SIMPACK AG, Friedrichshafener Strasse 1, 82205 Gilching, Germany
SIMPACK News
JULY 2013
02 CUSTOMER APPLICATION
Holistic Simulation of a Bucket Wheel Excavator
07 CUSTOMER APPLICATION
Offshore Wind Turbine Hydrodynamics
Modeling in SIMPACK
12 CUSTOMER APPLICATION
Review of Motion Sickness Evaluation Methods
and their Application to Simulation Technology
Holistic Simulation of a Bucket Wheel Excavator
Holistic multi-body simulations can be used to improve our understanding of complex
systems, determine design loads, and find operational modes to extend the fatigue life of
machine elements. This requires a complete modeling and verification of all mechanical and
electrical parts, including the control loop of the motor. Large-scale equipment for lignite
mining, like the largest bucket wheel excavator in the world, shown in Fig. 1, exhibit high
stability and insensitivity to mechanical vibrations because of their exceptionally high mass.
The experiences of recent years have nevertheless shown that even established mining
technologies can be enhanced. Measurement evaluations at the drivetrain.... See page 2
SIMPACK Realtime With SIMPACK 9.3,
the new solution
for realtime simulations — SIMPACK
Realtime — was introduced. SIMPACK
Realtime enables
the use of complex models for a wide range
of performance-critical realtime applications
such as Hardware-in-the-Loop (HiL) and
Software-in-the-Loop (SiL) scenarios. Typical
applications include handling and comfort
simulations, and ECU testing and component test rigs,.... See page 29
16 CUSTOMER APPLICATION
3D Simulation of the Human Middle Ear
with Multi-Body Systems
18 CUSTOMER APPLICATION
Wind Turbine Drivetrain Modeling and
Analysis Activities at CeSOS
SIMBEAM Reloaded
The first versions of SIMPACK
in the early 1990’s could
already model flexible Bodies
consisting of beam elements
without an interface to finite
element software. The first
available preprocessor was
called BEAM, which could
model straight beams based
on the differential equations
of the Euler-Bernoulli beam
theory. BEAM was frequently
used to model leaf springs and
to consider the... See page 32
26 CUSTOMER APPLICATION
Aeroelastic Simulation of Wind Turbines
Coupling SIMPACK with ADCoS
29 SOFTWARE
SIMPACK Realtime
31 SOFTWARE
Utilizing Multi-Core CPUs with SIMPACK 9
32 SOFTWARE
SIMBEAM Reloaded
CUSTOMER APPLICATIONS | Berthold Schlecht, Carsten Schulz, Institute of Machine Elements and Machine Design,
Chair of Machine Elements, Dresden University of Technology
Berthold Schlecht, Carsten Schulz, Institute of Machine Elements and Machine Design, | CUSTOMER APPLICATIONS
Chair of Machine Elements, Dresden University of Technology
Holistic Simulation of a Bucket Wheel Excavator
Holistic multi-body simulations can be
used to improve our understanding of
complex systems, determine design
loads, and find operational modes
to extend the fatigue life of machine
elements. This requires a complete modeling and verification of all mechanical
and electrical parts, including the control loop of the motor.
establishes that the response function of
the drivetrain depends on the response of
the bucket wheel boom.
Because of this dependency between subsystems, it is necessary to consider elastic
structures like gear housings, the superstructure or the torque support of the drivetrain. A single simulation of the drivetrain
that neglects the bucket wheel boom is not
sufficient for a complete system analysis.
DRIVETRAIN MODELING
The Chair of Machine Elements at Dresden
University of Technology uses full elastic
models with six degrees of freedom for
the mechanical components of the system. These models are based on original manufacturer drawings and have
been verified with measurements
INTRODUCTION
Large-scale equipment for lignite mining,
on the real system. This ensures
the highest possible modeling
like the largest bucket wheel excavator in
standard, a basic requirement
the world, shown in Fig. 1, exhibit high
for a complex
stability and insensisystem
tivity to mechanical
“A single simulation of the
vibrations because drivetrain that neglects the bucket analysis.
of their exceptionThe gearwheel boom is not sufficient for
box of the
ally high mass.
a complete system analysis”
bucket
The experiences of
wheel
recent years have
excavator, whose gear
nevertheless shown that even established
mining technologies can be enhanced.
pairs can easily be modMeasurement evaluations at the drivetrain
eled by the SIMPACK
element Gear Pair (Force
of the bucket wheel or of the superstructure
Element 225), has a total
clearly show that the whole system is sensitransmission ratio of
tive to mechanical vibrations. Increasing
243. The nominal torque
requirements during operation and excavation in hard clay-iron layers are forcing opof the three motors of
16 200
Nm adds up to
erators to adapt their operation and control
11 700 kNm at the bucket
strategy.
wheel. For considering
As part of a research project, the dynamic
higher orders of bending
behavior of the drivetrain of the bucket
wheel was analyzed and optimized with the
vibrations, gear shafts are
modeled as beam elements.
help of SIMPACK.
The
mathematical
approaches of beam elements,
SYSTEM ANALYSIS
which are integrated within
Fig. 2a shows the measured values of the
torque at the bucket wheel during coal
the SIMBEAM elements of
SIMPACK, ease the modeling of
mining. The transformation of the signal
into the frequency domain illustrates the
all shafts. All shafts are elastically
mounted. The bearings are reprehigh dynamics connected to the mining
sented by spring-damper elements
process (Fig. 2b). Due to the engagement
with a characteristic curve. A simplified
of the bucket wheel at 1.1 Hz, the system
responds with its first natural torsional
representation of bearings via a fixed operating stiffness is also allowable for normal
frequency at 1.8 Hz. Furthermore, one can
also see a reaction of the bucket wheel
load cases, because significant changes
in the bearing stiffness only occur in low
boom at 0.35 Hz, which is the first natural
speed ranges.
frequency in the vertical direction. This
2 | SIMPACK News | July 2013
ELASTIC STRUCTURES
In addition to the bearing stiffness, the stiffness of the housings affects the behavior
of the drive train. Because of this, all gear
housings (especially the torque arm) must
be integrated as elastic bodies. These are,
after their construction with the help of
CAD, modeled by finite element models
and integrated into the multi-body system.
The full elastic multi-body system can now
be simulated without difficulty despite the
large number of degrees of freedom.
In addition to the detailed drivetrain model,
it is necessary to integrate the superstructure of the bucket wheel excavator into
the multi-body system. After modeling
the complete geometry, all supporting
structures of the superstructure subsystems
are meshed via 1D
or 2D elements
(Fig.
3). As the
number of nodes is
too large for a multibody system, the finite
element model has to be
modally reduced.
When integrating the superstructure, one
also has to consider the kinematics and
kinetics of the rope system because, it connects the superstructure subsystems which
are necessary for stability. Now the multibody system of the bucket wheel excavator
is able to lift and lower the bucket wheel
boom. This can be seen as an addition to
the complete model but, one should take
into account that the operating position
of the excavator influences the natural
frequencies of the bucket wheel boom.
Depending on the position and the length
of free rope, the natural frequencies of the
bucket wheel boom change.
The subsequent comparison between numerically calculated and measured natural
frequencies shows very good compliance.
LOADS AND EXCITATIONS
In addition to modeling mechanical parts,
the loads and excitations acting on the
bucket wheel and motors must be considered. Fig. 4 shows the outer and inner excitations. The characteristic force function,
being associated with the mining process,
has a broad excitation spectrum and high
dynamics. In contrast, the control loop of
the motor reacts slowly, which can increase
the dynamics.
SIMPACK News | July 2013 | 3
CUSTOMER APPLICATIONS | Berthold Schlecht, Carsten Schulz, Institute of Machine Elements and Machine Design,
Chair of Machine Elements, Dresden University of Technology
Berthold Schlecht, Carsten Schulz, Institute of Machine Elements and Machine Design, | CUSTOMER APPLICATIONS
Chair of Machine Elements, Dresden University of Technology
Fig. 3: Finite element model of the bucket wheel boom
© Jürgen Leuffen
Fig. 1: Bucket wheel excavator 293 (model and real excavator)
10
LOAD CASE SIMULATION
Calculations in the time domain provide
information about the time histories of
loads and displacements of the system. The
transformation of those time signals in the
frequency domain shows the main influential variables concerning the amplitudes.
Based on the system reaction (frequency
and amplitude), engineers can evaluate the
complete behavior of the drivetrain. When
specifying improvements, this makes the
quality of simulation results critical.
4 | SIMPACK News | July 2013
Measurement
8
son between simulation and measurement
for a standard load case.
Initially, the bucket wheel excavator slews
into the surface. Consequently, the torque
and dynamics increase quickly. A quick
visual comparison of the torques in the
simulation and actual measurement shows
a good correlation. The signals in the frequency domain confirm this.
The dynamic factor of all drivetrain elements is interesting in regard to the general
directional behavior of the drivetrain which
Torque [Nm]
6
4
2
0
-2
Motor reaction
0 10 2030 405060708090
Time [s]
Fig. 2a: Measured torque: time domain
7
x 105
Measurement
6
Amplitude of torque [Nm]
The tooth mesh frequency is an example
of an inner excitation which can also be
defined with SIMPACK Force Element 225.
This effect is associated with a permanent
amplitude modulation which is an excitation
for torsional vibrations. As the tooth mesh
frequency is, however, much higher than
the first natural torsional frequency, vibrations caused by the tooth mesh frequency
have a much lower amplitude.
After verifying the excitation function and
the reaction of the control loop of the
motor based on measurements, one can
assume that the holistic multi-body system
will give reliable results. To combine the elements of the holistic simulation — excitation
function, multi-body model, motor control
loop — the Chair of Machine Elements generally uses Co-Simulation with MATLAB®
and Simulink®. This allows for a comfortable
calculation of complex excitation functions,
a comfortable routing of signals into and
out of SIMPACK and the storage and evaluation of results.
x 106
These optimizations are especially important for the bucket wheel gearbox. Before
defining new operation strategies or constructional changes, one has to compare the
current behavior of the simulation with real
measurements. Fig. 5 shows the compari-
5
Tooth stiffness variation
1.8 Hz
4
3
2
1
0
00.511.522.5 33.54
Frequency [Hz]
Fig. 2b: Measured torque: frequency domain
Load function
Fig. 4: Main influential variables
SIMPACK News | July 2013 | 5
CUSTOMER APPLICATIONS | Berthold Schlecht, Carsten Schulz, Institute of Machine Elements and Machine Design,
10
x 106
Measurement
Simulation
8
Torque [Nm]
6
4
2
0
-2
0 10 2030 405060708090
Time [s]
Fig. 5a: Comparison of simulation and measurement: time domain
7
x 105
Measurement
Simulation
Amplitude of torque [Nm]
6
5
4
3
2
1
0
Denis Matha, Friedemann Beyer, Stuttgart Chair of Wind Energy, University of Stuttgart | CUSTOMER APPLICATION
Chair of Machine Elements, Dresden University of Technology
00.511.522.5 33.54
Frequency [Hz]
Fig. 5b: Comparison of simulation and measurement: frequency domain
0.9
0.8
can be seen indirectly in Fig. 6. There is a
visible gap between the dynamic factor of
the coupling and the rest of the gearbox.
This illustrates the elastic function of the
coupling which reduces the vibration on the
motor shaft. This function prevents the motor shaft from overloading. In regard to the
control of the drivetrain, this indicates that
the speed-controlled motor controls are too
soft and do not react quickly enough. It also
means that, even though the control loop
has a load limiter, the loads in the gearbox
may be much higher.
The results prove the high quality of the
holistic simulation and show that SIMPACK
is suitable for large models with complex
excitations. Furthermore, the results show
that the damping of the first torsional natural frequency at 1.8 Hz is too low. This can
be explained by the supporting effect of the
surrounding ground which could easily be
taken into account by an additional damper
element.
