Reports of Research Institute for Applied Mechanics, Kyushu University, No.150 (60-70) March 2016

Reproducibility of Complex Turbulent Flow
Using Commercially-Available CFD Software―Report 2: For the Case of a Two-Dimensional Ridge With Steep Slopes―
Takanori UCHIDA*1
E-mail of corresponding author: takanori@riam.kyushu-u.ac.jp(Received January 29, 2016)
Abstract
Choosing appropriate sites for wind turbines is extremely important in Japan because the spatial distribution of windspeed is highly complex over steep complex terrain, which is abundant in Japan. The author's research group has beendeveloping an unsteady CFD software package called RIAM-COMPACT®. This package is based on an LES
turbulence model. In this paper, to examine the accuracy of RIAM-COMPACT®, numerical simulations of uniform,
non-stratified airflow over a two-dimensional ridge were performed. The analysis primarily focused on airflow
characteristics in the wake region. The results from the simulation with RIAM-COMPACT® were compared to thosefrom a commercially-available CFD software package (STAR-CCM+), and no significant differences were foundamong these results.
Key words: Commercially-available CFD software, STAR-CCM+, RIAM-COMPACT®, Ridge model

1. Introduction
The author's research group has developed the numerical

2. Summary of Commercially-Available
CFD Softwarewind diagnosis technique named RIAM-COMPACT® 1, 2).

Commercially-available computational fluid dynamics

The core technology of RIAM-COMPACT® is under(CFD) software packages have been developed and used

continuous development at the Research Institute for Applied

mainly as design tools primarily in the automobile andMechanics, Kyushu University, Japan. An exclusive license

aviation industries up to the present time. The following is aof the core technology has been granted by Kyushu TLO Co.,

list of the major CFD software packages available on theLtd. (Kyushu University TLO) to RIAM-COMPACT Co.,

market:Ltd. (http://www.riam-compact.com/), a venture corporation
which was founded by the author and originated at Kyushu

General-purpose CFD thermal fluid analysis software

University in 2006. A trademark, RIAM-COMPACT®, and apackagesutility model patent were granted to RIAM-COMPACT Co.,
Ltd. in the same year. In the meantime, a software package■STAR-CCM+

has been developed based on the above-mentioned technique

http://www.cd-adapco.co.jp/products/star_ccm_plus/index.

and is named the RIAM-COMPACT® natural terrain version

html

software. Efforts have been made to promote this software asa standard software package in the wind power industry.
In the previous paper2), a numerical simulation was■ANSYS(CFD, Fluent, CFX)
http://ansys.jp/solutions/analysis/fluid/index.html

performed for airflow around an isolated-hill with a steep■SCRYU/Tetra

slope angle using RIAM-COMPACT® natural terrain

http://www.cradle.co.jp/products/scryutetra/

version, and the results were compared to those from■STREAM

numerical

http://www.cradle.co.jp/products/stream/index.html

simulations

performed

using

anothercommercially-available CFD software package. In the present
paper, a similar study is conducted for airflow over a ridge,
the shape of which is identical to the shape created byextending the central cross-section of the isolated-hill fromthe previous paper2) continuously in the spanwise (y)direction. The results of the comparisons are discussed.
*1 Research Institute for Applied Mechanics, Kyushu University■CFD2000
http://www.cae-sc.jp/docs/cfd2000/index.htm■PHOENICS
http://www.phoenics.co.jp/

Reports of Research Institute for Applied Mechanics, Kyushu University, No.150 March 2016

61

■Autodesk Simulation CFD

available CFD software packages. The results of the

http://www.cfdesign.com/

comparison are discussed.

■CFD++
http://bakuhatsu.jp/software/cfd/■CFD-ACE+
http://www.wavefront.co.jp/CAE/cfd-ace-plus/■AcuSolve
http://acusolve.jsol.co.jp/index.html■FLOW-3D

