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Contract No. DE-AC36-08GO28308

Summary of Conclusions and 

Recommendations Drawn from 

the DeepCWind Scaled Floating 

Offshore Wind System Test 

Campaign

Preprint

Amy N. Robertson, Jason M. Jonkman, 

Marco D. Masciola, and Paul Molta

National Renewable Energy Laboratory

Andrew J. Goupee and Alexander J. Coulling

University of Maine

Ian Prowell

MMI Engineering

James Browning

University of Colorado

Presented at the ASME 2013 32nd International Conference on 

Ocean, Offshore and Arctic Engineering

Nantes, France

June 9-14, 2013

Conference Paper

NREL/CP-5000-58076

July 2013
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SUMMARY OF CONCLUSIONS AND RECOMMENDATIONS DRAWN FROM THE 

DEEPCWIND SCALED FLOATING OFFSHORE WIND SYSTEM TEST CAMPAIGN

Amy N. Robertson

National Renewable Energy Laboratory

Golden, Colorado, U.S.A.

Jason M. Jonkman

National Renewable Energy Laboratory

Golden, Colorado, U.S.A.

Andrew J. Goupee

University of Maine

Orono, Maine, U.S.A.

Alexander J. Coulling

University of Maine

Orono, Maine, U.S.A.

Ian Prowell

MMI Engineering

Oakland, CA, U.S.A.

James Browning

University of Colorado

Boulder, CO, U.S.A.

Marco D. Masciola

National Renewable Energy Lab.

Golden, Colorado, U.S.A.

Paul Molta

National Renewable Energy Lab. 

Golden, Colorado, U.S.A.

ABSTRACT

The DeepCwind consortium is a group of universities, 

national labs, and companies funded under a research initiative 

by the U.S. Department of Energy (DOE) to support the 

research and development of floating offshore wind power. The 

two main objectives of the project are to better understand the 

complex dynamic behavior of floating offshore wind systems 

and to create experimental data for use in validating the tools 

used in modeling these systems. In support of these objectives,

the DeepCwind consortium conducted a model test campaign in 

2011 of three generic floating wind systems: a tension-leg 

platform (TLP), a spar-buoy (spar), and a semi-submersible 

(semi). Each of the three platforms was designed to support a 

1/50th-scale model of a 5-MW wind turbine and was tested 

under a variety of wind/wave conditions.

The focus of this paper is to summarize the work done by 

consortium members in analyzing the data obtained from the 

test campaign and its use for validating the offshore wind 

modeling tool, FAST. 

1. INTRODUCTION

The floating offshore wind power industry is still in a 

development stage. No commercial projects have been 

constructed, but demonstration projects such as Statoil’s 

Hywind and Principle Power’s WindFloat are building 

confidence in this industry. In addition, the DOE has awarded 

$4M of funding each to three floating demonstration projects in 

the United States to perform a one-year front end engineering 

study, with the potential of future deployment. 

The DeepCwind project represents a significant resource in 

the research and development of floating wind. It is the first 

project to offer public data of the response of floating offshore 

wind systems in a wave tank setting for use in validating

offshore wind modeling tools. Computer-aided-engineering 

(CAE) tools that model the coupled aerodynamic, 

hydrodynamic, control system, and structural response of 

floating wind systems are needed to develop innovative 

technologies that are reliable and cost effective. For CAE tools 

to be used effectively, their accuracy needs to be assured 

through verification and validation efforts. The DeepCwind 

model test campaign will provide data to the public so that 

anyone may use it in their validation efforts. In addition, the 

openness of the project provides an opportunity for researchers 

and developers to learn from the mistakes and issues 

encountered in the test program.

The DeepCwind test campaign was performed at the 

Maritime Institute of the Netherlands (MARIN) in Wageningen, 

the Netherlands. The turbine was a 1/50th-scale horizontal-axis

model of the NREL 5-MW Reference Wind Turbine [1] with a 

flexible tower affixed atop three distinct platforms: a TLP, spar, 

and semi. The three generic platform designs are intended to 

cover most of the popular concepts, each based on proven 

floating offshore structure technology. The models were tested 

under Froude-scaled wind and wave loads; see Jain [2] for 

more details on the scaling process. The high quality wind 

environments, unique to these tests, were realized in the 

offshore basin via a novel wind machine that exhibits negligible

swirl and low turbulence intensity in the flow field. Recorded 

data from the floating wind turbine models included rotor 

torque and position, tower-top and -base forces and moments, 

mooring line tensions, six-axis platform motions, and 

accelerations at key locations on the nacelle, tower, and 

platform. A large number of tests were performed ranging from 

simple free-decay tests to complex operating conditions with 

irregular sea states and dynamic winds.

The focus of this paper is an examination of the test data 

from the DeepCwind tests and ongoing efforts to validate the 

overall coupled offshore floating wind system solution of FAST

[3], a CAE tool for modeling offshore wind systems, which was 

developed by the National Renewable Energy Laboratory 

(NREL) with DOE support. The outline of the paper is as 

follows: the remainder of Section 1 will review the systems and 

tests performed in the basin, Section 2 will examine the system

response behavior, and Section 3 will examine current efforts to 

validate FAST using the test data. Finally, Section 4 will 
2 

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summarize conclusions and recommendations drawn from the 

DeepCwind test campaign.

1.1 Description of Systems

The approach for designing a floating offshore wind 

system is to create a structure with positive buoyancy and 

sufficient restoring stiffness to resist the overturning moments 

created from both the wind and the waves. In addition, the 

natural frequencies of the structure must be placed to minimize

excitation from the environmental conditions and periodic 

forcing from operation of the turbine. This includes avoiding 

wave frequencies of significant energy, from about 0.05 Hz up 

to 0.25 Hz (or 4 – 20 s), and the frequencies at which the blades 

pass the tower (commonly called 1P and 3P for the rotational 

frequency of the rotor and the frequency at which a single blade 

passes the tower, respectively). 

Figure 1. The three DeepCwind floating wind system 

designs, clockwise starting at left: spar, TLP and semi

The three systems tested in the DeepCwind measurement 

campaign span the space for how to achieve hydrostatic 

stability of the floating system in pitch and roll. The first is the 

TLP, which uses the approach of taut mooring lines and excess 

buoyancy to achieve hydrostatic pitch and roll stability (see 

Figure 1). The design is a generic one created by the University 

of Maine, but closely resembles Glosten’s PelaStar concept [4]. 

