To investigate the impact of different pressure relief port areas on the evolution of hydrogen-air flame morphology, experiments on hydrogen-air explosions were conducted using a self-built experimental platform, and numerical simulations were performed using the open-source software OpenFOAM. The characteristics of deflagration and the morphology of the flame under conditions of various pressure relief port areas (0%, 25%, 50%, 75%, 100%) were analyzed. The results indicate that the pressure relief port area has a minor impact on the flame morphology but affects the moment of flame formation. As the pressure relief port area increases, the propagation speed of the tulip-shaped flame increases, the deflagration pressure decreases, and the moment of peak occurrence is delayed. Changes in the pressure relief port area affect the flow field structure of the unburned gas, which in turn influences the flame morphology. Smaller pressure relief port areas are conducive to the formation of vortex structures in the unburned gas, promoting the formation of flat and tulip-shaped flames. The pressure relief port area is an important factor affecting the morphology and deflagration characteristics of hydrogen flames. By optimizing the structural parameters of the pressure relief port, the propagation speed of hydrogen flames and deflagration pressure can be effectively controlled, reducing the risk of explosion, which is of great significance for the safe use of hydrogen energy.

In order to explore the influence of factors such as moisture content of foamed asphalt, cement/lime, aging degree of old asphalt and temperature on the interface characteristics of cold reclaimed foamed asphalt binder (composed of cement/lime, old asphalt and foamed asphalt, hereinafter referred to as binder), molecular models of different types of binder were constructed by molecular dynamics method. Interface energy, interaction energy, cohesive energy density (CED) and water molecule radial distribution function (RDF) were used as calculation and characterization indexes to quantitatively analyze the interface characteristics of each component material in the binder. Then the microscopic mechanism of the interaction of each component material is revealed. The results show that: In terms of the same material properties of  other components, the binder with long-term aging asphalt (LTAA) exhibits lower interfacial energy, interaction energy, CED and RDF of water molecules than the binder with short-term aging asphalt(STAA), The maximum interfacial energy, interaction energy, CED and water molecule RDF of binder are obtained when the moisture content of foam asphalt is 2.4%. The interfacial energy, interaction energy, CED and RDF of water molecules of binder are the minimum when the water content of foam asphalt is 1.8%. Compared with the lime characterized by CH, the cementing materials containing CSH performs higher interface energy and interaction energy, but lower CED and RDF of water molecules. When the temperature is 303 K~308 K, the binder containing STAA has higher interface energy and interaction energy than the binder containing LTAA, but that is opposite when the temperature is 313 K~318 K, and the CED of the binder basically remains stabilization as the temperature increases. Compared with the cementing material containing CH, the cementing material containing CSH has higher interfacial energy and interaction energy, which gradually increases with the increase of temperature and reach the highest value at 318 K,  however, the CED of both remains stabilization. With the increase of temperature, the RDF of water molecules of different cementing materials increases, and a large number of water molecules concentrated in the end.

Currently, the paths planned by unmanned boats in inland lake environments using the A* algorithm suffer from insufficient collision avoidance capability, many steering maneuvers, and unsmooth steering paths, which significantly reduces the efficiency and safety of the unmanned boats during autonomous cruising tasks. Based on this problem, an improved A* and path smoothing algorithm is proposed. The algorithm firstly improves the valuation function and introduces the obstacle avoidance cost and steering cost; secondly, iteratively uses the A* algorithm to generate the path by reversing the segmentation and eliminating the redundant path of the A* algorithm; finally, the steering trajectory is optimized by considering the rotary performance of the unmanned boat. Simulation experiments on a real inland lake water raster map show that the improved algorithm significantly reduces the collision probability, steering angle and traveling distance of the unmanned boat, and improves the steering performance of the unmanned boat.