3. Summary of STAR-CCM+ Software
In this section, a summary of STAR-CCM+, a generalpurpose thermal fluid analysis software package distributedby CD-adapco is provided (see Table 1). The version of thesoftware package used in the present study is 8.02.008 (for64-bit Windows).
STAR-CCM+ uses a single graphical user interface (GUI)

http://www.terrabyte.co.jp/FLOW-3D/flow3d.htm

for computational grid generation, execution of fluid■FloEFD

analyses, and data post-processing. The grid generation

http://www.sbd.jp/product/netsu/floefd3cad.shtml

method in STAR-CCM+ is distinctive. In STAR-CCM+,■Flow Designer

both a polyhedral grid and a prism layer grid can be used (forhttp://www.akl.co.jp/

example, see Fig.3). The polyhedral grid is a new type of■PowerFLOW
http://www.exajapan.jp/pages/products/pflow_main.html

grid offered and promoted by CD-adapco and consists ofpolyhedral cells which possess 10 to 15 faces on average.
The use of this cell type makes it possible to dramatically■KeyFlow

reduce 1) the number of grid cells required to obtain analysis

http://www.kagiken.co.jp/product/keyflow/index.shtml

results equivalent to those that can be obtained using a■OpenFOAM

conventional tetrahedral grid and 2) the memory required by

http://www.cae-sc.jp/docs/FOAM/

the solver. With the use of this cell type, the computational■FrontFlow
http://www.advancesoft.jp/product/advance_frontflow_red/
The wind power industry has independently developed anddistributed CFD software designed for selecting sites
appropriate for the installation of wind turbines (see the list
below). Recently, some of the above-listed general-purpose
thermal fluid analysis software packages have also started
being adopted in the wind power industry.

stability improves significantly, and the time required toobtain convergent solutions also decreases. The prism layer
grid is a refined grid designed to capture the behavior of theboundary layer that develops over the surface of an object. In
this type of grid, layers of thin grid cells are distributed
regularly over the object. Since the thickness and number oflayers in the normal direction with respect to the object
surface can be freely adjusted, the behavior of the boundary
layer in the vicinity of a wall can be captured with highaccuracy. However, when the number of prism layer grid

CFD software packages designed for the wind power industry

cells is very large, the computation time increases(wind farm design tools)

significantly.
Numerical simulations are based on the finite-volume■RIAM-COMPACT®

method (FVM), and the Navier-Stokes equation is used as

http://www.riam-compact.com/

the governing equation. Iterative calculations are performed■MASCOT
http://aquanet21.ddo.jp/mascot/

for the velocity and pressure fields using an algebraic
multi-grid (AMG) linear solver. For the time marching
method, a first-order implicit method is used. STAR-CCM+■WindSimcan be run either with a Reynolds-averaged Navier-Stokes

http://www.windsim.com/(RANS) turbulence model or a large-eddy simulation (LES)■METEODYN

turbulence model. For the convective term in the

http://meteodyn.com/

RANS models, a second-order upwind scheme is adopted.
For the convective term in the LES models, a bounded

In the present paper, the simulation results from RIAM-

central differencing (BCD) scheme is employed. Table 1

COMPACT® natural terrain version are compared to thoseshows an overview of the computational techniques,from STAR-CCM+, one of the leading commercially-

62

Uchida : Reproducibility of Complex Turbulent Flow Using Commercially-Available CFD Software, Report 2

parameters, and simulation set-up used for one of thegroup, will be described. In this software package, asimulations performed with STAR-CCM+ in the present

collocated grid in a general curvilinear coordinate system isstudy, namely the simulation with a steady RANS turbulence

adopted in order to numerically predict local wind flow overmodel, as an example.

complex terrain with high accuracy while avoiding
numerical instability. In this collocated grid, the velocity

Simulation code
Governing equation

STAR-CCM+ v.8.02.008

components and pressure are defined at the grid cell centers,

Three-dimensional unsteadyand variables that result from multiplying the contravariant

Navier-Stokes equation

velocity components by the Jacobian are defined at the cell

Steady RANS
Turbulence modelTime marching

on

the

filter is applied to the flow field to separate eddies of various

1. First-order implicit

scales into grid-scale (GS) components, which are larger

unsteady analysis

than the computational grid cells, and sub-grid scale (SGS)

2. Steady analysis(The steady-state solution is
obtained by specifying thenumber of time steps.)

components, which are smaller than the computational gridin non-dimensional time)

2. Spin-up: 0 – 2000

upwind scheme
Discretization of the(No options available

convective termother than first-order andsecond-order
upwind schemes)

Gas

Constant density

Density ρ

1.0 [kg/m3]

Coefficient of viscosity μ

1.0 × 10-5 [Pa•s]

Ridge model height h

0.1 [m]Inflow wind velocity U

1.0 [m/s]∆ｔ = (∆t U) / hbased

turbulence model)