The second design is a spar concept, which is based on the 

OC3-Hywind spar [5], and achieves hydrostatic pitch and roll 

stability through a low center of mass (CM) far from the center 

of buoyancy. The third design is a semi-submersible created by 

Technip and the University of Maine, which achieves 

hydrostatic pitch and roll stability through a combination of low 

CM and a large water-plane inertia. It should be emphasized 

here that these models are generic, publicly available designs 

that were created to provide fairly realistic approximations to 

floating platforms being proposed for commercial development. 

Each of the three platforms was designed to support a 

1/50th Froude-scaled model of the NREL 5-MW reference 

turbine. Tables 1-3 summarize some of the main properties of 

the turbine and support structures. For more details on these 

structures, please refer to Martin [6]. Note that all values in this 

paper are reported at full scale unless otherwise stated, though 

the testing was performed at 1/50th scale.

Table 1. Properties of the wind turbine

Property Value

Rotor orientation, Configuration Upwind, 3 Blades

Control Fixed Speed

Rotor, Hub diameter 126 m, 3 m

Hub height 90 m

Freeboard to tower base 10 m

Overhang, Shaft tilt, Precone 10.58 m, 0°, 0°

Rotor mass 122,220 kg

Nacelle mass 274,940 kg

Tower mass 302,240 kg

Table 2. Properties of the platforms

Platform Properties (not 

incl. tower + turbine) TLP Spar Semi

Diameter of members (m)

6.5 

(column)

15 (tank)

6.5 to 9.4 

(tapered)

6.5 (main col.)

12 (offset col.)

24 (heave 

plates)

Draft (m) 30 120 20

Water displacement (m3) 2771 8029 13917 

Mass, incl. ballast (kg) 6.616E+5 7.281E+6 1.344E+7

Platform CM below SWL (m) 11.2 91.1 14.4

Roll inertia @CM (kg m2) 2.343E+8 3.966E+9 7.686E+9 

Pitch inertia @CM (kg m2) 2.208E+8 3.966E+9 8.335E+9 

Yaw inertia @CM (kg m2) 5.846E+7 9.860E+7 1.391E+10 

Number of mooring lines 3 3 3 

Depth to fairleads, anchors

( )

28.5, 200 70, 200 14, 200

Radius to fairleads, anchors 

( )

30, 30 5.2, 445 40.87, 837.6 

Unstretched line length (m) 171.4 424.4, 30 835.5 

Line diameter (m) 0.6 0.285 0.08 

Line mass density (kg/m) 301.2 43.5, 3.8 123.8 

Line extensional stiffness (N) 7.500E+9 9.67E+7 7.529E+8

System Properties

Total Mass (mt) 1361 7980 14040 

System CM below SWL (m) -34.1 76.3 9.9 
3 

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Table 3. Eigenvalues of each of the floating systems (Hz)

TLP Spar Semi Fixedbase

Surge 0.026 0.023 0.0093

Sway 0.026 0.023 0.0088

Heave 0.86 0.035 0.058

Roll 0.28 0.031 0.037

Pitch 0.27 0.031 0.037

Yaw 0.049 0.21 0.012

1st Tower Fore/Aft 1.32 0.43 0.35 0.29 

1st Tower Side/Side 1.30 0.44 0.38 0.29 

2nd Tower Fore/Aft 3.12 2.35 2.55 1.24 

2nd Tower Side/Side 3.24 2.39 2.66 1.24

1.2 Test Matrix

A large array of tests was performed at the MARIN wave 

basin for each of these three systems to characterize the 

behavior of the systems in a variety of conditions. The tests 

performed are summarized in Koo [7] and include:

• Hammer tests to identify natural frequencies

• Static offset and free-decay tests

• Wave-only tests using both regular and irregular waves 

(operational, survival, and white noise)

• Wind-only tests with both steady and dynamic wind

• Combined wind/wave tests, including bidirectional and 

oblique waves in addition to those listed above. 

The sampling frequency for most tests was 100 Hz at

model scale, corresponding to a Froude-scaled sampling 

frequency at full scale of roughly 14 Hz. The hammer tests 

were captured at 1000 Hz at model scale. All data from the 

MARIN tests were converted to full scale using Froude scaling 

prior to analysis [6]. 

1.3 Testing Issues

Because the DeepCwind tests are the first floating offshore 

wind tests to be open to the public, they provide an opportunity 

for others to learn from the issues encountered during the 

testing campaign. The following subsections describe some of 

the issues encountered.

Scaling of the Model

A major challenge in the scale-model testing of an offshore 

wind turbine that is excited both by wind and waves is deciding 

on the appropriate scaling approach for the experiment. For 

wind turbine testing, a scaling approach based on preserving 

the Reynolds number is typically used as this preserves the 

relationship of viscous and inertial forces for fluid flow. For 

offshore structural testing, however, a scaling approach based 

on preserving Froude number is more typical as this preserves 

the relationship between the gravitational and inertial forces of 

the waves. For the DeepCwind tests, a Froude-based scaling 

approach was used both to create the scaled geometry of the 

structure and to scale the environmental conditions of the tests. 

The drawback of a Froude-based scaling approach is that 

the turbine airfoils are scaled geometrically, which does not 

preserve their aerodynamic performance. Under Froudescaling, the Reynolds number at rated wind speed is severely 

reduced from 11.5 × 106 (turbulent flow) to 35.7 × 103 (laminar 

flow) [6]. Reducing the Reynolds number changes the lift and 

drag coefficients of the turbine blades, which determine the 

distributed forces the wind imparts on the blades. This drastic 

change in Reynolds number (between full and model scale) 

created a significant change in the lift and drag behavior for the 

airfoil sections, resulting in lower-than-desired values of 

generated torque and lift. Further discussion on this topic can 

be found in Molta [8]. 

To counteract the reduced aerodynamic forces on the 

turbine during testing, the wind speeds were increased to ensure 

appropriately scaled thrust forces, one of the key forcing 

components on the offshore wind system created by wind.

Model Fidelity

While not directly a testing issue, it is worth pointing out 

here that the wind turbine tested differed from a commercialscale turbine. First, to eliminate any issues associated with 

scaling the stiffness of the blades, the blades of the model 

turbine were made to be as rigid as possible. Second, the 

turbine was forced to rotate at the appropriate speed for a given 

wind condition (based on the tip speed ratio), rather than trying 

to achieve the correct torque on the blades from the wind. 

