4.1. Bed Shear Stress Analysis
The shear stress over an undisturbed seabed is composed by the shear stress caused by the steady current (
) and the oscillating wave orbital velocity near the seabed (
) as defined in Equations (10) and (11),
where
and
are the dimensionless friction coefficients of the bed due to currents and waves, separately. For the steady flow condition and assuming a logarithm velocity profile above the seabed as shown in Equation (12), the depth averaged current velocity
can be derived by Equation (13). The flow shear velocity
is equal to
. Combined with Equation (10),
is obtained via Equation (14).
where
is the Von Karman constant,
= 0.4,
= 2.718, and
is the roughness length. For a hydraulically rough flow when
,
,
is the Nikuradse roughness [
40].
, as suggested in [
38].
For the wave shear stress of hydraulically rough conditions, several models are available [
38,
41,
42,
43]. De Vos et al. (2011) [
18] compares the differences between these models and uses the model of Dixen et al. (2008) [
43] in the static design approach, see Equation (15).
To comply with a consistency of using the Soulsby’s curve for the threshold of the motion (
Figure 1), the bed shear stress is also analyzed via Equation (16),
where
is the amplitude of the wave orbital motion at the bed. For regular waves,
,
is the wave number. For irregular waves,
and
[
38].
Regarding the bed shear stress for a combined waves and currents conditions, [
44] proposes a simple and explicit formula by using a direct fit of laboratory and field measurements in order to compute the maximum shear stress
, which is known as the DATA2 method, as shown in Equations (17) and (18).
The corresponding shear velocities are then defined with Equations (19)–(21).
The result of the bed shear stress analysis is shown in
Table 3. It can be seen that the bed shear stress due to waves gives the main contribution to the maximum bed shear stress in the regular wave cases. For the irregular wave cases, the bed shear stress due to the steady flow also plays an important role.
4.2. Static Stability Analysis
During the experiments, the threshold of motion is detected by visual observation via the underwater camera. This visual observation method has been used in both [
18,
25], where the reliability is discussed in detail by the latter reference. However, for the visual assessment of the present experiments, the visibility is affected by the sand suspension, therefore only very clear rock movement is observed.
The static stability analysis approach is thoroughly explained in [
18] while the regression formula for a pile model of
= 0.1 m is given in Equation (7). For the tests using a
m model, the predicted critical bed shear stress
can be calculated via Equation (22). Further, for tests using a
= 0.6 m model,
is calculated by Equation (23).
The regression in [
18] applied the critical bed shear stress using a stone size of
and a critical Shields parameter of
= 0.035, which leads
as expressed in Equation (24).
A comparison between Equations (24) and (3) is introduced by [
45]. The experimental results and predicted shear stresses are presented in
Table 4.
Figure 7a shows the difference between the critical bed shear stress and the predicted bed shear stress using the method of De Vos et al. (2011) [
18] (Equations (22)–(24)). From the perspective of onset of motion,
Figure 7a shows that the predicted critical bed shear stress for the small scale model introduced in [
18] results in a conservative approach. For the cases with
= 0.3 m and
= 6.75 mm, the clear stone movement happens when
. For the cases with
= 0.6 m and
= 13.5 mm, the clear stone movement happens when
. It can be seen that the predicted critical bed shear stress will lead to a conservative value for the large scale ratio.
Figure 7b shows the relationship between the local bed shear stress around the pile and the critical bed shear stress via the models of reference [
37]. The local bed shear stress is calculated by Equation (3) and determined by assuming a uniform amplification factor
= 2. It is seen that using
= 2 results in a more scattered distribution of the local bed shear stress and a conservative estimation of the threshold of motion.
It should be noted that during the present large-scale tests, a live-bed situation was measured and the sediment suspension made the recorded image blurry after 2–3 waves, which clearly affects the recording quality and the possibility to see initiation of motion. Meanwhile, due to the great distance between the pile and the underwater camera, the motions of very small stones are not able to be captured. It is therefore possible that stone entrainment occurred before it was visually acknowledged, and it is not possible to develop a new formula based on these data. However, it can be noted that the predicted critical shear stress by [
18] tends to be on the safe side.
