A Methodology for Estimating the Position of the Engineering Bedrock for Offshore Wind Farm Seismic Demand in Taiwan

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Article A Methodology for Estimating the Position of the Engineering Bedrock for Offshore Wind Farm Seismic Demand in Taiwan

Yu-Shu Kuo 1,*, Tzu-Ling Weng 1, Hui-Ting Hsu 1, Hsing-Wei Chang 2, Yun-Chen Lin 1, Shang-Chun Chang 3, Ya-Jhu Chuang 1, Yu-Hsiu Tseng 4 and Yih-Ting Wong 1

1 Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Tainan 701, Taiwan; [email protected] (T.-L.W.); [email protected] (H.-T.H.); [email protected] (Y.-C.L.); [email protected] (Y.-J.C.); [email protected] (Y.-T.W.) 2 Taiwan Semiconductor Manufacturing Co., Ltd., Hsinchu 300, Taiwan; [email protected] 3 CECI Engineering Consultants, Inc., Taipei 114, Taiwan; [email protected] 4 Cheng Da Environment and Energy Ltd., Taipei 104, Taiwan; [email protected] * Correspondence: [email protected]; Tel.: +886-6-2757575 (ext. 63271)

Abstract: Taiwan lies in the circum-Pacific earthquake zone. The seabed soil of offshore wind farms in Taiwan is mainly composed of loose silty sand and soft, low-plasticity clay. The seismic demand for offshore wind turbines has been given by the local code. Ground-motion analysis is required to consider the site effects of the soil liquefaction potential evaluation and the foundation design of offshore wind turbines. However, the depth of the engineering bedrock for ground motion analysis Citation: Kuo, Y.-S.; Weng, T.-L.; is not presented in the local code. In this study, we develop a three-dimensional ground model Hsu, H.-T.; Chang, H.-W.; Lin, Y.-C.; of an offshore wind farm in the Changhua area, through use of collected in situ borehole and PS Chang, S.-C.; Chuang, Y.-J.; Tseng, (P wave (compression) and S (shear) wave velocities) logging test data. The engineering bedrock is Y.-H.; Wong, Y.-T. A Methodology for the sediment at the depth where the average shear wave velocity of soil within 30 m, Vsd30, is larger Estimating the Position of the than 360 m/s. In this ground model, the shear wave velocity of each type of soil is quantified using Engineering Bedrock for Offshore the seismic empirical formulation developed in this study. The results indicate that the engineering Wind Farm Seismic Demand in bedrock lies at least 49.5–83 m beneath the seabed at the Changhua offshore wind farm. Based on Taiwan. Energies 2021, 14, 2474. these findings, it is recommended that drilling more than 100 m below the seabed be done to obtain https://doi.org/10.3390/ en14092474 shear wave velocity data for a ground response analysis of the seismic force assessment of offshore wind farm foundation designs. Academic Editors: Jesús Manuel Riquelme-Santos and Keywords: ground model; offshore wind farm; seismic demand Adrian Ilinca

Received: 20 February 2021 Accepted: 20 April 2021 1. Introduction Published: 26 April 2021 Taiwan lies in the circum-Pacific earthquake zone. Offshore wind farms in the western sea area are affected by earthquakes and active faults. In order to ensure the stability of Publisher’s Note: MDPI stays neutral the offshore wind turbine foundations, site effects and soil liquefaction must be taken into with regard to jurisdictional claims in consideration in its design. published maps and institutional affil- The seismic demand for offshore wind turbines is given in the local code for offshore iations. wind farm seismic demand (CNS 15176–1) by the Bureau of Standards, Metrology, and Inspection in the Ministry of Economic Affairs [1]. AppendixA of CNS 15176–1 states that, when evaluating the offshore wind farm seismic force and the potential for soil liquefaction, a site-specific seismic hazard analysis is required. Copyright: © 2021 by the authors. The duration of the seismic acceleration applied to the offshore wind turbine foun- Licensee MDPI, Basel, Switzerland. dation can be determined by calculating the amplified response of the seismic wave This article is an open access article transmitted from the engineering bedrock to the seabed surface. AppendixA of CNS distributed under the terms and 15176–1 [1] suggests that the soil beneath the seabed can be treated as engineering bedrock conditions of the Creative Commons for ground response analysis when the shear wave velocity value (Vsd30) of the 30 m soil Attribution (CC BY) license (https:// profile reaches 360 m/s. However, the CNS standard does not present a recommended creativecommons.org/licenses/by/ 4.0/). depth of engineering bedrock for offshore wind farms in Taiwan.

