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The realism of ocean visual systems is a key challenge in developing maritime simulators within ocean engineering. Achieving high realism in turbulence simulation is crucial for enhancing the effectiveness of these simulators. Traditional spectrum-based methods lack realism and fail to generate turbulent interaction effects. To address this, an improved Hybrid Smoothed Particle Hydrodynamics method is proposed for simulating ocean scenes, incorporating advanced micropolar fluid model techniques to enhance detail realism. The proposed algorithm introduces a density constraint solver that directly adjusts particle distribution and couples it with a divergence-free velocity solver, aiming to construct a physical-based fluid simulation framework that enhances detail realism in ocean scene simulations. The results demonstrate that the proposed method effectively accelerates the convergence of constraint conditions, reduces simulation time, and improves overall incompressibility. Additionally, the introduced turbulence model addresses high-frequency detail loss caused by numerical dissipation in the Smoothed Particle Hydrodynamics method, enabling more complex navigation scenarios. This study provides theoretical and technical references for achieving realistic ocean scene simulations in maritime simulators.

Timely and effective maintenance is imperative to minimize operational disruptions and ensure the reliability of marine vessels. However, given the low early warning rates and poor adaptability under complex conditions of previous data-driven fault prediction methods, this paper presents a hybrid deep learning model based on multi-layer attention mechanisms for predicting faults in a marine diesel engine. Specifically, this hybrid model first introduces a Convolutional Neural Network (CNN) and self-attention to extract local features from multi-feature input sequences. Then, we utilize Long Short-Term Memory (LSTM) and multi-head attention to capture global correlations across time steps. Finally, the hybrid deep learning model is integrated with the Exponential Weighted Moving Average (EWMA) to monitor the operational status and predict potential faults in the marine diesel engine. We conducted extensive evaluations using real datasets under three operating conditions. The experimental results indicate that the proposed method outperforms the current state-of-the-art methods. Moreover, ablation studies and visualizations highlight the importance of fusing multi-layer attention, and the results under various operating conditions and application scenarios demonstrate that this method possesses predictive accuracy and broad applicability. Hence, this approach can provide decision support for condition monitoring and predictive maintenance of marine mechanical systems.

In inland waterways, there is a high density of various objects, with a predominance of small objects, which can easily affect navigation safety. To improve the navigation safety of inland ships, this paper proposes a new lightweight water-surface object-detection model named LWS-YOLOv7, which is based on the baseline model YOLOv7. Firstly, the localization loss function is improved and the w-CIoU function is introduced to reduce the model’s sensitivity to position deviations of small objects and to improve the allocation accuracy of positive and negative sample labels. Secondly, a new receptive field amplification module named GSPPCSPC is proposed to reduce the model’s parameters and enhance its receptive field. Thirdly, a small-object feature-fusion layer, P2, is added to improve the recall rate of small objects. Finally, based on the LAMP model pruning method, the weights with lower importance are pruned to simplify the parameters and computational complexity of the model, facilitating the deployment of the model on shipborne devices. The experimental results demonstrate that, compared to the original YOLOv7 model, the map of LWS-YOLOv7 increased by 3.1%, the parameters decreased by 38.8%, and the GFLOPS decreased by 28.8%. Moreover, the model not only has better performance and higher speed for input images of different sizes, but it can also be applied to different meteorological conditions.

Abstract Background Rosai-Dorfman disease (RDD) is a rare, non-Langerhans cell histiocytosis of unknown etiology. we report a very rare case of recurrent central nervous system RDD with KRAS gene mutation and review the literature to improve our understanding of this disease. Case presentation A 19-year-old male patient was admitted to our hospital for headache. Cranial magnetic resonance imaging revealed a mass of abnormal signal shadows in the prepontine cistern. The mass was surgically removed and the patient was consequently diagnosed with intracranial Rosai-Dorfman disease. Seven months later, pathological examination confirmed that the RDD had recurred. Next-generation sequencing found KRAS mutation in exon 4 (C.351A > C. P. K117n). Conclusion RDD of the CNS has no distinct clinical manifestations and imaging characteristics, and the final diagnosis should be based on the results of the pathological examination. Although RDD is not currently classified as a neoplastic disorder, some evidence of clonality has changed our understanding of it. Follow up examinations over a long period are necessary to determine the efficacy of treatment.

