On the Use of Coupled Wind,
Wave, and Current Fields in the
Simulation of Loads on BottomSupported Offshore Wind
Turbines during Hurricanes
March 2012 — September 2015
Eungsoo Kim and Lance Manuel
University of Texas at Austin
Austin, Texas

Milan Curcic and Shuyi S. Chen
University of Miami
Coral Gables, Florida

Caleb Phillips and Paul Veers

National Renewable Energy Laboratory
Golden, Colorado
NREL Technical Monitor: Paul Veers
NREL is a national laboratory of the U.S. Department of Energy
Office of Energy Efficiency & Renewable Energy
Operated by the Alliance for Sustainable Energy, LLC
This report is available at no cost from the National Renewable Energy
Laboratory (NREL) at www.nrel.gov/publications.
Technical Report
NREL/TP-5000-65283
June 2016

Contract No. DE-AC36-08GO28308

On the Use of Coupled Wind,
Wave, and Current Fields in
the Simulation of Loads on
Bottom-Supported Offshore
Wind Turbines during
Hurricanes
March 2012 — September 2015
Eungsoo Kim and Lance Manuel
University of Texas at Austin
Austin, Texas

Milan Curcic and Shuyi S. Chen
University of Miami
Coral Gables, Florida

Caleb Phillips and Paul Veers

National Renewable Energy Laboratory
Golden, Colorado
NREL Technical Monitor: Paul Veers

NREL is a national laboratory of the U.S. Department of Energy
Office of Energy Efficiency & Renewable Energy
Operated by the Alliance for Sustainable Energy, LLC
This report is available at no cost from the National Renewable Energy
Laboratory (NREL) at www.nrel.gov/publications.
National Renewable Energy Laboratory
15013 Denver West Parkway
Golden, CO 80401
303-275-3000 • www.nrel.gov

Technical Report
NREL/TP-5000-65283
June 2016

Contract No. DE-AC36-08GO28308

This publication was reproduced from the best available copy
submitted by the subcontractor and received little editorial review at NREL.

NOTICE
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Acknowledgments

The authors wish to acknowledge the assistance received from project collaborators including
Mr. John Michalakes, previously a staff member at the National Renewable Energy Laboratory
where he initiated the project summarized in this report, and now at the National Oceanic andAtmospheric Administration. John’s leadership was essential in formulating the team and setting
the direction for this work. We also acknowledge substantial assistance from Dr. Mark Donelan,of the University of Miami’s Rosenstiel School of Marine and Atmospheric Science. Mark was atireless and insightful collaborator on the wave dynamics simulation and helped interpret theresults for use in the loads simulation.
This work was supported by the U.S. Department of Energy under Contract No. DE-AC3608GO28308 with the National Renewable Energy Laboratory. Funding for the work wasprovided by the DOE Office of Energy Efficiency and Renewable Energy, Wind and Water
Power Technologies Office.

1

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1 Overview

In the United States, potential offshore wind plant sites have been identified along the Atlantic
seaboard and in the Gulf of Mexico. It is imperative that we define external conditions associatedwith hurricanes and severe winter storms and consider load cases for which wind turbines mayneed to be designed. We selected two hurricanes, Ike (2008) and Sandy (2012), and investigatedthe effect these tropical storms would have on bottom-supported offshore wind turbines thatwere hypothetically in or close to their path as they made landfall. For realistic turbine loads
assessment, it is important that the coupled influences of the changing wind, wave, and current
fields are simulated throughout the evolution of the hurricanes. We employed a coupled model—
specifically, the University of Miami Coupled Model (UMCM)—that integrates atmospheric,wave, and ocean components to produce needed wind, wave, and current data. The wind data areused to generate appropriate vertical wind profiles and full wind velocity fields including
turbulence; the current field over the water column is obtained by interpolated discrete output
current data; and short-crested irregular second-order waves are simulated using output
directional wave spectra from the coupled model.
We studied two monopile-supported offshore wind turbines sited in 20 meters of water in the
Gulf of Mexico to estimate loads during Hurricane Ike, and a jacket space-frame platformsupported offshore wind turbine sited in 50 meters of water in the mid-Atlantic region toestimate loads during Hurricane Sandy. In this report we discuss in detail how the simulated
hurricane wind, wave, and current output data are used in turbine loads studies. In addition,
important characteristics of the external conditions are studied, including the relative importanceof swell versus wind seas, aerodynamic versus hydrodynamic forces, current velocity effects,
yaw control options for the turbine, hydrodynamic drag versus inertia forces, and soil-structureinteraction effects. A detailed framework is presented that explains how coupled inputs can be
included in turbine loads studies during a hurricane. This framework can aid in future efforts
aimed at developing offshore wind turbine design criteria and load cases related to hurricanes.
The UMCM was created by the University of Miami for this project and was essential inproducing simultaneous wind and wave conditions during all aspects of the hurricane, especiallyas it approached and passed through areas of potential offshore wind plant development.
Appendix A includes a description of the scope and nature of the UMCM and details themodeling capabilities that it possesses. Some example outputs provide a visualization of thekinds of data that are generated. The results for each of the two selected hurricanes (Ike andSandy) are also detailed. The University of Miami team used extensive buoy data from bothstorms to validate the UMCM capabilities, some extracts of which are shown here. Moredocumentation of model validation can be found in the References section.
Appendix B describes how users can access this extensive data set of wind and wave conditions
for both Hurricane Ike and Hurricane Sandy at user-specified potential development sites. The
data have been housed at the National Renewable Energy Laboratory for future use, and software
hooks have been created to enable users to extract time series of interest from the more than two
Tera-byte data set. Examples time series from the Hurricane Ike and Hurricane Sandy data areplotted to illustrate the types of the data that can be extracted.

2This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2 Modeling Hurricane Ike’s Influence on a Monopile-Supported Offshore Wind Turbine
2.1 Problem description
Over a 5-day period in the evolution of Hurricane Ike (2008) prior to landfall, the response of a monopile-supported
5-MW offshore wind turbine is evaluated in a step-wise procedure. As sites for the turbines to be analyzed, we selectlocations 60 km to the right and left of the track of Ike, points A and B, respectively, as shown in Fig. 2.1, where thewater depth is 20 meters.

35
Hurricane Ike Track

A
30

Latitude

15:00 UTC 2008−09−12

25

B

20
A : 60km right of track
B : 60km left of track
15
−100

−95

−90

−85
−80
Longitude

−75

−70

Figure 2.1. Track of Hurricane Ike and selected locations of two sites, one tothe left and the other to the right of the track where the water depth is 20 m.

Based on output from UMCM, coupled wind and wave fields at the two selected locations are simulated andwe evaluate the turbine response on a 5-MW offshore wind turbine over a period of the storm’s evolution when it
is close to landfall. We present the theoretical background and formulation for directional second-order nonlinear
irregular wave modeling and outline a procedure for numerical simulation of the sea surface elevation and associatedwave kinematics. We also present characteristics of the hurricane wind fields and show how a spectral method
is adopted to simulate these hurricane turbulent wind fields. Finally, we investigate how yaw and pitch controls
influence the response of the selected offshore wind turbine during a hurricane.

3This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2.2 Hurricane Waves
In this study, hurricane-generated wave kinematics are simulated based on directional wave spectra resulting fromthe UMCM output; the model was initialized at 12:00 UTC on September 9, 2008. A wave spectrum from the
UMCM output consists of 36 directional bins and 37 frequency bins covering a range from 0.03 Hz to 2 Hz, overwhich the discrete frequencies are logarithmically spaced. As an illustration of the development of wave inputs forturbine loads analysis, we present in Fig. 2.2 normalized directional wave spectra with significant wave height (Hs )obtained from UMCM that apply to the two selected site A and B; these spectra are for 80 to 120 hours after thestart of the simulation (with updates shown every 10 hours). Red and blue arrows in these spectra represent the mean
wind and wave direction, respectively. Also, in these wave spectra, N describe waves propagating toward north, etc.,
and the dashed circles and the solid circle (inner to outer) correspond to wave frequencies of 0.1, 0.2, 0.3, and 0.4
Hz. In these wave spectra plots, we see that directional spreading of wave energy is significant and that the wave
spectrum, before passing the sites, has two well-separated peaks. Although the wave energy at high frequencies isclosely linked to the wind field and the mean wave direction is dominated by the low-frequency wave component;
this low-frequency wave component is classified as swell which contributes significantly to the total wave energy at
the two sites.
2.2.1

Wave simulation theory

It is common practice to model the irregular sea surface elevation process as a Gaussian random process using
linear Airy wave theory. However, to generate realistic hurricane wave fields, it is essential to account for both
wave directionality and nonlinearity. In this study, directionality and nonlinearity of the waves are accounted for by
employing directional irregular second-order wave formulations proposed by Sharma and Dean [1] for finite water
depths. This second-order wave modeling formulation is an extension of the theory developed by Longuet-Higgins
et al. [2] for waters of infinite depth to apply to waters of arbitrary finite depth. A nonlinear boundary value problem
is solved up to second order by a perturbation approach accounting for contributions from linear components fromarbitrary frequencies and directions. The second-order wave system is one that is forced by the linear system and all
information on second-order amplitudes and phases is related to the characteristics of the first-order spectrum.
2.2.1.1

Boundary value problem formulation

If the effects of viscosity and turbulence can be regarded as small, incompressible flows can be described well by avelocity potential. In other words, the velocity components u, v, and w, can be defined in terms of the gradients of thevelocity potential, φ , given in terms of the three Cartesian directions, x, y, and z.
∂φ ∂φ ∂φ(u, v, w) =
,
,
(2.1)
∂x ∂y ∂z
The mass conservation equation for an incompressible fluid is∂u ∂v ∂w++=0
∂x ∂y ∂z(2.2)

which can be combined with Eq. 2.1 to yield∇2 φ =∂ 2φ ∂ 2φ ∂ 2φ
+ 2 + 2 =0
∂ x2
∂y
∂z

(2.3)

where −h ≤ z ≤ η and −∞ ≤ x, y ≤ ∞Sharma and Dean proposed a second-order velocity potential function that satisfies the appropriate boundary
conditions for the problem.

4

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Site A

Site BHs= 1.5 m

N

Hs= 1.6 m

N

h = 80ĂƚϴϬŚƌƐ
Hs= 3.2 m

N

0

0.5

1

Hs= 3.6 m

N

0

0.5

1

h = 90ĂƚϵϬŚƌƐ
Hs= 5.0 m

N

0

0.5

1

Hs= 7.2 m

N

0

0.5

1

ĂƚϭϬϬŚƌƐ
h = 100
Hs= 4.5 m

N

0

0.5

1

Hs= 8.3 m

N

0

0.5

1

ĂƚϭϭϬŚƌƐ
h = 110

0

N
0.5

1

0

0.5

1

Hs= 4.3 m

Hs= 4.8 m

N

0

0.5

1

0

0.5

1

h = 120ĂƚϭϮϬŚƌƐ

Figure 2.2. Wave spectra for Sites A and B from over a 40-hour period during Hurricane Ike; N describe
waves propagating toward north, etc., and the dashed circles and the solid circle (inner to outer) correspondto wave frequencies of 0.1, 0.2, 0.3, and 0.4 Hz. (blue arrow: wave direction; red arrow: wind direction).

5This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

• Bottom Boundary Condition (BBC)At the bottom boundary, the velocity normal to the boundary is equal to zero. For this case of a horizontal
boundary at depth, h, we have:
∂φ
=0
(2.4)
∂ z z=−h• Kinematic Free Surface Boundary Condition (KFSBC)
A water particle on the free surface remains on the free surface and the vertical velocity at the free surface isequal to the total rate of change of the sea surface elevation:∂η ∂φ ∂η ∂φ ∂η
∂φ
+
+
=
∂t
∂x ∂x ∂y ∂y
∂z

(2.5)

where z = η .
• Dynamic Free Surface Boundary Conditions (DFSBC)
The pressure, p, follows from Bernoulli’s equation:p∂φ 1+ gz ++ ∇φ · ∇φ = −Q(t)
ρ
∂t 2

(2.6)

where Q(t) is an arbitrary function of time. Instead of including the variation with time of Q in the velocity potential,
φ , let Q be a constant. At the free surface, z = η , the pressure is equal to the atmospheric pressure, patm and if wechoose Q = −patm /ρ in Eq.2.6, we can rewrite the equation as follows [3]:
⇒

gη +

∂φ 1
+ ∇φ · ∇φ = 0
∂t 2

(2.7)

• Combined Free Surface Boundary Condition (CFSBC)
We can write an alternative form of Eqs. 2.5 and 2.7 above, by eliminating the unknown free surface elevation
η . This then involves only φ and its derivatives:
−

∂ 2φ
∂φ
∂
1
−g
− ( + ∇φ · ∇)|∇φ |2 = 0
∂ t2
∂z
∂t 2

(2.8)

where z = η
2.2.1.2

Solution of the boundary value problem

A perturbation approach is adopted for solution of the boundary value problem formulated in the previous section.
This approach assumes that all variables can be expanded as a convergent power series of a small parameter, suchas the wave steepness. Also, it is assumed that the combined free surface boundary condition (CFSBC) can be
expanded in a convergent Maclaurin series about the mean water level, z = 0, in terms of the small parameter.
The velocity potential, φ , and sea surface elevation, η , may be represented in the following manner using wave
steepness, ε , as the perturbation parameter:

φ (x, y, z,t) = φ (1) (x, y, z,t) + φ (2) (x, y, z,t) + ...

(2.9)

η (x, y,t) = η (1) (x, y,t) + η (2) (x, y,t) + ...

(2.10)

where η (i) and φ (i) (where i=1,2) is proportional to ε i or O(ε i ). By substituting the perturbation expansions for
φ and η into the Laplace equation (Eq. 2.3) and the bottom boundary condition (Eq. 2.4), we obtain two separate
boundary conditions as follows:6This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

∇2 φ (1) = 0;

∂ φ (1)∂z
We also have:∇2 φ (2) = 0∂ φ (2)
∂z

= 0;
z=−h

(2.11)=0(2.12)z=−h∂ 2 φ (1)∂ φ (1)
+g
=0
2
∂t
∂z

(2.13)"#
2 φ (1)(1)
2∂ 2 φ (2)∂ φ (2)
∂
∂
∂
∂
φ
+g
=−
∇φ (2) − η (1)
+g
∂ t2
∂z
∂t
∂t
∂ t2
∂z

(2.14)

η (1) = −
η

(2)

1
=−
g

1 ∂ φ (1)g ∂t!
∂ φ (2) 1∂ 2 φ (1)1(1) 2
+ |∇φ | − η (1)∂t2g∂ z∂ t(2.15)(2.16)

where z = 0.
• First-Order Solution
We select a first-order velocity potential, φ (1) of the following form which satisfies 2.11, 2.12, and 2.13:

gcosh[|~ki |(h + z)]aimcosh(|~ki |h)
i=1m=1 ωiNM

φ (1) (~x, z,t) = (−1) ∑ ∑(2.17)· sin(ωi t −~kim ·~x + εim )gcosh[|~ki |(h + z)]· exp(ιωi t)
Aim
cosh(|~kim |h)i=1m=1 ωiNM⇒ φ (1) (~x, z,t) = Re[ ∑ ∑ ι(2.18)· exp(−ι (~kim ·~x)]where Aim = aim exp(−ιεim ); ~x = (x, y) is a point on the horizontal x-y plane; ωi is the angular frequency; ~ki is thewave number which is related to the frequency, ωi, through the linear dispersion
relation, ωi2 = g|~ki |tanh(|~ki |h)√(where h is the water depth); ι = −1 and ~kim = |~ki | cos θm , |~ki | sin θm ; N and M are the total number of frequen-cies and the total number of wave directions considered, respectively. Also, aim refers to the component spectral
amplitudes, which are calculated as follows: 2 aE im = S(ωi , θm )∆ω ∆θ
(2.19)
2
where, E [•] is the expected value of •.

By substituting Eq. 2.17 into Eq. 2.15, we obtain the first-order component of the surface wave elevation, η (1) ,as follows:

7This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

NMη (1) (~x,t) = ∑ ∑ aim cos(ωit −~kim ·~x + εim )(2.20)

i=1m=1NM⇒ η (1) (~x,t) = Re[ ∑ ∑ Aim · exp(ιωit)
i=1m=1(2.21)· exp(−ι (~kim ·~x)]• Second-Order Solution
Second-order waves are obtained as a result of sum and difference interactions between pairs of frequencies andthe phases of the second-order contributions are determined by the sum and difference interactions of the phases ofthe first-order component phases, which are random. The second-order velocity potential which satisfies Eqs. 2.11,
2.12, and 2.14 is given as follows:NM

φ (2) (~x, z,t) = (−1) · ∑∑ aim a jn · B±i jmn · sin((ωi ± ω j )ti, j=1m,n=1(2.22)− (~kim ·~x ±~k jn ·~x) + (εim ± ε jn ))NM⇒ φ (2) (~x, z,t) = Re[ ∑∑ ι Aim A jn · B±i jmn · exp(ι (ωi ± ω j )t)i, j=1m,n=1(2.23)· exp(−ι (~kim ·~x ±~k jn ·~x))
By employing the first-order potential, φ (1) , the first-order surface elevation. η (1) , and the second-order potential, φ (2) , in Eq. 2.16, we obtain a second-order correction to the linear sea surface elevation as follows:NMη (2) (~x,t) = ∑∑ aim a jn · Ki±jmn · cos((ωi ± ω j )ti, j=1m,n=1(2.24)− (~kim ·~x ±~k jn ·~x) + (εim ± ε jn ))N⇒ η (2) (~x,t) = Re[ ∑M∑ Aim A jn · Ki±jmn · exp(ι (ωi ± ω j )t)i, j=1m,n=1(2.25)· exp(−ι (~kim ·~x ±~k jn ·~x))
Quadratic transfer functions (QTF), Ki±jmn and B±
i jmn , derived by Sharma and Dean [1] are given as follows:#D±
i jmn − (ki k j cos(θm − θn ) ∓ Ri R j )p+ (Ri + R j )4
Ri R j1
Ki±jmn ="1B±
i jmn =

cos[ki±jmn (h + z)] D±
i jmn

4 cos[ki±jmn (h)] ωi ± ω j(2.26)(2.27)

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whereRi = |~ki | tanh(|~ki |h)(2.28)pp√√
Ri ± R j )[ R j (ki 2 − Ri 2 ) ± Ri (k j 2 − R j 2 )]p 2√[( Ri ± R j ) − ki±jmntanh(ki±jmnh)]p 2√[2( Ri ± R j ) ][ki k j cos(θm − θn ) ∓ Ri R j ]+p 2√[( Ri ± R j ) − ki±jmntanh(ki±jmn h)](D±i jmn =

(2.29)In the above, ki+jmn and ki−jmn are given as follows :q
ki 2 + k j 2 + 2ki k j cos(θm − θn )qki−jmn = ki 2 + k j 2 − 2ki k j cos(θm − θn )ki+jmn =(2.30)For infinite water depth, the equations proposed by Sharma and Dean [1] reduce to those derived by LonguetHiggins et al. [2] for deep water. Also, for ~ki = ~k j and N = 1, the formulas for the velocity potential and surface
elevation reduce to the familiar Stokes second-order equations [4].
• Validity of Second-Order Wave Theory
While the second-order irregular wave modeling outlined above is a more accurate representation of irregularseas in shallow waters compared to the linear irregular wave model, it obviously does not model the complete nonlinear characteristics of ocean waves and is not valid for all cases. The physical parameter that determines the range ofvalidity is the wave steepness. When the wave steepness exceeds a certain value, the second-order model is no longer
valid and a higher-order model is then required. In fact, when waves become too steep, they can break and no model
based on solution of Laplace’s equation (given in terms of velocity potential) is valid.
2.2.2

Second-order wave kinematics

Second-order wave kinematics are evaluated using the wave velocity potentials presented in Sec. 2.2.1.2. It is assumed that the considered fluid is incompressible, inviscid, and irrotational.
2.2.2.1

Water particle velocity

The velocity field of the irrotational fluid can be expressed as follows:~u = ∇φ(2.31)~u(1)(1) (1) (1)= (ux , uy , uz ) = ∇φ (1) =∂ φ (1) ∂ φ (1) ∂ φ (1)
,
,
∂x
∂y
∂z

!

(2.32)~u(2)(2) (2) (2)= (ux , uy , uz ) = ∇φ (2) =∂ φ (2) ∂ φ (2) ∂ φ (2)
,
,
∂x
∂y
∂z

!

(2.33)

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2.2.2.2

Water particle acceleration

The acceleration of a water particle can be evaluated by the material or substantial derivative of the velocity vector,
~u:

∂~u
D
~u =
+~u| ·{z
∇~u}
Dt
∂t
|{z}

(2.34)

Term 2

Term 1

where Term 1 and Term 2 are the local acceleration at a fixed point and the convective acceleration, respectively.
We are only interested in the acceleration at a fixed point, which is evaluated as follows:

2.2.2.3∂~u(1) (1) (1)= (ax , ay , az ) =

(1)

~a

(1)

∂~u
(2) (2) (2)= (ax , ay , az ) =

(2)

~a

(2)

∂t

∂t

(1)

(1)

(1)

=

∂ ux ∂ uy ∂ uz
,
,
∂t
∂t
∂t

=

∂ ux ∂ uy ∂ uz
,
,
∂t
∂t
∂t

(2)

(2)

(2)

!

(2.35)!

(2.36)

Dynamic pressure

To obtain the first- and second-order pressure, we substitute the perturbation expansions of the velocity potential into
Bernoulli’s equation (Eq. 2.6) and separate terms of the same order:∂p
1+ gz + (φ (1) + φ (2) + ...) + ∇(φ (1) + φ (2) + ...) · ∇(φ (1) + φ (2) + ...) = −Q
ρ
∂t
2
"
# "
#
p
∂ φ (1)∂ φ (2) 1 (1)(1)= −gz − Q +++O(ε 3 ) + ...
+ ∇φ · ∇φρ∂t∂t2| {z } |
{z
}
O(ε )

(2.37)(2.38)O(ε 2 )

(1)

(2)

Thus, the first- and second-order dynamic pressures, pd and pd , are obtained as follows [5] [6]:(1)pd = −ρ(2)
pd = −ρ"∂ φ (1)∂t(2.39)#"#∂ φ (2) 1 (1)∂ φ (2)
1(1)+ ∇φ · ∇φ= −ρ−ρ ~u(1) ·~u(1)
∂t
2
∂t
2
{z
}
|
{z
}|
Term 1(2.40)

Term 2where Term 1 and Term 2 are the second-order potential term and the quadratic interaction term, respectively.
The second-order dynamic pressure in this study is evaluated by only including the contribution of the second-order
potential term, Term 1.
2.2.3

Numerical simulation of second-order waves

In this section, the criteria and algorithms used to numerically simulate irregular second-order wave are presented.
First, we discuss the issue of validity of the second-order wave theory that was briefly raised in Sec. 2.2.1.2.
10This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2.2.3.1

Limitation of Second-Order Wave Theory and Cut-Off Frequency

The solution of the second-order boundary value problem is derived based on a perturbation approach, which uses
wave steepness, ε ≪ 1 as an expansion parameter. For a regular wave, Dean and Dalrymple [7] defined ε = ka/2,
where k and a are the wavenumber and wave amplitude, respectively. According to them, the second-order wave
theory is valid if two criteria are fulfilled:• Convergence: First, the ratio of the second-order term to the first order term in Eq. 2.9 must be much smaller
than unity:
ε 2 φ (2) kaφ (2)=≪ 1(2.41)εφ (1)
2φ (1)⇒

3 ka cosh(2kh)≪ 1
8 cosh(kh) sinh3 (kh)(2.42)• No bump in the trough: Second, the physical properties of the wave profile require that there is no bump in
the trough. This is indicated by a negative second derivative of the wave trough, which leads to the criterion:ka <sinh3 (kh)cosh(kh)[2 + cosh(2kh)](2.43)In addition to the above two criteria, the breaking criterion for the wave steepness must be fulfilled. For arbitrary water depth, the Miche breaking criterion is as follows [8]:2aH=
< 0.142 tanh(kh)L
2π /k(2.44)⇒ ka < 0.142π tanh(kh)(2.45)

Figure 2.3 illustrates the different limiting criteria expressed for ka as a function of kh. The shaded region in
Fig. 2.3 represents wave steepness conditions for which second-order wave theory is valid. According to the figure,
we note (except when kh → 0) that:• when kh < 0.62π , the maximum wave steepness is restricted by the “no bump in the trough” criterion in
Eq. 2.43.
• when kh > 0.62π , the maximum wave steepness is restricted by the breaking wave criterion in Eq. 2.45.
In the regular wave case, the validity of the second-order wave theory can be controlled by simply limiting
the considered maximum wavenumber in order to satisfy the three criteria (see Eqs. 2.42, 2.43, and 2.45). However, because these criteria were derived for regular waves, they may not be directly extended for use with irregularwave. The following three criteria can be used to arrive at the maximum wave frequency for valid application of thesecond-order wave theory:• Hu and Zhao [9]: Based on results from numerical simulations, Hu and Zhao [9] suggested that the secondorder wave model presented here is valid as long as Hs /Lz is less than approximately 0.08, where Hs pis thesignificant wave height and Lz is the wavelength corresponding to the zero-crossing frequency, ωz = γ2 /γ0 ,where γn is given byZγn =ω n S(ω )d ω

(2.46)• Stansberg [10]: Stansberg [10] proposed a useful criterion to establish the highest frequency for which
second-order wave theory may be considered valid. It is given in terms of a cut-off wavenumber as follows:
kcut =

2E(amax )[1 + 1/2(k pE(amax ))](2.47)

11

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shallow

Intermediate depth

deep

ConvergenceNo bump
Breaking wave

0.5

ka

0.4
0.3
0.2
0.1
0

૙Ǥ ૚࣊

૙Ǥ
kh૟૛࣊

kh

࣊

Figure 2.3. Different limiting criteria for wave steepness, ka, as afunction of normalized water depth, kh, for second-order waves

where kcut is related to the limiting (cut-off) frequency, ωcut , through the linear dispersion relation and k p is thewavenumber corresponding to the spectral peak period, Tp ; E(amax ) is the expected value of the extreme wave
amplitude of a Gaussian wave record, which follows a Rayleigh distribution. The denominator in Eq. 2.47 is a
simplified second-order correction for a non-Gaussian wave field. According to extreme value theory, E(amax )is given as follows:E(amax ) =

Hs p
γem
]
[ 2 ln(Nz ) + p
42 ln(Nz )
Nz =

tmax
Tz

(2.48)(2.49)

where γem = 0.577... is the Euler-Mascheroni constant; Nz is the number of zero-upcrossing wave cycles andtmax is the duration of the simulation.
• DNV-RP-C205 [11]: DNV-RP-C205 [11] guidelines provide a simpler criterion for the application of secondorder wave theory by defining a limiting cut-off frequency as follows:r2g
ωcut =(2.50)Hs
For irregular waves, the validity of the use of second-order wave theory is significantly affected by the spectralor statistical properties of the considered irregular waves such as the peak wave period (Tp ), the significant wave
height (Hs ), and the duration of the simulations (tmax ), which influence the limiting criteria. During a numericalsimulation of the second-order wave kinematics, therefore, the maximum wave frequency arbitrarily assigned without considering the spectral properties of the irregular waves may result in the generation of physically incorrect
12This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

second-order wave kinematics. In this study, the criterion proposed by Stansberg [10] is employed to simulate thesecond-order sea surface elevation and associated wave kinematics.
2.2.3.2

Sampling Theorem and Additional Requirement of Cut-Off Frequency, ωcut

In digital simulation of the sea surface elevation and associated kinematics, we replace continuous time, t, by adiscrete time array, t p = p∆t, where ∆t = tmax /Nt , such that p = 1, 2, ..., Nt . By virtue of the periodicity of Fourier
series, we have2π∆ω =(2.51)
tmax
Consideration of the Nyquist frequency provides a prescription for the nominal sampling interval required to
avoid aliasing. This may be stated simply as follows:• The sampling frequency, ωs = 2π /∆t, should be at least twice the highest frequency contained in the signal.
In mathematical terms, we have:ωs ≥ 2ωcut

If ωcut = Nω ∆ω , we must then satisfy the following inequality:

 

2π
2π
2π
=
ωs =
≥ 2ωcut = 2Nω ∆ω = 2Nω
∆ttmax /Nttmax⇒ Nt ≥ 2Nω

(2.52)(2.53)(2.54)In the numerical simulation of second-order wave kinematics, the largest frequency of wave components generated by the second-order wave-wave interaction is 2Nω ∆ω , which is associated with the sum-frequency interaction.
Therefore, to satisfy the sampling theorem for second-order wave simulation, we must ensure that:Nt ≥ 4Nω

(2.55)

This simply means that the cut-off frequency, ωcut , evaluated by the criterion presented in Sec. 2.2.3.1 mustsatisfy:htmax i
ωcut
ωcut
Nt =
≥ 4Nω = 4=4(2.56)∆t∆ω
2π /tmax⇒ ωcut ≤2.2.3.3π2∆t(2.57)

Singularity of Quadratic Transfer Function (QTF)

Formulations for the first- and second-order wave kinematics shown in previous sections are determined from thesolution of the boundary value problem (see Eqs. 2.3 - 2.8). When we implement these formulations to numericallysimulate wave kinematics, some problems arise that stem from the physically correct or weakly-correct assumptions
considered in solution of the boundary value problem. One of the issues has to do with the singularity of the firstand second-order wave kinematics transfer functions. This singularity problem is also seen in QTFs proposed byother researchers (Longuet-Higgins [2]; Marthinsen and Winterstein [12]; Nwogu [13]) presented below.
QTF proposed by Longuet-Higgins [2]B±ij =g2 (ωi ± ω j )(~ki · ~k j ∓ |~ki ||~k j |)
ωi ω j (ωi ± ω j )2 − g|~ki ± ~k j |(2.58)

13

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QTF used by Marthinsen and Winterstein [12]22g2 |~ki ||k~ j |g2 ωi |~k j | ±ω j |~ki |12
2
2ωi ω j − 4 (ωi + ω j ± ωi ω j ) + 4 ωi ω j (ωi ±ω j )|~k |±|k~ |(ωi ± ω j ) − g ωii ±ω jj tanh[(|~ki | ± |~k j |)h]g2
B±i j = (1 − δi, j )ωi ω j(2.59)

where δi, j = 1 if i = j and zero otherwise. This is introduced to avoid the singularity of B±ij.
QTF proposed by Nwogu [13]Ki±j =++

ωi ω j (ki±j h)2 cos(θi − θ j )[1 − (α + 1/3)(ki±j h)2 ]2 λ ki k j h 3′ ′′ωi±j [1 − α (ki±j h)2 ][ωi k j h(|~ki |h ± |~k j |h cos(θi − θ j ))2 λ ki k j h 3′ ′(2.60)′

ω j ki h(|~ki |hcos(θi − θ j ) ± |~k j |h)]′ ′2 λ ki k j h 3

λ = (ωi±j )2 [1 − α (ki±j h)2 ] − g(ki±j )2 h[1 − (α + 1/3)(ki±j h)2 ]′ki = |~ki |[1 − (α + 1/3)(|~ki|h)2(2.61)(2.62)

where α = (zα /h)2 /2 + (zα /h) and zα ≈ −0.53h from shallow water depths up to the deep water depth limit.

• Singularity at ω = 0
When ωi in Eq. 2.17 approaches zero, the denominator of the equation approaches zero. Although the numerator also approaches zero, we may have computational difficulties and special treatment may be required during
numerical simulation of the kinematics depending on the software tool used. To avoid discontinuity or singularity
problems at zero frequency, one can simply set the kinematics equal to zero there and not attempt evaluation.
QTFs of the second-order wave elevation and the velocity potential, i.e., Ki±jmn and B±
i jmn , also have similar
singularity
issuesatzero
frequency.
As
shown
in
Eq.
2.26,
the
denominator
of
the
first
term
in the expression forp
Ki±jmn is Ri R j , which approaches zero when either ωi or ω j approaches zero.

±In the numerator of the expression for B±
i jmn in Eq. 2.27, the term, Di jmn , appears that is defined in Eq. 2.29. The±
numerator in both the first and second terms in the expression for Di jmn approaches zero when either ωi or ω j goes tozero. In this case, there is no need for any special treatment during numerical simulation because the denominator ofB±
i jmn is not zero unless ωi = ω j = 0.

Based on the possibility of singularities in the first- and second-order transfer functions, we assume that theformulations presented in Sec. 2.2.1.2 are not used to evaluate first- and second-order wave kinematics when ωi = 0
or ω j = 0. This assumption is physically acceptable because we are assuming that a zero-frequency regular wave
does not have any wave energy and that the zero-energy wave component does not interact with any other wave
components.
• Singularity at diagonal components of Ki−jmn and B−i jmn
Another singularity to be considered during numerical simulation results from the discontinuity in the diagonal−−component of Ki−jmn and B−
i jmn . When ωi = ω j , the denominator terms for Di jmn are equal to zero, which makes Ki jmn
and B−
i jmn singular along the diagonal components. Physically, the interaction between two wave components propagating in opposite directions with same magnitude results in total energy loss. This can be explained by studying
Fig. 2.4, which shows how two wave components interact. As shown in the figure, two free wave components, ~ki

14This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

and ~k j , generate new bounded wave components, ~ki +~k j and ~ki −~k j , by sum and difference interactions, respectively. Therefore, unlike difference-interaction QTFs for second-order wave (hydrodynamic) forces, in the case of
kinematics, all diagonal components of Ki−jmn and B−
i jmn should be set to zero; this only means that total energy loss
results from the interaction of two wave components with the same magnitude and opposite propagation directions,
i.e., ~ki −~ki .

‫ݕ‬

‫ݕ‬

‫ݔ‬

‫ݔ‬
(a) Sum interaction.

(b) Difference interaction.

Figure 2.4. Sum and difference interaction of wavenumber vectors

2.2.3.4

Inverse Fast Fourier Transform

Agarwal and Manuel [14] discuss the numerical simulation of uni-directional second-order waves in detail. It involves a single sum of component harmonics that can be efficiently computed using the Inverse Fast Fourier Transform (IFFT). On the other hand, simulation of directional irregular second-order waves involves a double sum, which
can be computationally expensive. The procedure presented by Agarwal and Manuel [14] made it possible to rewrite
the double summation as a single summation by appropriately re-assembling and rewriting indices (or coefficients)of terms involved. Once the indices for an equivalent single summation are assembled, a one-dimensional IFFT
procedure, similar to that for linear waves, can be used to carry out the nonlinear (second-order) wave simulations
efficiently. We extend this same procedure to the numerical simulation of irregular directional second-order waves. A
flowchart for calculation of directional second-order wave kinematics and resulting hydrodynamic loads is presented
in Fig. 2.5. This calculation procedure is incorporated into the open-source software, FAST, for coupled aero-servohydro-elastic analysis of offshore wind turbines.

2.3 Hurricane Winds
UMCM provides mean wind field data corresponding to 10 meters above the mean surface level generated at a
1.3 km grid resolution. This large-scale mean wind field data must be down-scaled using a scale-bridging procedure
to provide the needed wind field at about a 10 m resolution around the rotor to allow meaningful aerodynamic load
computations. In this study, the turbulent wind fields are simulated using a spectral method based on characteristicsof the surface wind field obtained from UMCM; these characteristics consist of the sustained 1-minute surface windspeeds, U1min , the mean wind direction, the surface drag coefficient, CD , and the surface stress, τ .

15This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Wave Spectrum
S(ωi , θm )Random amplitude and Phaseaim ∼ RayleighE[a2im ] = 2S(ωi , θm )∆ω ∆θ
εim ∼ Uniform[0, 2π ]First-Order

Second-Order2-D Fourier coefficient(r = x or y or z)

Fourier coefficient(r = x or y or z)
M

Xi =
M

c Ur,i =

(1)

∑ Xim

Xi±j =

m=1

M

(1)

(1)

∑ Ur,im and U̇r,i = ∑ U̇r,im

± =
Ur,i
j

m=1

m=1

M

M

M

M

(2)±

∑ ∑ Xi jmn

m=1 n=1

M

(2)±

M

(2)±

± =
∑ ∑ Ur,i jmn and U̇r,i∑ ∑ U̇r,i jmn
j

m=1 n=1m=1 n=1

M M (2)±∑ ∑ Pi jmn
m=1 n=1(2)± (2)±(2)±(2)±
Xi jmn , Ur,i jmn , U̇r,i jmn , and Pi jmn ⇒

M (1)
∑ Pim
m=1
(1) (1)(1)(1)
Xim , Ur,im , U̇r,im , and Pim ⇒Pi±j =Pi =Appendix C

Appendix C

Assemble 1-D Fourier coefficient 
Yk± = ∑∑ Xi±j
|i± j|=k





±
±
Zr,k
= ∑∑ Ur,i± j and Żr,k= ∑∑ U̇r,i± j|i± j|=k |i± j|=k
Pk± = ∑∑ Pi±j
|i± j|=kTime series

Time seriesηη (1) (t) ← R[IFFT (Xi )]

(2)



(t) ← R IFFT Yk±

h
 i
(2)
±
ur (z,t) ← R IFFT Zr,k(1)

ur (z,t) ← R[IFFT (Ur,i )]

h
 i
(2)
±
u̇r (z,t) ← R IFFT Żr,k



(1)
u̇r (z,t) ← R IFFT U̇r,ip(1) (z,t) ← R[IFFT (Pi )]p(2) (z,t) ← R IFFT Pk±

Add First- and Second-Order component
η (t) = η (1) (t) + η (2) (t)u(z,t) = u(1) (z,t) + u(2) (z∗ ,t)u̇(z,t) = u̇(1) (z,t) + u̇(2) (z∗ ,t)p(z,t) = p(1) (z,t) + p(2) (z∗ ,t)z∗ = min(0, z)

Figure 2.5. Flowchart for the numerical simulation of second-order directional waves

16This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2.3.1

Mean wind field

We are interested in simulations of 1-hour duration for turbine response statistics; for this, we desire information on
the 1-hour mean wind speed at hub height of the turbine. This requires conversion from 1-minute to 1-hour averaging in time as well as adjustment of 10 m winds to elevations corresponding to the rotor swept area of the turbine. In
a World Meteorological Organization (WMO) report by Harper et al. [15], conversion factors are recommended for
relating the WMO standard 10-minute average wind speed to 1-minute, 2-minute, and 3-minute “sustained” winds
in tropical cyclone conditions. The report indicates that an at-sea conversion factor between the 1-minute sustained
wind speed and the 10-minute average wind speed should be 0.93, rather than the traditional value of 0.88, which isshown to be associated more with an off-land exposure. Accordingly, this conversion factor of 0.93 is used to estimate the 10-minute mean wind speed from the 1-minute sustained wind speed. Since there is not enough publisheddata to obtain an estimate of the 1-hour mean wind speed from the 1-minute or the 10-minute wind speed, we assume
that the 1-hour mean wind speed (needed for this study) is the same as the 10-minute wind speed, without applying
any additional conversion factor. Bryan and Rotunno [16] showed that the grid size used in hurricane wind field
simulation can significantly affect the wind speed averaged over the grid. Although the mean wind velocity fields
from UMCM are generated for a coarse 1.3 km grid resolution, we interpolate these mean wind fields over a finer
grid (10 m × 10 m) over the wind turbine rotor swept area, which is used for the dynamic analysis of the selected
offshore wind turbine in this study.
Among various approaches adopted to describe the variation of wind speed with elevation in the atmosphericboundary layer, Panofsky and Dutton [17] proposed a form for the vertical wind speed profile that includes a stability
term, Ψm , from planetary boundary layer theory, as follows:zu∗
U10min (z) = [ln( ) − Ψm ](2.63)
κz0pwhere u∗ is the friction velocity, equal to τ /ρa ( where τ = wind stress on the ocean surface and ρa = air density),κ is the von Kármán constant, and z0 is the surface roughness length. Powell et al. [18] showed that logarithmic
mean wind profiles apply in tropical cyclones at least in the lowest 200 m and then the profile levels off slightly witha peak near 500 m. Also, Hsu [19] has shown that, during a hurricane, the effect of stability in Eq. 2.63 is negligible.
Accordingly, in this study, we use the familiar logarithmic law wind profile to estimate surface mean wind speeds
during a hurricane:u∗z
U10min (z) = ln( )(2.64)
κz0
The friction velocity, u∗ , and the surface roughness length, z0 , in Eq. 2.64 were derived based on mean wind fieldparameters from UMCM as shown in Fig. 2.6. Because the wind stress, τ , from UMCM takes into account the
influence of wave height, the surface mean wind speeds evaluated by Eq. 2.64 and the wave heights are coupledthrough τ . Vertical wind profiles are evaluated with respect to the mean surface level (MSL); variations in the MSL
due to storm surge are not considered.
2.3.2

Turbulent wind field

The turbulence intensity is an important controlling parameter for simulating turbulent wind fields; it is dependent
on the atmospheric stability and the surface roughness length. Ishizaki [20] evaluated the turbulent intensity of hurricane winds as a function of mean wind speed up to 30 m/s and found that it generally reduces with an increase inmean wind speed. On the other hand, studies by Ochi [21] showed that, for hurricane winds over 40 m/s, turbulence
intensity increases slightly with increase in mean wind speed; the increase in sea surface roughness with wind speed
may be one of the factors that contributes to this increase in turbulent intensity. Due to the lack of measurement dataof hurricane turbulent wind fields over water, in this study, the relationship in IEC 61400-1 [22] between turbulence
intensity and wind speed (for a selected wind turbine class) is employed.
The modified Kaimal model, defined in the IEC wind turbine design standard (IEC 61400-1) [22], assumes
neutral atmospheric stability. The model is widely used in turbine loads studies and is presented here as the basis for
17This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

0
80 −3
x 10
2.5

90

100

110

(m/s)
1min(z=10m)

20
0
80 −3
x 10
3
2

120

0

2
1.5
1
80

40

U

20

60

z (mm)

40

Cd

U1min(z=10m) (m/s)

60

90

100

110

u (m/s)

120

90

100

110

120

4
2

90

100
hour

110

120

1

*

τ (N/m2)

110

2

6

0
80

100

1
0
80

120

90

90

100
hour

110

0
80

120

(a) UMCM (WRF) output.

(b) Derived values.

Figure 2.6. Various mean wind field parameters from UMCM (U1min , Cd , and τ ) and derived wind properties (z0 and u∗ ); where U1min =1-minute mean wind speed, Cd =drag coefficient, τ =wind stress, z0 =surface roughness length, and u∗ = friction velocity (note:the blue dashed line corresponds to Site B and the red solid line corresponds to Site A).