Figure 8 shows the relationship between the Stab parameter (Opti-Pile) and the observed onset of motion based on the camera results. Most of the calculated Stab parameters are in the range of 0.4–0.8. These values, according to reference [
17], have exceeded the criteria of a static design, which should trigger the incipient of motion. However, the experimental results show that this judgement could also be conservative and safe, and no clear relationship between the Stab parameter and the threshold of motion was identified for this dataset. Stab parameters of 0.6–0.8 may give a result of either observed stone motion or no motion.
The deviations between the present results of the large scale tests and the existing static design method can be attributed to several reasons. Firstly, the Soulsby’s curve (
Figure 1) has a wide dispersion for waves combined with current conditions in the range of
> 100. This makes it difficult to obtain an accurate analysis for the static analysis. Secondly, scale effects exist as the viscous forces cannot be scaled correctly, and the local amplification factor might be smaller as the model scale increases. Scale effects can also be seen from the Soulsby’s curve. As can be seen in
Figure 9, the
range for various experiments has been plotted. The critical bed shear stress for the present large scale tests are clearly larger than in the previous studies using small scale models, such as [
18,
22], which means the small scale experiments are more conservative with regard to the incipient of stone motion.
4.3. Dynamic Stability Analysis
Beside the study of the onset of motion, the dynamic stability of the scour protection layer was investigated. A dynamically stable scour protection will result in a much smaller stone size of the protection layer and significantly reduce the cost of the installation, depending on the volume of rock material for a proper thickness of the armor layer.
The large scale tests hereby have cover a wide range of environmental conditions, including different water depths, pile diameters and stone sizes. In order to have a clear insight, dimensionless expressions are necessary to depict the relationship among the combined conditions. The key dimensionless parameters in this situation include the Reynolds numbers for the pile (Equation (25)) and the stones (Equation (26)), the Froude number for the stones (Equation (27)), the Keulegen–Carpenter number (Equation (28)), the ratio between wave and current velocities (Equation (29)), the ratio between water depth and pile diameter (
) and the ratio between stone size and pile diameter (
).
An overview of the values of these dimensionless parameters for the irregular wave tests are listed in
Table 5. The dimensionless parameters can indicate the flow properties in the experiments which can determine the formation of flow separation, lee-wake vortexes and horseshoe vortexes. As seen from
Table 5, the Reynolds numbers of the pile,
, are in the magnitude of O(10
5), indicating the flow around the pile has a fully turbulent wake [
46]. The KC number reflects the effects of the oscillatory flows. In the present experiment, the range of KC number is 0.693 < KC < 1.448, which means the oscillatory flow due to the waves will not lead to severe vortex shedding nor to the development of a horseshoe vortex, but might only introduce a pair of vortices at the wake side of the wave-induced flow, according to [
9,
46]. The ratio between current and waves,
, reflects the velocity components of the flow and the wave or current dominated regime, where
= 1 gives a current only condition and
= 0 is a wave only condition. For all cases shown in
Table 5,
> 0.689. This means the flow is dominated by the steady current.
The damage patterns after 3000 waves from the overhead cameras and the corresponding scanned bed surface elevations are displayed in
Figure 10 and
Figure 11. The red colored stones in the inner ring can clearly show how they are transported by the flow around the pile due to the waves and the current. In most of the cases, significant horseshoe vortices and lee-wake vortices due to the current can be noticed as the inner ring stones are moved by the hydrodynamic loads and form a wake shape in the downstream of the pile. The removal of the inner ring stones leads to an erosion pattern nearby the pile at a ±45° position towards the incoming current, for example, in Test 04B, 08B, 12B, and 13B. The observed phenomena are in accordance with [
47], where the maximum amplification factor also occurs at ±45° position towards to the incoming flow. For Test 08B, the protection fails as many inner ring rocks are removed and the geotextile is exposed. For Test 02B, the removal of inner ring rocks is not obvious as the hydrodynamic load is relatively week.
The Stab parameter (Equation (5)) and the measured and predicted
(Equations (8) and (9)) values are also given in
Table 5. For the present cases, the Stab parameter is always less than 0.4. The protection layer is assumed to be statically stable [
17]. However, it can be seen that most of the presented results are clearly not statically stable but dynamically stable. This shows the design limitation of using the predicted Stab parameter as an underestimation of the damage level.
