In order to improve system development efficiency, the software is developed based on theBrowser/Server (B/S) architecture and the principle of front-end and back-end separation. The technical framework of the system software is decided. The main front-end interface and back-end functional modules are planned. The complete intelligent engine room system software based on principle of front-end and back-end separation is developed. The system software has been proved to be reliable and stable.

The plant extract deodorization technology is introduced to reduce the impact of odorous substances released during the loading, unloading, and compression process in municipal refuse transfer stations on the surrounding environment. By comparing and analyzing, the deodorization effects of plant extract deodorization under different experimental conditions are determined. The research shows that the deodorizing effect of plant extracts is dependent on their active ingredients and concentration ratios and influenced by factors such as the reaction time between plant extracts and exhaust gases, the deodorizing process and so on. In practical applications, it is recommended to optimize the plant extract deodorization formula for particular odor components, improve the plant liquid deodorization process, and extend the time for plant extracts-exhaust gas reaction, so as to improve the deodorization efficiency of plant liquid.

In order to augment the traffic perception capability of the ferry terminal and improve the overall digitalization level, a Transformer-MLP(Multi Layer Perceptron)-based method for short-term prediction of ferry terminal passenger flow is introduced, The design is capable of predicting the passenger flow in 4 predefined time periods of following day. The prediction method performs ETL (Extract-Transform-Load) and get passenger flow data in the form of time series from ferry business data. A combined time series model PatchTSTiDE is built based on the collected time series data transformed from ferry business data by means of the time series forecasting toolkit NeuralForecast. Tests show that, Compared with TiDE (Time-Series Dense Encoder) and PatchTST, the developed model is about 4.44% and 30.59% better in MAE (Mean Absolute Error) respectively.

Based on the guidelines for compiling air pollutant and greenhouse gas emission inventories, a comprehensive emission inventory for typical coastal container terminals is established. By integrating on-site investigation data, emission factors, and activity level data, emissions during four operational stages (quayside loading/unloading, yard loading/unloading, horizontal transportation, auxiliary and ancillary production) in 2023 are estimated. The Monte Carlo simulation is performed to quantify uncertainties. The research shows that NO_x and CO are the main air pollutants at the terminals, with container trucks and stackers as the primary sources of air pollutants. Indirect emissions from electricity consumption contribute the most to carbon emissions, with container trucks, yard cranes, and shore bridge being the main sources, accounting for 25.57%, 23.78%, and 23.43% respectively. The uncertainty of the inventory ranges from -67% to 139%. This comprehensive inventory reflects the characteristics of air pollutant and carbon dioxide emissions at coastal container terminals, providing scientific support for air pollution control and carbon emission reduction.

The commercial software SHIPFLOW MOTIONS based on potential flow theory is used to simulate the motion of a surveying vessel in waves. The physical characteristics of ship motion in regular waves are calculated using three-dimensional, time-domain, and fully nonlinear boundary element methods, The numerical calculation results are examined against the model test results. The research shows that the numerical calculation results of heave and pitch motion fit well with the model test results. For ship's resistance increase in waves, the maximum deviation between the RAO numerical calculation results and the model test results is about 13%, which is significantly more accurate than that the three-dimensional frequency-domain linear potential flow theory can produce. In addition, to verify the nonlinear problem-solving ability of the software, it is directly used to simulate the motion of the ship in irregular waves. The results shows that the deviation between the wave drag calculation results and the experimental results is about 7%, which implies that using the potential flow method to solve problems of ships in complex flow field is feasible.

A ship with high block coefficient is studied to determine the influential ship type characteristic parameters in designing the stern form of full-formed ships. The stern form is modeled and automatically varied under the constraint of drainage volume through semi-parametric control by means of software CAESES and corresponding resistance performance and wake of the ship type are calculated by means of software SHIPFLOW. The optimization strategy is designed based on the combination of Sobol algorithm and Nelder Mead Simplex algorithm, and the regression analysis is performed to examine the resistance and wake non-uniformity of different ship forms. The Performances for the form variations are calculated and verified by software Star CCM+. The findings are as follows: the fullness of the stern form at the maximum contrary flexure position above the target stern axis and the shape of the stern transom have significant impact on the wake. The optimization achieved about 2% reduction of the effective power and 6.4% reduction of the wake non-uniformity compared with the original design.