Finally, no control system was implemented on the turbine. 

Therefore, the blade pitch was kept constant for all tests, and no 

above-rated wind tests were run except for a shut-down 

condition. Non-automated pitching of the blades was possible, 

but it was found that this resulted in problems with pitch 

slippage.

Wind

The wind in the model basin was generated by fans, which

require special attention due to the recirculation of the wind 

field in the basin and the variation of the wind speed with the 

distance from the fans. For the DeepCwind tests, wind was 

generated by a bank of 35 fans with a honeycomb front plate to 

reduce swirl and a nozzle to reduce turbulence (Koo [7]). The 

output area of the nozzle covered the entire wind turbine rotor 

through its expected range of motion.

While the flow from the bank of fans was fairly consistent

with minimal swirl and an average turbulence of less than 5%, 

there were some drawbacks. The bank of fans needed to be 

placed high enough as to not interact with the water. This height 

decreased the wind speed on the lower portion of the rotor; 

thus, the nozzle was tilted downward by 2.16 degrees. This 

downward angle improved the wind speeds at the bottom of the 

rotor, but introduced a vertical component to the wind velocity. 

Even with this modification, wind speeds at the lower end of 

the rotor decreased by 20% and the turbulence intensity

increased to 15%. 
4 

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Instrumentation

The total topside mass (at full scale), which includes the 

wind turbine, tower and all accompanying instrumentation, is 

699,400 kg. This is 16.6% larger than the standard 

specifications for the combined NREL 5-MW Reference 

turbine and the OC3-Hywind tower, and was mostly a result of 

instrumentation cables. In addition to adding mass to the 

system, the instrumentation could have altered the dynamic 

response of the structure. As highlighted in the yellow circle in 

Figure 2 below, the cables used to record data from the turbine 

sensors were quite bulky. To mitigate the interaction of the 

cables with the dynamics of the system, the cables were 

attached to the tower, and then allowed to hang in a catenary 

configuration from a location just above the lower load cell. 

Though mitigation was attempted, it is likely that these cables 

altered the dynamics of the systems.

Figure 2. Sensor cable bundle for TLP

In addition, two load cells were placed at the connection 

points between the platform and the tower, and the tower and 

the turbine. The load cells enabled the measurement of tower 

loads/moments at the top and bottom, but also potentially 

induced compliance at the connection points, which could 

decrease the stiffness of the tower. 

Finally, the 6-degree of freedom (DOF) response motion of 

the platform was measured via an optical sensor pointed at the 

base of the tower. While this system worked well in general, it 

was not sensitive enough to accurately capture the very small 

pitching and rolling motions of the TLP.

Platform Designs

It should be emphasized that the platform designs used 

were generic ones, with very little optimization of the system 

properties. The goal was to find a good representation of the 

general types of platforms being used or proposed in the 

market, which are largely based on oil and gas industry

structures. However, the desire was to create systems that could 

be made available to the public and therefore did not rely on 

any proprietary information. As a result, the systems may not 

be sized or designed optimally for deployment. 

For instance, the semi-submersible system is heavier than 

one would expect for a commercial system. Also, the heave 

natural period is 17 seconds, which is within the normal wave 

frequency range. Placing system natural frequencies within the 

wave frequency range should be avoided to limit large 

excitation of the system. 

The TLP was designed to be quite small, and as a 

consequence, the mooring lines went slack during some 

extreme loading events. One of the reasons that slack-line 

events occurred is that the system was accidentally rotated 180 

degrees in its placement in the tank, with the mooring line 

aligned with the waves being placed in back of the turbine 

rather than in front. Slack-line events are to be avoided for TLP 

designs as the snap-back of the line can cause damage to the 

mooring line and induce broad-band frequency excitation in the 

system. The presence of a slack-line event therefore indicates 

that the TLP system would need to be modified before it could 

be used as a commercial design. 

The spar system did not have any major design limitations 

as it was more directly modeled after a commercial design, 

Statoil’s Hywind spar.

2. FLOATING SYSTEM BEHAVIOR 

The DeepCwind tests were useful in understanding how

different generic floating wind designs respond to a variety of 

wind/wave conditions—providing an indication of their relative 

performance. However, the systems were not optimized 

designs, and therefore do not necessarily reflect the most 

favorable aspects of a given design approach. With this 

limitation in mind, this section will highlight some of the 

behavioral properties and issues observed during the testing of 

the three floating systems.

2.1 Aerodynamic Response

The limitations of the wind excitation system used in the 

basin resulted in a wind field that was not entirely 

homogeneous across the rotor. This inhomogeneity is most 

easily seen in the response of the systems during steady, windonly tests by the presence of frequency peaks at one time (1P), 

six times (6P) and nine times (9P) the rotor’s rotational 

frequency. For example, Figure 3 shows the power spectral 

density (PSD) of the tower bending response of the semi under 

steady wind at 16.1 m/s. The rotor speed for this case was 9.19 

revolutions per minute (rpm), which results in a rotor frequency 

of 0.15 Hz with harmonics at 0.45, 0.90, and 1.35 Hz (3P, 6P, 

and 9P), all of which are clearly visible in Figure 3. For a 

homogeneous, steady-wind condition, only the 3P frequency 

should be present due to the dip in thrust as each blade passes 

the tower. The presence of harmonics means that for steady 

Load Cells

Cable Bundle
5 

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wind conditions, we will see excitation of the system at these 

frequencies.

The same wind-field generation system was used for all 

three designs, so, even with the limitations identified, one can 

compare the platform-restoring forces of the three systems by 

examining their response to steady wind conditions. Figure 4

shows the surge and pitch offsets of each of the systems due to 

steady wind at varying speeds, and the bending moment of the 

tower at its base. The surge response shows that the systems 

displace more as the wind speed increases (and the thrust force 

from the wind increases), until the speed of 30.5 m/s is reached, 

at which point the rotor is braked and has no rotational speed. 

One would expect mean thrust to peak at rated wind speed and 

then drop. Due to the problems with the thrust of the turbine 

mentioned earlier, the rated wind speed is at 21.8 m/s, which is 

quite a bit different than the specified value of 11.4 m/s for the

NREL 5-MW turbine. No above-rated wind cases were run 

(other than shut down) due to blade pitching issues.

The surge displacements are relatively similar between the 

three systems, with the spar displacement being the smallest. 

