Water wave theories and Wave loads

Stochastic Analysis of Offshore Steel Structures - An analytical Appraisal. Springer. 2013. Halil Karadeniz, Vedat Togan

Chapter3 Water wave theories and Wave loads

Introduction

海洋是人类已使用的地球重要部分,他们占了大约70%地球,含有丰富的成分和未开发的能源。大洋用于运输、粮食资源、军事用途等。
很多注意力都集中在发现上海底碳氢化合物的开采和利用[3]可再生能源[4]。海洋环境非常复杂和混乱,有时会很平静,主要是受到大气现象的干扰,偶尔在构造区域被地球地震运动激发而导致在生活和经济方面的灾难后果[1]。海洋表面的扰动是不规则的水波,主要由风产生。风产生风暴、地震、月球和月球的引力等来源孙,物理海浪可分为以下几种类型:源力、波形运动、水深、波长、波高度和周期等。月亮和太阳的引力吸引力产生海浪。==风从最小到最大的顺序是毛细管波或波纹、超重力波、重力波和次重力波。==风暴、滑坡、地震和爆炸可能会产生海啸,它是比风力产生的更长波和周期,以及更大的灾难性波浪。除了这些波浪,有时在海域还会发生很大的波浪。这些被称为怪波(freak waves)[5]。尽管其原因尚不清楚,已知的物理机制暗示了对怪异的波浪现象可能是波浪-电流相互作用、几何和衍射聚焦,由于色散和调制不稳定性引起的聚焦,碰撞和大气作用[5]。

海洋中最常见的波浪环境是由于风在不同阶段产生波浪毛细管、海浪和涌浪。风产生的波的大小取决于风速、持续时间和获取时间(风在吹过的水面长度比上水深)。在完全平静的海面上,风几乎没有抓地力,因此在水表面上掠过,水移动产生涡流和小波纹形成毛细波。由于这些涟漪,风更好地抓住了水面,它变得更粗糙。逐渐地,它发展出短波的不规则波传播在不同的方向。这种波浪状况称为海浪,它取决于风的持续时间和获取时间,海浪发展成一个完全发达的海面,达到最大大小,速度和超出抓取时间的周期,即风将最大的能量传递给了海浪,此时大海浪已经完全发展。

当海浪移出风力输入能量区域时,称为作为浪涌。它停止增长并获得通常的能量总大小以及光滑圆润的外形。由于它失去了能量输入,因此在传播过程中,波开始衰减。海浪的表面起伏不规则,可以由许多振幅不同周期、长度和方向的规则谐波组成,它们总共构成一个随机的表面高程。这些波形的条件定义了随机海浪谱[6,7],分析方法本质上是用来定量的。海浪也可以根据相对水深d/L分为深水波、浅水波和非常浅水波,其中d是静止水深,L是波长[8]。从理论上讲,规则波可以是由满足在水面和海底多个边界条件的波动方程确定。根据简化边界条件的程序,水波理论分为两种,线性和非线性(有限振幅),请参阅[8-21]。由于海浪是随机的,因此随机描述实际上是在实践中使用的[6,7],它构成了基本海洋结构随机分析的输入[22,23]。除其他外波浪是最重要的现象,对海洋中的海上结构施加载荷必须将结构设计为可以长期承受的随机力。由于海浪在海底结构上产生主要的动态载荷短期和长期都会造成疲劳损伤,在本章中,将介绍水波及其随机表示。然后,进行波浪载荷的随机分析计算程序基于波荷载公式的水-结构相互作用,着重强调附加质量和流体动力阻尼。

Introduction to Wave Theories

Water surface waves are obtained from inviscid, incompressible and irrotational flow under certain boundary conditions by using the principles of hydrodynamics [24]. To obtain wave equations the continuity of water is used. The continuity in fluid dynamics states that the fluid mass is conserved, i.e., in a steady state process, the rates of mass entering and leaving a system are equal which leads to the continuity equation [10], in general,
∂ρ∂t+∇⋅(ρV)=0\frac{\partial\rho}{\partial t}+\nabla\cdot (\rho V) =0∂t∂ρ​+∇⋅(ρV)=0
where ρ\rhoρ is the mass density and VVV is the velocity vector of the water, ∇\nabla∇ is the divergence operator defined as
∇=∂∂xi+∂∂yj+∂∂zk\nabla=\frac{\partial}{\partial x}i+\frac{\partial}{\partial y}j+\frac{\partial}{\partial z}k∇=∂x∂​i+∂y∂​j+∂z∂​k