CONCLUSION
The results of the holistic simulation of
bucket wheel excavator 293 show that the
current system behavior can be calculated
correctly. Further detailed work is justified
by the accurate conclusions of the system
behavior. This allows the definition of an
improved motor control that also takes
gearbox dynamics into account.
Besides system analysis, one can also
calculate load spectrums, after simulating
normal and special load cases. These can
accordingly be used for new construction or
revisions. This also includes the calculation
of bearing lifetime. The complete system
analysis of the bucket wheel excavators
with the help of SIMPACK not only increases
system knowledge, but also delivers ways
to improve operation. This lies within the
interest of the operating company, as they
are currently working to implement an
improved motor control.
Offshore Wind Turbine Hydrodynamics
Modeling in SIMPACK
HYDRODYNAMICS FOR OFFSHORE
WIND TURBINES
Offshore wind turbine support structure
types include:
As the offshore wind energy sector
expands, so too does the demand for
advanced simulation environments that
are able to accurately model these complex systems. The latest trend is floating
offshore wind turbines which can be
installed in deep water and hold great
economic potential. To accurately simulate offshore wind turbines, the Stuttgart Chair of Wind Energy
(SWE) at the University
of Stuttgart has extended SIMPACK
with a coupling to
the hydrodynamic
package HydroDyn developed
by NREL. A Morison force element and
dynamic MBS mooring system model
were also introduced. By taking advantage of these hydrodynamic extensions
plus existing advanced drivetrain and
aerodynamic submodels, a full dynamic
coupled simulation of fixed-bottom and
floating offshore wind turbines is possible with SIMPACK.
•monopile (gravity-based and suction
bucket foundations for shallow sites)
• jacket and tripod structures for depths up
to 50 m
• floating structures for deeper locations
In general, hydrodynamic and hydrostatic
loads on offshore structures subject to
waves and currents are an effect of the integrated pressure distribution on the wetted
surface. In offshore terminology, the various
load contributions are separated into:
•
•
•
buoyancy force (hydrostatic restoring)
radiation force:
a.inertia force from added mass
b.viscous damping force
wave excitation force:
a. diffraction (incident-wave scattering)
b.Froude-Kriloff (undisturbed pressure
field forces)
• sea current force and
•
nonlinear higher order forces
(slow, mean drift and sum-frequency forces).
Some substructures for wind turbines
consist of slender axisymmetric cylindrical
Normalized torque [Nm]
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Motor
Coupling
Bucket Wheel
0
19 19.119.219.319.4 19.519.619.719.819.9 20
Time [s]
Fig. 6: Normalized torques
6 | SIMPACK News | July 2013
SIMPACK News | July 2013 | 7
CUSTOMER APPLICATION | Denis Matha, Friedemann Beyer, Stuttgart Chair of Wind Energy, University of Stuttgart
elements. This enables the use of the simple
and efficient semi-empirical Morison Equation which is valid if the flow acceleration
can be assumed uniform at the location of
the cylinder thus simplifying the diffraction
problem. This requires that the diameter
of the cylinder D be much smaller than the
wavelength L — typically D/L values of less
than 0.15–0.2. It is also assumed that relative motions are small so that viscous drag
dominates the damping; radiation damping
can be neglected; and that off-diagonal
added-mass terms are negligible, as in the
case of axisymmetric structures. Since the
equation contains empirical coefficients for
added mass, inertia and drag (which depend on the Keulegan-Carpenter number,
Reynolds number and surface roughness),
careful attention to these is required to
obtain viable results.
For structures with larger diameters and
larger motions—typically tripods or floating structures—effects from hydrodynamic
radiation and diffraction (not considered
by Morison’s Equation) become important.
For such structures, linear hydrodynamic
fluid
Denis Matha, Friedemann Beyer, Stuttgart Chair of Wind Energy, University of Stuttgart | CUSTOMER APPLICATION
uk = ut + ωd Is/2
v
ds
Is/2
ωd
ωd
x
z
rs
x
ut
uk
y
y
Fig 1: Calculation of Morison forces on mooring line segment
theory is currently most commonly used. It
is based on potential theory, and includes
effects from linear hydrostatic restoring,
added mass and damping contributions
from linear wave radiation (including freesurface memory effects), and incident wave
excitation from linear diffraction. Typically,
nonlinear viscous drag contributions are
INPUTS-2:
frequency-dependent hydrodynamic matrices
frequency-domain radiation / diffraction
hydrodynamics preprocessor (SWIM or WAMIT)
platform geometry
WAMIT
wave excitation force
(diffraction problem)
INPUTS-1:
platfrom properties
and
wave conditions
restoring matrix
(hydrostatic problem)
damping matrix
(radiation problem)
added-mass matrix
(radiation problem)
Element was implemented at SWE into
SIMPACK 9. It uses the relative formulaspar buoy
φz
tion of the Morison equation according to
3 DOF
Östergaard and Schellin, and also includes
fairlead
φx
uy
an option to directly account for buoyancy
if the body is always completely submerged.
Due to the relative simplicity of the Morison
Joint
ct, dt
Equation, the user only needs to supply
values for the two empirical coefficients:
inertia Cm and drag CD. A Reynolds depencr, dr
dency of these coefficients can be added.
rigid Body
Water density, kinematic viscosity, effective
cylindrical diameter (to determine the cross
seabed
anchor
sectional area) and length of the body
where the Force Element is applied also
need to be defined. The desired discretizacs ds
tion of a mooring system can be achieved
by using multiple Morison Force Elements
Fig 3: Topology of dynamic nonlinear MBS mooring system
along cylindrical structures with different
diameters and lengths (Fig. 1).
Since the Morison equation in its relative
added from Morison’s equation. However,
modeling methodologies described have
formulation features an added mass term
nonlinear steep and/or breaking waves,
depending on the relative fluid acceleration,
been implemented. Currently, most other
vortex-induced vibrations, second-order
the routine requires
commercial
effects of mean-drift, slow-drift and sum“For cylindrical fixed-bottom structures
the structure to
codes only apfrequency excitation, and any other higher
ply
Morison’s
and mooring systems, a SIMorison
accelerate at each
order effects, are neglected within Hydrotime step. In MBS,
equation
and
user Force Element was implemented
Dyn. To overcome this limitation, a coupling
the acceleration is
are, therefore,
at SWE into SIMPACK 9.”
between SIMPACK and the Computational
usually not solved
limited to aforeFluid Dynamics (CFD) tool ANSYS CFX is
during integration, thus making the implementioned slender structures where radiacurrently being developed at SWE (Beyer,
tion damping and off-diagonal added-mass
mentation of Morison’s Equation complex.
Arnold & Cheng, 2013). The incorporation
terms are negligible.
Here, SIMPACK’s ability to use algebraic
of second-order hydrodynamic effects is
states (q-states) is utilized, "anticipating"
planned for future releases of HydroDyn.
acceleration results of the Right-Hand Side,
MORISON FORCE ELEMENT
To enable modeling of offshore wind turi.e., making them available before they are
For cylindrical fixed-bottom structures and
bines in SIMPACK, the two hydrodynamic
mooring systems, a SIMorison user Force
actually calculated.
time-domain hydrodynamics (HydroDyn)
seed for ring
cosine
transform
Box-Muller
method
platform
motions
hydrodynamic
forcing loads
impulsive
added mass
INPUTS-3:
OUTPUT:
platform marker kinematics
hydrodynamic forces and
moments on platform
Fig 2: HydroDyn calculation procedure and interface to SIMPACK (image source: NREL)
8 | SIMPACK News | July 2013
mooring
segment
α, γ
mooring
segment
3 DOF
mooring
segment
mooring
segment
3 DOF
y
1 DOF
α, β, γ
α, β, γ
α, β, γ
aerodynamics
3 DOF
x, y, z
2 DOF
α, γ, y
3 DOF
mooring
segment
α, γ, y
3 DOF
mooring
segment
mooring
segment
mooring
segment
mooring
segment
y
1 DOF
3 DOF
0 DOF
wind turbine
x, y, z
anchor
SIMPACK
α, γ
2 DOF
mooring
segment
platform
viscous drag
sun
forces
mooring
segment
α, γ, y
dummy
memory
effect
incident-wave
excitation
anchor
Morison's
Equation
SIMPACK
User Force
(NREL's HydroDyn)
α, γ
α, γ, y
dummy
buoyancy
incident-wave
kinematics
sea current
time
convolution
hydrodynamics
x, y, z
dummy
buoyancy
calculation
inverse FFT
hydrodynamic
calculations
anchor
radiation
kernel
white gaussian
noise
wave spectrum
& direction
infinite-freq.
limit
2 DOF
hydrodynamics
(Morison)
α, γ, y
mooring
segment
3 DOF
α, γ, y
3 DOF
y
1 DOF
3 DOF
6 DOF
Mooring-System
Fig 4: Topology of floating offshore wind turbine
SIMPACK News | July 2013 | 9
CUSTOMER APPLICATION | Denis Matha, Friedemann Beyer, Stuttgart Chair of Wind Energy, University of Stuttgart
Denis Matha, Friedemann Beyer, Stuttgart Chair of Wind Energy, University of Stuttgart | CUSTOMER APPLICATION
• linear hydrostatic restoring
• nonlinear viscous drag contributions from
Morison’s Equation
• added mass and damping contributions
from linear wave radiation (including
free-surface memory effects)
•incident wave excitation from linear
diffraction
10 | SIMPACK News | July 2013
VALIDATION WITH OC3 & OC4
The SIMHydro coupling was first validated
with results from phase four of the IEA
Annex 23 Offshore Code Comparison Collaboration (OC3) project (Fig. 5), and is currently used in phase two of the follow-up
OC4 project. Exemplary results from OC4
load cases 1.3, representing free decay
tests where the semi-submersible platform
(Fig. 6) is released at an initial displacement
in still water without wind loads, are shown
in Fig. 7 and Fig. 8.
The presented platform surge and pitch
displacement show very good agreement
between SIMPACK and other participants
applying linear hydrodynamic theory like
FAST (NREL) and DeepLinesWT (Principia).
Compared to codes using Morison’s equation for modeling the hydrodynamics — like
HAWC2 (DTU) and Bladed (GH) — distinct
REFERENCES
Fig 6: OC4 semi-submersible floating wind turbine with quasi-static mooring system
(only nodes displayed)
differences in load and motion predictions
are evident depending on the load case. This
is due to the differences in the semi-empiric
approach of a Morison-only formulation.
25
USAGE OF SIMPACK OFFSHORE
SWE uses SIMPACK to model offshore
floating wind turbines in the European
research projects OFFWINDTECH, Innwind,
HAWC2
Bladed
DeepLinesWT
FAST
SIMPACK
20
15
10
5
0
-5
-10
10
8
6
Platform pitch [º]
The wave generator can generate either
periodic waves or random irregular Airy
waves with user-defined significant wave
height and peak spectral period based on a
defined wave spectrum (the JONSWAP and
Pierson-Moskovitz spectra are predefined).
Kinematic stretching (Vertical, Extrapolation,
SIMHYDRO — COUPLING TO NREL’S
Wheeler) is also implemented to provide
HYDRODYN
predictions of wave kinematics above the
The SIMHydro Force Element couples
mean water level; an option used only for
NREL’s HydroDyn module with SIMPACK
Morison calculations since it is inconsistent
(Fig. 2). HydroDyn was developed by Jason
with linear hydrodynamic theory.
