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The modulational instability in deep water under the action of wind and dissipation

TL;DR: In this article, the modulational instability of gravity wave trains on the surface of water acted upon by wind and under influence of viscosity is considered, and the marginal curves separating stable states from unstable states are given.
Abstract: The modulational instability of gravity wave trains on the surface of water acted upon by wind and under influence of viscosity is considered. The wind regime is that of validity of Miles' theory and the viscosity is small. By using a perturbed nonlinear Schrodinger equation describing the evolution of a narrow-banded wavepacket under the action of wind and dissipation, the modulational instability of the wave group is shown to depend on both the frequency (or wavenumber) of the carrier wave and the strength of the friction velocity (or the wind speed). For fixed values of the water-surface roughness, the marginal curves separating stable states from unstable states are given. It is found in the low-frequency regime that stronger wind velocities are needed to sustain the modulational instability than for high-frequency water waves. In other words, the critical frequency decreases as the carrier wave age increases. Furthermore, it is shown for a given carrier frequency that a larger friction velocity is needed to sustain modulational instability when the roughness length is increased.

Summary (4 min read)

1. Introduction

  • Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
  • As of 1st August 2021, more than 196.9 million cases have been reported across 213 countries and territories with more than 4.2 million deaths and more than 1135.19 million people have been fully vaccinated.
  • Visiting the hospital has become a part of life, but after the attack of the COVID-19 pandemic, it has been observed a serious reduction in people visiting the hospitals, or even the health care workers avoiding patients visiting the hospitals.
  • (2) Nevertheless, the relative decline in visits remains largest among surgical and procedural specialties and paediatrics.
  • Therefore, their study aims to ask and find out the answers to all these major concerns and to address them properly.

2.1 Study Design and Sampling Technique

  • This is a cross-sectional survey among common people in two states of India (Maharashtra and Karnataka).
  • Conventional non-probability sampling technique was used to analyse the questions given to the respondents.
  • (4) The inclusion criteria were common people (undergraduate, postgraduate, and the people from medical field) at the time of data collection and having access to an internet connection to fill out the online questionnaire.
  • Individuals who did not fill the form completely were excluded from the study.

2.1 Study Instrument and Administration

  • A short online questionnaire was developed after a review of a similar study.
  • (4) Outcome variables include the respondent’s attitude towards visiting the hospitals and the reasons for not visiting the hospitals during the COVID-19 pandemic.
  • The following ten questions were formulated for the online survey through google forms as shown in Table 1.
  • The link to respondents was distributed across social media platforms and the data collection took place in June 2021.
  • The typical Google form is shown in Fig 2.

2.2 Data Analysis

  • There were around 636 respondents representing females and males from two states of India who responded to the survey through google forms.
  • Google forms data were downloaded and data were analysed using different statistical tools.
  • The tools are being used to verify the normal distribution of variables and comparisons between groups for categorical variables.
  • Binary logistic regression analysis was carried out to identify parameters more strongly associated with respondent’s Attitudes and behavior of people towards visiting the hospitals during the pandemic.

3. Results

  • Distribution and sociodemographic characteristics of respondents: A total of 1590 respondents representing females (48.4%) and males (50.3%) from two states of India completed the online survey.
  • The mean age of participants was 39.9 years.
  • There were 37.4% respondents were postgraduate & above and 35.8% respondents were undergraduate and remaining respondents were high school graduates and college graduates.
  • Table 2 shows the distribution of sociodemographic characteristics used in the study.
  • The analysis of each questionnaire are as follows:.

3.1 Were you going to the hospital for common illness before the pandemic started?

  • More than half of respondents i.e. about 62.6% were visiting the hospital for common illnesses like the common cold, cough headache, body ache, first degree burns, acidity, indigestion, eye, ear, joint, or skin related problems, etc. before the pandemic started.
  • On the other hand, 37.1% of respondents were not visiting the hospitals for such common illnesses even before the pandemic started.
  • Fig. 3 shows the percentage of people visiting to the hospital before the pandemic started.