In addition to the translational motion, one other important definition in fluid motion is the rotation of fluid particles. The rotation vector is defined as
Ω=12∇⊗V\Omega=\frac{1}{2}\nabla \otimes VΩ=21​∇⊗V
where ⊗\otimes⊗ denotes a vector product. The components in xxx, yyy, and zzz directions are
Ωx=12(∂w∂y−∂v∂z)\Omega_x=\frac{1}{2}\left(\frac{\partial w}{\partial y}- \frac{\partial v}{\partial z}\right)Ωx​=21​(∂y∂w​−∂z∂v​)
Ωy=12(∂u∂z−∂w∂x)\Omega_y=\frac{1}{2}\left(\frac{\partial u}{\partial z}- \frac{\partial w}{\partial x}\right)Ωy​=21​(∂z∂u​−∂x∂w​)
Ωz=12(∂v∂x−∂u∂y)\Omega_z=\frac{1}{2}\left(\frac{\partial v}{\partial x}- \frac{\partial u}{\partial y}\right)Ωz​=21​(∂x∂v​−∂y∂u​)

The irrotationality of the flow states that the rotation components are all zero, i.e., Ωx=0\Omega_x=0Ωx​=0, Ωy=0\Omega_y=0Ωy​=0 and Ωz=0\Omega_z=0Ωz​=0, and the flow undergoes only the translational motion. The continuity and irrotationality conditions of the flow, given by Eqs. (3.1c) and (3.2b), are the basic equations of water waves that satisfy a number of boundary conditions at the bottom and on the free surface of the sea:

  • At the bottom, the velocity components normal to the bottom surface will be zero and, for a body in the wave, the normal velocity of the water is equal to the normal velocity of the body. If the body is fixed, then the normal water velocity will be zero [14]. These are stated as, if the z axis is in vertical direction,

  • For inviscid and irrotational unsteady flows, the Bernoulli equation can be obtained from the spatial integration of the Navier–Stokes equation [10] as written in vector notations by

Symbol Designation
SWL Still water level
η\etaη Free surface elevation
HHH Wave height
LLL wavelength
η^\hat \etaη^​ Wave amplitude
ddd Water depth
CCC Wave celerity
CgC_gCg​ Wave group velocity
uuu, www Water particle velocities in horizontal and vertical directions
TTT Wave period
$x $ Wave frequency (rad/s)
mmm Wave number
α\alphaα Wave steepness

Stokes Wave Theory

Other Wave Theory

As presented in Sect. 3.2.1 the Stokes wave theories are most suitable for deep and intermediate water depth. Even higher order terms in the Stokes theory for steeper waves produce unrealistic results. For shallower water, a finite-amplitude wave theory is required. Cnoidal wave theory [9, 36–38] and, in very shallow water, solitary wave theory [9, 39, 40], are the analytical wave theories most commonly used for shallow water. Solutions in the cnoidal wave theory are obtained in terms of elliptical integrals of the first kind. The solitary wave theory is a special case of the cnoidal wave theory at one limit, and at the other limit it is identical with the linear wave theory. As the relative depth decreases the cnoidal wave becomes the solitary wave, which has a crest that is completely above the still water level and has no trough. The cnoidal wave theory covers a large class of long waves with finite amplitudes. It is presented in terms of two parameters, k2 and Ur, where k2 depends on the water depth, the wave length and height, which is one of the independent variables in the elliptical function. The parameter Ur is the Ursell parameter defined as Ur ¼ L2H=d3 which depends on the wave steepness and the relative water depth. This parameter defines the range of application of the wave theories. In general, the cnoidal wave theory is applicable for Ur[25, the Stokes theory is applicable for Ur\10 and both theories are applicable for Ur ¼ 10 25: The limiting case of (k2 = 0) results in the small amplitude wave theory while (k2 = 1) results in the solitary wave theory. The forms (water elevation) of different waves are shown in Fig. 3.2. Since the nonlinear wave theories are not the main topic covered in this book they are not further presented herein. The interested readers should consult related references [8, 9, 14, 16, 27, 32–41]. As the linear (Airy) wave theory is used for the stochastic analysis of offshore structures further in this book, it is presented below in detail.