Energies 2021, 14, 2474. https://doi.org/10.3390/en14092474 https://www.mdpi.com/journal/energies Energies 2021, 14, 2474 2 of 17

To perform a seismic force analysis for the offshore wind farm before a detailed foundation design is done, we need to determine the depth of the engineering bedrock, according to limited soil borehole data. In the early development stage of offshore wind farms in Taiwan, the standard penetration test (SPT test) is often used for site investigation. Ohta & Goto (1978) [2], Seed and Idriss (1981) [3], Lee (1992) [4], Dikmen (2009) [5], the Construction and Planning Agency (2011) [6], Silvia et al. (2015) [7], and others have provided recommendations for estimating the shear wave velocity of soil. Table1 indicates the recommended soil conditions proposed by various scholars for onshore soil data, which are not the same as the range of SPT-N values available for offshore constructions. To design onshore buildings, considering the soil characteristics of Taiwan, the Con- struction and Planning Agency (2011) [6] recommends calculating the shear wave velocity of soil using Equations (1) and (2): Cohesive soil: 0.36 120qu ; Ni < 2 Vsi = 1/3 , (1) 100Ni ; 2 ≤ Ni ≤ 25 Cohesionless soil: 1/3 Vsi = 80Ni ; 1 ≤ Ni ≤ 50, (2)

where Ni is the N-value of the ith soil layer obtained by the standard penetration test 2 (SPT) and qu is the unconﬁned compression strength (kg/cm ). The empirical formula of the Construction and Planning Agency (2011) [6] applies to the calculation of shear wave velocity for cohesionless soil with N-value less than 50 and for cohesive soil with N-value less than 25. According to the empirical formula in Table1, the shear wave velocity of offshore wind farm #29 in the Changhua area varies with depth, as shown in Figure1. A comparison is provided for the distribution trend of shear wave velocity with depth, calculated by the empirical formula with the experimental data of a resonant column test and the measured values of PS logging. At a depth of 5.5 m, the results obtained from the empirical formula of Dickmen (2009) [5] were close to that of the resonant column test. Meanwhile, at a depth of 9 m, the shear wave velocity calculated using the formulation suggested by Silvia et al. (2015) [7] was similar to that of the PS logging test results. At a depth of 18–40 m, the Construction and Planning Agency (2011) [6] and Lee (1992) [4] predicted the shear wave velocity as the measured values of PS logging. Seed and Idriss (1981) [3] and Dickenson (1994) [8] proposed empirical formulae speciﬁc to sand. While the range of the SPT-N value of Ohta and Goto (1978) [2] met the engineering requirements, their shear wave velocity estimation was more conservative.

Table 1. Empirical formulae for wave velocity and SPT-N values proposed in previous research [2–8].

Vs (m/s) Range of Area Researcher(s) Sand Clay Silt SPT-N Japan Ohta and Goto (1978) 85.35 N0.348 0 < N < 50 USA Seed and Idriss (1981) 61.4 N0.5 – – 0 < N < 50 Taiwan Lee (1990) 57 N0.49 114 N0.31 105.64 N0.32 0 < N < 50 USA Dickenson (1994) 88.4 (N + 1)0.3 – – 5 < N <90 Turkey Dikmen (2009) 73 N0.33 44 N0.48 60 N0.36 0 < N < 50 Construction Taiwan and Planning Agency 80 N1/3 100 N1/3 – 0 < N < 50 (2011) Italy Silvia et al. (2015) 149.3 N0.192 110.5 N0.252 – 0 < N < 60

Considering the difference between the application scope of the soil conditions and the analysis results proposed by various scholars to use the SPT-N value to estimate the shear wave velocity, this research compares the measured values of PS logging in an offshore wind farm in the Changhua area with the results of resonant column testing. A shear wave velocity prediction method for the soil of the offshore wind farm in Taiwan Energies 2021, 14, x FOR PEER REVIEW 3 of 19

Table 1. Empirical formulae for wave velocity and SPT-N values proposed in previous research. [2–8]

Vs (m/s) Range of Area Researcher(s) Sand Clay Silt SPT-N Japan Ohta and Goto (1978) 85.35 N0.348 0 < N < 50 USA Seed and Idriss (1981) 61.4 N0.5 – – 0 < N < 50 Energies 2021, 14, 2474 Taiwan Lee (1990) 57 N0.49 114 N0.31 105.64 N0.32 0 < N <3 50 of 17 USA Dickenson (1994) 88.4 (N + 1)0.3 – – 5 < N <90 Turkey Dikmen (2009) 73 N0.33 44 N0.48 60 N0.36 0 < N < 50 is proposed. TheConstruction depth of the engineering bedrock is determined using predicted shear waveTaiwan velocities. and Planning By collecting Agency the existing80 N borehole1/3 data100 N of1/3the offshore– Changhua0 < N < wind 50 farm, we established(2011) a three–dimensional ground model for the depth of the engineering bedrockItaly thatcan Silvia be et used al. (2015) to analyze ground 149.3 N0.192 motion 110.5 during N0.252 an earthquake.– 0 < N < 60

Figure 1. Shear wave velocity of borehole BH BH-3-3 at #29 offshore offshore wind wind farm farm ( (ee isis the the void void ratio ratio and and γm isγm the is the moist moist unit unit weight). weight).