 In order to effectively utilize the large amount of boil off gas (BOG) generated during the operation of liquefied natural gas (LNG) carriers, the fleet deployment and voyage planning problem of LNG shipping considering BOG management is studied. BOG generated by LNG can be used as ship power propulsion fuel during the navigation of LNG carriers. By using BOG as fuel, a model of fleet deployment and voyage planning of LNG shipping under economic sailing speed is formulated. Then, a BOG management strategy is designed based on the relationship between speed and demand of BOG, and a joint optimization model of fleet deployment, voyage planning and speed of LNG shipping considering BOG management is formulated. Taking an LNG shipping enterprise in China as an example, the lowest cost, optimal fleet deployment and voyage planning of the two models are obtained, respectively. It is found that the BOG management strategy can effectively reduce the cost by more than 8 %, and the corresponding management insights are proposed from the perspective of fluctuation of LNG spot price and the business scale of business scale, by comparing the optimal solutions of the two models. The research results indicate that this method can provide decision support for LNG shipping enterprises to reasonably allocate transportation resources and effectively manage BOG of LNG carriers.

Aiming at an innovative engineering structure spanning the bay, the Submerged Floating Tunnel (SFT), the three-dimensional solid model of SFT was established by using ABAQUS finite element analysis software, taking the SFT design scheme of Funkawan Bay in Japan as the object. The lateral deformation and torsional motion response characteristics of the submerged floating tunnel are analyzed under the conditions of single cable break and multiple cables continuous break. The influence of Weight-Buoyancy Ratio (WBR) on cable break response is discussed through parameter sensitivity analysis. The results show that the maximum torsion angle response and vertical displacement response increase nearly three times and double respectively when two cables are broken. Increasing the safety factor of the cable is significantly important to avoid continuous cable-breaking. In addition, the SFT equivalent model for dynamic responses analysis is proposed, which can accurately reflect the dynamic characteristics of the whole tunnel and the deformation characteristics under various loads.

In order to solve the problems of complex navigation scenes of inland waterway vessels, few shape and color characteristics of marine radar images, and difficult to label, an improved YOLOv8 marine radar image target detection method was proposed. Firstly, in order to alleviate the problem of labeling error and model overfitting, a label smoothing strategy was introduced in the model training stage. Then, combined with the unique position prior information of the radar image, a coordinate-based convolution structure was designed to extract the shape, color and position features of the target at the same time. In order to verify the effectiveness and superiority of the proposed method, the radar images of the Yangtze River channel were collected by comparative tests under different weather conditions. The experimental results show that the proposed method can ensure the real-time target detection, and its accuracy reaches 91.52%, and the average accuracy is 5.17% higher than that of the classic YOLOv8, which can provide technical support for improving the modern and intelligent management level of inland waterway shipping.

Due to inherent characteristics such as scattering and absorption of underwater media, underwater images face multiple degradation problems such as image blurring, low contrast and color distortion, which seriously affect visual perception performance. To address these issues, this paper proposes a deep learning-based underwater image restoration and enhancement framework (UIRENet) based on depth estimation and gradient descent strategy. With the help of convolutional and nonlinear activation function modules, a deep perception network is constructed to achieve scene depth perception maps for different degradation regions, overcoming the dependence of scene depth degradation. A gradient optimization strategy is proposed to optimize the parameters of convolutional networks and improve the performance of deep network enhancement. Combined with perceptual loss, edge loss and underwater color constancy loss, a loss function for underwater image enhancement networks is formed. Through comprehensive experiments on the UIEB-90, UIEB-M and EUVP datasets, it is verified that the UIRENet framework significantly outperforms the considered typical underwater image enhancement methods in terms of reducing underwater image blurriness and improving visual effects. In particular, on the objective evaluation metric UIQM, its scores are 0.37, 0.6446, 0.5919, 1.3081, 1.3032, 1.1672, 0.0593, 0.1329 and 0.0934 higher than CLAHE, ICM, GC, IBLA, DCP, ULAP, FUnIE-GAN, UGAN and Uformer respectively.

Under the impetus of the International Maritime Organization (IMO) emission reduction strategies and government policies to reduce emissions, shipping companies have started retrofitting vessels to use green fuels. However, the retrofitting of vessels disrupts regular shipping operations, indirectly impeding vessel retrofitting plans. In this context, it is proposed that shipping companies cooperate through fleet alliances, coordinating and scheduling transportation tasks to increase the rate of vessel retrofitting. To address these issues, a two-level optimization model is established. In the upper level, the objective is to maximize the overall economic benefits of the alliance. In the lower level, the focus is on maximizing the profits of liner shipping operations based on the retrofitting plans from the upper level. This model represents a multi-leader-single-follower game involving three alliance companies and liner shipping tasks, resulting in an equilibrium problem with equilibrium constraints (EPEC). Using Karush-Kuhn-Tucker (KKT) conditions, the model is transformed into multiple mathematical programs with equilibrium constraints (MPEC), and a diagonalization algorithm (DM) is applied for solving. Sensitivity analyses are conducted on the alliance effects. The results show that this model and its solving method are feasible and can provide new insights for decarbonization in the shipping industry.