A second-order

Number of grid cells

isadopted for the turbulence model. In LES models, a spatial

in time step number(Time averaging: 2000 4000 in time step number)

Non-dimensional time step

technique(Spalart-Allmaras(Time averaging: 100 – 200s

= U h (ρ / μ) = U h / νnumerical

one-equation eddy-viscosity

in non-dimensional time

Reynolds numberThe

finite-difference method (FDM), and an LES model is

1. Spin-up: 0 – 100s

Duration of simulation

faces.

cells. Large-scale eddies, i.e., the GS components of
turbulence eddies, are directly numerically simulated
without the use of a physically simplified model. In contrast,
dissipation of energy, which is the main effect of small-scaleeddies, i.e., the SGS components, is modeled according to aphysics-based analysis of the SGS stress.
For the governing equations of the flow, a spatially-filteredcontinuity equation for incompressible fluid (Eq.(1)) and a
spatially-filtered Navier-Stokes equation (Eq.(2)) are used.

ui
0
x i

ij
ui
ui
p
1 2 ui
 uj



t
x j
x i Re x jx j x j

Approx. 1.5 million

Table 1 Overview of STAR-CCM+, for the case of thesimulation using a steady RANS model in the present study

1 ' 'u k u k ij  2SGS Sij
3

ij  u 'i u 'j SGS   Cs fs   S2

S  2SijSij

1.0 × 10４
2.5 × 10-2

-(1)

Sij 

1/2



-(5)

1  u i u j 2  x j x i   hx h yhz



1/3

-(3)

-(4)



fs  1  exp  z  / 25

-(2)

-(6)



-(7)
-(8)

4. Summary of RIAM-COMPACT® Software
In this section, a summary of RIAM-COMPACT®
natural terrain version, developed by the author's research

For the computational algorithm, a method similar to a
fractional step (FS) method is used, and a time marching
method based on the Euler explicit method is adopted. The

Reports of Research Institute for Applied Mechanics, Kyushu University, No.150 March 2016

63

Upper and lateral boundaries:
free-slip condition

Inflow boundary:uniform inflow condition

Outflowboundary:
convective
Origin of coordinate
systemGround surface:no-slip condition

Fig.1 Computational domain, coordinate system, boundary conditions, and other related information
Poisson’s equation for pressure is solved by the successive

outflow boundaries, respectively. At the ground surface,over-relaxation (SOR) method. For discretization of all thenon-slip boundary conditions are imposed. The Reynolds

spatial terms except for the convective term in Eq.(2), a

number is set to Re (= Uh / ν) = 104, where h is the ridge

second-order central difference scheme is applied. For theheight and U is the wind speed at height h at the inflow

convective term, a third-order upwind difference scheme isboundary. The time steps are set to Δt = 2 × 10-3 (h / U) andapplied. An interpolation technique based on four-point

Δt = 2.5 × 10-2 (h / U) in the simulations with RIAM-

differencing and four-point interpolation by Kajishima is used

COMPACT® and STAR-CCM+, respectively.

for the fourth-order central differencing that appears in theFig.2 shows the computational grid (structured grid) useddiscretized form of the convective term. For the weighting offor the simulation with RIAM-COMPACT®. The number ofthe numerical diffusion term in the convective term

grid points used for this simulation is 326 (x) × 226 (y) × 67

discretized by third-order upwind differencing, α = 3.0 is(z) (approximately 5 million points in total). The grid points

commonly applied in the Kawamura-Kuwahara scheme.

in the x- and y-directions are spaced at an even interval of

However, α = 0.5 is used in the present study to minimize the

0.04h, and the grid points in the z-direction are spaced at

influence of numerical diffusion. For LES subgrid-scale

uneven intervals ranging from 0.003h to 0.6h.

modeling, the standard Smagorinsky model is adopted with a

For comparison, Fig.3 shows the computational gridmodel coefficient of 0.1 in conjunction with a wall-damping(unstructured grid) used for the simulation with STAR-

function.

5. Flow Field and Simulation-setup
Considered in the Present StudyIn this section, the flow field, coordinate system, andsimulation-setup considered for the present study aredescribed (Fig.1). The streamwise (x) cross-section of thehα ≈ 40ºa = 2hridge is identical to the central cross-section of the hill fromthe previous study2) .

