High Sea States Research Articles

Nonlinear analysis of hydrodynamics of a shallow-draft floating wind turbine

AbstractThis study investigates numerically the dynamic responses of the T-Omega Wind novel concept of Floating Offshore Wind Turbine. The turbine is light-weight, has a shallow-draft and a relatively high centre of gravity that allows it to glide over harsh marine environments. The turbine responses are studied under regular wave excitation, considering most probable ranges of discrete sea wave heights and periods representative of real ocean conditions. A multibody virtual model is developed, simplified to a rigid 6 DOF system and experimentally validated in the state-of-art Marine Simulator to define the types of dynamical responses for both “Low” and “High” Sea States. The dynamics of coupled heave and pitch DOFs are evaluated with time histories, phase-plane portraits, Poincaré sections and FFT analyses to conclude that period-1 stable solutions exist for all studied cases of “Low Sea States”, whereas period-2, period-3 and period-4 periodic responses are identified for short wave periods of excitation under “High Sea States” conditions. Simulation results show that regions where period-1 responses exist are highly sensitive to wave height and can widen as the wave amplitude reduces. Finally, the turbines’ nonlinearities generated by the floats’ geometry are observed in this dynamical system, which are identified to be related to variation in float waterplane area and particularly observable for “High Sea States”.

Maritime ISAR detection and tracking algorithm for multiple maneuvering extended vessels in heavy-tailed clutter using SK-MM-Sub-RMM-MB-TBD filter

Multiple extended objects tracking (EOT) tasks play an important role in computer vision and engineering applications of artificial intelligence. In particular, nonlinear marine object imaging and tracking has received an increasing amount of attention due to its enormous application potential in the field of marine engineering, Autonomous Underwater Vehicles, and Remotely Operated Vehicles. Under high sea state, ship-EOTs perform complex maneuvering movements due to strong disturbances such as sea winds and sea waves. In this paper, we exploit emergent maneuvering EOTs (M-EOTs) methodologies in heavy-tailed clutter. We propose a M-EOT procedure in real-time scenario based on the popular multi-Bernoulli (MB)-TBD filter in maritime inverse synthetic aperture radar (ISAR) systems, and in particular, we describe the extended ship target state through the random matrices model (RMM). In RMM, scatter centers are distributed symmetrically around the M-EOT's centroid. However, in ship M-EOT scenario, the distribution over the whole object is not symmetrical, but distributed and skewed in some portions while a target maneuvers. To solve this problem, a novel robustness observation model is represented by using skewed (SK) non-symmetrically normal distribution and multiple model (MM) MB-TBD with more than one ellipse. Simulation and experimental results illustrate that the proposed SK-MM-Sub-RMM-MB-TBD filter outperforms the existing filters for M-EOTs.

Comparative evaluation of floating OWC and BBDB wave energy converters by regular and irregular waves using numerical approach

ABSTRACT Point absorber wave energy converters (WECs) need to be predicted in order to estimate their durability in high sea states. Although little is known about hydrodynamics and there are few data available. Models of the wave conditions have been developed at the laboratory size using smooth particle hydrodynamics. To investigate how focused waves interact with a point absorber WEC, fixed OWC and BBDB type WEC are coupled. A validation research is evaluated by taking into account the wave amplitude and frequency. The hydrodynamic force and the motion response of the point absorber WEC have been measured throughout time. According to the numerical results, the hybrid configuration with the fixed OWC and BBDB has a significant impact on the motion response and hydrodynamic force. It is demonstrated that the position of hybrid OWCs affects the hydrodynamic force and intense motion response significantly.

