Applications of a new ecosystem model to study the dynamics of phytoplankton and nutrients in the Ariake Sea,west coast of Kyushu,Japan

In this study, we present the development and application of a new ecosystem model coupled with a hydrodynamic model to describe the important physical, chemical and biological processes of an ecosystem in the marine environment, the Ariake Sea in the west coast of Kyushu, Japan. The model was calibrated and validated using in-situ field measurements from various monitoring stations in the sea. The presented results covered the period from January 1991 to December 2000. The results showed that chlorophyll-a, nutrients and dissolved oxygen levels varied seasonally in response to weather and boundary condition. Through this study, the model was shown to be able to handle the flooding and drying processes that usually exist and play an essential role over the estuarine-tidal flats of the sea.     

Measurements of hydrodynamic forces, surface pressure, and wake for obliquely towed tanker model and uncertainty analysis for CFD validation

This article presents hydrodynamic forces and moments, surface pressures, estimated side force distributions, and wakes under oblique towing conditions for a practical tanker model (model KVLCC2M), which was designed by the Korea Research Institute of Ships and Ocean Engineering (KRISO). Ship offset data is readily available and can be obtained from the Internet. The model ship has no appendages and no rudder. Trim and sinkage were adjusted to zero in the static condition and the model ship was constrained against any motion. Although the drift angle β was primarily set to 0°, 6°, and 12°, other settings were used in some experiments. All experimental results were processed using uncertainty analysis. The uncertainty analyzing method follows the ANSI/ASME Performance Test Code (PTC19.1-1985) and the AIAA Standard S-071-1995. Only a few error components were considered here and they were empirically chosen because they had a heavy weighting when used in the uncertainty calculation. The results of these towing tank experiments will contribute to the development of computational fluid dynamics (CFD) research in ship hydrodynamics.     

Simple Lagrangian formulation of bubbly flow in a turbulent boundary layer (bubbly boundary layer flow)

For the theoretical consideration of a system for reducing skin friction, a mathematical model was derived to represent, in a two-phase field, the effect on skin friction of the injection of micro air bubbles into the turbulent boundary layer of a liquid stream. Based on the Lagrangian method, the equation of motion governing a single bubble was derived. The random motion of bubbles in a field initially devoid of bubbles was then traced in three dimensions to estimate void fraction distributions across sections of the flow channel, and to determine local bubble behavior. The liquid phase was modeled on the principle of mixing length. Assuming that the force exerted on the liquid phase was equal to the fluid drag generated by bubble slip, an equation was derived to express the reduction in turbulent shear stress. Corroborating experimental data were obtained from tests using a cavitation tunnel equipped with a slit in the ceiling from which bubbly water was injected. The measurement data provided qualitative substantiation of the trend shown by the calculated results with regard to the skin friction ratio between cases with and without bubble injection as function of the distance downstream from the point of bubble injection.List of symbols B law of wall constant - C _f local coefficient of skin friction - C _f0 local coefficient of skin friction in the absence of bubbles - d _b bubble diameter [m] - g acceleration of gravity [m/s²] - k ₁ k₄ proportional coefficient - k _L turbulent energy of the liquid phase [m²/s²] - L representative length [m] - l _b mean free path of a bubble [m] - m _A added mass of a single bubble [kg] - m _b mass of a single bubble [kg] - N _x ,N _y ,N _z force perpendicular to the wall or ceiling exerted on a bubble adhering to that wall or ceiling [N] - P absolute pressure [Pa] - Q _G rate of air supply [/min] - q _L ⁽ⁱ⁾ turbulent velocity at the ith time increment [m/s] - R> _ex Reynolds number defined by Eq. 32 - T _*L integral time scale of the liquid phase [s] - U velocity of the main stream [m/s] - ,¯v,¯w time-averaged velocity components [m/s] - u,v,w turbulent velocity components [m/s] - û _L ,v_L root mean square values of liquid phase turbulence components in thex- and y-directions [m/s] - V volume of a single bubble [m³] - X,Y,Z components of bubble displacement [m] - x _s ,y _s ,z _s coordinate of a random point on a sphere of unit diameter centered at the coordinate origin - root mean square of bubble displacement in they-direction in reference to the turbulent liquid phase velocity [m] - local void fraction - _m mean void fraction in a turbulent region - regular random number - R _v increment of the horizontal component of the force acting on a single bubble, defined by Eq. 22 [N] - t time increment [s] - ₁ reduction of turbulent stress [N/m²] - _L rate of liquid energy dissipation [m²/s³] - _m coefficient defined by Eq. 30 - law of wall constant in the turbulent region in absence of bubbles - ₁ law of wall constant in the turbulent region in presence of bubbles     

Dynamic control of a remotely operated vehicle using a neural network

The control of a remotely-operated underwater vehicle to maintain a prescribed depth in shallow water under irregular surface waves is realized through the application of the Robust Adaptive Neuro Controller, a composite control system incorporating—together with the conventional control algorithm—a neural network controller. This network bestows a learning capability on the system, allowing it to deal with unanticipated disturbances that would otherwise cause erroneous behavior of the vehicle. The effectiveness of this application is verified through mathematical simulation of a model vehicle's behavior, through experiment in a model basin, and through simulation of the behavior of an actual remotely operated vehicle in shallow water under irregular surface waves. Graphic data representing the learning process undergone by the neural network distinctly indicate the rising output from the network with the progression of learning, and the vehicle's depth variation traced in terms of the mean square error vividly show the diminution of deviation from the prescribed depth obtained with application of the neural network. Thus controlled to maintain constant depth, under-water vehicles with power supplied externally through a tether for propulsion and for heavy-duty operations should consolidate their advantage for such activities as maintenance of submarine structures and surveys in deep or hazardous water.     

