A fast wake evaluation method is devised for a full-formed ship. The CFD (Computational Fluid Dynamics) technology and artificial intelligence algorithm are used to standardize the wake field and construct the evaluation model. The accuracy of the model is checked by PIV (Particle Image Velocimetry) technology. The artificial intelligence algorithm for the model is chosen through model training. Three artificial intelligence algorithms are tried and the one gives the best fitting accuracy is picked up for the final model. The calculation error of the model is analyzed. Experiments show that for full-formed bulk carriers, CFD software is good for simulating the flow state of the wake field and displaying flow details. The parameters such as wake uniformity can be valuable references for optimizing the stern profile of full-formed ships, designing propellers and energy-saving devices.

To investigate and locate the leakage of a marine lubricating oil cooler, comprehensive analysis is conducted in chemical composition of equipment materials, metallographic structure of welds, scanning electron microscopy of corrosion morphology, and energy spectrum of corrosion products. The microstructure and chemical composition distribution around the corrosion area are obtained. The causes and mechanism of the corrosion are studied to avoid similar corrosion leaks.

Currently, the operation status of ship air coolers is mainly determined according to the temperature of the pressurized airT_A2. An alarm is only triggered when the air cooler is extremely abnormal, resulting in poor timeliness, let alone early warning. To effectively solve this problem, a GA-BP (Genetic Algorithm-Back Propagation) neural-network-based temperature prediction method for pressurized air at outlet of the air coolers is proposed. An air cooler state prediction model is built. By detect the deviation between the measured and predicted values of T_A2, abnormal states of the air cooler can be identified in a timely manner; Genetic optimization algorithms are introduced into the BP neural networks to speed up the convergence and avoid local optimal solutions. To verify the effectiveness of the prediction-based method, multiple sets of state data before and after air cooler cleaning are selected for training and validation. The results show that the GA-BP prediction results are consistent with the actual application of air coolers and could effectively identify abnormal states of air coolers.

Based on the experience of a ship yard designing and building LNG (Liquefied Natural Gas) vessels, this paper reviews the installations of NO96 membrane cargo containment systems on the vessels and the evolution of the design of NO96 system, from NO96 PERLITE, NO96 GW, NO96 L03+ to NO96 SUPER+. The principal specifications of different type of NO96 membrane cargo containment system, the BOR (Boil Off Rate), strength and weight and the relationship between them, are studied. With the design development of NO96 membrane cargo containment system, the BOR has been reduced from the initial value 0.150% to the current value 0.085%. Due to the application of new material and rationalized structure design, the strength and weight of the system have been improved significantly, too.

Noise pollution from traffic is on the increase and may impair the living environment of surrounding area. This paper provides a comprehensive analysis of common traffic noise control measures in terms of noise sources, propagation pathways and noise receptors. The current research progress on noise reduction materials of sound insulation and absorption is discussed. The prospects on future traffic noise prevention and control are given. The study indicates that, in active noise reduction measures, methods such as soundproof windows and acoustic barriers have proven to be effective in reducing the noise levels received by environmentally sensitive receptors. Regarding noise reduction materials, future research may focus on noise reduction performance, lightweight construction, durability, cost-effectiveness, and the development of high-quality materials suitable for various scenarios.

For the digital transformation of enterprises, the first task is to integrate management information systems scattered at different locations with a wide variety of applications. However, as these systems were developed in different periods and adopted different technical solutions, they have different operating platforms and databases, it is difficult to integrate them. Based on an actual case, this paper designs and develops a data governance solution based on the middle office technology, which aims to break through the data barriers and to achieve the goal of turning data into assets. The application of the solution shows that the efficiency of data collection, data processing, data analysis and data application of the case enterprise has been significantly improved, the level of operation and management has reached a higher level, and the digital transformation of efficient services, precise governance and intelligent decision-making has been basically achieved.

Two-stage turbocharging with intercooler system can reduce the power consumption in the process of air compression. The saved energy may be used and, therefore, improve overall efficiency of the system. The derivative uses of the two-stage turbocharging technology for marine two-stroke diesel engines are calculated and analyzed for the purposes of power generation, heating or producing air to the gas film drag reducing system. The impact of Two-stage turbocharging technology on scavenging system and exhaust treatment system in diesel engine is analyzed. The calculation results confirm and quantify the emission reduction effect, as well as the economic benefit. Also the disadvantages of this system are analyzed and avoided by system optimization. It is concluded that the energy saving effect of two-stage turbocharging with intercooler system can be achieved by combining it with some other technologies.

