Predicting Offshore Topside Wind Loading Using AcuSolve · PDF filePredicting Offshore Topside Wind Loading . Using AcuSolve . Abdel Fiala – CFD Technical Specialist . September

Predicting Offshore Topside Wind Loading Using AcuSolve

Abdel Fiala – CFD Technical Specialist

September 2nd, 2014

Copyright © 2014 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.

Content

Objective

Geometry

Modelling conditions

CFD models

Results and analysis

Conclusion


Objective

• To demonstrate the utility of CFD using AcuSolve in improving the prediction of wind loading on typical large offshore platform topside

• Current wind loading assessment is based on semi-empirical methods, nowadays widely used in the offshore industry. These tend to over-estimate wind loading on the topside structure

• This translates in to large safety factors and over-design of the structural components sustaining the stresses due to wind loading

• CFD simulation aims at reducing or disposing off this over-prediction

• No experimental data are available. Hence, comparison is made against the semi-empirical data available.

• A thorough investigation of CFD modelling/simulation parameters, such as mesh size, unsteadiness, timestep size, and turbulence modelling, is conducted to increase the reliability of the results obtained.


Digression: Validation of AcuSolve

JFE-2011 “Detached Eddy Simulation of Atmospheric Flow About aSurface Mounted Cube at High Reynolds Number”


Digression: Airflow around a building (JJ Tower)

.

Acusolve: CFD simulation is performed to evaluate the positioning of the JJ tower in the city


AcuSolve for External Air Flow – Terrain


Geometry

• Model consists of an assembly of rectangular blocks of 14 x 30 x 10 m3 in x, y, z respectively

• Maximum size is 70 x 60 x 40 m3 in x, y, z respectively.

• Reference elevation = 25m

M01

M11

M21

M31

M02 M03 M04 M05 M06

M16 M12 M13 M14

M26


CFD Geometry

• Model elevation = 25m above sea level

• External domain 1120 x 660 x 465 m3

• Sea is considered a flat wall (no waves)

• No sea current; Vsea = 0

• Wind directions investigated: +X, +Y, +XY, and -X.


Modelling Conditions

• Wind loading is based on 1-hour mean wind speed for the topside model

• This is initially applied on the model in the +X direction for the CFD modelling investigation

• Thereafter, it is applied in the +Y, +XY (45deg) and –X directions.

• No data on freestream turbulence are available

• A freestream turbulence viscosity ratio (VR) of 10 is used for the main CFD modelling investigations

• Effect of freestream turbulence is assessed; VR between 10 and 1e6


• Due to the lack of experimental data to compare directly to, an in-depth investigation of CFD methodology is conducted; wind in +X direction:

Mesh size dependency

Steady-state vs transient. The latter using Unsteady RANS turbulence model

Timestep size dependency for transient

Turbulence modelling o Freestream turbulence level

o Transient URANS vs DES turbulence RANS: Spalart-Allmaras model

DES: Delayed DES based on Spalart et al. (2006)

• Results are compared against data based on semi-empirical methods

CFD Models

M01

M11

M21

M31

M02 M03 M04 M05 M06

M16 M12 M13 M14

M26

Wind load (MN) winward leeward winward leeward winward leeward winward leewardTotal base shear along Y-axis (MN)Total base shear along X-axis (MN)Total base shear @ 45degs (MN)

+ve Y-axis45degs

+ve X-axis

6.2558.708

8.041

+ve Y-axis +ve X-axis±ve X-axis


1. Effects of CFD modeling parameters


Transient Time Step Size Effects

• An initial mid mesh size, without edge refinement, was used for this specific exercise

Number of Elements (million)

Max Surface Element Size

(m)

b.l. First Layer Height

(mm)

14.1 1.0 4.0

Timestep Size, Δt (ms)

Wind Load (MN)

Moment about Y-axis (MN.m)

Coarse (Run 03) 50.0 6.333 276.4 Mid (Run 04) 25.0 6.339 276.1 Fine (Run 05) 12.5 6.351 277.4

Largest difference - 0.018 1.3

Largest difference 0.3% 0.5%

• Very little effect on wind loading and Y-moment, with <<1% difference.


• All transient solutions converge towards steady-state

Transient Time Step Size Effects

zoom

zoom


• The solution shows very little sensitivity to mesh size in both steady-state and transient modes.