Jonkman at NREL
The Morison Equa“At SWE, a dynamic nonlinear
(Jonkman, 2007)
tion implementamooring line model has been developed
and has since been
tion of HydroDyn
within SIMPACK to overcome the
used to model
is equivalent to
drawbacks of the quasi-static approach.”
monopiles
and
the
previously
various
floating
described Morison
structures. The current release of HyForce Element. It accounts for the current
droDyn offers four important features:
fraction of wetted surface dependent on
instantaneous wave elevation. Currently, it is
• a wave generator for periodic and reguapplicable for monopile structures, and the
lar/irregular Airy waves (JONSWAP, PM
upcoming HydroDyn version 2 (already availspectra) including stretching
able in an alpha version) will then be able
• the Morison equation module for hydroto simulate multi-member fixed-bottom
dynamic load calculation
and floating substructures such as jackets
• a linear hydrodynamics module for load
or semi-submersibles with the Morison
calculation on non-slender (floating) bodies
Equation.
• a quasi-static mooring line module for
The third feature of HydroDyn is its linear
mooring system load calculation of floathydrodynamic model. It computes loading
ing platforms
contributions from:
At SWE, the SIMorison Force Element is
primarily used and validated by modeling
the hydrodynamic loads on mooring lines.
The regular or irregular Airy wave kinematics
used by this element are computed by the
SIMHydro element which is described next.
SUMMARY
The implementation of SIMorison and
SIMHydro Force Elements makes it possible
to simulate fixed-bottom and floating wind
turbines with SIMPACK. The coupling is validated by OC3 and OC4. SIMPACK offshore
wind turbine models have already been
successfully applied in a number of research
projects, and show excellent potential for
future applications.
Platform surge [m]
Fig 5: OC3 spar-buoy floating wind turbine model with MBS mooring system
The linear hydrodynamic option in HydroDyn requires the user to enter frequencydependent hydrodynamic vectors and
matrices. These must be pre-calculated by
external offshore panel-based codes such
as WAMIT® or ANSYS® AQWATM, which
solve the linearized radiation and diffraction problems in the frequency domain. Full
details of HydroDyn’s theory are given in
Jonkman (Jonkman, 2007). The upcoming
HydroDyn version 2 release will also feature
the possibility of Morison elements with
linear hydrodynamics which can be used to
model the hydrodynamic forces on the main
pontoons of a semi-submersible with linear
theory and on the braces with Morison’s.
The fourth module within HydroDyn provides a quasi-static mooring line model
to efficiently calculate mooring line loads
on floating platforms. At SWE, a dynamic
nonlinear mooring line model has been
developed within SIMPACK to overcome
the drawbacks of the quasi-static approach
(Fig. 3, 4). More details on this MBS mooring line model are given by Matha (Matha,
Fechter, Kühn, Cheng, 2011).
The original input file for HydroDyn has
been modified for usage in SIMPACK and
allows the user to define the incoming
waves, to select between the Morison and
linear hydrodynamic module, and define the
properties of the mooring system.
AFOSP and FLOATGEN. The latter is currently the largest EU-funded offshore wind
energy research project and will deploy two
multi-MW floating wind turbine systems in
Mediterranean waters over 40 m deep. With
this project, the SWE will have the opportunity to compare the SIMPACK floating wind
turbine model with measured scale and
full-scale prototype data, analyze the differences, validate the predictions and improve
the models where required.
4
0
-2
-4
-6
-20
-8
0 100200300400 500600
Simulation time [s]
Fig 7: OC4 LC 1.3a: Platform translation in surge direction
HAWC2
Bladed
DeepLinesWT
FAST
SIMPACK
2
-15
-25
Beyer, F., Arnold, M., Cheng, P. W. (2013).
Analysis of Floating Offshore Wind Turbine Hydrodynamics using coupled CFD and Multibody
Methods. ISOPE. Anchorage, USA.
Jonkman, J. (2007). Dynamics Modeling and
Loads Analysis of an Offshore Floating Wind
Turbine. NREL/TP-500-41958. Golden, US-CO:
National Renewable Energy Laboratory.
Matha, D., Fechter, U., Kühn, M., Cheng, P. W.
(2011). Non-linear Multi-Body Mooring System
Model for Floating Offshore Wind Turbines.
University of Stuttgart, OFFSHORE 2011, Amsterdam, Netherlands.
-10
0 50 100150200 250300
Simulation time [s]
Fig 8: OC4 LC 1.3c: Platform rotation in pitch direction
SIMPACK News | July 2013 | 11
CUSTOMER APPLICATION | This Wiederkehr, Dr. Friedhelm Altpeter, Helbling Technik AG, Aarau
This Wiederkehr, Dr. Friedhelm Altpeter, Helbling Technik AG, Aarau | CUSTOMER APPLICATION
Review of Motion Sickness
Evaluation Methods and their Application
to Simulation Technology
Seasickness or motion sickness (kinetosis) is not only an issue at sea, but on
rails as well. Unlike vibration discomfort,
no clear guidelines exist for assessing
motion sickness. Recent developments
such as tilting technology and increased
passenger demands regarding comfort
have led to higher requirements for rolling stock equipment and infrastructure.
This article presents a tool for assessing
train design with respect to motion sickness at the engineering stage.
This simple theory, however, does not
explain motion sickness sufficiently. It
was therefore extended to the sensory
rearrangement theory [7]. This theory states
that motion sickness is caused either by variance between the motion signals obtained
from two sensors, or between one sensor
and what is expected, based on previous
experience.
MODELS USED TO CHARACTERIZE
MOTION SICKNESS
One of the first studies characterizing
the effect of various frequencies with the
symptoms of motion sickness was carried
out in 1974 [8]. O’Halon and McCauley
determined that the most motion sicknessprovoking frequencies are found around
0.2 Hz. They defined the “motion sickness
incidence” (MSI) as the percentage of
WHAT IS MOTION SICKNESS
Motion sickness is a phenomenon usually
people who experienced emesis (vomiting).
experienced by persons exposed to a movSimilar to the frequency-weighting curves
ing environment with low frequency accelused for comfort assessment, M. J. Griffin
and Lawther [1] defined a frequencyerations. The most common symptoms of
weighting curve for kinetosis based on
seasickness are nausea and vomiting.
laboratory
tests
It is evident from
tests that the veswith
humans.
“Motion sickness is a phenomenon
tibular, visual, and
This
frequencythat is usually experienced by persons
weighting
curve
somatosensory
exposed to a moving environment
can
be
found
in
system play a role
with low frequency accelerations.”
the International
in the onset of
Standard
ISO
motion sickness.
Psychological factors are also involved [6].
2631-1 [2] and is named wf. The weighting
However, there is no agreement in the scifunction is displayed in Fig. 1.
Based on this frequency-weighting filter, the
entific community on why the human body
motion sickness dose value is introduced
has developed these symptoms. The most
as the square root of the integral of the
widely accepted hypothesis is the sensor
conflict theory. This theory states that our
squared frequency weighted accelerations
brain collects information from the human
over time. The full mathematical description
sensors and tries to correlate the informais as follows:
tion to body movement. If the brain is not
able to correlate the information properly, it
may develop the symptoms known as mo𝑀𝑆𝐷𝑉� ���𝑎�� ∙�𝑡
tion sickness.
12 | SIMPACK News | July 2013
Based on the motion sickness dose value,
the vomiting incidence (𝑉𝐼) is given as a
percentage. The illness rating (𝐼𝑅) can be
estimated from the following formulas:
𝑉𝐼 � ��� ∙ 𝑀𝑆𝐷𝑉� 𝐼𝑅 � ���� ∙ 𝑀𝑆𝐷𝑉�
The values obtained for the illness rating
allow one to judge motion sickness accordingly as shown in Table 1.
As the motion sickness dose value is the
integral over time of squared accelerations,
SIMPACK News | July 2013 | 13
CUSTOMER APPLICATION | This Wiederkehr, Dr. Friedhelm Altpeter, Helbling Technik AG, Aarau
the motion sickness dose values to horizontal (lateral) [4] and roll motions [3]. The latter
are of particular importance in the case of
railway vehicles [5].
For now, the simplicity of application and
clear rules make the motion sickness dose
value the preferred method for assessing
motion sickness.
-10
-15
-20
-25
-30
10-210-1100101
Frequency [Hz]
Fig. 1: Frequency weighting function for motion sickness
the dose value will never decrease over
[10]. Passenger surveys were carried out in
time. This is a weakness of the model as
addition to the acceleration measurements.
the human body is
Since the passenger
able to recover from
“As the most provoking
rating was used to
the effects of motion
frequencies for motion sickness are
fit parameters of the
sickness. Two models
around 0.2 Hz, it is essential to use a
model, it cannot be
that overcome this
representative track course with its
easily transferred to
weakness are Oman’s
curvature and super-elevation.”
judge other accelera(Developed by Charles
tion histories.
Oman at MIT [9]) and the net dose model
New frequency filters have recently been
(developed by the Swedish National Road
published which extend the application of
and Transport Research Institute VTI [10]).
Oman’s model attempts to model the neural
behavior of the human body with respect to
motion sickness. This model is therefore the
most complete one available but, also the
most difficult to apply.
The net dose model was used to analyze
a tilting train on a specific track in Sweden
APPLICATION USING SIMPACK
In order to judge a given train design with
respect to motion sickness, a multi body
simulation model is created. This model
simulates the vehicle on a given track and
calculates the respective numbers characterizing motion sickness from the simulation
results. SIMPACK is well-suited to perform
this simulation, as it comes with the important features for railway dynamic simulations
such as rail-wheel contact and track set up.
As the most provoking frequencies for
motion sickness are around 0.2 Hz, it is essential to use a representative track course
(Fig. 2) with its curvature and super-elevation. The track under observation consists of
a fairly straight section and segments with
curves to the left- and right-hand sides.
Once the simulation is complete, the postprocessing SIMPACK tool evaluates the
motion sickness dose value from the accelerations (Fig. 3) using the frequency filter
Wf. As the frequency filters for lateral motions are not yet integrated in SIMPACK, the
results are exported as MATLAB® readable
data for further processing. The results of
the motion sickness dose value for vertical
and lateral motions are displayed in Fig. 4.
Curvature
Filter Wf [dB]
-5
Acceleration
0
lateral
vertical
Time
Fig. 3: Representative accelerations
Based on the results of the motion sick[2] ISO2631-1, "Mechanical Vibration and
ness dose value, vehicle design assessment
Shock — Evaluation of Human Exposure to Whole
is possible. The
Body Vibration", Part 1:
results show that
General
Requirements,
“The method presented in t
the straight part of
1997.
his article allows the assessment of
the track does not
[3] B. E. Donohew and M. J.
a given railway vehicle design with
cause the MSDV
Griffin, "Effect of Roll Oscilrespect to the passengers’ feelings
to increase marklation Frequency on Motion
of motion sickness...”
edly. However, the
Sickness", Aviation Space
lateral accelerations, which result from the
Environmental Medicine (74), pp. 326–331, 2003.
curved part of the track, do increase the
[4] B. E. Donohew and M. J. Griffin, "Motion
MSDV, and thus, the symptoms of motion
Sickness: Effect of the Frequency of Lateral Oscilsickness.
CONCLUSION
The method presented in this article allows
for the assessment of a given railway vehicle
design with respect to the passengers’ feelings of motion sickness primarily by considering the frequency-weighted lateral and
roll accelerations. The presented method
can be applied to vertical, lateral and roll
motion separately. However, it ignores the
effect of phase angles between roll and
lateral accelerations which have proven to
be important [11].
While acceleration measurements are available from existing vehicles, multi-body simulation contributes to a more comfortable
train design during the engineering stage.
This can be accomplished by using SIMPACK
for parameter studies.
lation", Aviation Space Environmental Medicine
(75), pp. 649–656, 2004.
[5] Standard, DIN EN 12299: Bahnanwendungen — Fahrkomfort für Fahrgäste — Messungen
und Auswertung, 2009.
[6] M. J. Griffin, "Handbook of Human Vibration", London: Elsevier, 1990.
[7] J. T. Reason and J. Brand, "Motion Sickness",
London: Academic Press, 1975.