In order to investigate the influence of the stator vane passage shape on the internal flow field of a centrifugal compressor, this study focuses on the stator vane of a high-pressure centrifugal compressor. The study employs a method of middle arc line shaping, parametric modeling, and utilizes high-precision surrogate models to expedite the design optimization process. Data mining tools are used to analyze the sensitivity of design parameters and summarize the general design principles for stator vanes. The results show a close correlation between vane shape parameters and isentropic efficiency, with a moderate positive correlation, and strong interrelationships among various shaping variables. Some shaping parameters have a positive effect on static pressure efficiency. The optimal shaping structure indicates that reducing the inlet flow angle of the stator vane can alleviate the formation of separation vortices on the suction side and decreasing the outlet flow angle of the stator vane can reduce flow losses. Increasing the curvature from the middle to the trailing edge of the vane grid can mitigate blockage in the middle of the passage, leading to overall improvements in the performance of the centrifugal compressor's stator vane passage. After shape optimization, the isentropic efficiency at the design point increased by 1.7%, and the pressure ratio increased by 0.1 across the entire operating range.

In order to improve the control performance of the fault-tolerant permanent magnet vernier rim-driven motor (FTPMV-RDM) position sensorless control system, the speed controller and rotor position estimation algorithm of the system were studied. The speed loop uses a fast super-twisting sliding mode controller to reduce the chattering phenomenon that exists in traditional sliding mode controller. Adaptive sliding mode observer is used to estimate the rotor position to improve the position estimation accuracy. A simulation model of the FTPMV-RDM position sensorless control system was built in the Matlab/Simulink environment. The simulation results show that the control method proposed in this paper can accurately estimate the rotation speed and rotor position information of FTPMV-RDM when there is no fault and one-phase open-circuit fault, and the system has good dynamic and static performance.

Red tide is a common marine ecological disaster caused by the explosive proliferation or high aggregation of certain phytoplankton, protozoa, or bacteria in seawater under specific environmental conditions, leading to discoloration of the water. At present, the main methods for monitoring red tide include fixed-point monitoring of ships, monitoring stations, and aerial and satellite remote sensing monitoring. Among them, satellite remote sensing monitoring is widely used due to its wide monitoring range and comprehensive monitoring information. This article proposes a linear comprehensive identification index (LCI) method for red tide identification in multispectral satellite images based on five sub indices and their comprehensive methods that can indicate red tide outbreaks. Based on the multi day continuous monitoring spectral data of red tide in Xinghai Bay, Dalian City, support vector machine and logistic regression classification were carried out, and the classification plane coefficients were obtained as normalized sub index combination weights. Two optimal combinations of red tide identification indices were obtained. Both methods achieved classification results with an F1 score of 0.86 or higher on the validation set, and the LCI value showed a positive correlation with the probability of red tide occurrence. This article further applies the obtained classification coefficients to the extraction of red tide pixels in multispectral satellite images, and the results show that both linear composite indices have successfully extracted red tide areas in the images. The comprehensive identification index of red tide proposed in this article provides a new spectral index calculation method for red tide identification in remote sensing images.

Aiming at the rock instability caused by hydro(H)-machine(M)-damage(D) coupling during the construction process of foundation pit engineering in karst area, the stress-seepage-damage coupling model and algorithm based on Hoek-Brown strength criterion are established. Firstly, according to the damage theory, the H-B strength criterion was modified by introducing damage factor, and the governing equations of stress field and seepage field and permeability evolution equation were given to realize the complete coupling of stress, seepage and damage. Then, a solution algorithm for the model was provided, and the results of triaxial laboratory tests and simulation calculations of limestone were compared, which showed good fitting and verified the accuracy of the model. Finally, the model was used for the excavation stability analysis of the foundation pit project of the Suoyuwan South Station of Dalian Metro, and the surface settlement and underground continuous wall deformation under the coupling and non-coupling conditions were calculated respectively. The calculation results show that the deformation value considering the coupling is significantly greater than the uncoupling, and it is closer to the field monitoring value. At the same time, in order to determine the minimum thickness of the anti-outburst layer of the surrounding rock, the distribution characteristics of the damage area at 2m, 4m, 6m and 8m of the anti-outburst layer were calculated, which has certain significance for the risk prediction during actual construction.