This is likely due to the fact that the stiffness in the pitch 

direction is small, and the system will therefore tend to pitch 

instead of surge. This is confirmed in the pitch response, where 

the spar clearly dominates. On the opposite extreme, the TLP 

has very little pitch motion due to the high stiffness provided by 

the taut mooring lines. The bending moment is highest for the 

spar system due to its large pitch angles, but all systems are 

fairly similar. It should be noted that the pitch motion of the 

systems is commonly decreased through control 

methodologies; however, no control was used here.

2.2 Response Amplitude Operators (RAOs)

The system response amplitude operators (RAOs) are a 

good means for understanding the behavior of an offshore wind 

system due to wave excitation. In the DeepCwind tests, two 

sets of white noise wave spectrums were used to excite the 

structure. Both were band-limited to excite frequencies between 

0.05 and 0.2 Hz (5-25 s period), which is considered a normal 

wave-frequency range, but were set to two different energy 

levels approximating a significant wave height of 7.1 and 11.3 

m. Figure 5 shows the RAOs computed from the lower of the 

two white noise tests, both with steady wind present (at 21.8 

m/s), and without. The RAOs were computed by dividing the 

response spectrum of a given DOF by the wave spectrum. 

The three systems were designed such that most of the 

system modes did not lie in the wave-excitation region, so one 

can see that there is little response in the 0.05-0.2 Hz range. 

The only exception is the semi heave natural frequency at 0.058 

Hz, which can be viewed in the heave RAO. Outside of the 

wave frequency range, several frequency peaks are seen, 

including the surge natural frequencies of all three systems 

(0.026 Hz – TLP, 0.023 Hz – Spar, 0.0093 Hz – Semi) in the 

7.32 8.94 11.2 16.1 21.8 30.5

0

2

4

6

8

Steady Wind (m/s)

Surge (m)

TLP

Spar

Semi

7.32 8.94 11.2 16.1 21.8 30.5

0

1

2

3

4

5

Steady Wind (m/s)

Pitch (deg)

TLP

Spar

Semi

7.32 8.94 11.2 16.1 21.8 30.5

0

2

4

6

8

10

x 104

Steady Wind (m/s)

Bending Moment (kN-m)

TLP

Spar

Semi

Figure 4. Steady-state response under steady winds for 

surge, pitch, and tower-base fore-aft bending moment

0 0.5 1 1.5

106

108

1010

Frequency (Hz)

Bending Moment (kN-m)2/Hz

Figure 3. Power-spectral density of the tower-bending 

moment

= Blade passing frequency 

(1P, 3P, 6P, 9P)
6 

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surge RAO, the pitch natural frequencies of all three systems 

(0.27 Hz – TLP, 0.031 Hz – Spar, 0.037 Hz – Semi) in the pitch 

RAO, the heave natural frequency of the spar (0.035 Hz) in the 

heave RAO, and the pitch and first tower-bending frequencies 

of the spar and semi (0.43 Hz and 0.35 Hz) in the tower-base 

bending moment RAO. The heave natural frequency and the 

first tower-bending moment of the TLP are not seen because 

they are above the 0.5 Hz frequency range shown here. The 

frequencies that are excited outside the wave frequency range 

likely indicate an excitation from second-order hydrodynamics, 

which will be discussed in the following sections. It is 

interesting to note that the second-order responses are just as 

significant as the heave response of the semi, which lies in the 

wave frequency region, indicating that it may be important to 

take into account second-order excitation in the design of an 

offshore wind system. 

In general, the RAOs of the systems were relatively 

unchanged by wind, except at the natural frequencies of the 

systems where the wind damped the response. The exception to 

this is foremost in the lower frequency range, which is where 

the wind energy is highest. Other regions where the wind 

increases system response include the spar surge response in 

the 0.035 to 0.05 Hz range, the pitch response of all systems in 

the wave-frequency range, the TLP heave response at the lower 

frequencies, and the spar heave response at its surge natural 

frequency (0.023 Hz). The most noticeable deviation is for the 

heave response of the TLP, but the response amplitude is very 

low.

2.3 Second-Order Hydrodynamics 

Linear hydrodynamic theory states that the hydrodynamic 

loads on an offshore wind turbine in an irregular sea can be 

approximated by superimposing the loads from individual 

regular wave components. This implies that only frequencies 

within the wave spectrum should be excited through 

hydrodynamic loading; but, as shown in the RAOs in Figure 5, 

in physical tests, frequencies outside the wave-frequency range 

are excited. This excitation arises from the interaction of the 

individual waves, which results in mean forces and forces 

oscillating at the differences and sums of distinct wave

frequencies. Second-order hydrodynamic theory captures these 

effects.

The presence of a mean force from the waves can be seen 

by the non-zero value of the surge in the wave-only RAOs in

Figure 5 at 0.0 Hz, though this could also be contributed to by 

drift of the sensors. The difference-frequency excitation can be 

seen in Figure 5 by the presence of frequency peaks below the 

wave frequency range (0.05–0.2 Hz). Each of the four response 

DOFs show significant peaks in the 0 to 0.05 Hz range, but the 

semi has by far the largest difference-frequency excitation.

Sum-frequency excitation can be seen by the presence of 

frequency peaks above the wave-frequency range. Figure 5

shows significant excitation at the TLP pitch frequency (0.27 

0 0.05 0.1 0.15 0.2

100

102

Frequency(Hz)

Surge (m/m)

TLP, No Wind

TLP, Wind

Spar, No Wind

Spar, Wind

Semi, No Wind

Semi, Wind

0 0.05 0.1 0.15 0.2 0.25 0.3

10-2

10-1

100

101

Frequency(Hz)

Pitch (deg/m)

0 0.05 0.1 0.15 0.2

10-2

100

Frequency(Hz)

Heave (m/m)

0 0.1 0.2 0.3 0.4 0.5

103

104

105

106

Frequency(Hz)

Tower Bending (kN/m)

Figure 5. RAOs derived from white-noise wave excitation with 7.1-m significant wave height both with and without wind 

present at 21.8 m/s; colored box indicates wave frequency range
7 

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Hz) and the tower-bending frequencies of the spar and semi 

(0.43 Hz and 0.35 Hz). Fewer peaks are seen in the upper 

frequencies because most of the system frequencies are placed 

below the wave frequency range. The exception is the TLP 

system that has pitch, heave (0.86 Hz), and first tower-bending 

(1.3 Hz) natural frequencies above the wave-frequency range, 

most of which are above the range plotted in this figure. 