[8] J. F. O'Halon and M. E. McCauley, "Motion
Sickness Incidence as a Function of the Frequency
and Acceleration of Vertical Sinusoidal Motion",
Aerospace Medicine, pp. 366–369, April 1974.
[9] C. M. Oman, "Motion Sickness: a Synthesis
and Evaluation of the Sensory Conflict Theory",
CanJPhys, pp. 294–303, 1990.
[10] B. Kufver and J. Förstberg, "A Net Dose
Model for Development of Nausea", Swedish
National Road and Transport Research Institute
(VTI), pp. 229–239, 22 September 1999.
[11] J. A. Joseph and M. J. Griffin, "Motion
Sickness from Combined Lateral and Roll Oscillation: Effect of Varying Phase Relationships",
Aviation Space Environmental Medicine (78), pp.
994–950, 2007.
[12] K. Knothe and S. Stichel, Schienenfahrzeugdynamik, Berlin: Springer, 2003.
This work was carried out as a Master Thesis at
the Universities of Applied Sciences Landshut
and Ingolstadt in the program “Applied Computational Mechanics”. The authors would like to
thank Rhätische Bahn for supporting the project.
MSDV lateral
MSDV vertical
MSDV
5
This Wiederkehr, Dr. Friedhelm Altpeter, Helbling Technik AG, Aarau | CUSTOMER APPLICATION
REFERENCES
Table 1: Values obtained for illness rating
to judge motion sickness
14 | SIMPACK News | July 2013
Position on track
Fig. 2: Representative track course
[1] A. Lawther and M. Griffin, "Motion Sickness
and Motion Characteristics of Vessels at Sea",
Ergonomics 31, pp. 1373–1394, 1988.
Time
Fig. 4: Representative evolution of the motion sickness dose value
SIMPACK News | July 2013 | 15
Department of Applied Sciences and Mechatronics
3D Simulation of the Human Middle Ear
with Multi-Body Systems
The ear is an essential human sensory
organ. In Germany,
approximately 10
million people suffer from hearing impairments. Implantable systems can speed recovery from hearing loss, such
as the active middle ear implant "Vibrant SoundBridge"
produced by MED-El, Innsbruck, Austria. Active middle
ear implants are used in cases of sound conduction
hearing loss or sensorineural hearing loss.
In recent years, computer-aided 3D simulation has
significantly improved the medical world's understanding of the anatomy and function of middle
ear structures, thus, promoting the development
of middle ear prostheses.
Fig. 1: Middle ear MBS model
INTRODUCTION
A middle ear multi-body model was
developed (Fig.
1) to research hearing
impairments.
This research focuses on the development
and simulation of a 3D multi-body model
of the human middle ear. It examines how
the middle ear system responds to different
types of sound stimulation in both a normal
middle ear and a middle ear coupled with
an active implant.
MULTI-BODY MODEL
A 3D model of a normal human middle ear
and the middle ear coupled with an active
implant, as shown in Fig. 2, was developed
using the software package SIMPACK.
The MBS model contains the exact geometry of the middle ear structures — the
tympanum and the three ossicles (malleus,
16 | SIMPACK News | July 2013
In the Kelvin-Voigt model, massless springs
and dampers are connected in parallel.
The linear elastic material properties of muscles and ligaments have been modeled as
massless spring-damper Force Elements in
all three axes. To take into account the flexible fiber structure around the tympanum in
the model, the annulus fibrocartilagineus is
modeled by twelve spring force elements.
The ligamentum annulare stapedis is modeled by 25 massless spring-damper elements. The center of gravity of the tympanum is attached to the inertial system with
a one-degree of freedom (DOF) Joint. The
malleus is rigidly connected with the tympanum. The incudostapedial connection has
been modeled as a unilateral contact force
incus and stapes). This was facilitated by a
element on all three translational axes. Romicro-computer tomographic dataset of the
tational spring damper force elements were
human middle ear.
used for the rotation. A damping Force EleThe physical properties, and the inertia tenment is used for the coupling of the stapes
sor of the aforementioned structures, were
footplate with the inertial system, which is
calculated together
centrally and vertiwith the active im- “All anatomical structures, their location, cally arranged on
and 3D orientation are included in the
plant using approthe footplate. The
model of the middle ear.”
priate density values
damper represents
taken from the
the cochlea which is
literature in the CAD software SolidEdge.
filled with incompressible liquid. The system
All anatomical structures, their location,
contains 17 elements and has four degrees
and their 3D orientation are included in the
of freedom. The whole system is considered
model of the middle ear.
linear and time-invariant.
The tympanum, the active implant, and the
three ossicles are modeled as rigid bodies.
SIMULATION
The Kelvin-Voigt model is used for the bioA "click" sound stimulation in the form of a
mechanical description of linear viscoelastic
Gaussian pulse with a half-power width of
behavior of the ligaments and muscles of
100 ms and a wobbling signal stimulates all
the middle ear.
frequencies.
Theodor Bretan, Stefan Lehner, Munich University of Applied Sciences, | CUSTOMER APPLICATION
Department of Applied Sciences and Mechatronics
The dynamic behavior of the middle
ear in the steady state condition was
examined for both the normal model
of the middle ear (Fig. 3) and the
middle ear model coupled with a
active implant with two different
types of stimulation on the
tympanum: a "click" sound
excitation in the form
of a Gaussian pulse at
various sound pressure
levels (SPL) — 60, 80
and 94  dB — and a
harmonic
acoustic
stimulation.
The stapes and umbo
deflection in the speech
frequency range were studied, and the
phase shift between the incus and stapes
was analyzed.
RESULTS
Typically, the result that is noted in specialized literature is the deflection of the stapes
footplate. This result is the input that is
processed by the inner ear.
The amplitude and phase frequency response of the deflection of the stapes footplate and umbo deflection for frequencies
in the speech frequency range between 100
Hz and 10 kHz were determined, graphically
displayed and analyzed. The system's oscillation behavior was visualized by animations.
The deflection of the stapes footplate is
directly proportional to the sound pressure
stimulation up to a frequency of approximately 6.5 kHz. The results in Fig. 3 show
that the amplitude frequency response of
the deflection of the stapes footplate at
60 dB SPL (blue dashed line) is approximately 6.17 nm and reaches at the resonance
frequency of 1210 Hz 18.42 nm.
The use of an active implant attached
to the incus neck moves the resonance frequency to lower frequencies
and amplifies the stapes footplate
deflection for both a harmonic and a
Gaussian pulse sound excitation at the
tympanum.
CONCLUSION
The simulation results have illustrated
the complex 3D vibration of the ossicle resulting from the two types of
sound stimulation at the tympanum
and at different sound pressure levels.
The simulation results of an acoustic
excitation of the tympanum with
a Gaussian pulse coincide with the
literature.
The accuracy of the virtual model of
the middle ear was always validated
Fig. 2: Middle ear model
coupled with active implant
when compared with experimental Laser
Doppler Vibrometer (LDV) measurements,
with LDV measurements of petrous bones,
with finite element method models and
with multi-body system models, from specialized literature.
REFERENCES:
[1] Bretan, T. (2012): ’3D Simulation des Menschlichen Mittelohres mit Mehrkörpersystemen’,
bachelor thesis, University of Applied Sciences
Munich, Germany
10-6
10-7
10-8
Displacement of stapes x [m]
CUSTOMER APPLICATION | Theodor Bretan, Stefan Lehner, Munich University of Applied Sciences,
10-9
10-10
10-11
10-12
10-13
10-14
stapes_footplate.x 94 dB SPL
stapes_footplate.x 60 dB SPL
stapes_footplate.x 80 dB SPL
10-15
102103104
Frequnecy [Hz]
Fig. 3: Amplitude response for a click sound excitation at various sound pressure levels (SPL) —
60, 80 and 94 dB
SIMPACK News | July 2013 | 17
CUSTOMER APPLICATION | Yihan Xing, Centre for Ships and Ocean Structures (CeSOS), Marine Technology Centre, NTNU
Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU | CUSTOMER APPLICATION
Wind Turbine Drivetrain Modeling and Analysis Activities at CeSOS
In 2002, the Research Council of Norway and the Norwegian University of Science and
Technology (NTNU) established the Centre for Ships and Ocean Structures (CeSOS) as a center
for excellence. The research at CeSOS aims to develop fundamental knowledge about how
ships and other structures behave in the ocean environment using analytical, numerical and
experimental studies. CeSOS’ research on offshore wind turbines has focused on modeling
dynamic responses of various bottom-fixed and floating wind turbine concepts. Research
on the challenges and performance of wind turbine drivetrains used in offshore floating
applications has been of particular interest.
generator
three point support
(main bearing & two torque arm supports
bed plate
generator shaft
gearbox
hub
Fig. 1: NREL, Gearbox Reliability Collaborative (GRC)
18 | SIMPACK News | July 2013
main shaft
SIMPACK News | July 2013 | 19
CUSTOMER APPLICATION | Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU
Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU | CUSTOMER APPLICATION
crucial, as offshore maintenance and repair
are costly, and wind turbines are not always
accessible due to weather conditions.
Table 1: Model variants
BACKGROUND
At CeSOS, researchers use multiple software
tools to analyze wind turbines for the sake
of comparison. For example, in addition
to FAST
[1] and HAWC2
[2], researchers
at CeSOS employ software such as SIMO/
RIFLEX [3, 4] for wind turbine global analysis. SIMPACK has been used to model the
mechanical components of the drivetrain.
This article explores the use of SIMPACK in
wind turbine drivetrain research activities
within CeSOS.
Research on wind turbine drivetrains at
CeSOS focuses on the modeling and analy-
USING SIMPACK TO MODEL THE WIND
TURBINE DRIVETRAIN
CeSOS has utilized SIMPACK to model the
wind turbine drivetrain. Load conditions on
the drivetrain model are typically calculated
using other software codes. For instance,
the global analysis of the wind turbine is
typically simulated using aero-elastic codes,
and the loads at the nacelle are used as
inputs for the SIMPACK drivetrain model.
SIMPACK has several features that cater
specifically to modeling gearboxes. For
instance, the Force Element 225 Gear Pair
models the gear contact pair using the
slicing method, which allows the modeling
sis of the drivetrain for offshore applicaof the tooth load distribution along the
tions. The wind turbine drivetrain is a crucial
tooth flank, also known as the KH� factor.
component of the wind turbine. The geared
In addition, SIMPACK can model flexible
drivetrain
concept
bodies with complex
has been the focus
geometries, which are
“SIMPACK has several features
of CeSOS’s work. The
commonplace in wind
that are specifically catered to the
wind turbine gearbox
turbine
gearboxes,
modeling of gearboxes.”
is known as the "misse.g., the planet carrier
ing link" in the wind
and gearbox housing.
industry as it has not achieved its intended
Furthermore, the ability to incorporate user
routines in SIMPACK allows the modeling of
service life of 20 years. It has been blamed
for contributing significantly to wind turbine
user-defined Force Elements which are very
downtime. Understanding the wind turbine
useful in research where flexibility in model
gearbox for offshore wind applications is
definition is important.
Modeling of rigid planet pins
Modeling of rigid pin interfaces
pin reference node
(located in middle of pin)
pin interface reference modes
Modeling of rigid bearings
Modeling of rigid main shaft
main shaft
reference node
bearing reference nodes
Planet A upwind tangential
420
Fig. 4: Examining the influences of the subcomponents
350
400
Test
M1A
M1B
M3B
P2
300
380
360
Force [kN]
Torque [kNm]
250
340
200
150
320
300
280
Field
Dyno
0 2040 60
Time [sec]
Fig. 2: Test comparison cases 1 (Dynamometer) and 2 (Field)
20 | SIMPACK News | July 2013
100
50
0 50 100150200250300350
Carrier rotation [deg]
Fig. 3: Planet upwind loading comparison for test case 1
of the numerical models used. The in-depth
GRC gearbox measurements were used
to validate gearbox-modeling techniques
and to determine the right compromise
between model complexity and accuracy. A
set of models that represented different levels of fidelity was constructed. A total of five
models were compared; they are presented
in Table 1. The main shaft torque time series
from the measurements were input directly into the main shaft of the multi-body
model. Two test cases were used; these are
presented in Fig. 2.
