Broaching probability for a ship in irregular stern-quartering waves: theoretical prediction and experimental validation

To avoid stability failure due to the broaching associated with surf riding, the International Maritime Organization (IMO) has begun to develop multilayered intact stability criteria. A theoretical model using deterministic ship dynamics and stochastic wave theory is a candidate for the highest layer of this scheme. To complete the project, experimental validation of the theoretical method for estimating broaching probability in irregular waves is indispensable. We therefore conducted free-running model experiments using a typical twin-propeller and twin-rudder ship in irregular waves. A simulation model of coupled surge–sway–yaw–roll motion was simultaneously refined. The broaching probability calculated by the theoretical method was within the 95 % confidence interval of that obtained from the experimental data. This could be an example of experimental validation of the theoretical method for estimating the broaching probability when a ship meets a wave.     

Short-term prediction of vehicle waiting queue at ferry terminal based on machine learning method

Ferry service plays an important role in several cities with waterfront areas. Transportation authorities often need to forecast volumes of vehicular traffic in queues waiting to board ships at ferry terminals to ensure sufficient capacity and establish schedules that meet demand. Several previous studies have developed models for long-term vehicle queue length prediction at ferry terminals using terminal operation data. Few studies, however, have been undertaken for short-term vehicular queue length prediction. In this study, machine learning methods including the artificial neural network (ANN) and support vector machine (SVM) are applied to predict vehicle waiting queue lengths at ferry terminals. Through time series analysis, the existence of a periodic queue-length pattern is established. Hence, methodologies used in this study take into account periodic features of vehicle queue data at terminals for prediction. To further consider the cyclical characteristics of vehicle queue data at ferry terminals, a prediction approach is proposed to decompose vehicle waiting queue length into two components: a periodic part and a dynamic part. A trigonometric regression function is introduced to capture the periodic component, and the dynamic part is modeled by SVM and ANN models. Moreover, an assembly technique for combining SVM and ANN models is proposed to aggregate multiple prediction models and in turn achieve better results than could be attained from a lone predictive method. The prediction results suggest that for multi-step ahead vehicle queue length prediction at ferry terminals, the ensemble model outperforms the separate prediction models and the hybrid models, especially as prediction step size increases. This research has important practical significance to both traffic service management interests and the travelers in cities along waterfront areas.     

A study on TLP hull sizing by utilizing optimization algorithm

This paper reports a study on hull sizing for tension leg platforms (TLPs) using an optimization model. At the conceptual or basic design stage of an offshore platform project, hull sizing is one of the most important tasks, having a great impact on later stages of the project. Hull sizing is usually done by an engineering team combining several disciplines and taking account of factors including hydrodynamics, global performance, stability, and structure. This makes it difficult and time-consuming to optimize the hull dimensions. In this study, hull sizing was modeled as an optimization problem in which a range of design criteria had to be satisfied and an objective function minimized. Sizing was then performed using optimization algorithms. For each module, the result calculated by our method was compared with that produced by commercial software (DNV Sesam). Our system was tested for conventional TLP design in three specific metocean environments. Finally, our optimized hull shape was compared with an existing TLP, and the difference in hull shape demanded by each environment was analyzed.     

Panama Canal expansion: fuel economy and logistical risk

Since cargo capacity increases faster than fuel consumption, the significantly larger capacity fleets which will accompany expansion of the Panama Canal will introduce additional fuel economies and cost savings. Enabling larger, more fuel-efficient vessels to carry cargo the entire distance from Asia to US east-coast ports allows vessel operators to realize significant and meaningful savings compared with the alternatives of using smaller Panamax vessels for the whole distance, or sending the cargo over the US land bridge by train or truck. Fuel savings are quantified along with the monetary savings based on various assumptions for the price of fuel. These savings are dramatic and will increase directly with the price of crude petroleum. Finally, microeconomic theory is deployed to determine how cost savings will be distributed between shipping customers and vessel operators.     

Modeling of ship maneuvering motion using neural networks

In this paper, Neural Networks (NNs) are used in the modeling of ship maneuvering motion. A nonlinear response model and a linear hydrodynamic model of ship maneuvering motion are also investigated. The maneuverability indices and linear non-dimensional hydrodynamic derivatives in the models are identified by using two-layer feed forward NNs. The stability of parametric estimation is confirmed. Then, the ship maneuvering motion is predicted based on the obtained models. A comparison between the predicted results and the model test results demonstrates the validity of the proposed modeling method.     