18

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turbulence modeling and, later, it is combined with a steady wind profile to define the neutrally stable boundary layeror neutral boundary layer(NBL). The power spectral density functions for any of the three turbulence components, K= u′ , v′ , or w′ , are given as follows:
4σK2 LK /Uhub
SK ( f ) =(2.65)
5(1 + 6 f LK /Uhub) 3
where SK ( f ) (in (m/s)2 /Hz) is the one-sided power spectrum for turbulence component, K; σK is the standard deviation of turbulence component, K; f refers to the frequency of interest in Hertz (Hz); Uhub is the mean hub-heightmean wind speed; and LK is an integral length scale parameter that can be computed as follows:
Lu′
Lv′

=
=

8.10ΛU
2.70ΛULw′=

0.66ΛU(2.66)

where ΛU is a longitudinal turbulence scale parameter taken to be 42 m corresponding to a wind turbine with hub
height 90 m above the mean water level [22]. The required turbulence standard deviations may be computed asfollows:

σu′
σv′
σw′

=

Ire f (0.75Uhub + 5.6 m/s)==

0.8σu′
0.5σu′(2.67)

where Ire f is the expected value of the turbulence intensity at a hub-height mean wind speed of 15 m/s. For turbulence category B (medium turbulence characteristics) in wind turbine design, Ire f = 14%. The cross-power spectral
density function corresponding to locations, i and j, (for any turbulence component) is defined as follows:q
Si j ( f ) = Cohi j ( f ) Sii ( f )S j j ( f )(2.68)
where Cohi j ( f ) is the coherence function. For turbulence component, K, we have:


s
2 
2
f
r
r
(K)

K = u′ , v′ , w′ : Cohi j (r, f ) = exp −12
+ 0.12Uhub
LK(2.69)

in which r is the separation (distance) between points i and j.

2.4 Turbine Response
2.4.1

Turbine Model

A 5-MW wind turbine model developed at NREL and representative of utility-scale offshore wind turbines being
manufactured today is considered. The turbine is a variable-speed, collective pitch-controlled machine with a maximum rotor speed of 12.1 rpm; its rated wind speed is 11.5 m/s. It is assumed to have a hub height of 90 meters(above the mean sea level) and a rotor diameter of 126 meters. The turbine is assumed to be sited in 20 meters of water; it has a monopile support structure of 6-meter diameter, which is assumed to be rigidly connected at the seafloor.
Fundamental frequencies for the tower fore-aft and side-to-side bending modes are around 0.32 Hz and 0.31 Hz,
respectively. This turbine model with monopile foundation has been the subject of several simulation studies (see, forexample, Agarwal and Manuel [23], [24]).

19

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

$NCFG
4QVQT&KCOGVGT0CEGNNG

O

6QYGT
5GTXKEG
2NCVHQTO
5GC.GXGN(41068+'9*WD*GKIJVO

5+&'8+'9
9CVGT&GRVJ
O

5GC$GF/QPQRKNG
5QKN

Figure 2.7. Selected 5-MW offshore wind turbine with a monopile support structure

20This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2.4.2

Swell versus Wind Seas

As shown in Fig. 2.2, the hurricane directional waves are composed of swell at low frequencies and locally generated
waves above approximately three times the spectral peak frequency. There is, however, no tendency for the spectrum
to become bimodal in either frequency or direction. Rather, the spectra are directionally skewed, with a smooth directional transition from low frequency to high frequency [25]. Following Holthuijsen [26], wind sea waves are more
irregular and short-crested, respond quickly to wind variations, and are characterized by a rather broad spectrum.
On the other hand, swell consists of rather regular long-crested waves whose evolution is not as strongly affected by
the wind, and its spectrum is narrower. Still, the distinction between wind sea and swell is often not obvious. Underchanging winds (in both magnitude and direction) wave systems can overlap in parts of the frequency-direction domain giving rise to a rather continuous spectrum in which the presence of two or more distinct systems is not clearly
discernible. Portilla et al. [27] introduced several schemes to separate a swell from a locally generated wave, which
include a wind sea and swell identification scheme that uses the directional wave spectrum and available wind data(on the mean wind direction, ψ , and the mean wind speed, Uo ). If a directional wave spectrum and this wind information are available, a straightforward step to identify wind sea and swell components is to apply a definition forwind seas based on wave age [28]. The wind sea and swell identification scheme that we use is described in Fig. 2.8.
According to this separation scheme, wave components that (1) propagate in wave direction, θ , between ψ − π /2and ψ + π /2 and (2) travel at a wave phase velocity, c p , slower than Uo cos(θm − ψ ) are classified as being part ofa wind sea. In Fig. 2.9, the directional wave spectrum for a location on the left side of the track of Hurricane Ike(i.e., Site B), as obtained from the UMCM at 100 hours after the start of the simulation, is separated into wind sea
and swell by the wave age criterion proposed by Komen et al. [28]; in this figure, the wave spectrum is normalized
by a maximum wave spectrum value.
ŝƌĞĐƚŝŽŶĂůƐƉĞĐƚƌƵŵ

^;ʘŶ ͕ઙŵͿtŝŶĚƐƉĞĞĚ ͗hŽtŝŶĚĚŝƌĞĐƚŝŽŶ͗ΨŶсϭ͖ŵсϭŵсŵнϭ

EK^ǁĞůůɷ сͮઙŵͲ ΨͮфʋͬϮ͍ŶсŶнϭz^EKωŶхŐͬ;hŽĐŽƐɷͿ͍z^

000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000
000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000

ΎŐ͗ŐƌĂǀŝƚĂƚŝŽŶĂůĂĐĐĞůĞƌĂƚŝŽŶ

tŝŶĚ^ĞĂ
Figure 2.8. Wind sea and swell separation procedure using wave age criterion

Using the procedure outlined, directional wave spectra from 80 to 120 hours are separated into wind sea andswell. In Fig. 2.10, wave variances (ση2 ) and mean wave frequencies ( fm ) of wind sea and swell are evaluated after
the separation. Before the hurricane passes the selected sites, the swell components significantly contribute to theoverall wave energy. Note that the mean wave frequency of the swell component is significantly below 0.3 Hz (whichis the resonant frequency associated with the first tower bending mode for the wind turbine used in this study); thissuggests that the contribution of swell to total turbine response may not be significant.
The variation of the mean wave frequency and wave direction for swell and wind seas are presented in Fig. 2.11.

21

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0.4

1

Hs = 5.0 m

Wind
0.8

0.3

f(Hz)

0.6
0.2

Swell
0.4

0.1
0.2
mean winddirection
1

0.5

0

0
E

N

W

S

E

0

0
0.5
1

Figure 2.9. Wind sea and swell separation, normalized by the wave spectrum maximum value (blue line: swell spectrum; red line: wind sea spectrum).

22

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d (km)

600
400
200
0

σ2η(m2)6

30fm(Hz)

0.4

0.2

0
80

85

90

95

100
hour

105

110

115

120

105

110

115

120

(a) Site B.

d (km)

600
400
200
0

σ2η(m2)6

30fm(Hz)

0.4

0.2

0
80

85

90

95

100
hour
(b) Site A.

Figure 2.10. Variation with time in the distance between the site and hurricane eye (d), wave variance (ση2 ), and23+ swell; blue solid line: swell; red solid line: wind sea)mean wave frequency ( fm ) (black dashed line: wind sea

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

While the mean wave frequency and wave direction corresponding to wind seas are significantly changed with thehurricane movement because these wind seas are greatly affected by local wind direction and speed changes, thevariation in mean wave frequency and wave direction corresponding to swell is relatively insignificant because theevolution of swell is not as strongly affected by the local wind.

NN

at 120hrs
at 120hrs

at 120hrs

at 120hrs
at 80hrs

at 80hrs
at 80hrs

at 80hrs(a) Site B.

(b) Site A.

Figure 2.11. Variation of the mean wave frequency and wave direction every 10 hours; N indicateswaves propagating toward north, etc., and the dashed and solid circles (inner to outer) correspond towave frequencies of 0.1, 0.2, 0.3, and 0.4 Hz (blue dots and line: swell sea; red dots and line: wind sea).

After the hurricane waves are separated into wind sea and swell by the procedure described in Fig. 2.8, the variances of the tower bending moment resulting from the wind sea and swell are compared in Fig. 2.12. Only the effectof wave loads is included in evaluating the turbine response. Although the contribution from swell components tothe overall wave energy is comparable with and even sometimes higher than that from wind seas, the contributionof swell to the fore-aft tower bending moment (FATBM) at the base is relatively very small when compared with
its contribution to the side-to-side tower bending moment (SSTBM). Two possible factors can explain the small
FATBM contribution from swell; these are: (1) the significantly lower mean wave frequency of the swell component
is less than 0.3 Hz which is near the resonant frequency associated with first tower bending mode; and (2) the relatively strong misalignment between the mean wind direction (in the direction of bending of FATBM) and the mean
direction of the swell sea. This second factor also helps explain the higher contribution of swell to SSTBM than to
FATBM. On the other hand, because of the relatively slight misalignment between the wind sea and the mean winddirection, a larger portion of the wind sea energy contributes to FATBM and this leads to higher FATBM response
corresponding to wind seas rather than to SSTBM response. Still, for most of the time covered by the simulation, thecontribution from the wind sea to the SSTBM response is higher than from swell due to the significantly lower mean
wave frequency of the swell component. Overall, it is found that the FATBM response is significantly higher than the
SSTBM response.
2.4.3

Effect of feathered blades

During the hurricane, the blades of the wind turbine are pitched to feather to minimize turbine loads. The effect offeathering blades on the turbine response is evaluated using turbulent wind velocity fields with a mean longitudinal
wind velocity of about 27 m/s at 90 m above MSL. Two difference turbine states are studied: (1) Case 1: the turbine
maintains yaw control and can track the changing wind direction perfectly, and (2) Case 2: the turbine experiences

24

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6

4

4

2
0
80

90

100

110

400
300
200
100
0
80

90

100
hour

110

2
0
80

120
σ2FATBM(MN2−m2)

σ2FATBM(MN2−m2)

σ2η(m2)σ2η(m2)

6

0
80

120

110

110

120

150
120
90
60
30
110

2
0
80

120
σ2SSTBM(MN2−m2)

σ2SSTBM(MN2−m2)

σ2η(m2)σ2η(m2)

2

100
hour

100
hour

(b) FATBM-Site A.

4

90

90

100

4

0
80

120

200

6

100

110

300

6

90

100

400

(a) FATBM-Site B.

0
80

90

120

(c) SSTBM-Site B.

90

100

110

120

90

100
hour

110

120

150
120
90
60
30
0
80

(d) SSTBM-Site A.

Figure 2.12. Variation in the tower response (bending moment) variance with time indicating contributions
from wind sea and swell (black dash line: wind sea + swell; blue solid line: swell; red solid line: wind sea)

25

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Top view (A-A section)
Top view:LQGRQEODGH

Case 1

$
‫ݑ‬
ሺܸ ሻ

<URWRUSODQH

GRPLQDQW
ZLQG 

;

$

&DVH
FURVVZLQG ; URWRUSODQH‫ ݒ‬ሺܸ∥ ሻCase 2<FURVV
ZLQG 

&DVH

‫ݑ‬
ሺܸ∥ ሻ
‫ ݒ‬ሺܸ ሻ

GRPLQDQWZLQG /RDGRQEODGH
ே

=
<

;
் parallel to rotor planeFigure 2.13. Schematic sketch of a parked wind turbine and definition of loads on blades

some yaw misalignment or yaw error. In this study, a single yaw misalignment or yaw error case of 90 degrees isevaluated; note that this may not provide the worst-case scenario for turbine loads. Figure 2.13 shows a schematic
sketch of a parked wind turbine which is considered in this study; one of blades of the turbine is oriented at a 0◦
azimuth angle (i.e., in the 12 o’clock position) and is designated as Blade 1. The figure also shows the top view of across section of Blade 1 with wind flow directions indicated for both cases. Tangential forces, FT and normal forces,
FN , are defined in the figure for Blade 1. The dominant longitudinal wind and the cross (lateral) wind directions inboth cases are aligned with the x and y directions, respectively, of the turbine base coordinate system as shown in the
figure.
Table 2.1 shows 1-hour maximum bending moments at the root of Blade 1 for two different pitch angle cases.
As can be seen, when cross winds are not included, both out-of-plane and in-plane bending moments at the blade
root are decreased when the blades are pitched to feather; the in-plane bending moment is decreased from 1,215
kN-m to 563 kN-m and the out-of-plane bending moment is decreased from 8,053 kN-m to 453 kN-m. However,when cross winds are included, while the out-of-plane bending moment is decreased from 8,278 kN-m to 1,065 kNm by feathering the blades, the in-plane bending moment is increased from 1,688 kN-m to 2,788 kN-m. Also, upon
including the cross wind, in-plane and out-of-plane bending moments are both significantly increased, especiallywhen the blades are feathered. Feathering the blades increases the contribution of the cross wind on blade root
moments.
Table 2.1. One-hour maximum bending moment at blade root with and without the cross wind velocity contribution for a blade at a 0◦ azimuth angle.

without cross windwith cross windin-plane bending moment (kN-m)
pitch angle (β ) = 0◦ pitch angle (β ) = 90◦
1,215
563
1,688
2,788

out-of-plane bending moment (kN-m)
pitch angle (β ) = 0◦ pitch angle (β ) = 90◦
8,053
453
8,278
1,065

Figure 2.14 shows the effect of yaw misalignment on bending moments at the blade root. The blade root inplane bending moments are much more significantly influenced by yaw error than the out-of-plane bending moments. As shown in Fig. 2.13, the dominant wind in Case 2 is aligned with the rotor plane, and it increases the26This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

30
20
10
0

100

200

300
400
time (sec)

500

600

20
v(m/s)

10
0
−10
−20
0

100

200

300
400
time (sec)

500

600

RootMOoP(x103kN−m)u(m/s)

40

4
2
0
−2
−4
−6
−8
0

200

RootMIP(x103kN−m)

50

4
2
0
−2
−4
−6
−8
0

200

400

600

400

600

time (sec)

(a)

(b)

Figure 2.14. (a) Turbulent wind velocity time series and (b) associated blade root bending moments (blue line: Case 1; red line: Case 2)

maximum in-plane bending moment as well as the mean in-plane bending moment.
Figure 2.15 shows the variation in aerodynamic forces at several sections along Blade 1 for the two different
yaw-control cases. At most blade sections and for both cases, the tangential forces, FT , corresponding to bending
moments in the rotor plane are significantly larger than the normal forces, FN , corresponding to the moments orthogonal to the rotor plane. It is also seen that Case 2 leads to larger tangential forces than Case 1.
2.4.4

Effect of turbine control

We now investigate how yaw and pitch controls influence the response of the selected offshore wind turbine during ahurricane. A wind turbine’s control and safety systems play a vital role in regulating aerodynamic loads by adjusting
the blade pitch angle with changing wind speed and the nacelle yaw angle with changing wind direction. In thisstudy, using simulated wind and wave fields, we evaluate: (1) the effect of different nacelle yaw angles relative to thewind direction (i.e., different amounts of yaw error or misalignment); (2) the effect of different blade pitch angles;(3) the effect of different turbine parking strategies—e.g., parked (at standstill) or in an idling state; and (4) load
maxima at different blade azimuthal configurations while the turbine is in a standstill state.
2.4.4.1

Effect of yaw misalignment

First, the effect of yaw misalignment on turbine response is studied; seven different yaw misalignments (θyaw =-90, -60, -30, 0, 30, 60, and 90 degrees) are considered. The 0-degree yaw misalignment corresponds to a case withenough backup power for active yawing so as to have no yaw error; the others could represent cases with insufficient
yaw system backup power that, then, lead to varying degrees of yaw misalignment or error. We assume that thewind turbine is in an idling state and that all the blades are feathered, or turned to a 90-degree pitch angle. From
Fig. 2.16 for an idling turbine at Site A, it can be seen that while the contribution from hydrodynamic loading to
the tower response is only very slightly influenced by the amount of yaw misalignment, the aerodynamic loading
contribution is significantly influenced by it. Peak tower bending moment values occur for a yaw misalignment of

27

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30

Maximum FT(kN)

Maximum FN(kN)

30

20

10

0
0

3

6

9
12
Section #1 215

3 4 5 6 7 8

20

10

0
0

18

3

6

9
12
Section #15

18

9 10 11 12 13 14 15 16 17

Figure 2.15. Maximum normal force (FN ) and tangential force (FT ) on blade (circles: Case 1; triangles: Case 2)

140

140
only aero
only hydroaero+hydro

120

100
My(MN-m)Mx(MN-m)

100
80
60

80
60

40

40

20

20

0

only aero
only hydroaero+hydro

120

-90

-60

-30
0
30
θyaw(degree)

60

0

90

-90

-60

-30
0
30
θyaw(degree)

60

90

Figure 2.16. Maximum tower bending moment at mudline (at 100 hrs) for an idling turbine at Site A.

28

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100

100
My(MN-m)150

Mx(MN-m)

150

50

50

only aero
aero+hydro
0

0

10

20

only aero
aero+hydro30 40 50 60 70
pitch angle(degree)

80

0

90 1000102030 40 50 60 70
pitch angle(degree)80

90 100Figure 2.17. Effect of pitch angle on tower bending moment (at 100 hours) for an idling turbine at Site A.

80

80
azimuth=070

azimuth=90

azimuth=070oazimuth=180

o

60

50

My(MN-m)Mx(MN-m)

60

o

40
30
20

o

azimuth=180

o

50
40
30

10

10
0
80

azimuth=9020;180 Ϳ;90 Ϳ

;0 Ϳ

o

90

100
hour

110

0
80

120

90

100
hour

110

120

(a) wind alone.
80

80
azimuth=070

azimuth=90

azimuth=070oazimuth=180

o

60

50

My(MN-m)Mx(MN-m)

60

o

40
30
20
10
0
80

azimuth=90oazimuth=180

o

50
40
30
20

;180 Ϳ

;90 Ϳ

;0 Ϳ

o

10
90

100
hour

110

0
80

120

90

100
hour

110

120

(b) wind and waves.
Figure 2.18. Effect of blade azimuthal position on tower bending moment for a parked-standstill turbine at Site A during Hurricane Ike.

29

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about 30 degrees; when the misalignment changes from 0 to 30 degrees, the tower bending loads are seen to increaseby as much as a factor of 4.
2.4.4.2

Effect of blade pitch angle

We discuss next the sensitivity of the tower response to the blade pitch angle. In this sensitivity study, all the blades
are locked at a set pitch angle selected to be between 20 and 90 degrees. We assume that the wind turbine is in an
idling state and that the rotor is yawed to be in alignment with the mean wind direction. From Fig. 2.17, as expected,
we see that a 90-degree pitch angle results in the lowest tower response maxima and that, when the pitch angle isreduced from 30 to 20 degrees, an extremely large increase in the maximum tower bending moment results. Clearly,
blade pitch control is important during the hurricane.
60

60
Idlingstand-still

Idlingstand-still

My(MN-m)40

Mx(MN-m)

40

20

0
80

20

90

100
hour

110

0
80

120

90

100
hour

110

120

(a) only wind.
60

60
Idlingstand-still

Idlingstand-still40

Mx(MN-m)My(MN-m)

40

20

0
80

20

90

100
hour

110

0
80

120

90

100
hour

110

120

(b) wind + wave.
Figure 2.19. Effect of turbine parking strategy on tower loads for aturbine at Site A (with no yaw misalignment) during Hurricane Ike.

30

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2.4.4.3

Effect of blade azimuthal configuration

Next, for the wind turbine assumed to be in a parked-standstill state, we evaluate the tower response at three different
blade azimuthal configurations. In the first case, one of blades of the turbine is oriented at a 0◦ azimuth angle (i.e., in
the 12 o’clock position); this blade is designated as Blade 1. In the second and third cases, the azimuth counterclockwise angles of Blade 1 are 90 and 180 degrees, respectively. We assume that the wind turbine is in a parked-standstill
state, that the rotor and nacelle are yawed so as to be aligned with the mean wind direction, and that all three blades
are feathered. From Fig. 2.18, it can be seen that while My (the tower base fore-aft moment), in this case with zeroyaw error, is not significantly different for different blade azimuthal configurations, Mx (the tower base side-to-side
moment) is seen to vary by a considerably larger amount; this range can be as much as 25% of the value, say, atthe zero-degree azimuthal configuration. In general, though not at all times during the simulation, the largest andsmallest tower loads are observed at the 0 and 180 degree azimuthal configurations, respectively.
2.4.4.4

Effect of alternative turbine parking strategies: standstill versus idlingAt very high wind speeds, it is expected that an offshore wind turbine will be parked and held either at a standstill
state or allowed to rotate in an idling state. We now discuss the effect that such alternative turbine parking strategies
have on turbine loads. We assume that the turbine rotor is yawed so as to be aligned with the mean wind direction
and that all three blades are feathered; also, for the parked-standstill case, one of the blades is assumed to be at azero-degree azimuthal position. From Fig. 2.19, we can see that My (the tower base fore-aft moment), in this casewith zero yaw error, is not significantly different for the two different turbine parking strategies. In contrast, Mx (thetower base side-to-side moment) is seen to be noticeably different and the parked-standstill case leads to larger loads
than the idling case.

2.5 Result and Discussion
We have carried out in-depth studies of the response of a monopile-supported 5-MW offshore wind turbine during
Hurricane Ike. The intensity and track of Hurricane Ike are numerically simulated by a fully coupled atmosphericwave-ocean model, UMCM. Based on directional wave spectra resulting from the UMCM output, hurricanegenerated wave kinematics are simulated using directional irregular second-order waves. We have presented thewave modeling approach adopted as well as a numerical procedure for simulating the directional nonlinear waves.
A mean wind field is defined and turbulent wind fields are stochastically simulated using a Fourier-based spectral
procedure; both are based on characteristics of the surface wind field obtained from the UMCM output obtained overa duration of 120 hours.
Because hurricane directional waves are composed of two wave components, swell and wind sea which havedifferent characteristics, their characteristics are evaluated after separating swell and wind sea components fromdirectional wave spectra resulting from the UMCM output based on the wave age criterion. Although the swell
component significantly contributes to overall wave energy, the mean wave frequency of this swell component issignificantly lower than resonant frequencies associated with tower bending. Also, while mean wave frequencies
and wave directions corresponding to wind seas are significantly changed with hurricane movement because thesewind seas are greatly affected by the local wind direction and speed change; in contrast, the variation of mean wave
frequencies and wave directions corresponding to swell is relatively insignificant because the evolution is not asstrongly affected by the local wind.
At selected locations, we evaluated the effect on turbine load maxima, during the simulation of Hurricane
Ike, of: (i) different nacelle yaw angles relative to the mean wind direction (i.e., different amounts of yaw error
or misalignment); (ii) different blade pitch angles; and (iii) different turbine parking strategies (i.e., considering aturbine in either a standstill or idling state). In addition, we studied loads for different blade azimuthal positions.
Based on the numerical studies presented, we can make the following general conclusions:

31

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• While the contribution from hydrodynamic loading to the tower response is only very slightly influenced by
the amount of yaw misalignment, the aerodynamic loading contribution is significantly influenced by it; peak
tower bending moment values occur for a yaw misalignment of about 30 degrees. The significantly lower
turbine loads in the case of zero yaw misalignment highlights the importance of a reliable yaw backup powersystem, which is strongly recommended since a grid failure during a hurricane could result in loss of theneeded yaw control.
• Blade pitch control is important during the hurricane; as expected, a 90-degree pitch angle results in the lowest
tower response maxima and in a systematic study, it was found that when the pitch angle is reduced from 30 to
20 degrees, a significant increase in the maximum tower bending moment results.
• While the tower base fore-aft moment in a case with zero yaw error does not vary greatly for different blade
azimuthal positions, the tower base side-to-side moment is seen to vary by a considerably larger amount; thisrange can be as much as 25% of the value, say, at the zero-degree azimuthal position. In general, though not at
all times during the hurricane, largest and smallest tower load maxima occurred for rotor configurations where
one blade is in the 0 and 180 degree azimuthal position, respectively.
• While the tower base fore-aft moment in a case with zero yaw error is not significantly different for the different turbine parking strategies considered, the tower base side-to-side moment is seen to be noticeably different
and the parked-standstill case leads to systematically larger loads than the idling case during the hurricane.

32

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3 Modeling Hurricane Sandy’s Influence on a Jacket-Supported Offshore Wind Turbine
3.1 Problem Description
For evaluating the response of an offshore wind turbine (OWT) during the evolution of Hurricane Sandy (2012),
we consider ten mid-Atlantic sites identified for potential wind energy development. These selected sites shownin Figure 3.1 were in or close to the path of Hurricane Sandy. Some general information on the selected sites ispresented in Table 3.1. The water depth at some of these sites is greater than 30 m. Depending on the water depth
range, in our analyses, we considered at many as three fixed water depths (20 m, 45 m, and 50 m) possible at any
site. Because a monopile support structure becomes progressively uneconomical as the water depth increases beyond
25-30m [29], other types of support structures such as jackets or tripods might be better candidates at those water
depths. To illustrate the detailed procedure related to the response evaluations of an offshore wind turbine with ajacket support structure, we consider only a single site where the water depth is 50 m.

44
6

2

9

4

40
3
1
7
5

Latitude

36
10
8

32

28

Hurricane Sandy track
24
−86

−82

−78
−74
Longitude

−70

−66

Figure 3.1. The locations of ten selected offshore wind plant sites and the simulated track of Hurricane Sandy.

As was the case for Hurricane Ike discussed in Chapter 2, coupled wind and wave fields at the locations ofinterest are simulated based on the UMCM output. Figure 3.4 shows the variation with time of the wind and wave
directions; the red circle indicates the location of the hurricane eye at the specified time. In the figure, the red andblue arrows represent the wind and wave directions, respectively, at the ten selected sites (locally) while the green
arrows depict the full-field wind direction over the entire simulation domain. As shown in this figure, the wind andwave directions and the misalignments between the two at each site change noticeably as the hurricane moves along
its track.
33

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44
42

Latitude

40
38
36
34
32
30
−80 −78 −76 −74 −72 −70 −68 −66
Longitude(a) At 10:00 UTC on October 28, 2012 (t0 ).

44
42

Latitude

40
38
36
34
32
30
−80 −78 −76 −74 −72 −70 −68 −66
Longitude(b) At t0 + 10 hours.
Figure 3.2. Variation with time during Hurricane Sandy of the full-field wind direction (green arrows), local wind direction (blue arrows), and local wave direction (red arrows) at the locations of the ten selected sites (at t0 and t0 + 10 hours).

34

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

44
42

Latitude

40
38
36
34
32
30
−80 −78 −76 −74 −72 −70 −68 −66
Longitude(a) At t0 + 20 hours.

44
42

Latitude

40
38
36
34
32
30
−80 −78 −76 −74 −72 −70 −68 −66
Longitude(b) At t0 + 30 hours.
Figure 3.3. Variation with time during Hurricane Sandy of the full-field wind direction (green arrows), local wind direction (blue arrows), and local wave direction(red arrows) at the locations of the ten selected sites (at t0 + 20 and t0 + 30 hours).

35

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

44
42

Latitude

40
38
36
34
32
30
−80 −78 −76 −74 −72 −70 −68 −66
Longitude(a) At t0 + 40 hours.

44
42

Latitude

40
38
36
34
32
30
−80 −78 −76 −74 −72 −70 −68 −66
Longitude(b) At t0 + 50 hours.
Figure 3.4. Variation with time during Hurricane Sandy of the full-field wind direction (green arrows), local wind direction (blue arrows), and local wave direction(red arrows)at the locations of the ten selected sites (at t0 + 40 and t0 + 50 hour ) .

36

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Table 3.1. General information on ten potential offshore wind plantsites selected for analysis in this study (source: www.4coffshore.com).

1
2
3
4
5
6
7
8
9
10

Wind Energy Area (ID)
Maryland WEA South (US4O)
Massachusetts WEA (US0V)
New Jersey (US4S)New York RFI (US4J)
North Carolina(US4E)
Rhode Island & MA (US3C)
Virginia (US3H)
North Carolina(US4E)
Cape Wind, MA (US03)
Apex Offshore Wind, NC (US99)

Water Depth Range
11-36 m
31-62 m14-32 m18-42 m15-44 m
26-49 m
18-33 m15-44 m
1-18 m26-29 mDistance from shore
24.4 km38.7 km30.1 km40.8 km41.5 km31.5 km54.2 km41.5 km14.2 km32.2 km

In this chapter, we present detailed response results only for an offshore wind turbine at Site No. 1. Figure 3.5
shows the location of Site No. 1 along with the track of Hurricane Sandy as extracted from a best track database andestimated by the UMCM simulation; the larger red star indicates the location of Site No. 1 while the smaller bluestars indicate locations of the other nine sites. The figure serves to display the evolution of track of the hurricane overa 60-hour period beginning at 00:00 UTC on October 28, 2012 (0 hour).

3.2 Hurricane-Induced Waves
Irregular hurricane-generated waves are numerically simulated using second-order wave theory and the methodology
presented in Chapter 2. Table 3.2 summarizes information on wave spectra from UMWM output and on ocean
currents from HYCOM output obtained following the UMCM simulation of Hurricane Sandy. As shown in the table,
wave spectra for Hurricane Sandy are continuously generated for separate 1-min periods. However, to simulate
1-hour sea surface elevation process and associated wave kinematics in the time domain for subsequent turbine
load calculation, we need to employ a wave spectrum that represents the entire 1-hour period. Figure 3.6a shows
the wave spectrum 40 hours after 10:00 UTC on October 28, 2012 at the 50-meter water depth location within
Site No. 1. Figures 3.6b, 3.6c, and 3.6d show, respectively, computed wave spectra 1, 10, and 60 minutes later.
Differences between the wave spectra over the entire hour are not significant; hence, in this study, we simply assume
that the UMWM wave spectrum from the first minute each hour is representative of the spectrum over the entire
hour. Of course, as the hurricane progresses, these wave spectra are updated each hour to generate the changing sea
surface elevation and wave kinematics.
Table 3.2. Wave and current information from UMWM and HYCOM.

Physicsmodel
Current(HYCOM)
Wave(UMWM)

Outputfiles
current_xx.nc
umwmspc_xx.nc

Resolution
spatialtemporalevery 2 m depth
10 min(at each site)at each site
1 min

Data
used
vcx , vcy , vcz
F(~k), k, θU(z = 10 m)

Figures 3.7 and 3.8 show the variation with time of the frequency-dependent wave spectrum, S( fn ), and the
direction-dependent wave spreading function, D(θm ), defined as follows:
M

N

m=1

n=1

S( fn ) = ∑ S( fn , θm )∆θm ; ση2 = ∑ S( fn )∆ fn

(3.1)

37

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50hrs60hrs
40hrs
Site 1
30hrs
20hrs
10hrs

Figure 3.5. Location of Site No. 1 and the simulated track of Hurricane Sandy
evaluated based on UMCM output (compared to a best track database).

38

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N

M

n=1

m=1

D(θm ) = ∑ S( fn , θm )∆ fn ; ση2 = ∑ D(θm )∆θm

(3.2)

where ση2 is the variance of the sea surface elevation process. From Figs. 3.7 and 3.8, it can be seen that at around 46
hours, both the wave spectrum and the directional spreading change quite abruptly as the hurricane’s eye passes thesite. During that hour, our assumption that the first minute’s wave spectrum is representative of the entire hour would
not be an acceptable one.

3.3 Hurricane-Induced Wind Field
Table 3.3 summarizes information on the wind field from WRF output obtained following the UMCM simulation of
Hurricane Sandy. In the table, a geometric height, z (elevation above the mean sea level), corresponding to the three
output wind velocity components, Ux (z), Uy (z), and Uz (z), are evaluated as follows, using an initial geopotential,
PHB, and a perturbation geopotential, PH [30]:geometric height: z =PH + PHB
9.81

(3.3)

While turbulent wind fields for Hurricane Ike in Chapter 2 were simulated using mean wind field data sampled every hour and only at a location 10 meters above the mean sea surface level (with an assumed vertical wind
shear), we demonstrate how the WRF output can allow us to make use of available wind field data provided every 10
minutes and at several elevations to stochastically simulate turbulent wind fields for Hurricane Sandy.
Table 3.3. Wind field information from WRF output for Hurricane Sandy.

Physics
model
Wind
(WRF)

Outputfiles
wrf_xx.nc

Resolution
spatialtemporal
12 × 12 km
10 min4 × 4 km
1.3 × 1.3 km

Data
used
u∗ (t p )Ux (z,t p ), Uy (z,t p ), Uz (z,t p )PHB(z,t p ), PH(z,t p )Figure 3.9 presents the overall procedure to simulate turbulent wind fields using WRF output for Hurricane
Sandy. In order to simulate an hour-long fully turbulent wind field including the vertical wind shear, as a thefirst step, we compute six values of the 10-min sampled total wind speed, U(z,t p ), the horizontal wind direction,
θhor (z,t p ), and the vertical wind direction, θver (z,t p ), using WRF output Ux (z,t p ), Uy (z,t p ), and Uz (z,t p ) (wherep = 1, 2, . . . 6 during the hour). This is done as follows:p(3.4)
U(z,t p ) = [Ux (z,t p )]2 + [Uy (z,t p )]2 + [Uz (z,t p )]2

θhor (z,t p ) = atan2
θver (z,t p ) = atan2 √Uy (z,t p )Ux (z,t p )





(3.6)

x>0
y ≥ 0, x < 0
y < 0, x < 0
y > 0, x = 0
y < 0, x = 0
y = 0, x = 0(3.7)

Uz (z,t p )(Ux (z,t p ))2 +(Uy (z,t p ))2arctan xy
arctan yx + π
arctan yx − π
atan2(y, x) =
+π /2




−π /2



undefined

(3.5)

39

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The time-varying non-turbulent wind velocity at time, tn , i.e., U(z,tn ), and the wind directions, θhor (z,tn ) andθver (z,tn ) at intervals equal to ∆t may be found by applying the simple interpolation function, Interp, using computed values of U(z,t p ), θhor (z,t p ), and θver (z,t p ).
U(z,tn ) = Interp(n∆t,t p ,U(z,t p ))(3.8)

θhor (z,tn ) = Interp(n∆t,t p , θhor (z,t p ))(3.9)

θver (z,tn ) = Interp(n∆t,t p , θver (z,t p ))(3.10)

where tn = n∆t and n = 1, 2, . . . 3600/∆t, corresponding to a wind velocity field output every second for one hour.
The zero-mean turbulent wind fields for Hurricane Sandy, i.e., u′ (z,tn ), v′ (z,tn ), and w′ (z,tn ) are simulated using
the original form of the Kaimal turbulence power spectral density functions (Kaimal et al. [31]); needed quantities
such as the one-hour mean wind speed, Um (z), and friction velocity, u∗m , are evaluated as follows using the six 10minute interval WRF output variables, U(z,t p ) and u∗ (t p ), in each hour:
Um (z) = 61 ∑6p=1 U(z,t p )(3.11)u∗m = 61 ∑6p=1 u∗ (t p )(3.12)

Effectively, then, u∗m , arising from the WRF output, scales the turbulence intensity during each hour of the simulationof the hurricane.
Finally, the “total” wind velocity field is computed by adding the time-varying non-turbulent wind field to thezero-mean turbulent wind field as follows:u(z,tn ) = U(z,tn )+v(z,tn ) = U(z,tn )+u′ (z,tn )v′ (z,tn )(3.13)(3.14)

w(z,tn ) = U(z,tn )+w′ (z,tn )(3.15)

Next, the wind velocities evaluated in Eqs. 3.13-3.15 are rotated relative to a fixed inertial reference frame
coordinate system (defined at the wind turbine) by employing two transformation matrices, [Thor ] and [Tver ]. Thus,
we have:




ux
u
 uy  = [Thor ][Tver ]  v (3.16)
uz
w
where



− sin θhorcos θhor
0


0
0 
1

(3.17)


0 − sin θver
1
00 cos θver(3.18)cos θhor[Thor ] =  sin θhor0cos θver0[Tver ] = 
sin θverand θhor and θver are defined in Eqs. 3.9 and 3.10 for every time instant if interest, tn .
The overall simulation procedure leading to full 4-D wind fields, presented in Fig. 3.9, is integrated into the
open-source aeroelastic simulation program, FAST [32], by making use of the UserWind module there.

40

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3.3.1

Mean Wind Field during Hurricane Sandy

The mean vertical wind profile for Hurricane Ike was estimated using the classical log law that was presented in
Eq. 2.64. Such a logarithmic profile, which is commonly used to describe vertical wind shear, does not account foratmospheric stability effects. In contrast, because the WRF output provides wind field data at several elevations, we
can directly use these data to obtain the mean wind shear for full wind field simulation during Hurricane Sandy. The
WRF output for Hurricane Sandy provides mean wind field data at 6 different elevations up to 200 meters above thebottom surface; Fig. 3.10 shows the variation with time of the horizontal mean wind speed and the vertical mean
wind speed. The vertical wind direction, θver (z,t p ), is less than 2 degrees during the simulation. Even though the
WRF output includes a vertical wind velocity component, U(z,t p ), the magnitude of this component is very small as
can be confirmed from Fig. 3.10.
In Fig. 3.11, the surface wind shear extracted from the WRF output is compared with the wind shear estimatedby the classical log law (Eq. 2.64) which does not account for stability effects. The computed wind shear profile
presented in Fig. 3.11 corresponds to a time, 40 hours after 00:00 UTC on October 28, 2012 and it applies to a 50-m
water depth location at Site No. 1; this profile more closely resembles stable atmospheric boundary layer conditions
with greater wind shear than in the log-law profile.
3.3.2

Turbulent Wind Field during Hurricane Sandy

In the present study, the Veers method [33], based on Fourier techniques, is utilized to generate a turbulent wind field(over the swept area of the offshore wind turbine rotor) that is comprised of three orthogonal zero-mean velocity
components. To this turbulent wind field, the time-varying mean wind field, discussed previously, is added to yield
the full wind field over the rotor that is needed for loads analyses. The required inputs for the Veers method aretarget turbulence power spectral density (PSD) functions and coherence functions; physical parameters in these targetfunctions depend on the WRF output that changes every hour.
3.3.2.1

Turbulence Power Spectral Density Functions

A power spectral density function describes the contribution to the variance of a stochastic process as a function of
frequency; it has, for example, dimensions of [variable units]2 per Hertz (Hz). Intuitively, then, the PSD function
describes the frequency content of the stochastic process. In this study, the original Kaimal turbulence power spectra(Kaimal et al. [31]) are used as the basis for simulating the three orthogonal components of turbulence:
Su ( f ) =105u2∗z/Ure f
1 + 33 f z/Ure f

Sv ( f ) =17u2∗z/Ure f

5

1 + 9.5 f z/Ure f
Sw ( f ) =2u2∗ z/Ure f
1 + 5.3 f z/Ure f(3.19)

3

5(3.20)

3

5(3.21)

3

where Su ( f ), Sv ( f ), and Sw ( f ) (in (m/s)2 /Hz) are one-sided power spectra for the longitudinal, transverse, and vertical wind velocity components, respectively. Also, f refers to the frequency of interest in Hertz (Hz), u∗ is the friction
velocity (in m/s), z is the elevation (in meters), and Ure f is a reference wind velocity (in m/s). For Hurricane Sandy,
Ure f and u∗ , needed to define the Kaimal power spectra are taken as Um (z) and u∗m as given by Eqs. 3.11 and 3.12,
respectively. It should be noted that the modified Kaimal power spectra as specified in the IEC wind turbine design standard [22] are defined differently from the ones described above in Eqs. 3.19-3.21. One benefit of using theoriginal Kaimal power spectra in Eqs. 3.19-3.21 instead of the IEC Kaimal spectra is that the parameters involved

41This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

depend only on physical quantities and they do not require any additional assumptions. With the IEC Kaimal spectra,
a pre-determined longitudinal turbulence scale parameter, ΛU , and reference turbulence intensity, Ire f , have to be
assigned.
3.3.2.2

Turbulence Coherence Functions

The coherence function for any single turbulence component is a frequency-dependent measure of the correlation ofthat component at two spatially separated points. In this study, this coherence function is modeled as follows [34] : 2
1/2 #cy (y j − yk )2 + c2z (z j − zk )2
Cohε ( j, k, f ,U jk ) = exp − f
0.5 Ure f (z j ) + Ure f (zk )"(3.22)

where Cohε ( j, k, f ,U jk ) is a dimensionless coherence function for each turbulence component of interest, ε (i.e., u,v, or w), at locations, (y j , z j ) and (yk , zk ), expressed as a function of frequency, f ; also, cy and cz are coherence decay
parameters (dimensions: L−1 ) for lateral (y) and vertical (z) separations, respectively; for k = 1, cy = 10 and cz = 3 ,for k = 2, cy = 6.5 and cz = 3 and for k = 3, cy = 3.0 and cz = 0.5 [35]. Again, Ure f , needed to define the coherencefunctions is taken as Um (z) as given by Eq. 3.11. The coherence functions together with the PSD functions are used
to assemble the full-field frequency-dependent cross-power spectral density (CPSD) function matrix over the entire
simulation domain covering the turbine’s rotor; the Veers method provides a means to use this CPSD matrix togenerate time series of the wind velocity over the rotor-swept area. Note that even though no coherence is consideredbetween the orthogonal turbulence components, they are intrinsically correlated with each other in time through u∗mresulting from the WRF model output.

3.4 Offshore Wind Turbine Response during Hurricane Sandy
An uncoupled modeling scheme is used to analyze the response of an offshore wind turbine with a jacket support
structure as illustrated in Fig. 3.12. While in a coupled modeling approach, aerodynamic and hydrodynamic load
effects are evaluated in a single computation step or software tool, an uncoupled modeling approach uses two separate software tools or computational steps to evaluate the aerodynamic and hydrodynamic load effects. The rotor
aerodynamic forces are first evaluated in FAST, using a baseline wind turbine assumed fixed rigidly at the base.
Aerodynamic loads evaluated at the nacelle (top of the tower) are applied as point loads in Abaqus [36] to a structural model of the tower and jacket support structure, which is also subjected to hydrodynamic forces resulting fromwaves and currents.
Unlike monopile-type support structures that have rotational symmetry due to their cylindrical sections, theorientation of its jacket support structure beneath affects the overall response of a wind turbine due to lack of rotational symmetry. Hence, as shown in Fig. 3.13, a combination of three separate considerations should be made inorder to evaluate the response of the wind turbine with a jacket support structure during a hurricane. These threes
considerations are:(1) Support structure orientation, θ1 (defined with regard to the wind direction),(2) Wind and wave misalignment, θ2 ,(3) Yaw misalignment, θ3 .
To simplify the analyses in this study, we assume that the support structure orientation, θ1 , and the yaw misalignment, θ3 , are each equal to zero. Thus, only wind-wave misalignment varies during the evolution or movementof the hurricane in our analyses. As mentioned earlier, we will present response evaluations of 1-hour duration, beginning at 00:00 UTC on October 28, 2012 (the start of the UMCM simulations). These response computations arerepeated every 10 hours, beginning 10 hours after the start of the simulations and ending 60 hours after the start. The
response computations are only for a Site No. 1, depicted in Fig. 3.5.

