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  • 1. Kotovirta, Ville
    et al.
    Jalonen, Risto
    Axell, Lars
    SMHI, Research Department, Oceanography.
    Riska, Kaj
    Berglund, Robin
    A system for route optimization in ice-covered waters2009In: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 55, no 1, p. 52-62Article in journal (Refereed)
    Abstract [en]

    Information about ice is indispensable to navigation in ice-covered sea areas. For vessels traveling long distances in ice, it is worth planning routes that will reduce fuel consumption and travel time, as well as the risk of ending up in hazardous areas or getting stuck in the ice. In addition to observations on board. there is a multitude of data sources available for seafarers like satellite images, ice model data, weather observations and forecasts. However, it is difficult for a human to take into consideration all the time-varying data parameters when planning a route. In this paper, a prototype system for optimizing routes through the ice field is presented. The system integrates state-of-the-art ice modeling, ship transit modeling, and an enduser system as a route optimization tool for vessels navigating in ice-covered waters. The system has recently been validated on board merchant vessels in the Baltic Sea, and the system's performance has been analyzed statistically using AIS data. Based on the AIS data analysis the mean relative error of the estimated transit time was 0.144 [s/s] with a standard deviation of 0.147 [s/s] for long routes (90-650 km), and 0.018 [s/s] with standard deviation of 0.193 [s/s] for 50 km route segments. (C) 2008 Elsevier B.V. All rights reserved.

  • 2.
    Omstedt, Anders
    et al.
    SMHI, Research Department, Oceanography.
    Svensson, Urban
    SMHI, Research Department, Oceanography.
    ON THE MELT RATE OF DRIFTING ICE HEATED FROM BELOW1992In: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 21, no 1, p. 91-100Article in journal (Refereed)
    Abstract [en]

    The melt rates of fresh and saline drifting ice, heated from below, are examined using a one-dimensional ice/ocean model with high vertical resolution. The model is based on the conservation equations for heat, salt, and momentum and uses turbulence models to achieve closure. The model includes a low-Reynolds number turbulence model for the viscous region, coupled to a high-Reynolds number turbulence model for the outer boundary, and a discrete element approach to the parameterization of roughness. It is shown that the melt rate of drifting ice is sensitive to ice roughness and molecular salt diffusion, and it is found that bulk heat transfer coefficients vary within a rather narrow range in the examined interval.

  • 3.
    Sahlberg, Jörgen
    SMHI, Professional Services.
    MODELING THE THERMAL REGIME OF A LAKE DURING THE WINTER SEASON1988In: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 15, no 2, p. 151-159Article in journal (Refereed)
  • 4.
    Svensson, Urban
    et al.
    SMHI, Research Department, Oceanography.
    Omstedt, Anders
    SMHI, Research Department, Oceanography.
    Numerical simulations of frazil ice dynamics in the upper layers of the ocean1998In: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 28, no 1, p. 29-44Article in journal (Refereed)
    Abstract [en]

    The frazil ice dynamics in a turbulent Ekman layer have been investigated using a mathematical model. The model is based on the conservation equations for mean momentum, energy and salinity, and employs a two-equation turbulence model for the determination of turbulent diffusion coefficients. A crystal number continuity equation is used for the prediction of the frazil ice dynamics. This equation considers several processes of importance, as for example turbulent diffusion, gravitational up-drift, flocculation/break-up and growth. The results focus on the frazil ice characteristics in the upper layers of the ocean, like suspended ice volume, ice crystals per m(3), vertical distributions, etc. From the idealized calculations, it is indicated that a large number of ice crystals can be mixed into the ocean during freezing. However, the amount of ice in suspension, measured as vertically integrated ice thickness, adds only a minor part to the total surface ice budget. Small crystals are mixed deep in the ocean while the large ones are found only in the top of the mixed layer. Knowledge about the vertical distribution of ice crystals of different sizes, which is calculated from the model, should be of importance when analysing processes as formation of ice covers in the ocean and ice-sediment or ice-algae interaction. (C) 1998 Elsevier Science B.V. All rights reserved.

  • 5.
    Svensson, Urban
    et al.
    SMHI, Research Department, Oceanography.
    Omstedt, Anders
    SMHI, Research Department, Oceanography.
    SIMULATION OF SUPERCOOLING AND SIZE DISTRIBUTION IN FRAZIL ICE DYNAMICS1994In: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 22, no 3, p. 221-233Article in journal (Refereed)
    Abstract [en]

    The objective of the work presented is to formulate a mathematical description of frazil ice dynamics. The formulation is to be in balance with the current knowledge of the physical processes, for example secondary nucleation. As the knowledge of some of these processes is fragmentary, this means that a conceptually simple formulation is sought. A number of processes are known to influence the supercooling rate and the frazil ice production. The present formulation accounts for the following processes: initial seeding, secondary nucleation, gravitational removal, growth due to cooling of water volume and flocculation/break up. Equations are formulated for these present considering a resolution in time and radius of particles but not in space (well-mixed jar). The equations are solved using a simple explicit numerical scheme. Preliminary results indicate that the model can be calibrated to describe the experimental results reported in the literature. It is mainly the supercooling curves that are used for comparison but some information about the crystal size distribution is also considered. It is to be noted that the model is calibrated to fit the experiments, due to the lack of detailed mathematical description of some of the physical processes. Sensitivity analysis is also used in order to establish that the model behaves according to experimental findings and expectations. The main conclusion of the study is that a fairly simple mathematical model can be formulated and calibrated, which fits the experimental data reported in the literature hitherto. It is further concluded that a resolution in radial space gives additional insight into the dynamics of the process. The evolution of the size distribution and its sensitivity to seeding and dissipation rate has been predicted with results that look physically plausible.

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