3.4 Are you under treatment of any long term diseases (like Diabetes or BP)?

  • About 86.5% of respondents were not under any long- term treatment because of the average age group of respondent being 39.9 years, on the other hand, 13.5% of respondents were under the treatment of long term disease.
  • This question was asked to know how people are maintaining the long term diseases like diabetes or blood pressure during the COVID-19 pandemic when they are afraid to go out for regular follow-ups and laboratory tests.
  • Fig. 6 shows the percentage of people having long term diseases.

3.5 How often were you going to the hospital before the pandemic started?

  • About 73% of respondents are visiting the hospital less than two times a year, 19.8% of respondents are visiting three-four times a year and 7.2% of respondents are visiting more than four times a year for any disease before pandemic started.
  • Fig. 7 shows the percentage of visits to the hospital before the pandemic started.

3.6 Has the frequency of you visiting the hospital reduced after the pandemic started?

  • About 74.8% of respondents stated that the frequency of visiting the hospital has reduced after the pandemic started and 25.2% of respondents stated that the frequency of visiting the hospital has not reduced even after the pandemic started.
  • Fig. 8 shows the percentage of people who have reduced the number of visits to the hospital after the pandemic started.

3.7 How often do you go to the hospital after the pandemic started?

  • About 49.7% of respondents are visiting the hospital once or twice a year for any disease, 5.3% of respondents are visiting three-four times a year to the hospitals, 40.6% of the respondents have not visited the hospital since the pandemic has started and other 3.8% of the respondents visit more than four times a year to the hospital.
  • Fig. 9 shows the percentage of visits a person makes to the hospital after the pandemic started.

3.9 If you are reducing the number of visits how are you managing your health

  • Problem About 58.4% of respondents are managing their health problems by online consultation of doctors, 20.1% of respondents by taking medications on their own, 19.4% of respondents by calling the doctor home for consultation or lab technician to collect samples if needed.
  • Whereas other respondents are managing by home remedies like homeopathy, yoga, Ayurveda medicines, and immunity boosters.
  • But Some of the patients who have long term diseases go to the hospital for regular follow-ups to avoid unavoidable risks.
  • About 53.7% of respondants have not increased the frequency of visiting the hospitals even after taking both the doses of vaccination, on the other hand 27.3% of respondents have gained the confidence to visit the hospital for the treatment after vaccination.

4. Discussion

  • Total of 636 respondent’s forms data was analysed.
  • This analysis reveals that more percentage of respondents have reduced the visit to the hospitals due to getting infected within the hospitals.
  • The data shows that 58.4% of respondents manage their health themselves by online consultation of doctors, 20.1% by taking medications on their own, 19.4% by calling the doctor or lab technician home for sample collection and others by home remedies.
  • The increased online consultations have increased demand for the relevant clinical services and reduced hospital visits, thus decreasing COVID-19 spread.
  • (11) Instead of increasing stress of some patients at home with the fear of isolation and family member’s misconception towards the disease, it’s better to visit the hospital and get treated, this will reduce the serious mental health problems of patients.

5. Conclusion

  • This study reveals that there is drastic reduction in hospital visits due to a reduction in attitude and behaviour of common people towards visiting the hospital during the COVID-19 pandemic due to the fear of getting an infection by the virus.
  • Informed consent was obtained from all subjects involved in the study, also known as Informed Consent Statement.

