Ship Performance Research Articles

Analysis of Fin Stabilizer Base on NACA 0010 in Fast Patrol Boat to Reduce Appendage Resistance on Numerical Method

The main function of the fin stabilizer on patrol boats is anti-rolling and providing comfort for ship personnel. However, the installation of the fin stabilizer has a consequence in the form of appendage resistance of the ship. This study analyzes the magnitude of the appendage resistance due to the installation of the NACA 0010 stabilizer fin mounted on a 60m patrol boat at an angle of 0º. Reduction of ship resistance is expected to improve the ship performance which then can optimize the use of fuels and minimize pollution. In the early stages, the bare hull was validated with the results of the model test on the towing tank with a resistance difference of less than 3%. Based on the simulation results, it is known that the average resistance value of Fine Marine Numeca is 1.87% higher than the resistance value of the Maxsurf software. From the results of testing the appendage resistance value with 3 variations of the shape of the NACA 0010 fin, it is known that the appendage resistance value of fin stabilizer 2 is 1.04%, fin stabilizer 1 is 1.26% while fin stabilizer 3 is 1.6%. The appendage resistance of fin stabilizer 2 is smaller than the variation of fin stabilizer 1 and 3 models.

Biofouling occlusion of ships’ internal seawater systems: operational, economic, and biosecurity consequences

Biofouling of ships’ internal seawater systems (ISS) can cause significant operational issues and is a potential transfer mechanism for marine nonindigenous species. This study used an engine room simulator and economic evaluation to quantify impacts on commercial ship performance of biofouling occlusion within various ISS nodes (sea chest, strainer, and heat exchangers). A characteristic hockey-stick relationship between occlusion and impact emerged, whereby engine room systems could tolerate up to 55% occlusion of a single node without operational impact, followed by rapid performance deterioration. The relative magnitude of impacts varied by ISS node and in response to changes in ambient seawater temperatures. System tolerance was much lower when simultaneous occlusion of multiple nodes was assessed. In economic terms, consequences included required freight rate increases of 1–26% prior to forced (automatic) slowdown of the ship and up to 82% increases if slowdown conditions were required.

Validation of short-term prediction of added resistance in head seas considering wave steepness nonlinearity with probability density function method

The added resistance in waves, which is an important component in the estimation of actual sea performance of ships, has been evaluated as the average value by short-term prediction methods. In this paper, a novel probabilistic method to account for non-linearities of added resistance with respect to wave height in short-term sea conditions is proposed using the joint occurrence probability distribution of wave height and period and non-linear added resistance response in the frequency region. It is a method of averaging the combination of crest and trough that ships encounter in irregular waves, which is considered as one wave of the regular waves, and the resulting added resistance is combined stochastically. The non-linearity with respect to wave height is empirically expressed as a “correction coefficient” obtained from the comparison of CFD data and potential-based linear calculation results in regular waves. The results of the proposed method have a reasonable agreement in the acceptable range of accuracy with results of RANSE based CFD numerical simulations in long crested irregular waves and the experimental model tests. As a result, the proposed method is applicable for obtaining added resistance in irregular head waves having the non-linearity with respect to wave height with a scope of further improvement in the method.

Effect of Hull and Propeller Roughness during the Assessment of Ship Fuel Consumption

The effects of hull and propeller roughness are presented over ten years of operation on ship performance. The developed model used in this study is a combination of NavCad and Matlab to perform the resistance and propulsion computations of the selected ship as well as the processing of input and output data. By considering the ship hull, the engine installed and an optimized propeller, the ship performance is computed for a different combination of hull and propeller roughness according to the ITTC recommendations and the opinion of experts in the marine field. Twelve cases are simulated over the selected years of operations and compared to the new ship performance. The hull roughness has the dominant effect on the performance of the ship due to its large area. However, by adding the effect of propeller roughness, an increment is noticed in the loading ratio and fuel consumption by 1–4% and 2–4%, respectively, in addition to the hull roughness. From this study, it is concluded that the roughness of both the hull and propeller is important consider to achieve more accurate results than just considering the hull roughness.

