Effects of an explosive polar cyclone crossing the Antarctic marginal ice zone

Antarctic sea ice shows a large degree of regional variability, which is partly driven by severe weather events. Here we bring a new perspective on synoptic sea ice changes by presenting the first in situ observations of an explosive extratropical cyclone crossing the winter Antarctic marginal ice zone (MIZ) in the South Atlantic. This is complemented by the analysis of subsequent cyclones and highlights the rapid variations that ice-landing cyclones cause on sea ice: Midlatitude warm oceanic air is advected onto the ice, and storm waves generated close to the ice edge contribute to the maintenance of an unconsolidated surface through which waves propagate far into the ice. MIZ features may thus extend further poleward in the Southern Ocean than currently estimated. A concentration-based MIZ definition is inadequate, since it fails to describe a sea ice configuration which is deeply rearranged by synoptic weather

Antarctic sea ice properties on zero meridian side during Austral summers 2012-14 and 2018-19

Polar Supply and Research Vessel S.A. Agulhas II has visited Antarctic continent annually since her maiden voyage 2012. Commonly, the voyage duration is from December to Februaryor March. Aalto University and Stellenbosch University have been conducting ship and ice conditions related measurements with varying focus since the maiden voyage. The mechanical properties of sea ice (flexuraland compressive strength) have been measured during voyages 2012-13, 2013-14, and 2014-15 while the focus in voyage 2018-19 was in physical properties, i.e. the salinity, density, temperature, and grain sizeof ice.This paper presents themethods and results of these measurementsto contribute to therelatively rare dataset of Antarctic sea ice properties. The mean flexural strength was around 280 kPa. The measured compressive strength of sea ice varied from 100 kPa to 3.0 MPa in the vertical direction, and from 100 kPa to 1.5 MPain the horizontal direction, the averages being 740 kPa and 560 kPa, respectively. The shelf ice compressive strength varied generally from 100 kPa to 400 kPa with an average of 160 kPa.The measured ice temperature generally varies from air temperature on the top to -1.8°C in the bottom. Ice salinity varies from around 1‰ to 8‰ and ice density is in the range from 830to 940kg/m3.Peer reviewe

System identification and tracking using a statistical model and a Kalman filter

The sensitivity of system identification estimates to changing environmental and operational parameters is important for structural health monitoring and inverse force estimation. Damage to a structure can be misidentified or masked by modal shifts as a result of environmental parameters. In this paper a novel approach to reduce the uncertainties and improve the sensitivity of system identification and tracking is presented based on a data driven statistical model and a Kalman filter. A key objective is to make experimental data maximally informative by using additional system inputs. The method is first demonstrated on numerical data where it was found to improve accuracy and identify underlying trends. Investigations were then conducted on full scale data from the research vessel Polarstern. Model training led to the development of a sliding predictive model using an optimized linear regression method. The model was found to accurately re-create the training data set and was used to make predictions based on future system inputs. Since both the model prediction and the system identification estimates contain different uncertainties the Kalman filter was used to combine both estimates in an optimal way. The Kalman filter estimates were observed to produce balanced and consistent results. The Kalman estimates were also not overly or consistently biased by the SSI estimates or the model predictions

Automatic modal parameter selection using a statistical model and a Kalman filter

The automation of system identification is important for processing large amounts of data without expert user interaction. Automation is also important to maintain consistency in estimates, especially when investigating trends in data which could be masked by variations of mathematical parameters. This research presents a novel idea to obtain automatic modal parameter estimates based on a data driven statistical model and a Kalman filter. A key objective was to make observed data maximally informative. This lead to the development of a sliding predictive model using an optimized linear regression method to use system inputs which are not included in standard system identification. The method was first demonstrated on a numerical data set where it was found to improve system predictions. The method was then tested on full scale data from the German research vessel Polarstern during a voyage to the Arctic. The automatic Kalman estimates showed improved estimates using the combination of statistical model and modal parameters