42This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3.4.1

Turbine ModelAll the investigations in this study are for a 5-MW offshore wind turbine with a jacket support structure as shownin Fig. 3.14. This is the same system used by the Offshore Code Comparison Collaboration Continuation (OC4)project (Phase I). The rotor nacelle assembly (RNA) of the OWT is that of the NREL 5-MW baseline turbine [37].
The jacket support structure has four legs, four levels of X-braces, and mudbraces. This support structure has been
described in detail by Vorpahl et al. [38]. ,3.4.1.1

OC4 Jacket Support Structure

The jacket support structure for the NREL 5-MW turbine is based on a reference design developed as part of theEuropean Union’s UpWind project [39]. The UpWind jacket is designed for a site with a water depth of 50 m. The
jacket consists of four legs, four levels of X-braces, and mudbraces. The top and bottom widths of the jacket are 8 m
and 12 m, respectively. A rigid concrete block with a weight of 660 tons and dimensions of 9.6 m (length) × 9.6 m(width) × 4 m (height) is positioned at the top of the jacket and serves as the transition piece (TP) or platform thatconnects the jacket with the tower of the baseline wind turbine. The geometric configuration and dimensions of themembers of the OC4 jacket support structure are presented in Fig. 3.15. The jacket is made up of a medium-grade
structural steel with a Young’s modulus of 210 GPa. The density is assumed to be 8500 kg/m3, which accounts forpaint, bolts, welds, and all other additional masses.
As marine growth can influence the overall loading and, thus, the dynamic behavior of the system, it is taken
into consideration in the model described herein as per DNV guidelines [40] and as given by Fisher and Kuehn [41].
The depth range with respect to the mean sea level (MSL) over which to consider marine growth is −40 ≤ zg (m) ≤−2, its thickness, tg , is 100 mm, and its density, ρg , is 1,100 kg/m3 . The legs of the jacket structure are assumed to be
flooded by sea water with density, ρw , equal to 1,025 kg/m3; the braces are not assumed flooded.
There is a grouted connection between the piles and the jacket legs as shown in Fig. 3.16. The bottom of thegrouted connection is at z = −49.5 m and the upper end of the grout is at z = −45.5 m. The properties of the legs at
the lowest level (Level 4) and the piles are included in Fig. 3.15. The density of the grout material between the twosteel parts, ρG , is assumed to be 2,000 kg/m3 . As the stiffness of the two steel members together with the grout material is very high, the grouted part from MSL − 49.5 m to MSL − 45.5m (including pile, leg, and grout) is modeled as
rigid in Abaqus. The embedded length of the pile is assumed to be 47 m.
As shown in Fig. 3.17, the Abaqus model used in this study consists of a tower top mass, a tower, a transition
piece, and the jacket structure. All the separate parts in the model are connected via kinematic coupling constraints
in Abaqus. The rotor nacelle assembly (RNA) including the hub is modeled as a nodal mass without rotary inertia
and the transition piece between the baseline turbine and the jacket structure is modeled as a rigid body, where the660 tons dead load of this transition piece is modeled as a rectangular body with the dimensions of 9.6 m (length)
× 9.6 m (width) × 4 m (height). Because the purpose of this study is not to evaluate localized stress concentration
at member joints or local buckling of members, all the jacket members are modeled using Euler-Bernoulli beam
elements.
In this study, member forces and reaction forces at a total of 13 locations (referred to as “sensor locations”)
are evaluated. Figure 3.18 provides detailed information on these sensor location. The structural response of braces
and legs are evaluated with respect to the member (local) coordinate system; for axial forces, positive values imply
tensile forces while negative values imply compressive forces.
3.4.1.2

Verification of the Abaqus Model

The Abaqus model is verified by comparison with the study presented by Popko et al. [42], which includes resultsfrom the IEA Wind Task 30 OC4 Project Phase I, which was focused on the coupled simulation of an offshore
wind turbine with a jacket support structure. In the verification studies with our model, it is assumed that the jacket
structure is cut and clamped or fixed at the mudline.
43

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Comparison of Masses
Before comparing the wind turbine or support structure response with any other studies, we first consider the
structural mass as well as all additional mass in the model. This is done in Table 3.4. Structural mass includes thejacket, transition piece, tower, and rotor-nacelle assembly (RNA), while additional mass includes marine growth andwater in the flooded legs. In general, a very good agreement is observed when our model is compared with that inPopko et al. [42].
Table 3.4. Comparison of structural and additional mass in our Abaqus model with that in Popko et al. [42].

Structural Mass (kg)

Abaqus Model
Popko et al. [42]Difference

RNA

Tower

TP

Jacket

350
350
0

216
220
-4

660
660
0

674
677
-3

Additional mass (kg)

Total

Flooded
Leg
204
200
+4

2290
2290
0

MarineGrowth180
177+3Comparison of Natural Frequencies
An eigenvalue analysis is performed to obtain natural frequencies based on our Abaqus model, which arethen compared with the natural frequencies evaluated with an Ansys model used by Song et al. [43]. The natural
frequencies for the Abaqus and Ansys models are presented in Table 3.5. Generally, values from the two models arein a good agreement with each other. Small discrepancies are expected as the two models include a different numberof degrees of freedom (DOF) and somewhat dissimilar structural modeling assumptions. As shown in Fig. 3.19,
Popko et al. [42] also provides eigenvalue analysis results based on various OWT modeling codes used as part of theOC4 project. Eigenfrequencies of the first and second global fore-aft and side-to-side modes in the figure are very
close to eigenfrequencies for the same modes determined using our Abaqus model.
Table 3.5. Natural frequencies of the OC4 wind turbine system.

Mode

1
2
3
4
5
6
7
8
9
10

Natural frequencies (Hz)Ansys
AbaqusDifference(Song et al.) (this study)|%|
0.31900.33334.4
0.31900.33334.4
1.19361.21551.8
1.19361.21551.8
3.44253.36432.2
4.12534.43547.5
4.12534.43547.5
5.33915.32420.2
6.6953
6.6084
1.2
6.6953
6.6084
1.2

Comparison of Turbine Response
As further verification of the Abaqus model, we consider two response measures under regular wave loading:(1) the fore-aft shear force at the base of the jacket structure; and (2) the out-of-plane displacement (i.e., in the foreaft direction, x) of the central joint of the X-brace at Level 2 on Side 2 (S2) (see Fig. 3.15). Our response calculations
are compared with those presented in Popko et al. [42].
First, the fore-aft shear force is evaluated for the offshore wind turbine excited using a regular Airy wave (H = 6
m, T = 10 sec). As shown in Fig. 3.20, good agreement is seen for the evaluated fore-aft force between our modeland others reported in Popko et al. [42]. Next, the out-of-plane displacement (effectively, in the fore-aft direction) is
44This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

considered for the offshore wind turbine excited by a regular 9th -order stream function wave (H = 8 m, T = 10 sec).
In Fig. 3.21, the surface wave elevation resulting from using this stream function is compared with the surface wave
elevation based on Airy wave theory used with our Abaqus model (the wave profiles for the 9th -order stream function
and the Airy theory cases are very similar). Figure 3.22 shows that the X-brace out-of-plane displacement evaluatedfrom our Abaqus model (thick black line) matches well with results presented in Popko et al. [42].
3.4.1.3

Modeling Soil-Pile Interaction

Because the interaction between the soil and the embedded pile changes the dynamic characteristics of wind turbine,
this interaction effect is considered in our Abaqus model of the jacket support structure. In our model, this interaction represented by a p-y curve model specified in the American Petroleum Institute (API) RP2A guidelines [44].
The p-y curve method for designing offshore pile foundations has been utilized by the offshore oil and gas industry for decades and is based largely on work performed in the early 1970s [45, 46]. The method approximates thestiffness of the soil-pile system by a number of discrete nonlinear soil springs arranged along the length of the pile.
These springs act independently of one another and therefore do not affect the displacement of neighboring springs.
The lateral resistance of the pile is represented by p-y curves, with “p” representing the lateral resistance and “y”
representing the lateral displacement of the pile. The soil profile assumed for the design of the OC4 Jacket [39] isused to evaluate the lateral soil stiffness characteristics and is presented in Table 3.6.

45This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

N

0

0.2

0.4

N

0.6

0.8

1

0

(a) At 40 hours (Hs = 9.3
m; Uz=10m = 26.9 m/s).

0.2

0.4

N

0

0.2

0.4

0.6

0.8

1

0.8

1

(b) At 40 hours + 1 min (Hs =9.3 m; Uz=10m = 27.2 m/s).
N

0.6

0.8

1

0

(c) At 40 hours + 10 min (Hs =9.4 m; Uz=10m = 26.9 m/s).

0.2

0.4

0.6

(d) At 40 hours + 60 min (Hs =9.9 m; Uz=10m = 28.4 m/s).

Figure 3.6. Variation with time of Hurricane Sandy wave spectra (at and after 40hours) at the location of Site No. 1 with 50-m water depth (blue arrow: wave direction; red arrow: wind direction). Only very small changes are seen over one hour.

46This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Frequency wave spectrum(m2−sec)
0.4

25
20

f(Hz)

0.3

15
0.2
10
0.1

5
10

20

30

40

50

60

70

0

hour
Normalized frequency wave spectrum
0.4
0.8

f(Hz)

0.3

0.6
0.2
0.4
0.1

0.2
10

20

30

40

50

60

70

0

hour

Figure 3.7. Variation with time of the frequency-dependent wave spectrum during Hurricane Sandy (at thelocation of Site No. 1 with 50-m water depth. Normalization to unity with variation in time is also shown.)

Directional spreading of wave energy (m2/rad)5
2
4

θ(rad)

1

3

0
−1

2

−2

1

−3

10

20

30

40

50

60

70

0

hour
Normalized wave energy2

0.8

θ(rad)

1

0.6

0
0.4

−1

0.2

−2
−3

10

20

30

40

50

60

70

0

hour

Figure 3.8. Variation with time of the directional-dependent wave spreading function during Hurricane Sandy (at the location of Site No. 1 with 50m water depth. Normalization to unity with variation in time is also shown.)

47

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tZ&ŽƵƚƉƵƚ
ϭϬͲŵŝŶŝŶƚĞƌǀĂůtŝŶĚƐƉĞĞĚĂŶĚĨƌŝĐƚŝŽŶĂůǀĞůŽĐŝƚǇ

DĞĂŶнǌĞƌŽͲŵĞĂŶƚƵƌďƵůĞŶƚǁŝŶĚ,   ᇱ ,   , ,   ᇱ , ,   ᇱ , ௫௬  Tு௢௥ T௏௘௥௭ ு௢௥
Tு௢௥   ு௢௥0, 

,  с  ௫ ,  ଶ   ௬ ,  ଶ   ௭ ,  ଶdƌĂŶƐĨŽƌŵƚŽŝŶĞƌƚŝĂĨƌĂŵĞĐŽŽƌĚŝŶĂƚĞ



T௏௘௥ 

 ு௢௥ ு௢௥
0 ௏௘௥
0 ௏௘௥

ϭͲŚŽƵƌDĞĂŶǁŝŶĚƐƉĞĞĚ&ƌŝĐƚŝŽŶĂůǀĞůŽĐŝƚǇ



0
0
1

0  ௏௘௥
1
00  ௏௘௥ ௫,ĞƌŽͲŵĞĂŶƚƵƌďƵůĞŶƚ
ǁŝŶĚƐŝŵƵůĂƚŝŽŶ
′, , ′, ͕ ′, Ϳ^ƚĂŶĚĂƌĚ<ĂŝŵĂů
^ƉĞĐƚƌƵŵ

௬͕

௭Ϳ

௏௘௥
ு௢௥

Ǉ

z(m)

Figure 3.9. Procedure for simulation of the turbulent wind field during Hurricane Sandy.
200

40

150

30

100

20

50

10

0

10

20

30

40

50

60

70

0

hour

z(m)

(a) Horizontal mean wind speed.
200

0.2

150

0.15

100

0.1

50

0.05

0

10

20

30

40

50

60

70

0

hour

(b) Vertical mean wind speed.
Figure 3.10. Variation with time of the horizontal mean wind speed and the vertical mean wind speed (at the location of Site No. 1 with 50-m water depth).

48

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400
350

WRF
Log−law

300

z(m)

250
200
150
100
50
0
20

25

30
35
wind speed(m/s)

40

45

Figure 3.11. Mean wind shear interpolated from the WRF output for Hurricane Sandy versus
that estimated by the classical log law (corresponding to the time, 40 hours, and at Site No. 1).

CoupledUncoupled
wind

wind

Tower top
load
Tower top
load

Wave

ൎ

Wave
FAST
AbaqusFigure 3.12. Coupled and uncoupled modeling approach for
an offshore wind turbine with a jacket support structure.

49

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WIND

N
WIND

WIND

N

WAVE

ߠଵ

(1)

ߠଷ

ߠଶ

(2)

(3)

Figure 3.13. Three considerations in evaluating the responseof a jacket-type structure supporting an offshore wind turbine.

50

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04'./9
6WTDKPG*WD*GKIJV\ O,CEMGV
5WRRQTV

9CVGT&GRVJ
O\ O/5.

5GC$GF

Figure 3.14. Schematic diagram of the jacket-supported NREL 5-MW wind turbine model.

51

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Z = 16.1m

L2(Top View)
S1

Level 1

L1

Y

Z = 4.3m

X

S2

Level 2S4

Z = -8.9m

L3

Level 3Z = -24.6m

Level 4L4S3Component

Color

Outer
Dia.(m)Thickness(mm)

X- and mud brace

Grey

0.8

20

Leg (Level 4)

Blue

1.2

50

Leg (Level 1-3)

Red

1.2

35

Leg crossing TP

Not shown

1.2

40

Pile

Black

2.082

60

Z = -43.1m

Figure 3.15. Geometric configuration and dimensions of members of the OC4 jacket support structure.

Properties: Leg lowest level
MSL -45.5m: Grout top

Grout Material

Properties: Pile

MSL -49.5: Grout bottom
MSL -50m: Mudline

Figure 3.16. Grouted leg and pile connection for the jacket support structure.

52

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NACELLE(350 ton)

TOWER

Concrete TP(660 ton)Jacket pile

Figure 3.17. Abaqus modeling of the OC4 reference jacket structure used in this study.

BRA-W-L1

NO.

SensorName

Location

Membertype

LEG-SW-L1

1

BRA-W-L1

On side 2(west) at level 1

Brace

BRA-S-L1

2

BRA-W-L2

On side 2(west) at level 2

Brace

3

BRA-W-L3

On side 2(west) at level 3

Brace

4

BRA-W-L4

On side 2(west) at level 4

Brace

5

BRA-S-L1

On side 3(west) at level 1

Brace

LEG-SW-L2
BRA-W-L2
BRA-S-L2

BRA-W-L3

6

BRA-S-L2

On side 3(west) at level 2

Brace

LEG-SW-L3

7

BRA-S-L3

On side 3(west) at level 3

Brace

BRA-S-L3

8

BRA-S-L4

On side 4(west) at level 4

Brace

9

LEG-SW-L1

Leg3(south west) at level 1

Leg

10

LEG-SW-L2

Leg3(south west) at level 2

Leg

11

LEG-SW-L3

Leg3(south west) at level 3

Leg

12

LEG-SW-L4

Leg3(south west) at level 4

Leg

13

LEG-SW-MUD

Leg3(south west) at
mudlineReaction

LEG-SW-L4
BRA-W-L4
BRA-S-L4

LEG-SW-MUD

Figure 3.18. Sensor names and locations for the dynamic response
analyses of the offshore wind turbine and jacket support structure.

53

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3.5

3.0

2.5

Frequency [Hz]

2.0

1.5

ABAQUS

Fraunhofer IWES / ADCoS-Offshore
Risø DTU / HAWC2
GLGH / Bladed V4.0
POSTECH / Bladed V3.85
CGC / Bladed V3.80
IFE / 3Dfloat
Fedem Technology AS / FEDEM WindPowerCeSOS-NTNU / USFOS-vpOne
NTUA / GAST
SWE / Flex5-Poseidon
REpower /ANSYS
LUH / Flex5-Poseidon
ABS / ANSYS-BModes
NTNU / ASHES
ECN-WMC / Phatas-WMCfem

1.0

0.5

0.0

Figure 3.19. Natural frequencies based on various OWT modeling codes [42].

ABAQUS

Figure 3.20. Fore-aft shear force at the mudline for our Abaqus
model and comparison with results presented in Popko et al. [42].

54This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

6
Airy
Stream

η(m)

4
2
0
−2
−4
0

2

4
6
time(sec)

8

10

Figure 3.21. Surface wave elevation evaluated using Airy theory and a 9th -order stream function approach.

ABAQUS

Figure 3.22. Out-of-plane deflection at center of X-brace at Level 2 on Side 2 of
our Abqaus model and comparison with results presented in Popko et al. [42].

55This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 3.6. Soil properties assumed for the jacket support structure [39].
′Depth (m) Soil type γ (kN/m3 ) ϕ (deg) cu (kPa) ε50 (%)
0-3
SAND
10
36.0
3-5
SAND
10
36.0
5-7
CLAY
10
60.0
0.7
7-10
SAND
10
37.0
10-13
SAND
10
35.0
13-15
SAND
10
35.0
15-18
SAND
10
37.5
18-47
SAND
10
37.5
′
γ : effective soil weightϕ : angle of internal friction
cu : undrained shear strength
ε50 : strain that occurs at one-half of the maximum stress
ε50 : in laboratory undrained compression test
Table 3.7. Development of sand p-y curves [44].

1. Theoretical ultimate bearing capacity
for wedge failure, pus
2. Theoretical ultimate bearing capacity
for flow failure, pud
3. Governing ultimate bearing capacity,pu′

pus = (C1 z + C2 D)γ z′

pud = C3 Dγ z
pu = min(pus , pud )kz
4. Develop p-y curvep = Apu tanhyApu
D: Average pile diameter from surface to depth
A: Factor to account for cyclic loading condition (take A = 0.9)
C1 , C2 , and C3 : Coefficients determined from Figure 6.8.6-1 in API [44]k: Initial modulus of subgrade reaction determined from Figure 6.8.7-1 in API [44]In the API guidelines, p-y curves for sand and clay are developed using the procedures presented in Tables 3.7
and 3.8, respectively. Figures 3.23a and 3.23b present characteristic shapes of the p-y curves for sand and clay,
respectively. In our Abaqus model, the lateral stiffness of the soil is modeled using a nonlinear spring element,
SPRING1. Table 3.9 shows the effect of soil-structure interaction on the eigenfrequencies of the model; consideration of soil-structure interaction (SSI) effects leads to noticeable reduction in the system natural frequencies.
3.4.2

Hydrodynamic Loads and Associated Response on Jacket Members during Hurricane
Sandy

The hydrodynamic loading experienced by a jacket member is comprised of drag and inertia force components.
Morison’s equation is used to compute the hydrodynamic load per unit member length, ∆ f , as follows:1
π D2∆ f = ∆ fD + ∆ fM = CD ρ Dur |ur | +CM ρw u̇r
2
4

(3.23)

where ∆ fD and ∆ fM are the drag and inertia forces per unit length, respectively, CD is the drag coefficient taken as
1.0, and CM is the inertia coefficient taken as 2.0. Also, in Eq. 3.23, ur and u̇r , respectively, are the “relative” velocity
and acceleration (accounting for the motions of the water particles and the structure), ρw is the density of water, and56

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Table 3.8. Development of clay p-y curves [44].

Static Loading

1. Compute ultimate soil resistance, pu

2. Compute deflection at one-half theultimate soil resistance, y50

Dynamic Loading
1. Develop p-y curves
2. Determine transition depth, zr

4. If depth z < zr

pu2 = 0.9cu D
pu = min(pu1 , pu2 )y50 = 2.5ε50 D 1/3
p
y
= 0.5
pu
y50

3. Develop p-y curves

3. If depth z ≥ zr#′γJpu1 = 3 + z + z cu D
cuD"Construct p-y curve in the same manner as forstatic loading for values of p < 0.72pu
6cu D
zr = ′
γ D + Jcu
p = 0.72pu f or y > 3y50p=
0.72pu at
y = 3y50
 zp = 0.72pu
aty = 15y50
zr

Table 3.9. Variation of system natural frequencies under different foundation modeling assumptions.

Mode

1
2
3
4
5
6
7
8
9
10

Natural frequencies (Hz)AbaqusAbaqus(clamped at mudline) (including SSI)
0.33330.30530.33330.30531.21550.95921.21550.95923.36432.39324.43543.44274.43543.44275.32424.73266.60845.11406.60845.1140Difference
|%|
8.4
8.4
21.0
21.0
28.8
22.3
22.3
11.1
22.6
22.6

57

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࢖࢟(a) Representative p-y curves for sand.


࢛
࢘

. 


࢘

. 
‫ܚ‬






૞૙

(b) Representative p-y curve for clay.
Figure 3.23. Characteristic Shapes of the p-y curves used in this study.

58

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D is the diameter of the jacket member. In the case of linear Gaussian waves, the inertia force in Morison’s equation
is a Gaussian process as it is a linear of the water particle acceleration which is a Gaussian process; the drag force,
however, is a non-Gaussian process as it is a nonlinear function of the water particle velocity.
We are interested in the response of the jacket support structure as various locations—braces, legs, and at the
mudline. The four response measures that we consider here are: axial force in brace, BRA-W-L4; axial force inleg, LEG-SW-L4; vertical reaction force, Fz , at mudline, LEG-SW-MUD; and bending moment, My , at mudline,
LEG-SW-MUD. Refer to Fig. 3.18 which helps to identify these response variables and their locations on the jacket
structure. Response statistics are for hydrodynamic loading alone and apply to a single hour during Hurricane Sandy
for the wind turbine at Site No. 1.
Table 3.10 summarizes response statistics considering hydrodynamic drag and inertia loads separately as well as
in combined (total) effect. Based on an estimate of the number of upcrossings of the mean of the response process,one can compute a theoretical peak factor for response extremes, assuming the process were Gaussian [47]. As
shown in Table 3.10 for the axial force in brace, BRA-W-L4, the response due to inertia forces has skewness close tozero, kurtosis close to 3, and peak factor close to the corresponding Gaussian peak factor—all of these findings arein line with expected Gaussian characteristics of the response due to inertial load effects alone. Similar observations
can be made as well for the other response measures’ statistics under inertia loads, as can be seen in Tables 3.11,
3.12, and 3.13. In contrast, the response due to drag forces has a significantly higher kurtosis and a peak factor
larger than the corresponding Gaussian peak factor—therefore, the response due to drag forces is clearly strongly
non-Gaussian.
Table 3.10. Statistics of the axial force in a brace, BRA-W-L4, due to hydrodynamic loading
during Hurricane Sandy (corresponding to 50 hours after 00:00 UTC on October 28, 2012).

Axial force in a brace member, BRA-W-L4
draginertia
total
Mean (kN)
212
162
210
Max (kN)
1053
668
1100
Min (kN)
-1334
-1084
-1499
SD (kN)271
299
403
Skewness
0.31
-0.10
0.16
Kurtosis
6.62
2.79
3.35
Peak Factor (PF)1
4.66
3.08
3.25
PF (Gaussian)2
2.97
3.02
3.00
1
PF = Maximum(|Max − Mean|, |Min − Mean|)/SD
1 SD = standard deviation
2 Peak factor evaluated from the mean upcrossing rate
2 of the process, assuming it were Gaussian
Agarwal [48] studied the relative importance of drag and inertia forces to the tower base bending moment of an
offshore wind turbine supported by a monopile, which was a cylinder of 6 m diameter installed in 20 meters of water.
It was found in that study that the response due to hydrodynamic loading was dominated by inertia forces and the
response was close to a Gaussian process. However, the OC4 reference jacket support structure used in the present
study is composed of brace members of 1.0 m diameter and leg members of 1.2 m diameter, which are much smaller
sized sections than the monopile studied by Agarwal [48]. Thus, the relative contribution of drag to inertia forces
toward the total response is greatly increased in our study. From Tables 3.10, 3.11, 3.12, and 3.13, it is clear thatinertia and drag force effects are of comparable importance for all the response variables studied. The ratios of the
maximum response due to drag loads alone to the maximum response due to inertia loads alone are about 1.23, 1.00,
0.90, and 1.33, respectively, for the brace axial force (BRA-W-L4), the leg axial force (LEG-SW-L4), the vertical
reaction force at mudline (Fy at LEG-SW-MUD), and the bending moment at mudline (My at LEG-SW-MUD); thecorresponding ratios for the response standard deviation are about 0.91, 0.92, 0.98, and 0.90, respectively.

59

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Table 3.11. Statistics of the axial force in a leg, LEG-SW-L4, due to hydrodynamic loading
during Hurricane Sandy (corresponding to 50 hours after 00:00 UTC on October 28, 2012).

Mean (kN)
Max (kN)
Min (kN)
SD (kN)
Skewness
KurtosisPeak Factor(PF)PF (Gaussian)

drag
-3237
629
-5332
533
1.12
10.05
7.26
3.02

Axial force in a leg, LEG-SW-L4
inertia
total
-3110
-3231
-1394
853
-5319
-5760
577
781
-0.17
0.47
3.05
4.33
3.83
5.23
3.06
3.03

Table 3.12. Statistics of the vertical reaction force, Fz , at the mudline, LEG-SW-MUD, due to hydrodynamic loading during Hurricane Sandy (corresponding to 50 hours after 00:00 UTC on October 28, 2012).

Mean (kN)
Max (kN)
Min (kN)
SD (kN)
Skewness
KurtosisPeak Factor(PF)PF (Gaussian)Vertical reaction force at mudline, LEG-SW-MUD
draginertia
total
-3330
-3575
-3326
3024
-467
3501
-5877
-6538
-6409
874
890
1259
2.22
-0.08
0.99
12.88
3.44
5.87
7.27
3.49
5.42
3.01
3.05
3.02

We note from the preceding results that although the drag and inertia contributions to the different response
variables are comparable, the response due to the combined or total hydrodynamic load effects, accounting for dragand inertia, depends on the location and type of the evaluated response. For example, for axial force evaluated ina brace (BRA-W-L4) and for the mudline reaction moment, My (at LEG-SW-MUD), the computed response extreme peak factors are quite close to the peak factors theoretically estimated based on the assumption of a Gaussian
response process. This implies that the 1-hour maximum values of these two response variables during Hurricane
Sandy can be estimated based on Gaussian response assumptions. In contrast, the computed response extreme peakfactors for the axial force in a leg (LEG-SW-L4) and for the mudline vertical reaction force, Fz (at LEG-SW-MUD)
are significantly higher than the corresponding Gaussian peak factors.
3.4.3

Effect of Hurricane-Induced Currents

For the case of a monopile-supported offshore wind turbine, because the contribution of drag loads to the totalhydrodynamic loads is insignificant as was shown by Agarwal [48], we might expect that the contribution of wave
currents to the total response would also be negligible in that case. In the present study, we know that drag load
effects for the OC4 jacket support structure are of comparable importance to the inertia load effects. Since the dragload effects must include the contribution from ocean currents, we are interested in learning to what extent thesecurrents influence the total response.
For Hurricane Sandy, available depth-dependent ocean current velocities from HYCOM are vectorially combined with the wave particle velocities before computing drag forces. Figure 3.24 shows the variation with time ofthe ocean current velocities, evaluated by post-processing HYCOM output at Site No. 1, during the UMCM simulation of Hurricane Sandy. Figure 3.25 shows how the ocean current velocity components, ucx and ucy , influence the60This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 3.13. Statistics of the bending moment, My , at the mudline, LEG-SW-MUD, due to hydrodynamic
loading during Hurricane Sandy (corresponding to 50 hours after 00:00 UTC on October 28, 2012).

Mean (kN)
Max (kN)
Min (kN)
SD (kN)
Skewness
KurtosisPeak Factor(PF)PF (Gaussian)

Bending moment at mudline, LEG-SW-MUD
draginertia
total
61
-2
57
1641
1290
1846
-1714
-1170
-1779
393
438
582
-0.35
0.09
-0.17
6.36
2.73
3.17
4.52
2.95
3.16
2.98
3.01
3.01

axial force in a brace (BRA-W-L4); including the ocean currents increases the maximum axial force in the brace by
about 19% (from 1255 kN to 1499 kN).
3.4.4

Hydrodynamic versus Aerodynamic Loads

In this section, we evaluate the relative importance of hydrodynamic loads versus aerodynamic loads toward different
jacket response measures. Figures 3.28 and 3.31 show, respectively, simulated time series of axial forces in diagonalbraces on Side 2 and in leg L3 at different vertical levels (refer to Fig. 3.15). These time series plots are taken froma 1-hour simulation during Hurricane Sandy. In the brace members, while the wind load effect is dominant at theupper levels of the jacket (e.g., Level 1), the wave load effect becomes dominant at the lower level (e.g. Levels 2-4).
In contrast, the axial force in the leg member (L3), even at the lowest levels, is significantly affected by both wind
and wave loads.
Figure 3.32 shows maximum mudline reaction forces and moments evaluated from 1-hour simulations (carriedout every 10 hours) over a period from 10 to 60 hours into the UMCM simulation of Hurricane Sandy. As can beseen in this figure, the contribution of wind loads to the various mudline reaction forces and moments is not significant. It is only for the vertical reaction force, Fz , at the mudline that the wind loads are relatively more important, buteven there, when wind and wave load effects are combined, the very largest maximum Fz value (which occurs at 50
hours) shows that the total effect on the 1-hour maximum Fz of wind and waves together is almost the same as that
due to waves alone.

3.5 Discussion and Conclusions
In-depth studies of the response, during Hurricane Sandy, of a 5-MW offshore wind turbine with a jacket support
structure have been presented. To evaluate the response of offshore wind turbines during the evolution of this hurricane, ten mid-Atlantic potential offshore wind plant sites were selected. The track and intensity of Hurricane Sandy
were numerically simulated by a fully coupled atmospheric-wave-ocean model, UMCM.
Based on directional wave spectra resulting from the UMCM output, hurricane-generated wave kinematics were
simulated using second-order wave theory that was presented in Chapter 2. It was shown that wave spectra based on
the first 1 minute each hour could be used to represent the entire 1-hour period and to simulate waves for that hour as
needed for subsequent turbine response computations.
While the vertical wind shear profile for Hurricane Ike in Chapter 2 was estimated using the classical log law,in this chapter, we used wind field data from the WRF output, updated every 10 minutes and provided at several
elevations, to stochastically simulate needed wind velocity fields for Hurricane Sandy. The WRF output for Hurricane Sandy provided mean wind velocity data at 6 different levels up to 200 m above the surface. The vertical

61

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Current speed (m/s): to east direction

z(m)

0

0.6

−10

0.4

−20

0.2
0

−30

−0.2
−40
−50

−0.4
10

20

30

40

50

60

70

hour
Current speed (m/s): to north direction
0

0.5

−10
z(m)

0
−20
−0.5

−30
−40
−50

−1
10

20

30

40

50

60

70

hour

Figure 3.24. Variation with time of the depth-dependent current velocities during Hurricane Sandy (at the 50-m water depth location within Site No. 1).

wind profile that resulted, based on the WRF output, showed significant difference from the log law, which ignores
atmospheric stability effects. Because the mean wind velocity and wind direction during the hurricane show somevariation with time in each hour, the time-varying non-turbulent part of the full wind field was developed by using
an interpolation function based on six 10-min sampled wind field data values from the WRF output. The turbulent
wind part was stochastically simulated using standard Kaimal power spectra and coherence functions; the reference
wind velocity and friction velocity needed to define parameters of the Kaimal power spectra were evaluated using the
10-min wind speed and friction velocity values provided as part of the WRF output.
Due to the limitation of available software tools, an uncoupled modeling scheme was used to analyze the response of an offshore wind turbine with a jacket support structure. While in a coupled modeling approach, aerodynamic and hydrodynamic load effects can be evaluated simultaneously, an uncoupled modeling approach requires
separate computational steps to evaluate the aerodynamic loads and the hydrodynamic loads. The aerodynamic
load effects on the turbine rotor was first evaluated using a wind turbine model in FAST with a fixed base; the rotor
aerodynamic loads were then applied as point loads at the top of a model of a tower that was supported by a jacket
structure in Abaqus. Before evaluating the response of the offshore wind turbine with the jacket support during Hurricane Sandy, the uncoupled model was verified by comparing masses, natural frequencies, and the turbine response
in regular waves against results presented in the OC4 project report. For verification purposes, it was assumed thatthe jacket structure was fixed at the mudline. We found that the masses, the natural frequencies, and the turbine response in regular waves, evaluated using our uncoupled model, were all comparable to the results presented in the
OC4 project report.
Because interaction between the soil and an embedded pile can change the dynamic characteristics of the windturbine, this interaction effect was included in our Abaqus model of the jacket support structure. In this model, theinteraction between the soil and the embedded pile was modeled using the p-y curve approach specified in the American Petroleum Institute (API) RP2A guidelines. The soil profile used for the design of the OC4 jacket was used

62

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10

Wave Elevation(m)

5
0
-5
-10
5

0

࢛࢞ at z = -5m (m/s) (࢛ࢉ࢞ = 0.10m/s)
with current
without current

-5
5

0

࢛࢟ at z = -5m (m/s) (࢛ࢉ࢟ = -0.63m/s)-51500
Axial force at BRA-W-L4(kN)
1000
500
0
-500
-1000
-1500
400
420
440
460
Time(sec)

480

500

Figure 3.25. Time series at Site No. 1 of the wave elevation, the near-surface x-direction wave
and current velocities, the near-surface y-direction wave and current velocities, and the axial force in a brace, BRA-W-L4, after including and excluding the ocean current contribution(corresponding to 50 hours after 00:00 UTC on October 28, 2012 during Hurricane Sandy).

63

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60

Hub height wind velocity(m/s)

50
40
10

Wave Elevation(m)

0
-10
200

Axial force at BRA-W-L1 (kN)

0
-200
-400
800

Axial force at BRA-W-L2(kN)

400
0
-400
1000

Axial force at BRA-W-L3(kN)

0
-1000
2000
Axial force at BRA-W-L4(kN)
1000
0
-1000
200

220

240
260
Time(sec)

280

300

(a) only wind loads.
Figure 3.26. Time history of diagonal brace axial forces on Side 2 at various vertical levels of the jacket support structure at Site No. 1 during Hurricane Sandy (only wind loads).

64

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60

Hub height wind velocity(m/s)

50
40
10

Wave Elevation(m)

0
-10
200

Axial force at BRA-W-L1(kN)

0
-200
-400
800

Axial force at BRA-W-L2(kN)

400
0
-400
1000

Axial force at BRA-W-L3(kN)

0
-1000
2000
Axial force at BRA-W-L4(kN)
1000
0
-1000
200

220

240
260
Time(sec)

280

300

(a) only wave loads.
Figure 3.27. Time history of diagonal brace axial forces on Side 2 at various vertical levels of the jacket support structure at Site No. 1 during Hurricane Sandy (only wave loads).

65

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60

Hub height wind velocity(m/s)

50
40
10

Wave Elevation(m)

0
-10
200

Axial force at BRA-W-L1(kN)

0
-200
-400
800

Axial force at BRA-W-L2(kN)

400
0
-400
1000

Axial force at BRA-W-L3(kN)

0
-1000
2000
Axial force at BRA-W-L4(kN)
1000
0
-1000
200

220

240
260
Time(sec)

280

300

(a) considering wind and wave loads.
Figure 3.28. Time history of diagonal brace axial forces on Side 2 at various vertical levels of thejacket support structure at Site No. 1 during Hurricane Sandy (considering wind and wave loads).

66

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60

Hub height wind velocity(m/s)

50
40
10

Wave Elevation(m)0-100 Axial force at LEG-SW-L1(kN)
-4000
-8000
0

Axial force at LEG-SW-L2(kN)

-4000
-8000
0

Axial force at LEG-SW-L3(kN)

-4000
-8000
0 Axial force at LEG-SW-L4(kN)
-4000
-8000
200

220

240
260
Time(sec)

280

300

(a) only wind loads.
Figure 3.29. Time history of leg (L3) axial forces at various vertical levels of thejacket support structure at Site No. 1 during Hurricane Sandy (only wind loads).

67

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60

Hub height wind velocity(m/s)

50
40
10

Wave Elevation(m)0-100 Axial force at LEG-SW-L1(kN)
-4000
-8000
0

Axial force at LEG-SW-L2(kN)

-4000
-8000
0

Axial force at LEG-SW-L3(kN)

-4000
-8000
0 Axial force at LEG-SW-L4(kN)
-4000
-8000
200

220

240
260
Time(sec)

280

300

(a) only wave loads.
Figure 3.30. Time history of leg (L3) axial forces at various vertical levels of thejacket support structure at Site No. 1 during Hurricane Sandy (only wave loads).

68

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60

Hub height wind velocity(m/s)

50
40
10

Wave Elevation(m)0-100 Axial force at LEG-SW-L1(kN)
-4000
-8000
0

Axial force at LEG-SW-L2(kN)

-4000
-8000
0

Axial force at LEG-SW-L3(kN)

-4000
-8000
0 Axial force at LEG-SW-L4(kN)
-4000
-8000
200

220

240
260
Time(sec)

280

300

(a) considering wind and wave loads.
Figure 3.31. Time history of leg (L3) axial forces at various vertical levels of the jacket support structure at Site No. 1 during Hurricane Sandy (considering wind and wave loads).

69

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3
2.5

9

only wave
only wind
wind+wave

87
6
Mx(MN-m)Fx(MN)

2

only wave
only wind
wind+wave

1.5
1

5
4
3
2

0.5
1
0

0

10
20
30
40
50
60
Time after 00:00 UTC 2012-10-28(hours)

10
20
30
40
50
60
Time after 00:00 UTC 2012-10-28(hours)(a) x-direction.
1.4
1.2

18

only wave
only wind
wind+wave

16
14

only wave
only wind
wind+wave

1
My(MN-m)Fy(MN)

12
0.8
0.6

10
8
6

0.4
4
0.2
0

2
0

10
20
30
40
50
60
Time after 00:00 UTC 2012-10-28(hours)

10
20
30
40
50
60
Time after 00:00 UTC 2012-10-28(hours)(b) y-direction.
25

20

0.7

only wave
only wind
wind+wave

0.6

only wave
only wind
wind+wave

15

Mz(MN-m)Fz(MN)

0.5

10

0.4
0.3
0.2

5
0.1
0

0

10
20
30
40
50
60
Time after 00:00 UTC 2012-10-28(hours)

10
20
30
40
50
60
Time after 00:00 UTC 2012-10-28(hours)(c) z-direction.
Figure 3.32. Maximum mudline reaction forces (LEG-SW-MUD) at Site No. 1 during Hurricane Sandy.

70

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to evaluate the soil lateral stiffness characteristics. Because soil-structure interaction effects can significantly influence the overall dynamic characteristics of the structural system, we evaluated the effect of different soil-interaction
models on overall system eigenfrequencies.
In turbine response studies related to Hurricane Sandy, we first studied the hydrodynamic loads experienced
by a jacket member. As was shown by Agarwal [48], hydrodynamic loading on a monopile-supported wind turbine
is dominated by inertia force and the turbine response can then be close to a Gaussian process, especially for linear
waves. With the OC4 reference jacket used in this study, composed of brace members of 1.0 m diameter and leg
members of 1.2 m diameter, which are more slender than the 6-meter diameter monopile studied by Agarwal [48],
we found that drag load effects were comparable to inertia load effects and that the nonlinearity and non-Gaussiancharacter of the total hydrodynamic load effect increased. As a results, maximum response values estimated basedon Gaussian assumptions were significantly different from the actual response maxima computed in hour-longsimulations during Hurricane Sandy.
We also evaluated the effect of ocean currents on turbine response during Hurricane Sandy. Because drag load
effects for the OC4 jacket are comparable in importance to inertia load effects and because drag loads depend on
current velocities, the effect of including ocean currents toward the total response was found to be non-negligible as
was seen when we studied maximum axial forces in a jacket brace member. This finding suggests that it is importantto have fully coupled wave and ocean current inputs for realistic evaluation of the response of an offshore windturbine during a hurricane.
Finally, we evaluated the relative importance of hydrodynamic versus aerodynamic loads on the overall jacket
response during Hurricane Sandy. We found that the relative contribution of wind and wave loads varied dependingon the type and location of the jacket member being considered. For a diagonal brace member’s axial forces thatwere studied, while the wind load effect was found to be dominant at upper levels in the jacket, the wave load effectwas dominant at the lower levels. In contrast, the axial force in a leg member at lower level was significantly influenced by both wind and wave loads. The contribution of wind load effects to the total mudline vertical reaction force
was found to be insignificant.

71

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4

Summary and Conclusions

4.1 Summary of Research Objectives
The simulation of a coupled wind, wave, and current inputs based on UMCM output and the response evaluationof an offshore wind turbine using these coupled inputs were the primary goals of this study. In particular, we had
three main research objectives: (i) to investigate the characteristics of hurricane-generated wind, waves, and currents;(ii) to generate time series input of turbulent wind fields and wave kinematics using the hurricane simulation output;and (iii) to predict and interpret the turbine response during Hurricanes Ike (2008) and Sandy (2012) using theassembled turbulent wind fields, wave kinematics, and current fields.

4.2 Summary of the Problem Descriptions
In order to assess the risks to potential U.S. offshore wind farms from the destructive environmental conditions
induced by hurricanes, Hurricane Ike(2008) and Sandy(2012) were numerically simulated by a state-of-the-art hurricane numerical simulation model, the University of Miami Coupled Model (UMCM). We used the wind, wave, andcurrent output data provided from these numerical simulations of the two hurricanes. UMCM consists of atmosphere(WRF), ocean surface wave (UMWM), and ocean (HYCOM) component models.
We selected two and ten sites, respectively, for Hurricanes Ike (2008) and Sandy (2008). For Ike, single turbine units at the two sites in the Gulf of Mexico were studied. For Sandy, a detailed turbine response at one of ten
potential mid-Atlantic wind energy development sites was undertaken.
The coupled wind and wave fields at selected locations were stochastically simulated and we evaluated theturbine response of a 5-MW offshore wind turbine supported by a monopile or a jacket structure over important
periods when the storm is close to making landfall.
For Hurricane Ike, we investigated:• swell versus wind seas;• the effect of yaw misalignment;• the effect of blade pitch angle variation and control;• the effect of blade azimuthal position on loads; and• the effect of turbine parking strategies.
Also, under the assumption of zero yaw misalignment and of blades pitched to feather for Hurricane Sandy, weinvestigated:• hydrodynamic loads and associated response on jacket members;• the effect of hurricane-induced currents; and• a comparison of hurricane-induced hydrodynamic versus aerodynamic loads.

4.3 Conclusions
4.3.1

Modeling Hurricane Ike’s Influence

Because hurricane directional waves can be thought of as composed of two wave components, swell and wind seas,
which have different characteristics, their characteristics are evaluated after separating swell and wind seas from thedirectional wave spectra resulting from the UMCM output by the wave age criterion. The mean wave frequenciesof swell components are significantly lower than resonant frequencies associated with tower bending. Also, the72This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

variation of mean wave frequency and wave direction corresponding to swell is relatively insignificant because theevolution is not as strongly affected by the local wind.
While the contribution from hydrodynamic loading to the tower response is only very slightly influenced by
the amount of yaw misalignment, the aerodynamic loading contribution is significantly influenced by it. The significantly lower turbine loads in the case of zero yaw misalignment highlights the importance of a reliable yaw backup
power system, which is strongly recommended since a grid failure during a hurricane could result in loss of theneeded yaw control.
Blade pitch control is important during the hurricane; as expected, blades pitched to feather result in the lowest
tower response maxima.
While the tower base fore-aft moment in a case with zero yaw error does not vary greatly for different blade
azimuthal positions, the tower base side-to-side moment is seen to vary by a considerably larger amount. In general,though not at all times during the hurricane, largest and smallest tower load maxima occurred for rotor configurations
where one blade is in the 0 and 180 degree azimuthal position, respectively.
While the tower base fore-aft moment in a case with zero yaw error is not significantly different with the different turbine parking strategies, the tower base side-to-side moment is seen to be noticeably different and the parkedstandstill case leads to systematically larger loads than the idling case during the hurricane.
4.3.2

Modeling Hurricane Sandy’s InfluenceFirst, we evaluated the nature of the hydrodynamic loads experienced by a jacket member. The small section sizeof jacket members makes the drag load effect comparable to the inertia load effect; it also makes the nonlinearityof the total hydrodynamic load effect increase. Consequently, this high nonlinearity of the response process makes
differences between actual response maxima relative to Gaussian-based maxima significant.
We also evaluated the effect of ocean currents on the overall turbine response. Because the drag load effects
for the selected OC4 jacket are of comparable importance to the inertia load effect and because drag loads include
contributions from the ocean current, we found that the influence of ocean currents on the total response was nonnegligible. This was confirmed by studying maximum axial forces in a diagonal brace member of the jacket structure.
The relative importance of hydrodynamic and aerodynamic loads was also investigated. We found that therelative contribution of wind versus wave loads depends on the type and location of the jacket member of interest.
For example, in the brace members studied, while wind load effects were dominant at the higher levels of the jacket
structure, wave load effects were dominant at the lower levels. Axial forces in leg members at the lower level, however, were significantly affected by both wind and wave loads. The contribution of wind load effects on total mudline
reaction forces was not significant.

