长江城陵矶—武汉河段航道最大稳定航深研究*

为探明城陵矶—武汉河段的航道水深资源，根据每一水道的河相关系参数对研究河段进行区段划分，并采用稳定航深估算法对不同区段的航道最大稳定航深进行计算，进而确定研究河段的航道最大水深。结果表明：研究河段依据水道河相关系参数变化规律，可自上游至下游分为仙峰水道—新堤水道、石头关水道—簰洲水道、水洪口水道—白沙洲水道区段；这3个区段在98%设计通航保证率流量、航宽200 m下的航道最大稳定水深自上而下分别为6.133、11.268和6.433 m，故城陵矶—武汉河段在200 m规划航宽下基于自然禀赋的最大稳定航深为6.1 m。     

Wave spectrum estimation conditioned on machine learning-based output using the wave buoy analogy

In this work, a hybrid approach for wave spectrum estimation is proposed. Fundamentally, the approach is based on the wave buoy analogy, processing ship response measurements, via a framework combining machine learning and a physics-based method dependent on available transfer functions. Specifically, a non-parametric (Bayesian) estimate is obtained of the directional wave spectrum conditioned on integral wave parameters established by a convolutional neural network. The developed method is assessed in a case study considering about two years of data obtained from an in-service container ship. The method produces good results, significantly improved when compared to the initial estimate made without constraints.     

Evaluation of RAOs of a semi-submersible platform using field measurements: A full-scale model in Caspian sea environmental conditions

The present research investigates the motion response of a semi-submersible platform using measured field data. The Iran-Amirkabir semi-submersible platform (SSP) was considered as full-scale model in operation conditions. First, 14 accelerometer sensors were installed on the platform's hull, and measurements were made in 5 different scenarios in the Caspian Sea environmental conditions. Then, the Response Amplitude Operators (RAOs) for six degrees of motion were extracted using measured accelerator data. The Surge, Sway, and Heave RAOs processed by the Kalman estimation filter, Pitch, Roll, and Yaw RAOs were calculated from the Sensor Array method. Moreover, the boundary element method in ANSYS/AQWA software for the Iran-Amirkabir semi-submersible model was developed, and the RAO results were validated against the extracted field measurements. The obtained results from the Sensor Array method and the Kalman estimation filter are compared with the numerical simulations, which show Root Mean Square Errors of less than 3% and 4%, respectively for rotational and translational movements. The Mean Square Errors between both methods were also close to zero. Therefore, the proposed methods predicted activities of the studied SSP with relatively good accuracy by field data collected in the Caspian Sea.     

饱和潜水系统试验气体估算方法

分析饱和潜水系统气体试验阶段氦气估算的重要性和饱和潜水气体试验的相关内容。根据试验内容和要求,对饱和潜水系统试验阶段氦气用气量公式计算进行总结和实船示例,明确试验氦气的估算方法和估值大小,并进一步探讨优化试验方案的可行性以减少试验气体的方案选择。研究内容可作为类似饱和潜水船舶建造过程中的重要参考。     

Stochastic wave spectra estimation (SWSE) based on response surface methodology considering uncertainty in transfer functions of a ship

In this paper, a new wave spectra estimation method is proposed in which the frequency domain wave estimation method (FDWE) is extended into a probabilistic analytical framework in order to estimate the encountered sea states involving uncertainty in transfer functions of a ship. The proposed method, named the Stochastic Wave Spectra Estimation (SWSE), makes use of an Hermite polynomial chaos expansion (PCE) to represent the uncertainty in the transfer functions and the response surfaces. The method involves a mathematical formulation where an extension of the deterministic FDWE concept to the space of random variables is made. The proposed method can accurately and easily estimate the encountered wave spectra based on ship response measurements accounting for uncertainty in the transfer functions. In this paper, numerical and experimental investigations of the proposed SWSE are made, where the uncertainties in the transfer functions of heave and pitch motions of a containership are taken into account. The validity of the SWSE is demonstrated by comparison to results of uncertainty analyses through the Monte-Carlo simulations (MCS).