To solve the global path planning problem of the ship in the static and dynamic environment, we propose an improved ant colony algorithm to plan the ship’s navigation path. We use the artificial potential field method to compute the force direction of the ship at the initial iteration stage. The attraction potential field function is modified to improve the iteration efficiency of the hybrid ant colony algorithm. We design the pseudo-random state transition rule and improve the convergence of the hybrid algorithm by strengthening the selection of good paths. When updating the pheromone, we consider the path’s length, safety, and smoothness to plan a safer navigation path. The simulation results show that the improved ant colony algorithm has a faster convergence speed than the original ant colony algorithm. The optimal solution quality is higher, which can realize global ship path planning in static and dynamic environments.

To effectively address the increase in maritime accidents and the challenges posed by the trend toward larger ships for maritime safety, it is crucial to rationally allocate the limited maritime search and rescue (MSAR) resources and enhance accident response capabilities. We present a comprehensive method for allocating MSAR resources, aiming to improve the overall efficiency of MSAR operations. First, we use long short-term memory to predict the number of future accidents and employ the K-medoids algorithm to identify the accident black spots in the studied area. Next, we analyze the multi-constraint conditions in the MSAR resource allocation process. A multi-objective integer programming model is constructed to minimize the response time and allocation cost. Finally, we use the non-dominated sorting genetic algorithm II (DNSGA-II) with Deb’s rules to solve the model, and we propose a multi-attribute decision optimization-based method for MSAR resource allocation. We found that the DNSGA-II exhibits better convergence and generates higher-quality solutions compared to the NSGA-II, particle swarm optimization (PSO), and enhanced particle swarm optimization (EPSO) algorithms. Compared with the existing MSAR resource emergency response system, the optimized scheme reduces the response time and allocation cost by 11.32% and 6.15%, respectively. The proposed method can offer decision makers new insights when formulating MSAR resource allocation plans.

In this paper, we introduce PyVT, an open-source Python toolkit for preprocessing and analysis of vessel spatio-temporal trajectories. The toolkit realizes four functions: trajectory preprocessing, trajectory data management, trajectory mining, and trajectory visualization. The toolkit is simple to use, provides satisfactory default parameter settings, and makes it easy for basic users to use and replicate its functionality in proprietary applications. More advanced users can further adjust the functions to meet their needs by optimizing parameters. At the same time, its design focuses on composability and reusability, making it functional modular and maintainable, allowing for further development.

In order to reduce the cost of navigation training in the waters of ice zones and improve the effectiveness of the training process, a method for simulating sea ice fragmentation in an ice zone navigation simulator is proposed. The Voronoi diagram algorithm, which takes the ice thickness into account and affects the degree of fragmentation, was used to preprocess the sea ice model so that the number and sizes of the ice model fragmentations would be related to the ice thickness. According to the position of the preprocessed sub-blocks of the ice model, the collision bodies of the Mesh Collider and Sphere Collider were set up to realize the effect of the conduction of ice cracking as a result of the ship’s hull colliding with the ice surface. Based on the positional relationship between mesh triangle elements and the water surface, the volume of an ice floe that should have been underwater when it reached equilibrium was calculated to achieve the sea-floating effect of the broken ice floe. The quadtree method for the management of sea ice scenes was improved to improve the timeliness of the replacement of the ice model. The experiments show that this method improved the realism of simulations of sea ice breaking in ice zones and can be used for simulations in ice zone navigation simulators.

In recent years, the research on ship behavior and ship berthing behavior is a hot topic in the navigation theory research, but the research on ship berthing behavior evaluation is relatively less. Based on the navigation theory, the characteristics of ship berthing behavior (including course, course changes, speed, speed changes and ship position) are extracted, and the berthing behavior evaluation index system is established. According to the characteristics of each behavior, the mathematical description is given for quantitative analysis. Based on the principle of “safety, stability and efficiency”, the evaluation standard is determined for each evaluation index, and the evaluation model is established. The Z-score method is used to standardize the evaluation index data, and the critical method is used to calculate the objective weight of each evaluation index; finally, the model is used to get the evaluation results of each berthing behavior. In this paper, the evaluation model is tested by using the one month’s AIS (Automatic Identification System) berthing data of Tianjin port, and the evaluation results are in line with the actual navigation.