2.4 Mooring-Line Behavior

The mooring lines of the spar and semi systems are 

catenary configurations, which mean that they hang in a curve 

from the platforms and are predominantly used for restoring 

stiffness in the surge/sway directions to prevent the systems 

from drifting away. The TLP, on the other-hand, uses a taut

mooring system, which also provides stiffness in the heave and 

pitch/roll DOFs, significantly limiting the motion of the system 

in these DOFs. The lack of motion of the TLP can be seen in

Figure 5 in the lower magnitude response of the TLP in all 

DOFs. The trade-off, however, is an increase in mooring 

tension and unique mooring behavior for the TLP. Figure 6

shows the mooring-tension RAO for the mooring line aligned

with the wave direction for each of the systems. For the TLP 

and spar, this mooring line is downwind of the turbine, but is 

upwind for the semi. 

Sum-frequency forces can be problematic for the mooring 

lines of TLPs, which is evident in this RAO. In addition to 

response in the wave-frequency range (0.05-0.20 Hz), two 

significant peaks are seen at the pitch natural frequency (0.27 

Hz) and the heave natural frequency (0.86 Hz). This type of 

response in a TLP is called springing, and can contribute to 

fatigue in the structure and in the mooring lines. In addition, for 

the case with wind, the TLP shows a response around 0.64 Hz, 

which is the 3P frequency of the rotor. This shows that dynamic 

excitation at the blade passage frequency can also excite the 

mooring lines, illuminating the coupled nature of the system 

response.

In addition to springing, TLP mooring systems can also 

create a ringing phenomenon, which is the broad-band 

frequency excitation of the mooring line due to a sudden 

loading of the line. Ringing can occur when a mooring line 

goes slack and then snaps back, or when a wave breaks over the 

platform. In the DeepCwind tests, ringing was observed due to 

slack-line events for the following cases: (1) the higher of the 

two white-noise cases without wind, (2) an operational case 

with winds at 21.8 m/s and a significant wave height (Hs) of 7.1 

m, (3) a survival wave-only case with 10.5-m Hs, and (4) a 

survival case with winds at 30.5 m/s (turbine turned off) and an 

Hs of 10.5 m. The slack-line events occur just after a 

significantly large wave passes, as seen in Figure 7, with highfrequency ringing occurring just after. In the design of TLPs, 

slack-line events should be avoided, as the large loading and 

broad-band frequency excitation in the structure could cause 

significant damage. The presence of these events indicates that 

this TLP design was not sufficiently robust. 

0 0.2 0.4 0.6 0.8 1

100

101

102

103

104

105

Frequency(Hz)

Mooring Tension (kN/m)

TLP, No Wind

TLP, Wind

Spar, No Wind

Spar, Wind

Semi, No Wind

Semi, Wind

Figure 6. Wave-oriented mooring-line tension RAO from 

white noise waves (7.1 Hs) with and without wind (21.8 m/s)

5900 5950 6000 6050 6100 6150 6200

-5

0

5

10

Time (sec)

Wave Amplitude (m)

5900 5950 6000 6050 6100 6150 6200

0

5000

10000

15000

Time (sec)

Mooring Tension (kN)

Figure 7. Ringing event for survival wind/wave case with Hs

= 10.5 m and wind = 21.8 m/s

3.VALIDATION OF FAST

With DOE support, NREL has developed and maintains a 

robust open-source, modular CAE tool known as FAST, with 

state-of-the-art capabilities for modeling offshore wind 

systems. One of the key reasons for performing the DeepCwind 

tests was to obtain data for validating FAST as a tool capable of 

modeling the dynamic behavior of offshore wind turbines. 

FAST has been successfully verified and validated for landbased wind turbines, and the offshore functionality of FAST has 

been verified through model-to-model comparisons under the 

NREL-led International Energy Agency (IEA) Wind Task 23 

Offshore Code Comparison Collaboration (OC3) project and 

the ongoing NREL-led OC3 Continuation (OC4) project, which 

operates under IEA Wind Task 30. However, data has not been 

available until recently for validating the offshore functionality 

of FAST and the coupled system response due to combined 

aerodynamic and hydrodynamic loading.
8 

This report is available at no cost from the National 

Renewable Energy Laboratory (NREL) at 

www.nrel.gov/publications.

Validation of FAST is defined as the comparison of 

simulated responses from FAST to experimental test data. The 

DeepCwind tests have provided data useful to this process. In 

the following subsections, FAST simulations are compared to 

the DeepCwind tests to understand the limitations of the FAST 

tool in accurately modeling the dynamics of offshore wind 

systems. 

3.1 Testing Issues 

Efforts have been made to build validated models of each 

of the three floating systems within FAST; see Coulling [9], 

Browning [10], and Prowell [11]. Part of the process in building 

these models was a calibration step to tune system parameters 

so that simulation responses matched the behavior of the 

systems from a small subset of the tank tests. While tuning 

parameters can create a model that will give the right results, 

one must understand why the tuning is needed to be assured 

that the simulation tool (FAST) is working correctly. Even with 

this knowledge, the calibration process can mask issues with 

the model that are not well understood.

In the DeepCwind tests, issues arose that required 

calibration of the models created in FAST. First, the

turbine/tower sensors and their cabling needed to be 

accommodated for in the model. This was accomplished by 

adding weight to the system at the location of each of the 

sensors, and at each of the node points on the tower where the 

cabling was tied to the tower. It was assumed that the cabling 

added negligible stiffness to the tower, but that the two force 

sensors at the top and bottom of the tower altered the tower 

stiffness. These connection points, as well as a connection point 

in the middle of the tower, could add compliance to the tower. 

In the end, all three systems needed to decrease the stiffness of 

the tower to achieve a match between the tower modal 

properties of the FAST model and the experimental tests. 

The aerodynamics model also needed calibration due to 

test limitations. As mentioned in previous papers ([6], [12]), the 

altered performance of the wind turbine at model scale required 

large alterations to the airfoil data from what is appropriate at 

full scale. An attempt was made to create this model within 

XFOIL [13], but due to its questionable ability to model the 

separated flow experienced by this turbine, tuning of the lift 

and drag curves was needed using the experimental data. 