An ultrafast rechargeable and high durability lithium metal battery using composite electrolyte with the three-dimensional inorganic framework by Li6.4La3Zr1.4Ta0.6O12 surface functionalization

The liquid electrolyte used in traditional lithium-ion batteries has risks of leakage, combustion and explosion. Solid electrolyte is one of the effective strategies to solve the safety problems of lithium-ion batteries. And the use of solid electrolytes makes it possible to use lithium metal as an anode to achieve higher energy densities. At present, the main factors restricting the performance improvement of all-solid-state lithium batteries are the low electrochemical performance of electrolytes and poor solid-solid interface contact. The composite electrolyte has the advantages of both inorganic materials and polymers, but its electrochemical performance is still not up to the requirements of use. In situ synthesis of LaRuO3 with perovskite structure on the surface of Li6.4La3Zr1.4Ta0.6O12(LLZTO) induces the formation of Li2Zr2O7 while introducing defects. The Li2Zr2O7 phase "welds" inorganic particles into three-dimensional(3D) inorganic framework, increasing the reaction sites between inorganic fillers and polymers. Compared with the primitive sample, the ionic conductivity of the modified electrolyte is increased by an order of magnitude at room temperature, wherein the lithium-ion conductivity of the composite electrolyte with 3% LaRuO3 is as high as 6.06 × 10−4 S cm−1. At 5C, the discharge specific capacity of LiFePO4 | [email protected] 3% LRO | Li can reach 114.6 mAh g−1; After 400 cycles, the discharge specific capacity remains at 129.6 mAh g−1. Under the same conditions, the discharge specific capacities of the unmodified samples are only 92.4 mAh g−1 and 35 mAh g−1. The high rate discharge performance of solid-state lithium metal battery supports the high torque output of motor, which improves the acceleration performance of electric vehicles or ships. The high capacity and excellent cycle performance of solid-state lithium metal battery can significantly extend the driving range and service life of electric vehicles.

A Boundary Element Method for the Prediction of Hydrodynamic Ship–Ice–Wave Interactions in Regular Waves

AbstractFor ships navigating in ice floe fields, ship–ice–wave interactions may affect ship performance and ice impact forces. This paper presents an approach to evaluate the cross-coupling added mass and hydrodynamic damping between a passing ship and a free-floating small/medium size ice floe based on the boundary element method (BEM). The influences of added mass and hydrodynamic damping are explored for different wave frequencies and headings. Results are presented for a regular waves scenario whereby a tanker progressing at a slow speed is passing by a free-floating ice floe modeled as a round disk. Radiation and diffraction potentials of the interacting floating bodies are linearly superimposed to reflect the influence of hydromechanical coupling on responses. Parametric analysis of response amplitude operators (RAOs) indicates that the cross-coupling terms of added mass and hydrodynamic damping are of the same order of magnitude as those of the ice floe but smaller by one or two orders of magnitude than those of the ship. It is concluded that hydrodynamic interactions primarily influence the motions of the ice floe and are significant attributes in terms of suitably idealizing ship–ice system dynamics.

Cost–Benefit Analysis of a Trans-Arctic Alternative Route to the Suez Canal: A Method Based on High-Fidelity Ship Performance, Weather, and Ice Forecast Models

Climate change in recent years has produced viable shipping routes in the Arctic. However, critical uncertainties related to maritime operations in the Arctic make it difficult to predict ship speeds in ice and, thus, the voyage time and fuel costs. Cost–benefit analysis of alternative Arctic routes based on accurate environmental condition modeling is required. In this context, this paper presents a holistic approach that considers the major voyage-related costs of a trans-Arctic route as an alternative to the conventional routes via the Suez Canal Route (SCR) for existing merchant ships. This tool is based on high-fidelity models of ship performance, metocean forecasting, and a voyage optimization algorithm. Case studies are performed based on a general cargo vessel in operation to quantify realistic expenses inclusive of all the major operational, fuel, and voyage costs of the specific voyages. A comparison is made between the total costs of the trans-Arctic route and SCR for different seasons, which proves the economic feasibility of the trans-Arctic route. Overall, this work can provide valuable insights to help policymakers as well as shipbuilders, owners, and operators to assess the potential cost-effectiveness and sustainability of future Arctic shipping, thereby better developing future strategies.