The comparison results, presented in Fig. 3,
show that the computational models
were able to reproduce the planet bearing
loads well. This indicates that a multi-body
SIMPACK model can accurately reproduce
actual test conditions numerically. More
details on this work can be found in LaCava
et al. [6, 7].
THE CASE STUDY
The gearbox from the Gearbox Reliability Collaborative (GRC) [5] coordinated by
the National Renewable Energy Laboratory (NREL), Colorado, USA, was used as the
case study for most wind turbine drivetrain
modeling and analysis work at CeSOS. The
GRC drivetrain is a 750 kW high-speed generator type. It has one planetary and two
parallel gear stages and uses the three-point
support system. The GRC gearbox within its
drivetrain is illustrated in Fig. 1.
COMPARISONS AGAINST EXPERIMENTAL MEASUREMENT RESULTS
In collaboration with NREL, the experimental
measurements from the GRC gearbox were
used for extensive model fidelity studies.
The GRC has conducted extensive field and
dynamometer test campaigns on two heavily instrumented wind turbine gearboxes.
The data from the planetary stage is used to
evaluate the accuracy and computation time
DETAILED MODELING STUDY OF THE
PLANET CARRIER IN THE GRC GEARBOX
A detailed modeling study of the planet
carrier in the GRC gearbox was also performed. This study was carried out in two
parts. First, the influence of the subcomponents mated to the planet carrier in the
gearbox assembly was investigated in detail.
These components consist of the planet
pins, bearings and the main shaft. Fig. 4
shows how these subcomponents were
modeled as rigid in order to investigate their
influences on the planet carrier. This was
performed in Abaqus. Second, the flexible
body modeling of the planet carrier for use
proximity sensor at 47°
(fixed to DUMMY body)
sun gear
(output)
planet gear
planet gear
ring gear
planet carrier
(input at the main shaft interface)
Fig. 5: SIMPACK model used for the planet carrier modeling study
SIMPACK News | July 2013 | 21
CUSTOMER APPLICATION | Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU
Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU | CUSTOMER APPLICATION
Main shaft shear forces
Main shaft axial forces
Main shaft bending moments
Main shaft torque
3m
3m
4m
48.2 m
54.81 m
z
x
40 m
70 m
7m
line 1
60°
y
clumped
weights
line 2
x
39
.7
600 m
m
610
line 3
300°
m
Fig. 6: The floating spar system for the GRC wind turbine
in SIMPACK is examined through the use of
condensed finite element and multi-body
models. Both eigenvalue analyses and time
domain simulations were performed. Fig. 5
illustrates the SIMPACK model used for this
dummy body (in blue)
where the nacelle motions
are applied
study. Only the planetary stage was modeled as the focus was on the planet carrier.
It was found that the compliance of the
planet pins was very important. Using rigid
planet pins leads to a very stiff planet car-
r
ato
ner
ge
loads, motions
Fig. 7: Application of the calculated loads, generator speed and motions as inputs into
the drivetrain model. The torque arms and housing casings are not shown.
22 | SIMPACK News | July 2013
ed
spe
rier with many significantly higher eigenfrequencies. Various methods of flexible
modeling of the planet carrier were evaluated, and an efficient method of prescribing
the Frequency Response Modes (FRMs) was
proposed. More details of this work can be
found in Xing et al. [8].
MODELING AND ANALYSIS OF THE
DRIVETRAIN IN A SPAR-TYPE FLOATING
WIND TURBINE
In this study, the GRC drivetrain and wind
turbine were mounted onto a spar-floating
platform to be deployed for offshore wind
use. The floating spar system was designed
in-house in CeSOS and is similar to the
HyWind and OC3 spar concept. Fig. 6 illustrates the dimensions of the design spar
platform. This is a catenary moored spar
system with three mooring lines. The main
purpose of the mooring lines is to keep the
structure stationary, with minimal sway.
The delta mooring line layout provides additional yaw stiffness. The platform is also
ballast-stabilized, which results in large roll
and pitch hydrostatic restoring moments
due to the low center of gravity.
A decoupled solution was used in this
instance. First, the global aero-hydro-elasticservo floating wind turbine (FWT) problem
is solved using HAWC2
[2]. The loads,
generator speed, and motions experienced
by the drivetrain in the HAWC2 analysis are
then used as inputs for a SIMPACK drive-
Fig. 8: Comparison of frequency spectra of the axial force, shear force, bending moment and
torque on the main shaft. The mean wind speed at hub height is 20 m/s.
Axial forces
Radial forces
Tilting moments
INP-A
180°
PLC-B
460 m
PL-B
200 m
train model. See Fig. 7 for an illustration
of the applications of these inputs into the
drivetrain model.
A comparison of the responses in the FWT
and its land-based equivalent counterpart
was performed. It was determined that
there are general increases in the standard
deviations of the main shaft loads and internal drivetrain responses. These increases are
larger in the response variables associated
with the low-speed planetary stage. This is
intuitive as the gearbox has the capability to
isolate loads between the individual stages.
These differences, however, do propagate
to the intermediate- and high-speed stages
at the less severe load cases. Comparisons
of the frequency spectra (Fig. 8 and Fig. 9)
show that wave-induced responses appear
both in the main shaft loads and internal
drivetrain response variables. More detailed
investigations into the individual contributions of the main shaft loads and nacelle
motions revealed that the increases in the
internal drivetrain responses in the FWT are
a result of the increase in the main shaft
non-torque loads that the FWT experiences.
Fig. 9: Floating wind turbine vs. land-based wind turbine. Comparisons of the frequency spectra of the INP-A (main bearing),
PLC-B (downwind planet carrier bearing) and PL-B (downwind planet gear bearing). The mean wind speed at hub height is 20 m/s.
SIMPACK News | July 2013 | 23
CUSTOMER APPLICATION | Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU
2nd mode
1200
3rd mode
4th mode
Hz
1000
800
600
400
200
0
600
2.000
kW
5.000
10.000
Fig. 10: Eigenfrequency comparison, 0.6 and 2MW: 3 stages, 5 and 10 MW: 4 stages
Frequency (Hz)
The nacelle motions, i.e., inertia forces have
excitations are found in the Campbell dialimited contributions to the FWT drivetrain
grams. See Fig. 11 for the Campbell diagram
responses.
of the 10 MW drivetrain. More details of
Lastly, an additional main bearing was
this work can be found in Nejad et al. [12].
added to the GRC drivetrain to
reduce the non-torque loads
going into the gearbox. This is
Resonance diagram (10.000 KW)
the so-called four-point support
system. It was found that the
1.000
tooth and bearing loads in the
planetary stage are significantly
900
reduced as a result of this additional main bearing. More de800
tails of this work can be found
in Xing et al. [9–11].
700
DYNAMICS OF LARGE
OFFSHORE WIND TURBINE
600
DRIVETRAINS
In this study, the internal dy500
namics of wind turbine gear
trains were examined. The
pure torsional model is applied
400
in SIMPACK for eigenmodes
analysis and the evaluation
300
of internal excitations by the
use of resonance diagrams.
200
The gear trains studied were
designed in-house using industrial standards. Case studies
100
of 0.6, 2, 5 and 10 MW were
performed. A negative trend of
0
eigenfrequencies was observed
0 5 1015202530
in the larger gear trains. This is
Rotor speed (rpm)
illustrated in Fig. 10. Many possible resonances due to internal
Fig. 11: 4-stage drivetrain resonance diagram (10 MW)
24 | SIMPACK News | July 2013
p1
0
m1
p1: near the point of engagement
of the driven gear
0: in the vicinity of the pitch point
of the driven gear
m1: close to the recess point
of the driven gear
2
0
Raw data
2-parameter Weibull
generalized gamma
3-parameter Weibull
-2
log (-log(1-Pf))
1400
4
-4
-6
-8
-10
-12
Point p1
-14
-16
2.533.5 44.5 55.56 6.577.5
log (∆Pmax)
4
2
Fig. 12: Positions of the considered points on the gear profile
0
Raw data
2-parameter Weibull
generalized gamma
3-parameter Weibull
-2
The results indicate that the generalized
[5] Link, H., LaCava, W., van Dam, J., McNiff, B.,
gamma distribution is better than the
Sheng, S., Wallen, R., McDade, M., Lambert, S.,
Weibull distribution, though the twoButterfield, S., Oyague, F., "Gearbox Reliability
parameter Weibull
Collaborative
project
“Research at CeSOS in drivetrain
is simpler to use. A
report: Findings from
modeling and analysis uses SIMPACK
so-called 'limit-state
Phase 1 and Phase 2",
to accurately model and analyze
function' for contact
National
Renewable
the wind turbine drivetrain...”
fatigue
analysis
Energy
Laboratory,
could be established
Report number: NREL/
based on the pitting life prediction model
TP-5000-51885, 2011.
presented in this work. More details of this
[6] LaCava, W., Xing, Y.H., Guo, Y., Moan, T.,
work can be found in Dong et al. [13, 14].
"Determining Wind Turbine Gearbox Model
CONCLUSIONS
The wind turbine drivetrain is a crucial component of the wind turbine that needs to be
better studied for offshore applications. Research at CeSOS in drivetrain modeling and
analysis uses SIMPACK to accurately model
and analyze the wind turbine drivetrain in a
variety of research topics.
ACKNOWLEDGEMENTS
The author would like to thank William
LaCava, University of Massachusetts, Yi
Guo, NREL, and Wenbin Dong and Amir
Rasekhi Nejad, CeSOS, for their contributions to this article.
REFERENCES
[1] Jonkman, J., Buhl, M.L., "FAST's User Guide",
National Renewable Energy Laboratory, Report
number: NREL/EL-500-38230, 2005.
[2] Larsen, T.J., Hansen, A.M., "How 2 HAWC2",
Risø National Laboratory, Technical University of
Denmark, Report number: Risø-R-1597 (ver. 3-1)
(EN), 2007.
[3] Ormberg, H., Mo, K., "SIMO — User's manual
version 3.6", MARINTEK, Report number: 2009.
[4] Ormberg, H., Passano, E., "RIFLEX — User's
Manual Version 3.6", MARINTEK, Report number: 2009.
Complexity using Measurement Validation and
Cost Comparison", in: European Wind Energy Association annual event, Copenhagen, 2012.
[7] LaCava, W., Xing, Y.H., Marks, C., Guo, Y.,
Moan, T., "Three-Dimensional Bearing Load
Share Behavior in the Planetary Stage of a Wind
Turbine Gearbox", under review in IET Renewable
Power Generation 2012.
[8] Xing, Y.H., Moan, T., "Multi-Body Modelling
and Analysis of a Planet Carrier in a Wind Turbine
Gearbox", Article accepted in Wind Energy 2012.
[9] Xing, Y.H., Karimirad, M., Moan, T., "Effect of
Spar-Type Floating Wind Turbine Nacelle Motions
on Drivetrain Dynamics", in: European Wind
Energy Association annual event, Copenhagen,
2012.
[10] Xing, Y.H., Karimirad, M., Moan, T., "Modelling and Analysis of Floating Spar-Type Wind
Turbine Drivetrain", Accepted for publication in
Wind Energy 2012.
[11] Xing, Y.H., Moan, T., Karimirad, M., Etemaddar, M., "Influence of the Design Parameters of a
Spar-Type Floating Wind Turbine on Component
Loads, with Emphasis on the Drivetrain", Under
review in Wind Energy 2012.
