Reducing offshore pile driving noise:
Shape optimization of the impact hammer
Elin KLAGES(1) , Jonas VON PEIN(1) , Stephan LIPPERT(1) , Otto VON ESTORFF(1)(1) Hamburg University of Technology (TUHH), Institute of Modelling and Computation, Germany, mailto: mub@tuhh.de

Abstract
Offshore wind energy is an emerging source of electricity generation and new offshore wind parks are underconstruction around the world. The foundation of offshore wind turbines is most often realized driving steel
monopiles into the sea bed using impact hammers, a technique that causes high underwater sound pressurelevels threatening to harm marine mammals and other sea life. In order to protect the marine fauna, limiting
values have been introduced by several countries. Their fulfillment until now has been possible applying stateof-the-art sound mitigation systems. However, rapidly increasing dimensions of wind turbines with accordingly
increasing pile diameters require an ongoing development of sound mitigation systems. Nowadays appliedsound mitigations systems, e.g. bubble curtains, reduce the propagation of the emitted sound, but do not affectits generation. Therefore, modifying the sound source, i.e. the hammer and pile, to reduce the generation of thesound, has recently gained attention. This contribution focuses on the development of a hammer that causes lessnoise but is still capable of driving the pile. First results of optimizing the shape of the impact hammer regarding
its acoustic characteristics are presented.

Keywords: offshore pile driving, impact hammer design, shape optimization, particle swarm optimization

1

INTRODUCTION

In order to construct an offshore wind park, piles are often driven into the sea bed to serve as foundations
for wind energy turbines. In order to drive these piles, an impact hammer, usually consisting of two main
components, namely an impact weight and an anvil, is used. During pile driving, the impact weight falls
repeatedly on the anvil resting on the pile head. The anvil then transmits the impact to the pile, driving it into
the sea bed but also deforming the pile. The pile deformation excites sound waves in the surrounding water
as well as in the sea bed, often causing high underwater sound pressure levels. As these sound emission may
harm marine mammals and fishes, several countries have defined official limits that the sound pressure levels
must not exceed.
To comply with these regulations, several noise mitigation systems, e.g. bubble curtains, have been developedand successfully applied. However, the capacity of offshore wind turbines and with them the pile diameters are
steadily increasing, causing even higher sound pressure levels. For this reason, in addition to existing approaches
to hinder sound propagation, the development of an impact hammer with improved acoustic characteristics has
been recently gained attention.
This contribution focuses on the optimization of the shape of the main hammer components, i.e., impact weight
and anvil. Since no explicit analytical relationship of the hammer shape, defined as parameter vector θ , andsound pressure levels (SPL), i.e. SPL = f (θ ) can be formulated, the optimization relies on numerical methods.
Here, particle swarm optimization (PSO) is applied, an optimization method that only relies on the function
evaluations f (θ ), i.e. no gradients have to be computed numerically, and has been successfully applied in thecontext of shape optimization, [1].

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2

NUMERICAL MODEL

Two axisymmetric finite element (FE) models are used to compute the sound excitation and propagation causedby the hammer impact on the pile. The first model includes only hammer and pile and serves to simulate theimpact and to obtain the resulting deformation of the pile head. The pile head velocity vp (t) is then passed tothe second model, used to model the propagation of waves in pile, water, and soil. The described modelingapproach is visualized in Figure 1. Further specifications of the FE models can be found in [2], [3].
INPUT:
hammer design θ

