wind characterization around offshore platform for real-time helicopter simulator

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Copyright © ESI Group, 2015. All rights reserved.

www.esi-group.com


Wind characterization around

offshore platform for real-time

helicopter simulator

Stefano Scala

Aeronautical Engineer – TXT NEXT

October 19 – 21 – Stuttgart, Germany

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Introduction

ESI OpenFOAM User Conference 2015 – October 19 – 21 in Stuttgart, Germany

TXT NEXT is a valuable partner that can support aircraft manufacturers in the development of the state-of-the-art training and operational solutions

AgustaWestland is committed to be a worldwide leader in the rotary wing industry by delivering best-in-class products and services and focusing on customer satisfaction, sustainable business, integrity and value creation.

Training Helicopter Support System Department

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Flight Simulation Training Devices

Introduction


• Development of Full Flight Simulators Lev. D Devices

• Devices that re-create aircraft flight and the environment for pilot training

• Each Full Flight Simulator performances are analyzed against aircraft flight data to ensure that its handling characteristics are representative of real helicopter

• Flight Simulator allow training of critical – emergency conditions in a safe, but yet realistic environment

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Aerodynamic effects in ground proximity operations

Introduction

• Atmospheric conditions can compromise mission effectiveness

• Atmospheric phenomena may vary according to ground obstacles

• Ground proximity operations are among the most dangerous flight phases

• The correct modeling of atmospheric conditions is crucial to allow the trainee pilot to exercise for these critical and complex maneuvers in a cost-effective and safe way

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Our approach

Introduction


• 3d moving models from Visual System

• CFD computation

• Local velocity tables in grid points

• Run-time query to extract data

• Airwake model algorithm

• Local velocity in hc control points

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3D model

CFD Computation


Oilrig Landable Ship

• 4 oil rigs models

• 2 ships models

• Models provided in Stereolithography (STL) format

• Mesh generation using snappyHexMesh

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OpenFoam analysis

CFD Computation


Boundary conditions

• 36 wind directions (every 10°) obtained rotating the 3D model

• 5 intensity of wind (5,15,25,35,45 knots)

• 180 standalone simulations for each model

Turbulence model

• SimpleFOAM with a stationary incompressible k-ԑ turbulence RANS model

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Mesh parameters

CFD Computation


External domain:

200 x 1150 x 150 meters

60 x 230 x 30 cells

Refinement domain:

100 x 150 x 70 meters

Total 1.3x106 cells

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Results

CFD Computation


• Velocity components stored in a table of about 35Mb

• Time required for a single run of about 2h.

• Total time for a 3D model: 6 Gb and 15 days.

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Results

CFD Computation


• Stream tracer on the backside of

the oilrig with 0° and 45 knots

• Stream tracer of a vortex generated

on the oil rig with 0° and 45 knots

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Requirements

Integration


• The goal.

‣ Provide run-time local wind to flight model

• The challenge.

‣ Real time environment (120 Hz frequency).

‣ Select right CFD computation depending on boundary conditions

‣ Manage such a big amount of data

‣ Local wind velocities in grid points only

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Database extraction (1)

Integration

• Database to store all the bulk of data produced by CFD.

• Algorithm for DB data extraction depending on

‣ Asymptotic wind speed

‣ Asymptotic wind direction

‣ 3Dmodel – HC distance


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Database extraction (2)

Integration

• Extraction of portion of points

‣ Nearest to helicopter

‣ Depending on helicopter attitude and airspeed

‣ Less points means faster query

• New query when hc is about to leave the portion obtained with previous query


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Helicopter control points

Integration

• 95 HC control points

‣ 81 Main rotor

‣ 9 Tail rotor

‣ 2 Horizontal stab

‣ 1 Tail fin

‣ 1 Fuselage

‣ 1 Pitot tube


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Run-time algorithm

Integration


For each helicopter control point:

• Evaluate distance between hc point and grid points

• Identify the 8 grid points closest to hc point and extract wind components on these points

• Calculate wind components in hc point using a linear interpolation weighted on distance of the 8 points previously selected

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Unsteady effects

Integration


• Stationary CFD approach:

‣ Best trade-off between run-time requirements and our goal of improving fidelity of simulation during takeoff, approach and landing

‣ Unsuitable to reproduce unsteady micro-instabilities typical of flight in these conditions

• Our solution:

‣ Run-time evaluation of statistical indicators of velocity components in 95 hc control points

‣ Development of an algorithm on the basis of statistical indicators to add different intensities of turbulence to the flight model

‣ Turbulence is obtained by passing band-limited white noise though appropriate forming filters, according to military specification MIL-F-8785C

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Results and Validation

Conclusions


• OpenFOAM range of features provide us all the capabilities to obtainthe best compromise between fidelity level and simulation real-timerequirements

• OpenFOAM allows us to perform about 1000 CFD computation in anacceptable timeframe

• Successfully integration within Full Flight Simulator real-time software

• Very positive pilots’ evaluation during all takeoff\landing\approachesnear oil rigs and ships

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Future applications

Conclusions


New challenge: urban environments

• Stereolithography (STL) format models generation of a wider area

• Higher computational effort

• Trade-off between grid discretization and run-time environment

• Validation of results by test pilots

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Copyright © ESI Group, 2015. All rights reserved. ESI OpenFOAM User Conference 2015 – October 19 – 21 in Stuttgart, Germany

THANK YOU FOR YOUR ATTENTION

Wind characterization around offshore platform for real-time

helicopter simulator

wind characterization around offshore platform for real-time helicopter simulator

Engineering