73

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Appendices74

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Appendix A
UMCM input files
A.1 Hurricane Ike Simulation
A.1.1 WRF(namelist.input)&time_control
run_days
run_hours
run_minutes
run_seconds
start_year
start_monthstart_day
start_hour
start_minutestart_second
end_year
end_month
end_day
end_hourend_minute
end_second
interval_seconds
input_from_file
history_intervalframes_per_outfile
restartrestart_interval
io_form_history
io_form_restart
io_form_input
io_form_boundary
debug_level
input_from_hires
rsmas_data_path/&domains
sr_x
sr_y
time_step
time_step_fract_num
time_step_fract_den
max_dom
s_we
e_we
s_sn
e_sn
s_verte_vertnum_metgrid_levels
eta_levels

use_surfacedxdy
grid_idparent_id
i_parent_startj_parent_startparent_grid_ratio
parent_time_step_ratio
feedbacksmooth_option

= 8,
= 0,
= 0,
= 0,
= 2008, 2008, 2008,
= 09,
09,
09,
= 08,
08,
08,
= 12,
12,
12,
= 00,
00,
00,
= 00,
00,
00,
= 2008, 2008, 2008,
= 09,
09,
09,
= 13,
13,
13,
= 12,
12,
12,
= 00,
00,
00,
= 00,
00,
00,
= 21600= .true.,.false.,.false.,= 60, 60, 60= 1, 1, 1,= .f.,= 360,
= 2
= 2
= 2
= 2
= 0
= .f., .t., .t.,
= "/home/disk/manta9/joe/topo/ts",

= 0,
0,
0,
= 0,
0,
0,
= 60,
= 0,
= 1,
= 3,
= 1,
1,
1,
= 400,
700,
331,
= 1,
1,
1,
= 360,
502,
331,
= 1,
1,
1,
= 36,
36,
36,
= 22
= 1.000, 0.996, 0.992, 0.988, 0.983, 0.970, 0.954,
0.934, 0.909, 0.880, 0.845, 0.807,
0.765, 0.719, 0.672, 0.622, 0.571,
0.520, 0.468, 0.420, 0.376, 0.335,
0.298, 0.263, 0.231, 0.202, 0.175,
0.150, 0.127, 0.106, 0.088, 0.070,
0.055, 0.040, 0.026, 0.000= .false.
= 12000, 4000, 1333.33,= 12000, 4000, 1333.33,
= 1,
2,
3,
= 0,
1,
2,
= 1,
35, 473,
= 1,
85,
90,
= 1,
3,
3,
= 1,
3,
3,
= 1,
= 0

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vortex_interval
max_vortex_speed
time_to_move
corral_dist/= 20, 20, 20, 20,= 40, 40, 40, 40,= 0, 9999, 0= 0, 25, 25, 25,&physics
mp_physics
ra_lw_physics
ra_sw_physics
radt
sf_sfclay_physics
sf_surface_physics
bl_pbl_physics
bldt
cu_physics
cudt
isfflxisftcflx
ifsnow
icloudsurface_input_source
num_soil_layers
sf_urban_physics
mp_zero_out
maxiens
maxensmaxens2
maxens3
ensdimslope_rad
topo_shading
omlcall
oml_hml0
oml_gamma
/

= 4,
= 1,
= 1,
= 15,
= 1,
= 1,
= 1,
= 0,
= 1,
= 5,
= 1,
= 2,
= 0,
= 1,
= 1,
= 5,
= 0,
= 0,
= 1,
= 3,
= 3,
= 16,
= 144,
= 0,
= 0,
= 0,
= 100,= 0.14,&fdda
grid_fdda
gfdda_inname
gfdda_end_h
gfdda_interval_m
fgdt
fgdtzero
if_no_pbl_nudging_uv
if_no_pbl_nudging_t
if_no_pbl_nudging_ph
if_zfac_uv
k_zfac_uv
if_zfac_tk_zfac_t
if_zfac_phk_zfac_phdk_zfac_uv
dk_zfac_tdk_zfac_ph
guv
gt
gph
if_ramping
dtramp_min
io_form_gfdda
/

= 1,
0,
0,
= "wrffdda_d<domain>",
= 24,
24,
24,
= 360,
360,
360,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 10,
10,
10,
= 0,
0,
0,
= 10,
10,
10,
= 0,
0,
0,
= 10,
10,
10,
= 1,
1,
1,
= 1,
1,
1,
= 1,
1,
1,
= 0.0003,
0.0000,= 0.0000,
0.0000,= 0.0000,
0.0000,= 1,= 60.0,= 2,&dynamics
iso_temp
w_damping
diff_opt
km_optdiff_6th_opt
diff_6th_factor
base_temp
damp_opt
zdamp
dampcoef
khdif

= 0.,
= 1,
= 1,
= 4,
= 0,
= 0.12,= 290.
= 0,= 5000.,= 0.2,
= 0,

4,
1,
1,
15,
1,
1,
1,
0,
0,
0,

4,
1,
1,
15,
1,
1,
1,
0,
0,
0,

5000.,
0.2,
0,0.0000,0.0000,0.0000,5000.,
0.2
0,76This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

kvdifnon_hydrostatic
moist_adv_opt
scalar_adv_opt
use_baseparam_fr_nml/&bdy_control
spec_bdy_width
spec_zone
relax_zone
specifiednested
/

= 0,
0,
0,
= .true., .true., .true.,= 0, 0, 0,= 0, 0, 0,= .true.

= 5,
= 1,
= 4,
= .true., .false.,.false.,= .false., .true., .true.,&grib2/&namelist_quilt
nio_tasks_per_group = 0,
nio_groups = 1,/

A.1.2 UMWM(main.nml)&DOMAIN
isGlobal= .F.
! Global (.T.) or regional (.F.)
mm= 1195! Domain size in x
nm
= 1075! Domain size in yom
= 37
! Number of frequency binspm
= 36
! Number of directions
fmin= 0.0313! Lowest frequency bin [Hz]
fmax
= 2.0
! Highest frequency bin [Hz]
fprog
= 0.5
! Highest prognostic frequency bin [Hz]startTimeStr = ’2008-09-08_12:00:00’ ! Simulation start timestopTimeStr= ’2008-09-13_12:00:00’ ! Simulation end time
dtg
= 60
! Global (I/O) time step [s]restart= .f.
! Restart from file/
&PHYSICSg= 9.80665 ! Gravitational acceleration[m/s^2]
nu_air
= 1.56E-5 ! Kinematic viscosity of air[m^2/s]nu_water= 0.9E-6 ! Kinematic viscosity of water [m^2/s]
sfct= 0.07! Surface tension [N/m]
kappa
= 0.4
! Von Karman constantz= 10.
! Height of the input wind speed [m]gustiness= 0.0! Random wind gustiness factor (should be between 0 and 0.2)
dmin
= 20.
! Depth limiter [m]explim= 1.1! Exponent limiter (0.69 ~ 100% growth)
sin_fac= 0.11! Input factor from following winds
sin_diss1= 0.10! Damping factor from opposing winds
sin_diss2= 0.01! Damping factor from swell overrunning windsds_fac= 42.
! Breaking dissipation factor
sds_power= 2.5! Saturation spectrum power
mss_fac= 120.
! Mean-square-slope adjustment to Sds
snl_fac= 5.
! Wave energy downshifting factor
sdt_fac= 0.01! Dissipation due to turbulence factor
sbf_fac= 0.003! Bottom friction coefficient [m/s]sbp_fac= 0.003! Bottom percolation coefficient [m/s]/&GRID
gridFromFile = .T.
! Set to .T. if lon/lat fields are input from filedelx
= 12000 ! Grid spacing in x [m] if gridFromFile = .F.
dely= 12000 ! Grid spacing in y [m] if gridFromFile = .F.
topoFromFile = .T.
! Set to .T. to input bathymetry from filedpt
= 1000 ! Constant water depth [m] if topoFromFile = .F.
fillEstuaries = .F.
! Set to .T. to fill cells with 3 land neighbours
fillLakes= .F.
! Set to .T. to fill user chosen seas/lakes/&FORCING
winds= .F. ! Wind input from filecurrents= .F. ! Currents input from file
air_density= .F. ! Air density input from filewater_density = .F. ! Water density input from file77

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/&FORCING_CONSTANT
wspd0
= 25
! Wind speed [m/s]
wdir0
= 0.
! Wind direction [rad]uc0= 0.
! x-component ocean current [m/s]vc0= 0.
! y-component ocean current [m/s]rhoa0= 1.2 ! Air density [kg/m^3]
rhow0= 1025 ! Water density [kg/m^3]/&OUTPUT
outgrid= 1! Gridded output interval [hours]
outspec=-1! Spectrum output interval [hours]
outrst= 6! Restart output interval [hours]
xpl= 600 ! Grid cell in x for stdout (screen)ypl= 400 ! Grid cell in y for stdout (screen)stokes= .T. ! Output Stokes drift velocity fields/&STOKES
depths
= 0 1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 25 30 35 40 50 60 70 80 90 100

A.1.3 HYCOM(blkdat.input)
ERA-15 forcing; flx-s14w; LWcorr; precip+2mm; SSSrlx; FCT2 tsadvc.; 0-tracer.
Sigma0; GDEM3 init; KPP mixed layer; SeaWiFS mon KPAR; nested in ATLd0.08 2.6;
S-Z(15-11): dp00/f/x/i=3m/1.125/12m/1m; ds=1m/1.125/4m; src_2.2.34;
12345678901234567890123456789012345678901234567890123456789012345678901234567890
22’iversn’ = hycom version number x10
201’iexpt ’ = experiment number x10
1000
’idm
’ = longitudinal array size
1000
’jdm
’ = latitudinal array size
700
’itest ’ = grid point where detailed diagnostics are desired
700’jtest ’ = grid point where detailed diagnostics are desired
32’kdm’ = number of layers
32’nhybrd’ = number of hybrid levels (0=all isopycnal)
14’nsigma’ = number of sigma levels (nhybrd-nsigma z-levels)
3.0’dp00 ’ = deep
z-level spacing minimum thickness (m)450.0’dp00x ’ = deep
z-level spacing maximum thickness (m)1.18’dp00f ’ = deep
z-level spacing stretching factor (1.0=const.space)
0.5’ds00 ’ = shallow z-level spacing minimum thickness (m)75.0’ds00x ’ = shallow z-level spacing maximum thickness (m)1.18’ds00f ’ = shallow z-level spacing stretching factor (1.0=const.space)
1.0’dp00i ’ = deep iso-pycnal spacing minimum thickness (m)6.0’isotop’ = shallowest depth for isopycnal layers(m, <0 from file)35.0’saln0 ’ = initial salinity value (psu), only used for iniflg<21’locsig’ = locally-referenced pot. density for stability (0=F,1=T)
2’kapref’ = thermobaric ref. state (-1=input,0=none,1,2,3=constant)2’thflag’ = reference pressure flag (0=Sigma-0, 2=Sigma-2)
34.0’thbase’ = reference density (sigma units)0’vsigma’ = spacially varying isopycnal target densities (0=F,1=T)
28.10’sigma ’ = layer 1 isopycnal target density (sigma units)
28.90’sigma ’ = layer 2 isopycnal target density (sigma units)
29.70’sigma ’ = layer 3 isopycnal target density (sigma units)
30.50’sigma ’ = layer 4 isopycnal target density (sigma units)
30.95’sigma ’ = layer 5 isopycnal target density (sigma units)
31.50’sigma ’ = layer 6 isopycnal target density (sigma units)
32.05’sigma ’ = layer 7 isopycnal target density (sigma units)
32.60’sigma ’ = layer 8 isopycnal target density (sigma units)
33.15’sigma ’ = layer 9 isopycnal target density (sigma units)
33.70’sigma ’ = layer 10 isopycnal target density (sigma units)
34.25’sigma ’ = layer 11 isopycnal target density (sigma units)
34.75’sigma ’ = layer 12 isopycnal target density (sigma units)
35.15’sigma ’ = layer 13 isopycnal target density (sigma units)
35.50’sigma ’ = layer 14 isopycnal target density (sigma units)
35.80’sigma ’ = layer 15 isopycnal target density (sigma units)
36.04’sigma ’ = layer 16 isopycnal target density (sigma units)
36.20’sigma ’ = layer 17 isopycnal target density (sigma units)
36.38’sigma ’ = layer 18 isopycnal target density (sigma units)
36.52’sigma ’ = layer 19 isopycnal target density (sigma units)
36.62’sigma ’ = layer 20 isopycnal target density (sigma units)
36.70’sigma ’ = layer 21 isopycnal target density (sigma units)
36.77’sigma ’ = layer 22 isopycnal target density (sigma units)
36.83’sigma ’ = layer 23 isopycnal target density (sigma units)
36.89’sigma ’ = layer 24 isopycnal target density (sigma units)
36.97’sigma ’ = layer 25 isopycnal target density (sigma units)

78

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37.02’sigma ’ = layer 26 isopycnal target density (sigma units)
37.06’sigma ’ = layer 27 isopycnal target density (sigma units)
37.10’sigma ’ = layer 28 isopycnal target density (sigma units)
37.17’sigma ’ = layer 29 isopycnal target density (sigma units)
37.30’sigma ’ = layer 30 isopycnal target density (sigma units)
37.42’sigma ’ = layer 31 isopycnal target density (sigma units)
37.48’sigma ’ = layer 32 isopycnal target density (sigma units)3’iniflg’ = initial state flag (0=levl, 1=zonl, 2=clim)
0’jerlv0’ = initial jerlov water type (1 to 5; 0 to use KPAR)
3’yrflag’ = days in year flag
(0=360, 1=366, 2=366J1, 3=actual)0’sshflg’ = diagnostic SSH flag (0=SSH,1=SSH&stericSSH)
0.0416667 ’dsurfq’ = number of days between model diagnostics at the surface
0.0416667 ’diagfq’ = number of days between model diagnostics
0.0’proffq’ = number of days between model diagnostics at selected locs
0.0
’tilefq’ = number of days between model diagnostics on selected tiles
0.0’meanfq’ = number of days between model diagnostics (time averaged)
9999.0’rstrfq’ = number of days between model restart output
1.0’bnstfq’ = number of days between baro nesting archive input
1.0’nestfq’ = number of days between 3-d nesting archive input
0.125 ’cplifq’ = number of days (or time steps) between sea ice coupling
120.0’baclin’ = baroclinic time step (seconds), int. divisor of 86400
5.0’batrop’ = barotropic time step (seconds), int. div. of baclin/20’incflg’ = incremental update flag (0=no, 1=yes, 2=full-velocity)
100’incstp’ = no. timesteps for full update (1=direct insertion)
1’incupf’ = number of days of incremental updating input
0.125 ’wbaro ’ = barotropic time smoothing weight1’btrlfr’ = leapfrog barotropic time step (0=F,1=T)
0’btrmas’ = barotropic is mass conserving (0=F,1=T)
8.0’hybrlx’ = HYBGEN: inverse relaxation coefficient (time steps)
0.01’hybiso’ = HYBGEN: Use PCM if layer is within hybiso of target density
3’hybmap’ = hybrid
remapper flag (0=PCM, 1=PLM, 2=PPM, 3=WENO-like)0’hybflg’ = hybrid
generator flag (0=T&S, 1=th&S, 2=th&T)0’advflg’ = thermal advection flag (0=T&S, 1=th&S, 2=th&T)
2’advtyp’ = scalaradvection type (0=PCM,1=MPDATA,2=FCT2,4=FCT4)2’momtyp’ = momentum advection type (2=2nd order, 4=4th order)-1.0’slip ’ = +1 for free-slip, -1 for non-slip boundary conditions
0.05’visco2’ = deformation-dependent Laplacian viscosity factor
0.0’visco4’ = deformation-dependent biharmonic viscosity factor
0.0’facdf4’ =speed-dependent biharmonic viscosity factor
0.003 ’veldf2’ = diffusion velocity (m/s) for Laplacian momentum dissip.
0.02’veldf4’ = diffusion velocity (m/s) for biharmonic momentum dissip.
0.0’thkdf2’ = diffusion velocity (m/s) for Laplacian thickness diffus.
0.01’thkdf4’ = diffusion velocity (m/s) for biharmonic thickness diffus.
0.005 ’temdf2’ = diffusion velocity (m/s) for Laplacian temp/saln diffus.
1.0’temdfc’ = temp diffusion conservation (0.0,1.0 all dens,temp resp.)
0.0’vertmx’ = diffusion velocity (m/s) for momentum at MICOM M.L.base
0.05’cbar ’ = rms flow speed(m/s) for linear bottom friction
2.2e-3 ’cb’ = coefficient of quadratic bottom friction
0.0’drglim’ = limiter for explicit friction (1.0 none, 0.0 implicit)
0.0’drgscl’ = scale factor for tidal drag(0.0 for no tidal drag)
500.0’thkdrg’ = thickness of bottom boundary layer for tidal drag (m)10.0’thkbot’ = thickness of bottom boundary layer (m)0.02’sigjmp’ = minimum density jump across interfaces (kg/m**3)
0.3’tmljmp’ = equivalent temperature jump across mixed-layer (degC)
15.0’thkmls’ = reference mixed-layer thickness for SSS relaxation (m)0.0’thkmlt’ = reference mixed-layer thickness for SST relaxation (m)5.0’thkriv’ = nominal thickness of river inflow (m)20.0’thkfrz’ = maximum thickness of near-surface freezing zone (m)0’iceflg’ = sea ice model flag (0=none,1=energy loan,2=coupled/esmf)
0.0’tfrz_0’ = ENLN: ice melting point (degC) at S=0psu-0.054 ’tfrz_s’ = ENLN: gradient of ice melting point (degC/psu)
0.0’ticegr’ = ENLN: temp. grad. inside ice (deg/m); =0 use surtmp
0.5’hicemn’ = ENLN: minimum ice thickness (m)10.0’hicemx’ = ENLN: maximum ice thickness (m)0’ntracr’ = number of tracers (0=none,negative to initialize)0’trcflg’ = tracer flags(one digit per tr, most sig. replicated)
240’tsofrq’ = number of time steps between anti-drift offset calcs
0.0’tofset’ = temperature anti-drift offset (degC/century)
0.0’sofset’ = salnity
anti-drift offset (psu/century)
1’mlflag’ = mixed layer flag (0=none,1=KPP,2-3=KT,4=PWP,5=MY,6=GISS)
1’pensol’ = KT:
activate penetrating solar rad.
(0=F,1=T)
999.0’dtrate’ = KT:
maximum permitted m.l. detrainment rate (m/day)
19.2’thkmin’ = KT/PWP: minimum mixed-layer thickness (m)1’dypflg’ = KT/PWP: diapycnal mixing flag (0=none, 1=KPP, 2=explicit)
240’mixfrq’ = KT/PWP: number of time steps between diapycnal mix calcs
1.e-7 ’diapyc’ = KT/PWP: diapycnal diffusivity x buoyancy freq. (m**2/s**2)

79

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0.25’rigr ’ = PWP:
critical gradient richardson number
0.65’ribc ’ = PWP:
critical bulk
richardson number
0.7’rinfty’ = KPP:
maximum gradient richardson number (shear inst.)
0.25’ricr ’ = KPP:
critical bulk
richardson number
0.0’bldmin’ = KPP:
minimum surface boundary layer thickness (m)1200.0’bldmax’ = K-PROF: maximum surface boundary layer thickness (m)0.7’cekman’ = KPP/KT: scale factor for Ekman depth
1.0’cmonob’ = KPP:
scale factor for Monin-Obukov depth0’bblkpp’ = KPP:
activate bottom boundary layer(0=F,1=T)
1’shinst’ = KPP:
activate shear instability mixing (0=F,1=T)
1’dbdiff’ = KPP:
activate double diffusion mixing (0=F,1=T)
1’nonloc’ = KPP:
activate nonlocal b. layer mixing (0=F,1=T)0’botdiw’ = K-PROF: activate bot.enhan.int.wav mixing (0=F,1=T)
1’difout’ = K-PROF: output visc/diff coffs in archive (0=F,1=T)0’difsmo’ = K-PROF: number of layers with horiz smooth diff coeffs
50.0e-4 ’difm0 ’ = KPP:
max viscosity
due to shear instability (m**2/s)
50.0e-4 ’difs0 ’ = KPP:
max diffusivity due to shear instability (m**2/s)
0.3e-4 ’difmiw’ = KPP:
background/internal wave viscosity(m**2/s)
0.1e-4 ’difsiw’ = KPP:
background/internal wave diffusivity(m**2/s)
10.0e-4 ’dsfmax’ = KPP:
salt fingering diffusivity factor(m**2/s)
1.9’rrho0 ’ = KPP:
salt fingering rp=(alpha*delT)/(beta*delS)
98.96
’cs
’ = KPP:value for nonlocal flux term
10.0
’cstar ’ = KPP:
value for nonlocal flux term
0.0’cv
’ = KPP:buoyancy frequency ratio (0.0 to use a fn. of N)
5.0’c11’ = KPP:value for turb velocity scale2’hblflg’ = KPP:
b. layer interp. flag (0=const.,1=linear,2=quad.)2’niter ’ = KPP:
iterations for semi-implicit soln. (2 recomended)0’fltflg’ = FLOATS: synthetic float flag (0=no; 1=yes)
4’nfladv’ = FLOATS: advect every nfladv bacl. time steps (even, >=4)1’nflsam’ = FLOATS: output (0=every nfladv steps; >0=no. of days)
0’intpfl’ = FLOATS: horiz. interp. (0=2nd order+n.n.; 1=n.n. only)0’iturbv’ = FLOATS: add horiz. turb. advection velocity (0=no; 1=yes)
1’ismpfl’ = FLOATS: sample water properties at float (0=no; 1=yes)
4.63e-6’tbvar ’ = FLOATS: horizontal turb. vel. variance scale (m**2/s**2)
0.4’tdecri’ = FLOATS: inverse decorrelation time scale (1/day)2’lbflag’ = lateral barotropic bndy flag (0=none, 1=port, 2=input)2’tidflg’ = TIDES: tidal forcing flag
(0=none,1=open-bdy,2=bdy&body)
11111111 ’tidcon’ = TIDES: 1 digit per (Q1K2P1N2O1K1S2M2), 0=off,1=on
0.06’tidsal’ = TIDES: scalar self attraction and loading factor (<0: file)1’tidgen’ = TIDES: generic time (0=F,1=T)
1.0’tidrmp’ = TIDES:
ramp time (days)
0.0’tid_t0’ = TIDES: origin for ramp time (model day)12
’clmflg’ = climatology frequency flag
(6=bimonthly, 12=monthly)2’wndflg’ = wind stress input flag (0=none,1=u/v-grid,2,3=p-grid)1’ustflg’ = ustar forcing
flag(3=input,1,2=wndspd,4=stress)3’flxflg’ = thermal forcing
flag (0=none,3=net-flux,1,2,4=sst-based)0’empflg’ = E-P
forcing
flag (0=none,3=net_E-P, 1,2,4=sst-bas_E)
0’dswflg’ = diurnal shortwave flag (0=none,1=daily to diurnal corr.)
0’sssflg’ = SSS relaxation flag (0=none,1=clim,-1=clim&rmx)
0’lwflag’ = longwave (SST) flag (0=none,1=clim,2=atmos)
0’sstflg’ = SST relaxation flag (0=none,1=clim,2=atmos,3=observed)0’icmflg’ = ice mask
flag (0=none,1=clim,2=atmos,3=obs/coupled)0’flxoff’ = net flux offset flag
(0=F,1=T)0’flxsmo’ = smooth surface fluxes(0=F,1=T)0’relax ’ = activate lateral boundary nudging(0=F,1=T)0’trcrlx’ = activate lat. bound. tracer nudging (0=F,1=T)0’priver’ = rivers as a precipitation bogas(0=F,1=T)0’epmass’ = treat evap-precip as a mass exchange (0=F,1=T)

A.2 Hurricane Sandy Simulation
A.2.1 WRF(namelist.input)&time_control
run_days
run_hours
run_minutes
run_seconds
start_year= 2012, 2012, 2012,
start_month = 10,10,10,start_day
= 27,
27,
27,
start_hour
= 00,
00,
00,
start_minute = 00,
00,
00,

= 7,
= 0,
= 0,
= 0,

80

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start_second = 00,00,00,
end_year= 2012, 2012, 2012,
end_month
= 10,
10,
10,
end_day
= 31,
31,
31,
end_hour
= 00,
00,
00,
end_minute
= 00,
00,
00,
end_second
= 00,
00,
00,
interval_seconds
input_from_file
input_from_hires
history_intervalframes_per_outfile
restartrestart_interval
io_form_history
io_form_restart
io_form_input
io_form_boundary
debug_levelrsmas_data_path/&domains
hypsometric_opt
time_step
time_step_fract_num
time_step_fract_den
max_dom
s_we
e_we
s_sn
e_sn
s_verte_vertnum_metgrid_levels
eta_levels

use_surfacedxdy
grid_idparent_id
i_parent_startj_parent_startparent_grid_ratio
parent_time_step_ratio
feedbacksmooth_option
vortex_interval
max_vortex_speed
time_to_move
corral_dist
track_level/&physics
mp_physics
ra_lw_physics
ra_sw_physics
radt
sf_sfclay_physics
sf_surface_physics
bl_pbl_physics
bldt
cu_physics
cudt
kfeta_trigger
isfflxisftcflx
ifsnow
icloud= 21600= .t.,.f.,.f.,= .f.,.t.,.t.,= 60, 60, 60,= 1, 1, 1,= .f.,= 360,
= 2
= 2
= 2
= 2
= 0
= "/home/disk/manta9/joe/topo/ts",

= 1,
= 60,
= 0,
= 1,
= 2,
= 1,
1,
1,
= 400,
562,
361,
= 1,
1,
1,
= 360,
622,
361,
= 1,
1,
1,
= 36,
36,
36,
= 27
= 1.000, 0.996, 0.992, 0.988, 0.983, 0.970, 0.954,
0.934, 0.909, 0.880, 0.845, 0.807,
0.765, 0.719, 0.672, 0.622, 0.571,
0.520, 0.468, 0.420, 0.376, 0.335,
0.298, 0.263, 0.231, 0.202, 0.175,
0.150, 0.127, 0.106, 0.088, 0.070,
0.055, 0.040, 0.026, 0.000= .false.
= 12000, 4000, 1333.33,= 12000, 4000, 1333.33,
= 1,
2,
3,
= 0,
1,
2,
= 1,
130, 257,= 1,
130, 205,
= 1,
3,
3,
= 1,
3,
3,
= 1,
= 0
= 20, 20, 20,= 40, 40, 40,= 0, 9999, 0,= 0, 15, 15,= 85000

= 4,
= 4,
= 4,
= 15,
= 1,
= 1,
= 1,
= 0,
= 1,
= 5,
= 2,
= 1,
= 2,
= 0,
= 1,

4,
4,
4,
15,
1,
1,
1,
0,
0,
0,

4,
4,
4,
15,
1,
1,
1,
0,
0,
0,

81

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surface_input_source
num_soil_layers
sf_urban_physics
mp_zero_out
maxiens
maxensmaxens2
maxens3
ensdimslope_rad
topo_shading
omlcall
oml_hml0
oml_gamma
stoch_force_opt
stoch_vertstruc_opt
tot_backscat_psi
tot_backscat_t
nens
/

= 1,
= 5,
= 0,
= 0,
= 1,
= 3,
= 3,
= 16,
= 144,
= 0,
= 0,
= 0,
= 100,= 0.14,= 0, 0, 0, ! turns SKEBS on (0=off)= 1, 1, 1, ! makes SKEBS pattern vary with height= 1E-05,! default perturbation amplitude for streamfunction field= 1E-06,!default perturbation amplitude for temperature field= 9,!random seed&fdda
grid_fdda
gfdda_inname
gfdda_end_h
gfdda_interval_m
fgdt
fgdtzero
if_no_pbl_nudging_uv
if_no_pbl_nudging_t
if_no_pbl_nudging_ph
if_zfac_uv
k_zfac_uv
if_zfac_tk_zfac_t
if_zfac_phk_zfac_phdk_zfac_uv
dk_zfac_tdk_zfac_ph
guv
gt
gph
if_ramping
dtramp_min
io_form_gfdda
/

= 0,
0,
0,
= "wrffdda_d<domain>",= 120,
120,
24,= 360,
360,
360,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 0,
0,
0,
= 10,
10,
10,
= 0,
0,
0,
= 10,
10,
10,
= 0,
0,
0,
= 10,
10,
10,
= 1,
1,
1,
= 1,
1,
1,
= 1,
1,
1,
= 0.0003,
0.0000,= 0.0000,
0.0000,= 0.0000,
0.0000,= 1,= 60.0,= 2,&dynamics
iso_temp
w_damping
diff_opt
km_optdiff_6th_opt
diff_6th_factor
base_temp
damp_opt
zdamp
dampcoef
khdif
kvdif
non_hydrostatic
moist_adv_opt
scalar_adv_opt
use_baseparam_fr_nml
/

= 0.,
= 1,
= 1,
= 4,
= 0,
= 0.12,= 290.
= 0,= 5000., 5000., 5000.,= 0.2,
0.2,
0.2
= 0,
0,
0,
= 0,
0,
0,
= .true., .true., .true.,= 0, 0, 0,= 0, 0, 0,= .true.

&bdy_control
spec_bdy_width
spec_zone
relax_zone
specifiednestedperturb_bdy

0.0000,0.0000,0.0000,

= 5,
= 1,
= 4,
= .true., .false.,.false.,= .false., .true., .true.,= 1,!boundary perturbations on (0=off)/82

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&grib2/&namelist_quilt
nio_tasks_per_group = 0,
nio_groups = 1,/

A.2.2 UMWM(main.nml)&DOMAIN= .F.
! Global (.T.) or regional (.F.)
isGlobalmm= 1195! Domain size in x
nm
= 1075! Domain size in yom
= 37
! Number of frequency binspm
= 36
! Number of directions
fmin= 0.0313! Lowest frequency bin [Hz]
fmax
= 2.0
! Highest frequency bin [Hz]
fprog
= 0.5
! Highest prognostic frequency bin [Hz]startTimeStr = ’2008-09-08_00:00:00’ ! Simulation start timestopTimeStr= ’2008-09-08_01:00:00’ ! Simulation end time
dtg
= 60
! Global (I/O) time step [s]restart= .f.
! Restart from file/
&PHYSICSg= 9.80665 ! Gravitational acceleration[m/s^2]
nu_air
= 1.56E-5 ! Kinematic viscosity of air[m^2/s]nu_water= 0.9E-6 ! Kinematic viscosity of water [m^2/s]
sfct= 0.07! Surface tension [N/m]
kappa
= 0.4
! Von Karman constantz= 10.
! Height of the input wind speed [m]gustiness= 0.0! Random wind gustiness factor (should be between 0 and 0.2)
dmin
= 20.
! Depth limiter [m]explim= 1.1! Exponent limiter (0.69 ~ 100% growth)
sin_fac= 0.11! Input factor from following winds
sin_diss1= 0.10! Damping factor from opposing winds
sin_diss2= 0.01! Damping factor from swell overrunning windsds_fac= 42.
! Breaking dissipation factor
sds_power= 2.5! Saturation spectrum power
mss_fac= 120.
! Mean-square-slope adjustment to Sds
snl_fac= 5.
! Wave energy downshifting factor
sdt_fac= 0.01! Dissipation due to turbulence factor
sbf_fac= 0.003! Bottom friction coefficient [m/s]sbp_fac= 0.003! Bottom percolation coefficient [m/s]/&GRID
gridFromFile = .T.
! Set to .T. if lon/lat fields are input from filedelx
= 12000 ! Grid spacing in x [m] if gridFromFile = .F.
dely= 12000 ! Grid spacing in y [m] if gridFromFile = .F.
topoFromFile = .T.
! Set to .T. to input bathymetry from filedpt
= 1000 ! Constant water depth [m] if topoFromFile = .F.
fillEstuaries = .F.
! Set to .T. to fill cells with 3 land neighbours
fillLakes= .F.
! Set to .T. to fill user chosen seas/lakes/&FORCING
winds= .F. ! Wind input from filecurrents= .F. ! Currents input from file
air_density= .F. ! Air density input from filewater_density = .F. ! Water density input from file/
&FORCING_CONSTANT
wspd0
= 25
! Wind speed [m/s]
wdir0
= 0.
! Wind direction [rad]uc0= 0.
! x-component ocean current [m/s]vc0= 0.
! y-component ocean current [m/s]rhoa0= 1.2 ! Air density [kg/m^3]
rhow0= 1030 !
Water density [kg/m^3]/&OUTPUT
outgrid= 1! Gridded output interval [hours]
outspec= 1! Spectrum output interval [hours]
outrst= 6! Restart output interval [hours]

83

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xpl
ypl
stokes/&STOKES
depths= 400 ! Grid cell in x for stdout (screen)= 500 ! Grid cell in y for stdout (screen)= .T. ! Output Stokes drift velocity fields

=

0

0.2

0.4

0.6

0.8 1 2 5 10 30 50 100

A.2.3 HYCOM(blkdat.input)
ERA-15 forcing; flx-s14w; LWcorr; precip+2mm; SSSrlx; FCT2 tsadvc.; 0-tracer.
Sigma0; GDEM3 init; KPP mixed layer; SeaWiFS mon KPAR; nested in ATLd0.08 2.6;
S-Z(15-11): dp00/f/x/i=3m/1.125/12m/1m; ds=1m/1.125/4m; src_2.2.34;
12345678901234567890123456789012345678901234567890123456789012345678901234567890
22’iversn’ = hycom version number x10
201’iexpt ’ = experiment number x10
1000
’idm
’ = longitudinal array size
1000
’jdm
’ = latitudinal array size
700
’itest ’ = grid point where detailed diagnostics are desired
700’jtest ’ = grid point where detailed diagnostics are desired
32’kdm’ = number of layers
32’nhybrd’ = number of hybrid levels (0=all isopycnal)
14’nsigma’ = number of sigma levels (nhybrd-nsigma z-levels)
3.0’dp00 ’ = deep
z-level spacing minimum thickness (m)450.0’dp00x ’ = deep
z-level spacing maximum thickness (m)1.18’dp00f ’ = deep
z-level spacing stretching factor (1.0=const.space)
0.5’ds00 ’ = shallow z-level spacing minimum thickness (m)75.0’ds00x ’ = shallow z-level spacing maximum thickness (m)1.18’ds00f ’ = shallow z-level spacing stretching factor (1.0=const.space)
1.0’dp00i ’ = deep iso-pycnal spacing minimum thickness (m)6.0’isotop’ = shallowest depth for isopycnal layers(m, <0 from file)35.0’saln0 ’ = initial salinity value (psu), only used for iniflg<21’locsig’ = locally-referenced pot. density for stability (0=F,1=T)
2’kapref’ = thermobaric ref. state (-1=input,0=none,1,2,3=constant)2’thflag’ = reference pressure flag (0=Sigma-0, 2=Sigma-2)
34.0’thbase’ = reference density (sigma units)0’vsigma’ = spacially varying isopycnal target densities (0=F,1=T)
28.10’sigma ’ = layer 1 isopycnal target density (sigma units)
28.90’sigma ’ = layer 2 isopycnal target density (sigma units)
29.70’sigma ’ = layer 3 isopycnal target density (sigma units)
30.50’sigma ’ = layer 4 isopycnal target density (sigma units)
30.95’sigma ’ = layer 5 isopycnal target density (sigma units)
31.50’sigma ’ = layer 6 isopycnal target density (sigma units)
32.05’sigma ’ = layer 7 isopycnal target density (sigma units)
32.60’sigma ’ = layer 8 isopycnal target density (sigma units)
33.15’sigma ’ = layer 9 isopycnal target density (sigma units)
33.70’sigma ’ = layer 10 isopycnal target density (sigma units)
34.25’sigma ’ = layer 11 isopycnal target density (sigma units)
34.75’sigma ’ = layer 12 isopycnal target density (sigma units)
35.15’sigma ’ = layer 13 isopycnal target density (sigma units)
35.50’sigma ’ = layer 14 isopycnal target density (sigma units)
35.80’sigma ’ = layer 15 isopycnal target density (sigma units)
36.04’sigma ’ = layer 16 isopycnal target density (sigma units)
36.20’sigma ’ = layer 17 isopycnal target density (sigma units)
36.38’sigma ’ = layer 18 isopycnal target density (sigma units)
36.52’sigma ’ = layer 19 isopycnal target density (sigma units)
36.62’sigma ’ = layer 20 isopycnal target density (sigma units)
36.70’sigma ’ = layer 21 isopycnal target density (sigma units)
36.77’sigma ’ = layer 22 isopycnal target density (sigma units)
36.83’sigma ’ = layer 23 isopycnal target density (sigma units)
36.89’sigma ’ = layer 24 isopycnal target density (sigma units)
36.97’sigma ’ = layer 25 isopycnal target density (sigma units)
37.02’sigma ’ = layer 26 isopycnal target density (sigma units)
37.06’sigma ’ = layer 27 isopycnal target density (sigma units)
37.10’sigma ’ = layer 28 isopycnal target density (sigma units)
37.17’sigma ’ = layer 29 isopycnal target density (sigma units)
37.30’sigma ’ = layer 30 isopycnal target density (sigma units)
37.42’sigma ’ = layer 31 isopycnal target density (sigma units)
37.48’sigma ’ = layer 32 isopycnal target density (sigma units)3’iniflg’ = initial state flag (0=levl, 1=zonl, 2=clim)
0’jerlv0’ = initial jerlov water type (1 to 5; 0 to use KPAR)
3’yrflag’ = days in year flag
(0=360, 1=366, 2=366J1, 3=actual)0’sshflg’ = diagnostic SSH flag (0=SSH,1=SSH&stericSSH)
0.0416667 ’dsurfq’ = number of days between model diagnostics at the surface
0.0416667 ’diagfq’ = number of days between model diagnostics

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0.0’proffq’ = number of days between model diagnostics at selected locs
0.0
’tilefq’ = number of days between model diagnostics on selected tiles
0.0’meanfq’ = number of days between model diagnostics (time averaged)
9999.0’rstrfq’ = number of days between model restart output
1.0’bnstfq’ = number of days between baro nesting archive input
1.0’nestfq’ = number of days between 3-d nesting archive input
0.125 ’cplifq’ = number of days (or time steps) between sea ice coupling
120.0’baclin’ = baroclinic time step (seconds), int. divisor of 86400
5.0’batrop’ = barotropic time step (seconds), int. div. of baclin/20’incflg’ = incremental update flag (0=no, 1=yes, 2=full-velocity)
100’incstp’ = no. timesteps for full update (1=direct insertion)
1’incupf’ = number of days of incremental updating input
0.125 ’wbaro ’ = barotropic time smoothing weight1’btrlfr’ = leapfrog barotropic time step (0=F,1=T)
0’btrmas’ = barotropic is mass conserving (0=F,1=T)
8.0’hybrlx’ = HYBGEN: inverse relaxation coefficient (time steps)
0.01’hybiso’ = HYBGEN: Use PCM if layer is within hybiso of target density
3’hybmap’ = hybrid
remapper flag (0=PCM, 1=PLM, 2=PPM, 3=WENO-like)0’hybflg’ = hybrid
generator flag (0=T&S, 1=th&S, 2=th&T)0’advflg’ = thermal advection flag (0=T&S, 1=th&S, 2=th&T)
2’advtyp’ = scalaradvection type (0=PCM,1=MPDATA,2=FCT2,4=FCT4)2’momtyp’ = momentum advection type (2=2nd order, 4=4th order)-1.0’slip ’ = +1 for free-slip, -1 for non-slip boundary conditions
0.05’visco2’ = deformation-dependent Laplacian viscosity factor
0.0’visco4’ = deformation-dependent biharmonic viscosity factor
0.0’facdf4’ =speed-dependent biharmonic viscosity factor
0.003 ’veldf2’ = diffusion velocity (m/s) for Laplacian momentum dissip.
0.02’veldf4’ = diffusion velocity (m/s) for biharmonic momentum dissip.
0.0’thkdf2’ = diffusion velocity (m/s) for Laplacian thickness diffus.
0.01’thkdf4’ = diffusion velocity (m/s) for biharmonic thickness diffus.
0.005 ’temdf2’ = diffusion velocity (m/s) for Laplacian temp/saln diffus.
1.0’temdfc’ = temp diffusion conservation (0.0,1.0 all dens,temp resp.)
0.0’vertmx’ = diffusion velocity (m/s) for momentum at MICOM M.L.base
0.05’cbar ’ = rms flow speed(m/s) for linear bottom friction
2.2e-3 ’cb’ = coefficient of quadratic bottom friction
0.0’drglim’ = limiter for explicit friction (1.0 none, 0.0 implicit)
0.0’drgscl’ = scale factor for tidal drag(0.0 for no tidal drag)
500.0’thkdrg’ = thickness of bottom boundary layer for tidal drag (m)10.0’thkbot’ = thickness of bottom boundary layer (m)0.02’sigjmp’ = minimum density jump across interfaces (kg/m**3)
0.3’tmljmp’ = equivalent temperature jump across mixed-layer (degC)
15.0’thkmls’ = reference mixed-layer thickness for SSS relaxation (m)0.0’thkmlt’ = reference mixed-layer thickness for SST relaxation (m)5.0’thkriv’ = nominal thickness of river inflow (m)20.0’thkfrz’ = maximum thickness of near-surface freezing zone (m)0’iceflg’ = sea ice model flag (0=none,1=energy loan,2=coupled/esmf)
0.0’tfrz_0’ = ENLN: ice melting point (degC) at S=0psu-0.054 ’tfrz_s’ = ENLN: gradient of ice melting point (degC/psu)
0.0’ticegr’ = ENLN: temp. grad. inside ice (deg/m); =0 use surtmp
0.5’hicemn’ = ENLN: minimum ice thickness (m)10.0’hicemx’ = ENLN: maximum ice thickness (m)0’ntracr’ = number of tracers (0=none,negative to initialize)0’trcflg’ = tracer flags(one digit per tr, most sig. replicated)
240’tsofrq’ = number of time steps between anti-drift offset calcs
0.0’tofset’ = temperature anti-drift offset (degC/century)
0.0’sofset’ = salnity
anti-drift offset (psu/century)
1’mlflag’ = mixed layer flag (0=none,1=KPP,2-3=KT,4=PWP,5=MY,6=GISS)
1’pensol’ = KT:
activate penetrating solar rad.
(0=F,1=T)
999.0’dtrate’ = KT:
maximum permitted m.l. detrainment rate (m/day)
19.2’thkmin’ = KT/PWP: minimum mixed-layer thickness (m)1’dypflg’ = KT/PWP: diapycnal mixing flag (0=none, 1=KPP, 2=explicit)
240’mixfrq’ = KT/PWP: number of time steps between diapycnal mix calcs
1.e-7 ’diapyc’ = KT/PWP: diapycnal diffusivity x buoyancy freq. (m**2/s**2)
0.25’rigr ’ = PWP:
critical gradient richardson number
0.65’ribc ’ = PWP:
critical bulk
richardson number
0.7’rinfty’ = KPP:
maximum gradient richardson number (shear inst.)
0.25’ricr ’ = KPP:
critical bulk
richardson number
0.0’bldmin’ = KPP:
minimum surface boundary layer thickness (m)1200.0’bldmax’ = K-PROF: maximum surface boundary layer thickness (m)0.7’cekman’ = KPP/KT: scale factor for Ekman depth
1.0’cmonob’ = KPP:
scale factor for Monin-Obukov depth0’bblkpp’ = KPP:
activate bottom boundary layer(0=F,1=T)
1’shinst’ = KPP:
activate shear instability mixing (0=F,1=T)
1’dbdiff’ = KPP:
activate double diffusion mixing (0=F,1=T)
1’nonloc’ = KPP:
activate nonlocal b. layer mixing (0=F,1=T)0’botdiw’ = K-PROF: activate bot.enhan.int.wav mixing (0=F,1=T)85