Third, the wind in the tank is not as consistent as is

possible in a wind tunnel. There were drop-offs in the wind 

velocity and increased turbulence at the edges of the rotor 

plane, as well as some low-level swirling behavior. To obtain an 

appropriate representation of the wind, a shear law with an 

exponent of 0.0912 was needed to represent the change in wind 

speed with height, as well as a slight decrease (a factor of 

0.952) in the average wind speed. No accommodations were

made in the simulations for the vertical wind speed components

or turbulence variations. This helped to match the wind 

excitation; however, there was still unmodeled wind behavior in 

the FAST model due to not having a full spatial and temporal 

characterization of the velocity. These inconsistencies in the 

wind induced unwanted excitation in the system (such as the 

3P, 6P, and 9P frequencies seen in Figure 3) that were not 

modeled in FAST, and therefore influenced the validation 

process.

The testing issues described in this section, as well as 

uncertainty in model properties and limitations of FAST,

inhibited the ability to directly validate FAST using the tank 

test data. In some cases, calibration was performed to more 

closely match the response in the tank. Calibration procedures 

were performed to achieve the correct displacement in the 

water, the correct quasi-static mooring behavior, and the correct 

system frequencies and damping.

In the remainder of this section, we will discuss the 

limitations identified for FAST through this validation process.

3.2 Hydrodynamics 

The hydrodynamic loading on an offshore wind turbine is 

typically categorized into contributions from hydrostatics, 

excitation from incident waves (including diffraction and 

Froude-Kriloff forces), radiation from outgoing waves 

(generated by the platform motion), added mass effects, and 

viscous forces. There are many different approaches to 

modeling these hydrodynamic forces. The two main approaches 

involve Morison’s Equation - an empirical formulation 

typically used to describe the inertia, added mass, and viscous 

drag loads on slender structures; and, potential-flow theory, 

which defines the radiation and diffraction loads important for 

larger structures not subject to flow separation. FAST uses a 

combination of these two formulations to describe 

hydrodynamic loads, but with limitations. One limitation is that 

FAST presently only models the viscous drag forces on the 

central column of the structure. Second, FAST currently only 

uses the first-order approximation of the radiation and 

diffraction problem. The influence of these modeling 

assumptions will be discussed below.

Viscous Drag

Because the viscous-drag effects in FAST are only defined 

for the central column of the structure, this means that viscous 

drag on the arms of the TLP and the offset columns and cross 

members of the semi will not be modeled. This drag can have 

significant effects on the damping of the system motion. The 

DeepCwind tests showed that the system damping was underpredicted by the FAST models of all three systems, most likely 

due to this lack of viscous drag modeling on the TLP and semi. 

For the spar, this could be a result of not modeling the damping 

of the mooring lines. To accommodate this limitation, quadratic 

drag was artificially added to the FAST models globally, with 

one quadratic drag coefficient per mode of motion. The values 

for the drag coefficients were chosen such that the FAST 

simulations matched the damped behavior of the systems 

during the free-decay tests. 

Second Order Hydrodynamics

As discussed in the section above, RAOs from the 

DeepCwind tests showed the presence of frequencies outside 

the wave-excitation range, which were assumed to be excited

by the interaction of the wave components of the irregular, 
9 

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white-noise wave. In the present version of FAST, a linear 

approximation is used for the diffraction problem. A secondorder model of the diffraction is needed to capture 

hydrodynamic loads at the sum and difference-frequencies of 

the waves. 

To examine the influence of omitting second-order 

hydrodynamic effects, Figure 8 shows a comparison of the 

RAOs calculated for the white noise, wave-only experiment 

with 7.1 m Hs to RAOs generated from FAST simulations. 

Once again, the white noise excitation was band-limited to 

frequencies between 0.05 and 0.2 Hz. The RAOs show fairly 

good agreement between the experimental and simulated data 

in the wave region, with the exception of the TLP in the pitch 

DOF. Previous papers have highlighted issues in achieving 

good agreement for the pitching motion between the FAST 

model developed for the TLP and the experimental data, in 

large part due to the inability to accurately measure the small 

pitching motion of the TLP in the tank. Further discussion of 

the topic can be found in Prowell [11]. 

The FAST model is a nonlinear model and so some 

excitation outside the wave frequency range will occur, as can 

be seen in Figure 8. The peaks outside the wave frequency 

range are, in general, much smaller in the simulated response 

than those observed in the experimental data, and we assume

that this difference is the contribution of second-order effects. 

In addition, some of the excitation outside the wave 

frequency range could be caused by transient behavior 

produced by the initial interaction between the waves and 

structure, which has not completely died out. The results 

presented here do not consider the first 2,000 seconds of the 

simulated FAST data in an attempt to remove transient 

behavior, but this time may need to be increased. The tests 

perform a ramp-up of the waves over a long period of time, and 

this portion of the response is also removed.

Figure 9 shows results from Coulling, et al. [9] to 

approximate the influence of second order difference-frequency 

diffraction terms added to FAST using Newman’s 

approximation. Surge displacement is presented for an irregular 

wave-only test with a peak spectrum of 0.133 Hz, or wave 

period (Tp) of 7.5 s. The wave energy is clearly seen in this 

figure starting at about 0.08 Hz, but the largest peak is the surge 

frequency of the system (0.0093 Hz), which is well below the 

wave-excitation range. Using a linear solution, FAST severely 

underestimates the response at the surge natural frequency; 

however, using Newman’s approximation, FAST is able to get 

much closer to the experimental data. Tuning the damping of 

the system allows FAST to match the surge response almost 

0 0.05 0.1 0.15 0.2

10-1

100

101

102

Frequency(Hz)

Surge (m/m)

TLP, Exp

TLP, Sim

Spar, Exp

Spar, Sim

Semi, Exp

Semi, Sim

0 0.05 0.1 0.15 0.2 0.25 0.3

10-2

10-1

100

101

Frequency(Hz)

Pitch (deg/m)

0 0.05 0.1 0.15 0.2

10-3

10-2

10-1

100

101

Frequency(Hz)

Heave (m/m)

0 0.1 0.2 0.3 0.4 0.5

103

104

105

106

Frequency(Hz)

Tower Bending (kN/m)

Figure 8. RAOs derived from white-noise wave excitation with 7.1-m significant wave height both from FAST simulations 

(sim) and the experimental data (Exp); colored box indicates wave frequency range
10

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exactly. This example shows that second-order hydrodynamics 

are needed within FAST to capture the appropriate system 

behavior.