The flow field in an cavitation tunnel is simulated by RANS (Reynolds-Averaged Navier-Stokes) equations. The experiments are conducted to verify the RANS-equation simulation of the flow in the cavitation tunnel. The simulations with/without honeycomb/guide vanes are carried out to study the influence of honeycomb and guide vanes on flow field in the test section of cavitation tunnel. It is proved that the honeycomb and guide vanes are effective in keeping water flow even.

In order to improve the information transmission efficiency between the operation site and the bridge and the safety of anchoring operation, an intelligent windlass control system is conducted to upgrade the mechanical system, the hydraulic system and the electric control system. The upgrade windlass control system features one-push-button operation beside the windlass or in the bridge, to automatically do anchor standby, anchor releasing and anchor drawing according to the water depth measurements. The upgraded electronic control system can collect electrical and hydraulic status data through various types of sensors in the windlass and achieve the health status monitoring function. The system has been installed, and proved to be efficient.

The in-depth reinforcement learning technology is introduced into the highway traffic management and a traffic smoothing control system is designed and physically developed. The system controls the speed of vehicles by adjusting the speed limit value of The in-depth reinforcement learning technology is introduced into the highway traffic management and a traffic smoothing control system is designed and physically developed. The system controls the speed of vehicles by adjusting the speed limit value of road sections according to the traffic situation in bottleneck area. The system consists of three functional modules: dynamic speed limit initiation, speed limit determination and update-information board dynamic releasing. The mainstream deep reinforcement learning algorithm DDQN (Double Deep Q-Network) is used in the system, and a traffic smoothing control strategy based on DDQN is developed to improve the performance of the algorithm by the destination network and experience replay technologies. Based on the CTM(Cellular Transmission Model), a traffic flow scenario at a road section of Ningxia expressway is simulated, and the control strategy is verified in such environment. The experiment shows that the system can improve the traffic efficiency in the bottleneck area in terms of volume of traffic and vehicle transit time.road sections according to the traffic situation in bottleneck area. The system consists of three functional modules: dynamic speed limit initiation, speed limit determination and update-information board dynamic releasing. The mainstream deep reinforcement learning algorithm DDQN (Double Deep Q-Network) is used in the system, and a traffic smoothing control strategy based on DDQN is developed to improve the performance of the algorithm by the destination network and experience replay technologies. Based on the CTM(Cellular Transmission Model), a traffic flow scenario at a road section of Ningxia expressway is simulated, and the control strategy is verified in such environment. The experiment shows that the system can improve the traffic efficiency in the bottleneck area in terms of volume of traffic and vehicle transit time.

At present, the city's video image surveillance system can no longer meet the growing demands for urban digital operation and application due to technical bottlenecks such as forwarding strategy, technical architecture and software and hardware updating. This paper, with technologies such as distributed management, integrated media services, video source forwarding, all-round data aggregation and multi-mode data sharing, devises a set of digital management system suitable for million-level video images. The theoretical basis of the technical architecture is presented through the current situation analysis, problem analysis and strategy analysis. The feasibility of the technical architecture is demonstrated by a pilot project. The compatibility of the system with the equipment commercially available today is examined an for reference of future development.

The conventional air compression stations for gas supply in large-scale ship yards simply maintain a preset pressure in main pipe and leave the pressure at user ends letting it be. Such a system is weak in adapting to the changes at user ends. This paper introduces the user end information dynamically into existing air pressure control system to improve the adaptability. The relationship between main tube pressure setting and actual air pressure at user end is studied and the load changes at user ends are investigated. A control strategy based on big data analysis, which dynamically predict load changes and adjust the pressure setting value of the air compression station, is developed. The developed control system integrates multiple technologies such as cloud computing technology, energy applying application in the form of mini program, data modeling and analysis, and grey prediction models.