Linear (Airy) Wave Theory

The linear wave theory (also known as the Airy wave theory) is the simplest and most useful theory among other wave theories. It assumes small wave steepness and small relative water depth (H/d), which allows the free surface boundary conditions to be linearized and satisfied at the mean water level (still water level, SWL). It is equivalent to the first-order Stokes wave theory. The linearized differential equations are stated from Eqs. (3.5a) and (3.5b) as written by,
∇2Φ=0→{Bottom boundary condition. …:∂Φ∂z∣z=−d=0Free surface boundary condition :→(∂2Φ∂t2+g∂Φ∂z)z=0=0\nabla^{2} \Phi=0 \rightarrow\left\{\begin{array}{l} \text { Bottom boundary condition. } \ldots:\left.\frac{\partial \Phi}{\partial z}\right|_{z=-d}=0 \\ \text { Free surface boundary condition }: \rightarrow\left(\frac{\partial^{2} \Phi}{\partial t^{2}}+g \frac{\partial \Phi}{\partial z}\right)_{z=0}=0 \end{array}\right. ∇2Φ=0→{ Bottom boundary condition. …:∂z∂Φ​∣∣​z=−d​=0 Free surface boundary condition :→(∂t2∂2Φ​+g∂z∂Φ​)z=0​=0​

The horizontal and vertical water particle velocities are calculated from,

Water particle velocities : →{u=∂Φ∂x=−iη^ωcosh⁡m(z+d)sinh⁡mdei(ωt−mx)w=∂Φ∂z=η^ωsinh⁡m(z+d)sinh⁡mdei(ωt−mx)\begin{array}{l} \text { Water particle velocities : } \rightarrow\left\{\begin{array}{l} u=\frac{\partial \Phi}{\partial x}=-i \hat{\eta} \omega \frac{\cosh m(z+d)}{\sinh m d} \mathrm{e}^{i(\omega t-m x)} \\ w=\frac{\partial \Phi}{\partial z}=\hat{\eta} \omega \frac{\sinh m(z+d)}{\sinh m d} \mathrm{e}^{i(\omega t-m x)} \end{array}\right. \end{array}  Water particle velocities : →{u=∂x∂Φ​=−iη^​ωsinhmdcoshm(z+d)​ei(ωt−mx)w=∂z∂Φ​=η^​ωsinhmdsinhm(z+d)​ei(ωt−mx)​​
The corresponding accelerations for small amplitude waves are calculated from the time derivatives of these velocities as written
Water particle accelerations: →{u˙=∂u∂t=η^ω2cosh⁡m(z+d)sinh⁡mdei(ωt−mx)w˙=∂w∂t=iη^ω2sinh⁡m(z+d)sinh⁡mdei(ωt−mx)\begin{array}{l} \text { Water particle accelerations: } \rightarrow\left\{\begin{array}{l} \dot{u}=\frac{\partial u}{\partial t}=\hat{\eta} \omega^{2} \frac{\cosh m(z+d)}{\sinh m d} \mathrm{e}^{i(\omega t-m x)} \\ \dot{w}=\frac{\partial w}{\partial t}=i \hat{\eta} \omega^{2} \frac{\sinh m(z+d)}{\sinh m d} \mathrm{e}^{i(\omega t-m x)} \end{array}\right. \end{array}  Water particle accelerations: →{u˙=∂t∂u​=η^​ω2sinhmdcoshm(z+d)​ei(ωt−mx)w˙=∂t∂w​=iη^​ω2sinhmdsinhm(z+d)​ei(ωt−mx)​​
The water particle displacements are calculated from the time integration of
velocities as written by,
Water particle displacements: →{ξx=∫udt=−η^cosh⁡m(z+d)sinh⁡mdei(ωt−mx)ξz=∫wdt=−iη^sinh⁡m(z+d)sinh⁡mdei(ωt−mx)\begin{aligned} \text { Water particle displacements: } \rightarrow &\left\{\begin{array}{l} \xi_{x}=\int u \, \mathrm{d} t=-\hat{\eta} \frac{\cosh m(z+d)}{\sinh m d} \mathrm{e}^{i(\omega t-m x)} \\ \xi_{z}=\int w \, \mathrm{d} t=-i \hat{\eta} \frac{\sinh m(z+d)}{\sinh m d} \mathrm{e}^{i(\omega t-m x)} \end{array}\right. \end{aligned}  Water particle displacements: →​{ξx​=∫udt=−η^​sinhmdcoshm(z+d)​ei(ωt−mx)ξz​=∫wdt=−iη^​sinhmdsinhm(z+d)​ei(ωt−mx)​​
The real parts of these displacements form an elliptical orbit around a fixed point (x0, z0) as shown in Fig. 3.4. The equation of the orbit is
Water particle orbit: →((ξx0−x0)2cosh⁡2m(z0+d)+(ξz0−z0)2sinh⁡2m(z0+d))=η^2sinh⁡2md\text { Water particle orbit: } \rightarrow\left(\frac{\left(\xi_{x_{0}}-x_{0}\right)^{2}}{\cosh ^{2} m\left(z_{0}+d\right)}+\frac{\left(\xi_{z_{0}}-z_{0}\right)^{2}}{\sinh ^{2} m\left(z_{0}+d\right)}\right)=\frac{\hat{\eta}^{2}}{\sinh ^{2} m d}  Water particle orbit: →(cosh2m(z0​+d)(ξx0​​−x0​)2​+sinh2m(z0​+d)(ξz0​​−z0​)2​)=sinh2mdη^​2​
With these velocity and acceleration information the wave forces on structural members can be calculated using the Morison’s equation [35] as it will be explained later in this chapter. However, since the deep water condition is used further in this book, the velocity potential function, velocity and acceleration components, and the orbit equation for deep water condition are presented below.

