical properties, thereby eliminating any training results that contradict established physical laws. Consequently, this approach not only excludes incongruous training outcomes but also reinforces the adherence to physical properties in the finalized training results.
Gaussian Process-Based Model Predictive Control for Autonomous Underwater Vehicles
Authors: Xuyu Shen , Gongwu Sun , Ying Mao , Xuanyu Hu , Zhenzhong Chu
Published: March 2024

Traditional MPC algorithms, assuming constant values, suffer from performance degradation caused by model mismatch. This paper addresses the enhancement of predictability in Autonomous Underwater Vehicles (AUVs) under uncertain disturbances and unknown system dynamics through the design of Model Predictive Controllers (MPCs). We propose a hybrid model that integrates a first-principles nominal model with a learning-based model utilizing Gaussian Processes (GPs). The algorithm addresses the problem of model mismatch in AUV motion control by constructing a precise GP model, which captures the dynamic characteristics of the process through the collection and learning of deviations between the reference model and the controlled system. Additionally, the GP model transforms stochastic constraints into deterministic convex constraints, enhancing safety guarantees in complex and challenging environments. The effectiveness of the proposed algorithm is demonstrated through two simulation examples.
Underwater target recognition algorithm based on improved convolutional neural network: YOLOV5-Improved
Authors: Wu Sheng , Zhang Chaolan , Liu Chao , Jin Yuqiang
Published: March 2024

This paper proposes an underwater identification method based on the YOLOV5-Improved model. The MobileOne module is added to the Backbone network of the previous model to improve the lightweight model and reduce the network complexity. The amount of parameters, the amount of calculation, and the inference time; the CA full-dimensional dynamic convolution module is embedded in the MP module of the previous model to focus on the main features, and better focus on the discriminative features of fishing nets, thereby improving the accuracy of fishing net recognition; in The adaptive spatial feature fusion module ASFF is introduced into the head network of the previous model to perform multi-scale feature fusion and remove useless background information to improve the detection and mining capabilities of smaller targets in complex backgrounds under natural conditions. The final experiment proved that the YOLOV5-Improved model has a good learning effect and faster convergence speed during the training process, and the experimental accuracy can reach 99.6%, which can better detect underwater fishing nets and provide assistance for safe navigation at sea.
Prediction of the sea surface temperature in Perhentian Islands by EMD-LSTM model
Authors: Jiang Lifang , Xu Weiming , Zeng Lihong , Xing Huibin , Yin Yi
Published: March 2024

The increase in the sea surface temperature (SST) is currently an important factor in the decline of coral reef ecosystems worldwide, and SST prediction has always been an important research direction in operational oceanography. This paper collects and analyses the buoy data deployed at Malaysian Perhentian islands and combines CRW data to develop coral bleaching warning products for Malaysian Perhentian islands. The Long Short-Term Memory Network(LSTM) and Empirical Mode Decomposition(EMD)-LSTM methods are used to research the SST prediction, and the differences between the two prediction methods were compared. The research results show that both the LSTM prediction model and the EMD-LSTM prediction model can accurately predict SST, with almost all prediction errors at 0.11°C and 0.01°C, respectively.
A scaled tank experiment for layered stochastic rough interface scattering reflection coefficient
Authors: Wang Mingkai , Gao Bo , Zhou Zhen , Pang Jie
Published: March 2024

The stochastic reflection coefficient of the seabed holds valuable acoustic information about the seabed, making it vital for seabed parameter detection. Therefore, it is crucial to achieve some improved results. In this study, we utilized the small-slope approximation method to obtain the fluctuation characteristics of the reflection coefficient for a layered medium with rough interface. Moreover, we addressed the changes in grazing angle by combining the stochastic rough interface scattering with the layered medium reflection. Initially, we present a simulation result, and subsequently, we conducted a scaled tank experiment to verify the variation characteristics of the reflection coefficient. These findings can serve as a theoretical reference for future seabed exploration.
Discrete Distribution Model of Ship Noise Source in Shipping Channel
Authors: Shan Yuanchun , Jiang Pengfei , Sun Junping , Yi Xuejuan , Lin Jianheng
Published: March 2024

Ship noise plays an important role in low-frequency ocean ambient noise. With the increasingly busy sea traffic, the randomness of the spatiotemporal distribution characteristics of ship noise is also increasing. However, most ships sail in a relatively fixed range in different sea areas. Most of the previous studies assumed that the ship noise sources in shipping channel satisfy a uniformly distribution, actually all kinds of large ships are not uniformly distributed in the shipping channel, and there are also many small boats distributed on the channel that contribute significantly to low-frequency ocean ambient noise. The channel within a certain sea area will be divided into different regions, and ship information (AIS) in different regions will be analyzed statistically in this paper. It is assumed that the ship noise sources in different channel regions are discrete point noise sources that obey a certain spatiotemporal statistical distribution, combined with the noise source level models of different types of ships to form a discrete source model of ship noise in shipping channel. Using the ray propagation theory considering the horizontal refraction of sound energy, the vertical distribution of the ship noise level in this sea area is calculated, and compared with the vertical noise level distribution of ship noise source uniform distribution model, the variation range of noise level vertical distribution of two models is close calculated noise level (such as maximum and minimum values) is consistent with the measured data. The discrete source model of ship noise established in this paper may provide a technical support for predicting low-frequency ambient noise characteristics near the channel.
Research on Noise Reduction Method of Underwater Acoustic Signal Based on CEEMDAN Decomposition-Improved Wavelet Threshold
Authors: Jiang Si Yuan , Zhang Xin Xin , Mo Yi , Huang Yan Jie
Published: March 2024