A comprehensive analysis is conducted on the Environmental Steward services and corporate environmental management. Through literature reviews and case studies, the current issues in corporate environmental management, the features and functions of the Environmental Steward services and development status of the services are studied. Measures are proposed to enhance the integration of the Environmental Steward services with corporate environmental management. The analysis concludes that the Environmental Steward is an effective innovative mode for enhancing corporate environmental management capabilities. The legal guidance for the standardization of Environmental Steward services is needed and the government and regulatory agencies can provide the guidance through powerful regulations and close supervision and guidance. The providers of the Environmental Steward services should enhance their own capabilities, actively update their knowledge base, and track and apply various new technologies, including cloud computing and big data, to achieve precise management and to improve work efficiency. Enterprises should actively assume environmental responsibilities and ensure the practical implementation of the technical services provided by Environmental Steward. Through the joint efforts of the government, consulting firms and enterprises, the Environmental Steward can play an effective role in corporate environmental management and effectively enhance the quality and efficiency of corporate environmental management.

Ships characterized as same type can be significantly different in technical parameters. For reasonably evaluate ship's fuel efficiency, they should be divided in a better way. This paper studies the way of grouping ships belonging to a shipping company for fuel efficiency evaluation. The ships involved covering bulk carriers, container ships, and tankers. A "two-step" ship grouping method is proposed. The unsupervised machine learning algorithm weighted K-Means is employed to divide the company's ships into groups according to nine ship attributes of the vessels, and the number of clusters is determined using the elbow method. Based on the obtained cluster number, the K-Means model is applied again to group the ships and assign category labels. The ship data are further processed using the supervised machine learning algorithm weighted XG-Boost according to the above categories to gain the capability of handling incomplete/bad quality data and providing categorizing probability. The enhanced model is used to process the ships belonging to other companies, the accurate attributes of which may be available. The effectiveness of the proposed method is verified through actual fuel consumption estimation.

In order to satisfy the core requirements of the highway engineering firms for internal operation data exchange and sharing in construction, management, maintenance, operation and safety and for the respond of external data demands, an resource capacity open platform for construction, management, maintenance, operation and safety is designed based on the API (Application Programming Interface) gateway principle with secondary development. The work is focused on the following: sorting and classifying the businesses associated with the highway construction and operation; design of the overall framework of the platform and the structure of resource service directory and system engineering. The transformation of existing business system is carried out to make it fit to the open platform. The internal and external data sharing and opening are realized.

In order to imediately detect unsafe actions of crew members and to reduce the risk of accidents caused by crew misoperation, a method for identifying unsafe actions of crew members based on YOLOv5-Lite algorithm is proposed. The Fire Module structure is introduced into the YOLOv5 algorithm to achieve channel transformation, which also reduces the number of image recognition model residual modules and the size of the model, and, in turn, to improve the operational efficiency of the model. As an example, an image recognition model for detecting persons in operation area who is not wearing a safety helmet is established. The model collects image data, generates an HTST (Helmet Tumble Smoke Tired) dataset, and performs image processing. The model is trained to achieve the identification of movements of people. The output of the model is compared with the recognition results obtained with algorithms YOLOv3 and YOLOv4 to verify the effectiveness of the method. The results show that the method for identifying unsafe behaviors of crew members based on YOLOv5-Lite algorithm can effectively identify unsafe behaviors of crew members with a mAP value of 95.70%. YOLOv5-Lite algorithm has better stability and detection capability than that of YOLOv3 and YOLOv4. The FPS (Frames Per Second) detection speed is fast, meeting the demand for real-time identification of unsafe behavior of crew members.

This paper studies the demands of traffic management industry for video incident detectors and the application of the detectors in traffic engineering projects at development stages and highlights the developments of mainstream AI (Artificial Intelligence) video incident detectors in traffic engineering market. The video incident detector has developed in four stages, from standard definition video incident detector, high-definition video incident detector, cloud desktop video incident detector to AI video incident detector. The detection effectiveness and recognition efficiency and other function-alities have been improved through the stages, but with the ever-escalating requirements, the technical and application bottleneck is gradually emerging. With the development of AI and cloud computing technology, deep involvement of AI technology will be the main development trend of video incident detector and they will develop the capability to dynamically perceive the status of traffic incidents and traffic flow in real time and to actively predict traffic safety incidents and traffic conditions.

Sound barrier installation projects usually have the characteristics of short effective construction period, complex construction environment and high safety risks. The sound barrier installation project for Shanghai metro line 1 which has been keeping in service has completed on schedule and without any accidents. This paper reports the experiences of the project management. The hazard identification analysis table and targeted preventive measures are prepared, covering catenary grounding, material loss, welding electric shock, falling from high place and object strike. The measures for improving efficiency are devised for all tasks of the project, such as design, process, quality and machinery.