Formulation for Deep Water Condition

Deep water approximations: →{tanh⁡md≈1sinh⁡m(z+d)≈emzsinh⁡mdcosh⁡m(z+d)≈emzsinh⁡md\text { Deep water approximations: } \rightarrow\left\{\begin{array}{l} \tanh m d \approx 1 \\ \sinh m(z+d) \approx \mathrm{e}^{m z} \sinh m d \\ \cosh m(z+d) \approx \mathrm{e}^{m z} \sinh m d \end{array}\right.  Deep water approximations: →⎩⎨⎧​tanhmd≈1sinhm(z+d)≈emzsinhmdcoshm(z+d)≈emzsinhmd​
Velocity potential function :→Φ=η^gωemzei(ωt−mx)\text { Velocity potential function }: \rightarrow \quad \Phi=\hat{\eta} \frac{g}{\omega} \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)}  Velocity potential function :→Φ=η^​ωg​emzei(ωt−mx)
Water elevation ∴→η=−iη^ei(ω−r−m)x\therefore \rightarrow \eta=-i \hat{\eta} e^{i(\omega-r-m) x}∴→η=−iη^​ei(ω−r−m)x
Dispersion relationship :→ω2=mg: \rightarrow \omega^{2}=m g:→ω2=mg
Water particle velocities... :→{u=η^−iωemzei(ωt−mx)w=η^ωemzei(ωt−mx)Water particle accelerations :→{u˙=η^ω2emzei(ωt−mx)w˙=iη^ω2emzei(ωt−mx)\begin{aligned} &\text { Water particle velocities... } \quad: \rightarrow\left\{\begin{array}{l} u=\hat{\eta}-i \omega \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)} \\ w=\hat{\eta} \omega \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)} \end{array}\right.\\ &\text { Water particle accelerations }: \rightarrow\left\{\begin{array}{l} \dot{u}=\hat{\eta} \omega^{2} \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)} \\ \dot{w}=i \hat{\eta} \omega^{2} \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)} \end{array}\right. \end{aligned} ​ Water particle velocities... :→{u=η^​−iωemzei(ωt−mx)w=η^​ωemzei(ωt−mx)​ Water particle accelerations :→{u˙=η^​ω2emzei(ωt−mx)w˙=iη^​ω2emzei(ωt−mx)​​
Water particle displacements : →{ξx=−η^emzei(ωt−mx)ξz=−iη^emzei(ωt−mx)\text { Water particle displacements : } \rightarrow\left\{\begin{array}{l} \xi_{x}=-\hat{\eta} \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)} \\ \xi_{z}=-i \hat{\eta} \mathrm{e}^{m z} \mathrm{e}^{i(\omega t-m x)} \end{array}\right.  Water particle displacements : →{ξx​=−η^​emzei(ωt−mx)ξz​=−iη^​emzei(ωt−mx)​
Water particle orbit : →(ξx0−x0)2+(ξz0−z0)2=η^2e2mz0\text { Water particle orbit : } \rightarrow\left(\xi_{x_{0}}-x_{0}\right)^{2}+\left(\xi_{z_{0}}-z_{0}\right)^{2}=\hat{\eta}^{2} \mathrm{e}^{2 m z_{0}}  Water particle orbit : →(ξx0​​−x0​)2+(ξz0​​−z0​)2=η^​2e2mz0​