On Uncertainty Assessment of Fatigue Damage of Propulsion Shaft Under Ice Impact

In this paper, the importance of maintenance of marine propulsion is discussed with specific focus on the use of condition monitoring to inform maintenance schedules. The design requirements of DNV GL for shafts expected to operate in ice infested waters is adapted and a method is proposed to calculate the short-term fatigue damage during ice impacts. This method uses the Palmgren-Miner rule to calculate fatigue damage based on a transient, lumped-mass model simulation of the shaft with ice loads calculated from shaft measurements using inverse methods. Relevant sources of uncertainty in this assessment method are identified and quantified in order to express the short-term fatigue damage in a stochastic form. Sources of uncertainty include uncertainty in the calculation of ice loads, uncertainty of the transient analysis and uncertainty regarding the actual failure of the shaft as predicted by the S-N material curve and the Palmgren-Miner method. Uncertainties that influence the stress history are found to be the greatest contributor to fatigue damage uncertainty. A method is discussed that calculates the remaining useful life of the shaft as a function of short-term fatigue damage and the identified sources of uncertainty. The S.A. Agulhas is used as a case study to quantify the fatigue damage

Visual Antarctic sea ice condition observations during Austral summers 2012-2016

Due to Antarctica's remoteness, sea ice condition observations and measurements on board ships are rare. However, ship based annual expeditions are conducted from Cape Town to Antarctica within the South African National Antarctic Program. The S.A. Agulhas II replaced the S.A. Agulhas in 2012 and departed Cape Town on December 2012 for her maiden voyage to Antarctica. Intensive sea ice observations have been performed since by researchers during annual relief voyages from December to February. In this paper, we present the visual observations on board the S.A. Agulhas II from the annual expeditions of four austral summers 2012 to 2016. The sea ice condition observations include ice thickness, concentration, and floe size. The changes in these parameters are studied between different years and during the voyages. The observations show that the thickness, concentration and floe size increase when moving from north towards south. Visual Antarctic Sea Ice Condition Observations during Austral Summers.Peer reviewe

Ship Motion Measurements and Human Responses Captured on the SA Agulhas II - SANAE 2021-2022

This dataset contains digitised human responses related to motion sickness recorded by participants on the SA Agulhas II during the South African National Antarctic Expedition (SANAE) Relief Voyage of 2021-2022 using paper-based questionnaire booklets, called daily diaries, and a mobile application, called Mariner 4.0.Additionally, this dataset contains ship motion measured by accelerometers in a specific array that enables the computation of z-oriented acceleration at points of interest on board beyond the array measurement locations. Acceleration measurements in the dataset are stored in 5-minute batches with a 10 Hz sample rate at the locations and orientations detailed in the associated readme file in the data collection. This dataset is a down-sampled subset of acceleration measurements sampled at 2048 Hz during the SANAE Relief Voyage of 2021-2022.Lastly, this dataset contains Motion Sickness Dose Values computed from ship motion measurements at each near-field communication tag installed shipboard, as detailed by position vectors in the supporting documentation.Note: A Readme file is included to guide dataset navigation and understanding.</p

The detection of wave slamming from vibration measurements on a polar supply and research vessel

The SA Agulhas II is a polar supply and research vessel, which operates in the stormy Southern ocean and icy Antarctic waters. She is predisposed to problematic stern slamming. Twelve accelerometer channels from a full-scale vibration measurement system were used to capture measurements of wave incidence on the main deck close to the water line. An automated slamming detection and classification algorithm is proposed to extract slamming incidents from expansive full-scale data. This method is based on image processing of scalograms which are produced by continuous transforms, using the Morlet wavelet. Slams are classified based on the time of incidence. It is shown that high crest factor stern slamming occurs as often as twice per minute

The detection of wave slamming from vibration measurements on a polar supply and research vessel

The SA Agulhas II is a polar supply and research vessel, which operates in the stormy Southern ocean and icy Antarctic waters. She is predisposed to problematic stern slamming. Twelve accelerometer channels from a full-scale vibration measurement system were used to capture measurements of wave incidence on the main deck close to the water line. An automated slamming detection and classification algorithm is proposed to extract slamming incidents from expansive full-scale data. This method is based on image processing of scalograms which are produced by continuous transforms, using the Morlet wavelet. Slams are classified based on the time of incidence. It is shown that high crest factor stern slamming occurs as often as twice per minute