A two-module bias-correction model for sea wave hindcasting based on the long-short term memory neural network

The lack of observations and biases of winds and bathymetry in the coastal region result in significant biases in the numerical modeling of sea waves. In this study, we establish a two-module bias correction model based on the Long-Short Term Memory neural network (denoted as TM-BCM) which accounts for the data imbalance by separately training the neural network for low and high sea states. The in-situ observations in 2020 and 2021 are used to model training and testing, respectively. The test results show that TM-BCM significantly reduces the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of modeled sea waves by 52.9% and 65.5%, respectively. In addition, TM-BCM outperforms the single-module model (denoted as SM-BCM) that does not account for the imbalance of training data. Our results highlight the great value of deep learning in correcting biases for numerical models and the importance of accounting for data imbalance in training the neural network.

Calibration of CFOSAT Off‐Nadir SWIM SWH Product Based on CNN‐LSTM Model

AbstractHigh‐precision observation of significant wave height (SWH) is crucial for marine research. The Surface Waves Investigation and Monitoring (SWIM) aboard the China France Oceanography Satellite (CFOSAT) provides the ocean wave spectrum that allows for the calculation of the off‐nadir SWH parameters, but there exists a certain bias with the in‐situ SWH values. To improve the accuracy of the SWH calculation bias from the off‐nadir 6°, 8°, 10° wave spectra and the whole combined spectrum, this paper establishes a spatio‐temporal hybrid model that combines convolutional neural network (CNN) and long short‐term memory network (LSTM). Additionally, to further correct bias exhibited under high sea state, we introduce a bias correction module based on deep neural network (DNN) to adjust the SWIM off‐nadir SWH greater than 4 m. The experimental results demonstrate a significant enhancement in the accuracy of corrected SWIM off‐nadir SWH, and the best calibration result is 10° with 0.267 m root mean square error (RMSE), and 0.979 correlation coefficient (R) compared with the ERA5 value. We conducted a comprehensive study and analysis on the performance of the proposed model under different wave heights, extreme sea states, and wind and swell regions. Meanwhile, the buoy and altimeters are leveraged to render further evaluation the RMSE of the corrected SWH is less than 0.5 m.

New Technique to develop Intelligent High reliable & Efficient Unmanned Power Generation Modular

Primary aim of this research project is to develop Modular Generator Total Power Output: 1 MW or greater, integrated with High density diesel (NATO F76) generator. This modular comprises of Generators, Fuel Cells (MTBF), Gas Turbine Generators. Note that novelty will be sought on how to configure installation of multiple power units to allow for easy access for maintenance, quick removal and replacement as well as optimize operating life via controls. This proposed power modular will Operate in a marine environment condition such as salt air ingestion, ships motion in high sea states, shock, vibration. Note that novelty will be pursued on how to best optimize design to combine multiple power unit connections to a single ship interface.[1] Key words. Novelty, Corrective Maintenance and Preventive maintenance and Intelligent module.

Intelligent prediction of wave loads based on multi-source data-driven methods

ABSTRACT High-fidelity wave-load tests is pivotal in the design and development of modern ship structures. Nonetheless, the prohibitive cost of conducting such tests limits their applicability. A wave-load data fusion method was implemented using the model test data from a typical displacement-type ship to generalise the small sample test, and a multi-source data characterisation and model parameter optimisation method were established to achieve efficient wave-load (wave frequency and slamming superposition) prediction. Using multi-source data, a multi-fidelity wave-load prediction (MFWLP) model was constructed by combining numerical computation, regular wave tests (RWT), and irregular wave test (IWT) data based on transfer learning with a secondary correction wave load prediction under irregular wave conditions. The model was effectively employed in a ship wave-load engineering case. This study reveals that the adopted MFWLP model demonstrates adequate extrapolation and prediction capabilities, even with limited high-fidelity test samples. The discrepancy between the nonlinear wave load prediction and model test was found to be within 15%. Therefore, the proposed method can serve as a foundation for rapidly assessing ship wave loads across various sea conditions, especially under high sea states.