Mesh Size Effects

Steady-State Number of Elements (million)


(m)


(mm)

Wind Load (MN)

Moment about Y-axis

(MN.m)

Coarse (Run11) 8.2 2.0 8.0 6.397 276.6 Mid (Run 09) 27.9 1.0 4.0 6.459 280.2 Fine (Run 10) 119.2 0.5 2.0 6.501 282.5

≠ Coarse to fine - - - 1.6% 2.1%

Transient (Δt = 25ms)

Number of Elements (million)


(m)


(mm)

Wind Load (MN)

Moment about Y-axis

(MN.m)

Coarse (Run13) 8.2 2.0 8.0 6.408 277.3 Mid (Run06) 27.9 1.0 4.0 6.454 280.0

Fine (Run 07) 119.2 0.5 2.0 6.482 281.7 ≠ Coarse to fine - - - 1.2% 1.6%


Steady-state Transient Δt = 25ms

Mesh Size Effects – Solution History


Mesh Size Effects (Coarse)


Mesh Size Effects (Mid)


Mesh Size Effects (Fine)


• Very similar surface pressure distributions with some small differences in surface streak-lines; separation and reattachment lines.

Mesh Size Effects – Pressure/Streak-lines


• Separation right off the corners of the windward face => Large wake => Wind loading mainly consists of “form” drag.

Mesh Size Effects – Velocity Field


Mesh Size Effects – Performance

Steady-State Running CPU (sec) Cores Running CPU

(hour) Timesteps Physical Time (sec)

Coarse (Run 11) 2196 16 0.61 47 - Mid (Run 09) 4855 64 1.35 56 - Fine (Run 10) 30854 64 8.57 65 -

Transient (Δt = 25ms)

Coarse (Run 13) 201110 16 55.9 2800 70 Mid (Run 06) 154487 64 42.9 2800 70 Fine (Run 07) 335864 128 93.3 2800 70

Number of Elements (million) Number of Nodes (million) Meshing CPU (min) Meshing Memory (MB)

Coarse 8.237 1.413 1.67 2808 Mid 27.92 4.760 5.95 8962 Fine 119.25 20.11 23.2 36495

Running on cluster of Intel® Xeon® Processor E5-2670 (8-core 20M Cache 2.60 GHz)

Meshing on desktop with Intel i7-4820K quad core CPU @ 3.7GHz


Transient vs Steady-State

• Very little difference is seen between the steady-state and transient solutions; < 0.3% difference

• Using URANS turbulence model, there is little unsteady behaviour in the flowfield to require fully transient solution.

Δ Transient – Steady-state

Wind Load (MN)

Moment about Y-axis (MN.m)

Coarse (Runs 13 - 11) 0.011 (0.2%)

0.7 (0.3%)

Mid (Runs 06 - 09) -0.005 (<0.1%)

-0.2 (<0.1%)

Fine (Runs 07 - 10) -0.019 (-0.3%)

-0.8 (-0.3%)


• At the end of the transient run, the flowfield settles into a steady-state

Transient vs Steady-State


2. Freestream Turbulence Level


Freestream Turbulence (Steady-State Mid Mesh)

• There is a clear trend in wind loading and Y-moment as functions of freestream turbulence level,

• Yet, little effect (<3%) in the range [10,1e6] of freestream viscosity ratio. Run Number Inlet νt Inlet νt/ν Wind Loading (MN) Moment-Y (MN.m)

run09 1.454E-04 1.E+01 6.459 280.2run14 1.454E-01 1.E+04 6.477 280.6run19 1.454E+00 1.E+05 6.502 281.5run18 1.454E+01 1.E+06 6.627 282.6

Difference (18 -09) 2.6% 0.9%


Freestream Turbulence – νt/ν = 1e6

• The little effect of freestream turbulence level is due to: Even larger turbulence level generated in the wake behind the model, Wake-dominated or “form” (in contrast to skin-friction) drag based wind loading.


3. Detached Eddy Simulation (DES) High Fidelity Turbulence Modelling


DES Turbulence – Mid Mesh ; Δt = 25ms

• Mid mesh was used:

• Same timestep size as the URANS simulation, i.e., Δt = 25ms

• Inlet B.C. identical to that of the URANS simulation, i.e., constant Eddy viscosity with νt /ν = 10.