How to ensure the safe evacuation of personnel in port accidents has become a key research topic in port planning and operation. The key to solving the problem of crowd evacuation is to understand the movement patterns of the crowd. The key to solve the problem of crowd evacuation is to understand the movement law of the crowd. Crowd movement is a complex system, involving many factors such as crowd interaction behavior, urban spatial form, and architectural environ-ment. In order to provide accurate and reliable research basis for the study of crowd evacuation, this paper proposes a crowd motion simulation model based on deep convolutional neural network. In order to obtain the data required for neural net-work training, this paper uses CSRNet neural network and DBSCAN algorithm to extract real crowd trajectory data from surveillance video. Through the training of deep convolutional neural network, the real crowd behavior pattern is deeply studied, and the crowd motion simulation model is established by using the trained deep convolutional neural network. The experimental results show that the model can accurately predict the movement behavior of the crowd and truly simulate the movement trajectory of the crowd, which can provide a basis for the formulation of emergency evacuation strategies and the design of evacuation channels in public places.

Aiming at the problem of intelligent ship trajectory tracking control under network spoofing attacks, an improved reaching law sliding mode trajectory tracking control scheme with observer is proposed. Using Bernoulli distribution to generate random binary numbers to simulate network spoofing attacks. By designing observers to observe the impact of attacks and feedback compensation to the controller to resist the damage caused by attacks on the system. Design adaptive laws to cope with the impact of environmental disturbances, while further enhancing system robustness through coordination with the observer. Design an improved sliding mode reaching law with fast compensation for large errors and smooth compensation for small errors, which reduces the chattering problem of traditional sliding mode control and improves the control efficiency of the controller. Finally, the overall stability of the system was verified using Lyapunov stability theory, and comparative simulation experiments were conducted using Matlab. The experimental results show that the control scheme can respond quickly to the impact of attacks and provide good compensation, and the trajectory tracking error can quickly converge to a very small bounded interval near zero, achieving ship trajectory tracking in a network attack environment. This plan can provide certain reference value for research on safe navigation of ships and military confrontation of maritime equipment.

The fluid swivel is an important component in the FPSO single point mooring system that performs the functions of rotation, sealing and fluid transmission. To verify the safety and reliability of the function and structure of the fluid swivel in the long-term marine environment, this paper conducts research on the comprehensive performance test method of the fluid swivel. According to the performance index requirements of the newly added 8-inch domestic fluid swivel products of the Nanhai-Fenjin FPSO, the test device for simulating the dynamic marine environment was designed, and 2 running-in tests and 4 functional pressure tests were formulated. Through the above tests, the sealing pressure, rotational torque and fluid transmission performance of the fluid swivel were tested under static and dynamic swing conditions. The test results show that the comprehensive performance of the domestic fluid swivel meets the design requirements, which provides ideas and guidance for future performance testing and verification of the domestic fluid swivel. 

Dual-cycling operation is an effective way to improve container handling efficiency and resource utilization of container terminal. The complexity of quay crane scheduling with dual-cycling operation lies in the need to make decisions on the sequence of container handing operations, with considering the constraints of the ship's stability, heel angle, and hatch cover. An optimization model for quay crane scheduling is established, which takes the minimum energy consumption of quay crane as the optimization target. The improved variable neighborhood search algorithm based on the Johnson rule is designed to solve the model. The validity of the model and algorithm was verified, highlighting the importance of constraining the ship's stability and heel angle during the handing operation. It has been determined that the optimal time interval for checking heel angle is 2 min. The results showed that the model proposed can improve the handing efficiency and reduce the energy consumption of quay crane, all while ensuring the safety of container handing operation. 