2. Methodology for Estimating Engineering Bedrock of Offshore Wind Farm A ground model constructed from the data of seabed soil layers and geological structure can be applied to the basic conceptual design and detailed design of offshore wind turbine foundations. The seabed soil layering and geotechnical parameters in the ground model can be used for ground response analysis and soil liquefaction assessment. A procedure for estimating such a ground model is presented in this section. Figure2 shows the flowchart of the procedure, which includes four steps: In the first step, the soils of each borehole are classified by means of the Unified Soil Classification System (USCS). In the second step, the shear wave velocities of soils are estimated with the semi-empirical formulation developed based on PS logging. In the third step, the average shear wave velocities of soils within 30 m Vsd30 are calculated to determine the depth of the engineering bedrock. In the final step, the engineering bedrock is mapped to the three-dimensional Energies 2021, 14, x FOR PEER REVIEW 4 of 19

2. Methodology for Estimating Engineering Bedrock of Offshore Wind Farm. A ground model constructed from the data of seabed soil layers and geological structure can be applied to the basic conceptual design and detailed design of offshore wind turbine foundations. The seabed soil layering and geotechnical parameters in the ground model can be used for ground response analysis and soil liquefaction assessment. A procedure for estimating such a ground model is presented in this section. Figure 2 shows the flowchart of the procedure, which includes four steps: In the first step, the soils of each borehole are classified by means of the Unified Soil Classification System Energies 2021, 14, 2474 (USCS). In the second step, the shear wave velocities of soils are estimated4 ofwith 17 the semi- empirical formulation developed based on PS logging. In the third step, the average shear wave velocities of soils within 30 m Vsd30 are calculated to determine the depth of the engineering bedrock. In the final step, the engineering bedrock is mapped to the three- ground model ofdimensional the offshore ground wind model farm. of Descriptions the offshore ofwind each farm. step Descriptions are provided of each in the step are pro- following sections.vided in the following sections.

Figure 2. FlowchartFigure 2. Flowchart of estimating of estimating the engineering the engineering bedrock bedrock for an for offshore an offshore wind wind farm. farm. 2.1. Classification of the Soils of Boreholes 2.1. Classification of the Soils of Boreholes Due to the lack of CPT (cone penetration test) data in the early stage of offshore wind Due to the lackfarm ofdevelopment CPT (cone in penetration Taiwan, a three-dimensional test) data in the engineering early stage geological of offshore model was es- wind farm developmenttablished in by Taiwan, stratifying a three-dimensional the engineering soil engineering obtained from geological the SPT model(standard was penetration established by stratifyingtest) borehole the engineering data. The USCS soil obtainedhas classified from soils the SPTinto (standard15 groups, penetrationbased on particle size test) borehole data.distribution The USCS and has soil classified plasticity. soilsIn this into study, 15 groups,we classified based soils on into particle sandy size soil (SW, SP, distribution and soil plasticity. In this study, we classified soils into sandy soil (SW, SP, SM, SC), silty soil (ML, MH), and clayey soil (CL, CH), according to the USCS classification, and developed a semi-empirical formulation to estimate the shear wave velocity of the soil based on the SPT boreholes and PS logging. Soil profiles used for the establishment of the ground model mainly stratified the original borehole layers according to the soil classification for sand, silt, and clay. No organic soils were found in the offshore wind farm boreholes collected in this study. When carrying out stratification on cohesionless soils, the fine particle content should be considered for subsequent analysis and the application of soil liquefaction potential. When classifying soil as silty sand, it should be determined if it is classified as a sandy soil according to its liquid limit and plasticity index. If layers of other types are sandwiched between successive layers of the same type of soil, the layer of soil may be regarded as thin and can generally be incorporated into the adjacent main soil type. If the layers adjacent to two boreholes with the same elevation also contain the same type of soil as a thin interlayer, the above two principles need to be compared to confirm whether the thin interlayer is layered independently. Energies 2021, 14, 2474 5 of 17