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1’difout’ = K-PROF: output visc/diff coffs in archive (0=F,1=T)0’difsmo’ = K-PROF: number of layers with horiz smooth diff coeffs
50.0e-4 ’difm0 ’ = KPP:
max viscosity
due to shear instability (m**2/s)
50.0e-4 ’difs0 ’ = KPP:
max diffusivity due to shear instability (m**2/s)
0.3e-4 ’difmiw’ = KPP:
background/internal wave viscosity(m**2/s)
0.1e-4 ’difsiw’ = KPP:
background/internal wave diffusivity(m**2/s)
10.0e-4 ’dsfmax’ = KPP:
salt fingering diffusivity factor(m**2/s)
1.9’rrho0 ’ = KPP:
salt fingering rp=(alpha*delT)/(beta*delS)
98.96
’cs
’ = KPP:value for nonlocal flux term
10.0
’cstar ’ = KPP:
value for nonlocal flux term
0.0’cv
’ = KPP:buoyancy frequency ratio (0.0 to use a fn. of N)
5.0’c11’ = KPP:value for turb velocity scale2’hblflg’ = KPP:
b. layer interp. flag (0=const.,1=linear,2=quad.)2’niter ’ = KPP:
iterations for semi-implicit soln. (2 recomended)0’fltflg’ = FLOATS: synthetic float flag (0=no; 1=yes)
4’nfladv’ = FLOATS: advect every nfladv bacl. time steps (even, >=4)1’nflsam’ = FLOATS: output (0=every nfladv steps; >0=no. of days)
0’intpfl’ = FLOATS: horiz. interp. (0=2nd order+n.n.; 1=n.n. only)0’iturbv’ = FLOATS: add horiz. turb. advection velocity (0=no; 1=yes)
1’ismpfl’ = FLOATS: sample water properties at float (0=no; 1=yes)
4.63e-6’tbvar ’ = FLOATS: horizontal turb. vel. variance scale (m**2/s**2)
0.4’tdecri’ = FLOATS: inverse decorrelation time scale (1/day)2’lbflag’ = lateral barotropic bndy flag (0=none, 1=port, 2=input)2’tidflg’ = TIDES: tidal forcing flag
(0=none,1=open-bdy,2=bdy&body)
11111111 ’tidcon’ = TIDES: 1 digit per (Q1K2P1N2O1K1S2M2), 0=off,1=on
0.06’tidsal’ = TIDES: scalar self attraction and loading factor (<0: file)1’tidgen’ = TIDES: generic time (0=F,1=T)
1.0’tidrmp’ = TIDES:
ramp time (days)
0.0’tid_t0’ = TIDES: origin for ramp time (model day)12
’clmflg’ = climatology frequency flag
(6=bimonthly, 12=monthly)1’wndflg’ = wind stress input flag (0=none,1=u/v-grid,2,3=p-grid)2’ustflg’ = ustar forcing
flag(3=input,1,2=wndspd,4=stress)3’flxflg’ = thermal forcing
flag (0=none,3=net-flux,1,2,4=sst-based)0’empflg’ = E-P
forcing
flag (0=none,3=net_E-P, 1,2,4=sst-bas_E)
0’dswflg’ = diurnal shortwave flag (0=none,1=daily to diurnal corr.)
0’sssflg’ = SSS relaxation flag (0=none,1=clim,-1=clim&rmx)
0’lwflag’ = longwave (SST) flag (0=none,1=clim,2=atmos)
0’sstflg’ = SST relaxation flag (0=none,1=clim,2=atmos,3=observed)0’icmflg’ = ice mask
flag (0=none,1=clim,2=atmos,3=obs/coupled)0’flxoff’ = net flux offset flag
(0=F,1=T)0’flxsmo’ = smooth surface fluxes(0=F,1=T)0’relax ’ = activate lateral boundary nudging(0=F,1=T)0’trcrlx’ = activate lat. bound. tracer nudging (0=F,1=T)0’priver’ = rivers as a precipitation bogas(0=F,1=T)0’epmass’ = treat evap-precip as a mass exchange (0=F,1=T)86

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Appendix B
List of UMCM output
B.1 List of WRF output
dimensions:// (1 currently
Time = UNLIMITED;
DateStrLen = 19;
west_east = 399;
south_north = 359;
bottom_top = 35;
bottom_top_stag = 36;
soil_layers_stag = 5;
west_east_stag = 400;
south_north_stag = 360;
variables:char Times(Time=1, DateStrLen=19);
float XLAT(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LATITUDE, SOUTH IS NEGATIVE";:units = "degree_north";:stagger = "";float XLONG(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LONGITUDE, WEST IS NEGATIVE";:units = "degree_east";:stagger = "";float LU_INDEX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LAND USE CATEGORY";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float ZNU(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "eta values on half (mass) levels";:units = "";:stagger = "";float ZNW(Time=1, bottom_top_stag=36);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "eta values on full (w) levels";:units = "";:stagger = "Z";float ZS(Time=1, soil_layers_stag=5);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "DEPTHS OF CENTERS OF SOIL LAYERS";:units = "m";:stagger = "Z";float DZS(Time=1, soil_layers_stag=5);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "THICKNESSES OF SOIL LAYERS";:units = "m";:stagger = "Z";float VAR_SSO(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "variance of subgrid-scale orography";:units = "m2";87This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

:stagger = "";:coordinates = "XLONG XLAT";
float LAP_HGT(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Laplacian of orography";:units = "m";:stagger = "";:coordinates = "XLONG XLAT";
float U(Time=1, bottom_top=35, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "x-wind component";:units = "m s-1";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float V(Time=1, bottom_top=35, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "y-wind component";:units = "m s-1";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float W(Time=1, bottom_top_stag=36, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "z-wind component";:units = "m s-1";:stagger = "Z";:coordinates = "XLONG XLAT";
float PH(Time=1, bottom_top_stag=36, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "perturbation geopotential";:units = "m2 s-2";:stagger = "Z";:coordinates = "XLONG XLAT";
float PHB(Time=1, bottom_top_stag=36, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "base-state geopotential";:units = "m2 s-2";:stagger = "Z";:coordinates = "XLONG XLAT";
float T(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "perturbation potential temperature (theta-t0)";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";
float HFX_FORCE(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "SCM ideal surface sensible heat flux";:units = "W m-2";:stagger = "";float LH_FORCE(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "SCM ideal surface latent heat flux";:units = "W m-2";:stagger = "";float TSK_FORCE(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";88This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

:description = "SCM ideal surface skin temperature";:units = "W m-2";:stagger = "";float HFX_FORCE_TEND(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "SCM ideal surface sensible heat flux tendency";:units = "W m-2 s-1";:stagger = "";float LH_FORCE_TEND(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "SCM ideal surface latent heat flux tendency";:units = "W m-2 s-1";:stagger = "";float TSK_FORCE_TEND(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "SCM ideal surface skin temperature tendency";:units = "W m-2 s-1";:stagger = "";float MU(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "perturbation dry air mass in column";:units = "Pa";:stagger = "";:coordinates = "XLONG XLAT";
float MUB(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "base state dry air mass in column";:units = "Pa";:stagger = "";:coordinates = "XLONG XLAT";
float NEST_POS(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "-";
:units = "-";
:stagger = "";:coordinates = "XLONG XLAT";
float P(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "perturbation pressure";:units = "Pa";:stagger = "";:coordinates = "XLONG XLAT";
float PB(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "BASE STATE PRESSURE";:units = "Pa";:stagger = "";:coordinates = "XLONG XLAT";
float FNM(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "upper weight for vertical stretching";:units = "";:stagger = "";float FNP(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "lower weight for vertical stretching";

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:units = "";:stagger = "";float RDNW(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "inverse d(eta) values between full (w) levels";:units = "";:stagger = "";float RDN(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "inverse d(eta) values between half (mass) levels";:units = "";:stagger = "";float DNW(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "d(eta) values between full (w) levels";:units = "";:stagger = "";float DN(Time=1, bottom_top=35);:FieldType = 104; // int:MemoryOrder = "Z ";:description = "d(eta) values between half (mass) levels";:units = "";:stagger = "";float CFN(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "extrapolation constant";:units = "";:stagger = "";float CFN1(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "extrapolation constant";:units = "";:stagger = "";float P_HYD(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "hydrostatic pressure";:units = "Pa";:stagger = "";:coordinates = "XLONG XLAT";
float Q2(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "QV at 2 M";:units = "kg kg-1";:stagger = "";:coordinates = "XLONG XLAT";
float T2(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TEMP at 2 M";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";
float TH2(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "POT TEMP at 2 M";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";

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float PSFC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SFC PRESSURE";:units = "Pa";:stagger = "";:coordinates = "XLONG XLAT";
float U10(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "U at 10 M";:units = "m s-1";:stagger = "";:coordinates = "XLONG XLAT";
float V10(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "V at 10 M";:units = "m s-1";:stagger = "";:coordinates = "XLONG XLAT";
float RDX(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "INVERSE X GRID LENGTH";:units = "";:stagger = "";float RDY(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "INVERSE Y GRID LENGTH";:units = "";:stagger = "";float RESM(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "TIME WEIGHT CONSTANT FOR SMALL STEPS";:units = "";:stagger = "";float ZETATOP(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "ZETA AT MODEL TOP";:units = "";:stagger = "";float CF1(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "2nd order extrapolation constant";:units = "";:stagger = "";float CF2(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "2nd order extrapolation constant";:units = "";:stagger = "";float CF3(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "2nd order extrapolation constant";:units = "";:stagger = "";int ITIMESTEP(Time=1);:FieldType = 106; // int91This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

:MemoryOrder = "0 ";:description = "";:units = "";:stagger = "";float XTIME(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "minutes since simulation start";:units = "";:stagger = "";float QVAPOR(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "Water vapor mixing ratio";:units = "kg kg-1";:stagger = "";:coordinates = "XLONG XLAT";
float QCLOUD(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "Cloud water mixing ratio";:units = "kg kg-1";:stagger = "";:coordinates = "XLONG XLAT";
float QRAIN(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "Rain water mixing ratio";:units = "kg kg-1";:stagger = "";:coordinates = "XLONG XLAT";
float QICE(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "Ice mixing ratio";:units = "kg kg-1";:stagger = "";:coordinates = "XLONG XLAT";
float QSNOW(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "Snow mixing ratio";:units = "kg kg-1";:stagger = "";:coordinates = "XLONG XLAT";
float SHDMAX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ANNUAL MAX VEG FRACTION";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float SHDMIN(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ANNUAL MIN VEG FRACTION";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float SNOALB(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ANNUAL MAX SNOW ALBEDO IN FRACTION";:units = "";:stagger = "";:coordinates = "XLONG XLAT";

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float TSLB(Time=1, soil_layers_stag=5, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "SOIL TEMPERATURE";:units = "K";:stagger = "Z";:coordinates = "XLONG XLAT";
float SMOIS(Time=1, soil_layers_stag=5, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "SOIL MOISTURE";:units = "m3 m-3";:stagger = "Z";:coordinates = "XLONG XLAT";
float SH2O(Time=1, soil_layers_stag=5, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "SOIL LIQUID WATER";:units = "m3 m-3";:stagger = "Z";:coordinates = "XLONG XLAT";
float SMCREL(Time=1, soil_layers_stag=5, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "RELATIVE SOIL MOISTURE";:units = "";:stagger = "Z";:coordinates = "XLONG XLAT";
float SEAICE(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SEA ICE FLAG";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float XICEM(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SEA ICE FLAG (PREVIOUS STEP)";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float SFROFF(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SURFACE RUNOFF";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float UDROFF(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "UNDERGROUND RUNOFF";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
int IVGTYP(Time=1, south_north=359, west_east=399);:FieldType = 106; // int:MemoryOrder = "XY ";:description = "DOMINANT VEGETATION CATEGORY";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
int ISLTYP(Time=1, south_north=359, west_east=399);:FieldType = 106; // int:MemoryOrder = "XY ";:description = "DOMINANT SOIL CATEGORY";

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:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float VEGFRA(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "VEGETATION FRACTION";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float GRDFLX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "GROUND HEAT FLUX";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float ACGRDFLX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED GROUND HEAT FLUX";:units = "J m-2";:stagger = "";:coordinates = "XLONG XLAT";
float ACSNOM(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED MELTED SNOW";:units = "kg m-2";:stagger = "";:coordinates = "XLONG XLAT";
float SNOW(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SNOW WATER EQUIVALENT";:units = "kg m-2";:stagger = "";:coordinates = "XLONG XLAT";
float SNOWH(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "PHYSICAL SNOW DEPTH";:units = "m";:stagger = "";:coordinates = "XLONG XLAT";
float CANWAT(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "CANOPY WATER";:units = "kg m-2";:stagger = "";:coordinates = "XLONG XLAT";
float SSTSK(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SKIN SEA SURFACE TEMPERATURE";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";
float LAI(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Leaf area index";:units = "area/area";:stagger = "";:coordinates = "XLONG XLAT";

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float VAR(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "OROGRAPHIC VARIANCE";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float MAPFAC_M(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on mass grid";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float MAPFAC_U(Time=1, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on u-grid";:units = "";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float MAPFAC_V(Time=1, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on v-grid";:units = "";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float MAPFAC_MX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on mass grid, x direction";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float MAPFAC_MY(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on mass grid, y direction";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float MAPFAC_UX(Time=1, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on u-grid, x direction";:units = "";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float MAPFAC_UY(Time=1, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on u-grid, y direction";:units = "";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float MAPFAC_VX(Time=1, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on v-grid, x direction";:units = "";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float MF_VX_INV(Time=1, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Inverse map scale factor on v-grid, x direction";95

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:units = "";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float MAPFAC_VY(Time=1, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Map scale factor on v-grid, y direction";:units = "";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float F(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Coriolis sine latitude term";:units = "s-1";:stagger = "";:coordinates = "XLONG XLAT";
float E(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Coriolis cosine latitude term";:units = "s-1";:stagger = "";:coordinates = "XLONG XLAT";
float SINALPHA(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Local sine of map rotation";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float COSALPHA(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Local cosine of map rotation";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float HGT(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "Terrain Height";:units = "m";:stagger = "";:coordinates = "XLONG XLAT";
float TAUX_ESMF(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "WIND STRESS X-COMPONENT FROM UMCM";:units = "N/m^2";:stagger = "";:coordinates = "XLONG XLAT";
float TAUY_ESMF(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "WIND STRESS Y-COMPONENT FROM UMCM";:units = "N/m^2";:stagger = "";:coordinates = "XLONG XLAT";
float TSK(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SURFACE SKIN TEMPERATURE";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";

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float P_TOP(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "PRESSURE TOP OF THE MODEL";:units = "Pa";:stagger = "";float T00(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "BASE STATE TEMPERATURE";:units = "K";:stagger = "";float P00(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "BASE STATE PRESURE";:units = "Pa";:stagger = "";float TLP(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "BASE STATE LAPSE RATE";:units = "";:stagger = "";float TISO(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "TEMP AT WHICH THE BASE T TURNS CONST";:units = "K";:stagger = "";float MAX_MSTFX(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "Max map factor in domain";:units = "";:stagger = "";float MAX_MSTFY(Time=1);:FieldType = 104; // int:MemoryOrder = "0 ";:description = "Max map factor in domain";:units = "";:stagger = "";float RAINC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED TOTAL CUMULUS PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float RAINSH(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED SHALLOW CUMULUS PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float RAINNC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED TOTAL GRID SCALE PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float PRATEC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";97

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:description = "PRECIP RATE FROM CUMULUS SCHEME";:units = "mm s-1";:stagger = "";:coordinates = "XLONG XLAT";
float PRATESH(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "PRECIP RATE FROM SHALLOW CUMULUS SCHEME";:units = "mm s-1";:stagger = "";:coordinates = "XLONG XLAT";
float RAINCV(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TIME-STEP CUMULUS PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float RAINSHV(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TIME-STEP SHALLOW CUMULUS PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float RAINNCV(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TIME-STEP NONCONVECTIVE PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float RAINBL(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "PBL TIME-STEP TOTAL PRECIPITATION";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float SNOWNC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED TOTAL GRID SCALE SNOW AND ICE";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float GRAUPELNC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED TOTAL GRID SCALE GRAUPEL";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float HAILNC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED TOTAL GRID SCALE HAIL";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float SNOWNCV(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TIME-STEP NONCONVECTIVE SNOW AND ICE";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";

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float GRAUPELNCV(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TIME-STEP NONCONVECTIVE GRAUPEL";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float HAILNCV(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TIME-STEP NONCONVECTIVE HAIL";:units = "mm";:stagger = "";:coordinates = "XLONG XLAT";
float REFL_10CM(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "Radar reflectivity (lamda = 10 cm)";:units = "dBZ";:stagger = "";:coordinates = "XLONG XLAT";
float CLDFRA(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "CLOUD FRACTION";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float SWDOWN(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "DOWNWARD SHORT WAVE FLUX AT GROUND SURFACE";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float GLW(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "DOWNWARD LONG WAVE FLUX AT GROUND SURFACE";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float SWNORM(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "NORMAL SHORT WAVE FLUX AT GROUND SURFACE (SLOPE-DEPENDENT)";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float OLR(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "TOA OUTGOING LONG WAVE";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float XLAT_U(Time=1, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LATITUDE, SOUTH IS NEGATIVE";:units = "degree_north";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float XLONG_U(Time=1, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XY ";99

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:description = "LONGITUDE, WEST IS NEGATIVE";:units = "degree_east";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float XLAT_V(Time=1, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LATITUDE, SOUTH IS NEGATIVE";:units = "degree_north";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float XLONG_V(Time=1, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LONGITUDE, WEST IS NEGATIVE";:units = "degree_east";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float ALBEDO(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ALBEDO";:units = "-";
:stagger = "";:coordinates = "XLONG XLAT";
float CLAT(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "COMPUTATIONAL GRID LATITUDE, SOUTH IS NEGATIVE";:units = "degree_north";:stagger = "";:coordinates = "XLONG XLAT";
float ALBBCK(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "BACKGROUND ALBEDO";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float EMISS(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SURFACE EMISSIVITY";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float NOAHRES(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "RESIDUAL OF THE NOAH SURFACE ENERGY BUDGET";:units = "W m{-2}";:stagger = "";:coordinates = "XLONG XLAT";
float TMN(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SOIL TEMPERATURE AT LOWER BOUNDARY";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";
float XLAND(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LAND MASK (1 FOR LAND, 2 FOR WATER)";:units = "";:stagger = "";:coordinates = "XLONG XLAT";

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float UST(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "U* IN SIMILARITY THEORY";:units = "m s-1";:stagger = "";:coordinates = "XLONG XLAT";
float PBLH(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "PBL HEIGHT";:units = "m";:stagger = "";:coordinates = "XLONG XLAT";
float HFX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "UPWARD HEAT FLUX AT THE SURFACE";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float QFX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "UPWARD MOISTURE FLUX AT THE SURFACE";:units = "kg m-2 s-1";:stagger = "";:coordinates = "XLONG XLAT";
float LH(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LATENT HEAT FLUX AT THE SURFACE";:units = "W m-2";:stagger = "";:coordinates = "XLONG XLAT";
float ACHFX(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED UPWARD HEAT FLUX AT THE SURFACE";:units = "J m-2";:stagger = "";:coordinates = "XLONG XLAT";
float ACLHF(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "ACCUMULATED UPWARD LATENT HEAT FLUX AT THE SURFACE";:units = "J m-2";:stagger = "";:coordinates = "XLONG XLAT";
float SNOWC(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "FLAG INDICATING SNOW COVERAGE (1 FOR SNOW COVER)";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float SR(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "fraction of frozen precipitation";:units = "-";
:stagger = "";:coordinates = "XLONG XLAT";
int SAVE_TOPO_FROM_REAL(Time=1);:FieldType = 106; // int:MemoryOrder = "0 ";101This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

:description = "1=original topo from real/0=topo modified by WRF";:units = "flag";:stagger = "";float VERTSTRUCC(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "vertical structure for stoch. forcing";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float VERTSTRUCS(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "vertical structure for stoch. forcing";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float RU_TENDF_STOCH(Time=1, bottom_top=35, south_north=359, west_east_stag=400);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "stochastic forcing, U";:units = "m/s";:stagger = "X";:coordinates = "XLONG_U XLAT_U";
float RV_TENDF_STOCH(Time=1, bottom_top=35, south_north_stag=360, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "stochastic forcing, V";:units = "m/s";:stagger = "Y";:coordinates = "XLONG_V XLAT_V";
float RT_TENDF_STOCH(Time=1, bottom_top=35, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XYZ";:description = "stochastic forcing, T";:units = "K/s";:stagger = "";:coordinates = "XLONG XLAT";
int SEED1(Time=1);:FieldType = 106; // int:MemoryOrder = "0 ";:description = "RANDOM SEED NUMBER 1";:units = "";:stagger = "";int SEED2(Time=1);:FieldType = 106; // int:MemoryOrder = "0 ";:description = "RANDOM SEED NUMBER 2";:units = "";:stagger = "";float LANDMASK(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "LAND MASK (1 FOR LAND, 0 FOR WATER)";:units = "";:stagger = "";:coordinates = "XLONG XLAT";
float SST(Time=1, south_north=359, west_east=399);:FieldType = 104; // int:MemoryOrder = "XY ";:description = "SEA SURFACE TEMPERATURE";:units = "K";:stagger = "";:coordinates = "XLONG XLAT";

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B.2 List of UMWM output
dimensions:x = 1195;
y = 1075;
f = 37;th = 36;z = 19;variables:
float z(z=19);:description = "Depth";:units = "m";float u_stokes(z=19, y=1075, x=1195);:description = "Stokes drift x-component";:units = "m/s";
float v_stokes(z=19, y=1075, x=1195);:description = "Stokes drift y-component";:units = "m/s";
float frequency(f=37);:description = "Frequency";:units = "Hz";float theta(th=36);:description = "Directions";:units = "rad";float lon(y=1075, x=1195);:description = "Longitude";:units = "degrees East";
float lat(y=1075, x=1195);:description = "Latitude";:units = "degrees North";
int seamask(y=1075, x=1195);:description = "Seamask";:units = "non-dimensional";
float depth(y=1075, x=1195);:description = "Ocean depth";:units = "m";float wspd(y=1075, x=1195);:description = "Wind speed";:units = "m/s";
float wdir(y=1075, x=1195);:description = "Water density";:units = "kg/m^3";
float uc(y=1075, x=1195);:description = "Ocean current y-component";:units = "m/s";
float vc(y=1075, x=1195);
float rhoa(y=1075, x=1195);
float rhow(y=1075, x=1195);
float momx(y=1075, x=1195);:description = "Momentum, x-component";:units = "kgm/s";
float momy(y=1075, x=1195);:description = "Momentum, y-component";:units = "kgm/s";
float cgmxx(y=1075, x=1195);:description = "Cg*Momentum, xx-component";:units = "kgm^2/s^2";103This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

float cgmxy(y=1075, x=1195);:description = "Cg*Momentum, xy-component";:units = "kgm^2/s^2";
float cgmyy(y=1075, x=1195);:description = "Cg*Momentum, yy-component";:units = "kgm^2/s^2";
float taux_form(y=1075, x=1195);:description = "Form drag, x-component";:units = "N/m^2";
float tauy_form(y=1075, x=1195);:description = "Form drag, y-component";:units = "N/m^2";
float taux_form_1(y=1075, x=1195);:description = "Form drag, part 1, x-component";:units = "N/m^2";
float tauy_form_1(y=1075, x=1195);:description = "Form drag, part 1, y-component";:units = "N/m^2";
float taux_form_2(y=1075, x=1195);:description = "Form drag, part 2, x-component";:units = "N/m^2";
float tauy_form_2(y=1075, x=1195);:description = "Form drag, part 2, y-component";:units = "N/m^2";
float taux_form_3(y=1075, x=1195);:description = "Form drag, part 3, x-component";:units = "N/m^2";
float tauy_form_3(y=1075, x=1195);:description = "Form drag, part 3, y-component";:units = "N/m^2";
float taux_skin(y=1075, x=1195);:description = "Skin drag, x-component";:units = "N/m^2";
float tauy_skin(y=1075, x=1195);:description = "Skin drag, y-component";:units = "N/m^2";
float taux_ocn(y=1075, x=1195);:description = "Momentum flux from breaking waves to ocean top, x-component";:units = "N/m^2";
float tauy_ocn(y=1075, x=1195);:description = "Momentum flux from breaking waves to ocean top, y-component";:units = "N/m^2";
float taux_bot(y=1075, x=1195);:description = "Momentum flux from waves to ocean bottom, x-component";:units = "N/m^2";
float tauy_bot(y=1075, x=1195);:description = "Momentum flux from waves to ocean bottom, y-component";:units = "N/m^2";
float taux_snl(y=1075, x=1195);:description = "Momentum flux due to Snl, x-component";:units = "N/m^2";
float tauy_snl(y=1075, x=1195);:description = "Momentum flux due to Snl, y-component";:units = "N/m^2";
float tailatmx(y=1075, x=1195);:description = "Atmosphere tail stress part, x-component";:units = "N/m^2";

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float tailatmy(y=1075, x=1195);:description = "Atmosphere tail stress part, y-component";:units = "N/m^2";
float tailocnx(y=1075, x=1195);:description = "Ocean tail stress part, x-component";:units = "N/m^2";
float tailocny(y=1075, x=1195);:description = "Ocean tail stress part, y-component";:units = "N/m^2";
float cd(y=1075, x=1195);:description = "Drag coefficient of air";:units = "non-dimensional";
float ust(y=1075, x=1195);:description = "Friction velocity of air";:units = "m/s";
float swh(y=1075, x=1195);:description = "Significant wave height";:units = "m";float mss(y=1075, x=1195);:description = "Mean-squared slope";:units = "non-dimensional";
float mwp(y=1075, x=1195);:description = "Mean wave period";:units = "s";float mwl(y=1075, x=1195);:description = "Mean wavelength";:units = "m";float mwd(y=1075, x=1195);:description = "Mean wave direction";:units = "rad";float dwp(y=1075, x=1195);:description = "Dominant wave period";:units = "s";float dwl(y=1075, x=1195);:description = "Dominant wavelength";:units = "m";float dwd(y=1075, x=1195);:description = "Dominant wave direction";:units = "rad";float dcp0(y=1075, x=1195);:description = "Dominant phase speed, intrinsic";:units = "m/s";
float dcg0(y=1075, x=1195);:description = "Dominant group speed, intrinsic";:units = "m/s";
float dcp(y=1075, x=1195);:description = "Dominant phase speed";:units = "m/s";
float dcg(y=1075, x=1195);:description = "Dominant group speed";:units = "m/s";}

B.3 List of HYCOM output
dimensions:
MT = UNLIMITED;// (1 currently

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Latitude = 1000;
Longitude = 1000;
Depth = 40;
variables:
double MT(MT=1);:long_name = "time";:units = "days since 1900-12-31 00:00:00";:calendar = "gregorian";:axis = "T";
double Date(MT=1);:long_name = "date";:units = "day as %Y%m%d.%f";:C_format = "%13.4f";:FORTRAN_format = "(f13.4)";
float Depth(Depth=40);:standard_name = "depth";:units = "m";:positive = "down";:axis = "Z";float Latitude(Latitude=1000);:standard_name = "latitude";:units = "degrees_north";:axis = "Y";float Longitude(Longitude=1000);:standard_name = "longitude";:units = "degrees_east";:point_spacing = "even";:axis = "X";float u(MT=1, Depth=40, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "eastward_sea_water_velocity";:units = "m/s";:_FillValue = 1.2676506E30f; // float:valid_range = -1.975024f, 1.876598f; // float:long_name = " u-veloc. [20.1H]";
float v(MT=1, Depth=40, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "northward_sea_water_velocity";:units = "m/s";:_FillValue = 1.2676506E30f; // float:valid_range = -1.3474879f, 2.665912f; // float:long_name = " v-veloc. [20.1H]";
float w_velocity(MT=1, Depth=40, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "upward_sea_water_velocity";:units = "m/s";:_FillValue = 1.2676506E30f; // float:valid_range = -0.037467636f, 0.017186552f; // float:long_name = " w-veloc. [20.1H]";
float water_temp(MT=1, Depth=40, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "sea_water_temperature";:units = "degC";:_FillValue = 1.2676506E30f; // float:valid_range = 2.6080048f, 30.902374f; // float:long_name = " temp [20.1H]";
float salinity(MT=1, Depth=40, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "sea_water_salinity";:units = "psu";:_FillValue = 1.2676506E30f; // float:valid_range = 12.106584f, 38.24341f; // float:long_name = " salinity [20.1H]";
float pot_density(MT=1, Depth=40, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "sea_water_potential_density";

106

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:units = "sigma";:_FillValue = 1.2676506E30f; // float:valid_range = 13.050988f, 36.986603f; // float:long_name = " p.dens [20.1H]";
float bathymetry(MT=1, Latitude=1000, Longitude=1000);:coordinates = "Date";:units = "m";:_FillValue = 1.2676506E30f; // float:valid_range = 9.999999f, 8477.0f; // float:long_name = " bathymetry[20.1H]";float ilt(MT=1, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "ocean_mixed_layer_thickness";:units = "m";:_FillValue = 1.2676506E30f; // float:valid_range = 1.0797554f, 1146.0001f; // float:long_name = " ILT (0.50 degC)[20.1H]";float mlt(MT=1, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "ocean_mixed_layer_thickness";:units = "m";:_FillValue = 1.2676506E30f; // float:valid_range = 0.715755f, 1146.0001f; // float:long_name = " MLT (0.50 kg/m3) [20.1H]";
float ssh(MT=1, Latitude=1000, Longitude=1000);:coordinates = "Date";:standard_name = "sea_surface_elevation";:units = "m";:_FillValue = 1.2676506E30f; // float:valid_range = -0.95362926f, 0.84672445f; // float:long_name = " sea surf. height [20.1H]";

107

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Appendix C
Fourier coefficients for wave kinematics
C.1 Wave Surface Elevation
C.1.1 First-Order(1)

Xim = aim · exp(−ιεim ) · exp(−ι (~kim ·~x))where ~x = (x, y) is a point on the horizontal x-y plane; ι =

(1)



√
−1 and ~kim = |~ki | cos θm , |~ki | sin θm ; ωi is the angular frequency; ~ki is the wave number which isrelated to the frequency, ωi , through the linear dispersion relation, ωi2 = g|~ki |tanh(|~ki |h) (where h is the water depth).

C.1.2 Second-Order(2)±

Xi jmn = aim a jn · exp(−sgn(ωi±j )ιεi±jmn ) · Ki±jmn· exp(−sgn(ωi±j )ι (~kim ·~x ±~k jn ·~x))where,

εi±jmn = εim ± ε jn and ωi±j = ωi ± ω j 10sgn(x) =
 −1

x>0
x=0
x<0

(2)

(3)

(4)

C.2 Wave Particle Velocity
C.2.1 First-Order(1)

Ux,im = aim · exp(−ιεim )ωi(1)

Uy,im = aim · exp(−ιεim )ωi(1)

cosh[|~ki |(h + z)]
cos θm · exp(−ι (~kim ·~x))sinh(|~ki |h)(5)cosh[|~ki |(h + z)]
sin θm · exp(−ι (~kim ·~x))sinh(|~ki |h)(6)sinh[|~ki |(h + z)]· exp(−ι (~kim ·~x))sinh(|~ki |h)(7)

Uz,im = (ι )aim · exp(−ιεim )ωi

C.2.2 Second-Order
(2±)

~
~
Ux,i jmn = aim a jn · exp(−sgn(ωi±j )ιεi±jmn ) · B±i jmn · (|ki | cos θm ± |k j | cos θn )· exp(−sgn(ωi±j )ι (~kim ·~x ±~k jn ·~x))

(8)

(2±)

~
~
Ux,i jmn = aim a jn · exp(−sgn(ωi±j )ιεi±jmn ) · B±i jmn · (|ki | sin θm ± |k j | sin θn )· exp(−sgn(ωi±j )ι (~kim ·~x ±~k jn ·~x))

(9)

(2±)

±
±
Ux,i jmn = (ι ) · aim a jn · exp(−sgn(ωi±j )ιεi±jmn ) · B±i jmn · ki jmn · tanh[ki jmn (h + z)]· exp(−sgn(ωi±j )ι (~kim ·~x ±~k jn ·~x))

(10)

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C.3 Wave Particle Acceleration
C.3.1 First-Order
(1)

(1)

(1)

(1)

(1)

(1)

U̇x,im = (ι ) · ωi ·Ux,imU̇y,im = (ι ) · ωi ·Uy,imU̇z,im = (ι ) · ωi ·Uz,im

(11)

(12)

(13)

C.3.2 Second-Order
(2±)

(2±)

(2±)

(2±)

(2±)

(2±)

U̇x,i jmn = (ι ) · ωi±j ·Ux,i jmn
U̇y,i jmn = (ι ) · ωi j ± ·Uy,i jmn
U̇z,i jmn = (ι ) · ωi j ± ·Uz,i jmn

(14)

(15)

(16)

C.4 Dynamic Pressure
C.4.1 First-Order(1)

Pim = (ρw g) · aim · exp(−ιεim )ωicosh[|~ki |(h + z)]· exp(−ι (~kim ·~x))cosh(|~ki |h)(17)

C.4.2 Second-Order (only second-order potential term)(2±)±
Pi jmn = (ρw ) · aim a jn · exp(−sgn(ωi±j )ιεi±jmn ) · B±i jmn · ωi j

· exp(−sgn(ωi±j )ι (~kim ·~x ±~k jn ·~x))

(18)

109

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Appendix D
FAST input files for the parked NREL 5-MW baseline turbine
D.1 Primary Input File(∗.fst)-------------------------------------------------------------------------------------- FAST INPUT FILE -------------------------------------------------------NREL 5.0 MW Baseline Wind Turbine for Use in Offshore Analysis.
Properties from Dutch Offshore Wind Energy Converter (DOWEC) 6MW Pre-Design (10046_00---------------------- SIMULATION CONTROL -------------------------------------False
Echo- Echo input data to "echo.out" (flag)
1
ADAMSPrep- ADAMS preprocessor mode {1: Run FAST, 2: use FAST as a preproc
1
AnalMode- Analysis mode {1: Run a time-marching simulation, 2: create a3
NumBl- Number of blades (-)
4000.0TMax- Total run time (s)0.01000DT- Integration time step (s)---------------------- TURBINE CONTROL ----------------------------------------0
YCMode- Yaw control mode {0: none, 1: user-defined from routine UserYa
9999.9TYCOn- Time to enable active yaw control (s) [unused when YCMode=00
PCMode- Pitch control mode {0: none, 1: user-defined from routine Pitc
0.0
TPCOn
- Time to enable active pitch control (s) [unused when PCMode=0]0
VSContrl- Variable-speed control mode {0: none, 1: simple VS, 2: user-de9999.9VS_RtGnSp- Rated generator speed for simple variable-speed generator c9999.9VS_RtTq- Rated generator torque/constant generator torque in Region
9999.9
VS_Rgn2K- Generator torque constant in Region 2 for simple variable-s
9999.9VS_SlPc- Rated generator slip percentage in Region 2 1/2 for simple
2
GenModel- Generator model {1: simple, 2: Thevenin, 3: user-defined fr
True
GenTiStr- Method to start the generator {T: timed using TimGenOn, F:
True
GenTiStp- Method to stop the generator {T: timed using TimGenOf, F: w
9999.9
SpdGenOn- Generator speed to turn on the generator for a startup (HSS
9999.9
TimGenOn- Time to turn on the generator for a startup (s) [used only
9999.9
TimGenOf- Time to turn off the generator (s) [used only when GenTiStp
1
HSSBrMode- HSS brake model {1: simple, 2: user-defined from routine UserH
0
THSSBrDp- Time to initiate deployment of the HSS brake (s)9999.9TiDynBrk- Time to initiate deployment of the dynamic generator brake
9999.9
TTpBrDp(1) - Time to initiate deployment of tip brake 1 (s)9999.9
TTpBrDp(2) - Time to initiate deployment of tip brake 2 (s)9999.9
TTpBrDp(3) - Time to initiate deployment of tip brake 3 (s) [unused for9999.9TBDepISp(1) - Deployment-initiation speed for the tip brake on blade 1 (r9999.9TBDepISp(2) - Deployment-initiation speed for the tip brake on blade 2 (r9999.9TBDepISp(3) - Deployment-initiation speed for the tip brake on blade 3 (r9999.9TYawManS- Time to start override yaw maneuver and end standard yaw co9999.9TYawManE- Time at which override yaw maneuver reaches final yaw angle
0.0
NacYawF- Final yaw angle for yaw maneuvers (degrees)
9999.9TPitManS(1) - Time to start override pitch maneuver for blade 1 and end s
9999.9TPitManS(2) - Time to start override pitch maneuver for blade 2 and end s
9999.9TPitManS(3) - Time to start override pitch maneuver for blade 3 and end s
9999.9TPitManE(1) - Time at which override pitch maneuver for blade 1 reaches f9999.9TPitManE(2) - Time at which override pitch maneuver for blade 2 reaches f9999.9TPitManE(3) - Time at which override pitch maneuver for blade 3 reaches f
90.0
BlPitch(1) - Blade 1 initial pitch (degrees)
90.0
BlPitch(2) - Blade 2 initial pitch (degrees)
90.0
BlPitch(3) - Blade 3 initial pitch (degrees) [unused for 2 blade
90.0
B1PitchF(1) - Blade 1 final pitch for pitch maneuvers (degrees)
90.0
B1PitchF(2) - Blade 2 final pitch for pitch maneuvers (degrees)
90.0
B1PitchF(3) - Blade 3 final pitch for pitch maneuvers (degrees) [---------------------- ENVIRONMENTAL CONDITIONS -------------------------------9.80665 Gravity- Gravitational acceleration (m/s^2)---------------------- FEATURE FLAGS ------------------------------------------True
FlapDOF1- First flapwise blade mode DOF (flag)
True
FlapDOF2- Second flapwise blade mode DOF (flag)
True
EdgeDOF- First edgewise blade mode DOF (flag)
False
TeetDOF- Rotor-teeter DOF (flag) [unused for 3 blades]
True
DrTrDOF- Drivetrain rotational-flexibility DOF (flag)
True
GenDOF- Generator DOF (flag)
False
YawDOF- Yaw DOF (flag)
True
TwFADOF1- First fore-aft tower bending-mode DOF (flag)
True
TwFADOF2- Second fore-aft tower bending-mode DOF (flag)
True
TwSSDOF1- First side-to-side tower bending-mode DOF (flag)
True
TwSSDOF2- Second side-to-side tower bending-mode DOF (flag)
True
CompAero- Compute aerodynamic forces (flag)
False
CompNoise- Compute aerodynamic noise (flag)---------------------- INITIAL CONDITIONS --------------------------------------

