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This work includes the description of a novel way to tackle the problem of real time stability monitoring. Instead of taking natural roll frequency as the only variable to estimate the stability level of the vessel, a methodology based on the use of signal-based methods with statistical change detection tools is used for detecting changes in the vessel stability and differentiating between safe and non-safe situations. This methodology also includes a colour coded risk alarm that informs the crew about the current state of the vessel. Moreover, in the proposed work, the behaviour and performance of this method is analysed using roll motion data of a stern trawler generated by a one degree of freedom nonlinear model in irregular beam waves. In addition, the obtained results are compared to those from the application of a Fast Fourier Transform (fft)- based methodology previously developed by the authors. The performance of this new proposal has been good, both regarding the estimation of the vessel natural roll frequency and the change detection schemes, showing a better performance than the fft-based method. However, further analysis is needed to validate these results under more wave conditions and sailing situations.

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Active monitoring of transverse stability in fishing vessels is paramount due to its significant incidence in operational accidents. Access to systems for automatic detection of changes in vessel's stability related parameters would better support the crew during fishing and navigation operations. The paper presents an initial experimental validation of a signalbased transverse stability monitoring system, which consists of an estimator-detector kernel that solely uses measurements of roll motion to identify changes in vessel's metacentric height by estimating the roll natural frequency. Its performance is evaluated based on experimental data from a towing tank scale model test campaign. The proposed transverse stability monitoring system well performs by identifying the potential risks and changes in loading condition.

Typically, slow steaming is adopted to lower ship’s resistance, which in turn reduces exhaust gas emissions due to lower propulsion power demands. Fine tuning of the underlying hydrodynamic models is key to the reliable forecasting of fuel consumption. Accurate knowledge of the vessel’s speedthrough- water (STW) is paramount to estimate the actual resistance of the vessel. The paper presents a feasibility study about the use of sensor fusion methods for real-time estimation of STW based on inertial measurements of ship motions and measurement of sea current. By combining a purely kinematic model together with linear Kalman filtering, the paper addresses the challenge of designing an optimal STW estimator by detailing the fundamental design choices. The proposed STW estimator is verified on simulated data and tested with measured data from an in-service container vessel.

The IMO Weather Criterion has proven to be the governing stability criteria regarding minimum GM for e.g. small ferries and large passenger ships. The formulation of the Weather Criterion is based on some empirical relations derived many years ago for vessels not necessary representative for current new buildings with large superstructures. Thus it seems rea-sonable to investigate the possibility of capsizing in beam sea under the joint action of waves and wind using direct time domain simulations. This has already been done in several studies. Here it is combined with the First Order Reliability Method to define possible combined critical wave and wind scenarios leading to capsize and corresponding probability of capsize. The results for a fictitious vessel are compared with Monte Carlo simulation and good agreement is found at a much lesser computational effort. Finally, the results for a large container vessel and a small ferry will be discussed in the light of the current weather criterion.

Uncertainties related to numerical modelling of parametric roll have been investigated by using a 6-DOFs model with nonlinear damping and roll restoring forces. At first, uncertainty on damping coefficients and its effect on the roll response is evaluated. Secondly, uncertainty due to the “effective (equivalent) wave” concept in calculation of restoring moment is studied. Finally, uncertainty to roll response from different methods of GZ calculation has been checked. It is found that the equivalent wave concept is sufficiently accurate for the purpose of GZ calculation. Two different GZ approximations give a good agreement with direct calculation method if relevant coefficients have been properly found in the fitting.

One method to estimate the wave spectrum onboard ships is to use measured ship responses. In this method, known also as Wave Buoy Analogy, amongst various responses that are available from sensor measurements, a couple of responses (at least three) are usually utilized. Selec-tion of the best combination of ship responses is important. Optimally, this selection should not be implemented manually in onboard applications. Therefore, availability of an automatic response selection procedure would be a great advantage for decision support. In this paper, a local sensitivity analysis is applied to evaluate the importance of individual responses in sea state estimation. The sensitivity factor is defined by calculation of the partial derivatives of wave parameters with respect to the variance of individual responses.

In Europe, the most widely used Christmas tree species, Abies nordmanniana, has a long history of infestation with the adelgid Dreyfusia nordmannianae. Since 2011, the species has furthermore been increasingly damaged by the fungus Neonectria neomacrospora. The objective was to study whether infestations by N. neomacrospora were facilitated by the presence of adelgids in Nordmann fir and to explore the genetic components of this potential interplay. The damage caused by D. nordmannianae and N. neomacrospora in two Nordmann fir clonal seed orchards in Denmark was evaluated in 2014, and an experimental infestation was conducted to test the performance of Nordmann fir somatic embryogenesis-derived trees exposed to N. neomacrospora and D. nordmannianae individually or in combination by setting up an artificial infestation chamber. The genetic correlation between the two diseases was 0.54 at two clonal seed orchards, indicating that the trees susceptible to N. neomacrospora were also susceptible to D. nordmannianae or vice versa. In the experimental test, only trees in the treatment with both D. nordmannianae and N. neomacrospora developed needle loss and dieback symptoms. Thus, both the field evaluations and the experimental test revealed an interplay between D. nordmannianae and N. neomacrospora damage on Nordmann fir trees. Future studies should explore in more detail how D. nordmannianae interacts with N. neomacrospora. Our findings and future studies on this topic could have important implications for suitable breeding programs for Nordmann fir Christmas trees and forest pest management.