2.2. Estimation of the Shear Wave Velocity of Soil Classes

The value of the moist unit weight γm, void ratio e, and the plastic index PI are decided from the borehole data, where the void ratio e for each depth is determined by laboratory tests. The coefﬁcient of earth pressure at rest, K0, of cohesionless soil refers to Jaky (1944) [9], while that of cohesive soil refers to Massarsch (1979) [10], as Equations (3) and (4), respectively: Cohesionless soil: 0 K0 = 1 − sinφ , (3) Cohesive soil: PI(%) K = 0.44 + 0.42 (4) 0 100 We developed a formulation to estimate the shear wave using the data of borehole BH–3 shown in Figure1. The average value of the moist unit weights γm of sand, clay, and silt were 19.49, 19.55, and 18.77 kN/m3, respectively, while the average values of the coefﬁcient of earth pressure at rest, K0, were 0.48, 0.5, and 0.48, respectively. With the shear wave velocity, soil density, and void ratio of each soil in Figure1, the shear wave velocity of soils could be calculated using Equation (5), which was derived from the maximum shear modulus, G0, in Equation (6) and the semi-empirical formulation for calculating the maximum shear wave velocity suggested by the DNV (2002) [11], where 3 0 2 ρ (kg/m ) is the density of soil (ρ = γm/g); σ0 (kN/m ) is the average effective stress at each depth, which can be calculated according to the thickness of the soil layer and the effective unit weight; e is the void ratio; OCR is the over-consolidated ratio; and A is an empirical parameter that varies with the particle size of soil and shape of the particles. The DNV (Det Norske Veritas) (2002) [11] suggested adopting the value of A as 3000 ± 1000. The parameter k is a function of the plastic index, PI, as shown in Figure3. The semi- empirical parameter (A) for each engineering soil can be obtained through Equation (5) by using the shear wave velocity obtained from the PS logging test (Figure1).

" 2 #0.5 A (3 − e) q 0 k VS = σ0(OCR) (5) Energies 2021, 14, x FOR PEER REVIEW ρ 1 + e 6 of 19

2 G0 = ρVs (6)

Figure 3. Relationship between the parameter k and plasticity index PI of the soil [Adapted from Figure 3. Relationship between the parameter k and plasticity index PI of the soil [Adapted from SeedSeed & & Idriss Idriss (1970) (1970) [12]]. [12]].

TheThe sediments sediments of of offshore offshore wind wind farms farms in the in the Changhua Changhua area area are fresh are fresh washout washout from from thethe Zhuoshui Zhuoshui River. River. Hence, Hence, the the over-consolidated over-consolidated ratio ratio (OCR (OCR),), was was set set as as 1.0 1.0 in in this this anal- analysis. ysis.Table Table2 shows 2 shows the parameterthe parameterA for A for each each soil soil type type found found in in borehole borehole BH-3. BH-3. A Atube tube with with material was adopted in the PS logging test for stabilization, and the shear velocity of the soil near the seabed surface was absent. The sampling rate of the shear wave velocity in the PS logging test was 1 sample per meter. As the shear wave velocity measured at different depths of various engineering soils was not the same, the semi-empirical parameter A value corresponding to each soil presented an interval distribution as shown in Table 2.

Table 2. The semi-empirical A value calculated using the shear wave velocity obtained from the PS logging test of BH3 borehole.

Engineering Soil Type Sample No. A (PS Logging) Standard Deviation Sand 9 3203 996.2 Silt 4 2773 1561.5 Clay 16 3813 221.2 The shear wave velocity of soil and the SPT-N obtained from borehole BH-3 are shown in Figure 1. The shear wave velocity of soils can be calculated with the power formulation in Figure 4—Equations (7)–(9)—using the SPT-N presented in Figure 1, where Vs,C is the shear wave velocity of clayey soil; Vs,S is the shear wave velocity of sandy soil; and Vs,M is the shear wave velocity of silty soil. . ,(/) = 139.67 (7)

. ,(/) = 61.25 (8)

. ,(/) = 241.24 (9)

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material was adopted in the PS logging test for stabilization, and the shear velocity of the soil near the seabed surface was absent. The sampling rate of the shear wave velocity in the PS logging test was 1 sample per meter. As the shear wave velocity measured at different depths of various engineering soils was not the same, the semi-empirical parameter A value corresponding to each soil presented an interval distribution as shown in Table2.

Table 2. The semi-empirical A value calculated using the shear wave velocity obtained from the PS logging test of BH3 borehole.

Engineering Soil Type Sample No. A (PS Logging) Standard Deviation Sand 9 3203 996.2 Silt 4 2773 1561.5 Clay 16 3813 221.2

The shear wave velocity of soil and the SPT-N obtained from borehole BH-3 are shown in Figure1. The shear wave velocity of soils can be calculated with the power formulation in Figure4—Equations (7)–(9)—using the SPT- N presented in Figure1, where Vs,C is the shear wave velocity of clayey soil; Vs,S is the shear wave velocity of sandy soil; and Vs,M is the shear wave velocity of silty soil.