Rosai-Dorfman disease (RDD) is an uncommon condition characterized by the proliferation of histiocytes and multiple intracranial involvements and it is extremely rare. Here, we present two cases of multiple intracranial RDD mimicking meningioma. These patients underwent surgery for tumour resection and pathological findings revealed an increased number of IgG4-positive plasma cells in RDD. The radiographic appearance and histology may contribute to a diagnostic dilemma, and immunohistochemical and serological examinations are a necessary complement for definitive diagnosis. Treatment protocols pertaining to such types of RDD cases are reviewed. Currently, surgical resection is the most effective therapy, and steroid therapy, radiotherapy, or chemotherapy may be provided as adjuvant treatments in some selected patients.

Operational efficiency is one of the key performance indicators of a port’s service level. In the process of making scheduling plans for container terminals, different types of equipment are usually scheduled separately. The interaction between quay cranes (QCs) and automated guided vehicles (AGVs) is neglected, which results in low operational efficiency. This research explores the integrated scheduling problem of QCs and AGVs. Firstly, a multi-objective mixed integer programming model (MOMIP) is conducted, with the aim of minimizing the makespan of vessels and the unladen time of AGVs. Then, embedded with a new heuristic method, the non-dominated sorting genetic algorithm-II (NSGA-II) is designed for the scheduling problem. The heuristic method includes two parts: a bay-based QC allocation strategy and a container-based QC-AGV scheduling strategy. Finally, in order to test the performance of the proposed algorithm, differently sized benchmark tests are performed, and the results are compared to the multi-objective particle swarm optimization algorithm (MOPSO) and the weighted-sum method. The computational results indicate that the proposed algorithm can effectively solve the multi-objective integrated scheduling problem of QCs and AGVs. For large-scale problems, the NSGA-II algorithm has better performance and more obvious advantages compared to others. The proposed method has the capability of providing a theoretical reference for the QC and AGV scheduling of container terminals.

In this study, we propose a real-time ship anomaly detection method driven by Automatic Identification System (AIS) data. The method uses ship trajectory clustering classes as a normal model and a deep learning algorithm as an anomaly detection tool. The method is divided into three main steps: (1) quality maintenance of the original AIS data, (2) extraction of normal ship trajectory clusters using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), in which a segmented improved Dynamic Time Warping (DTW) algorithm is used to measure the degree of trajectory similarity, (3) the clustering results are used as a normative model to train a Bi-directional Gated Recurrent Unit (BiGRU) recurrent neural network, which is used as a trajectory predictor to achieve real-time ship anomaly detection. Experiments were conducted using real AIS data from the port of Tianjin, China. The experimental results are manifold. Firstly, the data pre-processing process effectively improves the quality of raw AIS data. Secondly, the ship trajectory clustering model can accurately classify the traffic flow of different modes in the sea area. Moreover, the trajectory prediction result of the BiGRU model has the smallest error with the actual ship trajectory and has a better trajectory prediction performance compared with the Long Short-Term Memory Network model (LSTM) and Gated Recurrent Unit (GRU). In the final anomaly detection experiment, the detection accuracy and timeliness of the BiGRU model are also higher than LSTM and GRU. Therefore, the proposed method can achieve effective and timely detection of ship anomalous behaviors in terms of position, heading and speed during ship navigation, which provides insight to enhance the intelligence of marine traffic supervision and improve the safety of marine navigation.

