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MEK 4450 Marine Operations 2-2 Kværner ASA / DNV, Fall 2014

Numerical Tools / Analysis Software

Why numerical tools? More accurate and detailed description

Why comercial tools:

Time consuming to produce inhouse Better quality checks (?) Clients acceptance

Numerical models

Hydrostatic / stability models (e.g. AutoHydro, Hydro D) Basic hydrodynamic analyses (e.g. WADAM, WAMIT) Time domain coupeled analyses (e.g. SIMO) CFD Beam theory (e.g. Orcaflex, Riflex) FEM

Hydrostatic Analysis

Hydrostatic model

INPUT Wet hull

shape Mass COG

OUTPUT Floating condition Stability margins

MODEL Geometry: stripes Mass and COG Archimedes Buoyancy and

moments

Use with care for non- standard

aplications

Quick and simple to use

Purpose made For normal ship Hull and normal

operations

Stability characteristics: four examples

Hydrodynamic Analysis

Floating object in waves - standard theory

INPUT Wet hull

shape Mass

distribution

OUTPUT Motion, pressure ++ Transfer function Postprocessing

MODEL Geometry: panels Mass matrix Inviscid

Incompressible Vessel: rigid body Incident waves

Viscous damping neglected

Couplings and nonlinearity

neglected

Quick and accurate solutions when

relevant

Purpose made For normal ship Hull and normal

operations

Transfer function

Time Domain Analysis

Time domain simulation program

INPUT (Hydro)dynamic

characteristics Links, wires,

beams etc Environment

OUTPUT Time series for

motions, forces etc Design values: post processing

MODEL Rigid body

motions Forces from

environments and links

Quality of coefficients?

Time consuming

Realistic modeling of marine operations

Stepping forward in time.

Runge Kutta etc

CFD

CFD INPUT

Boundary geometry and

conditions Initial conditons Fluid and turbulence parameters

OUTPUT Fields for velocity,

pressure etc at different time steps Integrated quantities

MODEL Viscous fluid Turbulence Bodies with

prescribed motion

Time consuming Floating bodies?

Realistic modeling of fluid flow

Accurate (?) calcs of coefficients

Stepping forward in time.

Runge Kutta etc

16.10.2014 © Kvaerner 2011 15

Extreme value statistics

Time series: basic output from Marine analyses Model tests Full scale test

Normal question: design value for dynamic parameter Maximum wave height => Water on deck Vessel roll motion => Sea fastening loads Wire loads => minimum breaking loads in wire

How to link time series to design value Maximum observed value Not robust with respect to repititions

Create the time series many times Series of observed maxima Calculate: Maximum of the maxima: very conservative Mean value of maxima Median of maxima Given procentile

How to link time series to design value Establish empirical distribution of maxima Fit an apropriate diostribution to the values

Gumbel is normaly used

0

0.2

0.4

0.6

0.8

1

1.2

250000 260000 270000 280000 290000 300000 310000 320000 330000 340000 350000

Empirical distribution

Empirical distribution

Gumbel approach

How to link time series to design value

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

250000 260000 270000 280000 290000 300000 310000 320000 330000 340000 350000

Fitted gumbel distributionEmpirical distribution

Alternative approach for stationary processes For each series one single value used only

Costly and time consuming Robust approach, fits all types of processes

Alternative: use one long time series

Identify individual tops Fit to these values Extract statistical max

Shortcomings Distribution type unknown,- may jepardize the whole strategy Long time series needed Stationary process required

Stationary and non- stationary processes

Stationary process: constant statistical properties Wind gusts at constant average wind Waves generated by this type of wind Wave induced responses to stationary waves

Non- stationary Wind or wave picking up (storm build-up) Dynamic responses when objects hits free surface Operational induced responses