Stochastic Description of Ocean Waves and Short-Term Sea States

Sea waves have irregular profiles changing randomly in time and space. They cannot be determined in a deterministic way like those presented in above sections. Sea waves are random in nature and mostly short crested. During a relatively short period, they are composed of infinite number of independent regular waves with different amplitudes, frequencies, traveling directions, and phases that are all random. Since we assume that these individual regular waves are determined from the linear wave theory, the superposition rule is applied to form a random wave group traveling along an arbitrary direction with individual waves scattered around it. Since there is infinite number of waves in a random wave group with different mplitudes, in the light of central limit theorem, the random surface displacement (surface elevation) becomes a Gaussian random process [7, 42–46] with zero mean value. A random wave profile obtained from the superposition of a number of individual independent regular waves is shown in Fig. 3.5. Over a time interval of about 3 h at some locations on the sea surface, the surface elevations g are measured relative to the still water level and, in this way, a number of records are obtained. Under the same sea condition, over another time intervals with about 3 h long at different locations, the measurements of the surface elevations are repeated and different records are obtained. From the comparison of all records of the surface elevation it can be seen that the surface elevation g would have a similar appearance and its general properties would not change. Thus, a single record of the surface elevation represents its random characteristics. This observation reveals that, in a short term, the water surface elevation g is a stationary ergodic process. Similarly, the water particle velocities and accelerations become also stationary ergodic processes. In a short term, random waves are usually described in terms of sea states. A unidirectional sea state is a stationary ergodic process described by the parameters, the significant wave height Hs and mean zerocrossings period Tz, and also by a spectral function SggðxÞ of the surface elevation g, which is defined between ð0x1Þ as known to be the sea spectrum, or wave energy spectral density function [14, 22].

Transfer Functions of a Random Wave in Deep Water

Statistics and Spectral Functions of the Water Elevation in the Short Term

The Pierson–Moskowitz Sea Spectrum

PM sea spectrum : →Sηη(ω)=Aω5exp⁡(−Bω4)\text { PM sea spectrum : } \rightarrow S_{\eta \eta}(\omega)=\frac{A}{\omega^{5}} \exp \left(-\frac{B}{\omega^{4}}\right)  PM sea spectrum : →Sηη​(ω)=ω5A​exp(−ω4B​)
A=αηg2and B=5ωp4/4A=\alpha_{\eta} g^{2} \quad \text { and } \quad B=5 \omega_{p}^{4} / 4 A=αη​g2 and B=5ωp4​/4
Peak wave frequency ( Hsrepresents severity): →ωp=(165αηg2Hs2)1/4\text { Peak wave frequency ( } H_{s} \text { represents severity): } \rightarrow \quad \omega_{p}=\left(\frac{16}{5} \frac{\alpha_{\eta} g^{2}}{H_{s}^{2}}\right)^{1 / 4}  Peak wave frequency ( Hs​ represents severity): →ωp​=(516​Hs2​αη​g2​)1/4
Hs&Tzrepresent severity: {A=αηg2=4π3Hs2Tz4ωp=2πTz(45π)1/4→peak wave frequency \begin{aligned} H_{s} \& T_{z} \text { represent severity: } &\left\{\begin{aligned} A &=\alpha_{\eta} g^{2}=\frac{4 \pi^{3} H_{s}^{2}}{T_{z}^{4}} \\ \omega_{p} &=\frac{2 \pi}{T_{z}}\left(\frac{4}{5 \pi}\right)^{1 / 4} & \rightarrow\text { peak wave frequency } \end{aligned} \right. \end{aligned} Hs​&Tz​ represent severity: ​⎩⎪⎪⎪⎨⎪⎪⎪⎧​Aωp​​=αη​g2=Tz4​4π3Hs2​​=Tz​2π​(5π4​)1/4​→ peak wave frequency ​​

