MaxSea International

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MaxSea International Software editor for marine market MaxSea is distributed in 25 countries Available in 13 languages. 90.000 ships equiped

description

MaxSea International. Software editor for marine market MaxSea is distributed in 25 countries Available in 13 languages . 90.000 ships equiped. Our group. 75 Employes Turnover 2012: 6.2 M€ (+10%). Charts Bidart - France. Software Bidart - France. Holding Bidart - France. - PowerPoint PPT Presentation

Transcript of MaxSea International

Page 1: MaxSea  International

MaxSea International

Software editor for marine market

MaxSea is distributed in 25 countriesAvailable in 13 languages.

90.000 ships equiped

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Our group

HOLDING BIDART - FRANCE

SOFTWAREBIDART - FRANCE

COMMERCIAL, SALES, MARKETING, SUPPORT

BARCELONA - SPAIN

SOFTWAREPORTLAND - USA

CHARTSBIDART - FRANCE

75 EMPLOYESTURNOVER 2012: 6.2 M€ (+10%)

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Radar Overlay

Strong collaboration with FURUNO Japan (1st worldwide marine electronics manufacturer).

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Cameras FLIR (IR, night vision…)

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Isochrones for minimum time route optimization

• Wind polar• Wave polar• Set sail• Weather prediction (wind, waves)• Currents

• Optimal route

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DEMO

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Isochrone : Dynamic programmingN Objective:

Maximize distance for a given time interval ∆t

D Step n→Isochrone at time ζ

Reference : Knmi publicatie met nummer : 102.94On minimal-time ship routingS.J. Bijlsma 1975

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N

D

Wind Polars

Isochrone : Dynamic programming

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D

ad1

d2d3

d4

What is the shorter path ?

Isochrone : Dynamic programming

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D

Wind polar

Direct construction of next point :normal to isochrone == normal to

polar

Isochrone : Dynamic programming

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D

Repeat for all isochrone point, you construct next isochrone.

Isochrone : Dynamic programming

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Next isochrone (dash)

Optimization becomes a geometrical optimization.

Not easy to resolve, in good computational time, taking into account numerical precision.

Multiple path for optimal route at intersection point.

Isochrone : Dynamic programming

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Route optimization for motor boats

• Main goal: fuel consumption optimization. But also limit weather conditions.

• Several types of boats– Motor– Motor with sail assistance– Motor Sailing– Sailing

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3D Routing

• New problem : find best course (2d) and best motor speed (power) to minimize fuel consumption.

• Motor and MotorSail boats have round speed polars (motor always on) => isochrones are isodistance (shortest path).

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Fuel Consumption models

• Motor :– Hydro & areo dynamic forces + motor consumption

curve.– Approximation 2nd degree from speed inside speed

limits (18-25kts) :Conso t/nm = 0.0036*V2 + 0.1015V + 0.8848 (not linear)

• Motor Sailing : mutilple Wind polar curves (for each motor power / sail %).

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Fast Marching MethodOrdered Upwind Method

• We wanted a new method for 2D & 3D (more easy to implement than 3D geometric calculation).

• Differential equation : Consumption = f(x,y,t,course,motor power).

• Front propagation.

• Strong anisotropy : wind and wind polar (sailing) or waves.

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Ordered Upwind Method

Considered are sorted according to cost.

Reference : SIAM J. Numer. Anal., 41(1), 325–363. (39 pages)Ordered Upwind Methods for Static Hamilton--Jacobi Equations: Theory and Algorithms

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Ordered Upwind Method

Smallest Considered is removed from Sorted Queue. It becomes the Last Accepted.

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Ordered Upwind Method

All Neighbors of Last Accepted are updated. Cost and Arrival Time are computed.

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Ordered Upwind Method

Again, smallest Considered => Last Accepted

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Ordered Upwind Method

The Front advanced with 2 new Accepted. Loop until arrival point is reached.

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3D OUM

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OUM : 3 update methods

• Direct Cost : from a node to horizontal, vertical or diagonal node.

• Enumeration : minimise over 20 angles (original method from Vladimirsky)

• Gradiant : from downwind gradiant, select best speed vector in polar, use it to compute upwind.

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Enumeration

Linear cost interpolation between U2 & U3.

20 angles tried for minimization.

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Gradiant, when 3 accepted neighboors

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DEMO

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Experience

• Difficult to validate results : reference solution.

• Gradiant was working during unit testing, we found problems during integration.

• Parallel algorithm is not evidence.• Software optimization is needed for interactive

simulations.