3.3 Mooring Model

The mooring-line model used within FAST is a quasistatic, catenary solution, which means that it is able to capture 

the nonlinear mooring tension associated with slowly-varying 

motion. The model does not include dynamics of the cable

itself, or drag on the cable from the interaction of water. 

Mooring Dynamics

These two limitations were investigated by Masciola [14] 

in terms of the significance in FAST’s ability to model the 

mooring-line behavior observed in the DeepCwind tests. For 

the wave-only JONSWAP excitation case with Hs = 7.04 m (see

Figure 10), it was found that a FAST model of the semi

significantly underpredicted the mooring tension for line 2,

which is in line with the wave excitation. The discrepancy 

between the results at the surge natural period is theorized to be

caused by the presence of difference-frequency diffraction 

excitation in the tank, which is not present in the FAST model. 

This is confirmed by an underprediction of the surge motion of 

the structure at the surge natural frequency (see Masciola [14]). 

The surge and heave motion, however, match well in the wavefrequency range (0.05 to 0.20 Hz), but the mooring response is 

different. 

To examine this behavior more closely, Masciola modeled 

the DeepCwind semi-submersible system in a coupled FASTOrcaFlex model [14], which has the ability to model the 

dynamics of the moorings and the drag on the lines along with 

the turbine dynamics. These results are presented with the 

MARIN experimental results and FAST results in Figure 10. 

The OrcaFlex (A) solution does not deviate far from the FAST 

solution in the wave frequency region, implying the mooring 

dynamics and cable drag do not influence the ability to capture 

mooring tension at the wave frequencies. The reason for the 

major difference in the mooring tension between the MARIN 

tests and numerical models is unknown, but the presumption is 

that it is related to the simplification of the mooring line 

representation within the modeling tools. Because the mooring 

tension does not affect the global motion of the structure for 

this case, the limitation in FAST is in the ability to capture the 

large mooring loads, which need to be known to correctly 

design the mooring system to avoid failure. Masciola did find 

that for larger wave scenarios, the mooring dynamics and drag 

were important in capturing the correct mooring behavior, so 

this work solidifies the need for these capabilities within FAST. 

Further investigation is needed to understand the limitations of 

both the FAST and OrcaFlex models in being able to capture 

the correct interaction between the waves and the mooring.

Slack-line Events

During the DeepCwind tests of the TLP, several slack-line 

events occurred for wave-only and combined wind/wave cases 

with large wave heights. Each of the events was caused by the 

passing of a large wave that allowed the tension in one of the 

tendons to go negative as the trough of the wave passed the 

structure. FAST was able to predict some of the slack-line 

events, but not all of them (see Prowell [11] for more details). 

One of the reasons was that the FAST simulations used a wave 

spectrum that only approximated the waves used in the tests, 

but did not have the exact same wave elevation time series. So, 

FAST did not always simulate waves as extreme as those 

occurring in the tests. Other issues are that FAST does not 

model the second order pitch loads and the wind drag on the 

tower and the exposed portion of the platform above the 

waterline. This increased loading could contribute to the 

pitching of the system and the development of slack-line 

events.

Figure 9. Comparison of simulated to experimental surge 

response of the semi for a regular wave-only test (Tp = 

7.5 s)

0 0.05 0.1 0.15 0.2 0.25 0

2

4

6

8 x 1011

Fr equency (H z)

M oor ing Tension (kN 2/ H z)

MARIN

FAST+ OrcaFlex (A)

FAST+ OrcaFlex (B)

FAST

Figure 10. Mooring line forces for a wave-only case, Hs = 

7.04 m , Tp = 12.18 s JONSWAP spectrum
11

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4. CONCLUSIONS AND RECOMMENDATIONS

The two main purposes for the DeepCwind testing 

campaign were to better understand the behavior of floating 

offshore wind systems and to obtain experimental data to be 

used for validating offshore wind system modeling tools. The 

tests were essential in meeting these goals, and were 

groundbreaking in regard to producing data that will be made 

publicly available. This section summarizes the lessons learned

from the experimental tests in regard to the limitations of FAST 

as a modeling tool for offshore wind turbines, as well as the 

scaled-model testing of these systems.

4.1 Suggestions for Future Test Campaigns

From this process, we are able to share some of the lessons 

learned involving what to do differently if future testing of this 

kind were to be pursued. First, in regard to the testing 

methodology itself, here is a list of suggestions for future test

campaigns:

• Scaling approach: While a Froude-based scaling approach 

is, in general, a sound methodology, the approach must be 

modified in regard to the rotor due to the aerodynamic

loading being so dependent on Reynolds number. It is 

suggested that future coupled wind/wave turbine testing 

under a Froude-scaled environment should use a blade 

geometry which is specifically designed for a low

Reynolds number environment [8]. This can easily be 

accomplished by simply increasing the blade chord, which 

is often done in wind tunnel tests. While the blade 

geometry will likely not represent the full-scale 

architecture, the blade should be designed to increase 

torque output, match full power and thrust coefficient 

curves and, if possible, closely match the change in total 

blade lift force with respect to blade pitch. The first two 

points will ensure that the global mean forces on the 

structure are maintained in a Froude-scaled environment, 

while the second will help maintain the effect of turbine 

damping forces due to either changing wind speed or 

global motion of the floating wind turbine structure. 

• Instrumentation: The DeepCwind tests highlighted the 

importance of having instrumentation that is light-weight 

and does not alter the dynamic behavior of the offshore 

wind system. At 1/50th scale, the systems are so small that 

the weight of the sensors and the cabling becomes 

significant. The effect of the cable bundle on the dynamics 

of the systems in the DeepCwind tests could not be fully 

characterized. Therefore, it is suggested that, if possible, 

wireless sensors or smaller cabling should be used for 

small-scale testing. In addition, we suggest avoiding 

adding additional compliance to the tower through sensor

placement, such as the load sensors used in these tests. If 

they are needed, periodic inspection should be done to 

assess that the tower properties have not changed due to 

loosening of a joint, perhaps through hammer tests.

• Wind quality: It should be the normal procedure in 

offshore testing to apply the correct wind load instead of 

the correct wind speed. The wind load should be correct in 

all directions relative to the model. Finally, the wind should 

be modeled as a constant force or with the appropriate 

wind spectrum to take into account real wind gusting.