Fig.2 Computational grid in the vicinity of the ridge from theRegarding the boundary conditions, uniform inflow

simulation with RIAM-COMPACT®, structured grid,conditions, free-slip conditions, and convective outflow

central plane (y = 0) normal to the spanwise (y) axis

conditions are applied at the inflow, lateral and upper, and64

Uchida : Reproducibility of Complex Turbulent Flow Using Commercially-Available CFD Software, Report 2
the use of a wall damping function and 2) the eddy viscosity
coefficient is not calculated for laminar shear flow.
Spalart-Allmaras one-equation
Case 1eddy-viscosity turbulence model:

RANS

steady RANS

modelsSST k-ω two-equation eddy
Case 2-viscosity model: unsteady RANS(URANS)(a) Side view (y = 0), overall view

LES model

Case 3
Case 4Standard Smagorinsky model:
LES
WALE model: LES

Table 2 Turbulence models used in the simulations with
STAR-CCM+
Prism layer setting
thickness
h×8%
number of25
layersLES model

Case 5

Standard Smagorinsky model:
LES

Table 3 Turbulence model used in the simulation with
RIAM-COMPACT®

(b) Side view (y = 0), enlarged view

6. Simulation Results and Discussion
First, flow patterns generated in the vicinity of the ridge
considered in the present study are described (Fig.4). The
qualitative behaviors of the flows numerically simulated by
RIAM-COMPACT® and observed in a wind tunnel
experiment resemble each other quite closely. As was thecase in the previous study2), the shear layer which separated
from the vicinity of the ridge top rolls up into isolated
vortices (indicated by arrows in Fig.4 (b)). These isolated(c) Top view (z = 0.5h), overall viewFig.3 Computational grid used for the simulation with
STAR-CCM+, unstructured gridvortices then form into large-scale vortices, which areperiodically shed downstream of the ridge. Refer to Uchida etal.2) for detailed comparisons between the results of the

CCM+. The total number of grid points is approximately 1.5
million (1/3 of that used for the simulation with RIAMCOMPACT®). The grid resolution in the vicinity of the ridgein the simulation with STAR-CCM+ is set to be nearly
identical to that with RIAM-COMPACT®.

(a) Wind tunnel experiment, smoke-wire method
Flow

Tables 2 and 3 list the turbulence models (RANS and LES
models) considered in the present comparative study. For
convenience, simulations performed with the use of each of
the models are referred to as Cases 1 to 5. The models
considered in the present study are the same as those from theprevious study2). A brief description of the WALE model
used in Case 4 is as follows: the WALE model has been(b) Numerical simulation (RIAM-COMPACT®),
passive particle tracking

designed in such a way that 1) the eddy viscosity coefficientFig.4 Visualization of the flow field

becomes zero in the vicinity of the ground surface without

in the vicinity of the ridge; instantaneous fieldReports of Research Institute for Applied Mechanics, Kyushu University, No.150 March 2016

65

simulation with RIAM-COMPACT® and those from thefor the vertical profiles of the standard deviation of thewind tunnel experiment.

streamwise (x) wind velocity component (not shown).

Due to space limitations, Figs.5 and 6 compare theRegarding the computational time, although the number

simulation results only from Case 1 (STAR-CCM+ with theof grid points used for the simulation with RIAM-

steady RANS model; a steady simulation in which the

COMPACT® (structured grid, approximately 5 million gridsteady-state solution is obtained by using the number of time

points) was approximately three times as large as that usedsteps specified in Table 1 for time marching) and Case 5

for the simulations with STAR-CCM+ (unstructured grid,(RIAM-COMPACT® with the LES model) here as an

approximately 1.5 million grid points), the simulation with

example. Fig.7 compares the vertical profiles of the mean

RIAM-COMPACT® completed much faster than those withstreamwise (x) velocity from all the cases (Cases 1 to 5). In

STAR-CCM+, as was the case in the previous study2).

Figs.5 to 7, the time-averaged flow field and turbulence
statistics for Case 5 (RIAM-COMPACT® with the LES
model) were evaluated from the time period t = 100 - 200

7. Conclusion(h/U), An examination of Figs. 5 to 7 reveals, in contrast to

In the previous study2), the simulation results fromthe previous study2), no significant difference between the

RIAM-COMPACT® natural terrain version of airflow

results from the simulation which used the steady RANS

around an isolated-hill with a steep slope angle weremodel (Case 1) and those from the RIAM-COMPACT®

compared to those from another commercially-available

simulation, which used the Smagorinsky LES model (Case 5),

CFD software package (STAR-CCM+).

indicating that the overall trends of the flow field are similar
between the two cases.