A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation

AbstractLinear frequency modulation (LFM) signal is a common radar signal in modern electronic warfare, and smeared spectrum (SMSP) can generate multiple false targets, causing jamming to radar detection. The authors propose a chirplet‐based masking algorithm that can solve the problem of SMSP jamming suppression and address a more complex problem: the separation of jamming signal and multiple LFM signals from intercepted mixed signal. First, the authors obtain matched chirp rates of the source signals through the changing tendency of the Rényi entropy. Then, the ridge of each source signal is extracted from the high‐resolution chirplet transform result using an image processing‐based algorithm. Finally, the jamming and LFM signals are accurately reconstructed through the time‐frequency mask to achieve separation. Even in the extreme case where multiple source signals with close chirp rates are overlapped, the proposed slope‐matching ridge extraction method and iterative update reconstruction method can still achieve commendable signal separation effects. Extensive experimental results demonstrate that the proposed algorithm performs well under extreme conditions of low signal‐to‐noise ratio, high jamming‐to‐signal ratio, and high sea state.

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

SummaryData‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches. Numerical results in two case studies involving the course‐keeping of a naval destroyer in a high sea state using simulation data at model scale are presented. The proposed methods reveal successful in predicting ship motions both in short‐term and medium‐term perspectives with accuracy and reduced computational effort, thus enabling further advances in the identification, control, and optimization of ships operating in waves.

Pre-Processing of Simulated Synthetic Aperture Radar Image Scenes Using Polarimetric Enhancement for Improved Ship Wake Detection

Ship wake detection using synthetic aperture radar (SAR) imagery provides a way to obtain small marine ship information, but it often becomes unavailable and unreliable during a high sea state. Polarimetric information provides a potential way to solve this problem, which can enhance the ship target as well as the ship wake features. However, three challenges still exist in ship wake detection in polarimetric SAR imagery: the unwanted influences of bright and singular points on ship wake detection, the lack of performance analysis of wake detection by new-type polarimetric enhancement methods, and the difficulty of using the assessment criteria for ship wake detection. In this paper, we try to solve the above problems. Firstly, fully polarized SAR imagery of both ship turbulent and Kelvin wake is simulated based on the two-scale composite model, and the Polarimetric Whitening Filter (PWF) and Polarimetric Detection Optimization Filter (PDOF) are applied to the simulated fully polarized SAR imagery to enhance the ship wake features. Secondly, since the bright and singular points resulting from the ship echoes and the polarimetric enhancement methods may lead to misdetections, a logarithm process and z-score normalization pre-processing has been applied to the images. Then, a new assessment criterion for wake detection performance has been formulated, and the probability of missing detections (PMDs) and the probability of false alarms (PFAs) have been defined for two different requirements. And a Radon transform-based ship wake detection method for both ship turbulence and Kelvin wake has been carried out in horizontal–horizontal (HH), vertical–vertical (VV), horizontal–vertical (HV), PWF and PDOF SAR imagery. Finally, an analysis of the wake detection performance has been carried out. The PWF and PDOF can improve the wake detection performance by an average of nearly 50 percent compared with the HH and VV.

The Application of Risk Based-Design (RBD) Methodology For LNG Carrier Under Varied Sea State

The energy transition issue is being pursued following the outcomes of the 22nd Summit by the G-20 group. The use of Liquified Natural Gas (LNG) fuel has emerged as one of the solutions in addressing the energy transition challenge. In line with the issuance of the Ministry of Energy and Mineral Resources Decision in January 2022, the Indonesian Government will increase the utilization of natural gas in the form of LNG for the electricity generation sector. LNG fuel is considered to possess numerous advantages and is more environmentally friendly. The distribution of LNG fuel is often carried out by tanker ships equipped with cryogenic tanks called LNG carrier. However, challenges arise when ships operate in waters which has high sea state condition, where the vessel faces the risk of accidents such as sloshing, increased motion response, stability disruptions, and other. Therefore, this paper provide a comprehensive risk analysis to minimize the existing accident risks caused by varied sea state condition using Risk-Based Design (RBD). RBD is a structured and systematic method to ensure safety levels and cost-effectiveness and utilizing risk analysis.