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0.0
OoPDefl- Initial out-of-plane blade-tip displacement (meters)
0.0
IPDefl- Initial in-plane blade-tip deflection (meters)
0.0
TeetDefl- Initial or fixed teeter angle (degrees) [unused for 3 blades]
0.0
Azimuth- Initial azimuth angle for blade 1 (degrees)
0.0
RotSpeed- Initial or fixed rotor speed (rpm)0.0
NacYaw- Initial or fixed nacelle-yaw angle (degrees)
0.0
TTDspFA- Initial fore-aft tower-top displacement (meters)
0.0
TTDspSS- Initial side-to-side tower-top displacement (meters)---------------------- TURBINE CONFIGURATION ----------------------------------63.0
TipRad- The distance from the rotor apex to the blade tip (meters)
1.5
HubRad- The distance from the rotor apex to the blade root (meters)
1
PSpnElN- Number of the innermost blade element which is still part of t
0.0
UndSling- Undersling length [distance from teeter pin to the rotor apex]
0.0
HubCM
- Distance from rotor apex to hub mass [positive downwind] (mete-5.01910 OverHang- Distance from yaw axis to rotor apex [3 blades] or teeter pin
1.9
NacCMxn- Downwind distance from the tower-top to the nacelle CM (meters
0.0
NacCMyn- Lateral distance from the tower-top to the nacelle CM (meters
1.75
NacCMzn- Vertical distance from the tower-top to the nacelle CM (meters
87.6
TowerHt- Height of tower above ground level [onshore] or MSL [offshore
1.96256 Twr2Shft- Vertical distance from the tower-top to the rotor shaft (meter
0.0
TwrRBHt- Tower rigid base height (meters)-5.0
ShftTilt- Rotor shaft tilt angle (degrees)
0.0
Delta3- Delta-3 angle for teetering rotors (degrees) [unused for 3 bla-2.5
PreCone(1) - Blade 1 cone angle (degrees)-2.5
PreCone(2) - Blade 2 cone angle (degrees)-2.5
PreCone(3) - Blade 3 cone angle (degrees) [unused for 2 blades]
0.0
AzimB1Up- Azimuth value to use for I/O when blade 1 points up (degrees)---------------------- MASS AND INERTIA ---------------------------------------0.0
YawBrMass- Yaw bearing mass (kg)240.00E3
NacMass- Nacelle mass (kg)56.78E3
HubMass- Hub mass (kg)0.0
TipMass(1) - Tip-brake mass, blade 1 (kg)0.0
TipMass(2) - Tip-brake mass, blade 2 (kg)0.0
TipMass(3) - Tip-brake mass, blade 3 (kg) [unused for 2 blades]
2607.89E3
NacYIner- Nacelle inertia about yaw axis (kg m^2)
534.116GenIner- Generator inertia about HSS (kg m^2)
115.926E3 HubIner- Hub inertia about rotor axis [3 blades] or teeter axis [2 bl---------------------- DRIVETRAIN ---------------------------------------------90.0
GBoxEff- Gearbox efficiency (%)
94.4
GenEff- Generator efficiency [ignored by the Thevenin and user-define
97.0
GBRatio- Gearbox ratio (-)
False
GBRevers- Gearbox reversal {T: if rotor and generator rotate in oppos
0.5162E3 HSSBrTqF- Fully deployed HSS-brake torque (N-m)
0
HSSBrDT- Time for HSS-brake to reach full deployment once initiated (sec)
DynBrkFi- File containing a mech-gen-torque vs HSS-speed curve for a dynamic brak
867.637E6 DTTorSpr- Drivetrain torsional spring (N-m/rad)6.215E6 DTTorDmp- Drivetrain torsional damper (N-m/(rad/s))---------------------- SIMPLE INDUCTION GENERATOR -----------------------------9999.9
SIG_SlPc- Rated generator slip percentage (%) [used only when VSContr
9999.9SIG_SySp- Synchronous (zero-torque) generator speed (rpm) [used only
9999.9SIG_RtTq- Rated torque (N-m) [used only when VSContrl=0 and GenModel=
9999.9SIG_PORt- Pull-out ratio (Tpullout/Trated) (-) [used only when VSCont---------------------- THEVENIN-EQUIVALENT INDUCTION GENERATOR ----------------9999.9
TEC_Freq- Line frequency [50 or 60] (Hz) [used only when VSContrl=0 a
9998
TEC_NPol- Number of poles [even integer > 0] (-) [used only when VSCo
9999.9TEC_SRes- Stator resistance (ohms) [used only when VSContrl=0 and Gen
9999.9TEC_RRes- Rotor resistance (ohms) [used only when VSContrl=0 and GenM
9999.9TEC_VLL- Line-to-line RMS voltage (volts) [used only when VSContrl=09999.9TEC_SLR- Stator leakage reactance (ohms) [used only when VSContrl=09999.9TEC_RLR- Rotor leakage reactance (ohms) [used only when VSContrl=0 a9999.9
TEC_MR- Magnetizing reactance (ohms) [used only when VSContrl=0 and---------------------- PLATFORM -----------------------------------------------0
PtfmModel- Platform model {0: none, 1: onshore, 2: fixed bottom o"NRELOffshrBsline5MW_Platform_Monopile_RF.dat"
PtfmFile- Name of file contai---------------------- TOWER --------------------------------------------------99
TwrNodes- Number of tower nodes used for analysis (-)"NRELOffshrBsline5MW_Tower_Onshore.dat"
TwrFile- Name of file containin---------------------- NACELLE-YAW --------------------------------------------9028.32E6
YawSpr- Nacelle-yaw spring constant (N-m/rad)19.16E6
YawDamp- Nacelle-yaw damping constant (N-m/(rad/s))
0.0
YawNeut- Neutral yaw position--yaw spring force is zero at this yaw (de---------------------- FURLING ------------------------------------------------False
Furling- Read in additional model properties for furling turbine (flFurlFile- Name of file containing furling properties (quoted string) [unused when---------------------- ROTOR-TEETER -------------------------------------------0
TeetMod- Rotor-teeter spring/damper model {0: none, 1: standard, 2: use

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0.0
TeetDmpP- Rotor-teeter damper position (degrees) [used only for 2 blades
0.0
TeetDmp- Rotor-teeter damping constant (N-m/(rad/s)) [used only for 2 b
0.0
TeetCDmp- Rotor-teeter rate-independent Coulomb-damping moment (N-m) [us0.0
TeetSStP- Rotor-teeter soft-stop position (degrees) [used only for 2 bla
0.0
TeetHStP- Rotor-teeter hard-stop position (degrees) [used only for 2 bla
0.0
TeetSSSp- Rotor-teeter soft-stop linear-spring constant (N-m/rad) [used0.0
TeetHSSp- Rotor-teeter hard-stop linear-spring constant (N-m/rad) [used---------------------- TIP-BRAKE ----------------------------------------------0.0
TBDrConN- Tip-brake drag constant during normal operation, Cd*Area (m^2)
0.0
TBDrConD- Tip-brake drag constant during fully-deployed operation, Cd*Ar
0.0
TpBrDT- Time for tip-brake to reach full deployment once released (sec---------------------- BLADE --------------------------------------------------"NRELOffshrBsline5MW_Blade.dat"
BldFile(1) - Name of file containin"NRELOffshrBsline5MW_Blade.dat"
BldFile(2) - Name of file containin"NRELOffshrBsline5MW_Blade.dat"
BldFile(3) - Name of file containin---------------------- AERODYN ------------------------------------------------"NRELOffshrBsline5MW_AeroDyn.ipt"
ADFile- Name of file containin---------------------- NOISE --------------------------------------------------NoiseFile- Name of file containing aerodynamic noise input parameters (quoted stri---------------------- ADAMS --------------------------------------------------"NRELOffshrBsline5MW_ADAMSSpecific.dat"
ADAMSFile- Name of file containin---------------------- LINEARIZATION CONTROL ----------------------------------"NRELOffshrBsline5MW_Linear.dat"
LinFile- Name of file containin---------------------- OUTPUT -------------------------------------------------True
SumPrint- Print summary data to "<RootName>.fsm" (flag)
1
OutFileFmt - Format for tabular (time-marching) output file(s) (1: text
True
TabDelim- Generate a tab-delimited tabular output file. (flag)"ES10.3E2" OutFmt- Format used for tabular output except time. Resulting fiel
0TStart- Time to begin tabular output (s)10
DecFact- Decimation factor for tabular output {1: output every
10.0
SttsTime- Amount of time between screen status messages (sec)-3.09528 NcIMUxn- Downwind distance from the tower-top to the nacelle IMU (mete0.0
NcIMUyn- Lateral distance from the tower-top to the nacelle IMU (meter
2.23336 NcIMUzn- Vertical distance from the tower-top to the nacelle IMU (meter
1.912
ShftGagL- Distance from rotor apex [3 blades] or teeter pin [2 blades] t
3
NTwGages- Number of tower nodes that have strain gages for output [0 to10,11,12
TwrGagNd- List of tower nodes that have strain gages [1 to TwrNodes]
3
NBlGages- Number of blade nodes that have strain gages for output [0 to5,9,13
BldGagNd- List of blade nodes that have strain gages [1 to BldNodes] (OutList- The next line(s) contains a list of output parameters. See OutList.txt"WindVxi , WindVyi , WindVzi"- Longitudinal, lateral,"GenPwr, GenTq"- Electrical generator p"OoPDefl1 , IPDefl1 , TwstDefl1"- Blade 1 out-of-plane a"BldPitch1"- Blade 1 pitch angle"Azimuth"- Blade 1 azimuth angle"RotSpeed , GenSpeed"- Low-speed shaft and hi"TTDspFA , TTDspSS , TTDspTwst"- Tower fore-aft and sid"Spn2MLxb1, Spn2MLyb1"- Blade 1 local edgewise"RootFxc1 , RootFyc1 , RootFzc1"- Out-of-plane shear, in"RootMxc1 , RootMyc1 , RootMzc1"- In-plane bending, out"RotTorq , LSSGagMya, LSSGagMza"- Rotor torque and low-s"YawBrFxp , YawBrFyp , YawBrFzp"- Fore-aft shear, side-t"YawBrMxp , YawBrMyp , YawBrMzp"- Side-to-side bending,"TwrBsFxt , TwrBsFyt , TwrBsFzt"- Fore-aft shear, side-t"TwrBsMxt , TwrBsMyt , TwrBsMzt"- Side-to-side bending,"NacYaw, YawPos""RootMxb1 , RootMyb1 , RootMzb1"- Blade 1 edgewise, flap
"NacYawErr, HorWndDir""WaveElev"
END of FAST input file (the word "END" must appear in the first 3 columns of this las--------------------------------------------------------------------------------

D.2 AeroDyn Input Files(∗.ipt)
NREL 5.0 MW offshore baseline aerodynamic input properties; Compatible with AeroDyn v1SI
SysUnits- System of units used for input and output [must be SI for FA
STEADY
StallMod- Dynamic stall included [BEDDOES or STEADY] (unquoted string)
NO_CM
UseCm
- Use aerodynamic pitching moment model? [USE_CM or NO_CM] (unqEQUIL
InfModel- Inflow model [DYNIN or EQUIL] (unquoted string)
NONE
IndModel- Induction-factor model [NONE or WAKE or SWIRL] (unquoted stri
0.005
AToler- Induction-factor tolerance (convergence criteria) (-)
PRANDtl
TLModel- Tip-loss model (EQUIL only) [PRANDtl, GTECH, or NONE] (unquo
PRANDtl
HLModel- Hub-loss model (EQUIL only) [PRANdtl or NONE] (unquoted stri"userwind"
WindFile- Name of file containing wind data (quoted stri112

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

90.0
HH
- Wind reference (hub) height [TowerHt+Twr2Shft+OverHang*SIN(Shf
0.0
TwrShad- Tower-shadow velocity deficit (-)
9999.9ShadHWid- Tower-shadow half width (m)9999.9T_Shad_Refpt- Tower-shadow reference point (m)1.225
AirDens- Air density (kg/m^3)
1.464E-5 KinVisc- Kinematic air viscosity [CURRENTLY IGNORED] (m^2/sec)
0.0125 DTAero- Time interval for aerodynamic calculations (sec)8
NumFoil- Number of airfoil files (-)"AeroData\Cylinder1.dat"
FoilNm- Names of the airfoil fi"AeroData\Cylinder2.dat""AeroData\DU40_A17.dat""AeroData\DU35_A17.dat""AeroData\DU30_A17.dat""AeroData\DU25_A17.dat""AeroData\DU21_A17.dat""AeroData\NACA64_A17.dat"
17
BldNodes- Number of blade nodes used for analysis (-)
RNodesAeroTwst DRNodes Chord NFoil PrnElm
2.8667 13.308
2.73333.542 1PRINT
5.6000 13.308
2.73333.854 1PRINT
8.3333 13.308
2.73334.167 2
PRINT
11.7500 13.308
4.10004.557 3PRINT
15.8500 11.480
4.10004.652 4PRINT
19.9500 10.162
4.10004.458 4PRINT
24.0500
9.011
4.10004.249 5PRINT
28.1500
7.795
4.10004.007 6PRINT
32.2500
6.544
4.10003.748 6
PRINT
36.3500
5.361
4.10003.502 7PRINT
40.4500
4.188
4.10003.256 7PRINT
44.5500
3.125
4.10003.010 8PRINT
48.6500
2.319
4.10002.764 8PRINT
52.7500
1.526
4.10002.518 8PRINT
56.16670.863
2.73332.313 8PRINT
58.9000
0.370
2.73332.086 8PRINT
61.6333
0.106
2.7333
1.419 8PRINT

113This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Appendix E
Abaqus files for modeling the jacket support structure
E.1 Phyton script to read field output from .odb(∗.py)from odbAccess import *from textRepr import *from abaqusConstants import *import odbAccess
odb=openOdb(path=’myjob.odb’)
mySteps = odb.steps
numSteps = len(mySteps)
for i in range(numSteps):
stepKey = mySteps.keys()[i]step = mySteps[stepKey]
numFrames = len(step.frames)
regS1= odb.rootAssembly.instances[’PART-1-1’].nodeSets[’BC_NODE’]
regU1= odb.rootAssembly.instances[’PART-1-1’].nodeSets[’ZERO_POINT’]regL1= odb.rootAssembly.instances[’PART-1-1’].elementSets[’LEG1_MEMB1’]
regL2= odb.rootAssembly.instances[’PART-1-1’].elementSets[’LEG2_MEMB1’]
regL3= odb.rootAssembly.instances[’PART-1-1’].elementSets[’LEG3_MEMB1’]
regL4= odb.rootAssembly.instances[’PART-1-1’].elementSets[’LEG4_MEMB1’]
regB1M1= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA1_MEMB1’]
regB2M1= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA2_MEMB1’]
regB3M1= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA3_MEMB1’]
regB4M1= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA4_MEMB1’]
regB1M2= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA1_MEMB2’]
regB2M2= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA2_MEMB2’]
regB3M2= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA3_MEMB2’]
regB4M2= odb.rootAssembly.instances[’PART-1-1’].elementSets[’BRA4_MEMB2’]
frameRepository = step.frames
moment_out
force_out
disp_out_zero
L1_outL2_outL3_outL4_out
B1M1_out
B2M1_out
B3M1_out
B4M1_out
B1M2_out
B2M2_out
B3M2_out
B4M2_out=open(’abaqus_moment1.txt’,’w’)=open(’abaqus_force1.txt’,’w’)=open(’abaqus_disp_zero.txt’,’w’)=open(’abaqus_L1.txt’,’w’)=open(’abaqus_L2.txt’,’w’)=open(’abaqus_L3.txt’,’w’)=open(’abaqus_L4.txt’,’w’)=open(’abaqus_B1M1.txt’,’w’)=open(’abaqus_B2M1.txt’,’w’)=open(’abaqus_B3M1.txt’,’w’)=open(’abaqus_B4M1.txt’,’w’)=open(’abaqus_B1M2.txt’,’w’)=open(’abaqus_B2M2.txt’,’w’)=open(’abaqus_B3M2.txt’,’w’)=open(’abaqus_B4M2.txt’,’w’)

for frame in frameRepository:
RForce=frame.fieldOutputs[’RF’]
RMoment =frame.fieldOutputs[’RM’]
UDisp=frame.fieldOutputs[’U’]
URDisp=frame.fieldOutputs[’UR’]
SForce=frame.fieldOutputs[’SF’]
SMoment =frame.fieldOutputs[’SM’]
Time = frame.frameValue
FX= RForce.getSubset(region=regS1).values[0].data[0]FY= RForce.getSubset(region=regS1).values[0].data[1]FZ= RForce.getSubset(region=regS1).values[0].data[2]MX= RMoment.getSubset(region=regS1).values[0].data[0]MY= RMoment.getSubset(region=regS1).values[0].data[1]MZ= RMoment.getSubset(region=regS1).values[0].data[2]U_zero1= UDisp.getSubset(region=regU1).values[0].data[0]U_zero2= UDisp.getSubset(region=regU1).values[0].data[1]U_zero3= UDisp.getSubset(region=regU1).values[0].data[2]UR_zero1 = URDisp.getSubset(region=regU1).values[0].data[0]UR_zero2 = URDisp.getSubset(region=regU1).values[0].data[1]UR_zero3 = URDisp.getSubset(region=regU1).values[0].data[2]114This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

L1_F1= SForce.getSubset(region=regL1).values[0].data[0]L1_F2= SForce.getSubset(region=regL1).values[0].data[1]L1_F3= SForce.getSubset(region=regL1).values[0].data[2]L1_M1= SMoment.getSubset(region=regL1).values[0].data[0]L1_M2= SMoment.getSubset(region=regL1).values[0].data[1]L1_M3= SMoment.getSubset(region=regL1).values[0].data[2]L2_F1= SForce.getSubset(region=regL2).values[0].data[0]L2_F2= SForce.getSubset(region=regL2).values[0].data[1]L2_F3= SForce.getSubset(region=regL2).values[0].data[2]L2_M1= SMoment.getSubset(region=regL2).values[0].data[0]L2_M2= SMoment.getSubset(region=regL2).values[0].data[1]L2_M3= SMoment.getSubset(region=regL2).values[0].data[2]L3_F1= SForce.getSubset(region=regL3).values[0].data[0]L3_F2= SForce.getSubset(region=regL3).values[0].data[1]L3_F3= SForce.getSubset(region=regL3).values[0].data[2]L3_M1= SMoment.getSubset(region=regL3).values[0].data[0]L3_M2= SMoment.getSubset(region=regL3).values[0].data[1]L3_M3= SMoment.getSubset(region=regL3).values[0].data[2]L4_F1= SForce.getSubset(region=regL4).values[0].data[0]L4_F2= SForce.getSubset(region=regL4).values[0].data[1]L4_F3= SForce.getSubset(region=regL4).values[0].data[2]L4_M1= SMoment.getSubset(region=regL4).values[0].data[0]L4_M2= SMoment.getSubset(region=regL4).values[0].data[1]L4_M3= SMoment.getSubset(region=regL4).values[0].data[2]B1M1_F1= SForce.getSubset(region=regB1M1).values[0].data[0]B1M1_F2= SForce.getSubset(region=regB1M1).values[0].data[1]B1M1_F3= SForce.getSubset(region=regB1M1).values[0].data[2]B1M1_M1= SMoment.getSubset(region=regB1M1).values[0].data[0]B1M1_M2= SMoment.getSubset(region=regB1M1).values[0].data[1]B1M1_M3= SMoment.getSubset(region=regB1M1).values[0].data[2]B2M1_F1= SForce.getSubset(region=regB2M1).values[0].data[0]B2M1_F2= SForce.getSubset(region=regB2M1).values[0].data[1]B2M1_F3= SForce.getSubset(region=regB2M1).values[0].data[2]B2M1_M1= SMoment.getSubset(region=regB2M1).values[0].data[0]B2M1_M2= SMoment.getSubset(region=regB2M1).values[0].data[1]B2M1_M3= SMoment.getSubset(region=regB2M1).values[0].data[2]B3M1_F1= SForce.getSubset(region=regB3M1).values[0].data[0]B3M1_F2= SForce.getSubset(region=regB3M1).values[0].data[1]B3M1_F3= SForce.getSubset(region=regB3M1).values[0].data[2]B3M1_M1= SMoment.getSubset(region=regB3M1).values[0].data[0]B3M1_M2= SMoment.getSubset(region=regB3M1).values[0].data[1]B3M1_M3= SMoment.getSubset(region=regB3M1).values[0].data[2]B4M1_F1= SForce.getSubset(region=regB4M1).values[0].data[0]B4M1_F2= SForce.getSubset(region=regB4M1).values[0].data[1]B4M1_F3= SForce.getSubset(region=regB4M1).values[0].data[2]B4M1_M1= SMoment.getSubset(region=regB4M1).values[0].data[0]B4M1_M2= SMoment.getSubset(region=regB4M1).values[0].data[1]B4M1_M3= SMoment.getSubset(region=regB4M1).values[0].data[2]B1M2_F1= SForce.getSubset(region=regB1M2).values[0].data[0]B1M2_F2= SForce.getSubset(region=regB1M2).values[0].data[1]B1M2_F3= SForce.getSubset(region=regB1M2).values[0].data[2]B1M2_M1= SMoment.getSubset(region=regB1M2).values[0].data[0]B1M2_M2= SMoment.getSubset(region=regB1M2).values[0].data[1]B1M2_M3= SMoment.getSubset(region=regB1M2).values[0].data[2]B2M2_F1= SForce.getSubset(region=regB2M2).values[0].data[0]B2M2_F2= SForce.getSubset(region=regB2M2).values[0].data[1]B2M2_F3= SForce.getSubset(region=regB2M2).values[0].data[2]B2M2_M1= SMoment.getSubset(region=regB2M2).values[0].data[0]B2M2_M2= SMoment.getSubset(region=regB2M2).values[0].data[1]B2M2_M3= SMoment.getSubset(region=regB2M2).values[0].data[2]B3M2_F1= SForce.getSubset(region=regB3M2).values[0].data[0]B3M2_F2= SForce.getSubset(region=regB3M2).values[0].data[1]B3M2_F3= SForce.getSubset(region=regB3M2).values[0].data[2]B3M2_M1= SMoment.getSubset(region=regB3M2).values[0].data[0]B3M2_M2= SMoment.getSubset(region=regB3M2).values[0].data[1]B3M2_M3= SMoment.getSubset(region=regB3M2).values[0].data[2]B4M2_F1= SForce.getSubset(region=regB4M2).values[0].data[0]B4M2_F2= SForce.getSubset(region=regB4M2).values[0].data[1]B4M2_F3= SForce.getSubset(region=regB4M2).values[0].data[2]B4M2_M1= SMoment.getSubset(region=regB4M2).values[0].data[0]B4M2_M2= SMoment.getSubset(region=regB4M2).values[0].data[1]B4M2_M3= SMoment.getSubset(region=regB4M2).values[0].data[2]force_out.write(str(Time)+""+str(FX)+""+str(FY)+""+str(FZ)+"\n")moment_out.write(str(Time)+""+str(MX)+""+str(MY)+""+str(MZ)+"\n")disp_out_zero.write(str(Time)+""+str(U_zero1)+""+str(U_zero2)+""+str(U_zero3)+""+str(UR_zero1)+""+str(UR_zero2)+""+str(UR_zero3)+"\n")115This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

L1_out.write(str(Time)+""+str(L1_F1)+""+str(L1_F2)+""+str(L1_F3)+""+str(L1_M1)+""+str(L1_M2)+""+str(L1_M3)+"\n")L2_out.write(str(Time)+""+str(L2_F1)+""+str(L2_F2)+""+str(L2_F3)+""+str(L2_M1)+""+str(L2_M2)+""+str(L2_M3)+"\n")L3_out.write(str(Time)+""+str(L3_F1)+""+str(L3_F2)+""+str(L3_F3)+""+str(L3_M1)+""+str(L3_M2)+""+str(L3_M3)+"\n")L4_out.write(str(Time)+""+str(L4_F1)+""+str(L4_F2)+""+str(L4_F3)+""+str(L4_M1)+""+str(L4_M2)+""+str(L4_M3)+"\n")B1M1_out.write(str(Time)+""+str(B1M1_F1)+""+str(B1M1_F2)+""+str(B1M1_F3)+""+str(B1M1_M1)+""+str(B1M1_M2)+""+str(B1M1_M3)+"\n")B2M1_out.write(str(Time)+""+str(B2M1_F1)+""+str(B2M1_F2)+""+str(B2M1_F3)+""+str(B2M1_M1)+""+str(B2M1_M2)+""+str(B2M1_M3)+"\n")B3M1_out.write(str(Time)+""+str(B3M1_F1)+""+str(B3M1_F2)+""+str(B3M1_F3)+""+str(B3M1_M1)+""+str(B3M1_M2)+""+str(B3M1_M3)+"\n")B4M1_out.write(str(Time)+""+str(B4M1_F1)+""+str(B4M1_F2)+""+str(B4M1_F3)+""+str(B4M1_M1)+""+str(B4M1_M2)+""+str(B4M1_M3)+"\n")B1M2_out.write(str(Time)+""+str(B1M2_F1)+""+str(B1M2_F2)+""+str(B1M2_F3)+""+str(B1M2_M1)+""+str(B1M2_M2)+""+str(B1M2_M3)+"\n")B2M2_out.write(str(Time)+""+str(B2M2_F1)+""+str(B2M2_F2)+""+str(B2M2_F3)+""+str(B2M2_M1)+""+str(B2M2_M2)+""+str(B2M2_M3)+"\n")B3M2_out.write(str(Time)+""+str(B3M2_F1)+""+str(B3M2_F2)+""+str(B3M2_F3)+""+str(B3M2_M1)+""+str(B3M2_M2)+""+str(B3M2_M3)+"\n")B4M2_out.write(str(Time)+""+str(B4M2_F1)+""+str(B4M2_F2)+""+str(B4M2_F3)+""+str(B4M2_M1)+""+str(B4M2_M2)+""+str(B4M2_M3)+"\n")moment_out=open(’abaqus_moment2.txt’,’w’)
force_out=open(’abaqus_force2.txt’,’w’)
for frame in frameRepository:
RForce =frame.fieldOutputs[’RF’]
RMoment=frame.fieldOutputs[’RM’]
Time = frame.frameValue
FX= RForce.getSubset(region=regS1).values[1].data[0]FY= RForce.getSubset(region=regS1).values[1].data[1]FZ= RForce.getSubset(region=regS1).values[1].data[2]MX= RMoment.getSubset(region=regS1).values[1].data[0]MY= RMoment.getSubset(region=regS1).values[1].data[1]MZ= RMoment.getSubset(region=regS1).values[1].data[2]force_out.write(str(Time)+""+str(FX)+""+str(FY)+"
moment_out.write(str(Time)+""+str(MX)+""+str(MY)+""+str(FZ)+"\n")"+str(MZ)+"\n")moment_out=open(’abaqus_moment3.txt’,’w’)
force_out=open(’abaqus_force3.txt’,’w’)
for frame in frameRepository:
RForce =frame.fieldOutputs[’RF’]
RMoment=frame.fieldOutputs[’RM’]
Time = frame.frameValue
FX= RForce.getSubset(region=regS1).values[2].data[0]FY= RForce.getSubset(region=regS1).values[2].data[1]FZ= RForce.getSubset(region=regS1).values[2].data[2]MX= RMoment.getSubset(region=regS1).values[2].data[0]MY= RMoment.getSubset(region=regS1).values[2].data[1]MZ= RMoment.getSubset(region=regS1).values[2].data[2]force_out.write(str(Time)+""+str(FX)+""+str(FY)+"
moment_out.write(str(Time)+""+str(MX)+""+str(MY)+""+str(FZ)+"\n")"+str(MZ)+"\n")moment_out=open(’abaqus_moment4.txt’,’w’)
force_out=open(’abaqus_force4.txt’,’w’)
for frame in frameRepository:
RForce =frame.fieldOutputs[’RF’]
RMoment=frame.fieldOutputs[’RM’]
Time = frame.frameValue
FX= RForce.getSubset(region=regS1).values[3].data[0]FY= RForce.getSubset(region=regS1).values[3].data[1]FZ= RForce.getSubset(region=regS1).values[3].data[2]MX= RMoment.getSubset(region=regS1).values[3].data[0]MY= RMoment.getSubset(region=regS1).values[3].data[1]MZ= RMoment.getSubset(region=regS1).values[3].data[2]force_out.write(str(Time)+""+str(FX)+""+str(FY)+"
moment_out.write(str(Time)+""+str(MX)+""+str(MY)+""+str(FZ)+"\n")"+str(MZ)+"\n")odb.close()

116

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

E.2 Abaqus Input File(∗.inp)*Heading*Preprint, echo=NO, model=NO, history=NO, contact=NO**** PARTS***Part, name=PART-1*Node1,6000.,
6000.,-50000.
2,
6000.,
6000.,-45000.
3,5967.,
5967.,-44001.
4,5939.,
5939.,-43127.
5,5333.,
5333.,-24614.
6,-6000.,
6000.,-50000.
7,-6000.,
6000.,-45000.
8,-5967.,
5967.,-44001.
9,-5939.,
5939.,-43127.
10,-5333.,
5333.,-24614.
11,-6000.,-6000.,-50000.
12,-6000.,-6000.,-45000.
13,-5967.,-5967.,-44001.
14,-5939.,-5939.,-43127.
15,-5333.,-5333.,-24614.
16,
6000.,-6000.,-50000.
17,6000.,-6000.,-45000.
18,5967.,-5967.,-44001.
19,5939.,-5939.,-43127.
20,5333.,-5333.,-24614.
21,4820.,
4820.,-8922.
22,4385.,
4385.,
4378.
23,
4016.,
4016.,
15651.
24,
4000.,
4000.,
16150.
25,-4820.,
4820.,-8922.
26,-4385.,
4385.,
4378.
27,-4016.,
4016.,
15651.
28,-4000.,
4000.,
16150.
29,-4820.,-4820.,-8922.
30,-4385.,-4385.,
4378.
31,-4016.,-4016.,
15651.
32,-4000.,-4000.,
16150.
33,
4820.,-4820.,-8922.
34,
4385.,-4385.,
4378.
35,
4016.,-4016.,
15651.
36,
4000.,-4000.,
16150.
41,
5620.,
0.,-33373.
42,-5620.,
0.,-33373.
43,0.,5620.,-33373.
44,0.,-5620.,-33373.
45,5064.,
0.,-16371.
46,-5064.,
0.,-16371.
47,
0.,5064.,-16371.
48,
0.,-5064.,-16371.
49,4592.,
0.,-1958.
50,-4592.,
0.,-1958.
51,
0.,4592.,-1958.
52,
0.,-4592.,-1958.
53,
4193.,
0.,10262.
54,-4193.,
0.,10262.
55,
0.,4193.,
10262.
56,
0.,-4193.,
10262.
57,
4000.,
4000.,
20150.
58,-4000.,
4000.,
20150.
59,
4000.,-4000.,
20150.
60,-4000.,-4000.,
20150.
61,
0.,0.,16150.
62,0.,0.,18150.
63,
0.,0.,20150.
1001,
0.,
0.,
21150.
1011,
0.,
0.,
32150.
1021,
0.,
0.,
42150.
1031,
0.,
0.,
54150.
1041,
0.,
0.,
64150.
1051,
0.,
0.,
74150.
1061,
0.,
0.,
83150.
1071,
0.,
0.,
88150.

117

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10041,10042,
10043,
10044,
10045,
10046,
10047,
10081,
10082,
10083,
10084,
10085,
10086,
10087,
10121,
10122,
10123,
10124,
10125,
10126,
10127,
10161,
10162,
10163,
10164,
10165,
10166,
10167,
10171,
10172,
10173,
10174,
10175,
10176,
10177,
10181,
10182,
10183,
10184,
10185,
10186,
10187,
10191,
10192,
10193,
10194,
10195,
10196,
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10212,
10213,
10214,
10215,
10216,
10217,
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10223,
10224,
10225,
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10227,
10231,
10232,
10233,
10234,
10235,
10236,
10237,
10251,
10252,
10253,
10254,
10255,
10256,

5863,
5863,
5787,
5787,
5711,
5711,
5636,
5636,
5560,
5560,
5484,
5484,
5408,
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5268.,
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4948.,
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4711.,
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4548.,
4493.,
4439.,
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4246.,
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4062.,
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4062.,-5269.,-5205.,-5141.,-5077.,-5013.,-4949.,-40813.
-38499.
-36185.
-33871.
-31557.
-29243.
-26929.
-40813.
-38499.
-36185.
-33871.
-31557.
-29243.
-26929.
-40813.
-38499.
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-33871.
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-14807.
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-10884.
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-5597.
-3935.
-2272.
-610.
1053.
2715.
5787.
7196.
8605.
10014.
11423.
12832.
14241.
-22653.
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-18730.
-16768.
-14807.
-12845.
-10884.
-7260.
-5597.
-3935.
-2272.
-610.
1053.
2715.
5787.
7196.
8605.
10014.
11423.
12832.
14241.
-22653.
-20691.
-18730.
-16768.
-14807.
-12845.

118

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10257,10261,
10262,
10263,
10264,
10265,
10266,
10267,
10271,
10272,
10273,
10274,
10275,
10276,
10277,
10291,
10292,
10293,
10294,
10295,
10296,
10297,
10301,
10302,
10303,
10304,
10305,
10306,
10307,
10311,
10312,
10313,
10314,
10315,
10316,
10317,
10371,
10372,
10373,
10374,
10375,
10376,
10377,
10381,
10382,
10383,
10384,
10385,
10386,
10387,
10391,
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10393,
10394,
10395,
10396,
10397,
10401,
10402,
10403,
10404,
10405,
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10411,
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10413,
10421,
10422,
10423,
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4948.,
4884.,
4765.,
4711.,
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4493.,
4439.,
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4292.,
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4062.,
4475.,
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0.,-1492.,-2984.,-4476.,-5967.,-5967.,-5967.,-5967.,-5967.,-5967.,-5967.,-4476.,-2984.,-1492.,
0.,1491.,
2983.,
4475.,
5967.,
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5967.,
5967.,
5967.,
5967.,
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5699.,
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5699.,
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5967.,
5967.,
5967.,
5967.,
5967.,
5967.,
5967.,
4475.,
2983.,
1491.,
0.,-1492.,-2984.,-4476.,-5967.,-5967.,-5967.,-5967.,-5967.,-5967.,-5967.,-4476.,-2984.,-1492.,
0.,1491.,
2983.,
4475.,
4454.,
2969.,
1484.,-1334.,-2667.,-4000.,-4455.,-2970.,-1485.,
1333.,
2666.,
3999.,-10884.
-7260.
-5597.
-3935.
-2272.
-610.
1053.
2715.
5787.
7196.
8605.
10014.
11423.
12832.
14241.
-22653.
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-18730.
-16768.
-14807.
-12845.
-10884.
-7260.
-5597.
-3935.
-2272.
-610.
1053.
2715.
5787.
7196.
8605.
10014.
11423.
12832.
14241.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-44001.
-40689.
-38250.
-35812.
-31184.
-28994.
-26804.
-40689.
-38250.
-35812.
-31184.
-28994.
-26804.

119

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10451,10452,
10453,
10461,
10462,
10463,
10471,
10472,
10473,
10481,
10482,
10483,
10491,
10492,
10493,
10501,
10502,
10503,
10511,
10512,
10513,
10521,
10522,
10523,
10531,
10532,
10533,
10541,
10542,
10543,
10551,
10552,
10553,
10561,
10562,
10563,
10571,
10572,
10573,
10581,
10582,
10583,
10591,
10592,
10593,
10601,
10602,
10603,
10611,
10612,
10613,
10621,
10622,
10623,
10631,
10632,
10633,
10641,
10642,
10643,
10651,
10652,
10653,
10661,
10662,
10663,
10671,
10672,
10673,
10681,
10682,
10683,
10691,
10692,
10693,
10701,-5860.,-5780.,-5700.,-5549.,-5477.,-5405.,-5860.,-5780.,-5700.,-5549.,-5477.,-5405.,
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2969.,
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1333.,-1205.,-2410.,-3615.,-4000.,-2667.,-1334.,
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2410.,
3615.,
3999.,
2666.,
1333.,-1205.,

4454.,
2969.,
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5779.,
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4881.,-5266.,-5199.,-5132.,-5003.,-40689.
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-31184.
-28994.
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-28994.
-26804.
-40689.
-38250.
-35812.
-31184.
-28994.
-26804.
-40689.
-38250.
-35812.
-31184.
-28994.
-26804.
-40689.
-38250.
-35812.
-31184.
-28994.
-26804.
-40689.
-38250.
-35812.
-31184.
-28994.
-26804.
-22554.
-20493.
-18432.
-14509.
-12647.
-10785.
-22554.
-20493.
-18432.
-14509.
-12647.
-10785.
-22554.
-20493.
-18432.
-14509.
-12647.
-10785.
-22554.
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-18432.
-14509.
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-10785.
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-14509.
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-22554.
-20493.
-18432.
-14509.
-12647.
-10785.
-22554.
-20493.
-18432.
-14509.

120

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10702,10703,
10711,
10712,
10713,
10721,
10722,
10723,
10731,
10732,
10733,
10741,
10742,
10743,
10751,
10752,
10753,
10761,
10762,
10763,
10771,
10772,
10773,
10781,
10782,
10783,
10791,
10792,
10793,
10801,
10802,
10803,
10811,
10812,
10813,
10821,
10822,
10823,
10831,
10832,
10833,
10841,
10842,
10843,
10851,
10852,
10853,
10861,
10862,
10863,
10871,
10872,
10873,
10881,
10882,
10883,
10891,
10892,
10893,
10901,
10902,
10903,
10911,
10912,
10913,
10921,
10922,
10923,
10931,
10932,
10933,
10941,
10942,
10943,
10951,
10952,-2410.,-3615.,-4000.,-2667.,-1334.,
1205.,
2410.,
3615.,
4763.,
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4540.,
4488.,
4436.,
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3288.,
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4104.,
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4241.,
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4540.,
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3288.,
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1004.,
2008.,
3012.,
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2192.,
1096.,-1004.,-2008.,-3012.,-3289.,-2193.,-12647.
-10785.
-22554.
-20493.
-18432.
-14509.
-12647.
-10785.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
-7181.
-5440.
-3699.
-374.
1210.
2794.
5849.
7320.
8791.
11609.
12956.
14303.
5849.
7320.
8791.
11609.
12956.
14303.
5849.
7320.
8791.
11609.
12956.
14303.
5849.
7320.

121

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10953,10961,
10962,
10963,
10971,
10972,
10973,
10981,
10982,
10983,
10991,
10992,
10993,
11001,
11002,
11003,
11011,
11012,
11013,
11021,
11022,
11023,
11031,
11032,
11033,
11041,
11042,
11043,
21001 ,
21002 ,
21003 ,
21004 ,
21005 ,
21006 ,
21007 ,
21008 ,
21009 ,
21010 ,
21011 ,
21012 ,
21013 ,
21014 ,
21015 ,
21016 ,
21017 ,
21018 ,
21019 ,
21020 ,
21021 ,
21022 ,
21023 ,
21024 ,
21025 ,
21026 ,
21027 ,
21028 ,
21029 ,
21030 ,
21031 ,
21032 ,
21033 ,
21034 ,
21035 ,
21036 ,
21037 ,
21038 ,
21039 ,
21040 ,
21041 ,
21042 ,
21043 ,
21044 ,
21045 ,
21046 ,
21047 ,
21048 ,

-4241.,-4149.,-4105.,-4061.,
3288.,
2192.,
1096.,-1004.,-2008.,-3012.,-3289.,-2193.,-1097.,
1004.,
2008.,
3012.,
3288.,
2192.,
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1004.,
2008.,
3012.,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,
6000 , 6000 ,-1097.,
1004.,
2008.,
3012.,
4337.,
4289.,
4241.,
4148.,
4104.,
4060.,
4337.,
4289.,
4241.,
4148.,
4104.,
4060.,-4337.,-4289.,-4241.,-4149.,-4105.,-4061.,-4337.,-4289.,-4241.,-4149.,-4105.,-4061.,-51000-52000-53000-54000-55000-56000-57000-58000-59000-60000-61000-62000-63000-64000-65000-66000-67000-68000-69000-70000-71000-72000-73000-74000-75000-76000-77000-78000-79000-80000-81000-82000-83000-84000-85000-86000-87000-88000-89000-90000-91000-92000-93000-94000-95000-96000-97000-980008791.
11609.
12956.
14303.
5849.
7320.
8791.
11609.
12956.
14303.
5849.
7320.
8791.
11609.
12956.
14303.
5849.
7320.
8791.
11609.
12956.
14303.
5849.
7320.
8791.
11609.
12956.
14303.