0.23 Vs,C(m/s) = 139.67N (7)

0.43 Vs,S(m/s) = 61.25N (8) Energies 2021, 14, x FOR PEER REVIEW 7 of 19

0.02 Vs,M(m/s) = 241.24N (9)

Figure 4. Relationship 4. Relationship between the between shear wave the velocity shear and wave SPT-N velocity obtained in and the field SPT- testN ofobtained in the ﬁeld test of borehole BH-3 in #29 offshore wind farm (a) Clay, (b) sand, (c) silt. borehole BH-3 in #29 offshore wind farm (a) Clay, (b) sand, (c) silt. The profiles of shear wave velocity in borehole #29 BH-3, calculated using the semi- empiricalThe parameters proﬁles A of (from shear the wavePS logging velocity test; Table inborehole 2) are shown #29 in BH-3,Figure 5. calculated The using the semi- empiricalestimated results parameters of Equation (5A) showed(from good the agreement PS logging with test;the PS Tablelogging2 )test are results. shown in Figure5. The The soil shear wave velocities calculated using Equations (7)–(9) are shown as blue lines in Figure 6. The difference between the estimated value and the PS logging test results was found at a depth greater than 30 m. This difference may have come about because the SPT-N only roughly presented the effects of soil density and hardness.

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estimated results of Equation (5) showed good agreement with the PS logging test results. The soil shear wave velocities calculated using Equations (7)–(9) are shown as blue lines in Figure6. The difference between the estimated value and the PS logging test results Energies 2021, 14, x FOR PEER REVIEW 8 of 19 was found at a depth greater than 30 m. This difference may have come about because the SPT-N only roughly presented the effects of soil density and hardness.

Figure 5. TheThe shear shear wave wave velocities velocities estimate estimatedd using using Equations Equations (5), (5), (7)–(9). (7)–(9). 2.3. Estimation of Average Shear Wave Velocity 2.3. Estimation of Average Shear Wave Velocity In AppendixA of the Chinese Normal Standard (CNS) 15176-1 [ 1], the engineering In Appendix H of the Chinese Normal Standard (CNS) 15176-1 [1], the engineering bedrock is deﬁned as sediment at the depth where the average shear wave velocity of bedrock is defined as sediment at the depth where the average shear wave velocity of soil soil within 30 m Vsd30 is larger than 360 m/s. The Vsd30 can be calculated from the within 30 m Vsd30 is larger than 360 m/s. The Vsd30 can be calculated from the following following equation, equation, n ∑ d Vsd30 = i=1 i (10) ∑ n ∑i=1 di/Vsi 30 = (10) ∑ / where di is the thickness (m) of the ith soil layer and Vsi is the average shear wave velocity ofwhere the idthi is soil the layers.thickness The (m) summation of the ith soil of layer di from andi V=si1 is to then isaverage 30 m. shearVsd30 waverepresents velocity the movingof the ith average soil layers. shear The wave summation velocity ofof soildi from from i the= 1 seabed;to n is 30 for m. example, Vsd30 represents the shear the wave velocitymoving average of soil at shear depth wave 0 can velocity be calculated of soil fr usingom the Equation seabed; (10)for example, for a depth the from shear 0 wave to 30 m, whilevelocity the of shear soil at wave depth velocity 0 can be of calculated soil at a depth using ofEquation 1 m can (10) be calculatedfor a depth using from the0 to shear30 wavem, while velocity the shear of soil wave from velocity a depth of soil of 1at to a depth 30 m. of Figure 1 m can6 shows be calculated the shear using wave the velocity, shear Vswave, obtained velocity fromof soil the from PS a logging depth of test 1 to (gray 30 m. line) Figure and 6 theshows average the shear shear wave wave velocity, velocity, Vsd30Vs, obtained(black from line). the The PS linear logging regression test (gray of line)Vsd30 andis the presented average as shear the dottedwave velocity, black line. WeVsd30 determined (black line). the The engineering linear regression bedrock of Vsd30 for borehole is presented BH-3 as as the 63 dotted m beneath black the line. seabed, We determined the engineering bedrock for borehole BH-3 as 63 m beneath the seabed, following the criteria suggested by CNS 15176-1 [1], where the average shear wave velocity Vsd30 was stably larger than 360 m/s.

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Energies 2021, 14, x FOR PEER REVIEW 9 of 19 following the criteria suggested by CNS 15176-1 [1], where the average shear wave velocity Vsd30 was stably larger than 360 m/s.

FigureFigure 6. 6.Position Position ofof engineeringengineering bedrockbedrock at boreholeborehole BH-3 in #29 of offshorefshore wind wind farm. farm.