[12] Nejad, A.R., Xing, Y.H., Moan, T., "Gear
Train Internal Dynamics in large Offshore Wind
Turbines", in: ASME 11th Biennial Conference
on Engineering Systems Design and Analysis,
Nantes, France, 2012.
log (-log(1-Pf))
1st mode
DYNAMIC TIME-DOMAIN-BASED
TOOTH CONTACT FATIGUE ANALYSIS
In this experiment, researchers performed
a time-domain-based gear contact fatigue
analysis of the GRC gearbox. The main
purpose was to investigate how the longterm distribution of gear contact pressures
can be represented by analytical functions
such as the Weibull distribution and the
generalized gamma distribution. These
distributions are necessary to design reliable
gears using probabilistic approaches and
to develop simplified methods for practical
design. A new, simplified predictive subsurface pitting model estimates the service
lives of gears under dynamic conditions. The
decoupled analysis method is used for the
dynamic analysis of the gears in the GRC
gearbox. First, aero-elastic simulations were
performed on the land-based GRC wind
turbine using FAST [1]. The main shaft loads
calculated from FAST were then used as
inputs in a SIMPACK drivetrain model. Three
points on the gear teeth were considered
for pitting lives as illustrated in Fig. 12.
The Weibull and generalized gamma distributions were then used to fit the long-term
probabilistic distributions of the gear tooth
contact pressures. An example of these fits
is presented in Fig. 13.
-4
-6
-8
-10
-12
Point 0
-14
-16
2.533.5 44.5 55.56 6.577.5
log (∆Pmax)
5
0
log (-log(1-Pf))
1600
Yihan Xing, Centre for Ships and Ocean Structures, Marine Technology Centre, NTNU | CUSTOMER APPLICATION
Raw Data
2-parameter Weibull
generalized gamma
3-parameter Weibull
-5
-10
-15
Point m1
-20
2.533.5 44.5 55.56 6.577.5
log (∆Pmax)
Fig. 13: Long-term results of the maximum
contact pressure range in the sun gear
[13] Dong, W.B., Xing, Y.H., Moan, T., "Time
Domain Modelling and Analysis of Dynamic Gear
Contact Force in Wind Turbine Gearbox with
Respect to Fatigue Assessment", Energies 2012,
5 (11), 4350-4371.
[14] Dong, W.B., Xing, Y.H., Moan, T., Gao, Z.,
"Time Domain based Gear Contact Fatigue
Analysis of a Wind Turbine Drive Train under
Dynamic Conditions", Accepted for publication in
International Journal of Fatigue 2012.
SIMPACK News | July 2013 | 25
CUSTOMER APPLICATION | Sebastian Rilli, Philipp Klausmann, Aero Dynamik Consult GmbH,
Stefan Hauptmann, SWE, University of Stuttgart
Sebastian Rilli, Philipp Klausmann, Aero Dynamik Consult GmbH | CUSTOMER APPLICATION
Stefan Hauptmann, SWE, University of Stuttgart
1.3
Aeroelastic Simulation of Wind Turbines
Coupling SIMPACK with ADCoS
Rotational speed ADCoS
Rotational speed coupled
1.25
1.2
Rotational speed [rad/s]
1.15
As the power output of wind turbines grows, the
dimensions of the gearboxes that transmit power
from the rotor to the generator have increased
accordingly. The impact of dynamic gearbox
behavior on other wind turbine components is
significant, and is the subject of current investigations. To gain a deeper understanding of the
influence gearboxes have on other components
of a wind turbine, the multi-body simulation
(MBS) software SIMPACK was coupled with the
wind turbine load calculation tool ADCoS. ADCoS — a finite element tool specifically
designed for wind turbine simulations — has proven its accuracy and efficiency over
the past years. SIMPACK is a powerful tool for simulating gearboxes and drivetrains.
This combination utilizes the specialties of both tools to investigate the dynamic
influences of the drivetrain on other components of a wind turbine. This article lays
out the realization of this coupling and its impact on the dynamic simulation of
wind turbines.
1.1
1.05
1
0.95
0.9
0.85
0.8
50 100150 200250
Time [s]
Fig 2: Comparison of rotor speed in both a coupled and a pure ADCoS simulation
26 | SIMPACK News | July 2013
gear contacts of the drivetrain model are
modeled using the very detailed and realistic force element FE 225. The gearbox is a
typical design for a 5 MW wind turbine with
two planetary gear stages and one parallel
gear stage.
LOAD CASES
Standard load simulations have been
performed to validate the correct implementation of the coupling. These tests
also investigate how the detailed modeling
of the drivetrain influences the results of
load simulations compared to pure ADCoS
simulations. Three different design load
cases (DLC) are carried out according to IEC
61400 [1]: DLC 1.1 Power Production, and
emergency shutdown with (DLC 2.2) and
without (DLC 5.1) occurrence of loss of electrical network connection. The evaluation
of the results of an emergency shutdown is
limited to the scenario with the additional
occurrence of a grid loss.
RESULTS OF LOAD CALCULATIONS
To validate the correct implementation of
the coupling, the rotational speed of the rotor and the generator torque are compared
between a coupled simulation and a pure
ADCoS simulation. Fig. 2 depicts the rotational speed of the rotor for DLC 1.1 (power
production) of the turbine facing a turbulent
wind field (mean wind speed of 8 m/s). The
similarity of the two curves shows that the
coupling was implemented correctly. Precise
observation of the two curves reveals larger
fluctuations in the coupled simulation.
These fluctuations are particularly distinctive when the rotor speed reaches the rated
5
x106
4.5
4
3.5
Torque [Nm]
ADCOS (AEROELASTIC AND DYNAMIC
COMPUTATION OF STRUCTURES)
ADCoS is a simulation tool specifically designed for the aeroelastic simulation of wind
turbines. It is used by Aero Dynamik Consult
GmbH to predict loads on wind turbine
components. Using this program, a wind
turbine is modeled by either Bernoulli or
Timoshenko beam elements — each beam
element consists of two nodes with six degrees of freedom (Fig. 1). The calculation is
based on the general equations of motion
for oscillating systems. The equations of motion are solved by non-linear, implicit integration in the time domain. Centrifugal and
acceleration stiffness are considered in the
equations of motion. Stiffness and damping matrices are updated simultaneously
at every time step. Nonlinear effects — like
the flap-wise deformation of the rotor
blades — are included in the simulation. ADCoS considers the torsional dynamics of the
rotor blades when calculating aerodynamic
loads. This leads to very accurate results for
displacements and bending moments. Due
to use of a general finite element method
in ADCoS, arbitrary support structures and
tower designs can be modeled and analyzed.
INTERFACE BETWEEN SIMPACK AND
ADCOS
Both non-turbulent and turbulent wind
fields can be used to perform calculations
The best way to utilize the benefits of both
according to IEC [1],
SIMPACK and ADCoS
GL [3] and DIBT [2]
“The best way to utilize the
is co-simulation. The
standards. The combenefits of both SIMPACK and ADCoS
interface is realized
ponent of interest of
is co-simulation.”
via a standard SIMthis investigation, the
PACK interface using
drivetrain, is modeled by a simple double
a Force Element. Windows sockets — a
oscillator.
library of functions for the exchange of data
in a network — are applied for the data
exchange. The Windows sockets function
library can communicate via network, allowing users to run ADCoS and SIMPACK
on different computers within the same
network.
For the simulation, the wind turbine is modeled in ADCoS, and the detailed drivetrain
in SIMPACK. The parameters exchanged in
this coupled simulation are the aerodynamic
torque at the hub, the rotational speed of
the rotor, the generator torque and the
rotational speed of the generator. The aerodynamic torque of the rotor is determined
in ADCoS and submitted to the SIMPACK
drivetrain model, where it is applied at the
main shaft.
The torque-speed curve of the generator
is considered in the drivetrain model by
Control Element 146. The rotational speed
of the rotor, the generator torque, and the
rotational speed of the generator are determined via time integration in the SIMPACK
drivetrain model and sent back to ADCoS.
With this information, ADCoS continues
Fig 1: ADCoS wind turbine model
its calculation for the current time step. All
rotor speed of the wind turbine. The same
effects are seen and are even more significant for the generator torque of a coupled
and a pure ADCoS simulation (Fig. 3). The
fluctuations in the range of the rated rotor
speed originate from resonance effects in
the drivetrain and will be subjected to a
more detailed investigation.
An even more interesting load case concerning the dynamic behavior of the drivetrain
is the emergency shutdown of the wind
turbine since excitations of a wide range
of frequencies arise from this situation. A
significant effect of the detailed modeling
of the drive train can be observed in Fig. 5.
Here, an emergency shutdown with a loss
of network connection occurs at 80 s simulation time. The wind turbine is exposed to
a homogeneous wind field of 8 m/s in this
simulation. Due to the grid loss, the rotor
speed rises in the coupled and the pure
ADCoS simulation immediately after the
emergency shutdown. Following this peak,
oscillations with a constant frequency occur
for the rotor speed of the coupled simulation. Oscillations with this frequency are
apparent in the generator speed and the
aerodynamic torque of the rotor as well.
The reason for this effect is the modeling
of the drivetrain in this investigation. The
generator is modeled solely by its torquespeed curve. This neglect of damping of the
generator leads to a direct influence on any
3
2.5
2
1.5
1
0.5
0
Generator torque ADCoS
Generator torque coupled
0 100200300400500600
Time [s]
Fig 3: Comparison of generator torque of a coupled and a pure ADCoS simulation
SIMPACK News | July 2013 | 27
CUSTOMER APPLICATION | Sebastian Rilli, Philipp Klausmann, Aero Dynamik Consult GmbH,
Remco Mansvelders, Wolfgang Trautenberg, SIMPACK AG | SOFTWARE
Stefan Hauptmann, SWE, University of Stuttgart
SIMPACK Realtime
change in the aerodynamic torque on the
rotor and generator speed. For future applications of the coupling, damping effects
of the generator will have to be considered
in the model of the generator to investigate
these oscillations in a more realistic manner.
CONCLUSION
The development of a coupling between
SIMPACK and ADCoS reveals that a cosimulation of these programs is ideal for investigating the interactions of the drive train
with other components of a wind turbine.
The effects of a more detailed drivetrain
model that utilizes the features of SIMPACK
are clearly noticeable in the aeroelastic
simulation of a wind turbine. For future applications of this coupling, more parameters
should be exchanged between the two
processes. For a more accurate reproduction
of real dynamic wind turbine behavior, the
forces and moments at the gearbox support
must be submitted from SIMPACK to ADCoS. This will enable the model to transfer
these loads to the tower via the bedplate.
To capture the influences of the drivetrain
and other components more accurately, the
28 | SIMPACK News | July 2013
Rotational speed [rad/s]
RESONANCE ANALYSIS OF THE
DRIVETRAIN
In order to gain a deeper understanding of
how the dynamics of the drivetrain influence other components of a wind turbine,
the drivetrain in this investigation is specially
modeled to have an eigenfrequency that
can be excited in the range of the rated
rotor speed. For the drivetrain used in this
analysis, the rotational mode of the planets
of the second gear stage is excited in the
Fig 4: SIMPACK drivetrain model
region of rated rotor speed. Characteristic
of this mode are an identical motion of all
planets relative to their bearings and a pure
motions and accelerations of the
rotation of the planet carrier, the ring wheel
and the sun. The inertia of the rotor is the
nacelle will have to be transferred
reason why only a very weak influence of
to the drivetrain model. This will influence
this
resonance
the forces and
of the drive train
“The effects of a more detailed
torques acting
can be observed
drivetrain model that utilizes the features
on the drivein the rotor speed
of SIMPACK are clearly noticeable in the
train.
Finally,
and the rotational
aeroelastic simulation of a wind turbine.”
the damping
speed of the sun
of the generaof the first planetary stage. The effect of
tor needs to be considered in the drivetrain
the resonance is clearly recognizable in the
modeling in SIMPACK in order to obtain
rotational speed of the sun of the second
more realistic results.
planetary stage and the generator speed.