Hammerpile model

OUTPUT/INPUT:
pile headvelocity vp (t)Acoustic model

OUTPUT:sound pressure p(t)Figure 1. Modeling the underwater sound pressure as a result of pile driving.
For the present contribution, the second model covers the propagation in water and soil up to 30 m distance tothe center of the pile. Although official limits include the SEL in 750 m and beyond, a relatively small model
is applied here, to keep the simulation time short and therefore the model suitable to be used within an optimization. However, a larger model would also include sound waves traveling in the sea bed whose contribution
to the SEL depends largely on the soil properties at the ram location. Therefore, a smaller model also serves
as a model less dependent on the specific location of the driven pile and therefore might be beneficial for the
purpose of defining a hammer design causing less sound emission independently of the specific site.
An approach to increase the considered range and additionally decrease simulation time is to replace the second
FE model by a transfer function. This approach is described in a publication by the same authors, in [4], but
has not been applied for the present contribution.
Here, a cylindrical pile with 70 m length, 6.5 m diameter, and 80 mm wall thickness serves as an example. The
embedded length of the pile is 35 m and the water depth is 30 m. Simulation time is set to 100 ms.
For the present contribution, the underwater sound pressure is evaluated based on the sound exposure level(SEL) according to Zt
2 p(t)2
1
SEL = 10 log10
dt
[dB],
(1)
t0 t1 p20
where p0 refers to the reference sound pressure for underwater sound, i.e. p0 = 1 µPa, and t0 to the referencetime, i.e. t0 = t2 − t1 = 1 s.

3

ANALYSIS OF THE INFLUENCE OF THE HAMMER DESIGN ON THE SEL

Although this contribution focuses on optimizing the hammer shape, an analysis of the influence of the hammer
material on the SEL is presented beforehand. The reason is that the material is rather easily described using
the density ρ and the Young’s modulus E, whereas the description of a realistic hammer shape requires several
parameters. The effect of material and shape, however, is linked, since the mass is changed by either density
or volume as is the stiffness by the Young’s modul or the length and the cross section.
For the purpose of analyzing the influence of the material parameters on the SEL, several hammer models withdifferent materials were generated to obtain the corresponding sound pressure levels. The shape was the sameas of the existing hammer MHU3500S by the company MENCK. Its original density and mass were varied
within a range of ±50%. The impact energy was set to 2000 kJ. For the first analysis, the original material wasused for one of the hammer components, while the material of the other were modified. 100 samples have been
generated. The results are shown in Figure 2. For the second analysis, the material of both components werechanged simultaneously, i.e, the parameter study was based on 4 parameters. 300 samples have been generated.
The results are shown in Figure 3.

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196

SEL [dB]

194
192
190
188
4,000

7,850

12,000density [kg/m3 ]

100

210

320

4,000

12,000density [kg/m3 ]Young’s modulus [GPa]impact weight

impact weight

7,850

100

210

320

Young’s modulus [GPa]
anvil

anvil

Figure 2. Parameter study hammer material for both hammer components individually.

196

SEL [dB]

194
192
190
188
4,000

7,850
density [kg/m3 ]impact weight

12,000

100

210

320

Young’s modulus [GPa]impact weight

4,000

7,850
density [kg/m3 ]anvil

12,000

100

210

320

Young’s modulus [GPa]anvilFigure 3. Parameter study hammer material for both hammer components simultaneously.
The results of the first analysis indicate that the SEL decreases with increasing mass and decreasing stiffness.
Although this can be observed for both components, impact weight and anvil, the influence of the material of
the impact weight seems to be stronger. Regarding the impact weight, a similar behavior of the SEL can beobserved in the results for the second analysis. No clear relationship for the material of the anvil, however,can be established from the results shown in Figure 3. Furthermore, the corresponding correlation coefficients,
shown in Table 1, support the above stated and indicate that especially the influence of the anvil design on the
SEL depends strongly on the design of the impact weight.

Analysis 1
Analysis 2

Table 1. Correlation factors for material parameters and the SEL.
density impact weight E-Modul impact weight density anvil E-Modul anvil
-0.79
0.67
-0.67
0.77
-0.73
0.60
-0.16
0.13

Therefore, an optimization of the anvil should only be performed, if the design of the impact weight is alreadyknown, or in a joint optimization. The correlation coefficients regarding the material of the impact weight also
decrease from analysis 1 to 2, indicating a low dependency on the shape of the anvil. In order to include all
possible coupled effects, the optimization, presented in the following section, includes both hammer components.