• Wind turbine testing: An integral part of validating an 

offshore wind modeling tool is building an accurate model 

of the wind turbine. For the DeepCwind tests, the 

performance of the wind turbine limited the ability to 

model it accurately within FAST, and instead, the FAST 

model had to be tuned to represent the behavior of the test 

turbine. In future campaigns, it would be advantageous to 

validate the wind turbine behavior independent of the 

support structure. This was done partially in the 

DeepCwind tests by fixing the wind turbine in the tank 

testing. However, with the limited wind quality of the tank, 

it would be best to first perform testing of the wind turbine 

in a wind tunnel, to be able to accurately validate a model 

of the turbine.

Second, in regard to providing data to validate offshore 

wind modeling tools, a list of suggestions are given to better 

provide the data needed:

• Focus on water/structure interaction: Since FAST was 

originally a land-based wind turbine modeling tool, 

extensive work has previously been done on verifying and 

validating the aerodynamic models used. The validation of 

FAST as an offshore wind turbine modeling tool should 

therefore be most focused on validation of the 

hydrodynamic loads and the coupled system behavior. 

Future testing campaigns should isolate and focus more 

closely on hydrodynamic loads. Performing wave-only 

cases as was done supports this. In addition, current-only 

tests would be beneficial in isolating the viscous-drag 

loading on the structure from the water. Viscous loading 

for a single cylinder is well understood, but its loading 

contribution for a complicated structure such as the TLP 

and semi with multiple connecting members is more 

complex. In addition, it may be good to step back and also 

do some component-level tests. For example, it would be 

good to include a test that examines the drag on a cylinder 

of the same size as the column of the semi in a current. 

This will help identify whether test/simulation

inconsistencies come from the modeling of the 

water/structure interaction or effects of water blockage by 

complicated geometry. 

• Obtain a higher-quality wind excitation: While measures 

were taken to reduce swirl and turbulence, there was still 

significant change in velocity and turbulence in the lower 

region of the rotor. The more consistent the wind can be, 

the better we would be able to assess modeling approaches.

• Focus on steady wind: As asserted by Kimball [15], the 

FAST simulations predicted the response of the systems for 

steady wind with reasonable accuracy, but not for dynamic 

wind. Therefore, for model validation purposes, we

propose focusing more on steady-wind tests. Until we can 

accurately predict the response for steady wind, there is 

limited advantage in moving to dynamic wind tests. 
12

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However, dynamic wind tests will be important in 

understanding the coupled behavior of the system and 

should be performed once confidence is obtained for 

steady-wind tests and one can produce a well-defined 

dynamic wind condition.

• Damping: Coulling [9] shows discrepancy in the towerbending response between simulation and experiment for 

the semi, but is unsure whether this is due to second order 

excitation or incorrect modeling of damping. Tests should 

be performed to better estimate the damping value—either 

by means of a hammer excitation test or purposely having 

a wave excitation in this frequency band.

4.2 FAST’s Modeling Limitations

Based on the validation work from the DeepCwind tests, 

the following limitations of FAST have been identified as 

important areas for improvement to successfully model a 

floating offshore wind system:

• Viscous drag: FAST can only model viscous drag for a 

constant-diameter cylinder at the centerline of the platform. 

This is a severe limitation for structures such as the semi 

that has columns offset from the centerline and the TLP 

that has arms off the centerline, causing the need to add 

additional damping to the structure to match the response 

seen in the tank tests. 

• Mooring model: FAST uses a quasi-static mooring line 

model. The main limitations of this model are that it cannot 

capture the dynamic characteristics of the mooring line, it 

does not model the interaction between the water and the 

mooring line, and it does not model the dynamic 

interaction between the mooring line and the seabed. These 

limitations result in an underprediction of forces in the 

mooring line and the inability for the mooring line to 

induce dynamic excitation in the structure, or perhaps 

damp dynamic behavior of the structure.

• Second-order hydrodynamics: FAST uses a linear 

diffraction model that does not capture the mean drift 

force, difference-frequency excitation, and sum-frequency 

excitation captured by second-order models. This means 

that not all frequency excitation of the system is being 

captured by FAST, which could result in an under 

prediction of fatigue estimates and extreme responses.

• Wave models: FAST models wave excitation through a 

definition of the wave spectrum. In general, this is a 

sufficient approach for modeling the wave excitation on a 

given design. However, for validation purposes, it would 

be beneficial to directly input a time signal of the wave 

height so that tests and simulations could be more directly 

compared.

• Other: While the tests did not reveal this, other 

improvements to FAST are also important for accurate 

modeling of large-scale floating wind systems, including 

higher fidelity structural and aerodynamic modeling.

4.3 Future Efforts to Complete Validation of FAST 

The present limitations of FAST’s modeling capabilities for 

both hydrodynamics and mooring line dynamics prevents the 

ability to fully validate FAST as a tool for modeling offshore 

wind turbines. Work is presently ongoing to augment FAST’s 

modeling approach to overcome the limitations identified. 

When this work is complete, efforts will be redone to compare 

the DeepCwind data with the new and improved FAST 

simulation tool. 

The comparison work with the DeepCwind data is just one 

step toward the validation of the coupled offshore floating wind 

system solution of FAST. FAST’s simulation capabilities will 

also need to be compared to other datasets to ensure a complete 

validation of the tool. Work is ongoing to compare FAST 

simulations to those from deployed, open-ocean floating 

offshore wind systems. In addition, future efforts will be 

focused on obtaining and comparing data from fixed-bottom 

structures, such as monopiles, jackets, and tripods that have 

their own unique characteristics that differ from floating 

systems. While FAST can be validated for a set of generic 

structures, it may have limitations for structures that deviate 

from FAST’s modeling approach or assumptions. Examples 

include structures that have sloped or multiple towers. 

On the aeroelastics side, FAST is also presently being 

modified to be able to model the torsional motion of the blades. 

This degree of freedom has been identified as being important 

for the larger-sized blades that are anticipated for use on 

offshore wind turbines.

ACKNOWLEDGMENTS

The authors gratefully acknowledge financial support from 

the DOE through DeepCwind Grants DE-EE0002981 and DEEE0003728 and NREL Grant DE-AC36-08GO28308, the 

National Science Foundation through Grant IIP-0917974 and 

the University of Maine. In addition, the expertise and support 

of MARIN in conducting the model tests is greatly appreciated.

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This report is available at no cost from the National 

Renewable Energy Laboratory (NREL) at 

www.nrel.gov/publications.

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