The hydrodynamic characteristics and mooring safety of the deep-water aquaculture platform ZHENYU No.2 is studied with the fishing net modeled based on Froude similarity criterion. The external force on the platform under the extreme wind speed and flow velocity is tested, and the frequency response of the platform to regular waves is studied through experiments and numerical simulation. The forces on the mooring system when moving and moored under the combined action of wind, wave and flow are tested to get the characteristic values of platform hydrodynamics and the forces acting on the mooring system. The results of numerical simulation and test show that, when ignoring the influence of the fishing net, wave itself has little effect on the motion of the platform. The safety factor of mooring system under cross-wind, cross-wave and cross-current action meets the requirements of relevant guidelines of classification society with a certain safety margin.

FreeCAD is used as the parametric modeling tool to generate a ship hull form. OpenFOAM is used as a numerical simulation tool to find the resistance of the ship hull. Regression analysis is used as the data processing method to learn the relationship between parameters and resistance and, in turn, the impact of each parameter on the resistance. The optimal parameters for the best resistance performance are decided. An engineering ship is examined and optimized as an example. The results show that the inflow section of the target ship has a significant effect on the resistance and the resistance is reduced through optimizing the parameters.

This paper introduces the key points of soil environmental management of industrial enterprises in three stages, namely, the construction period, the operation period and the shutdown period, analyzes the possible risk problems, and puts forward the preventive measures that can be taken, such as soil hidden danger investigation and strengthening self-monitoring, and strictly controlling the discharge of hazardous substances. The soil pollution potential investigation and self-monitoring carried out by a ship building and repairing enterprise are explained as an example. The hidden dangers of soil pollution scope were identified and rectified timely through hazardous waste disposal measures so as to reduce the risk of soil pollution.

The traditional turbocharger state trend prediction method has the problems of low accuracy and high subjectivity dependence. This paper proposes a LSTM (Long Short-Term Memory)-based turbocharger state trend prediction method. The turbine speed is taken as the evaluation index of turbocharger operation status. The strategy of turbocharger status data screening is devised to reduce the impact of operating conditions and external factors on the characteristics of turbocharger state change. The state trend of the turbocharger is predicted by using the cycle nodes in the LSTM hidden layer and the time sequence similarity search. The performance of LSTM trend prediction model is analyzed and verified. The results show that the LSTM-based turbocharger state trend prediction method has better tracking capability and significantly higher accuracy than those can be expected from the least square method.

In order to anticipate springing or whipping driving hull into the limit of the fatigue strength and ultimate strength in mega container ships and, meantime, enrich the relevant full scale ship data, a hull structural safety monitoring system considering the hydro-elastic effect of springing and whipping is proposed to monitor the structural safety of the ship. The application of the system on the mega container ship is introduced. By reasonably setting sensing points in the main structure and other relevant parts of the ship, and fusing the parameters of stress, acceleration and waves, it can provide early warning in case the structural stress is tend to beyond the threshold value, and can assist in decision making to avoid the risks caused by human decision errors during navigation. Springing vibration analysis of the monitoring data from the full-scale ship is carried out to provide reference for researches on the hydro-elastic effect of mega ships.

Aiming at the problem that time dependence and spatial correlation are not involved in the existing speed prediction models, this paper develops an early warning system based on a short-term road condition prediction algorithm with ST-GCN(Spatio-Temporal Graph Convolution Network) model. This algorithm comprehensively considers the impact of time dependence and spatial correlation. With real-time and historical traffic data, ST-GCN model analyzes and predicts the traffic speed and road condition in a certain period of time in the future. The predicted road condition is pushed to the color display boards installed with the expressway to guide drivers and passengers, thus, reducing the accident rate and improving the traffic efficiency of the expressway.

A new work order assigning method is proposed for coordinating comprehensive maintenance of public facilities to avoid duplicated resource assignment or maintenance gap. The method coordinates work order assigning process based on principle of economy. The new method sets up a work order pool and divides the work orders according to the urgency. The pressing ones will be sent to the nearest work team as early as possible. The remainings are grouped and assigned to suitable work team according to the distribution of work sites. In this way, the method improves the efficiency of work order handling and reduces maintenance costs.