122

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

21049 ,
21050 ,
22001 ,
22002 ,
22003 ,
22004 ,
22005 ,
22006 ,
22007 ,
22008 ,
22009 ,
22010 ,
22011 ,
22012 ,
22013 ,
22014 ,
22015 ,
22016 ,
22017 ,
22018 ,
22019 ,
22020 ,
22021 ,
22022 ,
22023 ,
22024 ,
22025 ,
22026 ,
22027 ,
22028 ,
22029 ,
22030 ,
22031 ,
22032 ,
22033 ,
22034 ,
22035 ,
22036 ,
22037 ,
22038 ,
22039 ,
22040 ,
22041 ,
22042 ,
22043 ,
22044 ,
22045 ,
22046 ,
22047 ,
22048 ,
22049 ,
22050 ,
23001 ,
23002 ,
23003 ,
23004 ,
23005 ,
23006 ,
23007 ,
23008 ,
23009 ,
23010 ,
23011 ,
23012 ,
23013 ,
23014 ,
23015 ,
23016 ,
23017 ,
23018 ,
23019 ,
23020 ,
23021 ,
23022 ,
23023 ,
23024 ,

6000 , 6000 , -99000
6000 , 6000 , -100000-6000 , 6000 , -51000-6000 , 6000 , -52000-6000 , 6000 , -53000-6000 , 6000 , -54000-6000 , 6000 , -55000-6000 , 6000 , -56000-6000 , 6000 , -57000-6000 , 6000 , -58000-6000 , 6000 , -59000-6000 , 6000 , -60000-6000 , 6000 , -61000-6000 , 6000 , -62000-6000 , 6000 , -63000-6000 , 6000 , -64000-6000 , 6000 , -65000-6000 , 6000 , -66000-6000 , 6000 , -67000-6000 , 6000 , -68000-6000 , 6000 , -69000-6000 , 6000 , -70000-6000 , 6000 , -71000-6000 , 6000 , -72000-6000 , 6000 , -73000-6000 , 6000 , -74000-6000 , 6000 , -75000-6000 , 6000 , -76000-6000 , 6000 , -77000-6000 , 6000 , -78000-6000 , 6000 , -79000-6000 , 6000 , -80000-6000 , 6000 , -81000-6000 , 6000 , -82000-6000 , 6000 , -83000-6000 , 6000 , -84000-6000 , 6000 , -85000-6000 , 6000 , -86000-6000 , 6000 , -87000-6000 , 6000 , -88000-6000 , 6000 , -89000-6000 , 6000 , -90000-6000 , 6000 , -91000-6000 , 6000 , -92000-6000 , 6000 , -93000-6000 , 6000 , -94000-6000 , 6000 , -95000-6000 , 6000 , -96000-6000 , 6000 , -97000-6000 , 6000 , -98000-6000 , 6000 , -99000-6000 , 6000 , -100000
6000 , -6000 , -51000
6000 , -6000 , -52000
6000 , -6000 , -53000
6000 , -6000 , -54000
6000 , -6000 , -55000
6000 , -6000 , -56000
6000 , -6000 , -57000
6000 , -6000 , -58000
6000 , -6000 , -59000
6000 , -6000 , -60000
6000 , -6000 , -61000
6000 , -6000 , -62000
6000 , -6000 , -63000
6000 , -6000 , -64000
6000 , -6000 , -65000
6000 , -6000 , -66000
6000 , -6000 , -67000
6000 , -6000 , -68000
6000 , -6000 , -69000
6000 , -6000 , -70000
6000 , -6000 , -71000
6000 , -6000 , -72000
6000 , -6000 , -73000
6000 , -6000 , -74000

123

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

23025 ,
23026 ,
23027 ,
23028 ,
23029 ,
23030 ,
23031 ,
23032 ,
23033 ,
23034 ,
23035 ,
23036 ,
23037 ,
23038 ,
23039 ,
23040 ,
23041 ,
23042 ,
23043 ,
23044 ,
23045 ,
23046 ,
23047 ,
23048 ,
23049 ,
23050 ,
24001 ,
24002 ,
24003 ,
24004 ,
24005 ,
24006 ,
24007 ,
24008 ,
24009 ,
24010 ,
24011 ,
24012 ,
24013 ,
24014 ,
24015 ,
24016 ,
24017 ,
24018 ,
24019 ,
24020 ,
24021 ,
24022 ,
24023 ,
24024 ,
24025 ,
24026 ,
24027 ,
24028 ,
24029 ,
24030 ,
24031 ,
24032 ,
24033 ,
24034 ,
24035 ,
24036 ,
24037 ,
24038 ,
24039 ,
24040 ,
24041 ,
24042 ,
24043 ,
24044 ,
24045 ,
24046 ,
24047 ,
24048 ,
24049 ,
24050 ,

6000 , -6000 , -75000
6000 , -6000 , -76000
6000 , -6000 , -77000
6000 , -6000 , -78000
6000 , -6000 , -79000
6000 , -6000 , -80000
6000 , -6000 , -81000
6000 , -6000 , -82000
6000 , -6000 , -83000
6000 , -6000 , -84000
6000 , -6000 , -85000
6000 , -6000 , -86000
6000 , -6000 , -87000
6000 , -6000 , -88000
6000 , -6000 , -89000
6000 , -6000 , -90000
6000 , -6000 , -91000
6000 , -6000 , -92000
6000 , -6000 , -93000
6000 , -6000 , -94000
6000 , -6000 , -95000
6000 , -6000 , -96000
6000 , -6000 , -97000
6000 , -6000 , -98000
6000 , -6000 , -99000
6000 , -6000 , -100000-6000 , -6000 , -51000-6000 , -6000 , -52000-6000 , -6000 , -53000-6000 , -6000 , -54000-6000 , -6000 , -55000-6000 , -6000 , -56000-6000 , -6000 , -57000-6000 , -6000 , -58000-6000 , -6000 , -59000-6000 , -6000 , -60000-6000 , -6000 , -61000-6000 , -6000 , -62000-6000 , -6000 , -63000-6000 , -6000 , -64000-6000 , -6000 , -65000-6000 , -6000 , -66000-6000 , -6000 , -67000-6000 , -6000 , -68000-6000 , -6000 , -69000-6000 , -6000 , -70000-6000 , -6000 , -71000-6000 , -6000 , -72000-6000 , -6000 , -73000-6000 , -6000 , -74000-6000 , -6000 , -75000-6000 , -6000 , -76000-6000 , -6000 , -77000-6000 , -6000 , -78000-6000 , -6000 , -79000-6000 , -6000 , -80000-6000 , -6000 , -81000-6000 , -6000 , -82000-6000 , -6000 , -83000-6000 , -6000 , -84000-6000 , -6000 , -85000-6000 , -6000 , -86000-6000 , -6000 , -87000-6000 , -6000 , -88000-6000 , -6000 , -89000-6000 , -6000 , -90000-6000 , -6000 , -91000-6000 , -6000 , -92000-6000 , -6000 , -93000-6000 , -6000 , -94000-6000 , -6000 , -95000-6000 , -6000 , -96000-6000 , -6000 , -97000-6000 , -6000 , -98000-6000 , -6000 , -99000-6000 , -6000 , -100000

124

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

*Element, type=B31
1001,
63, 1001
1011, 1001, 1011
1021, 1011, 1021
1031, 1021, 1031
1041, 1031, 1041
1051, 1041, 1051
1061, 1051, 1061
1071, 1061, 1071
10010,
1,
210020,
2,
310030,
3,
410050,
6,
710060,
7,
8
10070,
8,
910041,
4,
10041
10042,
10041,
10042
10043,
10042,
10043
10044,
10043,
10044
10045,
10044,
10045
10046,
10045,
10046
10047,
10046,
10047
10048,
10047,
510081,
9, 10081
10082, 10081, 10082
10083, 10082, 10083
10084, 10083, 10084
10085, 10084, 10085
10086, 10085, 10086
10087, 10086, 10087
10088, 10087,
1010090,
11,
12
10100,
12,
13
10110,
13,
14
10121,
14, 10121
10122, 10121, 10122
10123, 10122, 10123
10124, 10123, 10124
10125, 10124, 10125
10126, 10125, 10126
10127, 10126, 10127
10128, 10127,
15
10130,
16,
17
10140,
17,
18
10150,
18,
19
10161,
19, 10161
10162, 10161, 10162
10163, 10162, 10163
10164, 10163, 10164
10165, 10164, 10165
10166, 10165, 10166
10167, 10166, 10167
10168, 10167,
20
10171,
5, 1017110172, 10171, 10172
10173, 10172, 10173
10174, 10173, 10174
10175, 10174, 10175
10176, 10175, 10176
10177, 10176, 10177
10178, 10177,
21
10181,
21, 10181
10182, 10181, 10182
10183, 10182, 10183
10184, 10183, 10184
10185, 10184, 10185
10186, 10185, 10186
10187, 10186, 10187
10188, 10187,
22
10191,
22, 10191
10192, 10191, 10192
10193, 10192, 10193
10194, 10193, 10194
10195, 10194, 10195
10196, 10195, 10196
10197, 10196, 10197

125This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10198, 10197,
2310200,
23,
24
10211,
10, 10211
10212, 10211, 10212
10213, 10212, 10213
10214, 10213, 10214
10215, 10214, 10215
10216, 10215, 10216
10217, 10216, 10217
10218, 10217,
25
10221,
25, 10221
10222, 10221, 10222
10223, 10222, 10223
10224, 10223, 10224
10225, 10224, 10225
10226, 10225, 10226
10227, 10226, 10227
10228, 10227,
26
10231,
26, 10231
10232, 10231, 10232
10233, 10232, 10233
10234, 10233, 10234
10235, 10234, 10235
10236, 10235, 10236
10237, 10236, 10237
10238, 10237,
27
10240,
27,
28
10251,
15, 10251
10252, 10251, 10252
10253, 10252, 10253
10254, 10253, 10254
10255, 10254, 10255
10256, 10255, 10256
10257, 10256, 10257
10258, 10257,
2910261,
29, 10261
10262, 10261, 10262
10263, 10262, 10263
10264, 10263, 10264
10265, 10264, 10265
10266, 10265, 10266
10267, 10266, 10267
10268, 10267,
30
10271,
30, 10271
10272, 10271, 10272
10273, 10272, 10273
10274, 10273, 10274
10275, 10274, 10275
10276, 10275, 10276
10277, 10276, 10277
10278, 10277,
3110280,
31,
32
10291,
20, 10291
10292, 10291, 10292
10293, 10292, 10293
10294, 10293, 10294
10295, 10294, 10295
10296, 10295, 10296
10297, 10296, 10297
10298, 10297,
33
10301,
33, 10301
10302, 10301, 10302
10303, 10302, 10303
10304, 10303, 10304
10305, 10304, 10305
10306, 10305, 10306
10307, 10306, 10307
10308, 10307,
3410311,
34, 10311
10312, 10311, 10312
10313, 10312, 10313
10314, 10313, 10314
10315, 10314, 10315
10316, 10315, 10316
10317, 10316, 10317
10318, 10317,
35

126This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10320,35,3610371,
3, 10371
10372, 10371, 10372
10373, 10372, 10373
10374, 10373, 10374
10375, 10374, 10375
10376, 10375, 10376
10377, 10376, 10377
10378, 10377,
810381,
8, 10381
10382, 10381, 10382
10383, 10382, 10383
10384, 10383, 10384
10385, 10384, 10385
10386, 10385, 10386
10387, 10386, 10387
10388, 10387,
1310391,
13, 10391
10392, 10391, 10392
10393, 10392, 10393
10394, 10393, 10394
10395, 10394, 10395
10396, 10395, 10396
10397, 10396, 10397
10398, 10397,
18
10401,
18, 10401
10402, 10401, 10402
10403, 10402, 10403
10404, 10403, 10404
10405, 10404, 10405
10406, 10405, 10406
10407, 10406, 10407
10408, 10407,
310411,
4, 10411
10412, 10411, 10412
10413, 10412, 10413
10414, 10413,
41
10421,
41, 10421
10422, 10421, 10422
10423, 10422, 10423
10424, 10423,
20
10431,
19, 10431
10432, 10431, 10432
10433, 10432, 10433
10434, 10433,
4110441,
41, 10441
10442, 10441, 10442
10443, 10442, 10443
10444, 10443,
510451,
9, 10451
10452, 10451, 10452
10453, 10452, 10453
10454, 10453,
4210461,
42, 10461
10462, 10461, 10462
10463, 10462, 10463
10464, 10463,
1510471,
14, 10471
10472, 10471, 10472
10473, 10472, 10473
10474, 10473,
4210481,
42, 10481
10482, 10481, 10482
10483, 10482, 10483
10484, 10483,
1010491,
4, 10491
10492, 10491, 10492
10493, 10492, 10493
10494, 10493,
43
10501,
43, 10501
10502, 10501, 10502
10503, 10502, 10503
10504, 10503,
1010511,
9, 10511
10512, 10511, 10512
10513, 10512, 10513

127

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10514, 10513,
43
10521,
43, 10521
10522, 10521, 10522
10523, 10522, 10523
10524, 10523,
510531,
19, 10531
10532, 10531, 10532
10533, 10532, 10533
10534, 10533,
4410541,
44, 10541
10542, 10541, 10542
10543, 10542, 10543
10544, 10543,
1510551,
14, 10551
10552, 10551, 10552
10553, 10552, 10553
10554, 10553,
4410561,
44, 10561
10562, 10561, 10562
10563, 10562, 10563
10564, 10563,
20
10571,
5, 10571
10572, 10571, 10572
10573, 10572, 10573
10574, 10573,
4510581,
45, 10581
10582, 10581, 10582
10583, 10582, 10583
10584, 10583,
33
10591,
20, 10591
10592, 10591, 10592
10593, 10592, 10593
10594, 10593,
4510601,
45, 10601
10602, 10601, 10602
10603, 10602, 10603
10604, 10603,
2110611,
10, 10611
10612, 10611, 10612
10613, 10612, 10613
10614, 10613,
46
10621,
46, 10621
10622, 10621, 10622
10623, 10622, 10623
10624, 10623,
2910631,
15, 10631
10632, 10631, 10632
10633, 10632, 10633
10634, 10633,
4610641,
46, 10641
10642, 10641, 10642
10643, 10642, 10643
10644, 10643,
25
10651,
5, 10651
10652, 10651, 10652
10653, 10652, 10653
10654, 10653,
4710661,
47, 10661
10662, 10661, 10662
10663, 10662, 10663
10664, 10663,
2510671,
10, 10671
10672, 10671, 10672
10673, 10672, 10673
10674, 10673,
4710681,
47, 10681
10682, 10681, 10682
10683, 10682, 10683
10684, 10683,
2110691,
20, 10691
10692, 10691, 10692
10693, 10692, 10693
10694, 10693,
48
10701,
48, 10701
10702, 10701, 10702
10703, 10702, 10703

128

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10704, 10703,
2910711,
15, 10711
10712, 10711, 10712
10713, 10712, 10713
10714, 10713,
48
10721,
48, 10721
10722, 10721, 10722
10723, 10722, 10723
10724, 10723,
33
10731,
21, 10731
10732, 10731, 10732
10733, 10732, 10733
10734, 10733,
49
10741,
49, 10741
10742, 10741, 10742
10743, 10742, 10743
10744, 10743,
34
10751,
33, 10751
10752, 10751, 10752
10753, 10752, 10753
10754, 10753,
49
10761,
49, 10761
10762, 10761, 10762
10763, 10762, 10763
10764, 10763,
22
10771,
25, 10771
10772, 10771, 10772
10773, 10772, 10773
10774, 10773,
50
10781,
50, 10781
10782, 10781, 10782
10783, 10782, 10783
10784, 10783,
30
10791,
29, 10791
10792, 10791, 10792
10793, 10792, 10793
10794, 10793,
50
10801,
50, 10801
10802, 10801, 10802
10803, 10802, 10803
10804, 10803,
2610811,
21, 10811
10812, 10811, 10812
10813, 10812, 10813
10814, 10813,
51
10821,
51, 10821
10822, 10821, 10822
10823, 10822, 10823
10824, 10823,
2610831,
25, 10831
10832, 10831, 10832
10833, 10832, 10833
10834, 10833,
5110841,
51, 10841
10842, 10841, 10842
10843, 10842, 10843
10844, 10843,
2210851,
33, 10851
10852, 10851, 10852
10853, 10852, 10853
10854, 10853,
5210861,
52, 10861
10862, 10861, 10862
10863, 10862, 10863
10864, 10863,
3010871,
29, 10871
10872, 10871, 10872
10873, 10872, 10873
10874, 10873,
5210881,
52, 10881
10882, 10881, 10882
10883, 10882, 10883
10884, 10883,
3410891,
22, 10891
10892, 10891, 10892
10893, 10892, 10893

129

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10894, 10893,
53
10901,
53, 10901
10902, 10901, 10902
10903, 10902, 10903
10904, 10903,
3510911,
34, 10911
10912, 10911, 10912
10913, 10912, 10913
10914, 10913,
53
10921,
53, 10921
10922, 10921, 10922
10923, 10922, 10923
10924, 10923,
23
10931,
26, 10931
10932, 10931, 10932
10933, 10932, 10933
10934, 10933,
54
10941,
54, 10941
10942, 10941, 10942
10943, 10942, 10943
10944, 10943,
31
10951,
30, 10951
10952, 10951, 10952
10953, 10952, 10953
10954, 10953,
5410961,
54, 10961
10962, 10961, 10962
10963, 10962, 10963
10964, 10963,
27
10971,
22, 10971
10972, 10971, 10972
10973, 10972, 10973
10974, 10973,
55
10981,
55, 10981
10982, 10981, 10982
10983, 10982, 10983
10984, 10983,
27
10991,
26, 10991
10992, 10991, 10992
10993, 10992, 10993
10994, 10993,
55
11001,
55, 11001
11002, 11001, 11002
11003, 11002, 11003
11004, 11003,
23
11011,
34, 11011
11012, 11011, 11012
11013, 11012, 11013
11014, 11013,
56
11021,
56, 11021
11022, 11021, 11022
11023, 11022, 11023
11024, 11023,
31
11031,
30, 11031
11032, 11031, 11032
11033, 11032, 11033
11034, 11033,
56
11041,
56, 11041
11042, 11041, 11042
11043, 11042, 11043
11044, 11043,
35
11050,
24,
57
11060,
28,
58
11070,
32,
60
11080,
36,
59
20001,
61,
62
20002,
62,
63,
21001, 1, 21001
21002, 21001, 21002
21003, 21002, 21003
21004, 21003, 21004
21005, 21004, 21005
21006, 21005, 21006
21007, 21006, 21007
21008, 21007, 21008
21009, 21008, 21009

130This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

21010,21011,
21012,
21013,
21014,
21015,
21016,
21017,
21018,
21019,
21020,
21021,
21022,
21023,
21024,
21025,
21026,
21027,
21028,
21029,
21030,
21031,
21032,
21033,
21034,
21035,
21036,
21037,
21038,
21039,
21040,
21041,
21042,
21043,
21044,
21045,
21046,
21047,
21048,
21049,
21050,
22001,
22002,
22003,
22004,
22005,
22006,
22007,
22008,
22009,
22010,
22011,
22012,
22013,
22014,
22015,
22016,
22017,
22018,
22019,
22020,
22021,
22022,
22023,
22024,
22025,
22026,
22027,
22028,
22029,
22030,
22031,
22032,
22033,
22034,
22035,

21009, 21010
21010, 21011
21011, 21012
21012, 21013
21013, 21014
21014, 21015
21015, 21016
21016, 21017
21017, 21018
21018, 21019
21019, 21020
21020, 21021
21021, 21022
21022, 21023
21023, 21024
21024, 21025
21025, 21026
21026, 21027
21027, 21028
21028, 21029
21029, 21030
21030, 21031
21031, 21032
21032, 21033
21033, 21034
21034, 21035
21035, 21036
21036, 21037
21037, 21038
21038, 21039
21039, 21040
21040, 21041
21041, 21042
21042, 21043
21043, 21044
21044, 21045
21045, 21046
21046, 21047
21047, 21048
21048, 21049
21049, 21050
6, 22001
22001, 22002
22002, 22003
22003, 22004
22004, 22005
22005, 22006
22006, 22007
22007, 22008
22008, 22009
22009, 22010
22010, 22011
22011, 22012
22012, 22013
22013, 22014
22014, 22015
22015, 22016
22016, 22017
22017, 22018
22018, 22019
22019, 22020
22020, 22021
22021, 22022
22022, 22023
22023, 22024
22024, 22025
22025, 22026
22026, 22027
22027, 22028
22028, 22029
22029, 22030
22030, 22031
22031, 22032
22032, 22033
22033, 22034
22034, 22035

131

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

22036,22037,
22038,
22039,
22040,
22041,
22042,
22043,
22044,
22045,
22046,
22047,
22048,
22049,
22050,
23001,
23002,
23003,
23004,
23005,
23006,
23007,
23008,
23009,
23010,
23011,
23012,
23013,
23014,
23015,
23016,
23017,
23018,
23019,
23020,
23021,
23022,
23023,
23024,
23025,
23026,
23027,
23028,
23029,
23030,
23031,
23032,
23033,
23034,
23035,
23036,
23037,
23038,
23039,
23040,
23041,
23042,
23043,
23044,
23045,
23046,
23047,
23048,
23049,
23050,
24001,
24002,
24003,
24004,
24005,
24006,
24007,
24008,
24009,
24010,
24011,

22035, 22036
22036, 22037
22037, 22038
22038, 22039
22039, 22040
22040, 22041
22041, 22042
22042, 22043
22043, 22044
22044, 22045
22045, 22046
22046, 22047
22047, 22048
22048, 22049
22049, 22050
16, 23001
23001, 23002
23002, 23003
23003, 23004
23004, 23005
23005, 23006
23006, 23007
23007, 23008
23008, 23009
23009, 23010
23010, 23011
23011, 23012
23012, 23013
23013, 23014
23014, 23015
23015, 23016
23016, 23017
23017, 23018
23018, 23019
23019, 23020
23020, 23021
23021, 23022
23022, 23023
23023, 23024
23024, 23025
23025, 23026
23026, 23027
23027, 23028
23028, 23029
23029, 23030
23030, 23031
23031, 23032
23032, 23033
23033, 23034
23034, 23035
23035, 23036
23036, 23037
23037, 23038
23038, 23039
23039, 23040
23040, 23041
23041, 23042
23042, 23043
23043, 23044
23044, 23045
23045, 23046
23046, 23047
23047, 23048
23048, 23049
23049, 23050
11, 24001
24001, 24002
24002, 24003
24003, 24004
24004, 24005
24005, 24006
24006, 24007
24007, 24008
24008, 24009
24009, 24010
24010, 24011

132

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24012, 24011, 24012
24013, 24012, 24013
24014, 24013, 24014
24015, 24014, 24015
24016, 24015, 24016
24017, 24016, 24017
24018, 24017, 24018
24019, 24018, 24019
24020, 24019, 24020
24021, 24020, 24021
24022, 24021, 24022
24023, 24022, 24023
24024, 24023, 24024
24025, 24024, 24025
24026, 24025, 24026
24027, 24026, 24027
24028, 24027, 24028
24029, 24028, 24029
24030, 24029, 24030
24031, 24030, 24031
24032, 24031, 24032
24033, 24032, 24033
24034, 24033, 24034
24035, 24034, 24035
24036, 24035, 24036
24037, 24036, 24037
24038, 24037, 24038
24039, 24038, 24039
24040, 24039, 24040
24041, 24040, 24041
24042, 24041, 24042
24043, 24042, 24043
24044, 24043, 24044
24045, 24044, 24045
24046, 24045, 24046
24047, 24046, 24047
24048, 24047, 24048
24049, 24048, 24049
24050, 24049, 24050*Element, TYPE=SPRING1, ELSET=SPR_xdir1
31001, 21001
32001, 22001
33001, 23001
34001, 24001*Element, TYPE=SPRING1, ELSET=SPR_xdir2
31002, 21002
32002, 22002
33002, 23002
34002, 24002*Element, TYPE=SPRING1, ELSET=SPR_xdir3
31003, 21003
32003, 22003
33003, 23003
34003, 24003*Element, TYPE=SPRING1, ELSET=SPR_xdir4
31004, 21004
32004, 22004
33004, 23004
34004, 24004*Element, TYPE=SPRING1, ELSET=SPR_xdir5
31005, 21005
32005, 22005
33005, 23005
34005, 24005*Element, TYPE=SPRING1, ELSET=SPR_xdir6
31006, 21006
32006, 22006
33006, 23006
34006, 24006*Element, TYPE=SPRING1, ELSET=SPR_xdir7
31007, 21007
32007, 22007
33007, 23007
34007, 24007*Element, TYPE=SPRING1, ELSET=SPR_xdir8
31008, 21008

133

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

32008, 22008
33008, 23008
34008, 24008*Element, TYPE=SPRING1, ELSET=SPR_xdir931009, 21009
32009, 22009
33009, 23009
34009, 24009*Element, TYPE=SPRING1, ELSET=SPR_xdir10
31010, 21010
32010, 22010
33010, 23010
34010, 24010*Element, TYPE=SPRING1, ELSET=SPR_xdir11
31011, 21011
32011, 22011
33011, 23011
34011, 24011*Element, TYPE=SPRING1, ELSET=SPR_xdir12
31012, 21012
32012, 22012
33012, 23012
34012, 24012*Element, TYPE=SPRING1, ELSET=SPR_xdir13
31013, 21013
32013, 22013
33013, 23013
34013, 24013*Element, TYPE=SPRING1, ELSET=SPR_xdir14
31014, 21014
32014, 22014
33014, 23014
34014, 24014*Element, TYPE=SPRING1, ELSET=SPR_xdir15
31015, 21015
32015, 22015
33015, 23015
34015, 24015*Element, TYPE=SPRING1, ELSET=SPR_xdir16
31016, 21016
32016, 22016
33016, 23016
34016, 24016*Element, TYPE=SPRING1, ELSET=SPR_xdir17
31017, 21017
32017, 22017
33017, 23017
34017, 24017*Element, TYPE=SPRING1, ELSET=SPR_xdir18
31018, 21018
32018, 22018
33018, 23018
34018, 24018*Element, TYPE=SPRING1, ELSET=SPR_xdir19
31019, 21019
32019, 22019
33019, 23019
34019, 24019*Element, TYPE=SPRING1, ELSET=SPR_xdir20
31020, 21020
32020, 22020
33020, 23020
34020, 24020*Element, TYPE=SPRING1, ELSET=SPR_xdir21
31021, 21021
32021, 22021
33021, 23021
34021, 24021*Element, TYPE=SPRING1, ELSET=SPR_xdir22
31022, 21022
32022, 22022
33022, 23022
34022, 24022*Element, TYPE=SPRING1, ELSET=SPR_xdir23
31023, 21023
32023, 22023

134

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33023, 23023
34023, 24023*Element, TYPE=SPRING1, ELSET=SPR_xdir24
31024, 21024
32024, 22024
33024, 23024
34024, 24024*Element, TYPE=SPRING1, ELSET=SPR_xdir25
31025, 21025
32025, 22025
33025, 23025
34025, 24025*Element, TYPE=SPRING1, ELSET=SPR_xdir26
31026, 21026
32026, 22026
33026, 23026
34026, 24026*Element, TYPE=SPRING1, ELSET=SPR_xdir27
31027, 21027
32027, 22027
33027, 23027
34027, 24027*Element, TYPE=SPRING1, ELSET=SPR_xdir28
31028, 21028
32028, 22028
33028, 23028
34028, 24028*Element, TYPE=SPRING1, ELSET=SPR_xdir29
31029, 21029
32029, 22029
33029, 23029
34029, 24029*Element, TYPE=SPRING1, ELSET=SPR_xdir30
31030, 21030
32030, 22030
33030, 23030
34030, 24030*Element, TYPE=SPRING1, ELSET=SPR_xdir31
31031, 21031
32031, 22031
33031, 23031
34031, 24031*Element, TYPE=SPRING1, ELSET=SPR_xdir32
31032, 21032
32032, 22032
33032, 23032
34032, 24032*Element, TYPE=SPRING1, ELSET=SPR_xdir33
31033, 21033
32033, 22033
33033, 23033
34033, 24033*Element, TYPE=SPRING1, ELSET=SPR_xdir34
31034, 21034
32034, 22034
33034, 23034
34034, 24034*Element, TYPE=SPRING1, ELSET=SPR_xdir35
31035, 21035
32035, 22035
33035, 23035
34035, 24035*Element, TYPE=SPRING1, ELSET=SPR_xdir36
31036, 21036
32036, 22036
33036, 23036
34036, 24036*Element, TYPE=SPRING1, ELSET=SPR_xdir37
31037, 21037
32037, 22037
33037, 23037
34037, 24037*Element, TYPE=SPRING1, ELSET=SPR_xdir38
31038, 21038
32038, 22038
33038, 23038

135This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

34038, 24038*Element, TYPE=SPRING1, ELSET=SPR_xdir39
31039, 21039
32039, 22039
33039, 23039
34039, 24039*Element, TYPE=SPRING1, ELSET=SPR_xdir40
31040, 21040
32040, 22040
33040, 23040
34040, 24040*Element, TYPE=SPRING1, ELSET=SPR_xdir41
31041, 21041
32041, 22041
33041, 23041
34041, 24041*Element, TYPE=SPRING1, ELSET=SPR_xdir42
31042, 21042
32042, 22042
33042, 23042
34042, 24042*Element, TYPE=SPRING1, ELSET=SPR_xdir4331043, 21043
32043, 22043
33043, 23043
34043, 24043*Element, TYPE=SPRING1, ELSET=SPR_xdir44
31044, 21044
32044, 22044
33044, 23044
34044, 24044*Element, TYPE=SPRING1, ELSET=SPR_xdir45
31045, 21045
32045, 22045
33045, 23045
34045, 24045*Element, TYPE=SPRING1, ELSET=SPR_xdir46
31046, 21046
32046, 22046
33046, 23046
34046, 24046*Element, TYPE=SPRING1, ELSET=SPR_xdir47
31047, 21047
32047, 22047
33047, 23047
34047, 24047*Element, TYPE=SPRING1, ELSET=SPR_xdir48
31048, 21048
32048, 22048
33048, 23048
34048, 24048*Element, TYPE=SPRING1, ELSET=SPR_xdir49
31049, 21049
32049, 22049
33049, 23049
34049, 24049*Element, TYPE=SPRING1, ELSET=SPR_xdir50
31050, 21050
32050, 22050
33050, 23050
34050, 24050*Element, TYPE=SPRING1, ELSET=SPR_ydir1
41001, 21001
42001, 22001
43001, 23001
44001, 24001*Element, TYPE=SPRING1, ELSET=SPR_ydir2
41002, 21002
42002, 22002
43002, 23002
44002, 24002*Element, TYPE=SPRING1, ELSET=SPR_ydir3
41003, 21003
42003, 22003
43003, 23003
44003, 24003

136

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*Element, TYPE=SPRING1, ELSET=SPR_ydir441004, 21004
42004, 22004
43004, 23004
44004, 24004*Element, TYPE=SPRING1, ELSET=SPR_ydir541005, 21005
42005, 22005
43005, 23005
44005, 24005*Element, TYPE=SPRING1, ELSET=SPR_ydir641006, 21006
42006, 22006
43006, 23006
44006, 24006*Element, TYPE=SPRING1, ELSET=SPR_ydir7
41007, 21007
42007, 22007
43007, 23007
44007, 24007*Element, TYPE=SPRING1, ELSET=SPR_ydir841008, 21008
42008, 22008
43008, 23008
44008, 24008*Element, TYPE=SPRING1, ELSET=SPR_ydir941009, 21009
42009, 22009
43009, 23009
44009, 24009*Element, TYPE=SPRING1, ELSET=SPR_ydir10
41010, 21010
42010, 22010
43010, 23010
44010, 24010*Element, TYPE=SPRING1, ELSET=SPR_ydir11
41011, 21011
42011, 22011
43011, 23011
44011, 24011*Element, TYPE=SPRING1, ELSET=SPR_ydir12
41012, 21012
42012, 22012
43012, 23012
44012, 24012*Element, TYPE=SPRING1, ELSET=SPR_ydir13
41013, 21013
42013, 22013
43013, 23013
44013, 24013*Element, TYPE=SPRING1, ELSET=SPR_ydir14
41014, 21014
42014, 22014
43014, 23014
44014, 24014*Element, TYPE=SPRING1, ELSET=SPR_ydir15
41015, 21015
42015, 22015
43015, 23015
44015, 24015*Element, TYPE=SPRING1, ELSET=SPR_ydir16
41016, 21016
42016, 22016
43016, 23016
44016, 24016*Element, TYPE=SPRING1, ELSET=SPR_ydir17
41017, 21017
42017, 22017
43017, 23017
44017, 24017*Element, TYPE=SPRING1, ELSET=SPR_ydir18
41018, 21018
42018, 22018
43018, 23018
44018, 24018*Element, TYPE=SPRING1, ELSET=SPR_ydir19

137

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

41019, 21019
42019, 22019
43019, 23019
44019, 24019*Element, TYPE=SPRING1, ELSET=SPR_ydir20
41020, 21020
42020, 22020
43020, 23020
44020, 24020*Element, TYPE=SPRING1, ELSET=SPR_ydir21
41021, 21021
42021, 22021
43021, 23021
44021, 24021*Element, TYPE=SPRING1, ELSET=SPR_ydir22
41022, 21022
42022, 22022
43022, 23022
44022, 24022*Element, TYPE=SPRING1, ELSET=SPR_ydir23
41023, 21023
42023, 22023
43023, 23023
44023, 24023*Element, TYPE=SPRING1, ELSET=SPR_ydir24
41024, 21024
42024, 22024
43024, 23024
44024, 24024*Element, TYPE=SPRING1, ELSET=SPR_ydir25
41025, 21025
42025, 22025
43025, 23025
44025, 24025*Element, TYPE=SPRING1, ELSET=SPR_ydir26
41026, 21026
42026, 22026
43026, 23026
44026, 24026*Element, TYPE=SPRING1, ELSET=SPR_ydir27
41027, 21027
42027, 22027
43027, 23027
44027, 24027*Element, TYPE=SPRING1, ELSET=SPR_ydir28
41028, 21028
42028, 22028
43028, 23028
44028, 24028*Element, TYPE=SPRING1, ELSET=SPR_ydir29
41029, 21029
42029, 22029
43029, 23029
44029, 24029*Element, TYPE=SPRING1, ELSET=SPR_ydir30
41030, 21030
42030, 22030
43030, 23030
44030, 24030*Element, TYPE=SPRING1, ELSET=SPR_ydir31
41031, 21031
42031, 22031
43031, 23031
44031, 24031*Element, TYPE=SPRING1, ELSET=SPR_ydir32
41032, 21032
42032, 22032
43032, 23032
44032, 24032*Element, TYPE=SPRING1, ELSET=SPR_ydir33
41033, 21033
42033, 22033
43033, 23033
44033, 24033*Element, TYPE=SPRING1, ELSET=SPR_ydir34
41034, 21034

138

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

42034, 22034
43034, 23034
44034, 24034*Element, TYPE=SPRING1, ELSET=SPR_ydir35
41035, 21035
42035, 22035
43035, 23035
44035, 24035*Element, TYPE=SPRING1, ELSET=SPR_ydir36
41036, 21036
42036, 22036
43036, 23036
44036, 24036*Element, TYPE=SPRING1, ELSET=SPR_ydir37
41037, 21037
42037, 22037
43037, 23037
44037, 24037*Element, TYPE=SPRING1, ELSET=SPR_ydir38
41038, 21038
42038, 22038
43038, 23038
44038, 24038*Element, TYPE=SPRING1, ELSET=SPR_ydir39
41039, 21039
42039, 22039
43039, 23039
44039, 24039*Element, TYPE=SPRING1, ELSET=SPR_ydir40
41040, 21040
42040, 22040
43040, 23040
44040, 24040*Element, TYPE=SPRING1, ELSET=SPR_ydir41
41041, 21041
42041, 22041
43041, 23041
44041, 24041*Element, TYPE=SPRING1, ELSET=SPR_ydir42
41042, 21042
42042, 22042
43042, 23042
44042, 24042*Element, TYPE=SPRING1, ELSET=SPR_ydir43
41043, 21043
42043, 22043
43043, 23043
44043, 24043*Element, TYPE=SPRING1, ELSET=SPR_ydir44
41044, 21044
42044, 22044
43044, 23044
44044, 24044*Element, TYPE=SPRING1, ELSET=SPR_ydir45
41045, 21045
42045, 22045
43045, 23045
44045, 24045*Element, TYPE=SPRING1, ELSET=SPR_ydir46
41046, 21046
42046, 22046
43046, 23046
44046, 24046*Element, TYPE=SPRING1, ELSET=SPR_ydir47
41047, 21047
42047, 22047
43047, 23047
44047, 24047*Element, TYPE=SPRING1, ELSET=SPR_ydir48
41048, 21048
42048, 22048
43048, 23048
44048, 24048*Element, TYPE=SPRING1, ELSET=SPR_ydir49
41049, 21049
42049, 22049

139

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

43049, 23049
44049, 24049*Element, TYPE=SPRING1, ELSET=SPR_ydir50
41050, 21050
42050, 22050
43050, 23050
44050, 24050*Elset, elset=TP_BEAM
20001, 20002*Elset, elset=BEAM1
10371, 10372, 10373, 10374, 10375, 10376, 10377, 10378
10381, 10382, 10383, 10384, 10385, 10386, 10387, 10388
10391, 10392, 10393, 10394, 10395, 10396, 10397, 10398
10401, 10402, 10403, 10404, 10405, 10406, 10407, 10408
10411, 10412, 10413, 10414, 10421, 10422, 10423, 10424
10431, 10432, 10433, 10434, 10441, 10442, 10443, 10444
10451, 10452, 10453, 10454, 10461, 10462, 10463, 10464
10471, 10472, 10473, 10474, 10481, 10482, 10483, 10484
10491, 10492, 10493, 10494, 10501, 10502, 10503, 10504
10511, 10512, 10513, 10514, 10521, 10522, 10523, 10524
10531, 10532, 10533, 10534, 10541, 10542, 10543, 10544
10551, 10552, 10553, 10554, 10561, 10562, 10563, 10564
10571, 10572, 10573, 10574, 10581, 10582, 10583, 10584
10591, 10592, 10593, 10594, 10601, 10602, 10603, 10604
10611, 10612, 10613, 10614, 10621, 10622, 10623, 10624
10631, 10632, 10633, 10634, 10641, 10642, 10643, 10644
10651, 10652, 10653, 10654, 10661, 10662, 10663, 10664
10671, 10672, 10673, 10674, 10681, 10682, 10683, 10684
10691, 10692, 10693, 10694, 10701, 10702, 10703, 10704
10711, 10712, 10713, 10714, 10721, 10722, 10723, 10724
10731, 10732, 10733, 10734, 10741, 10742, 10743, 10744
10751, 10752, 10753, 10754, 10761, 10762, 10763, 10764
10771, 10772, 10773, 10774, 10781, 10782, 10783, 10784
10791, 10792, 10793, 10794, 10801, 10802, 10803, 10804
10811, 10812, 10813, 10814, 10821, 10822, 10823, 10824
10831, 10832, 10833, 10834, 10841, 10842, 10843, 10844
10851, 10852, 10853, 10854, 10861, 10862, 10863, 10864
10871, 10872, 10873, 10874, 10881, 10882, 10883, 10884
10891, 10892, 10893, 10894, 10901, 10902, 10903, 10904
10911, 10912, 10913, 10914, 10921, 10922, 10923, 10924
10931, 10932, 10933, 10934, 10941, 10942, 10943, 10944
10951, 10952, 10953, 10954, 10961, 10962, 10963, 10964
10971, 10972, 10973, 10974, 10981, 10982, 10983, 10984
10991, 10992, 10993, 10994, 11001, 11002, 11003, 11004
11011, 11012, 11013, 11014, 11021, 11022, 11023, 11024
11031, 11032, 11033, 11034, 11041, 11042, 11043, 11044*Elset, elset=BEAM2
10020, 10030, 10060, 10070, 10081, 10082, 10083, 10084
10085, 10086, 10087, 10088, 10100, 10110, 10121
10122, 10123, 10124, 10125, 10126, 10127, 10128, 10140
10150, 10161, 10162, 10163, 10164, 10165, 10166, 10167
10168, 10041, 10042, 10043, 10044, 10045, 10046, 10047
10048*Elset, elset=BEAM3
10171, 10172, 10173, 10174, 10175, 10176, 10177, 10178
10181, 10182, 10183, 10184, 10185, 10186, 10187, 10188
10191, 10192, 10193, 10194, 10195, 10196, 10197, 10198
10200, 10211, 10212, 10213, 10214, 10215, 10216, 10217
10218, 10221, 10222, 10223, 10224, 10225, 10226, 10227
10228, 10231, 10232, 10233, 10234, 10235, 10236, 10237
10238, 10240, 10251, 10252, 10253, 10254, 10255, 10256
10257, 10258, 10261, 10262, 10263, 10264, 10265, 10266
10267, 10268, 10271, 10272, 10273, 10274, 10275, 10276
10277, 10278, 10280, 10291, 10292, 10293, 10294, 10295
10296, 10297, 10298, 10301, 10302, 10303, 10304, 10305
10306, 10307, 10308, 10311, 10312, 10313, 10314, 10315
10316, 10317, 10318, 10320*Elset, elset=BEAM4, generate
11050, 11080,
10*Elset, elset=PILE, generate
10010, 10130,
40
21001, 21050,
1
22001, 22050,
123001, 23050,
124001, 24050,
1*Elset, elset=TW1

140

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1001,*Elset, elset=TW2
1011,*Elset, elset=TW3
1021,*Elset, elset=TW4
1031,*Elset, elset=TW5
1041,*Elset, elset=TW6
1051,*Elset, elset=TW7
1061,*Elset, elset=TW8
1071,*Nset, nset=TW_top_node
1071,*Nset, nset=TP_slave_node
24, 28, 32, 36, 57, 58, 59, 60, 61, 63*Nset, nset=X2S2
49, 50, 51, 52*Nset, nset=TP_master_node62,*Nset, nset=BC_node, generate
21050, 24050,
1000*SPRING, ELSET=SPR_xdir1, nonlinear
1-92700,-200-88460,-7-78678,-5-51463,-20,051463,
2
78678,
588460,
792700,200*SPRING, ELSET=SPR_xdir2, nonlinear1-241200,-200-229684,-9-203713,-6-132675,-30,0132675,3203713,6229684,9241200,200*SPRING, ELSET=SPR_xdir3, nonlinear
1-445500,-200-423651,-11-375082,-7-243627,-40,0243627,4375082,7423651,11445500,200*SPRING, ELSET=SPR_xdir4, nonlinear
1-547200,-200-525026,-17-470522,-11-311498,-60,0311498,6470522,11525026,17547200,200*SPRING, ELSET=SPR_xdir5, nonlinear
1-787500,-200-751842,-19-669132,-13-438120,
-6
0,
0

141

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438120,6669132,13751842,19787500,200*SPRING, ELSET=SPR_xdir6, nonlinear
1-198000,-525-336600,-315-475200,-105-330000,-350,0330000,35475200,105
336600,315
198000,525*SPRING, ELSET=SPR_xdir7, nonlinear
1-248500,-525-379850,-315-511200,-105-355000,-350,0355000,35511200,105
379850,315
248500,525*SPRING, ELSET=SPR_xdir8, nonlinear
1-2505600,-200-2380588,-20-2105253,-13-1365055,-70,01365055,72105253,13
2380588,202505600,
200*SPRING, ELSET=SPR_xdir9, nonlinear
1-3094200,-200-2940972,-22-2602129,-15-1688508,-70,01688508,7
2602129,15
2940972,223094200,
200*SPRING, ELSET=SPR_xdir10, nonlinear
1-3744000,-200-3559751,-24-3150933,-16-2045917,-80,02045917,83150933,163559751,24
3744000,
200*SPRING, ELSET=SPR_xdir11, nonlinear
1-3722400,-200-3537689,-29-3129671,-19-2030412,-100,02030412,103129671,193537689,293722400,
200*SPRING, ELSET=SPR_xdir12, nonlinear
1-4363200,-200-4166643,-32-3709493,-21-2430070,-11

142This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

0,02430070,113709493,21
4166643,324363200,
200*SPRING, ELSET=SPR_xdir13, nonlinear
1-5054400,-200-4821302,-34-4285850,-23-2801053,-110,02801053,114285850,23
4821302,345054400,
200*SPRING, ELSET=SPR_xdir14, nonlinear
1-5796000,-200-5523141,-36-4903174,-24-3197898,-120,03197898,124903174,245523141,36
5796000,
200*SPRING, ELSET=SPR_xdir15, nonlinear
1-6588000,-200-6272154,-38-5561459,-25-3620601,-130,03620601,
13
5561459,25
6272154,38
6588000,
200*SPRING, ELSET=SPR_xdir16, nonlinear
1-9417600,-200-8991304,-36-8002343,-24-5239773,-120,05239773,128002343,24
8991304,36
9417600,
200*SPRING, ELSET=SPR_xdir17, nonlinear
1-10557000,-200-10031500,-37-8872656,-25-5754420,-120,05754420,128872656,25
10031500,3710557000,
200*SPRING, ELSET=SPR_xdir18, nonlinear
1-11761200,-200-11179488,-39-9892261,-26-6419832,-130,06419832,
13
9892261,26
11179488,
39
11761200,
200*SPRING, ELSET=SPR_xdir19, nonlinear
1-13030200,-200-12389443,-41-10967137,
-27

143

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

-7121558,-140,07121558,
1410967137,
27
12389443,
4113030200,
200*SPRING, ELSET=SPR_xdir20, nonlinear
1-14363999,-200-13661364,-43-12097285,-29-7859598,-140,07859598,
1412097285,
2913661364,
43
14363999,
200*SPRING, ELSET=SPR_xdir21, nonlinear
1-15762598,-200-14995252,-45-13282704,-30-8633951,-150,08633951,1513282704,
30
14995252,45
15762598,
200*SPRING, ELSET=SPR_xdir22, nonlinear
1-17225995,-200-16391106,-47-14523394,-31-9444618,-160,09444618,1614523394,
31
16391106,47
17225995,
200*SPRING, ELSET=SPR_xdir23, nonlinear
1-18754190,-200-17848926,-49-15819354,-33-10291597,-160,010291597,
16
15819354,
33
17848926,
49
18754190,
200*SPRING, ELSET=SPR_xdir24, nonlinear
1-20347180,-200-19368712,-51-17170585,-34-11174891,-170,011174891,
17
17170585,
34
19368712,
51
20347180,
200*SPRING, ELSET=SPR_xdir25, nonlinear
1-22004963,-200-20950463,-53-18577087,-35-12094497,-180,012094497,
18
18577087,35
20950463,
53
22004963,
200*SPRING, ELSET=SPR_xdir26, nonlinear
1-23727534,-200-22594181,
-55

144

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

-20038858,-37-13050416,-180,013050416,
18
20038858,3722594181,55
23727534,
200*SPRING, ELSET=SPR_xdir27, nonlinear
1-25514888,-200-24299864,-57-21555900,-38-14042649,-190,014042649,
1921555900,
38
24299864,
57
25514888,
200*SPRING, ELSET=SPR_xdir28, nonlinear
1-27367015,-200-26067513,-59-23128212,-39-15071194,-200,015071194,20
23128212,39
26067513,
5927367015,
200*SPRING, ELSET=SPR_xdir29, nonlinear
1-29283903,-200-27897127,-61-24755794,-41-16136052,-200,016136052,
2024755794,
4127897127,61
29283903,
200*SPRING, ELSET=SPR_xdir30, nonlinear
1-31265537,-200-29788707,-63-26438646,-42-17237224,-210,017237224,
21
26438646,
4229788707,
63
31265537,
200*SPRING, ELSET=SPR_xdir31, nonlinear
1-33311896,-200-31651966,-64-27992780,-43-18152233,-210,018152233,
21
27992780,
4331651966,
6433311896,
200*SPRING, ELSET=SPR_xdir32, nonlinear
1-35422954,-200-33664837,-66-29780565,-44-19318982,-22
0,019318982,
2229780565,
44
33664837,
6635422954,
200*SPRING, ELSET=SPR_xdir33, nonlinear
1-37598676,
-200