FigureFigure7 7shows shows the the average average shear shear wave wave velocityvelocity ((Vsd30)) calculated calculated using using the the shear shear wavewave velocity velocity obtained obtained from from the the semi- semi-empiricalempirical formulation; formulation; that that is, is, by by Equations Equations (5), (5), (7)–(9) (7)– . The(9). dottedThe dotted lines lines are the arelinear the linear regression regression curves curves of the of averagethe average shear shear wave wave velocities. velocities. The depthThe depth of engineering of engineering bedrock bedrock determined determined by the by linear the linear regression regression of Vsd30 of Vsd30obtained obtained from thefrom PS the logging PS logging test (dotted test (dotted black black line) wasline) 75 was m. 75 The m. depthThe depth of bedrock of bedrock estimated estimated with thewith linear the linear regression regression formulation formulation of Vsd30 of Vsd30using using the Vs thecalculated Vs calculated with with Equation Equation (5) and(5) parameterand parameterA in TableA in Table2 was 2 80 was m (dotted80 m (dotted red line). red Theline). depth The depth of bedrock of bedrock estimated estimated with thewith linear the linear regression regression formulation formulation of Vsd30 of Vsd30using theusingVs thecalculated Vs calculated with Equations with Equations (7)–(9) was(7)–(9) 74 mwas (dotted 74 m (dotted blue line). blue line). The difference between the engineering bedrock depth estimated by the semi-empirical formulation and the depth determined through the shear wave velocities obtained from the PS logging test may have come from the use of a discontinuous SPT-N sampling rate time per 1.5 m to determine the soil profile. In this study, the position of engineering bedrock for a large area is estimated and presented using a three-dimensional ground model. The estimated position of the engineering bedrock can be used for seismic demand feasibility studies in the early stage of offshore wind farm development.

Energies 2021, 14, 2474 9 of 17 Energies 2021, 14, x FOR PEER REVIEW 10 of 19

FigureFigure 7. 7.PositionPosition of engineering of engineering bedrock determ bedrockined determinedfrom the linear regression from the of linear Vsd30 calcu- regression of Vsd30 calculated lated using the results of the PS logging test, Equation (5), and Equations (7)–(9). using the results of the PS logging test, Equation (5), and Equations (7)–(9). .2.4. Development of Three-Dimensional Ground Model and Mapping of Engineering Bedrock. AThe three-dimensional difference between ground model the engineeringcan be used to present bedrock the depth depth of estimatedthe engineer- by the semi-empirical formulationing bedrock beneath and the the seabed. depth We determined constructed a throughground model the for shear an offshore wave wind velocities obtained from farm in the Changhua area following the method of Lemon & Jones (2003) [13] that con- thesisted PS of loggingseven steps: test (i) mayDefining have the comeboundary from of the the ground use ofmodel, a discontinuous (ii) preparing the SPT- N sampling rate timeengineering per 1.5soil mprofile to determineof each borehole the used soil in the proﬁle. ground Inmodel, this (iii) study, determining the position the of engineering bedrocknumber for for the interface a large between area is two estimated soil layers in and each presented borehole; (iv) usingestablishing a three-dimensional a ver- ground model.tical two-dimensional The estimated section position between boreholes, of the engineering (v) generating bedrockirregular triangular can be mesh used for seismic demand feasibility studies in the early stage of offshore wind farm development.

2.4. Development of Three-Dimensional Ground Model and Mapping of Engineering Bedrock A three-dimensional ground model can be used to present the depth of the engineering bedrock beneath the seabed. We constructed a ground model for an offshore wind farm in the Changhua area following the method of Lemon & Jones (2003) [13] that consisted of seven steps: (i) Deﬁning the boundary of the ground model, (ii) preparing the engineering soil proﬁle of each borehole used in the ground model, (iii) determining the number for the interface between two soil layers in each borehole; (iv) establishing a vertical two-dimensional section between boreholes, (v) generating irregular triangular mesh planes at various soil levels, (vi) generating the three-dimensional ground model, and (vii) determining the soil parameters. In this study, the three-dimensional ground model was Energies 2021, 14, 2474 10 of 17

constructed using the commercial geographic information system analysis software ArcGIS and GMS (Groundwater Modeling System). Soil layering based on borehole data does not include complete information about the deposition sequence of each layer. Therefore, before building a three-dimensional ground model, it was necessary to compare the sequence of the soil layer arrangement of the engineering soil for each borehole, which is completed in step (ii) to assign unified soil layer numbers (horizon IDs). We used the horizon method proposed by Lemon and Jones (2003) [13] to construct a three-dimensional ground model for the offshore wind farm. The layer number of each columnar soil layer was given in the order of soil layer types, in order to reflect the characteristics of the soil deposition order. Then, we established a two-dimensional vertical soil profile of each borehole, according to the soil layer number and soil type. Considering that the borehole samples obtained in this study were rare, the inverse distance weighting (IDW) method was used to generate irregular triangular grids at each level. Next, the commercial software GMS was used to generate a three-dimensional ground model of solid elements from the irregular triangular grid plane and the two-dimensional soil profile. The depth of shear wave velocity for each borehole was mapped onto the three-dimensional ground model. After the construction of the model was completed, a two-dimensional vertical section could be cut at any position to understand better the position of the engineering bedrock.