For installation of fairing of multi-beam device on existing buoy tender, eliminating the influence of air bubbles, two different installation positions are proposed by the overall layout plan. By CFD（Computational Fluid Dynamics） numerical simulation, the ship performance assessments for the buoy tender to be equipped with the fairing are carried out both in moderate sea and calm water sea conditions. The anti-bubble property and resistance are predicted and analyzed. The results show that, for the two different installation positions, there is no significant difference in anti-bubble in moderate sea, while in calm water, different installation positions lead to different performances and the deflector angle of attack has a huge impact on the flow field around the hull.

A traffic guidance system based on flexible lane control algorithm is developed. With multi-source traffic condition data, emergency data and information board information release technology, this system can be used to achieve intelligent traffic guidance, when the management requirements of particular highway operator and the emergency response mechanism for particular highway segments are input to the system.

To effectively address various data heterogeneity issues in SAP (System Applications and Products) projects and to meet users' requirements for accuracy and efficiency in data conversion, a SAP universal data conversion platform is designed with Java language. By analyzing the problems encountered during the SAP project, such as large data volume, inconsistent data granularity and poor system operability, this paper elaborates on the design requirements of the data conversion platform. Based on this, the overall framework, design ideas, data processing models and important functions of the platform are discussed. The platform is physically developed. The practical application results show that the platform can meet the accuracy requirements of data fields with satisfactory efficiency of data processing, and has good operability, practicality and scalability. It can provide reference for efficient and fast conversion of massive data in similar projects.

Ordinary neural-network-based bearing fault diagnosis methods do not strong enough in extracting features. For scenarios with limited data samples or low robustness, these methods cannot obtain accurate diagnostic results. This paper develops a fault diagnosis method for rolling bearings based on integration ofCNN (Convolutional Neural Networks) with TL (Transfer Learning), i.e. TCNN (Transfer Convolutional Neural Network). The AlexNet network, one of the benchmark CNN models pretrained with the ImageNet dataset, is selected in the proposed transfer CNN.On this basis, TL is combined to freeze the underlying parameters inexisting prediction models, and only train and update upper level parameters. When the number ofiterations reaches a certain level, this approach can effectively improve the accuracy rate of fault diagnosis.The experimental results show that the TCNN can improve the noise resistance and generalization ability of the model with smaller dataset, and improve the accuracy of fault diagnosis.

The design of an anchor mooring type floating dock is required by the regulations to check its heeling angle during ship lifting operations, and make sure that the deck edge will not go into the water when it tilts under specified wind pressure. The conventional method for calculating vessel heeling cannot be used as it is, because it is valid only for free floating vessels. The mechanism of typical anchoring modes effecting the heeling angle of the floating dock is studied, which indicates that the bottom anchoring will increase the heeling angle and the dispersed anchoring will do the opposite. The formula for calculating the heeling angle of the floating dock in anchor mooring modes is derived. The anchoring system selection, the anchoring forces and their effect on a small floating dock is comprehensively analyzed as an example.

The structure strength of the extra-high-strength-streel-made cargo hold structure of a 20 000 DWT transfer barge is analyzed, emphasizing the calculation of the long block. The modeling, the boundary constraints defining and load scenario selection is described in detail and the model is solved. The welding technology and construction process of extra high strength streel hold is also described in detail.

The vibration source intensity and ground vibration attenuation at a typical section of an underground railway tunnel in a city in East China is measured and analyzed. The vibration source intensity measurement shows that when a train passes the section at a speed of 79 km/h, the average maximum Z-vibration levels at the rail, track bed, and tunnel wall of the test section are 122.9 dB, 92.9 dB, and 79.0 dB, respectively, as the expectation for the direction of vibration decrease; The characteristic intensity peak of the vibration source on the test section is concentrated at 50 Hz; Ground vibration attenuation tests are conducted on surface. The tests prove that the characteristic peak of ground vibration is at 50 Hz, same as the measurement at the tunnel wall and the maximum Z vibration levels at surface gradually decreased as the horizontal distance from the source increases. Compared with the tunnel wall, an amplification phenomenon in the low-frequency range below 31.5 Hz is found.

The mooring process of a 20 000 t on self-propelled transshipment barge is studied, focusing on mooring safety, operation time, and the impact of draft changes, and waves and surges on ship loading/unloading operations. Based on the configuration of port facilities and the characteristics of ship barge transportation, most suitable port facilities are designed including an automatic cable tension control system, automatic mooring piles, board side protection devices and control systems, and a centralized mooring winch remote control system.