For the design of ship equipment and crew training, it would be useful to develop software for the three-dimensional simulation of a totally enclosed lifeboat. To improve the simulation accuracy and immersion of the software, we present a multibody dynamics model for a lifeboat lowered from a ship, accounting for the coupled motion among the ship, lifeboat slings, a cable-pulley system, and the lifeboat. The equations of the whole system are formulated using Kane's method. The model of ship manoeuvring mathematical group is used to calculate the forces and moments acting on the hull of the ship. The hydrodynamic and wind loads on the boat are modeled using the strip theory. The impact force between the ship and the boat colliding is estimated using the contact theory of Hertz and an elastoplastic model. The method of lumped mass is used to model the lifeboat slings. For the cable-pulley system, we present an efficient model for the dynamics of the pay-out/reel-in process based on the framework of Kane's method. The local load of each cable segment between two pulleys is calculated by the model of a linear spring on the basis of the amount of cable passages over pulleys and the variation of the pulley positions, conversely, the cable segment exerts force and moment on the pulleys. The motion equations of the whole system are solved using fourth-order Runge-Kutta. The model can simulate the lowering of the lifeboat, and obtain the three-dimensional motion parameters of the ship, the lifeboat, slings and pulleys, and the local tension load of the cable. The results show that the simulation curves are near the ones of the model experiment, and their trends are coincident. Thus, it can be concluded that our model is feasible. According to our model, the motion of the ship has a significant effect on the magnitude of the lifeboat's oscillation when the sea state is above level 4; it is safe when the initial clear distance is greater than 1.5 times the width of the boat and the sea conditions are below level 5. Finally, the model is applied to the software for three-dimensional simulation.

The students generally lack the overall grasp about navigation and the operation practice of equipment and instruments on board under the current education mode. The simulator based on virtual reality has become an important way in learning and training. As a result, this paper develops a whole ship simulation training platform for the teaching and training of navigation. Occlusion Culling and Levels of Detail technology are used to optimize the scene. The six-degree freedom mathematical model of ship motion is established using the separation modeling theory. The flexible object simulation technology, the modeling and rendering of ocean technology and the reverse dynamics technology are adopted to realize the virtual equipment interaction. According to the simulation results, the platform has high efficiency and good immersion, and can show abundant navigation knowledge and realize virtual operation about navigation equipment and instruments. The platform can be used for the teaching and training of navigation.

It is urgent to improve the physical reality of ocean scenes in marine simulator for the maritime industry. In this paper, we propose a unified anisotropic particle-based ocean wave simulation framework for marine simulator. In the unified framework, a novel hybrid SPH method is applied to model the ocean waves, which combines a series of nonlinear density constraints and divergence-free velocity field constraints. By solving density constraints, the particle position distribution is directly adjusted to keep a constant density. Experiments show that the hybrid SPH method has advantages in compressibility and stability. Moreover, a novel stochastic fluctuating wind field model is integrated into the hybrid SPH method. The Perlin noise and a modified log wind profile are introduced to enrich the details of wind field. We also introduce a novel oil spill model for marine simulator based on number density, which can achieve a desired sharp density changes at interfaces between multiple fluids. For real-time surface reconstruction, we propose an improved anisotropic particle transformation method based on the distribution of the neighboring particles. The problem of particle deformation near the boundary is solved by our piecewise correction function, with the sharp features and anisotropy maintained. When calculating the covariance matrix and weighted position, the contribution of neighboring particles in other fluid phases is considered to eliminate gaps between multiple fluids in the oil spill scenes. The simulation results show that our unified anisotropic framework based on the SPH concept can easily integrate other models, has strong expansibility, and is very applicable to simulate complex ocean scenes.

The Lagrangian vortex method has the advantage of producing highly detailed simulations of fluids such as turbulent smoke. However, this method has two problems: the construction of the velocity field from the vorticity field is inefficient, and handling the boundary condition is difficult. We present a pure Lagrangian vortex method, including a nested grid to accelerate the construction of the velocity field, and a novel boundary treatment method for the vorticity field. Based on a tree structure, the nested grid algorithm considerably improves the efficiency of the velocity computation while producing visual results that are comparable with the original flow. Based on the vortex-generating method, the least square method is used to compute the vorticity strength of the new vortex elements. Further, we consider the mutual influence between the generated vortex particles. We demonstrate our method’s benefits by using a vortex ring and various examples of interaction between the smoke and obstacles.