Numerical analysis on free surface waves and stern viscous flow of a ship model

This paper deals with numerical techniques for computing the viscous flow past a ship hull with and without a free surface using a Reynolds-averaged Navier-Stokes solver with global conservation. In the first technique, a coarse grid is used to find an approximate solution to the free surface problem. Interpolation of a fine grid is subsequently carried out, and a more exact solution, particularly in the boundary layer and wake, is obtained. In the second technique, a modified Baldwin-Lomax model is introduced to compute the viscous flow with and without a free surface. These numerical techniques are applied to simulations of the flow around a Series 60 and an SR196C ship model. The results are compared with measurement data, and the usefulness of the numerical techniques is demonstrated.     

Estimation and prediction of effective inflow velocity to propeller in waves

A free running test using a container ship model clarified properties of effective inflow velocity to propellers in waves. The analysis assumes that thrust and torque vary keeping their relation to the effective inflow velocity as represented by open-water characteristics of a propeller in a steady calm water condition. Measurement in regular waves confirmed the variation of average values of the effective wake coefficient and ship speed depending on wavelength and wave encounter angle. Comparison with the longitudinal flow velocity measured at the sides of the propeller using an onboard vane-wheel current meters confirmed that one can estimate the effective inflow velocity based on thrust or torque data. Theoretical estimates in regular waves based on a strip method are provided and compared with the experimental data. A prediction model of the future inflow velocity is proposed to cope with a time delay of a propeller pitch controller for higher propeller efficiency in waves.     

Distribution of void fraction in bubbly flow through a horizontal channel: Bubbly boundary layer flow, 2nd report

A method of enveloping the hull with a sheet of microbubbles is discussed. It forms part of a study on means of reducing the skin friction acting on a ship's hull. In this report, a bubble traveling through a horizontal channel is regarded as a diffusive particle. Based on this assumption, an equation based on flow flux balance is derived for determining the void fraction in approximation. The equation thus derived is used for calculation, and the calculation results are compared with reported experimental data. The equation is further manipulated to make it compatible with a mixing length model that takes into account the presence of bubbles in the liquid stream. Among the factors contained in the equation thus derived, those affected by the presence of bubbles are the change of mixing length and the difference in the ratio of skin friction between cases with and without bubbles. These factors can be calculated using the mean void fraction in the boundary layer determined by the rate of air supply into the flow field. It is suggested that the ratio between boundary layer thickness and bubble diameter could constitute a significant parameter to replace the scale effect in estimating values applicable to actual ships from corresponding data obtained in model experiments.List of symbols a ₁ proportionality constant indicating directionality of turbulence - B law-of-the-wall constant - C _f local skin-friction coefficient in the presence of bubbles - C _f0 local skin-friction coefficient in the absence of bubbles - d _b bubble diameter (m) - g acceleration of gravity (m/s²) - j _g flow flux of gas phase accountable to buoyancy (m/s) - j _t flow flux of gas phase accountable to turbulence (m/s) - k ₄ constant relating reduction of liquid shear stress by bubble presence to decrease of force imparted to bubble by its displacement due to turbulence - l _b mixing length of gas phase (m) - l _m mixing length of liquid phase (m) - l _mb diminution of liquid phase mixing length by bubble presence (m) - Q _G rate of air supply to liquid stream (l/min) - q _/g velocity of bubble rise (m/s) - 2R height of horizontal channel (m) - T _* integral time scale (s) - U _m mean stream velocity in channel (m/s) - U friction velocity in channel (m/s) - V volume of a bubble (m³) - u, ¯ v time-averaged stream velocities inx- andy-directions, respectively (m/s) - u, v turbulent velocity components inx- andy-directions, respectively (m/s) - v root mean square of turbulence component in they-direction (m/s) - root mean square of bubble displacement iny-direction with reference to turbulent liquid phase velocity (m) - y displacement from ceiling (m) - local void fraction - _m mean void fraction in boundary layer - _m constant relating local void fraction to law-of-the-wall constant - _t reduction of turbulent stress (N/m²) - law-of-the-wall constant in turbulent liquid region in absence of bubbles - ₁ law-of-the-wall constant in turbulent liquid region in presence of bubbles - ₂ law-of-the-wall constant in gas phase - _m constant indicating representative turbulence scale (m) - viscosity (Pa × s) - v kinematic viscosity (m²/s) - density (kg/m³) Suffixes G gas - L liquid - 0 absence of bubbles