Sensor Data Quality in Ships: A Time Series Forecasting Approach to Compensate for Missing Data and Drift in Measurements of Speed through Water Sensors

In this paper, four machine learning algorithms are examined regarding their effectiveness in dealing with a complete lack of sensor drift values for a crucial parameter for ship performance evaluation, such as a ship’s speed through water (STW). A basic Linear Regression algorithm, a more sophisticated ensemble model (Random Forest) and two modern Recurrent Neural Networks i.e., Long Short-Term Memory (LSTM) and Neural Basis Expansion Analysis for Time Series (N-Beats) are evaluated. A computational algorithm written in python language with the use of the Darts library was developed for this scope. The results regarding the selected parameter (STW) are provided on a real- or near-to-real-time basis. The algorithms were able to estimate the speed through water in a progressive manner, with no initial values needed, making it possible to replace the complete missingness of the label data. A physical model developed with the simulation platform of Siemens Simcenter Amesim is used to calculate the ship STW under the real operating conditions of a banker ship type during a period of six months. These theoretically obtained values are used as reference values (“ground-truth” values) to evaluate the performance of each of the four machine learning algorithms examined.

Research on propeller bearing force of a four-screw ship in oblique flow

The present study conducted numerical simulations to investigate the influence of oblique flow on the bearing force performance of a four-screw ship, specifically analyzing the wake field and self-propulsion performance. The characteristics of the wake field and bearing force were compared and analyzed in detail under different drift angles (β=0°, ±10°, and ±20°). The findings suggest that the outside propeller wake field is more significantly impacted by a positive drift angle, whereas the effect is reversed for negative drift angles. Both the inside and outside propellers exhibited an increase in propeller axial average loads with an increase in drift angle. The drift angles were found to shift the location of the peak and trough of the single blade unsteady load due to the relative direction of propeller rotation and lateral incoming flow. Propeller loads with drift angles were observed to be larger than those under straight ahead conditions, with the amplitudes of the inside propeller at negative angles being greater than those at positive angles, likely due to the intense bilge vortex. Notably, the outside propeller demonstrated maximum amplitudes of axial loads at a β = 10° condition, while the minimum was observed at a β = −10° condition.

Assessing Ships’ Environmental Performance Using Machine Learning

Environmental performance of ships is a critical factor in the shipping industry due to evolving climate change and the respective regulations imposed by authorities all over the world. As shipping moves towards digitization, a large amount of ships’ environmental performance-related data, collected during ships’ voyages, provide opportunities to develop and enhance data-driven performance models by using different machine learning algorithms. This paper introduces new indices of ships’ environmental performance using machine learning techniques. The new indices are produced by combining clustering algorithms as well as principal component analysis. Based on the analysis of the data (14 variables with operational and design characteristics), the ships are divided into four clusters based on the new suggested indices. These clusters categorize the ships according to their physical dimensions, operating region, and operational environmental efficiency, offering insight into the distinctive traits of each cluster.

An Efficient Feature Augmentation and LSTM-Based Method to Predict Maritime Traffic Conditions

The recent emergence of futuristic ships is the result of advances in information and communication technology, big data, and artificial intelligence. They are generally autonomous, which has the potential to significantly improve safety and drastically reduce operating costs. However, the commercialization of Maritime Autonomous Surface Ships requires the development of appropriate technologies, including intelligent navigation systems, which involves the identification of the current maritime traffic conditions and the prediction of future maritime traffic conditions. This study aims to develop an algorithm that predicts future maritime traffic conditions using historical data, with the goal of enhancing the performance of autonomous ships. Using several datasets, we trained and validated an artificial intelligence model using long short-term memory and evaluated the performance by considering several features such as the maritime traffic volume, maritime traffic congestion fluctuation range, fluctuation rate, etc. The algorithm was able to identify features for predicting maritime traffic conditions. The obtained results indicated that the highest performance of the model with a valid loss of 0.0835 was observed under the scenario with all trends and predictions. The maximum values for 3, 6, 12, and 24 days and the congestion of the gate lines around the analysis point showed a significant effect on performance. The results of this study can be used to improve the performance of situation recognition systems in autonomous ships and can be applied to maritime traffic condition recognition technology for coastal ships that navigate more complex sea routes compared to ships navigating the ocean.