The JONSWAP Sea Spectrum

JONSWAP sea spectrum : →Sηη(ω)=Aω5exp⁡(−Bω4)γg(ω)\text { JONSWAP sea spectrum : } \rightarrow S_{\eta \eta}(\omega)=\frac{A}{\omega^{5}} \exp \left(-\frac{B}{\omega^{4}}\right) \gamma^{g(\omega)}  JONSWAP sea spectrum : →Sηη​(ω)=ω5A​exp(−ω4B​)γg(ω)
g(ω)=exp⁡[−12(ω−ωpωpσ)2]g(\omega)=\exp \left[-\frac{1}{2}\left(\frac{\omega-\omega_{p}}{\omega_{p} \sigma}\right)^{2}\right] g(ω)=exp[−21​(ωp​σω−ωp​​)2]
σ={0.07if ω≤ωp0.09if ω>ωp\sigma=\left\{\begin{array}{cl} 0.07 & \text { if } \omega \leq \omega_{p} \\ 0.09 & \text { if } \omega>\omega_{p} \end{array}\right. σ={0.070.09​ if ω≤ωp​ if ω>ωp​​
Peak wave frequency (Hsrepresents severity): →ωp=(fp(γ)αηg2Hs2)1/4\text { Peak wave frequency }\left(H_{s} \text { represents severity): } \rightarrow \quad \omega_{p}=\left(\frac{f_{p}(\gamma) \alpha_{\eta} g^{2}}{H_{s}^{2}}\right)^{1 / 4}\right.  Peak wave frequency (Hs​ represents severity): →ωp​=(Hs2​fp​(γ)αη​g2​)1/4
fp(γ)=3.19714(1−0.286ln⁡γ)f_{p}(\gamma)=\frac{3.19714}{(1-0.286 \ln \gamma)} fp​(γ)=(1−0.286lnγ)3.19714​

Station A(m) B(m) C Location
India 0.80 2.70 1.22 Atlantic Ocean
Juliett 0.90 2.70 1.24 Atlantic Ocean
Sevenstones 0.6 1.67 1.21 Atlantic Ocean
Morecambe Bay 0.0 0.78 1.05 Irish Sea
Mersey bay 0.00 0.69 1.01 Irish Sea
Varne 0.00 1.05 1.30 North Sea
Smith’s Knoll 0.08 0.89 1.28 North Sea

Directional Wave Spectrum

Wave-Current Interaction

Probabilistic Description of Sea States in the Long Term

Morison’s Equation and Wave Forces on Structural Members


The Morison’s equation is defined as a distributed wave force per unit length of the pile and is normal (perpendicular) to the pile. It is written as,
Morison’s equation : →f=CD∣u∣u+CMu˙\text { Morison's equation : } \rightarrow f=C_{D}|u| u+C_{M} \dot{u}  Morison’s equation : →f=CD​∣u∣u+CM​u˙
in which the first term is the drag force contribution and the second one is the inertia force contribution, uuu and u˙\dot uu˙ are respectively the velocity and acceleration components of a water particle which are normal to the pile, ∣⋅∣|\cdot|∣⋅∣ denotes an absolute value, CDC_DCD​ and CMC_MCM​ are respectively drag and inertia force constants defined as,
Drag and inertia force constants: →{CD=Dρwcd/2CM=πD2ρwcm/4\text { Drag and inertia force constants: } \rightarrow\left\{\begin{array}{l} C_{D}=D \rho_{w} c_{d} / 2 \\ C_{M}=\pi D^{2} \rho_{w} c_{m} / 4 \end{array}\right.  Drag and inertia force constants: →{CD​=Dρw​cd​/2CM​=πD2ρw​cm​/4​
in which DDD is the diameter of the pile, ρw\rho_wρw​ is the density of water, cdc_dcd​ and cmc_mcm​ are respectively the drag and inertia force coefficients of the Morison’s equation. These coefficients are functions of the Reynolds number (ReR_eRe​), Keulegan–Carpenter number (KcK_cKc​) and the roughness of the cylinder [14, 22, 23, 51, 91, 92]. API recommends the following drag and inertia values for circular cylinders [93, 94] for large Keulegan–Carpenter number (Kc>30)(K_c \gt 30)(Kc​>30):