In order to enhance the perception ability of ships to the surrounding environment under poor visibility conditions such as foggy weather, a maritime image dehazing method based on the cycle generative adversarial network is introduced. It enhances the stability of dehazing effects, avoiding excessive image deformation and the loss of important features by introducing cycle consistency loss and identity loss. Experimental validation is conducted on both simulated and real foggy maritime images, and then compared with mainstream dehazing methods. The results demonstrates that our method outperforms others in terms ofPSNR (Peak Signal-to-Noise Ratio), structural similarity, and color difference. An average PSNR of 21.92 dB, surpassing traditional dehazing methods by at least 8.79 dB, is achieved. It is seen that the fog is effectively removed from images, and the details and texture information are restored.

An offset pre-swirl energy-saving device to improve ship propeller's propulsion efficiency is developed and evaluated usingCFD (Computational Fluid Dynamics). For illustration, the device particularly for a new bulk carrier is designed. TheRANS (Reynolds-Averaged Navier-Stokes) method is employed to numerically calculate the resistance on the ship and the wake field at the propeller disk plane. Based on the wake field characteristics, the offset pre-swirl energy-saving device is designed, and its key design parameters are optimized for efficiency of the wake flow rotational energy recovery. Numerical calculation shows that this device can lead to an energy-saving of 3.1%, approximately 20% improvement over conventional pre-swirl energy-saving devices.

The safety of ammonia fuel transmission is a critical issue for application of the clean energy source. This paper examines fuel transmission performance of a newly developed marine ammonia fuel system through simulation to verify the design. Based on the physical characteristics of ammonia fuel, the mechanism model of the ammonia fuel transmission system is built, and the effectiveness of the model is verified. The real time simulation is performed with the transmission system model to test and verify the performance of the controller of the system. The simulation operation is effective in system performance testing, not only for normal working conditions but also for extreme working conditions.

The environmental impact assessment project for reconstruction and expansion of expressway in Guangdong Province is presented. The acoustic environment quality of sensitive buildings along the expressway was measured and the noise impact after highway expansion was predicted. The noise reduction effects of four different forms of sound barriers, including vertical sound barriers, bent sound barriers, semi closed sound barriers, and fully closed sound barriers were analyzed. Low noise pavement, and speed limit setting were investigated. Based on the requirements of relevant laws, regulations, and technical policies, a comprehensive noise reduction plan was devised for the entire area affected by the project, including speed limit setting, low noise pavement, and multiple forms of sound barriers. This paper also suggests that big data technology should be introduced to highway noise prevention design to address the problems of updating lag and narrow valid parameter value of the current formula for predicting the intensity of expressway noise sources; Comprehensive information platform should be developed to collect wider range of data, such as road traffic flow, vehicle type ratio, and driving speed of each vehicle type and support the environment projects.

A novel tail fin propulsion mechanism is developed for large-scale BCF (Body and Caudal Fin) biomimetic fish. This mechanism employs the crank-rocker principle to convert steady motor rotation into sinusoidal oscillations, enabling stable tail fin undulation and precise dual-joint angular adjustments through a single power source. This mechanism is characterized by compact structure and simplified control. The prototype of the large biomimetic fish adopts a metal skeleton-skin configuration, effectively resolving assembly precision issues in large-scale motion systems while enhancing mechanical reliability. Self-propulsion tests in a towing tank are conducted to measure swimming speeds by tail fin oscillations, validating the propulsion mechanism's efficacy. The achievement provides technical support for applications of large biomimetic fish in marine monitoring and underwater rescue.

The fuel switching process of a large methanol dual-fuel powered container ship is simulated and analyzed to accurately predict the nitrogen purging effectiveness in the fuel supply system and investigate methanol fuel purging patterns. The numerical simulations of the purging process are performed under the ship's actual operation conditions based on the 3D model of the fuel supply system, methanol fuel's physical properties, and purging process flow. The purging performance under constant inlet pressure is predicted and the results are compared with freshwater flushing simulation results. This analysis clarified the effects of different media and pipeline volumes on purging time and methanol residue rates, providing practical references for safely and effectively executing nitrogen purging operations.