To evaluate the practical ability of crews during the navigation of an inward-port single ship, a track evaluation model was developed on a planar forward normal cloud chart under sample information based on the forward normal and the backward normal cloud generator. Since the track sampling cloud may be too divergent, a track belt division method based on the contributions of normal cloud drops was proposed. Combining the track evaluation model with the track belt division method, a comprehensive track evaluation scheme of the local sampling cloud based on sampling information was established. The results of an example of M.V. DAQING 257 unloaded into Dalian Port demonstrated the effectiveness of the model and showed its consistency with expert evaluation results based on subjective information. The proposed uncertainty evaluation model provides a new approach for intelligent evaluation under sample information.

We sought to clarify the clinical relationship between REST/NRSF expression and the prognosis of glioma and explore the REST-associated competitive endogenous RNA (ceRNA) network in glioma. We downloaded RNA-seq, miRNA-seq and correlated clinical data of 670 glioma patients from The Cancer Genome Atlas and analyzed the correlation between REST expression, clinical characteristics and prognosis. Differentially expressed genes (DEGs) were identified with DESeq2 and analyzed with Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) using the Profiler package. Starbase was used to explore the regulatory interaction between REST and miRNAs or LncRNAs. The lncRNA-miRNA-REST ceRNA network was constructed with Cytoscape. RT-qPCR, WB, CCK8, wound-healing, and luciferase assays were performed to validate the ceRNA network. Results showed that REST expression was significantly higher in glioma patients than normal samples. Higher REST expression was significantly associated with worse overall survival, progression-free interval, and worse disease-specific survival in glioma patients. The DEGs of mRNA, miRNA, and lncRNA were identified, and GO and KEGG enrichment analyses were performed. Finally, REST-associated ceRNA networks, including NR2F2-AS1-miR129-REST and HOTAIRM1-miR137-REST, were experimentally validated. Thus, REST may be a prognostic biomarker and therapeutic target in glioma, and its regulatory network validated in this study may provide insights into glioma's molecular regulatory mechanisms.

Staged surgery strategy was preferred for patients with intra-extracranial communicating jugular foramen paraganglioma (IECJFP). A female patient who presented mild tinnitus, headache, and dizziness, together with preoperative related imaging, was diagnosed with a left intra-extracranial communicating jugular foramen lesion in November 2015 and accepted an initial operation for the intracranial tumor by retrosigmoid approach. The pathologic report was paraganglioma. In November 2021, a subtotal resection of the extracranial tumor was conducted for prominent lower cranial nerves (LCNs) deficit and middle ear involvement by infratemporal approach. In patients with IECJFP accompanied by LCNs deficit and middle ear involvement, an initial surgery for extracranial lesion and a second procedure for intracranial tumor were appropriate. However, the first operation for the intracranial lesion was preferred in IECJFP cases without LCNs deficit and middle ear involvement, as it could remove compression to the neurovascular structure and brain stem, clarify a pathological diagnosis, avoid a CSF leak, and prevent a severe neurological disorder from extracranial lesion excision. Subtotal resection of the extracranial tumor would be performed when lesion became larger combined with obvious LCNs disorder and tympanic cavity involvement. Consideration of specific staged surgical strategy for IECJFP in accordance with preoperative LCNs deficit and tympanic cavity involvement could prevent critical postoperative neurological deficit and improve quality of life in the long term.

Under the current background of navigation education, students generally lack a comprehensive grasp of ship firefighting equipment’s operation. Therefore, we develop a novel ship firefighting training simulator with a multi-sensory human–computer interaction function for teaching and training marine students. In the simulator, we consider a container ship of 1.8w containers as the prototype ship, and the entire ship models are built using three-dimensional modeling technology. We design various interactive modes and realize a full-process operation simulation of several standard ship firefighting equipment. Furthermore, we propose a purely Lagrangian vortex dynamics framework to simulate smoke and flame in fire scenarios. In this framework, we model fluids using velocity and vorticity fields discretized on discrete vortex segments. The main components of the framework include a stable geometric stretching solution and particle strength exchange method for solving the diffusion term. The simulation results show that the simulator has good behavioral realism and scene immersion and can be applied to ship firefighting training. To the best of our knowledge, this is the first study on real-time smoke simulation using a physics-based method in a firefighting training simulator.