145

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-35739673,-68-31623620,-45-20522045,-230,020522045,
23
31623620,
4535739673,
6837598676,
200*SPRING, ELSET=SPR_xdir34, nonlinear
1-39839023,-200-37876476,-70-33521946,-47-21761421,-230,021761421,
23
33521946,
4737876476,
70
39839023,
200*SPRING, ELSET=SPR_xdir35, nonlinear
1-42143944,-200-40075244,-72-35475543,-48-23037111,-240,023037111,
2435475543,
48
40075244,
72
42143944,
200*SPRING, ELSET=SPR_xdir36, nonlinear
1-44513381,-200-42335978,-74-37484409,-49-24349113,-250,024349113,25
37484409,
4942335978,7444513381,
200*SPRING, ELSET=SPR_xdir37, nonlinear
1-46947262,-200-44658677,-76-39548546,-51-25697429,-250,025697429,
25
39548546,
51
44658677,
76
46947262,
200*SPRING, ELSET=SPR_xdir38, nonlinear
1-49069898,-200-46639826,-77-41258491,-51-26764840,-260,026764840,
2641258491,
51
46639826,
77
49069898,
200*SPRING, ELSET=SPR_xdir39, nonlinear
1-50361212,-200-47867190,-77-42344241,-51-27469178,-260,027469178,26
42344241,51
47867190,
7750361212,
200*SPRING, ELSET=SPR_xdir40, nonlinear
1146

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

-51652525,-200-49094553,-77-43429991,-51-28173516,-260,028173516,
26
43429991,
51
49094553,
7751652525,
200*SPRING, ELSET=SPR_xdir41, nonlinear
1-52943838,-200-50321917,-77-44515740,-51-28877853,-260,028877853,
26
44515740,
51
50321917,
77
52943838,
200*SPRING, ELSET=SPR_xdir42, nonlinear
1-54235151,-200-51549281,-77-45601490,-51-29582191,-260,029582191,
26
45601490,
5151549281,
77
54235151,
200*SPRING, ELSET=SPR_xdir43, nonlinear
1-55526464,-200-52776645,-77-46687240,-51-30286529,-260,030286529,
26
46687240,
51
52776645,
77
55526464,
200*SPRING, ELSET=SPR_xdir44, nonlinear
1-56817777,-200-54004009,-77-47772990,-51-30990867,-260,030990867,26
47772990,
51
54004009,
77
56817777,
200*SPRING, ELSET=SPR_xdir45, nonlinear
1-58109090,-200-55231373,-77-48858739,-51-31695205,-260,031695205,
26
48858739,
51
55231373,
77
58109090,
200*SPRING, ELSET=SPR_xdir46, nonlinear
1-59400403,-200-56458736,-77-49944489,-51-32399543,-260,032399543,
2649944489,
51
56458736,
7759400403,
200*SPRING, ELSET=SPR_xdir47, nonlinear

147

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

1-60691717,-200-57686100,-77-51030239,-51-33103881,-260,033103881,
26
51030239,
51
57686100,77
60691717,
200*SPRING, ELSET=SPR_xdir48, nonlinear
1-61983030,-200-58913464,-77-52115989,-51-33808219,-260,033808219,
26
52115989,
51
58913464,
77
61983030,
200*SPRING, ELSET=SPR_xdir49, nonlinear
1-63274343,-200-60140828,-77-53201739,-51-34512556,-260,034512556,
26
53201739,
51
60140828,
7763274343,
200*SPRING, ELSET=SPR_xdir50, nonlinear
1-64565656,-200-61368192,-77-54287488,-51-35216894,-260,035216894,
26
54287488,
5161368192,77
64565656,
200*SPRING, ELSET=SPR_ydir1, nonlinear
2-92700,-200-88460,-7-78678,-5-51463,-20,051463,
2
78678,
588460,
792700,200*SPRING, ELSET=SPR_ydir2, nonlinear2-241200,-200-229684,-9-203713,-6-132675,-30,0132675,3203713,6229684,9241200,200*SPRING, ELSET=SPR_ydir3, nonlinear
2-445500,-200-423651,-11-375082,-7-243627,-40,0243627,4375082,7423651,11445500,200148This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

*SPRING, ELSET=SPR_ydir4, nonlinear
2-547200,-200-525026,-17-470522,-11-311498,-60,0311498,6470522,11525026,17547200,200*SPRING, ELSET=SPR_ydir5, nonlinear
2-787500,-200-751842,-19-669132,-13-438120,-60,0438120,6669132,13751842,19787500,200*SPRING, ELSET=SPR_ydir6, nonlinear
2-198000,-525-336600,-315-475200,-105-330000,-350,0330000,35475200,105
336600,315
198000,525*SPRING, ELSET=SPR_ydir7, nonlinear
2-248500,-525-379850,-315-511200,-105-355000,-350,0355000,35511200,105
379850,315
248500,525*SPRING, ELSET=SPR_ydir8, nonlinear
2-2505600,-200-2380588,-20-2105253,-13-1365055,-70,01365055,72105253,13
2380588,202505600,
200*SPRING, ELSET=SPR_ydir9, nonlinear
2-3094200,-200-2940972,-22-2602129,-15-1688508,-70,01688508,7
2602129,15
2940972,223094200,
200*SPRING, ELSET=SPR_ydir10, nonlinear
2-3744000,-200-3559751,-24-3150933,-16-2045917,-80,02045917,83150933,163559751,
24

149

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3744000,
200*SPRING, ELSET=SPR_ydir11, nonlinear
2-3722400,-200-3537689,-29-3129671,-19-2030412,-100,02030412,103129671,193537689,293722400,
200*SPRING, ELSET=SPR_ydir12, nonlinear
2-4363200,-200-4166643,-32-3709493,-21-2430070,-110,02430070,113709493,21
4166643,324363200,
200*SPRING, ELSET=SPR_ydir13, nonlinear
2-5054400,-200-4821302,-34-4285850,-23-2801053,-110,02801053,114285850,23
4821302,345054400,
200*SPRING, ELSET=SPR_ydir14, nonlinear
2-5796000,-200-5523141,-36-4903174,-24-3197898,-120,03197898,124903174,245523141,36
5796000,
200*SPRING, ELSET=SPR_ydir15, nonlinear
2-6588000,-200-6272154,-38-5561459,-25-3620601,-130,03620601,
13
5561459,25
6272154,38
6588000,
200*SPRING, ELSET=SPR_ydir16, nonlinear
2-9417600,-200-8991304,-36-8002343,-24-5239773,-120,05239773,128002343,24
8991304,36
9417600,
200
SPRING,ELSET=SPR_ydir17,
nonlinear*2-10557000,-200-10031500,-37-8872656,-25-5754420,-120,05754420,128872656,25

150

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

10031500,
37
10557000,
200*SPRING, ELSET=SPR_ydir18, nonlinear
2-11761200,-200-11179488,-39-9892261,-26-6419832,-130,06419832,
13
9892261,26
11179488,
39
11761200,
200*SPRING, ELSET=SPR_ydir19, nonlinear
2-13030200,-200-12389443,-41-10967137,-27-7121558,-140,07121558,
1410967137,
27
12389443,
4113030200,
200*SPRING, ELSET=SPR_ydir20, nonlinear
2-14363999,-200-13661364,-43-12097285,-29-7859598,-140,07859598,
1412097285,
2913661364,
43
14363999,
200*SPRING, ELSET=SPR_ydir21, nonlinear
2-15762598,-200-14995252,-45-13282704,-30-8633951,-150,08633951,1513282704,
30
14995252,45
15762598,
200*SPRING, ELSET=SPR_ydir22, nonlinear
2-17225995,-200-16391106,-47-14523394,-31-9444618,-160,09444618,1614523394,
31
16391106,47
17225995,
200*SPRING, ELSET=SPR_ydir23, nonlinear
2-18754190,-200-17848926,-49-15819354,-33-10291597,-160,010291597,
16
15819354,
33
17848926,
49
18754190,
200
SPRING,ELSET=SPR_ydir24,
nonlinear*2-20347180,-200-19368712,-51-17170585,-34-11174891,-170,011174891,
17

151This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

17170585,
34
19368712,
51
20347180,
200*SPRING, ELSET=SPR_ydir25, nonlinear
2-22004963,-200-20950463,-53-18577087,-35-12094497,-180,012094497,
18
18577087,35
20950463,
53
22004963,
200*SPRING, ELSET=SPR_ydir26, nonlinear
2-23727534,-200-22594181,-55-20038858,-37-13050416,-180,013050416,
18
20038858,3722594181,55
23727534,
200*SPRING, ELSET=SPR_ydir27, nonlinear
2-25514888,-200-24299864,-57-21555900,-38-14042649,-190,014042649,
1921555900,
38
24299864,
57
25514888,
200*SPRING, ELSET=SPR_ydir28, nonlinear
2-27367015,-200-26067513,-59-23128212,-39-15071194,-200,015071194,20
23128212,39
26067513,
5927367015,
200*SPRING, ELSET=SPR_ydir29, nonlinear
2-29283903,-200-27897127,-61-24755794,-41-16136052,-200,016136052,
2024755794,
4127897127,61
29283903,
200*SPRING, ELSET=SPR_ydir30, nonlinear
2-31265537,-200-29788707,-63-26438646,-42-17237224,-210,017237224,
21
26438646,
4229788707,
63
31265537,
200*SPRING, ELSET=SPR_ydir31, nonlinear
2-33311896,-200-31651966,-64-27992780,-43-18152233,
-21
0,
0

152

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

18152233,
2127992780,
4331651966,
6433311896,
200*SPRING, ELSET=SPR_ydir32, nonlinear
2-35422954,-200-33664837,-66-29780565,-44-19318982,-22
0,019318982,
2229780565,
44
33664837,
6635422954,
200*SPRING, ELSET=SPR_ydir33, nonlinear
2-37598676,-200-35739673,-68-31623620,-45-20522045,-230,020522045,
23
31623620,
4535739673,
6837598676,
200*SPRING, ELSET=SPR_ydir34, nonlinear
2-39839023,-200-37876476,-70-33521946,-47-21761421,-230,021761421,
23
33521946,
4737876476,
70
39839023,
200*SPRING, ELSET=SPR_ydir35, nonlinear
2-42143944,-200-40075244,-72-35475543,-48-23037111,-240,023037111,
2435475543,
48
40075244,
72
42143944,
200*SPRING, ELSET=SPR_ydir36, nonlinear
2-44513381,-200-42335978,-74-37484409,-49-24349113,-250,024349113,25
37484409,
4942335978,7444513381,
200*SPRING, ELSET=SPR_ydir37, nonlinear
2-46947262,-200-44658677,-76-39548546,-51-25697429,-250,025697429,
25
39548546,
51
44658677,
76
46947262,
200*SPRING, ELSET=SPR_ydir38, nonlinear
2-49069898,-200-46639826,-77-41258491,-51-26764840,
-26

153

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

0,026764840,
2641258491,
51
46639826,
77
49069898,
200*SPRING, ELSET=SPR_ydir39, nonlinear
2-50361212,-200-47867190,-77-42344241,-51-27469178,-260,027469178,26
42344241,51
47867190,
7750361212,
200*SPRING, ELSET=SPR_ydir40, nonlinear
2-51652525,-200-49094553,-77-43429991,-51-28173516,-260,028173516,
26
43429991,
51
49094553,
7751652525,
200*SPRING, ELSET=SPR_ydir41, nonlinear
2-52943838,-200-50321917,-77-44515740,-51-28877853,-260,028877853,
26
44515740,
51
50321917,
77
52943838,
200*SPRING, ELSET=SPR_ydir42, nonlinear
2-54235151,-200-51549281,-77-45601490,-51-29582191,-260,029582191,
26
45601490,
5151549281,
77
54235151,
200*SPRING, ELSET=SPR_ydir43, nonlinear
2-55526464,-200-52776645,-77-46687240,-51-30286529,-260,030286529,
26
46687240,
51
52776645,
77
55526464,
200*SPRING, ELSET=SPR_ydir44, nonlinear
2-56817777,-200-54004009,-77-47772990,-51-30990867,-260,030990867,26
47772990,
51
54004009,
77
56817777,
200*SPRING, ELSET=SPR_ydir45, nonlinear
2-58109090,-200-55231373,-77-48858739,
-51

154

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

-31695205,-260,031695205,
26
48858739,
51
55231373,
77
58109090,
200*SPRING, ELSET=SPR_ydir46, nonlinear
2-59400403,-200-56458736,-77-49944489,-51-32399543,-260,032399543,
2649944489,
51
56458736,
7759400403,
200*SPRING, ELSET=SPR_ydir47, nonlinear
2-60691717,-200-57686100,-77-51030239,-51-33103881,-260,033103881,
26
51030239,
51
57686100,77
60691717,
200*SPRING, ELSET=SPR_ydir48, nonlinear
2-61983030,-200-58913464,-77-52115989,-51-33808219,-260,033808219,
26
52115989,
51
58913464,
77
61983030,
200*SPRING, ELSET=SPR_ydir49, nonlinear
2-63274343,-200-60140828,-77-53201739,-51-34512556,-260,034512556,
26
53201739,
51
60140828,
7763274343,
200*SPRING, ELSET=SPR_ydir50, nonlinear2-64565656,-200-61368192,-77-54287488,-51-35216894,-260,035216894,
26
54287488,
5161368192,77
64565656,200********************************************* new sets for outputs at legs and braces********************************************Nset, nset=ZERO_POINT, generate
10741, 10881, 20*Elset, elset=LEG1_MEMB1
10271,*Elset, elset=LEG2_MEMB1
10261,*Elset, elset=LEG3_MEMB1
10251,*Elset, elset=LEG4_MEMB1
10121,*Elset, elset=BRA1_MEMB1
11031,

155

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

*Elset, elset=BRA2_MEMB1
10871,*Elset, elset=BRA3_MEMB1
10711,*Elset, elset=BRA4_MEMB1
10551,*Elset, elset=BRA1_MEMB2
10951,*Elset, elset=BRA2_MEMB2
10791,*Elset, elset=BRA3_MEMB2
10631,*Elset, elset=BRA4_MEMB2
10471,*Elset, elset=PILE_END
10050,** Section: Section-6-TW1 Profile: Profile-6*Beam Section, elset=TW1, material=STEEL, temperature=GRADIENTS, section=PIPE
2800., 32.
0.,-1.,0.
** Section: Section-7-TW2 Profile: Profile-7*Beam Section, elset=TW2, material=STEEL, temperature=GRADIENTS, section=PIPE
2788., 32.
0.,-1.,0.
** Section: Section-8-TW3 Profile: Profile-8*Beam Section, elset=TW3, material=STEEL, temperature=GRADIENTS, section=PIPE
2659., 30.
0.,-1.,0.
** Section: Section-9-TW4 Profile: Profile-9*Beam Section, elset=TW4, material=STEEL, temperature=GRADIENTS, section=PIPE
2541., 28.
0.,-1.,0.
** Section: Section-10-TW5 Profile: Profile-10*Beam Section, elset=TW5, material=STEEL, temperature=GRADIENTS, section=PIPE
2400., 24.
0.,-1.,0.
** Section: Section-11-TW6 Profile: Profile-11*Beam Section, elset=TW6, material=STEEL, temperature=GRADIENTS, section=PIPE
2282., 22.
0.,-1.,0.
** Section: Section-12-TW7 Profile: Profile-12*Beam Section, elset=TW7, material=STEEL, temperature=GRADIENTS, section=PIPE
2164., 30.
0.,-1.,0.
** Section: Section-13-TW8 Profile: Profile-13*Beam Section, elset=TW8, material=STEEL, temperature=GRADIENTS, section=PIPE
2059., 30.
0.,-1.,0.
** Section: Section-1-PILE Profile: Profile-1*Beam Section, elset=PILE, material=STEEL, temperature=GRADIENTS, section=PIPE
1041., 60.
0.,-1.,0.
** Section: Section-3-BEAM2 Profile: Profile-3*Beam Section, elset=BEAM2, material=STEEL, temperature=GRADIENTS, section=PIPE
600., 50.
0.,-1.,0.
** Section: Section-4-BEAM3 Profile: Profile-4*Beam Section, elset=BEAM3, material=STEEL, temperature=GRADIENTS, section=PIPE
600., 35.
0.,0.,-1.
** Section: Section-2-BEAM1 Profile: Profile-2*Beam Section, elset=BEAM1, material=STEEL, temperature=GRADIENTS, section=PIPE
400., 20.
0.,0.,-1.
** Section: Section-5-BEAM4 Profile: Profile-5*Beam Section, elset=BEAM4, material=STEEL, temperature=GRADIENTS, section=PIPE
600., 40.
0.,-1.,0.
** Section: Section-6-TP_BEAM Profile: Profile-6*Beam Section, elset=TP_BEAM, material=CONCRETE, temperature=GRADIENTS, section=RECT9600, 9600
0.,-1.,0.
*Element, type=MASS, elset=NAC_mass
50002, 1071
*Mass, elset=NAC_mass
350000.,156This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

*End Part** -------------------------------** ASSEMBLY** -------------------------------*Assembly, name=Assembly***Instance, name=PART-1-1, part=PART-1*End Instance*Nset, nset=TW_TOP, instance=PART-1-1
1071,*Nset, nset=TP_BOTTOM, instance=PART-1-1
61,*Nset, nset=JACKET_TOP, instance=PART-1-1
24,
28, 32, 36*Surface, type=NODE, name=TRANSITION_PIECE_BOTTOM
JACKET_TOP, 1.
** Constraint: TP_JACKET*Coupling, constraint name=TP_JACKET, ref node = TP_BOTTOM, surface=TRANSITION_PIECE_BOTTOM*Kinematic** Constraint: Constraint-2**MPC**TIE, PART-1-1.TP_slave_node, PART-1-1.TP_master_node*End Assembly** -------------------------------** MATERIALS** -------------------------------*Material, name=STEEL*Damping, beta=0.01*Density
7.85e-06,*Elastic
2.1e+08, 0.3*Material, name=RIGID_MASS*Damping, beta=0.01*Density
7.85e-06,*Elastic
2.9e+27, 0.0*Material, name=CONCRETE*Damping, alpha=3.18005, beta=0.216071*Density
1.806e-06,*Elastic
2.1e+08, 0.3** -------------------------------** Amplitude** -------------------------------*Amplitude, name=Fx_amp, INPUT=YawBrFxp.out*Amplitude, name=Fy_amp, INPUT=YawBrFyp.out*Amplitude, name=Fz_amp, INPUT=YawBrFzp.out*Amplitude, name=Mx_amp, INPUT=YawBrMxp.out*Amplitude, name=My_amp, INPUT=YawBrMyp.out*Amplitude, name=Mz_amp, INPUT=YawBrMzp.out** -------------------------------** BOUNDARY CONDITIONS** -------------------------------** Name: BC-1 Type: Symmetry/Antisymmetry/Encastre*Boundary**PART-1-1.BC_node, ENCASTRE
PART-1-1.BC_node, 3, 3**PART-1-1.BC_node, 2, 2
PART-1-1.BC_node, 6, 6** -------------------------------** Define Hydrodynamic load** -------------------------------*AQUA-50000, 0.0, 9800, 1026.05e-09*WAVE,TYPE=GRIDDED, DATA FILE=gridwave_3d_P1.binary
0.,0.,0.,1.,0.
**---------------------------------** STEP: dynamic analysis step**---------------------------------*Step, name=Step-2, nlgeom=YES, inc=400000*Dynamic, application=TRANSIENT FIDELITY**Dynamic
1,600,1e-08,0.10

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**---------------------------------** Wind LOADS**---------------------------------Type: Moment** Name: CFORCE-1*Cload, follower, amplitude=MZ_AMP
TW_TOP, 6, 0.0001
Type: Moment** Name: CFORCE-2*Cload, follower, amplitude=MY_AMP
TW_TOP, 5, 0.0001
Type: Moment** Name: CFORCE-3*Cload, follower, amplitude=MX_AMP
TW_TOP, 4, 0.0001
Type: Concentrated force** Name: CFORCE-4*Cload, follower, amplitude=FZ_AMP
TW_TOP, 3, 0.0001
Type: Concentrated force** Name: CFORCE-5*Cload, follower, amplitude=FY_AMP
TW_TOP, 2, 0.0001
Type: Concentrated force** Name: CFORCE-6*Cload, follower, amplitude=FX_AMP
TW_TOP, 1, 0.0001**---------------------------------** WAVE LOADS**---------------------------------*DLOAD, GRAV, 9800, 0., 0., -1.
*DLOAD
PART-1-1.BEAM1, FI, , 1000. , 2. , 0.
PART-1-1.BEAM2, FI, , 1400. , 2. , 0.
PART-1-1.BEAM3, FI, , 1400. , 2. , 0.
PART-1-1.BEAM4, FI, , 1400. , 2. , 0.
*DLOAD
PART-1-1.BEAM1, FDD, , 1000. , 1.
PART-1-1.BEAM2, FDD, , 1400. , 1.
PART-1-1.BEAM3, FDD, , 1400. , 1.
PART-1-1.BEAM4, FDD, , 1400. , 1.
**DLOAD**PART-1-1.BEAM1, PB, , 1000.
**PART-1-1.BEAM2, PB, , 1400.
**PART-1-1.BEAM3, PB, , 1400.
**PART-1-1.BEAM4, PB, , 1400.
**** OUTPUT REQUESTS****Restart, write, frequency=0**** FIELD OUTPUT: F-Output-2***OUTPUT,FIELD, Frequency=1*NODE OUTPUT, NSET=PART-1-1.BC_node
RF*NODE OUTPUT, NSET=PART-1-1.X2S2
U*ELEMENT OUTPUT, ELSET=PART-1-1.TW1
SF*NODE OUTPUT, NSET=PART-1-1.ZERO_POINTU*NODE OUTPUT, NSET=PART-1-1.TW_top_node
U*ELEMENT OUTPUT, ELSET=PART-1-1.LEG1_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.LEG2_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.LEG3_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.LEG4_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA1_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA2_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA3_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA4_MEMB1SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA1_MEMB2

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SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA2_MEMB2SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA3_MEMB2SF*ELEMENT OUTPUT, ELSET=PART-1-1.BRA4_MEMB2SF*ELEMENT OUTPUT, ELSET=PART-1-1.PILE_END
SF*End Step

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Appendix F. The University of Miami Coupled Model
for Combined Simulation of Hurricane Wind and Wave
FieldsSummary of University of Miami Work
This project aimed to develop a meteorologically-based simulation and design tool that addresses
uncertain risks to U.S. offshore wind farms from destructive wind and wave conditions in thehurricane-prone Gulf of Mexico and U.S. Eastern Seaboard wind energy development sites. This
process involves adapting a leading, coupled, atmosphere-wave-ocean model developed by the
research group at the University of Miami (UM) for hurricane research and prediction to provide
correlated wind and wave fields as input to the NREL-developed FAST turbine design tools. The
University of Miami Coupled Model (UMCM) has been configured to provide high-resolution
coupled model simulations of hurricanes for use in the analysis of wind and wave loads
conducted by the University of Texas (UT). We have completed the UMCM simulations of two
major hurricanes: Hurricane Ike (2008) over the Gulf of Mexico and Superstorm Sandy (2012)
over the U.S. Eastern Seaboard. The UMCM model output was provided to both NREL and UTgroups during the course of this project for studies of downscaling wind and wave effects toturbine scale. Documentation of the UMCM software and model output is included here. Thisappendix focuses on scientific results and model evaluation with observations of Hurricane Ike
and Superstorm Sandy.

Objectives
The main objectives of this work are to 1) configure and test the UMCM over the Gulf of
Mexico and the U.S. East Coast/Atlantic Seaboard for use in predicting wind turbine loads, 2)
conduct coupled atmosphere-wave-ocean model experiments using UMCM to better understandthe wind, surface waves, and ocean currents in hurricanes near landfall and their impacts on
offshore wind turbines, and 3) provide UMCM simulations of hurricanes over the Gulf of
Mexico and for downscaling studies at turbine and structural scales. Figure F1 shows aschematic of the coupled system and conceptual model for this project.
The UMCM was developed for research and prediction of marine and coastal weather systems
including tropical cyclones and winter storms. It is a fully coupled atmosphere-wave-ocean
model that consists of three model components: the Weather Research and Forecasting (WRF)model, the University of Miami Wave Model (UMWM), and the Hybrid Coordinate Ocean
Model (HYCOM). We have developed a unified air-sea interface module that couples multiple
atmosphere, wave, and ocean models using the Earth System Modeling Framework (ESMF). It
provides a physically based and computationally efficient coupling at the air-sea interface that is
flexible for use in a multi-model system and portable for transition to the next-generation
coupled atmosphere-wave/ocean-land models. The UMCM has been tested and evaluated using
the coupled air-sea observations collected in recent field campaigns in the Northern seas andGulf of Mexico and for tropical cyclones in the Atlantic and Pacific basins. The UMCM is used
to provide fully coupled model predictions of wind, ocean wave, and current fields as input toturbine design calculations.

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Figure F1. Schematic of the fully coupled atmosphere-wave-ocean modeling system University ofMiami Coupled Model that consists of WRF (atmospheric model), University of Miami Wave Model(wave model), and the Hybrid Coordinate Ocean Model (HYCOM) (ocean circulation model), as
well as the meteorological and oceanic variables in the coupled system

The development of the UMCM is based on basic coupled atmosphere-wave-ocean coupling
physics described in Chen et al. (2007, 2013). The latest version includes a standardized, unified,
air-sea coupling module, which provides routines that are compatible with different atmosphere,
wave and ocean component models. The development of the Earth System Modeling Framework(ESMF (Hill et al. 2004), a software library for geophysical model coupling, made the designand development of the unified air-sea coupled model feasible. ESMF provides the facilities forgrid and field data manipulation, as well as conventions for coupled model software design andparallel processing. The UMCM can be constructed using different atmosphere, wave, and ocean
circulation models, connected together through an ESMF coupling interface.

UMCM Component Model Descriptions
Atmosphere Model
The atmospheric model in UMCM is the Weather Research and Forecasting (WRF) model V3.5
with Advanced Research WRF (ARW) dynamical core (Skamarock et al. 2008). WRF is a stateof-the-art non-hydrostatic atmospheric model with a large number of model physics options anda storm-following, moving nest capability for hurricane forecasting. It is defined on a 12 km
horizontal resolution domain with 36 vertical levels and spans the area from 103.0 W to 55.0 W
in longitude, and from 7.0 N to 45.0 N in latitude. There are two square-shaped, vortexfollowing, inner nests of 4 km and 1.3 km horizontal resolution that are 2,000 km and 440 km
wide, respectively. The surface layer is based on Monin-Obukhov theory and the boundary layer
parameterization is based on the Yonsei University scheme (YSU, Hong et al. 2006). The cloud
microphysics is based on the single-moment 5-species scheme WSM5 (Hong et al. 2004), which
is used on 1.3 and 4 km nested domains. The Kain-Fritsch cumulus parameterization is based on
the 12 km domain (Kain and Fritsch 1993) in addition to WSM5. WRF passes the vertical wind
164This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

profile and air density to the wave model and radiative and heat fluxes and precipitation rate tothe ocean circulation model.
Ocean Surface Wave Model
The ocean wave model in UMCM is the University of Miami Wave Model (UMWM) V1.1.0(Donelan et al. 2012), a spectral ocean wave model that predicts wave energy spectra andatmosphere and ocean momentum fluxes based on input winds and ocean currents. UMWM is
initialized from a calm state, and the full wave development for the initial atmosphericconditions happens within 6 hours. The model covers the same domain as the WRF parent
domain, except that it is defined on a 4 km horizontal resolution. The wave energy spectrum isdefined on 36 directional bins and 37 frequency bins ranging from 0.0313 Hz to 2 Hz. UMWM
passes vectorial atmosphere stress to the atmosphere model, and vectorial ocean stress to theocean circulation model.
Ocean Circulation Model
The ocean circulation model in UMCM is the HYbrid Coordinate Ocean Model (HYCOM)
V2.2.34 (Wallcraft et al. 2009). It is a 3-dimensional hydrostatic ocean model with a hybrid
vertical coordinate, z-level in shallow water, terrain-following σ-coordinate in intermediatewater, and isopycnal (constant density) in deep water. In this study, we use the nonlocal Kprofile vertical-mixing scheme by Large et al. (1994). Its domain is defined on a 0.04 degree(deg) horizontal resolution grid that spans almost as large a domain as that of WRF and UMWM,
and with 32 vertical levels. In this region, the grid spacing of 0.04 deg corresponds to the spacing
between 3,250 m in the north, and 4,400 m in the south of the domain. Thus, the grid spacing
closely matches that of the UMWM grid and the WRF inner 4 km nest. HYCOM passes seasurface temperature to the atmosphere model and surface current field and water density to thewave model. The air-sea interface module is defined on an exchange grid that covers the WRF
and UMWM domains, at the horizontal resolution of 4 km. All fields are interpolated to theexchange grid, on which the calculation of air-sea exchange is defined, and are co-located indiscrete time. In the current model configuration, fields from WRF and UMWM are exchanged
every 60 seconds (s), whereas HYCOM fields are exchanged every 120 s.
Initial and Lateral Boundary Conditions
The WRF model initial and lateral boundary conditions are from the National Center for
Environmental Prediction (NCEP) Global Forecasting System (GFS) 6-hourly fields at 0.5 deghorizontal resolution. The initial and boundary conditions for the ocean model are provided by
the global, data-assimilated, 0.08 deg horizontal resolution daily HYCOM fields. Figure F2
shows an example of the UMCM domains and model forecast of Hurricane Sandy initialized by
the global GFS and HYCOM fields at 0000 UTC on 28 October 2012.

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Figure F2. UMCM model forecast of surface wind (left) and sea surface temperature andprecipitating cloud fields (right) for Hurricane Sandy at 0600 UTC on October 29, 2012

Combined Models
Each of the three component models in UMCM have separate origins and were originallydesigned to simulate their respective physical systems separately. The unified air-sea interface
serves not only as a coupler but also includes coupling computations related to air-sea heat,moisture, and momentum fluxes that are done consistently at each coupling time step. The
common grid is configured at the highest horizontal grid spacing of the three component models.
In the current coupling configuration, it is set to 1.3 km, which is consistent with WRF. The
UMWM and HYCOM grid resolution is at 4 km. The coupling time step for between theatmosphere-wave models is 1 minute and for the ocean model is 2 minutes.
The WRF model incorporates two-way interacting moving nests at an increasing resolution overa storm and which follows it as it moves. In the specific configuration used for simulations of
Hurricane Ike, the outermost domain has a 12 km horizontal resolution. This resolution provides
forcing for the lateral boundaries of a 4 km middle resolution domain, which in turn provides
forcing for the lateral boundaries of a moving 1.33 km fine-resolution domain centered over thehurricane using a vortex-tracking algorithm developed at the UM. The outermost domain of
WRF is initialized and forced using output from a global weather forecast model, typically the
National Weather Service’s GFS or the European Center’s Integrated Forecast System (IFS)models. The influence of observational data (from satellites, aircraft, etc.) has been incorporated
in the global forecast data. UMCM can also assimilate additional, more localized observational
data as it runs.

Completed Work at the University of Miami

UM group has completed the coupled atmosphere-wave-ocean model simulation of
Hurricane Ike (2008) and forecast of Superstorm Sandy (2012) using the University ofMiami Coupled Model (UMCM). UMCM has 1.3 km grid resolution for the atmosphereand 4 km for the wave and ocean model components. The UMCM full model fields
166

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(including all veridical levels and nested horizontal model grids) were made available at
an hourly output.


A site-specific, high-frequency model output at 1-minute intervals for 10 sites along theeastern seaboard selected by the UT group. This special model output was provided for
the UT group in support of their downscale modeling effort. The 1-min coupled model
output includes winds, ocean surface wave height, and 2-D wave spectra and othersurface variables. In addition to the wind and wave data, UM also provided the ocean
current profiles at each site for UT, which may be of value for estimating loads bothabove and below the ocean surface.

At NREL and UT request, we have also produced full model fields at 10-minute interval,
which is higher frequency than the normal 1-hour interval output. The full fields include
3D winds, temperature, humidity, significant wave height and wave periods, 3D ocean
currents, temperature, and so on. UM provided the full UMCM output to NREL for 1)
future research applications, 2) advanced visualization of high-resolution atmospherewave-ocean fields in hurricanes at NREL, and 3) open distribution online for users
outside NREL (see Appendix G).

Results
Superstorm Sandy (2012)
Superstorm Sandy formed as a tropical storm in the Caribbean Sea on 23 October 2012, and later
intensified into a Category 1 hurricane of the western Atlantic Ocean. It interacted with a strong
mid-latitude system and became a “superstorm” that made landfall over the U.S. northeastern
coastal region. UM conducted a UMCM forecast starting at 0000 UTC on 27 October 2012,using the NOAA GFS model forecast fields as the initial and lateral boundary conditions for
WRF and the global HYCOM forecast fields for the regional HYCOM in UMCM. Figure A3
shows the UMCM forecast storm track and intensity (red lines) compared with the National
Hurricane Center (NHC) best track data (black lines). Both the storm track and intensity were
well-forecasted by UMCM.

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Figure F3. The UMCM forecast (red) and National Hurricane Center best track data (black) of
Superstorm Sandy track (top left) and intensity (bottom left). Model forecast (red) and the National
Data Buoy Center (NDBC) buoy observation (black) of significant wave height (Hs), mean wave
period (MWP), wind speed (WSPD), sea-surface temperature (SST), and 2-m air temperature (Tair).

The UMCM is evaluated and verified with in-situ observations from the National Data Buoy
Center (NDBC) buoys. An example of the model verification against the buoy observation isshown in Figure F3. NDBC 41002 was near the center of Superstorm Sandy when the storm
passed the buoy location on 28 October 2012.
Hurricanes have major impacts on the coastal ocean and land when making landfall. The
characteristics of winds, surface waves, and ocean currents are shown in Figure A4. The storm
impacts are asymmetric around the storm. On the right side of the center, the wind is mostly
southeasterly and easterly onshore flow. The surface waves and sea surface height are the highest
when Sandy was making landfall on 30 October. On the left side, the wind changed direction
before and after landfall. The wave height peaked before the landfall and then decreased when
the wind became offshore at and after the landfall. The 2-D wave spectra shows that the sea
swells (long waves) dominated on the right side, whereas the wind-sea (short waves) and swellare both present on the left.

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Figure F4. UMCM forecasts of wind speed (red) and direction (black), significant wave height (red),sea level height (black), and 2-D wave spectra (color coded for power of wave spectrum and red
arrow represents wind vector) at three selected virtual turbine sites on the left, right, and near thecenter of Superstorm Sandy right before the landfall on 30 October 2012.

There is a significant vertical wind shear from the surface to the 200 m level in Superstorm
Sandy as shown in Figure F5. The wind speed varies from 25 to > 40 m s-1.

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Figure F5. The UMCM forecast of wind speed (color) near the center of the storm at location 03C(marked on the surface wind speed map in Figure F3). The black vectors indicate wind directions.

Hurricane Ike (2008)
The UMCM forecast fields in Hurricane Ike (2008) have been verified against the in situ
observations from the NDBC sites in the Gulf of Mexico during the hurricane passage in
September 2008. The fields of verification include 10-m surface wind speed (WSPD), sea levelpressure (SLP), surface air temperature (Ta), sea-surface temperature (SST), significant wave
height (SWH), and mean wave period (MWP). The site-specific comparisons are subject tostorm track forecast error. In order to evaluate hurricane-induced features, a storm-relative
approach with correction for track error is usually used for verification at sites within the storm
when it passed the site. Here we include examples from two nearshore sites that are outside of
the storm with an Earth-relative reference, and two within the storm along the Hurricane Ike pathwith a storm-relative comparison (Figures F6 through F10).

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Figure F6. Map of model storm track forecast compared with the National Hurricane Center (NHC)Best Track estimate and locations of the NDBC sites

Figure F7. Comparison of UMCM forecasts and NDBC Buoy 42001 data

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Figure F8. Comparison of UMCM forecasts and NDBC Buoy 42002 data

Figure F9. Comparison of UMCM forecasts and NDBC Buoy 42007 data

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Figure F10. Comparison of UMCM forecasts and NDBC Buoy 42020 data

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References
Chen, S. S., J. F. Price, W. Zhao, M. A. Donelan, and E. J. Walsh (2007), The CBLAST
Hurricane program and the next-generation fully coupled atmosphere-wave-ocean models for
hurricane research and prediction, Bull. American Meteor. Soc., 88, 311–317.
Chen, S. S., W. Zhao, M. A. Donelan, and H. L. Tolman (2013), Directional wind-wave couplingin fully coupled atmosphere-wave-ocean models: Results from CBLAST-hurricane, J. Atmos.
Sci., 70, 3198–3215.
Donelan, M. A., M. Curcic, S. S. Chen, and A. K. Magnusson (2012), Modeling waves and windstress, J. Geophys. Res., 117, C00J23.
Hill, C., C. DeLuca, V. Balaji, M. Suarez, and A. da Silva (2004), Architecture of the Earth
System Modeling Framework, Computing in Science and Engineering, 6, 18–28.
Hong, S.-Y., J. Dudhia, and S.-H. Chen (2004), A revised approach to ice microphysicalprocesses for the bulk parameterization of clouds and precipitation, Mon. Wea. Rev., 132, 103–
120.
Hong, S.-Y., Y. Noh, and J. Dudhia (2006), A new vertical diffusion package with an explicit
treatment of entrainment processes, Mon. Wea. Rev., 121, 2318–2341.
Kain, J. S., and J. M. Fritsch (1993), Convective parameterization for mesoscale models: The
Kain-Fritsch scheme, in The representation of cumulus convection in numerical models, editedby K. A. Emanuel and A. M. S. D. J. Raymond, Eds., p. 246pp.
Large, W. G., J. C. McWilliams, and S. C. Doney (1994), Oceanic vertical mixing: A review anda model with a nonlocal boundary layer parameterization, Reviews of Geophysics, 32, 363–403.
McWilliams, J. C., and P. P. Sullivan (2000), Vertical mixing by Langmuir circulations, Spill
Science and Technology Bulletin, 6, 225–237.
Wallcraft, A. J., E. J. Metzger, and S. N. Carroll (2009), Software design description for the
HYbrid Coordinate Ocean Model (HYCOM) version 2.2, Tech. rep., nRL/MR/732009-9166.

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Appendix G. Large Data Access System
The University of Miami Combined Model (UMCM) pairs atmospheric Weather Research andForecasting (WRF) data with University of Miami Wave Model (UMWM) and Hybrid
Coordinate Ocean Model data. The data set hosted at the National Renewable Energy Laboratory(NREL) contains detailed data for hurricanes Ike (2010) and Sandy (2012), stored in a series of
NetCDF-format files, totaling 1.3 Terabytes. The UMCM data store can be accessed at
http://opendap.nrel.gov (also listed on http://data.gov at
http://catalog.data.gov/dataset/combined-wind-wave-hurricane-model). Users internal to NREL
can access the data slicing application at http://jett.hpc.nrel.gov.
Each data set contains a number of files, one per time stamp, and each file contains a grid of
measurements using a custom map projection. The details of the data and their resolution are as
follows:Ikeo Time resolution:

1 sample/hour from 9/8 12:00 to 9/12 6:00



1 sample/10 minute (min) from 9/12 6:00 to 9/13 9:00



252 samples in time

Sandy
o Time resolution:


1 sample/10 min from 10/28 00:10 to 10/31 00:00



432 samples in time.

At 58 additional sites, the data set contains higher resolution “spectral” data from the UMWM
for Hurricane Sandy. Figure G1 shows the location of these points relative to the tracks of Ike
and Sandy. Of those sites, 26 were selected as potential areas of interest for offshore winddevelopment, and 32 were selected as validation locations for comparison with National Data
Buoy Center (NDBC) data. At these locations, 4,319 samples are available, providing a 1
min/sample resolution.

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Data Access Systems

Figure G1. Locations of 1 minute/sample resolution "spectral" data placed amidst storm tracks areindicated by the red balloons

Source: Orthoimagery courtesy of Google Inc.

Figure G2. Configuration of OpenDAP Hyrax server and slicing application for the database filesystem (DBFS)

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The data is stored in the NREL data center in the native NetCDF format on the DBFS highperformance data store. Remote Web access to the data is provided by a Hyrax data server,which accepts queries using the OpenDAP protocol as well as a basic Web access. OpenDAP
queries allow for arbitrary subsetting of the data using any number of client frameworks (e.g.,
Python, Matlab, etc.). In this way, only the necessary subset of data is retrieved from the serveron the fly as computations are performed. Visualization can be accomplished similarly, by
requesting a subset of relevant data.
Additionally, staff at the NREL Computational Sciences Center have developed a custom Web
framework for performing automatic time-series data extraction at an arbitrary location with any
subset of model variables. In this way, National Wind Technology Center researchers can extract
just those variables of greatest interest at exactly the sites they wish. These data “slices” arerequested through a Web interface. Data extraction is fielded by a queue-based system andresearchers are notified when their data is ready to download as spreadsheet by email. Figure G2
shows the configured elements of this data access system. At the time of writing, this framework
can only be accessed internally, but is designed for public access should that be deemed valuable
at a later time.

Analysis Example
To provide an example of analysis opportunities using these resources, we identified threelocations corresponding to points of interest for offshore wind turbine researchers. These
locations are 03A (39.2691,-74.2267), 03B (39.1576, -73.9192), and 07A (36.934,-75.5453).
Locations 03A and 03B are off the coast of Atlantic City along the direct path of Hurricane
Sandy, amounting to a worst-case scenario for this storm. Location 07A is off the coast ofVirginia outside the main path of the storm. Both locations are in a state of active wind turbine
planning and development. Figure G3 and Figure G4 show the locations in detail with the path of
Hurricane Sandy in blue.

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Figure G3. Close-up of locations 03A and 03B

Source: Orthoimagery courtesy of Google Inc.

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Figure G4. Close-up of location 07A

Source: Orthoimagery courtesy of Google Inc.
Example time series for location 03B are given in Figures G5 through G8. Figure G5 and Figure
G7 show the entire duration of the storm for 1 and 10 min resolutions, respectively. Figure G6
and Figure G8 show a close-up view of data from this time series around the time the storm
crosses over the location (i.e., at landfall). It is clear to see that the 10-min sample/snapshot in
Figure G8 is beginning to reach the limits of usefulness in terms of the resolution; however, themain trends are still clear. The higher resolution in Figure G6 gives a crisp view of the behaviorof the storm at landfall.
The peak wind event for location 03B occurs at approximately 03:00 on 30 October 2012,reaching a maximum average wind speed of 32 m/s (71 mph). The maximum wave event isapproximately 6 hours earlier, reaching 11 meter wave heights with a period of 11 seconds.
Wind direction changes radically between these two events (max wave and max wind), fromapproximately 200 degrees (SSW) to 80 degrees (ENE). The change in wind direction creates a
maximum wind-wave misalignment in this period of 30‒35 degrees. Sites 03A and 03B show
similar patterns (see Figure G9 and Figure G10). Site 07A exhibits the greatest misalignment inwind and wave directions: nearly 70 degrees phase mismatch during a period of greater than 30
m/s wind speeds and more than 10 m waves. Site 03A, which is more inland, appears quite
similar to 03B, although less severe.

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Figure G5. Time series at location 03B, 1 min/sample resolution

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Figure G6. Time series at location 03B, 1 min/sample resolution, close-up at landfall

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Figure G7. Time series at location 03B, 10 min/sample resolution, extracted with NREL data slice
tool

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Figure G8. Time series at location 03B, 10 min/sample resolution, close up at landfall

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Figure G9. Time series at location 03A, 1 min/sample resolution

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Figure G10. Time series for location 07A, 1 min/sample resolution

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