The objective of ship motion-based wave spectrum estimation is to provide the distribution of wave energy densities in absolute domain. However, as a ship generally advances relative to the progressing waves, any spectrum estimate inherently dates back to the encounter domain and, consequently, the spectrum estimate must be transformed to absolute domain. In following sea conditions, spectrum transformation from encounter to absolute domain has no unique (mathematical) solution. This article presents an optimisation-based technique to carry out the particular transformation in following sea conditions. The optimisation relies on an object function established using (wave) spectral moments; calculated directly using the estimated encounter-wave spectrum on the one side and by using a parameterised wave spectrum valid in absolute domain on the other side. The simplicity of the transformation technique is a strength in itself as it leads to an insignificant computational effort in the transformation to absolute domain. Equally important, the specific technique proves capable to provide accurate results in the majority of cases, when comprehensive testings with numerically simulated data of following sea conditions are performed. Furthermore, the technique is tested successfully using experimental full-scale sea trials data.

The article introduces a spectral procedure for sea state estimation based on measurements of motion responses of a ship in a short-crested seaway. The procedure relies fundamentally on the wave buoy analogy, but the wave spectrum estimate is obtained in a direct - brute-force - approach, and the procedure is simple in its mathematical formulation. The actual formulation is extending another recent work by including vessel advance speed and short-crested seas. Due to its simplicity, the procedure is computationally efficient, providing wave spectrum estimates in the order of a few seconds, and the estimation procedure will therefore be appealing to applications related to realtime, onboard control and decision support systems for safe and efficient marine operations. The procedure's performance is evaluated by use of numerical simulation of motion measurements, and it is shown that accurate wave spectrum estimates can be obtained for all wave directions in short-crested waves, taking the wave system to be composed by both wind generated sea and swell. Furthermore, the procedure is tested using full-scale motion data obtained from sea trials. Good wave estimations are achieved as compared to corresponding results from a free-floating (classical) wave buoy.

This paper presents a study focused on a newly developed procedure for wave spectrum estimation using wave-induced motion recordings from a ship. The particular procedure stands out from other existing, similar ship motion-based pro-cedures by its computational efficiency and - at the same time- providing accurate estimates of the on-site wave conditions. In the paper, the procedure is applied to full-scale experimental data obtained from dedicated sea trial runs. The results show favorable agreement with corresponding wave spectrum estimates by a directional wave buoy.

This paper presents a novel method for estimating the sea state parameters based on the heave, roll and pitch response of a vessel in dynamic positioning (DP), i.e., without forward speed. The algorithm finds the wave spectrum estimate from the response measurements by directly solving a set of linear equations, and as a result it is computationally efficient. Themain vessel parameters are required as input. Apart from this the method is signal-based, with no assumptions on the wave spectrum shape. Performance of the proposed algorithmis demonstrated on full-scale experimental DP data of a vessel in three different sea states at head, bow, beam, quartering and following sea waves, respectively.

This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine operations (crane lifts, helicopter landings, etc.), as a specic prediction can be used to inform whether it is safe, or not, to carry out the particular operation within the nearest time horizon. The examined prediction procedure relies on observations of the correlation structure of the wave-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input about the exciting wave system, and neither does it rely on o-line training. In the article, the prediction procedure is applied to experimental data obtained through model-scale tests, and the procedure's predictive performance is investigated for various irregular wave scenarios. The presented results show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action).

Short-term variability of ship responses is investigated by cross-spectrum analysis. In a steady state condition, it is well known that a certain length of sampled data is required for stable results of the spectral analysis. However, the phase lag between responses, in terms of the phase angle of the cross-spectra, has not been discussed in detail. Analyzing long stationary time series by direct Fourier transform, the authors pointed out that the short-term variability of the relative phase angle of the cross-spectra was very harmful to sea state estimation of the wave buoy analogy. In this report, the same investigation based on the correlation (Blackman-Tukey) method was applied to the same data. In the results, it was observed that the short-term variability of the relative phase angle was reduced to a certain extent.

Short-term variability of ship responses is investigated by cross-spectrum analysis. In a steady state condition, it is well-known that a certain length of sampled data is required for stable results of the spectral analysis. However, the phase lag between responses, in terms of the phase angle obtained from the (coupled) cross-spectra, has not been discussed in detail. In a previous but similar study, the authors pointed out that the short-term variability of the relative phase angle of the cross-spectra is harmful to sea state estimation using the wave buoy analogy, i.e. ship as a wave buoy. In the present report, an investigation based on the multi-variate auto-regressive model method has been applied to the same data. In the results, it has been observed that the short-term variability of the relative phase angle can be reduced.