Multi-fidelity data-adaptive autonomous seakeeping

Safe operation of a ship in heavy weather and high sea states requires accounting for the risk of extreme ship motion responses in stochastic ocean waves. Excessive ship motions can lead to hazardous and unsafe conditions such as pure loss of stability, surf-riding and broaching. Mitigation of these risks can be performed through selection of ship speeds and headings for a given seaway, and avoiding conditions likely to lead to severe motions. To address this challenge, a robust, fast, data-adaptive model is a prospective enabling capability for onboard autonomous seakeeping. In this study, data-adaptive Long Short-Term Memory (LSTM) neural networks are investigated as part of a multi-fidelity approach incorporating Large Amplitude Program (LAMP), and a reduced-order model known as SimpleCode. An assessment of this multi-fidelity approach focuses on prediction of ship motion responses in waves. LSTM networks are trained and tested with LAMP simulations as a target, and SimpleCode simulations and wave time-series as inputs. LSTM networks are shown to improve the fidelity of SimpleCode seakeeping predictions relative to LAMP, while retaining the computational efficiency of a reduced-order model. Potential areas of application include unmanned and reduced-crew vessels, operator guidance for manned systems, and weather-informed ship route planning.

Polarization-Enhancement Effects for the Retrieval of Significant Wave Heights from Gaofen-3 SAR Wave Mode Data

In order to investigate the impact of utilizing multiple pieces of polarization information on the performance of significant wave height (SWH) estimation from Gaofen-3 SAR data, the extreme gradient boosting (XGBoost) models were developed, validated, and compared across 9 single-polarizations and 39 combined-polarizations based on the collocated datasets of Gaofen-3 SAR wave mode imagettes matched with SWH data from ERA5 reanalysis as well as independent SWH observations from buoys and altimeters. The results show that the performance of our SWH inversion models varies across the nine different single-polarizations. The co-polarizations (HH, VV, and RL) and hybrid-polarizations (45° linear, RH, and RV) generally exhibit superior performance compared to the cross-polarizations (HV, VH, and RR) at low to moderate sea states, while the cross-polarizations are more advantageous for high SWH estimation. The combined use of multiple pieces of polarization information does not always improve the model performance in retrieving SWH from Gaofen-3 SAR. Only the polarization combinations that incorporate cross-polarization information have the potential to enhance the model performance. In these cases, the performance of our models consistently improves with the incorporation of additional polarization information; however, this improvement diminishes gradually with each subsequent polarization and may eventually reach a saturation point. The optimal estimation of SWH is achieved with the polarization combination of HV + VH + RR + RH + RV + 45° linear, which shows consistently lower RMSEs compared to ERA5 SWH (0.295 m), buoy SWH (0.273 m), Cryosat-2 SWH (0.109 m), Jason-3 SWH (0.414 m), and SARAL SWH (0.286 m). Nevertheless, it still exhibits a slight overestimation at low sea states and a slight underestimation at high sea states. The inadequate distribution of data may serve as a potential explanation for this.

Numerical study on damaged ship rolling and capsizing in irregular beam waves during quasi-steady flooding

To study roll dynamics and capsizing occurrence of damaged ship in irregular beam waves, computational fluid dynamics is used to simulate damaged ship motions at rough sea to high sea states. The velocity-inlet boundary and momentum source are combined for wave generation. A modified formula is adopted to calculate turbulent viscosity to prevent unphysical decay of wave. The lateral drift restrained model is integrated with a combined dynamic mesh strategy to handle the ship's sway, heave and roll motions. Benchmarking study of irregular wave generation and roll response of damaged ship in regular waves is performed. Based on the simulations of motions of intact and damaged ships in irregular waves, the effects of cross flooding and damage orientation on the roll response of ship are discussed. For symmetrical flooding, the roll behaviour of ship is insensitive to the damage orientation. Due to the increase of roll damping, the roll response of damaged ship is smaller than that of intact ship. For asymmetric flooding, the ship is liable to roll toward the damaged side with a large angle. The probability of capsizing of ship caused by waveward damage is high at high sea state.