In order to accurately determine the human error factors that causes pilotage accidents and take effective measures to prevent similar accidents from occurring, the Cognitive Reliability and Error Analysis Method (CREAM) is used to analyze pilotage accidents. Based on the retrospective analysis function in the CREAM, a pilotage accident retrospective model is established, and three types of human error factor relationship tables (the Genotypes Tables, General and Specific Antecedent Tables, Error Mode Antecedent Table) are constructed. Based on these tables, the causes of pilotage accidents are traced. With a typical grounding accident as the example, the method is used to trace the human factors that lead to the grounding, and the results is compared with the accident analysis results in the existing accident investigation report to verify the effectiveness of the method. Suggestions for improving the safety of ship pilotage are put forward, including strengthening the education and training of pilots, improving the reliability of pilotage facilities, and strictly implementing regulations, etc.

Drawbacks of traditional soil and water conservation monitoring methods, such as low efficiency, terrain limitations, and incomplete data integrity is overcome by introduction of UAV (Unmanned Aerial Vehicle) in the comprehensive soil erosion control project in Qingshan Small Watershed. By processing UAV imagery to generate high-precision DOM (Digital Orthophoto Maps) and DSM ( Digital Surface Models), geographic information such as bare land area, vegetation coverage, slope length, slope width, and slope gradient were automatically extracted. Using the acquired slope length and gradient data, the RUSLE (Revised Universal Soil Loss Equation) was applied to simulate soil loss. A comparison between simulated and field-measured data from six monitoring sample areas was conducted. The experimental results demonstrated minor discrepancies between simulated and measured values, with relative errors ranging from 3.13% to 11.80%, indicating that the simulation model effectively reflects soil loss dynamics. This project has confirmed that UAV technology combined with modeling can provide robust support for soil and water conservation monitoring.

To effectively predict congestion at highway toll stations and solve it, a digital twin solution to predicting congestion happening at highway toll stations based on random forest model is introduced. This solution mainly includes the following functional modules: traffic scene construction; real-time data collection; congestion analysis and prediction; toll station intervention; and visualization display. It collects traffic information through integrated sensing devices such as door frames, vehicle inspectors, and millimeter wave radar. It uses the Unity3D platform to create high-precision 3D models of toll stations and uses CART (Classification and Regression Tree) algorithm to construct a random forest model for traffic flow prediction. Research shows that this scheme can help alleviate congestion at toll stations, improve the efficiency of highway operation and management, and improve the feelings of drivers and passengers.

To address schedule management challenges in resource-constrained ship outfitting projects, a progress management model is developed based on global project resource scheduling. This model utilizes the AHP (Analytic Hierarchy Process) to decide resource allocation priorities for subtasks, establishing a resource scheduling framework under constrained conditions. Network planning techniques and priority rule-based heuristic algorithms are applied to separately allocate resources for critical and non-critical tasks. Trial results demonstrate that this model enables proactive resource configuration interventions, effectively improves resource utilization efficiency, and resolves issues of resource shortages or wastage.

The electric power system for a multi-purpose heavy lift vessel needs special design effort because it has to ensure the operation of the cranes onboard, which cause great surge loading. This paper explores the impact of cranes on the design of power plants on multi-purpose heavy lift vessels, focusing on the power station capacity configuration, the power management, reverse power handling, and the selection of cable and protection devices. The power requirements of the cranes are determined based on demand coefficients and probability calculation to ensure that the generator capacity meets actual needs. The design includes heavy load request and power limitation functions in the power management system to ensure safe operation. Various solutions for reverse power handling are investigated, including reverse power absorption resistors, power limitation, and battery absorption.

This paper focuses on how to build a set of data streaming and aggregation technologies suitable for large group enterprises to store data towards objects in a hybrid multi cloud scenario, providing business side secure access and diverse source data interaction scenarios in the form of unified object storage PaaS services; This method adopts the cloud native S3 protocol to redefine the encapsulation, parsing, and forwarding control of heterogeneous object storage services, achieving data access interaction, replication migration, customized data layering, aggregation, merging, and loading of object storage in mixed heterogeneous scenarios through unified service scheduling. This method has been applied in the cross-border container rental application scenario of a large shipping group enterprise, and the results have shown that it can efficiently achieve secure, flexible, and elastic data unified interaction capabilities in the business scenario of mixed heterogeneous object storage.

In order to improve the accuracy of prediction of wind speed and direction at sea the application of Auto-Regressive (AR) models is studied. The autocorrelation of the wind data time series is examined before AR processing. The Prediction of wind vector is conducted with Auto-Regressive Integrated Moving Average (ARIMA) model and the Vector Auto-Regressive (VAR) model separately and the results are examined. The experimental results show that 34.17% of the VAR model prediction results fall within the error range, while this number for ARIMA model reaches 61.25%.