In the present paper, in order to examine the prediction
accuracy of RIAM- COMPACT® (turbulence model: theThe previous study2) investigated airflow around a

standard Smagorinsky LES model), developed by thethree-dimensional isolated-hill, and thus, the investigatedauthor's research group, simulations were performed withflow field was complex with the co-existence of various

RIAM-COMPACT® and STAR-CCM+ for airflow over akinds of airflow including flow over the hill and flow aroundridge. The shape of the ridge is identical to the shape createdthe hill. Probably because of this complex flow field,by extending the central cross-section of the isolated-hillsignificant differences arose between the results from thefrom the previous study2) continuously in the spanwise (y)simulations which used the RANS models (i.e., the steadydirection. The simulation results were then compared.

and unsteady RANS models) and those from the simulations

For the simulations with STAR-CCM+, both RANS andwhich used the LES models (i.e., the standard Smagorinsky

LES turbulence models were adopted. Specifically, for theand WALE models).

RANS turbulence model, two such models were selected forSince numerical simulations performed in the wind power

use: the Spalart-Allmaras one-equation eddy-viscosity

industry are frequently for three-dimensional complex

model (steady RANS) and the SST k-ω two-equation

turbulent flow fields, the errors in the mean wind velocity

eddy-viscosity model (unsteady RANS). Similarly, for thepredicted using the RANS models in the previous study2)

LES turbulence model (SGS model), two such models werewould greatly affect assessments of the power to be generated

selected for use: the standard Smagorinsky model and theand other related variables. Therefore, it can be claimed that

WALE model.

the use of the LES models is effective for simulating highly
three-dimensional complex turbulent flow fields.

The comparisons of the simulation results revealed thefollowing findings. The significant differences which were

Although not shown here, as was the case in the previous

found for certain flow characteristics between the results ofstudy2), the vertical profiles of the standard deviation of thesimulations with the RANS models (the steady and unsteadystreamwise (x) wind velocity component evaluated from the

RANS models) and those with the LES models (theresults of the simulations in the present study which used the

Smagorinsky and WALE models) in the previous study2)

RANS models (i.e., the steady and unsteady RANS models)

were not found in the present study. The flow fields

showed no significant non-zero values at any position. As for

simulated with the use of the RANS models and those

the results of the simulations which used the LES models,simulated with the use of the LES models showed similar

those from STAR-CCM+ (the standard Smagorinsky andoverall trends.

WALE models) and those from RIAM-COMPACT® (theThe previous study 2) investigated airflow around a

standard Smagorinsky model) showed nearly identical trends

three-dimensional isolated-hill, and thus, the investigated66

Uchida : Reproducibility of Complex Turbulent Flow Using Commercially-Available CFD Software, Report 2

Flow(a) Case 1, Simulation results from STAR-CCM+ with the use of the steady RANS model,
Spalart-Allmaras one-equation eddy-viscosity turbulence model

-2h

0h

+4h

+8h

Height h(b) Case 5, Simulation results from RIAM-COMPACT® with the use of the LES model,
the standard Smagorinsky model, time-averaged field
Fig.5 Comparison of the streamwise (x) velocity component distribution,
central plane (y = 0) normal to the spanwise (y) axis.
Here, the velocity component is normalized by the magnitude of the uniform inflow wind velocity.

Reports of Research Institute for Applied Mechanics, Kyushu University, No.150 March 2016
Flow(a) Case 1, Simulation results from STAR-CCM+ with the use of the steady RANS model,
Spalart-Allmaras one-equation eddy-viscosity turbulence model

-2h

0h

+4h

+8h

Height h(b) Case 5, Smulation results from RIAM-COMPACT® with the use of the LES model,
the standard Smagorinsky model, time-averaged field
Fig. 6 Comparison of velocity vectors, central plane (y = 0) normal to the spanwise (y) axis.
Here, the velocity components are normalized by the magnitude of the uniform inflow wind velocity.

67

68

Uchida : Reproducibility of Complex Turbulent Flow Using Commercially-Available CFD Software, Report 2

STAR-CCM+
RIAM-COMPACT®

x=-2h

x=0h

Nearly the same values

Local increase in velocity

x=+4h
Similar trends between the
profiles from the simulations
with RANS and those with LES

x=+8hSimilar trends between the
profiles from the simulations
with RANS and those with LES

Reverse flow region

Fig. 7 Comparison of the mean streamwise (x) velocity profiles. Here, the velocity component is normalized
by the mean upper-air streamwise (x) velocity above the location of each profile evaluation.