A comparison is made between predicted and measured
values after 3000 waves as shown in
Figure 12. It can be noted that the predicted damage numbers are almost larger than the measured damage numbers, regardless of whether waves are following or opposing current. It is defined by De Vos et al. (2012) [
19] that failure occurs when the estimated damage number is larger than 1. However, despite Test 08B, no clear failure is seen in Test 02B, 04B, 06B, 10B, 12B, and 13B, despite the predicted damage numbers
being larger than 2. For Test 08B, the damage pattern shows a clear horseshoe vortex induced by the current, causing a large exposure area of the geotextile. The high damage number is mainly due to the high current condition, the small stone material, and a lower protection layer thickness.
The results show that Equation (9) will give a conservative prediction of the dynamic stability of the scour protection layer. Several reasons may lead to the deviations between the predicted values and the measured values. One key reason might be that the large scale experimental conditions are out of range for the input parameters in the regression formula (Equation (9)), especially the stone size (
and the ratio between velocities (
).
Table 6 shows the difference between the parameters in the present experiments and the experiments of [
19]. The applied stone sizes in the present experiments are smaller than in the study of [
19] and the experiments presented in this paper focuses on the current dominated flow,
> 0.69, which is larger than in most of the test cases in the experiments of [
19]. Another reason might be that the layer thicknesses exceeds the ones which were tested in [
19]. Other possible reasons can be the scale effects, model effects and experimental uncertainties.
Nielsen and Petersen (2019) [
25] proposed a new estimation approach by considering the relationship between the maximum bed shear stress
, the damage number
and the relative velocity
. The research suggests two estimated limits for low damage and failure, as the solid lines shown in
Figure 13.
is calculated using
in
Figure 13a and using
(significant value) in
Figure 13b. To obtain these values, the small-scale experimental data of De Vos et al. (2012) [
19] are analyzed for the estimated limits with
< 0.7. As a complement to the dataset, the large scale experimental data with 0.69 <
< 0.75 presented in this paper are added to the figure. Although some differences exist when using different wave orbital velocities to calculate
, the limit lines of
for high
conditions do not drop dramatically after
> 0.5 as given by [
25], but stay stable even when
> 0.7. This shows that the large scale scour protection can endure a relatively higher bed load than expected. As there is a lack of data regarding how small scale tests behave in very high
conditions, it is not easy to draw a fair conclusion regarding the scale effects, and therefore more investigations are expected in a future study to overcome this lack of knowledge.
4.4. Erosion Depth of Scour Protection Layer
The erosion depth is an important parameter to depict the damage of the scour protection. De Schoesitter et al. (2014) [
21] discussed that using more layers of smaller size stones will reduce the rate of failure of a scour protection. The failure is defined as the exposure of filter with an area of
. This is equivalent to an area of four adjacent stones removed in the bottom of the armor layer. However, this definition is quite sensitive to the randomness of the observation, since the area of exposure is usually rather small compared to the whole area of protection. To the safe side of this definition, it can be understood as the moment when the maximum depth of damage exceeds the thickness of the protection layer. This approach varies from De Vos et al. (2012) [
19], as it focuses on erosion depth instead of erosion volume and because the protection layer thickness used in the present large scale test (up to 9
) is much larger than
. Therefore, an investigation of the maximum damage depth of the protection layer can give interesting results.
The principles of the erosion of a scour protection layer under waves and currents is very similar to the scour itself. The discussion of scour depth around a monopile can be found in literature, where the most widely used formula is given in [
48] as below (Equations (30)–(32)),
where
and
where
is the scour depth in steady current alone condition, the mean value for live-bed conditions is
= 1.3 and the standard deviation is 0.7. For low KC numbers, Rudolph and Bos (2006) [
49] proposed a modified scour depth prediction equation in the current combined wave conditions, which is fitted using a series of experimental data within the range of 1 < KC < 10, as shown in Equations (33)–(36).