Due to the complex noise in the ocean environment, the signal-to-noise ratio of the hydrophone receiving signal is often low, making subsequent signal processing difficult. To solve this problem, this paper proposes using CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) decomposition algorithm combined with an improved wavelet threshold algorithm to process the signal, and obtain the reconstructed signal after denoising. In this method, the noise-containing signal is transformed by the function and decomposed into multiple natural mode components with frequencies ranging from high to low using the CEEMDAN algorithm. The correlation component and the non-correlation component are then determined using the cross-correlation function. The non-correlated compinents are denoised using the improved wavelet threshold method and the denoised signal is obtained by reconstructing the signal. Experimental results show that this method can improve the performance of underwater acoustic signal denoising.
Research on Volume Array Based on Curved Disk Transducers
Authors: Cheng Qihang , Yu Siyuan , Wu Hengfei
Published: March 2024

A curved disk transducer with a dual stack structure with a resonant frequency of 800Hz is used as the array element, and the mutual radiation effect between the transducer elements is utilized to form a densely arranged volume array. Based on the formation structure, establish corresponding finite element models in COMSOL software to simulate and analyse the acoustic performance of different volume arrays. Finally, prototype production and array acoustic performance testing were conducted, and the measured data basically matched the simulation results. The results show that compared to a single transducer, utilizing the mutual radiation effect between the transducer elements can effectively reduce the resonant frequency of the volumetric array and expand its operating bandwidth, while also improving the maximum sound source level after formation. In addition, with a reasonable number of array elements, keeping the spacing between the elements constant, the more elements there are, the lower the resonant frequency of the volumetric array, the smaller the quality factor, and the higher the emission voltage response.
A hybrid algorithm based on TDOA and DOA for underwater target localization
Authors: Xing Chuanxi , Cui Jing , Jiang Jiayuan , Wei Guangchun , Dong Saimeng
Published: March 2024

To address the problems of complex scenarios, low accuracy of a single localization algorithm, and high requirements for localization system equipment, this paper proposes a Taylor-weighted least squares algorithm based on Time Differences of Arrival (TDOA) and Direction of Arrival (DOA) joint localization method. The method first performs DOA estimation of the target by the Bayesian algorithm with off-grid sparse reconstruction and converts the obtained orientation information into position coordinates, and finds the final position of the target through iterative operations. The proposed algorithm is compared with the existing TDOA method based on the Chan algorithm and the Taylor algorithm based on the TDOA with the Chan algorithm as the initial value and the Two-Step Weighted Least Squares (TSWLS) algorithm in a simulation environment. The results show that the proposed algorithm has better performance in terms of localization accuracy, noise immunity, stability and is suitable for target localization in underwater.
Weak fluctuating spectral line reconstruction using deep learning
Authors: Li Zhen , Guo Junyuan , Wang Xiaohan
Published: March 2024

The detection of weak fluctuating spectral lines emitted by underwater and surface vehicles poses a challenging problem for passive sonar system. Therefore, a spectral line reconstruction algorithm based on deep learning called the DEDAN, is proposed. The DEDAN learns the time-frequency correlation of spectral lines through end-to-end training and then reconstructs the spatial location of spectral lines. Simulation results show that the DEDAN is robust to ambient noise, and outperforms other reconstruction algorithms at a mixed signal-to-noise ratio as low as -22 dB to -26 dB. Its reconstruction performance is also verified by the measured South China Sea data.
Design of an acoustic direction finding system based on split array frequency domain beamforming algorithm
Authors: Gao Qingze , Xia Shixuan , Yu Fan
Published: March 2024

According to the technical requirement, the principle of the acoustic direction finding and positioning algorithm is introduced, and based on the engineering implementation requirements of split array frequency domain beam forming algorithm, a hardware implementation method based on FPGA +DSP is introduced, which use FPGA to realize the logic control and two pieces of MS320C6678 multi-core DSP to realize the digital beam forming. The hardware system design scheme can realize the program-controlled amplification, filtering, collection, real-time data storage and beam forming processing of the multi-channel acoustic analog signals for acoustic receiving array. At the same time, it can also communicate with the upper computer to achieve upper computer instructions, data transmission, and parameter settings. It has been verified through engineering practice that this scheme has high data processing efficiency and reliable direction finding calculation effect.