  • for smooth cylinders: cd=0.65c_d = 0.65cd​=0.65 and cm=1.6c_m = 1.6cm​=1.6
  • for rough cylinders: cd=1.05c_d = 1.05cd​=1.05 and cm=1.2c_m = 1.2cm​=1.2

For Kc>30_Kc \gt 30K​c>30 these values are modified by a wake amplification factor. The DNV rules [51] accept the same values for the smooth and rough cylinders, except the inertia force coefficient cmc_mcm​. The DNV rules define higher cm values than the API recommended practices. For Kc<3Kc \lt 3Kc<3, cmc_mcm​ can be assumed to be independent of KcK_cKc​ and equal to the theoretical value of (cm=2.0)(c_m =2.0)(cm​=2.0) for both smooth and rough cylinders. In the case of Kc>3K_c > 3Kc​>3, it is calculated from [51] as,
cm=max⁡{1.6,[2−0.044(Kc−3)]→smooth cylinder 1.2,[2−0.044(Kc−3)]→rough cylinder c_{m}=\max \left\{\begin{array}{l} 1.6,\left[2-0.044\left(K_{c}-3\right)\right] \rightarrow \text { smooth cylinder } \\ 1.2,\left[2-0.044\left(K_{c}-3\right)\right] \rightarrow \text { rough cylinder } \end{array}\right. cm​=max{1.6,[2−0.044(Kc​−3)]→ smooth cylinder 1.2,[2−0.044(Kc​−3)]→ rough cylinder ​
For low Keulegan–Carpenter numbers, a detailed discussion on the drag and inertia force coefficients is presented in [95]. It is reported [96] that, for (Kc<10)(K_c \lt 10)(Kc​<10), the inertia force becomes dominant, for (10<Kc<20)(10 \lt K_c \lt 20)(10<Kc​<20), both inertia and drag force components are significant and for (Kc>20)(K_c \gt 20)(Kc​>20), the drag force becomes dominant. The diameter of the cylinder, DDD, is also an influential factor in the wave force regime. The Morison’s equation is appropriate for slender members. However, for large members, it can also be applied with modification of the inertia force coefficient cmc_mcm​. This is done by using wave diffraction theory to calculate dynamic pressure, which is explained in the following section.

20200408_W_水波理论和波浪载荷相关推荐

  1. 波浪理论和波浪载荷的matlab编程,波浪理论各个波浪的特性和数浪的原则(图文对照)...

    波浪理论理解市场的走势由市价格形态的结构重复组成.基本上,市场的周期是由两种波浪形态所组成:推动浪和调整浪.每一种推动浪可分为五个子浪的结构(1-2-3-4-5),而调整浪可分为三个子浪的结构(a-b ...

  2. 流体力学发展史(转)

    流体力学发展简史     流体力学是力学的一个分支,它主要研究流体本身的静止状态和运动状态,以及流体和固体界壁间有相对运动时的相互作用和流动的规律. 流体力学中研究得最多的流体是水和空气.它的主要基础 ...

  3. 物 理 学 简 介(二)

    (二)物理学分支-力 学 1.力 学 概 述 力学又称经典力学,是研究通常尺寸的物体在受力下的形变,以及速度远低于光速的运动过程的一门自然科学.力学是物理学.天文学和许多工程学的基础,机械.建筑.航天 ...

  4. #5.2探讨时空同时考虑的相关理论的软肋

    还有一类就是时空一起考虑的理论.所谓时空,就是股价与时间,说时空方便而已,而且在四维理论中,你可能要习惯这种简单的称呼股价与时间的方法. 这类理论,不仅仅要面对单独考虑时间或股价的理论遇到的问题,同时 ...