4

OPTIMIZATIONThe optimization problem considered here, i.e. defining the shape of the hammer components to minimize thesound emission caused by the hammer impact on the pile, is challenging. First, an integration of the FE model

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into the optimization is required since no explicit analytical relationship of the hammer shape and the soundpressure emission is known. Second, the hammer design underlies several restrictions, e.g, the size, mass, andmanufacturability of the hammer components, but also the ram efficiency, drivability of the pile, and tensionsof the material caused by the impact. Even more difficult to determine, but equally important, is the durabilityof the hammer.
The following sections present an optimization approach taking for now only relatively low restrictions in size,
efficiency, and driveability into account.
4.1 Particle swarm optimization
The PSO is a method to optimize nonlinear functions, also applicable for black box problems as it is the casehere, adapted from the behavior of animal swarms, e.g. birds or fish, originally proposed by [5]. Although themethod does not guarantee to find the optimum, it is commonly referred to as an optimization method.
As proposed in [6], the position x of each particle d is updated every step k, usingd
xk+1= xkd + vdk+1 ,vdk+1 = w vdk + c1 r1

(2)


d

p

− xkd



+ c2 r2pk − xkd



,

(3)

where k refers to the current time step, k + 1 subsequently to the next time step, v refers to the particle velocity,and p to the best position of either the current particle pd considering all time steps or the current time step
considering all particles pk . The PSO parameters are the inertia w, the cognitive factor c1 , the social factor
c2 , both equal two and two random factors r1 , r2 ∈ [0, 1]. Several extensions of the above definition have been
proposed, however, this contribution focuses on this basic version of PSO.
4.2 Setup of the optimization problem
The hammer design with best acoustic properties within a certain design space can be identified as it causes thelowest underwater sound pressure levels. Here, it is important to compare sound pressure levels that result fromthe same amount of energy transmitted to the pile. The impact energy, in the model defined by the drop heightof the impact weight, however, is usually not fully transmitted to the hammer. Since less energy transmitted
to the pile would also cause less sound emission, using the SEL as the objection value could lead particles tomove towards less efficient hammer designs. To avoid the above, the ram efficiency, defined as η = EP /E0 , i.e.
the relation of the energy transmitted during the impact to the pile EP to the energy of the impact weight E0
before the contact of impact weight and anvil, is part of the objective function. The applied objective functionis therefore defined asmin SELη = SEL − 10 log10 (η) ,
(4)
where
η ≥ 0.5,(5)max(vp (t)) ≤ 0.5 m/s.

(6)

The constraints in Equation (5) and (6) were introduced to avoid particles moving towards very unrealistic
hammer designs regarding their ram efficiency and ability to drive the pile into the sea bed.
If Equation (5) or (6) is not fulfilled, the inertia factor in Equation 3 is set to zero for the corresponding
optimization step and particle. If the stated conditions are fulfilled, the inertia factor w is set to 0.8. The socialand cognitive factor are chosen to be c1 = c2 = 2.
The parameters for the hammer design were chosen to be interpretable, to be able to get insights of theirinfluence from the optimization. The definition of the parameters is shown in Figure 4. One example of a6234

possible hammer design defined by the presented parameterization can be found in Figure 5. Parameters include
height, radius, and inclination of the components. Additionally, curvatures of the outer surfaces are defined.
Restrictions of the parameter space are stated in Table 2. The initial particle positions were chosen to havevalid shapes and η > 0.5, but are otherwise randomly placed.

impactweightanvil
pile

Figure 4. Parameterization.

Figure 5. A simplified axis symmetric illustrationof an existing hammer (left) in comparison to apossible hammer design for the proposed parameterization.

Table 2. Parameter bounds.
hW

hA1

hA2

rW

min

1m

0.5 m

-hA1 + 0.5 m

0.2 m

max

15 m

4m

3m

4m

αW  
− cot hrW
 W

r
−rW
+ cot W, max
hW

αA




m
− cot 3.45
 hA1 m
+ cot 0.55
hA1

rC

RC

|RW |, |RA |

0.2 m

5m

60 m

rW

50 m

300 m

4.3 Results and analysis
36 optimizations steps, i.e. 540 hammer evaluations, were performed until the process was stopped due to no
improvement in the SELη within the last 8 steps. The development of the objective value SELη , the efficiency and the design parameters over the optimization steps are shown in Figure 7. The objective value SELη
decreased successfully from 177 dB for the lowest value for the initial designs to the overall lowest value of170.6 dB. At the same time, the efficiency increased, staying over 0.8 after only ten steps and over 0.9 after
23 steps. The latter observation demonstrates that an unrealistic decrease in the SELη due to less energy transmitted to the pile was avoided using the modified objective value SELη defined in Equation (4). However, thedevelopment of the efficiency η also indicates that the penalization of the efficiency η might be too high, as
efficiencies between 0.8 to 0.9 may also be acceptable.