In order to allocate yard storage space reasonably, reduce waiting time for trucks at the yard bridges, and improve yard operation efficiency, the impact of uneven container volume in the yard area on the efficiency of bridge crane loading and unloading operations was considered in this study. A mathematical model for yard space allocation with the objective of minimizing the sum of queueing time cost and driving time cost for trucks was established. For the cost of queueing time for trucks, an embedded truck operation simulation model based on Anylogic was used to model the mathematical relationship between average queueing time at the yard bridges, bridge crane loading and unloading efficiency, and truck arrival rate. A variable neighborhood search algorithm was designed to solve the model for large-scale instances, and a series of numerical experiments were conducted to evaluate the performance of the proposed algorithm. The study investigated the degree of impact of changes in yard loading and unloading efficiency on yard space allocation decisions. The results indicates that considering the impact of uneven container volume in the yard area on bridge crane loading and unloading efficiency can effectively reduce the queueing time cost for trucks waiting for bridge crane operations (by approximately 14.74%) and accelerate truck operation turnover, thereby improving yard operation efficiency.

According to the change law reflected in the Arctic shipping data, the characteristics of Arctic shipping are systematically arranged: the navigation period is summer and autumn, the shipping volume is constrained by external conditions, the shipping structure is single and external transportation is the mainstay. On this basis, it is proposed that the transportation time, transportation complexity and transportation range are more suitable for the pendulum transportation mode of Arctic shipping, and the pendulum transportation mode design of the northeast Arctic route is carried out from the aspects of fulcrum port, ship type and modular transportation, and the annual shipping revenue of the pendulum transportation mode and the traditional transportation mode and mixed transportation mode are comparatively analyzed. The results show that compared with the other two transport modes, the pendulum transportation mode of the Northeast Arctic route can complete one more voyage per year, and the annual shipping revenue is 9% and 11.3%, respectively. Arctic shipping can be developed according to this mode of transport to further develop the potential of Arctic shipping.

In the context of a bus fleet combining gasoline and electric vehicles, the introduction of on-route wireless charging infrastructure significantly influences their operation and scheduling. This study revolves around the challenge of optimizing the placement of wireless charging stations and formulating operational strategies for such a hybrid bus fleet. A mixed-integer programming model has been thoughtfully devised, taking into account an array of constraints, including variables related to bus operations and the state of electric bus batteries. The objective is to minimize the overall operational costs. To tackle this model, an adaptive large neighborhood search algorithm is employed. Additionally, practical scenarios are meticulously designed to simulate a variety of fleet compositions and charging strategies. A comprehensive comparative analysis of overall operational costs is undertaken, accounting for different fleet compositions and charging strategies. Furthermore, a sensitivity analysis is conducted to scrutinize the effects of the charging power of wireless charging facilities on the results. The results underscore that in an environment featuring on-route wireless charging, the hybrid bus fleet stands out with the lowest total operational costs. Moreover, with the increase in charging power of wireless charging facilities, there is a concurrent reduction in the number of planned charging stations and gasoline-fueled buses, culminating in reduced overall costs. Therefore, the proposed model in this study offers an effective and efficient approach for significantly trimming down the overall operational costs of the bus fleet in the context of on-route wireless charging.

As the necessary core equipment of ocean-going merchant ships, ship navpilot can reduce the burden of ship pilots, improve navigation safety and economy, and is the hot direction of intelligent ship development. In this paper, focuses on the robust adaptive track keeping algorithm as the core technology, considering the practical control requirements of navigation engineering and using embedded Linux technology, a set of navpilot prototype with navigation control, monitoring and alarm, system information display functions, hardware interface in line with the requirements of international standards is developed. Finally, taking "Yu-Kun" as the experimental object, the effectiveness of the ship navpilot was tested according to the Maritime navigation and radiocommunication equipment and systems-Track control systems-Operational and performance requirements，methods of testing and required test results (GB/T 37417-2019) national standard test scene under random Marine environment interference conditions. The results show that the ship navpilot can realize the stable tracking control of the course spanning 0° longitude and latitude, and the course error is less than 2° and the track steady-state error is less than 13m, which meets the standard requirements. The course rudder proposed in this paper has important reference significance for the localization of high-end navigation equipment.