Digital transformation for cold chain management in freight forwarding industry

During the pandemic, the attention and demand for cold chain increased owing to considerable use of low-temperature logistics in transporting perishable goods and vaccines. To ensure the shipping performance for reduced damage, logistics companies are required to track continually and repetitively the status of shipments daily. However, typing various air waybills for searching the shipping status is a cause of frequent errors. Also, tracking the shipping status is labor-intensive, resource intensive, inefficient and repetitive. Moreover, repetitive tasks result in low employee satisfaction. Therefore, robotic process automation (RPA) applications have gained the attention of practitioners in the cold chain logistics industry. This study contributes to (i) determining possible areas requiring automation through the workflow study on cold chain logistics and (ii) streamlining the operation by the develop a robotic process automation bots. A case study tested and evaluated the performance of two unattended RPA bots applied in a freight forwarder company to check shipment status and temperature conditions. The results determined that implementing RPA in the workflow reduces significant data processing time. With the implementation of proposed RPA bots, the company can better comprehend its shipping performance of logistics and can get an immediate notification from RPA bots when an abnormal situation occurs with regard to a shipment.

Experimental and numerical investigation on self-propulsion performance of polar merchant ship in brash ice channel

Experimental and numerical investigation on self-propulsion performance of polar merchant ship in brash ice channel

Analyis of aerodynamic performance of passenger ship with different frontal accommodations using CFD

Research on aerodynamic performance and reduced wind drag acting on hull and large windward areas of high superstructures, such as passenger ships, container ships, roll on - roll off car ferries, and other ships, remains essential marine transportation. In this study, the wind drag acting on a passenger ship's above water hull was computed using ANSYS-Fluent, a commercial Computational Fluid Dynamics (CFD) code. Using CFD, the wind drag components, friction viscous wind drag, and pressure viscous wind drag acting on the hull of the original passenger ship were investigated. Based on the pressure and velocity distributions around the hull, several new hull forms with different frontal accommodation shapes have been proposed to reduce wind drag and improve the aerodynamic performances of the ship. By comparing the CFD results, a new above water surface hull with reduced wind drag was indentified in this study.

Nonlinear URANS model for path-following control problem towards autonomous marine navigation under wave conditions

An accurate prediction of the performance of maritime autonomous surface ships (MASS) to follow a predefined path in waves is of critical importance for ensuring safe autonomous marine navigation. Traditional methods for the study of path-following problems are based on simplified mathematical ship models and are incapable of precisely resolving the complicated interactions between the hull, propeller, rudder, and incident waves under path-following control. In the present study, a CFD-based dynamic model for path-following problems is developed for autonomous marine navigation by means of a fully nonlinear unsteady Reynolds-Averaged Navier-Stokes (RANS) solver combined with the Line-of-Sight (LOS) guidance law. Fortunately, an unsteady RANS solver is capable of incorporating viscous and turbulent effects and the free surface resolution critical to path-following problems, allowing a better prediction of a ship's path-following performance in waves. To obtain practical insight into the performance of the ship executing path-following control for autonomous navigation in waves, a comprehensive analysis of path-following tasks in waves covering the whole range of important wave directions and wave heights was carried out in this study. The numerical results demonstrated that when the ship performed the path-following manoeuvre under the beam and quartering seas, the greatest oscillatory deviation from the predefined path was observed due to the asymmetric pressure distribution on the ship hull caused by the incident waves. It was also confirmed that wave heights strongly affected the trajectories experienced by the ship performing the path-following task in the beam and oblique seas; the deviation from the predefined path was found to increase with the increase in the wave height. As high-performance computational resources become increasingly available, the proposed CFD method will provide an accurate and efficient way to predict the performance of autonomous surface ships performing path-following tasks in waves, providing a valuable contribution to enhancing the safety of autonomous marine navigation.

An Improved Method for Ship Target Detection Based on YOLOv4

The resolution of remote sensing images has increased with the maturation of satellite technology. Ship detection technology based on remote sensing images makes it possible to monitor a large range and far sea area, which can greatly enrich the monitoring means of maritime departments. In this paper, we conducted research on small target detection and resistance to complex background interference. First, a ship dataset with four types of targets (aircraft carriers, warships, merchant ships and submarines) is constructed, and experiments are conducted on the dataset using the object detection algorithm YOLOv4. The Kmeans++ clustering algorithm is used for a priori frame selection, and the migration learning method is used to enhance the detection effect of the YOLOv4. Second, the model is improved to address the problems of missed detection of small ships and difficulty in resisting background interference: the RFB_s (Receptive Field Block) with dilated convolution is introduced instead of the SPP (Spatial Pyramid Pooling) to enlarge the receptive field and improve the detection of small targets; the attention mechanism CBAM (Convolutional Block Attention Module) is added to adjust the weights of different features to highlight salient features useful for ship detection task, which improve the detection performance of small ships and improve the model’s ability to resist complex background. Compared to YOLOv4, our proposed model achieved a large improvement in mAP (mean Average Precision) from 77.66% to 91.40%.