With the globalization trend of the chemical industry, the operational efficiency and safety resilience of liquid chemical terminals have attracted much attention, and traditional management models are no longer suitable for the needs of modern logistics. This paper, based on real-life application scenarios, designs and develops a digital twin platform for smart liquid chemical terminals. The platform adopts a layered architecture, including data source layer, base engine layer, general capability layer, architecture fusion layer, and scenario empowerment layer. Implementation of integrated, visualized, and intelligent management and control of terminal operations at all levels is realized. Among them, the dock environment monitoring subsystem integrates multiple heterogeneous sensors to achieve real-time and comprehensive monitoring of the dock operation environment; The production safety management subsystem integrates multiple key systems to build a comprehensive safety protection system; The intelligent operation and maintenance subsystem of the dock utilizes digital twin technology to achieve real-time mapping of equipment status and intelligent operation and maintenance management. The system has been developed and integrated in a liquid chemical terminal shore area, achieving succesful results.

The scale effect in model tests and numerical simulations of a large bulk carrier with combined energy-saving devices is studied. The energy-saving performance achieved by the devices is tested and calculated in two different model scales respectively. The test data are compared with the calculation results. The comparison shows that the tests with larger model scale is better in predicting performance improvement and the trends of propulsive performance parameter change caused by the energy-saving devices. From the perspective of engineering application, it is recommended that, within the reasonable range of test conditions, large-scale ship models should be used for towing tank tests of ships equipped with energy-saving devices.

Based on the Computational Fluid Dynamics (CFD) software Star CCM+, a numerical simulation of ventilation of the pump compartment of a methanol-fueled 16 000 TEU ship is carried out. The volume change law of leaked methanol is derived by Volume Of Fluid (VOF), and the time required for the air in the pump compartment to reach the safety threshold at different jet velocities is studied. The research results show that with the existing ventilation system on the ship, the air in the pump compartment can reach the methanol safe threshold of 200 mg/L within 114.74 s. The ventilation effect is best when the jet velocity is 0.5 m/s, which shortens the time required for ventilation to meet the standard by 2%. When the jet velocity is too high, it will cause flow field disturbance, and some methanol gas will be blown into dead spaces and, hence, lower the ventilation effectiveness.

The ship mast vibration caused by excitation source coupling is analyzed as an element of ship system. The case of a Panamax bulk carrier is analyzed for illustration. The mast vibration prediction method is derived based on the ship'sglobal-structure-mast-coupled finite element model established in ship design phase. During sea trials, multi-channel vibration measurement technology is applied to conduct full-scale vibration measurement of the mast. The accuracy of the numerical predict method is verified against the full-scale measurement data. The results show that the error of the vibration predicting method can be controlled within 3%.

To continually Improve the maintenance timeliness for traffic mechanical and electrical equipment has been one of the major interests of traffic management departments. A Logistic regression model is built based on the related maintenance work order records kept in Shanghai. The cases that did not satisfy the system operators in terms of maintenance time are studied and the causes are analyzed. The analysis indicates that maintenance timeliness is strongly dependent on the following factors: the equipment type, the equipment location and trouble happening season. The camera equipment and the equipment for license plate recognition, information board are found to need more maintenance time. The equipment installed at the outer ring highway needs extra time. Besides, February, June and July are the higher fault rate months. The following improvement measures are suggested: to enhance the maintenance standard for key equipment; to set up operation and maintenance sub-centers at the outer ring highway; to increase the maintenance force in bad weather and holidays.

To achieve effective detection of safety helmet/working clothe targets from a work site image, an improved YOLOv5_6.0 small object detection algorithm is developed. Detecting helmet/working clothe targets has been challenging because they are small in size and similar in color, and yet, densely distributed. The bounding box regression loss function of the YOLOv5_6.0 algorithm is modified for optimizing the learning effect about dense small target feature information; One additional feature extraction layer is inserted to improve the small target detection performance; A Global Attention Mechanism (GAM) is introduced into the backbone to enhance the overall detection performance; A two-stage YOLOv5_6.0 small structure algorithm for confirming safety helmet/working clothe targets is integrated. The developed algorithm is used to process the images of shipping scenario for verification. The results show that the improved algorithm can achieve the average precision values of 97% for safety helmet detection and 87% for working clothe detection, an improvement of 5.5% and 5.3% respectively, compared to the original YOLOv5_6.0 algorithm.

