The paper explores the use of a GPU-Event-Mechanics (GEM) simulation to assess local ice loads on a vessel operating in pack ice. The methodology uses an event mechanics concept implemented using massively parallel programming on a GPU enabled workstation. The simulation domain contains hundreds of discrete and interacting ice floes. A simple vessel is modeled as it navigates through the domain. Each ship-ice collision is modeled, as is every ice-ice contact. Each ship-ice collision event is logged, along with all relevant ice and ship data. Thousands of collisions are logged as the vessel transits many tens of kilometers of ice pack. The GEM methodology allows the simulations to be performed much faster than real time. The resulting impact load statistics are qualitatively evaluated and compared to published field data. The analysis provides insight into the nature of loads in pack ice. The work is part of a large research project at Memorial University called STePS2 (Sustainable Technology for Polar Ships and Structures).
Analysis of data, recorded on March 8th 2014 at the Comprehensive Nuclear-Test-Ban Treaty Organisation’s hydroacoustic stations off Cape Leeuwin Western Australia, and at Diego Garcia, reveal unique pressure signatures that could be associated with objects impacting at the sea surface, such as falling meteorites, or the missing Malaysian Aeroplane MH370. To examine the recorded signatures, we carried out experiments with spheres impacting at the surface of a water tank, where we observed almost identical pressure signature structures. While the pressure structure is unique to impacting objects, the evolution of the radiated acoustic waves carries information on the source. Employing acoustic–gravity wave theory we present an analytical inverse method to retrieve the impact time and location. The solution was validated using field observations of recent earthquakes, where we were able to calculate the eruption time and location to a satisfactory degree of accuracy. Moreover, numerical validations confirm an error below 0.02% for events at relatively large distances of over 1000 km. The method can be developed to calculate other essential properties such as impact duration and geometry. Besides impacting objects and earthquakes, the method could help in identifying the location of underwater explosions and landslides.
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