Towed-body system dynamics and interaction

With increasing motivation to reduce environmental impact, there is a push towards less installed power in ships. While calculating the performance of ships at a steady design speed is relatively straightforward, understanding more realistic ‘off-design’ conditions are more demanding. Fishing vessels that by nature operate at a range of speeds and with different load conditions, present unique problems that are as yet not well investigated. In particular, the effect of trawling and/or retrieving a heavy tow, on overall resistance is not well studied. The aim of this paper is to study the effect of a towed object, in various condition, on a fishing vessel resistance. In particular, the study investigates the change in the vessel's resistance, rather that the additional load presented by the towed object; though interaction with the Kelvin wave and towed object is also investigated. The objective is to understand and provide guidance on best practice with respect to tow length.

A Techno-Economic Analysis of a Cargo Ship Using Flettner Rotors

In the last twenty years, the global shipping transport demand has strongly increased (around 4% per year since the 1990s), together with the request for new green propulsion technologies to break down carbon emissions and face the costs deriving from the usage of conventional diesel fuels. Flettner rotors (hereafter: FRs) have been identified by several researchers as a promising solution to exploit wind energy on commercial ships, reducing fuel consumption. The present work presents a six-degree-of-freedom (6DOF) ship performance model set up to evaluate the best way of using a pair of Flettner rotors. The study analyses the performance of this propulsion system in consideration of weather and sea conditions, evaluating the related reduction in fuel consumption. A discussion about the economic and environmental advantages of the usage of FRs is provided, considering the costs linked to their installation and the new emission restrictions. Relevant results have been obtained for different routes, speed ranges and rotor dimensions while investigating the best Flettner rotor arrangement to minimise both the emissions and the installation cost payback period.

Influences of Gap Flow on Air Resistance Acting on a Large Container Ship

In terms of speed lost and fuel consumed, wind loads are considered one of the main factors for large ship design, especially for container ships. Alongside water resistance, air resistance in strong wind conditions has a significant impact on the fuel efficiency and performance of container ships with large box-type bodies. This paper reports the effects of wind loads acting on a 20,000 TEU container ship carrying large numbers of deck containers using a commercial CFD software program (ANSYS Fluent V14.5 with RANS equation). A 1/255.3 scale model was used in this study to reveal the air resistance on the container ship configuration. The aerodynamic formations of the complex vortices, pressure, velocity contours, and streamlines, as well as the air forces acting on the container ship, are presented and discussed. The pressure distributions show that the gap air flows increase the stagnation pressure at the face side and decrease the pressure on the backside of each container gap through separate eddies. The difference in pressures created in the gaps contribute to the air resistance acting on the ship. It is confirmed that the use of side covers of deck containers to close the gap flows between container blocks can significantly reduce the air resistance for wind directions in the range of 30 to 60 degrees.

The method of navigation performance optimization analysis for high speed monohull ships

This paper is based on the drag resistance test data of the high-speed monohull model, a mathematical model for comprehensive optimization of the navigation performance of a high-speed monohull taking into account the rapidity, maneuverability, seakeeping and static performance of the ship is constructed. The optimization calculation software based on particle swarm, standard genetic algorithm and growth mechanism genetic algorithm is designed and written. Taking a high-speed monolithic sea-going ship with a displacement of 1500 tons and a large inclination-measuring single propeller as the object of discussion, the comparison of optimization methods, the comprehensive navigation performance of different ship types and the sensitivity analysis of design variables are carried out respectively. It provides a practical approach and an effective and practical scientific method for analysis and evaluation of how to maintain the comprehensive optimal navigation performance of high-speed monohull ships. At the same time, it provides a way to quickly evaluate the comprehensive performance of similar high-speed monolithic ships in the preliminary design stage, and can also obtain the model diagram with the best comprehensive performance through this software or method, which is useful for shortening the preliminary design cycle of the ship and improving the design quality of the ship. It has important reference value.