Integrated hydrodynamic-electrical hardware model for wave energy conversion with M4 ocean demonstrator

Wave energy is well known to be a renewable energy resource with worldwide capacity similar to wind. However there is to date negligible generation of electricity from wave. Many devices have been proposed without convergence on a particular design as there has been for wind. We are here concerned with a multi-float attenuator type M4 which has been widely tested in wave basins and modelled by linear diffraction/radiation methods. Potential of MW capacity for grid supply has been demonstrated at many sites. To advance development, small scale ocean tests are being planned for Albany, Western Australia where summer wind-wave conditions in King George Sound will excite the device giving principal absorption with mean periods in the range 2 - 3.5 seconds (or peak periods of 2.5 – 4.5 s). The aim is to learn about most aspects of ocean deployment from wave climate and environment planning to realistic electricity generation, albeit at kW scale. In this paper the emphasis is on the specification of electrical drive train (power take off) which requires the input of torque time variation for the wave conditions on the site, as described by a scatter diagram. First a linear time domain wave multi-float model (Fortran) is set up for the particular 121 configuration, shown in Fig. 1. Such models have been used and validated against wave basin tests for similar configurations. This is then converted into state-space form in Matlab. This is highly efficient and suited for real time PTO control in Simulink. Fig. 2 shows the main components of the electrical drive train, including the gearbox, generator, super-capacitors, power electronic converters and resistor bank to dissipate electricity. Bespoke Matlab models will be run for the wave conditions in the scatter diagram to check that components are suitably rated for normal sea-states, and are safely protected through electrical power-limiting control in high sea states. Simulated electrical generator results will be shown for typical sea states, with some power-limiting. Instrumentation will be specified. Only uni-directional waves are considered in this paper. Ultimately the efficacy of the system will be demonstrated in ocean conditions.

A probabilistic framework for fatigue damage of lift based wave energy converters

Wave cycloidal rotors are lift based wave energy devices that have shown great potential to harness the energy of the waves through the use of submerged hydrofoils. Although the lift force of the foils can be controlled passively or actively to maximise power extraction, the foils of the rotor are subject to variable loading which can expose these components to premature mechanical failure. Therefore, it is important to develop novel fatigue analysis tools that help predicting the lifetime of this type of lift based devices. In this paper, we test the hypothesis that when cyclorotor operates at constant rotational velocity in irregular waves, the fatigue damage of the hydrofoil stress hot spot can be computed through a probabilistic approach. We compare our results to the fatigue damage computed with well established deterministic methods. We find that for both narrow and broad band stress energy spectra, the probabilistic method works well at high probability sea states, when the range of stresses does not exceed the inflection point of a double slope SN curve. This is a promising outlook since it confirms that the fatigue damage of these versatile lift based wave devices can be treated in a similar fashion to the fatigue damage of conventional offshore structures.

A 40 YEAR WAVE CLIMATOLOGY OF SOUTH EAST QUEENSLAND, USING MODELLED AND IN-SITU WAVE OBSERVATIONS

Climate change has the potential to impact weather patterns that drive the Queensland wave climate and increase the intensity of extreme events such as tropical cyclones and east coast lows, due to a widening of the tropics. This will likely result in a changing wave climate, an increase of erosion events and subsequent coastal morphological change throughout the subtropics. Thus, it is important to examine not only the modal wave climate, but also the extreme wave climate. While a number of hind-cast models have been used to assess global wave climates (Perez et al. 2017), there has been an identified lack of regional assessments. Wave climatology assessments for the SEQ region, have consisted of several point specific assessments undertaken predominantly using buoy data, hind-cast data, or visual daily observations. These studies generally agree that tropical cyclone and east coast lows are the dominant source of high energy sea states and beach erosion in SEQ. A 40 year numerical wave hind-cast has been developed using the WaveWatch III (WW3) model version 4.08 (Durrant et al. 2013a, 2013b).