Reports of Research Institute for Applied Mechanics, Kyushu University, No.150 March 201669

flow field was a complex turbulent flow field with the

COMPACT® was approximately three times as large

co-existence of various kinds of airflow including flow over(structured grid, approximately 5 million grid points) as thatthe hill and flow around the hill. Probably for this reason,

used for the simulations with STAR-CCM+ (unstructured

significant differences arose between the results from thegrid, approximately 1.5 million grid points), the simulation

simulations which used the RANS models and the resultswith RIAM-COMPACT® completed much faster than thosefrom the simulations which used the LES models in thewith STAR-CCM+, as was the case in the previous study2).

2)

previous study . Since numerical simulations in the wind

References

power industry are frequently performed for threedimensional, complex turbulent flow fields, the errors in themean wind velocity predicted using the RANS models in the1)

Takanori

UCHIDA,

Validation

Testingoftheprevious study2) would greatly affect assessments of thePrediction Accuracy of the Numerical Wind Synopsis

power to be generated and other related variables. Therefore,

Prediction Technique RIAM-COMPACT for the Caseit can be claimed that the use of the LES models is effectiveof the Bolund Experiment –Comparison against afor simulating highly three-dimensional complex turbulent

Wind-Tunnel Experiment–, Reports of RIAM, Kyushu

flow fields.

University, No.147, pp.7-14, 20142)

As was the case in the previous study , the vertical profiles

2)

Takanori UCHIDA, Reproducibility of Complexof the standard deviation of the streamwise (x) wind velocity

Turbulent Flow Using Commercially-Available CFD

component evaluated from the simulations which used theSoftware –Report 1: For the Case of a Three-

RANS models (i.e., the steady and unsteady RANS models)Dimensional Isolated-Hill With Steep Slopes–, Reports

showed no significant non-zero values at any position in theof RIAM, Kyushu University, No.150, in press, 2016

present study. As for the results of the simulations whichused the LES models, the trends of this variable from
STAR-CCM+ (the standard Smagorinsky and WALE
models) and those from RIAM-COMPACT® (the standard
Smagorinsky model) were nearly identical.
Regarding the computational time, although the numberof grid points used for the simulation with RIAM-

Appendix
In this appendix, comparisons are made between the results of the simulation with RIAM-COMPACT® (turbulence model: thestandard Smagorinsky LES model) from the present study and those from the wind tunnel experiment performed by the author
previously. In both Figs.8 and 9, the variables on the horizontal and vertical axes are normalized by the mean upper-air
streamwise (x) velocity, Uref, above the location of each profile evaluation and the height of the ridge, h, respectively. The
variable z* on the vertical axis represents the height above the flat surface.
The simulations in the present study are performed for airflow over a ridge, the shape of which is identical to the shape createdby extending the central cross-section of the isolated-hill from the previous study2) continuously in the spanwise (y) direction.
Therefore, both the simulation and wind tunnel results are more subject to the effect of the blockage ratio than those in theprevious study. Specifically, at the ridge top (Fig.8(b)), the wind speed-up ratio for the simulation is significantly overestimatedwith respect to that for the wind tunnel. As a result, differences in the flow field arise between the two results, including a
difference in the size of the vortex region downstream of the ridge (Figs.8(c), 8(d), 9(c), and 9(d)). Although theabove-mentioned differences in the flow fields exist, the overall trends of the flow fields are in agreement between the simulated
and wind-tunnel flows in Figs.8 and 9.

70

Uchida : Reproducibility of Complex Turbulent Flow Using Commercially-Available CFD Software, Report 2(a) x=-2h(b) x=0h(c) x=+4h(d) x=+8h

Fig.8 Comparison of the mean streamwise (x) velocity profiles,
filled circle: wind tunnel experiment, line: simulation with RIAM-COMPACT® (turbulence model: LES)(a) x=-2h(b) x=0h(c) x=+4h(d) x=+8h

Fig.9 Comparison of the standard deviation of the streamwise (x) velocity,
filled circle: wind tunnel experiment, line: simulation with RIAM-COMPACT® (turbulence model: LES)