To address the congestion issues on highways caused by significant traffic flow variation to improve the road transportation efficiency and reduce the operational costs of traffic management departments, this paper conducts vehicle profiling research based on vehicle travel behavior and trajectory characteristics. The key vehicles that frequently appear on the road network are identified and occasional driving data are ignored; A travel behavior portrait system is constructed. The system operates based on a three-level labeling system, covering six core dimensions including vehicle information, travel frequency, duration, speed, distance, and travel preferences. It produces comprehensive and multidimensional vehicle portraits for peak hours and off-peak hours; An improved Analytic Hierarchy Process (AHP) algorithm and entropy weight method are used to decide the weights of lower level labels and calculate the score of the top level labels; The vehicle portraits are categorized into 6 categories by the K-Means clustering algorithm based on their scores; The PrioritSpan algorithm is used to mine the typical path patterns of the six types of vehicles at different time periods, generating sets of travel patterns for different types of vehicles. The effectiveness of the system is proved by experiments.

To enhance the safety of maritime operations, an in-depth analysis of cybersecurity risks faced by oceangoing vessels is conducted, along with the exploration of corresponding mitigation strategies. The study systematically categorizes major cybersecurity risks for oceangoing vessels, including external hacker intrusions, malware attacks, internal human errors, and inherent system vulnerabilities. Seven targeted mitigation strategies are proposed, emphasizing the adoption of advanced cybersecurity technologies and solutions-particularly the integration of AI (Artificial Intelligence) and ML (Machine Learning) technologies to strengthen threat detection capabilities. The strategies also highlight the need to intensify cybersecurity training for crew members to improve overall security awareness, implement rigorous data backup and recovery mechanisms, and employ dedicated networks and isolation technologies to reduce risks from external attacks.

A study on pollution control performance evaluation indicators for stormwater drainage systems is conducted to support urban stormwater management planning and to safeguard river water quality. Focusing on stormwater pumping systems within separated drainage systems, this research systematically analyzes pollutant sources in stormwater networks, and key factors influencing their discharge, through literature review and practical case studies. The formation mechanism of overflow pollution is studied. Based on drainage engineering characteristics, multiple critical indicators reflecting pollution control effectiveness in stormwater networks are set up. The analysis reveals that pollutant management in stormwater systems can be performed in three aspects: source control, process control, and end-of-pipe control. Specifically refined indicators are developed for each aspect with clear definitions, providing foundational references for establishing a comprehensive evaluation framework for pollution control in stormwater drainage systems.

The indoor secondary structural noise prediction method proposed in the environmental impact assessment guidelines has left several key parameters undefined, hence the prediction results with the method has quite often been found unsatisfactorily deviating from actual measurement results. This paper theoretically analyzes the on-site measurement data (indoor vibration acceleration, vibration velocity, and secondary structural noise) from the buildings along the underground railways in Shanghai, Suzhou and Guangzhou, and devises a reference data looking-up-based method to supplement the guideline and improve the method. A set of actual measurement data for typical scenarios, including Z-axes vibration level, vibration velocity level, and structural noise, is collected and recorded. Looking-up the data set and finding the data associated with interested scenario, one can get au usable prediction. Practical application shows that 81% of prediction achieved 3 dB accuracy or better. As a comparison, for the prediction based on vibration level measurement, the number is 86%. In the circumstances of measuring vibration impractical, reference looking-up method is a reasonable alternative measure.

Addressing the potential safety issues of hull structure and docking blocks during the strength test of large container ships in dock, this paper uses FEA (Finite Element Analysis) to simulate the process and verify the safety of hull structure. A suitable simulation method for docking blocks achieving both high FEA calculation efficiency and good reaction force calculation accuracy are introduced. An optimized scheme of docking block arrangement is devised. The fact is that the arrangement of docking blokes has been designed for ensuring the safety of ship construction in dock. Further requirements for in-dock strength test demands arrangement adjustment. The research shows that the knowledge on the distribution of reaction forces from the docking blocks can be the guide for the docking block arrangement adjustment, keeping it partial in range and minimum in quantity.