The reason for the significance of this effect
is the neglect of the damping of generator
1
enabling the generator shaft to oscillate undamped. Since there is no significant impact
of this resonance on the rotor speed, the
influence on other components of the wind
0.8
turbine is negligible.
With SIMPACK 9.3, the new solution
for realtime simulations — SIMPACK
Realtime — was introduced. SIMPACK
Realtime enables the use of complex
models for a wide range of performance-critical realtime applications
such as Hardware-in-the-Loop (HiL) and
Software-in-the-Loop (SiL) scenarios.
Typical applications include handling
and comfort simulations, and ECU testing and component test rigs, e.g., for
gearboxes and engines. To achieve realtime for complex models, SIMPACK Realtime runs on INTEL x86 hardware and
Linux operating systems with realtime
kernel extensions. This brings realtime
simulation to an unprecedented level of
REFERENCES
[1] IEC 61400-1 Wind turbines — Part 1: Design
requirements, Third Edition, 2005-08
[2] Schriften des Deutschen Instituts für Bautechnik (DIBT). Richtlinie für Windenergieanlagen,
2004
[3] Germanischer Lloyd. Guideline for the Certification of Wind Turbines, 2010.
Rotor speed ADCoS
Rotor speed coupled
performance. For
example, detailed
vehicle
models
with more than
200
DOF and a
stepsize of 0.2 ms
have been successfully solved in
realtime.
Unlike
previous
realtime solutions,
SIMPACK Realtime
works
directly
with fully parameterized SIMPACK
models without a time-consuming codeor lookup table generation process.
SIMPACK Realtime supports a wide
variety of targets, including dSPACE and
Concurrent. It includes the possibility of
animating the simulation results in realtime and logging them to disk.
SIMPACK REALTIME
Following a long history of successful
realtime implementations (e.g., see [1] and
[2]), SIMPACK has developed the next step
in realtime simulation products, SIMPACK
Realtime. SIMPACK Realtime has many
advantages over its predecessor (SIMPACK
classic Code Export).
A SIMPACK model can run directly in realtime when the model has no constraints, is
stable when using a fixed step-size solver,
and the individual elements do not require
internal iterations.
To execute the model in realtime mode, the
user can remain in the SIMPACK environment and start the SIMPACK Realtime solver
directly, without a time-consuming code
generation and compilation process.
Whereas previously, the Code Export based
using the included Realtime animation.
It is also possible to capture the realtime
SIMPACK realtime models were directly
simulation results using the realtime logger
executed on proprietary realtime hardware
for offline post-processing or to replay the
and operating systems, SIMPACK Realtime
runs on standard realtime-enabled Linux
animation.
operating systems and communicates
with realtime computers via a dedicated
SIMPACK REALTIME SETUP
network connection, shared memory or a
SIMPACK Realtime is designed to run on
Linux systems with
user-defined com“...the user can remain in
realtime kernel extenmunication library.
the SIMPACK environment and start
sions such as SUSE
To fully utilize latest
multi core procesthe SIMPACK Realtime solver directly,
Enterprise, Debian, or
sor hardware, the
without a time-consuming code
Concurrent RedHawk.
SIMPACK Realtime
generation and compilation process.”
The communication
between
SIMPACK
solver contains an
Realtime and proprietary realtime systems
automatic parallel computation feature. Betakes place either via a dedicated peer-tosides running the model in realtime mode,
it is now possible to view the results directly
peer UDP network communication (this
is a dual computer setup, see Fig. 3) or via
shared memory (a single computer setup,
Concurrent SimWB
e.g., with Concurrent Simulation WorkSIMPACK Realtime
Bench, see Fig. 4). The SIMPACK model
communicates via u-Inputs and y-Outputs
with the outside world.
Realtime clock
0.6
0.4
SIMPACK REALTIME PACKAGE
The SIMPACK Realtime package contains
the following products:
Logitech G27
dSpace
0.2
0
SENSODRIVE Sensowheel
User supplied
General UDP
7075 808590 95100
Time [s]
Fig 5: Comparison of rotor speed of a coupled and a pure ADCoS simulation of an emergency
shutdown with loss of electrical network connection
� IP-Header
�
�UDP-Header
�
Fig. 1: Realtime targets supported by SIMPACK
UDP
USB
IP-Datagram
�
UDP-Data �
UDP-Datagram
shared memory
FlexRay
CAN
• SIMPACK Realtime solver
• SIMPACK Realtime animation
• SIMPACK Realtime logger
The specific SIMPACK Realtime solver
enables direct realtime integration of the
model. It uses a constant step-size to solve
the equations of motion in realtime and
guarantees a fixed frame rate with a very
low margin. Frame rates of 0.2 ms in a
SIMPACK News | July 2013 | 29
SOFTWARE | Remco Mansvelders, Wolfgang Trautenberg, SIMPACK AG
Wolfgang Trautenberg, SIMPACK AG | SOFTWARE
Utilizing Multi Core CPUs
with SIMPACK 9
• Zero turnaround time after model
changes
• Offline models can be used for
realtime simulation
• Parts-based suspension models
supported
• Built-in multi-core support
• Communication with realtime targets
via UDP or shared memory
• Use of latest off-the-shelf hardware,
no expensive specialized realtime
hardware needed
• Various realtime targets predefined,
user target interface supported (Fig. 1)
• Can be applied to a wide range of
industrial applications in addition to
the automotive sector.
• Realtime animation and Realtime
logging included
• Fully parameterized models
CONCLUSION
SIMPACK Realtime introduces a new way
to run SIMPACK models directly in realtime
30 | SIMPACK News | July 2013
parameter studies, job runs can
be automatically distributed using
SIMPACK scripts. This is used, for
example, to compute wind turbine
dynamic loadcase scenarios (DLC) [1].
This reflects the paradigm shift in computer
processor development. Previously, more
speed and computing power was achieved
by increasing the CPU frequency; today,
more computing power is obtained by
increasing the number of CPU cores on a
processor chip.
Multi core CPUs can be used to speed up
simulations either by running multiple
independent simulations concurrently, or
by running a single simulation with the
multiple cores and can be used with the
latest off-the-shelf hardware; a fixed frame
rate of 0.2 ms for a more than 200 DOF
vehicle model has already been achieved in
realtime in industrial applications.
REFERENCES
[1] www.simpack.com/fileadmin/simpack/
doc/newsletter/2009/SN_2_Nov2009_BMWHighDyn_TestBench_using_SIMPACK.pdf
[2] www.simpack.com/fileadmin/simpack/doc/
newsletter/2004/sn-2-04-vdym.pdf
8
Multi core realtime Linux environment
running SIMPACK Realtime
Realtime environment,
e.g., dSpace
Realtime hardware
7
6
5
engine test bench
UDP
CAN,
FlexRay
4
3
2
1
simulator
0
9.0
9.1
9.2
9.3
SIMPACK Re
lease
desktop driving simulator
Fig 1: CPU comparsions — Rail simulation
Fig. 3: Dual computer setup, SIMPACK Realtime communicates via UDP network with
realtime environment
Multi core realtime Linux environment running SIMPACK Realtime,
e.g., Concurrent RedHawk
Realtime hardware
engine test bench
shared
memory
CAN,
FlexRay
simulator
desktop driving simulator
Fig. 4: Single computer setup, SIMPACK Realtime communicates via shared memory with
realtime environment
parallel solver that utilizes multiple CPU
cores. Whether a parameter study of a
model needs to be completed as quickly as
possible, or a single solver run should be executed with maximum speed, the user has
the choice to employ either approach.
PARAMETRIC STUDIES
Parametric studies best utilize the CPU cores
if, for each parameter setting, a single core
solver run is performed (single core meaning
that the solver run only uses a single CPU
core). In this scenario, the CPU cores can all
be used without requiring any special solver.
Speedups that can be achieved scale almost
linearly with the number of CPU cores. For
benefits to
the
complete
application range: Automotive, Engine, Rail, Wind
and General Machinery. Figs. 1 and
2 show performance gains with the parallel
solver for different typical applications and
SIMPACK releases 9.0 through 9.4 and for
different number of CPU cores. The table
also shows that the performance of the
standard single core solver was significantly
improved over the different SIMPACK 9
releases as well.
PARALLEL SOLVER
Speeding up the simulation by using multiple CPU cores for a single solver run is more
challenging. In this case, the solver must
automatically distribute its computation
tasks across the different CPU cores. For a
set of equations which is loosely coupled or
uncoupled, splitting the computations into
different threads for simultaneous execution
CONCLUSION
on different CPU cores is straightforward.
SIMPACK's parallel solver was developed
And for large matrices, it is easy to use
with today's typical multicore engineering
multiple CPU cores to speed up the matrix
workstations in mind which have 4–16
manipulation.
cores distributed across one or two CPUs
However, the equations of motion of an
and use a symmetric multiprocessing (SMP)
MBS model are often highly coupled and
approach. The best performance gains
the matrices are typically small
are achieved when all CPU cores used are
and densely populated. For
on the same physical CPU. The chosen
these types of problems, no
approach for the parallelization is unique
standard or readily available
to SIMPACK and goes far beyond the trasolutions exist to automatiditional approach of simply evaluating Force
cally take advantage of multiple
Elements in parallel. Performance gains with
CPU cores. This challenge is
SIMPACK parallel solver have already led to
addressed by SIMPACK's new
significant simulation time reductions across
parallel solver which was introthe whole application range. Future versions
duced in its earliest version with
of SIMPACK will further improve the speed1
SIMPACK 9.0.
ups achievable with the parallel solver.
2
The parallel solver automatically
4
distributes solving the different
REFERENCES:
6
parts of the equations of motion
[1] S. Mulski, SIMPACK AG: Wind and Driveonto the available CPU cores. Sections
train Conference 2012 — Modeling Elements,
that must be executed sequentially are
Data-base Management, DLC Calculations (www.
automatically detected and evaluated
simpack.com/fileadmin/simpack/doc/papers/
in the proper sequence. The rest of the
Wind_Drivetrain_Conf_2012/Harms_Mulski_
equations are executed in parallel with a
Wind_Drivetrain_SIMPACK_congress_DLC.pdf)
strong focus on evenly distributing the workload on the
available CPU cores. The
30
results generated by single
25
core and parellel solver are
20
bit-identical.
SIMPACK 9.0 delivered an
15
initial version of the paral10
lel solver which brought
5
significant speed-ups to
0
certain applications. The
9.0
4
9.1
focus of the subsequent
9.2
6
releases (SIMPACK 9.1
9.3
SIMPACK Re
lease
9.4
through 9.4) was thereFig 2: CPU comparsions — Automotive simulation
fore to bring the speed-up
CP
Us
200 DOF vehicle model have already been
achieved in realtime. The Realtime solver
supports automatic parallelization in order
to utilize multiple cores.
The SIMPACK Realtime animation displays
the simulation results in realtime as a 3D
animation. It can run on the same computer
as the Realtime solver, or a different machine, and utilizes one or more CPU cores.
The Realtime animation communicates
with the Realtime solver over UDP. For each
simulation step, the Realtime solver sends
its state vector to the Realtime animation.
The Realtime animation also loads the
model and performs online Measurements
with the received state vector and displays
the results in a 3D animation. The Realtime
animation computes and displays the next
animation frame once it has finished displaying the previous one. The target update
frequency for the Realtime animation is
25 Hz, whereas typical Realtime solver stepsizes and communication step-sizes range
from 0.2 to 2 ms.