3. Case Study Application for Estimating the Engineering Bedrock of an Offshore Wind Farm in Changhua Area 3.1. Summary of SPT Test Results in Changhua Area We collected a total of 23 SPT borehole data sets published for the Changhua area, including 16 from the Taipower offshore wind farm (TPC), 3 from Fuhai offshore wind farm (Taiwan Generations Corp., TGC), and 4 from offshore wind farm #29. Among these, 5 sets of data from the Taipower offshore wind farm were removed in the subsequent shear wave velocity calculation due to a lack of relevant parameters. The distribution of boreholes is shown in Figure8. The depth of each borehole ranged from 0 to 120 m. According to the unified soil classification system (USCS), the soil in Changhua area is mainly composed of silty sand (SM), low-plasticity clay (CL), and low-plasticity silt (ML) with thin layers Energies 2021, 14, x FOR PEER REVIEW 12 of 19 of poorly graded sand with silt (SP–ML) and silty clay (CL–ML). The distribution of soil profile is shown in AppendixA, with SPT- N values to the left of each soil profile.

Figure 8. DistributionFigure 8. Distribution of boreholes of boreholes in SPT in test SPT of test offshore of offshore wind wind farm farm in in thethe Changhua area. area.

By reclassifying the unified soil classification profiles in Figure 9, according to the aforementioned method, it was possible to determine the shear wave velocity of each soil layer. The moist unit weight (γm) and void ratio (e), which were computed based on water content (w) and specific gravity (Gs) obtained from borehole data, are listed next to each soil profile.

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By reclassifying the unified soil classification profiles in Figure9, according to the aforementioned method, it was possible to determine the shear wave velocity of each soil layer. The moist unit weight (γm) and void ratio (e), which were computed based on water Energies 2021, 14, x FOR PEER REVIEW 13 of 19 content (w) and specific gravity (Gs) obtained from borehole data, are listed next to each soil profile.

FigureFigure 9. Soil 9. Soil profile profile for for each each borehole. borehole. TGC, TGC, Fuhai Fuhai offshore offshore wind wind farm farm (Taiwan (Taiwan Generations Generations Corp.); Corp.); TPC, TPC, Taipower Taipower offshore offshore wind farm. wind farm. 3.2. Depth of Engineering Bedrock of each SPT borehole in Changhua Area 3.2. Depth of Engineering Bedrock of Each SPT Borehole in Changhua Area We collected SPT test data from 18 boreholes from offshore wind farms in the Chang- huaWe area collected and converted SPT test the data data from to 18the boreholes soil stratifications from offshore in Figure wind 9 farms. By giving in the the Changhua void area and converted the data to the soil stratifications in Figure9 . By giving the void ratio ratio (e) and moist unit weight (γm) obtained from in situ testing, the shear wave velocity (e)profile and moist was calculated unit weight using (γm )the obtained A parameters from in given situ testing, in Table the 2. shear Then, wave we calculated velocity profile the wasaverage calculated shear usingwave thevelocity,A parameters Vsd30, ofgiven each inborehole Table2 .in Then, Appendix we calculated A. To estimate the average the sheardepth wave of the velocity, engineeringVsd30 bedrock,, of each we borehole used li innear Appendix regressionA. Toanalysis estimate to find the depththe corre- of the engineeringsponding depth bedrock, where we the used Vsd30 linear stability regression was greater analysis than to 360 find m/s. the The corresponding estimated depth depth whereof the the engineeringVsd30 stability bedrock was for greater each thanborehole 360 m/s.is presented The estimated in Figure depth 10. When of the the engineering calcu- bedrocklated average for each shear borehole wave velocity is presented Vsd30 indid Figure not reach 10. Whenthe required the calculated wave velocity average thresh- shear waveold of velocity the engineeringVsd30 did bedrock, not reach the the depth required of the wave engineering velocity bedrock threshold obtained of the engineeringby linear bedrock,regression the exceeded depth of the the borehole engineering depth, bedrock as shown obtained in Table by 3. linear regression exceeded the borehole depth, as shown in Table3.

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FigureFigure 10. 10.Engineering Engineering bedrock bedrock distribution distribution calculation calculation for four for boreholes four boreholes (TPC). (TPC).

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Table 3. Distribution of engineering bedrock depths calculated by two methods.