• No synthetic turbulence imposed at inlet

• Initial condition: URANS transient solution


DES Turbulence – Solution History

Close-up

Close-up

280-timestep average

280-timestep average


• There is < 5% increase in average wind loading using DES. • Maximum instantaneous wind loading shows ~10% rise compared with

the steady-state value

• RANS : Steady-state Spalart-Allmaras turbulence model • URANS : unsteady (transient) Spalart-Allmaras turbulence model • DES : Delayed DES formulation of Spalart et. al., published in 2006

Max Surface Element Size (m)

First Layer Height (mm)

Wind Load (MN)

Y-moment (MN.m)

RANS 1.0 4.0 6.459 280.2 URANS 1.0 4.0 6.454 280.0

DES

AVG 1.0 4.0 6.748 307.4 MAX 1.0 4.0 7.135 370.4 MIN 1.0 4.0 6.282 246.6

Standard deviation - - 0.134 21.24

DESavg – RANS - - - 4.5% 9.7% DESmax – RANS - - - 10.5% 32.2%

DES Turbulence – Summary of Data


• About 80% increase in CPU time from URANS to DES simulation.

Running CPU (sec) Cores Running CPU

(hour) Timesteps Timestep Size (ms)

Physical Time (sec)

RANS 4855 64 1.35 56 - - URANS 154487 64 42.9 2800 25 70

DES 281186 128 78.1 5600 25 140

Running on cluster of Intel® Xeon® Processor E5-2670 (8-core 20M Cache 2.60 GHz)

DES Turbulence – Performance


DES Turbulence – Iso-Surface

• Iso-Surface of X-velocity; -1m/s • Coloured in pressure level


Velocity Field – URANS


• More unsteady (instantaneous) turbulent flow structures are captured.

Velocity Field – DES


Wind Direction (+Y) (90deg rotation about Z axis)


Wind Direction (+Y) – Model Configuration


Wind Direction (+Y)

• Freestream turbulence viscosity ratio = 10.

X moment

Wind Loading



(m)


Wind Load (MN)

Moment about X-axis

(MN.m)

Run 15 27.9 1.0 4.0 4.450 -187.3


Wind Direction (+Y)


Wind Direction (+XY) (45deg rotation about Z axis)


Wind Direction (+XY) – Model Configuration


Wind Direction (+XY)




(m)


Wind Load (MN)

Run 16 27.9 1.0 4.0 6.255


Wind Direction (-X) (180deg rotation about Z axis)


Wind Direction (-X)




(m)


Wind Load (MN)

Run 24 27.9 1.0 4.0 4.771


• A completely different flowfield.

Wind Direction (-X)

-X wind +X wind


Summary of Results

• CFD shows up to 45% reduction in the predicted wind loading compared with the semi-empirical data.

Wind Load +X (MN)

Wind Load -X (MN)

Wind Load +Y (MN)

Wind Load +XY (MN)

RANS - 6.459 4.771 4.450 6.255

DES AVG 6.748 - - - MAX 7.135 - - -

Semi-Empirical (SE) - 8.708 8.708 6.255 8.041

RANS – SE - -26% -45% -29% -22% DESavg – SE - -23% - - - DESmax – SE - -18% - - -


Concluding Remarks

• With Altair’s AcuSolve, CFD was used to predict wind loading on typical topside of offshore platform structure

• The predicted wind loading and moment show small to no dependency on mesh size, timestep size, steady-state vs transient, freestream turbulence level, and turbulence model

• This pertains to the fact that for this specific and typical geometry, wind loading mainly consists of “form” (pressure) drag, as a result of the large separation off the corners of the windward face

• The CFD results show a reduction of up to 45% in wind loading prediction compared to semi-empirical methods currently adopted by industry


Concluding Remarks

• It is clear that CFD becomes increasingly relevant and imperative with increasing complexity of the topside geometry

• Steady-state RANS should be used for a quick prediction of the wind loading on such structures

• For more detailed and accurate prediction, the DES transient approach should be adopted.


Future Work? Methane Dispersion example: Airport Terminal Exhaust Simulation – cut plane at 1 m height of 1%


Documents

Predicting Offshore Topside Wind Loading Using AcuSolve · PDF filePredicting Offshore Topside Wind Loading . Using AcuSolve . Abdel Fiala – CFD Technical Specialist . September