Qi and Gao (2014) [
50] carried out experiments with
and they found that the dimensionless scour depth is smaller, but still significant when
. As the rock material is often quite large when compared to the fine sediments, the undisturbed bed shear stress must be smaller than the critical bed shear stress (
), which is considered to be a clear water condition. The clear water condition scour depth under steady current was analyzed by Raudkivi and Ettema (1983) [
51]. However, for the damage depth of scour protection layer, there remains a scarcity of experimental data under low KC number, wave-plus-current, and clear water conditions.
With regards to the maximum damage depth of this scour protection layer,
, the definition is similar to that in scour problem. This depth is defined as the maximum eroded height of the scanned profile before and after actions of current and 3000 waves, as shown in
Figure 14. In order to ascertain a better insight into the relationship between the maximum damage depth of the scour protection layer around a monopile and the hydrodynamic load due to combined waves and currents conditions, an analysis is carried out based on the large-scale experimental data. The results are shown in
Table 7.
The effect of the ratio between maximum shear velocity and critical shear velocity,
and the Reynolds number of stone size,
, are plotted in
Figure 15 and
Figure 16, respectively. As a complement of the data and a comparison between small scale and large scale results, the re-analyzed scanning data from De Vos (2008) [
52] is also added to the figures. It is clearly seen that the dimensionless maximum damage depth
increases as
increases, for both present result and [
52]. The maximum depth to pile ratio,
, is mostly bounded between an upper limit and a lower limit with a range of 0.11, approximately. Using Equations (5) and (21), it can be derived that
. This shows that Stab parameter can reflect the main physics, but is too rough when predicting the damage of the scour protection.
From another perspective, as shown in
Figure 16 it is seen that the damage depth increases with the stone Reynolds numbers,
(
, based on the relationship between
and
). This is easy to explain as a larger bed shear stress or shear velocity will physically introduce a larger amount of rock material removal. For the present large scale tests,
,
increases slowly as
increases, while for the small scale tests,
,
increases sharply as
slightly increases. This corresponds to reference [
36] which stated that for
> 400, the critical bed shear stress is approaching a constant value and is much larger than when
< 200. Moreover, this may also be attributed to the horseshoe vortex behaviors in different scales. As in low Re number but turbulent flow condition, the turbulent boundary layer thickness to pile size (
) is usually larger, which can cause a larger relative separation distance of the horseshoe vortex [
9]. As the flow details are not captured in these experiments, more discussions related to the microscopic interactions between flow and rock material shall be addressed in the future. Nevertheless, the scale effects due to the pile Reynolds number (
) are clearly reflected. One exception is Test 08B which shows a significant failure. As listed in
Table 5, the stone Froude number for Test 08B is
= 2.103 and
= 0.778. These values are much larger than the values of the other test cases and could be the reason for the large deviation of
in
Figure 16.
In comparison with the existing models which predict the scour depth in sand under low KC number, the dimensionless damage depth versus
is plotted in
Figure 17. The regression lines from [
48,
49,
50] are plotted as well for reference. The experimental data from the present large scale tests and De Vos (2008) [
52] are categorized by different KC number ranges. All of these data points are within the range of KC < 3.5. It can be seen from the figure that the measured
are mostly smaller than the predictions. When
< 0.4, several data points can be well fitted to the three regression models, but when
> 0.4, most of the data points are not able to be fitted ideally, especially for the conditions when KC < 1.5. There are several reasons which could explain the discrepancies between the present experimental data and the existing prediction models. In the first place, the existing formulas are mostly valid for live-bed conditions. It is not clear yet whether the prediction methods are also valid for the scour protection materials in clear water conditions. However, according to the study of [
51] on the current-only scour depth in clear water conditions, the scour depth in clear water conditions is less than that in live-bed conditions. This conclusion could be reasonably expanded to the combined waves and current conditions. Secondly, the sediments used in [
48,
49,
50] are fine or coarse sands with small diameters, which results in a different scaling factor for sediment,
. This is different from the present study where the armor stones are scaled geometrically,
[
39]. Therefore, the existing theories are prone to give a higher damage depth. Thirdly, it was discussed in [
20] that the damage of the scour protection may still develop after 3000 waves, which indicates that the equilibrium damage depth might not have been reached. However, this effect is considered to be minor as the damage depth is almost ten times smaller than the predicted value. In addition,
Figure 17 shows that, for a scour protection,
does not necessarily increase or decrease with
or KC number.