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impact
weight

anvil

pile

Figure 6. Simplified illustration of the hammer design with lowest SELη . The corresponding values are
SELη =170.6 dB, SEL=170.3 dB, η=0.94.
The development of the design parameters for this example shows that most parameters converge to their given
limits. The hammer design with lowest SELη is shown in Figure 6. Here, the PSO moves to a long impact
weight with low radius at the bottom but increasing radius at the top (indicated by the parameters hW , rW , andαW ) with a pronounced curvature at the bottom (indicated by rC and RW ). The pronounced curvature and thelow radius at the bottom of the impact weight cause a low stiffness that increases due to the positive value ofthe angle αW towards the top. The angle αW converges here to the allowed maximum in case of the maximum
value for hW and the minimum value for rW . The radius RW , however, does not converge, eventually due tosmall to no influence on the SELη for, at least, the defined range in this case.
In contrast, the design parameters of the anvil move to a especially heavy anvil, as the parameters hA1 , hA2 ,and αW all move towards the maximum values. Especially the development of the parameter hA2 towards highpositive values is noteworthy, since negative values would have caused lower stiffness. The radius RA converges
to its minimum value, i.e. the curvature practically vanishes.
In summary, the presented optimization results in an impact weight with increasing stiffness from the bottom tothe top and a heavy anvil, while the introduced curvatures RW and RA appear to have zero or negative influenceon the objective value SELη . These results, however, should be viewed cautiously, as some limitations of thehammer design, i.e. maximum mass and maximum tension, have not been taken into account. Results are also
based on one optimization run with 15 particles and may therefore change with a different initial distributionof particles, i.e. hammer designs.

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1

190

0.8

180

0.6

10

hW [m]

efficiency

185
SELη [dB]

15

0.4

5

175

0.2

10

20

0

30

10

20

1

30

4

10

20

30

10

20

30

10

20

30

10

20

30

4
2
3

2

10

20

30

75

48

50

25

2

1

10

20

30
4

3

25
0
−25

rC [m]0
α A [◦ ]

−25
−50

−50
10

20

−82

30

10

20

30

200

RC [m]

RA [m]

40

2

1

200
RW [m]

α W [◦ ]

0

−2

1

−75

rW [m]

A2 [m]hA1 [m]

3

0

0

20
−200
10

20

30

optimization steps

−200
10

20

30

optimization steps

optimization steps

Figure 7. Development of the objective value SELη, the ram efficiency and the design parameters over the
optimization steps. The limits of the plots are the optimization constraints (see Table 2) as far as these areconstant, i.e. do not depend on other parameters.

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5

CONCLUSIONS

An approach to optimize the shape of an impact hammer for offshore pile driving regarding its acoustic properties has been presented. The characteristics of the hammer design with low SELη are a heavy anvil and an
impact weight with increasing stiffness from the bottom to the top. The SEL could be reduced by more than
6 dB while a high ram efficiency of 0.94 was maintaned. However, several constraints, e.g. regarding manufacturability were not taken into account. Future work will therefore include a more realistic parameter space.
Future work will be also directed towards a PSO using a more detailed parameterization that allows for different
shapes and therefore might uncover additional potential of the hammer shape to decrease sound pressure levels.

ACKNOWLEDGEMENTS
The presented research is part of the collaborative research project Investigation of primary measures for the reduction of underwater noise emission during offshore pile driving involving the companies Novicos GmbH as well
as MENCK GmbH and the Hamburg University of Technology. The authors gratefully acknowledge the projectfunding by the Federal Ministry for Economic Affairs and Energy due to an act of the German Parliament(Project No. 0324262).

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