8/3/2019 Disain Kapal Layar Balap Yach_Marine Transport_Scarponi_Matteo

1/1

M. Scarponi

matteo@ship.soton.ac.uk

School of Engineering Sciences, University of Southampton, UK

Facolt di Ingegneria, Universit di Perugia, Italy

A Combined Ship Science-Behavioural Science ApproachTo Create A Winning Yacht -Sailor Combination

Yacht motion described as in (Masayuma et al., 1997).

4 DoF are considered (surge, sway, yaw, heel): adequate effort/accuracy trade-off.

Reference yacht is IACC M566, thoroughly investigated in past Ship Science projects.

Forces and moments decomposed using Taylors expansion.

Yacht racing and human factorBackground

Proposition

Racing yacht designers aim at maximizing yacht performances within the boundariesof class rules. For a well-policed yacht rule, such performance gains are small.

Regattas are contexts rich in non-deterministic features: a crew deals with ever-changing states of nature (e.g. wind, tide) and opponents.

The main area of possible performance gains is in how best a crew.

Sailors performances should be accounted for as well as those of yachts.

An approach is suggested where yacht-crew systems are investigated as a whole,which gives the opportunity to rank sailors choices as well as yacht performances.

Possible behavioural models for choices of a strategical nature are highlighted.

Fluid Structure InteractionsResearch Group,

School of EngineeringSciences

Towards a dynamic VPP

Set-up of an automatic crew

Fig. 1: Refer ence angles for a yacht

Decision-making models

Upwind sailing and gambling

Helmsman

Sail tailer

Navigator

Modeled in terms of a proportional-integral-derivative (PID) controller.

Helmsman outputs are rudder angle and rudder rate.

Two possible options: steering to a reference apparent wind angle (for upwind anddownwind legs) or towards the next mark (for reaching legs).

Outputs of the sail tailer module are the sheetingangle () and its derivative.

A PID controller aims at minimizing the error

between a reference sheeting angle refand itsactual value (t).

An additional controller is dedicated to depoweringthe sail which, in turn, limits the heeling.

Checks the yacht position on theracecourse.

Detects changes in wind conditions(e.g. windshifts, wind oscillations).

Manages manoeuvers (e.g. tacks)and subsequent speed recovery.

Issues strategical decisions (e.g.when approaching an upwindmark).

( )U hull rudder sail

m u v X X X X = + + +&&

( )hull rudder sailm v u Y Y Y = + +&&

xx hull rudder sail stability I K K K K = + + +&&

zz hull rudder sail I N N N = + +&&

Masayuma, Y., Fukasawa, T., Sasagawa, H., Tacking Simulations of Sailing Yachts -Numerical Integration of Equations of Motions and Application of Neural Network Technique,Proceedings of the 12th CSYS, (1997)

Fig. 2: Yacht reachin g towards Mark #3, time = 1000s

Best sailors function as better decision-makers (Arajo et al., 2005).

Decision-making models mostly based on maximization of expected utility.

When making decision under risk, probability informations Pj should be

associated with outcomes Sj for j = 1,,n.

Non-normative models (heuristics) are likely to be used under time-pressure.

Decision-making problem of a strategical nature: yacht being headed at t =200 sec while sailing upwind.

Four possible weather scenarios are presented (two oscillating and twoveering wind patterns): n = 4 in Table 1. Probabilities for each scenario tooccur are varied and Monte Carlo simulations were run.

Options available to the crew: A1 - tack / A2 - dont tack / A3 - delay tack.

Payoffs Ci,j calculated through the sailing simulator. Choice based on expectedutility maximization.

Arajo, D., Davids, K., Serpa, S., An ecological approach to expertise effects in decision-making in a simulated sailing regatta, Psychology of Sport and Exercise, 6, 671-692 (2005)

S1 Sj SnP1 Pj Pn

A1

Ai Ci, j

Am

Ai = alternatives or gambles Sj = attributes or outcomes

Pj = probabilities

Ci,j = payoffs

Expected Payoff:

Expected Utility:

,

1

n

i j i j

j

E P C =

=

,

1

( ) ( )n

i i j i j

j

U u A P u C =

= =

Fig. 4: Risk-averse attitude

u

Ci,j

Fig. 3: Risk-taking attitude

u

Ci,j

Tab. 1: General form of a payoff matri x

Fig. 6: oscillating wind pattern, dashed-track-yachttacks on windshifts, solid-track-yacht never tacks

Fig. 5: expected utilities; blue dashed line = tack;green dotted line = tack delayed by 60 secs.Posc =probability for oscillating wind scenarios to occur

Conclusions A 4 DoF, dynamic VPP allows yacht-crew systems to be investigated as a whole.

A tool for race simulations and post-race analyses has been developed; results canbe delivered through offline animations in a Virtual Reality environment.

Rule-based and utility-based behavioural models for making choices of astrategical nature are highlighted.