2.2 DYNAMIC VPPS
Although further improvements can still be achieved, VPP technology in itself looks mature enough: research is therefore
required to take a step forward and investigate unsteady aspects of sailing yacht motion.
A few attempts to investigate yacht dynamics in the time- domain can be found in recent literature. Some Authors have focused on manoeuvring, in order to evaluate the optimal tacking procedure [3],
[4], while others have
simulated a yacht racing on an upwind leg, focusing on its motion in a seaway [5] or its interactions with an opponent [6]. A great part of the Authors concentrate on solving simultaneously the set of unsteady non-linear equations of motions, or the use of system identification, based on neural networks, has been investigated as well. Up to six degrees of freedom (DOFs) have been taken into account, but four DOFs (surge, sway, yaw and roll) analyses proved to be adequate for tacking simulations and yielded results whose agreement with full scale trials is reasonable [4]. Therefore, the latter approach has been followed in this work; the non-linear equations
of
motions are those proposed by Masuyama et al. [4]. The yacht reference frame adopted here is the horizontal body axes system.
3.
FEATURES OF THE SAILING SIMULATION
The four equations of motions mentioned in the above Section represent the core of the sailing simulator described herein, whose purpose is to estimate the time a given yacht takes to sail a racecourse. The simulator is composed of three interacting modules: a physical model of an International America’s Cup Class (IACC) yacht;
a visualization module where the yacht motion is shown in a virtual reality context;
a control module, referred to as ‘automatic crew’.
The IACC yacht is racing solo, against the clock: this is to show to what extent strategical decisions influence the time required to complete a race. The simulator has been implemented in MATLAB: this choice lead to slower simulation times but, facilitated algorithm development and offered the possibility of interacting with a virtual reality environment, either to model yacht features or to generate animations.
3.1 PHYSICAL MODEL OF THE YACHT
The geometry of an IACC hull referred to as ‘M566’ has been implemented in the present version of the simulator; several towing tank and CFD tests have been carried out on the M566 model so far [7], and a fairly large amount of data is available on its hydrodynamic resistance, side force and manoeuvring characteristics. However, data such as added masses and higher order hydrodynamic derivatives for the M566 have not been calculated so far;
Figure. 1 - Lift coefficient CL as a function of incidence angle ()
if the investigation pattern suggested in [4] were followed, full-scale trials such as rolling tests with and without sails would be required, which is well beyond the scope of this paper. So, although the experimental results provided in [4] are not referred to an IACC yacht, some of those data are still used herein, since it is thought they provide a sensible starting place dynamic analyses.
for
Figure. 2 - Drag coefficient CD as a function of incidence angle ()
A mainsail-jib combination only has been implemented here: geometry and further details on this sail inventory are provided in [8]. Lift and drag sail coefficients (CL and CD respectively) expressed as a function of true wind angle are available from past wind tunnel tests on IACC sail plans. When model sails are tested, they are usually trimmed in real-time by means of a remote control: aim of the trimming process is to attain the maximum CL or maximum CL/CD ratio at each apparent wind angle of the test matrix. However, when human sail trimmers are modelled, sub-optimal
sail performances should be
considered as well (i.e. CL and CD for under/over trimmed sails). A sensible way to account for an ill-trimmed sail
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©2008: Royal Institution of Naval Architects
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