In order to improve the efficiency of ship-shore information transmission, an integrated ship-shore communication solution based on an improved MQ (Message Queue) protocol is developed. A ship-shore communication method that features multiple communication mode automatic recognition-switching is introduced to address the issues of insufficient bandwidth and incomplete coverage area of a single communication method. Meantime, communication strategies for different ship operation scenarios are proposed. In response to the large amount of data to be exchanged between ship systems MQ communication technology with algorithm improvement and a traffic peak shaving technology scheme are introduced, which improves the communication reliability and Immediacy. The ship-shore information exchange scheme is tested on the ship-shore integrated safety monitoring system of a chemical ship to verify its feasibility. Different communication scenarios is simulated by setting network connection status and the bandwidth pressure of data transmission is simulated by setting different data transmission frequencies. The test results show that this scheme can effectively solve the problem of data packet loss, alleviate the pressure on computing resources, and improve information transmission efficiency.

In response to the need of systematic research on carbon emission management approaches for enterprises,this paper reviews the current situation and future development trend of carbon emission management in several key industries such as shipping industry, power industry, steel industry and aviation industry. The critical problems of existing carbon emission management in these enterprises are analyzed. 7 key critical problems limiting the efficient carbon emission management are identified. Top-level planning, data standardization system and carbon emission factor accounting are considered the most important 3 of them. 8 key things for carbon emission management are brought out. They cover developing strategy and roadmap for low-carbon transformation, improving carbon emission factor accounting system, developing low-carbon technology, and establishing carbon information publication management mechanism.

An increasing number of container terminals are transitioning into automated ones by automating their port machinery. The hybrid operation of manual and automated equipment has increased operational density and information exchange demand, making terminal operations more complicated. It is very difficult to manage, monitor, and control these automated machines using traditional methods after the transformation, so efficient data processing and control methods are needed. The data integration solution for container terminals under automation transformation built in this paper establishes a data rule engine for data governance based on comprehensively gathering terminal data and information. It reduces data acquisition latency through a time-series database, improves system concurrency performance through a microservice technology framework, and uses WebGL technology in the front end to achieve data visualization. It has multiple functions such as equipment monitoring, equipment control, and task scheduling management, providing an efficient, stable, and comprehensive full-field operation control system for automated container terminal managers.

The operation of propeller in uniform flow is simulated with SST k-ω (Shear Stress Transfer k-ω) turbulence model plus Schnerr-Sauer cavitation model and RANS (Reynolds Averaged Navier-Stokes) equations calculation. The cavitation area on blade surface of the propeller is determined. The study shows that the percentage of cavitation area on blade surface of the propeller is in good agreement with the experimental results and the numerical method is accurate enough for evaluating the cavitation area of the propeller in uniform flow.

The FMECA (Failure Mode and Effect Analysis) analysis on the photoelectric shaft power testing system is performed by means of software Isograph. The weak link of the system is defined based on the calculation of the FTA (Failure Tree Analysis). The modal analysis on probe and code disk is carried out by using software Solidworks and ANSYS Workbench. The analysis indicates that vibration may make the code disk severely deformed, which can guide the improvement of the existing system and effectively improve the reliability of the test system.

A ship data acquisition system supporting multiple communication modes is designed on an industrial computer with the embedded operating system Linux to meet the demand for multi-communication protocol transmission of intelligent ship data acquisition systems. The system comprises data transmission, data analysis and data storage modules. The data transmission module suports CAN (Controller Area Network) protocol, TCP/IP (Transmission Control Protocol/Internet Protocol) protocol, and serial port RS232 protocol. The data parsing module performs data format conversion and sends data to the upper computer in TCP/IP protocol. The upper computer, equipped with MATLAB, do data analysis. Experimental results show that the multi-communication protocol acquisition system based on industrial computer can meet the needs of intelligent ships, including diversified sensor interfaces, reliable and accurate data, real-time transmission and processing.

The design of the LNG (Liquefied Natural Gas) fuel tank of a 15 000-16 000 TEU new Panamax container ship is analyzed. A few structure and layout schemes are studied and compared in terms of swaying load of the fuel tank on the ship, ship’s loading capacity and ship stability. An optimized scheme is suggested. With his scheme, the width of the tank fuel is less than 56% of the breadth of the ship and the fore part of the tank or even the total tank is positioned under the superstructure of the ship. This design significantly improves the space utilization rate and stability of the ship.