The Position-Based Dynamics (PBD) method considers the rope as a series of particles in rope simulation. This paper introduces the PBD method and simulates mooring line in ship mooring simulation training system with four constraints, which are distance constraint, bending constraint, Long Range Attachment (LRA) constraint and pin constraint. In this paper, the LRA constraint method is applied to solve the overstretch problem of mooring line simulation caused by distance constraint and bending constraint. A pin constraint which combines two particles into one is put forward to achieve the connection effect between cable and the eye splice as well as the interaction between anchor and chain. Moreover, the method of Continuous Collision Detection (CCD) constraint is proposed to realize the collision detection between mooring lines and other objects. Compared with Newton's method, our adopted method is more efficient and robustness. Since it has sufficient visual plausibility and can realize real-time visualization, the simulation system developed by PBD method has a good training effect for crew.

The widespread of shipborne Automatic Identification System (AIS) equipment will continue to produce a large amount of spatiotemporal trajectory data. In order to explore and understand the hidden behaviour patterns in the data, an interactive visual analysis method combining multiple views is proposed. The method mainly includes four parts: using a trajectory compression algorithm that takes into account the vessel motion characteristics to preprocess the vessel trajectory data; displaying and replaying vessel trajectories based on Electronic Chart System (ECS), and proposing a detection algorithm for vessel stay points based on the principle of spatiotemporal density to semantically label vessel trajectories; using the Fast Dynamic Time Warping (FastDTW) similarity measurement algorithm and the Ordering Points to Identify the Clustering Structure (OPTICS) clustering algorithm to cluster vessel trajectories to show the differences and similarities between vessel traffic flows; and showing the distribution of vessels and the variation trend of vessel density based on the vessel heatmap. Based on the AIS data of the Yangtze River Estuary, three cases are used to prove the usefulness and effectiveness of the system in vessel behaviour analysis.

Glioma is one of the deadliest malignant brain tumors in adults worldwide. MicroRNA (miR) has been reported to be a pivotal regulator in human tumors. The aim of this study was to determine the expression, function, and mechanism of action of miR-1269a in glioma progression. The expression of miR-1269a was higher in both glioma cases reported in databases and glioma cell lines, and it was highly associated with poorer prognosis. Next, it was shown in vitro that mimic of miR-1269a could promote glioma progression and arrest apoptosis, whereas the inhibition of miR-1269a exhibited the opposite effects. In addition, miR-1269a was found to directly target ATRX chromatin remodeler by a dual-luciferase reporter assay. Moreover, ATRX overexpression could reverse the suppressive effects of miR-1269a on proliferation and apoptosis in vitro. In vivo subcutaneous xenograft tumor assay was also performed to confirm the phenotypes and molecular mechanism involved. Taking the findings together, our study implies that the miR-1269a/ATRX axis is a novel therapeutic target of glioma.

In the development of ship anchorage training systems, the problems of low efficiency and poor fidelity exist in the simulation of flexible anchor chains, and a position-based dynamics (PBD) method is proposed to express the chain movement. To satisfy the requirements of simulating anchoring manipulation, the PBD method modifies the position of anchor chain particles by controlling constraints. Using the original distance constraint and bending constraint of the PBD approach, two novel constraints, namely, the long-range attachment (LRA) constraint and pin constraint, are developed to simulate the bending and stretching of the anchor chain. Simulation of ordinary ropes can be achieved using distance and bending constraints. The developed LRA constraint is capable of preventing anchor chain particles from being overstretched. Adoption of the pin constraint is proposed to integrate two particles into one to be calculated as an attempt to simulate the connection between the chain and the anchor. The continuous collision detection (CCD) constraint method considering friction and viscosity is used to detect collisions in the ship anchoring training system. Collision detection covers chain collisions with other objects and chains. Finally, the PBD method is more efficient and robust than the Newton method. Since it has sufficient visual plausibility and can realize real-time visualization, the simulation system developed by the PBD method effective for training crew members.