The SIMPACK Realtime logger — same as
the SIMPACK Realtime animation — receives
the state vectors which can be used for
post-processing, like data plotting or performing a replay of the animation.
without a time-consuming code- or lookup
table generation process. SIMPACK Realtime
runs on standard realtime-enabled Linux
operating systems and communicates with
realtime computers via a dedicated network
connection, shared memory, or a user defined communication library. Users don't
need to leave the SIMPACK environment
and have the benefit of using all model elements (with a constant calculation time) in
realtime. SIMPACK Realtime solver supports
automatic parallelization in order to utilize
Time [s]
Fig. 2: SIMPACK Realtime desktop driving
simulator using a high precision SENSODRIVE
steering wheel
With SIMPACK 9, not only were the
data structures and Graphical User
Interface completely redesigned, but
also the architecture of the SIMPACK
solver was updated and significantly
improved. Apart from optimizations of
the standard solver, a parallel solver
was implemented which is significantly
faster than a single core solver.
9.4
SIMPACK News | July 2013 | 31
1
2
s
• Most modeling elements supported
CPU
• Users do not have to leave the
SIMPACK environment
• Direct realtime simulation; no time
consuming code- or lookup table
generation required
Time [s]
KEY FEATURES
SOFTWARE | Stefan Dietz, SIMPACK AG
Stefan Dietz, SIMPACK AG | SOFTWARE
SIMBEAM Reloaded
The first versions of SIMPACK in the
equations of motion, full parameterizaearly 1990’s could already model flextion by SubVars, and the use of scripting
ible Bodies consisting of beam elements
for setting up and modifying SIMBEAM
without an interface to finite element
models. This allows the user to carry
software. The first available preprocesout automatic parametric studies of
sor was called BEAM, which could model
entire systems, including variants of the
straight beams based on the differential
flexible structures. Extra utilities, such
equations of the Euler-Bernoulli beam
as ASCII input decks for quickly setting
theory. BEAM was frequently used
up flexible towers for wind turbines or
to model leaf springs and to consider
suspension leaf springs, are no longer
the basic modes of a railway carbody,
necessary.
among other tasks. However, as BEAM
did not allow users to model beam
structures with an arbitrary topology
and geometry (such as a stabilizer or a
chassis sub frame), Intec GmbH (now
named SIMPACK AG) decided to develop SIMBEAM in 2001. Right from the
start, SIMBEAM was based on the finite
element
approach.
Euler-Bernoulli,
Timoshenko beam elements, rigid body
MODULE DESCRIPTION, LICENSING
elements and arbitrary topology and
In the SIMBEAM module, the beam strucgeometry could be used for setting up
ture — consisting of nodes, elements, cross
flexible
bodies.
section and material
This made SIM“SIMBEAM allows the user to
properties — can
BEAM the basis for
carry out automatic parametric studies
be set up in the
modeling several
of entire systems, including variants
SIMPACK Pre(-proflexible bodies in
of the flexible structures.”
cessor). The modal
drivetrain, engine
representation
of
and wind energy applications. With
the flexible Body is instantaneously generthe completely new implementation of
ated and updated when any parameter or
SIMBEAM in SIMPACK 9.4, we seized the
property of the beam structure is changed.
opportunity to expand its capabilities
If requested, the SIMPACK Post(-processor)
towards an automated set-up of the
can display element stress as a contour plot
Fig. 3: Definition of nodes and elements
of the drive shaft
and generate/display 2D plots of the stress
data as well. SubVars can be used throughout the entire modeling process (to define
materials, cross sections, nodes, elements,
and further properties of the flexible Body).
MODELING
element model has been imported into
Once the material and cross section
SIMPACK.
properties are set up, beam elements can
Linear isotropic material is defined by
be defined between nodes. Nodes were
Young’s modulus, Poisson’s ratio and the
introduced into SIMPACK 9.4 as a new
shear modulus. A combination of two of
modeling element in
these parameters is
“With the completely redesigned
order to make a clear
used to define the
graphical user interface,
distinction between
material. The density
nodes and Markers,
getting started and setting up
is used to set up the
and to enable a model
models is easier than ever.”
mass matrix. The dethat is consistent with
fined materials appear
flexible Bodies imported via FlexModal (FEin the model tree.
interface to NASTRAN, ABAQUS, ANSYS
Standard cross section types like circles,
etc.). Finally, in the equations of motion,
rectangles and ellipses (either full or holthe deformation of SIMBEAM Bodies is
low) are defined by their respective physical
represented by a modal approach; the same
dimensions. The values of the physical cross
approximation that is used when a finite
section parameters (cross section area, area
moments of inertia, torsional stiffness) are
computed from the dimensions. The geometry and physical cross section parameters
are shown in an element plot in the Cross
Section property dialog. Further cross sections can be represented by the "General"
cross section types. The "General Basic"
type enables the use of arbitrary double
symmetric cross section geometries with
homogeneous mass density, whereas the
“General Advanced” Cross Section type can
additionally incorporate twist-bend coupling
and a nonhomogeneous mass density into
Fig. 2: Offshore wind
turbine. SIMBEAM
structures: rotorblades,
tower and jacket
Fig. 1: Definition of cross sections for a drive shaft with conical sections
32 | SIMPACK News | July 2013
Fig. 4: The finished drive shaft model — cross section definitions are shown for elements selected in the user interface
SIMPACK News | July 2013 | 33
SOFTWARE | Stefan Dietz, SIMPACK AG
the beam elements. The "General
Basic" Cross Section requires as
input the cross section area, the
moments of inertia and the torsional stiffness. In the case of the
“General Advanced” Cross Section type, these values are input in
combination with their respective
material parameters. If one of the
“General” Cross Section types is
used, geometry information for
the 3D Page is generated based on
a polyline that can be specified in
the Cross Section dialog.
Switching the Body type to
SIMBEAM yields a new layout of
the user interface. The first tab,
"SIMBEAM", is used to set up
nodes and elements.
The positions of the nodes are
specified with respect to the Body
Reference Frame. Once defined in
the node table, their position is displayed on the 3D Page. The data
can be pasted from Excel sheets
into the node list. Otherwise, the
node list may be exported from
the body property dialog into a
comma separated file.
A usual beam element definition
— consisting of connectivity, element type, cross section type, and
cross section orientation — can
be defined in the element list of
the Body property dialog. The
new SIMBEAM enables the user
to assign two different cross
sections of the same standard
cross section type to the nodes
of the same element, assuming
a linear change of the cross section dimensions along the beam
element axis. This new feature
allows a considerable increase
in accuracy with a smaller number of elements, and therefore,
an easier set-up of the model,
e.g., for drive shafts with conical sections and leaf springs
with variable cross section
height over the length of
the longitudinal axis. For the
elements being defined and
selected, the 3D Page shows
their connectivity, their assigned cross sections, and the
cross section orientation.
For non-selected elements,
the 3D Page shows the element axes. Once valid, node
and beam definitions are
applied to the SIMBEAM
34 | SIMPACK News | July 2013
Stefan Dietz, SIMPACK AG | SOFTWARE
Bending moment about Z
x 103
Node: 4 (Refernced by 476)
Bending moment about Z:
Element 3: 600.617
Element 4: 603.067
1.20
1.12
1.04
0.96
0.88
0.80
0.72
0.64
0.56
0.48
0.40
0.32
0.24
0.16
0.08
0.00
-0.08
-0.16
-0.24
-0.32
-0.40
-0.48
-0.56
-0.64
-0.72
-0.80
-0.88
-0.96
-1.04
-1.12
-1.20
Fig. 7: Contouring of a bending moment in
the SIMPACK Post
Fig. 5: Bending eigenmode of the offshore jacket
Fig. 6: Torsional eigenmode of the offshore jacket
model. The equations of motion are generated, after which the 3D Page shows the
surface of the elements. Also, the element
data can entirely be pasted from Excel
the "Options" tab, geometric stiffening is
sheets into the element table. An export
always considered for the accelerations,
into a comma separated file is also available
angular velocities and angular accelerations
for the elements.
of the body reference frame, as well as for
In the equations of motion, the deformation
concentrated forces and torques on the
of the SIMBEAM Body is represented by a
nodes which are subjected to loads. These
modal approach consisting of eigenmodes
terms are automatically considered for the
and interface modes. Eigenmodes are conaforementioned interface load cases regardsidered for a user-defined frequency range
ing concentrated forces and torques.
that is relevant to
Stress
recovery
the respective ap- “...everything can be described by SubVars, data is generated
plication. Interface
and every modeling step can be achieved
if requested in the
modes are used to
by scripting commands, making it easy
"Loads" tab. Then,
obtain an accurate
to generate variants...”
the cross section
response to loads
forces (i.e., the
that act on a Body via Joints, Force Elements
normal force, the shear forces, the bending
and Constraints.
moments and the torsional torque) can be
Either inertia relief modes or frequency
displayed as contour plots in the SIMPACK
response modes may be used for this purPost. Corresponding 2D plots over time can
pose. These interface load cases are generalso be generated and displayed. By default,
ated for nodes which have a connection to
the 3D Page and the SIMPACK Post show
Force Elements, Constraints and Joints via
the beam model according to the assumpthe Marker-node connection types (rigid
tion that cross sections are always perpenbody link, interpolation, etc.) if the interface
dicular to the respective beam axis in the
mode generation is in the "automatic"
undeformed state, which yields a graphical
mode. Manual interface mode generation
representation with gaps if the beam axis
for selected directions is available in the
of two adjoining elements is kinked. This
Marker dialog.
makes it easier to detect modeling errors.
The tabs "Mass properties", "Modes" and
However, for presentation purposes, this
"Options" have the same functionality as in
can be replaced by a CAD representation
FlexModal, except for the check box labeled
of the beam structure which can be loaded
"Stiffness depends on loads", which enables
optionally into the flexible Body Primitive.
or disables the geometric stiffening terms in
the equations of motion. Geometric stiffenFUTURE DEVELOPMENTS
ing represents the preloads, which can act
Beyond SIMPACK version 9.4, SIMBEAM
on the structure and lower or increase the
will be extended towards an easier set-up of
stiffness of the flexible Body. If enabled in
detailed models. This could be achieved by
subdivision of one element into a number of
elements in order to easily increase the accuracy of the representation of inertia forces
within the structure. Conversely, unnecessary details could be removed from the
modeling by merging a group of elements
into a smaller number of elements. Preliminary tests revealed significant added value
from the variable cross section approach. It
seems promising to extend this approach to
the "General" Cross Section types as well.
BENEFIT OF THE NEW SIMBEAM
With the completely redesigned graphical user interface, getting started and
setting up models is easier than ever. The
physical dimensions of a SIMBEAM Body,
and everything else, can be described by
SubVars. Every aforementioned step can be
achieved by scripting commands, making
it easy to generate variants thereof with a
solver script. This makes it possible to adjust the properties of flexible structures in
automated calculations in order to achieve
an improved design. Users can now easily
set up parameterized flexible components,
e.g., wind turbine towers or suspension leaf
springs. Thus, the new SIMBEAM is the final
link required for fully automated DoE of
multi-body systems, including variations of
flexible structures.
SIMPACK News | July 2013 | 35
SIMPACK News
INSIDE THIS ISSUE
1. Holistic Simulation of a Bucket Wheel Excavator
2. Offshore Wind Turbine Hydrodynamics
Modeling in SIMPACK
3. Review of Motion Sickness Evaluation Methods
and their Application to Simulation Technology
4. 3D Simulation of the Human Middle Ear
with Multi-Body Systems
Node: 4 (Refernced by 476)
Bending moment about Z:
Element 3: 600.617
Element 4: 603.067
5. Wind Turbine Drivetrain Modeling and
Analysis Activities at CeSOS
Rail simulation
6. Aeroelastic Simulation of Wind Turbines
Coupling SIMPACK with ADCoS
7. SIMPACK Realtime
8. Utilizing Multi-Core CPUs with SIMPACK 9
SIMPACK Release
9. SIMBEAM Reloaded
© Jürgen Leuffen
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SIMPACK News
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