  5. #第六章 四维股市理论数学模型基础6.1四维股市拟合理论的数学基础

    我把用三维或三维以下的数学方法解读四维或四维以上数学现象的理论暂且称为伪四维或者跨维解读.实际上,这类理论已经发现三维数学系统中存在的不足,从而通过增加考量因素的方法试图解决跨维解读的问题. 历史上, ...

  6. WebGL 水波及焦散(刻蚀)的渲染总结

    本文作者:木的树 关于小区域水波渲染以及焦散的技术原理,推荐下面两篇资源: https://github.com/martinRenou/threejs-caustics https://zhuanl ...

  7. maccamy fuchs matlab,近海固定式风机单桩大直径基础波浪载荷研究

    0 引 言 中国拥有较为丰富的近海风力资源,据中国气象科学研究院统计评估,我国近海可开发的风能资源储量约750 GW.海上风能具有海面粗糙度小.风湍流强度小.主导风向稳定等特点.这有利于增大装机容量, ...

  8. 诺奖终属黑洞理论-IT与物理的相互成就

    2020年诺贝尔物理学奖颁给了罗杰·彭罗斯(Roger Penrose),因他发现黑洞形成是广义相对论的一个预言:莱因哈特·根策尔(Reinhard Genzel),安德烈娅·盖兹(Andrea Gh ...

  9. 【交通流理论】初级基础

    概述 连续流与间断流:区别在于是否存在信号灯.交叉口等设施使得车流存在周期性中断 连续流的特征 由流率QQQ.行车速度Vs‾\overline{V_s}Vs​​.密度KKK三个基本参数之间的关系 Q= ...

  10. 2022诺贝尔物理学奖:曾背负恶名的贝尔理论与历经10年的探索

    北京时间10月4日下午,2022年诺贝尔物理学奖被授予科学家阿兰·阿斯佩(Alain Aspect),约翰·弗朗西斯·克劳泽(John F.Clauser)和安东·塞林格(Anton Zeilinge ...

最新文章

  1. spring boot整合spring5-webflux从0开始的实战及源码解析
  2. GDCM:读取UTF8 QtDir的测试程序
  3. [linux] shell脚本编程-统计日志文件中的设备号发通知邮件
  4. 使用视觉信息,为什么能把移动机器人的空间位置信息记录下来
  5. ServerSuperIO Designer IDE 发布,打造物联网通讯大脑,随心而联。附:C#驱动源代码。
  6. Linux学习之内核模块编程
  7. [SDOI2009]地图复原 递推
  8. android boot.img 结构,android boot.img文件结构、拆包、打包
  9. OPENCV3.0 双目立体标定
  10. 互联网+ 何人能挡?带着你的Code飞奔吧!
  11. Java链表的常用算法原理
  12. 外置存储权限在哪打开_安卓手机外置sd卡权限怎么打开
  13. 计算机windows用户名密码怎么查,如何查看Windows和Office的密码、序列号
  14. NDK学习笔记:FFmpeg解压MP34提取音频PCM(swrContext、swr_alloc_set_opts)
  15. IDE中使用package打包出现java.lang.TypeNotPresentException: Type org.springframework.boot.maven.RepackageMoj
  16. 学习区块链要掌握哪些专项能力?区块链学习培训多长时间?
  17. bat(batch)
  18. ZQOJ 1123: 最佳校友
  19. Python爬虫系列之抖音热门视频爬取
  20. 机械设计与制造类毕业论文文献都有哪些?

热门文章

  1. OpenGL超级宝典(第7版)笔记22 原子计数器 清单5.31-5.34
  2. 锐起无盘系统菜鸟教程
  3. Linux关机、开机、重启、定时重启、定时关机详细命令(shutdown命令)
  4. 2003系统如何搭建ftp服务器配置,WINDOWSSERVER2003系统架设FTP服务器配置方法.pdf
  5. r语言 怎么把字调大_R语言中字体设置
  6. opencv 模式识别学习
  7. [从零开始学习FPGA编程-27]:进阶篇 - 基本组合电路-数据比较器(Verilog语言)
  8. C语言基础入门:C-Free 5下载和安装详细教程
  9. 软件工程期末复习题库
  10. Java集合框架知识点