An elastic-plastic iceberg material model considering temperature gradient effects and its application to numerical study

To simulate the FPSO-iceberg collision process more accurately, an elastic-plastic iceberg material model considering temperature gradient effects is proposed and applied. The model behaves linearly elastic until it reaches the ‘Tsai-Wu’ yield surfaces, which are a series of concentric elliptical curves of different sizes. Decreasing temperature results in a large yield surface. Failure criteria, based on the influence of accumulated plastic strain and hydrostatic pressure, are built into the model. Based on published experimental data on the relationship between depth and temperature in icebergs, three typical iceberg temperature profiles are proposed. According to these, ice elements located at different depths have different temperatures. The model is incorporated into LS-DYNA using a user-defined subroutine and applied to a simulation of FPSO collisions with different types of iceberg. Simulated area-pressure curves are compared with design codes to validate the iceberg model. The influence of iceberg shape and temperature on the collision process is analyzed. It is indicated that FPSO structural damage not only depends on the relative strength between the iceberg and the structure, but also depends on the local shape of the iceberg.     

Tracking control of underwater vehicle subject to uncertainties using fuzzy inverse desired trajectory compensation technique

Computed-torque controller plus fuzzy inverse desired trajectory compensation technique based on robust adaptive fuzzy observer is proposed to control underwater vehicle subject to uncertainties. A fuzzy inverse desired trajectory compensator is developed as a nonlinear filter at input trajectory level outside the control loop to address the issue of unavailable normalizing factor. A robust adaptive state observer with loose constraint on the position of the uncertainty function is proposed to evaluate the unavailable states. Numerical simulation results of regulation performance demonstrate that the observer solves the problem of strict constraint conditions on position uncertainties. Comparisons of tracking performance between the proposed control method and computed-torque controller are performed. The results confirm that compensation at the input trajectory offers better position tracking performance and easier practical implementation than other fuzzy compensation techniques at joint torque level. The proposed control approach is simulated and its efficiency is validated through the simulation of an underwater vehicle.     

Design of the lines of underwater vehicles based on collaborative optimization

A generalized collaborative optimization (CO) framework is proposed to the optimization design of the lines of an underwater vehicle. The resistance and maneuvering performances are concerned about and taken as the optimization objectives in the optimization framework. The resistance, lateral force and yaw moment are calculated by RANS method. To improve the optimization efficiency, an automatic integration optimization platform is constructed in which a surrogate model is adopted. A SUBOFF model is taken as the verification model. The optimal results demonstrate the validity of the optimization strategy proposed.     

A mathematical model for acceleration phase of aerodynamically alleviated catamarans and minimizing the time needed to reach final speed

Racing catamarans use aerodynamic alleviation concept which in existing extreme ground effect significantly enhances the performance. Beside design measures, controlling strategies may be employed as convenient solutions to improve the performance and address concerns regarding poor stability in these crafts. Being of substantial importance for a racing catamaran to reach the final speed as soon as possible, this study attempts to find the optimal form of changing the drive angle (as control variable) to minimize its acceleration time. In this regard, a mathematical model is developed for forward acceleration phase of these catamarans based on empirical and theoretical methods. Then the formulation and solution algorithm for the time-optimal problem are described according to an indirect method. Results for a representative racing craft have been presented in uncontrolled and controlled conditions. Problem in controlled condition has been solved without and with a predefined constraint regarding stability margin. Optimal controlling of the drive angle without stability constraint during the acceleration results in 40 % reduction in time required to reach the speed of 110 kn and 14 % reduction in resistance at this speed in comparison to the uncontrolled case. Addition of the stability constraint changes optimal solution for drive angle and causes craft trim angle follow a decreasing trend at higher speeds.     

Do China Mainland and SARs Constitute an Optimal Currency Area?Evidence from Nonlinearity and Stationarity Behavior Testing on Real Exchange Rates

In this article, we use the unrestricted two-regime autoregressive threshold model to test both nonlinearity and stationarity of China’s real exchange rate against its Hong Kong and Macau special administrative regions (SARs). Our main finding is that China’s real exchange rate is neither linear nor stationary, indicating that the purchasing power parity does not hold between China Mainland and its two SARs, which implies, to certain extent, the three economies may not meet the condition of constituting an optimal currency area.