Comparative Performance of Radar, Laser, and Waverider Buoy Measurements of Ocean Waves. Part II: Time-Domain Analysis

Abstract Accurate measurements of ocean waves underpin efficient offshore operations and optimal offshore structure design, helping to ensure the offshore industry can operate both safely and economically. Popular instruments used by the offshore industry are the Rosemount WaveRadar (Radar) and the Waverider Buoy. The Optech Laser has been used at some locations for specific studies. Recent reports indicate systematic differences of order 10% among the wave measurements made by these instruments. This paper examines the relative performance of these instruments based upon various time-domain comparisons, including results from a quality control (QC) procedure, capabilities of measuring the wave surface profile (skewness), and crest heights for varying wind sea and swell conditions. The QC check provides good-quality data that can be further investigated with an assurance of error-free data, suggesting that the Waverider produces the best-quality data with the lowest failure rate compared to the Laser and Radar. A significant number of the Waverider surface elevation records have negative skewness, particularly at higher sea states, affecting its crest height measurements, which are lower than those from the Laser and Radar. Additionally, the significant wave height (H1/3) estimates of the Radar are lower than the Laser and Waverider, but its zero-crossing wave periods (TZ), on average, are longer than the Laser and the Waverider. The significant heights (H1/3) of Laser and Waverider are in good agreement for all three datasets, but the Waverider’s zero-crossing wave period (TZ) estimates are significantly longer than the Laser.

Surface wave height distributions and rogue wave probabilities on two-layer fluids

Rogue waves are individual ocean surface waves much larger than the prevailing wave field. In high sea states they can be a danger to marine operations. Rogue waves are well studied for unstratified water. However, on a two-layer fluid the surface wave spectra are modified due to triad interactions with interfacial waves. Such triad interactions are not possible in homogeneous water. We find the modified surface spectrum reduces rogue waves. These findings are relevant for the changing polar oceans where prolonged ice melt is expected to facilitate open water with higher sea states while also creating a surface layer of freshwater overlaying salt water, as in our idealized model calculations.

Comparative Performance of Radar, Laser, and Waverider Buoy Measurements of Ocean Waves. Part I: Frequency Domain Analysis

Abstract Accurate ocean wave measurements are needed for the safe design and operation of offshore facilities, but despite many ocean wave measurements, the accuracy of wave measurement systems remains an ongoing issue. Of paramount importance are measurements during extreme sea states. This paper examines wave measurements made with an Optech Laser (Laser), a Rosemount WaveRadar (Radar), and a Datawell Waverider buoy at North Rankin A (NRA) platform, Australia; Ekofisk, North Sea; and several South China Sea locations. We evaluate the relative performance of these instruments based upon various frequency domain comparisons, including comparisons of their 1D frequency spectra using spectrograms, spectral moments, high-frequency tail slopes, and significant wave heights derived from their wave spectra. A spectral relationship (transfer function) in terms of mean spectral ratio of the instruments is developed, which can be used for spectral calibration. On average, Laser and Waverider spectral estimates agree well at all sea states. However, at low wind speeds, the higher-frequency spectral levels of the Laser are relatively high and noisy compared with the other two instruments. Radar higher-frequency spectral estimates are relatively low compared to the other two instruments, particularly at lower sea states. In addition, the higher-frequency tail slopes of all three instruments vary between f−4 and f−5. However, at higher sea states, the Waverider tail slopes become steeper than f−5. The Radar produces the lowest significant wave heights (Hm0) compared to the Laser and Waverider, but its second-moment period (Tm02) estimates are longer than the Laser and Waverider.