Vsd30 Calculated with Vs in Vsd30 Calculated with Vs in Borehole Equation (5) Equations (7)–(9) TPC BH-1 49.5 111 TPC BH-2 55.65 107 TPC BH-3 67.5 89 TPC BH-4 64.5 117 TPC BH-5 57 130 TPC BH-6 69 108 TPC BH-7 69 130 TPC BH-8 66 100 TPC BH-9 51.25 125 TORI BH-1 58.5 67.5 TORI BH-2 55.5 69 TGC OWT-1 64.5 126 TGC OWT-2 83 140 TGC met mast 60 150 #29 BH-1 50 89 #29 BH-2 59 68 #29 BH-3 80 74 #29 BH-5 62 44

3.3. Engineering Bedrock Distribution in Changhua Area We developed a ground model using the 18 boreholes in the offshore area of Changhua (given in AppendixA). In Figure 11, we present the boreholes TPC BH-1, TPC BH-2, TPC BH-3, TPC BH-4, TPC BH-5, TGC tower, TGC OWT-1, and TGC OWT-2, from north to south (dotted yellow line) and the two-dimensional soil proﬁles of the offshore wind farms. The area of the ground model is given in Figure8, the length of which was 41 km in the north–south direction, while that in the east–west direction was 13 km. Figure 11 shows the depth of the engineering bedrock in the Changhua area, as estimated by Equation (5) using the parameter A in Table2 (black line), which varied from 49.5 to 83 m. The depth of the engineering bedrock estimated by using the average shear wave velocities calculated by Equations (7)–(9) is presented as a red line in Figure 11 and varied from 44 to 150 m. The estimated depth of the engineering bedrock mainly depended on the accuracy of the estimated soil shear wave velocity. The depth of engineering bedrock obtained by the linear regression (red line) may exceed the borehole depth, as shown in Figure 11, for which no soil information can be provided. Energies 2021, 14, 2474 14 of 17 Energies 2021, 14, x FOR PEER REVIEW 16 of 19

Figure 11. PositionFigure of the 11. engineering Position of the bedrock engineering in the developed bedrock in three-dimensional the developed three-dimensional ground model. ground model.

4. Conclusions Conclusions In this study, wewe presentedpresented aa procedureprocedure toto estimateestimate thethe positionposition ofof thethe engineeringengineering bedrock for use in seismic demand feasibility studies at the early stage of offshore wind farm development. development. This This procedure procedure included included four four steps: steps: classifying classifying the soils the soilsof each of bore- each hole,borehole, estimating estimating the shear the shear wave wave velocities velocities of soils of soils using using a semi-empirical a semi-empirical formulation, formulation, de- terminingdetermining the the depth depth of ofthe the engineering engineering bedrock bedrock using using the the average average shear shear wave wave velocities of soils, and mapping the position of the engineeringengineering bedrock on aa three-dimensionalthree-dimensional ground model of the offshore wind farm.

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A three-dimensional ground model of an offshore wind farm in the Changhua Area was developed. The depth of the engineering bedrock for this offshore wind farm was greater than 45 m. The estimated depth of the engineering bedrock mainly depended on the accuracy of the estimated soil shear wave velocity. It was found that the position of the engineering bedrock may be as deep as 150 m beneath the seabed. Therefore, in future geological surveys of offshore seabed soil in the Changhua area, drilling deeper than 100 m below the seabed should be considered to obtain sufﬁcient soil shear wave velocity data to provide a valid application of ground-response analyses during seismic force assessment in offshore wind farm design. In this study, we used very limited in situ test results to formulate the relationship between soil shear wave velocity and SPT-N. A more reliable formulation may be derived when more test data are available. The reader should keep in mind that this study provided a methodology to determine the location of the engineering bedrock; however, the formulations for estimating the shear wave velocity need to be upgraded for the optimal seismic design of offshore wind turbine foundations.

Author Contributions: Conceptualization, Y.-S.K.; Data curation, H.-T.H. and Y.-C.L.; Formal analysis, T.-L.W.; Funding acquisition, Y.-S.K.; Investigation, S.-C.C.; Methodology, Y.-S.K. and T.-L.W.; Project administration, Y.-S.K.; Resources, Y.-S.K.; Software, T.-L.W., Y.-H.T. and Y.-T.W.; Supervision, Y.-S.K.; Validation, H.-W.C. and Y.-J.C.; Visualization, Y.-S.K. and T.-L.W.; Writing—original draft, Y.-S.K. and T.-L.W.; Writing—review & editing, Y.-S.K. and Y.-H.T. All authors have read and agreed to the published version of the manuscript. Funding: The research was supported by the grants “Infrastructure Program of Offshore Wind Farm Zonal Development (PG10602-0177 and PG10702-0220)”, Bureau of Energy and “Evaluation of geotechnical and geo-environmental site investigations for offshore windfarms (MOST105-ET-E006- 002-ET)”, the Ministry of Science and Technology of Taiwan, and Taiwan power company. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conﬂicts of Interest: The authors declare no conﬂict of interest. Energies 2021, 14, 2474 16 of 17

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Appendix A

FigureFigure A1. SPT A1. boreholes SPT boreholes used in used this in study. this study.

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