In response to the issue of deviation in the meandering motion of shipboard fire snake-like robots, which hinders their effective movement within the complex gaps of vessels, based on the kinematic model of the hyper-redundant snake-like robot, the nonlinear offset causes are analyzed from the kinematic and dynamic perspectives, which are caused by the torsional torque generated during the rotation process between the joints. The experimental results show the influence rules of the swing amplitude A and the phase difference β between the adjacent links on the normal offset of the robot, proving that the two parameters can only affect the degree of the normal offset of the robot, and cannot effectively eliminate the offset. Based on the Serpenoid control curve, a simple and efficient adaptive offset correction control algorithm is established, and Webots robot simulation and prototype experiments are carried out. The results show that the average maximum radial offset of the fire-fighting snake-like robot is reduced by 42.8cm, decreasing by 75.2%, meeting the work requirements of the narrow environment of the ship without changing the shape of the robot motion.

A lightweight stacked residual low-light image enhancement network is proposed to overcome the difficulty in accurately sensing the environment under low-light conditions for Unmanned surface vessels (USV). Firstly, a pyramid multi-scale pooling is introduced into feature fusion to better preserve image details. Secondly, depthwise separable convolution is introduced to lighten the network and improve the image processing speed. Thirdly, a new composite loss function with color loss is designed to reduce color distortion. Finally, LeakyReLU activation function is used to prevent neuronal death. Results from extensive experiments demonstrate that our method can effectively improve image quality while speeding up image processing compared to Stacked Attention Residual Network (SARN). Specifically, SSIM (Structure Similarity Index Measure) and PSNR (Peak Signal-to-Noise Ratio) are improved by 3.31% and 2.08% and FLOPs (Floating point operations), params and processing time of single image are reduced by 81.88%, 75% and 43.02%. Therefore, the proposed method is suitable for low-light image enhancement of USV, and has certain application value.

To solve the problem of the large number of parameters and computation of ship target detection algorithm, as well as the difficulties of ship detection caused by the influence of the nearshore complex backgrounds and the mutual occlusion of ships in inland river environments, this paper makes improvements based on YOLOv7-tiny and proposes a lightweight algorithm MED-YOLO for ship target detection. Firstly, the MobileNetV3 network is used as the backbone feature extraction network, which greatly reduces the calculation cost of the model. Secondly, EMA attention module was introduced into the neck network, and EMA-ELAN module was constructed to enhance the multi-dimensional perception and multi-scale feature extraction capability of the network. Then, Dyhead, which combines scale perception, spatial perception, and task perception, is selected as the detection head of the improved model to obtain stronger feature expression ability. Finally, WIoU with dynamic non-monotonic focusing mechanism is used as the bounding box loss function to improve the model's ability to cope with ship occlusion and improve the detection performance. The experimental results show that compared with YOLOv7-tiny, MED-YOLO has 39.8% fewer parameters and 55.0% less computation, and its precision and mAP@0.5 have increased by 1.4% and 1.0% respectively, reaching 98.3% and 98.9%, which not only achieves lightweight, but also has better detection performance. It meets the deployment requirements in the environment with limited computing resources, and has certain practical engineering significance.

In view of the complexity of the ice situation and geographical environment of the Arctic shipping route, there are risks such as ship ice collision and grounding in polar navigation. In order to ensure the safety and economy of ship polar navigation, this paper proposes a route planning method that comprehensively considers multiple risk factors such as water depth, sea ice density and sea ice thickness. Firstly, for the global route planning, the Polar Operational Limit Assessment Risk Indexing System (POLARIS) is adopted to calculate the Risk Index Outcome (RIO) of the Arctic safe water depth region, reclassifying the risk grade and assigning it to risk cost. The lowest risk cost route in the safe water depth region was generated by Geographic Information System (GIS) lowest cost path analysis method and recommended as the global route. Secondly, the grid proportion of each risk level is extracted to evaluate the feasibility of the route. Finally, for the sea ice area along the global route that is larger than the maximum ice thickness of the International Association of Classification Societies (IACS) polar class ship operating restrictions comparison table, the local route planning is carried out by combining the improved A* and the Dynamic Window Approach (DWA), considering the risk of ship-ice collision under complex and variable ice conditions. The comparison of global and local routes with different risk factors show that the global routes planned in this paper have the lowest risk while avoiding grounding; The ship can make collision avoidance decision against the new ice blocking the channel when sailing along the local planned route.