Under the guidance of industry 4.0, peoples pay more attention to the intelligent equipment and system. Intelligent vessel without crew on board has acquired growing attention worldwide over the years. The navigation condition of intelligent vessel without crew at sea should be monitored and controlled by the shore-based intelligent vessel support system. The navigation-related data collected by the multi-source navigation sensors should be presented on the shore-based support system in an efficient and friendly way. This article presents a simulation model for multi-source navigation sensors such as echo sounder and electronic position-fixing system. Furthermore, this work proposes an efficient architecture for the shore-based support system by way of multi-source navigation sensors simulation. The results show that the simulation model of multi-source navigation sensors is efficient for the simulation of echo sounder and electronic position-fixing system. The shore-based intelligent vessel support system based on multi-source navigation sensors simulation can present navigation-related data and monitor the condition of intelligent vessel at sea.

In order to improve the accuracy of the freefall of lifeboat motion simulation in a ship life-saving simulation training system, a mathematical model using the strip theory and Kane’s method is established for the freefall of the lifeboat into the water from a ship. With the boat moving on a skid, the model of the ship’s maneuvering mathematical group (MMG) is used to model the motion of the ship in the waves. Based on the formula of elasticity and friction theory, the forces of the skid acting on the boat are calculated. When the boat enters the water, according to the analytical solution theory of slamming, the slamming force of water entry is solved. The simulation experiments are carried out by the established model. The results of the numerical simulation are compared with the calculation results of the hydrodynamics software Star CCM+ at water entry under initial condition A in the paper. The position and velocity of the center of gravity of the boat, the angle, and velocity and acceleration of pitch calculated by the two methods are in good agreement. There is a little difference between the values of translation acceleration calculated by the two methods, which is acceptable. This shows that our numerical algorithm has good accuracy. A qualitative analysis is performed to find the safe point of water entry under the condition of different wave heights and two situations of a ship encountering waves. Finally, the model is applied to the ship life-saving training system. The model can meet the system requirements and improve the accuracy of the simulation.

It is a challenging work to simulate wind and waves in virtual scenes of marine simulators. In this paper, a divergence-free position based fluid (DFPBF) framework is introduced for ocean wave modeling in marine simulators. We introduce a set of constant density constraints and divergence-free velocity constraints to enforce incompressibility. By adjusting the position distribution of fluid particles, the particle density is forced to be constant. Constraining the divergence-free velocity field can keep the density change rate at zero. When correcting the position and velocity of particles, we introduced a relaxation correction scheme to accelerate the convergence of the framework. The simulation results show that as the scene scale expands and the number of fluid particles increases, this acceleration effect will be more significant. Secondly, we propose a novel particle-based three-dimensional stochastic fluctuating wind field. The Perlin noise is introduced to disturb the constant horizontal wind field to form a stochastic wind field. On this basis, a stochastic fluctuating wind field simulation framework is proposed. By adjusting the pulse period and pulse width, users can flexibly control the fluid turnover under the action of the wind field. This wind field framework can be easily integrated into the DFPBF model. Based on this wind field model, we simulated some typical wind wave scenarios, including interaction scenarios with lighthouse and lifebuoy, and verified the effectiveness of the wind field model.

The realistic simulation of ocean scenes is of great significance in many scientific fields. We propose an improved Smoothed Particle Hydrodynamics (SPH) framework to simulate the ocean scenes. The improved SPH combines nonlinear constant density constraints and divergence-free velocity field constraint. Density constraints adjust the particle distribution on position layer, so that the density is constrained to a constant state. The addition of the divergence-free velocity field constraint significantly accelerates the convergence of constant density constraint and further reduces the density change. The simulation results show that the improved SPH has high solution efficiency, large time steps, and strong stability. Then, we introduce a unified boundary handling model to simulate coupling scenes. The model samples the boundary geometry as particles by means of single layer nonuniform sampling. The contribution of the boundary particles is taken into account when the physical quantities of fluid particles are computed. The unified model can handle various types of complex geometry adaptively. When rendering the ocean, we propose an improved anisotropic screen space fluid method, which alleviates the discontinuity problem near the boundary and maintains the anisotropy of particles. The research provides a theoretical reference for the highly believable maritime scene simulation in marine simulators.