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J. Fluid Mech. (2010), vol. 664, pp. 138–149.
c
Cambridge University Press 2010
doi:10.1017/S0022112010004349
The modulational instability in deep water under
the action of wind and dissipation
C. KHARIF
1
, R. A. KRAENKEL
2
, M. A. MANNA
3
AND R. THOMAS
1
1
Institut de Recherche sur les Ph
´
enom
`
enes Hors
´
Equilibre, 49, rue F. Joliot-Curie, BP 146,
13384 Marseille CEDEX 13, France
2
Instituto de Fisica Teorica, UNESP, R. Pamplona 145, 01405-900 S
˜
ao Paulo, Brazil
3
Laboratoire de Physique Th
´
eorique et Astroparticules, CNRS-UMR 5207, Universit
´
e Montpellier II,
Place Eug
`
ene Bataillon, 34095 Montpellier CEDEX 05, France
(Received 5 February 2010; revised 11 August 2010; accepted 11 August 2010;
first published online 1 November 2010)
The modulational instability of gravity wave trains on the surface of water acted
upon by wind and under influence of viscosity is considered. The wind regime is that
of validity of Miles’ theory and the viscosity is small. By using a perturbed nonlinear
Schr
¨
odinger equation describing the evolution of a narrow-banded wavepacket under
the action of wind and dissipation, the modulational instability of the wave group is
shown to depend on both the frequency (or wavenumber) of the carrier wave and the
strength of the friction velocity (or the wind speed). For fixed values of the water-
surface roughness, the marginal curves separating stable states from unstable states
are given. It is found in the low-frequency regime that stronger wind velocities are
needed to sustain the modulational instability than for high-frequency water waves.
In other words, the critical frequency decreases as the carrier wave age increases.
Furthermore, it is shown for a given carrier frequency that a larger friction velocity
is needed to sustain modulational instability when the roughness length is increased.
Key words: air/sea interactions, surface gravity waves, wind–wave interactions
1. Introduction
Since Stokes (1847), it is well known that the potential water wave problem
admits as solutions uniform wave trains of two-dimensional progressive waves. The
stability of the Stokes’ wave solution started with the work by Lighthill (1965) who
provided a geometric condition for wave instability. Later on, Benjamin & Feir (1967)
showed analytically that Stokes waves of moderate amplitude are unstable to small
long-wave perturbations travelling in the same direction. This instability is called
the Benjamin–Feir instability (or modulational instability). Whitham (1974) derived
the same result independently by using an averaged Lagrangian approach, which
is explained in his book. At the same time, Zakharov (1968), using a Hamiltonian
formulation of the water wave problem obtained the same instability result and
derived the nonlinear Schr
¨
odinger equation (NLS equation). The evolution of a
two-dimensional nonlinear wave train on deep water, in the absence of dissipative
effects, exhibits the Fermi–Pasta–Ulam recurrence phenomenon. This phenomenon
is characterized by a series of modulation–demodulation cycles in which initially
Email address for correspondence: kharif@irphe.univ-mrs.fr

Modulational instability in deep water under the action of wind and dissipation 139
nearly uniform wave trains become modulated and then demodulated until they are
again nearly uniform. Modulation is caused by the growth of the two dominant
sidebands of the Benjamin–Feir instability at the expense of the carrier. During
the demodulation, the energy returns to the components of the original wave train.
Recently, within the framework of the NLS equation, Segur et al. (2005a) revisited
the Benjamin–Feir instability when dissipation is taken into account. The latter
authors showed that for waves with narrow bandwidth and moderate amplitude,
any amount of dissipation stabilizes the modulational instability. In the wavenumber
space, the region of instability shrinks as time increases. This means that any initially
unstable mode of perturbation does not grow for ever. Damping can stop the growth
of the sidebands before nonlinear interactions become important. Hence, when the
perturbations are small initially, they cannot grow large enough for nonlinear resonant
interaction between the carrier and the sidebands to become important. The amplitude
of the sidebands can grow for a while and then oscillate in time. Segur et al. (2005a)
have confirmed their theoretical predictions by laboratory experiments for waves of
small to moderate amplitude. Later, Wu, Liu & Yue (2006) developed fully nonlinear
numerical simulations which agreed with the theory and experiments of Segur et al.
(2005a).
Within the framework of random waves, there exists a stochastic counterpart of
the modulational instability discussed above. The stability of nearly Gaussian and
narrow-banded water wave trains was investigated by Alber & Saffman (1978), Alber
(1978) and Crawford, Saffman & Yuen (1980). They found that the modulational
instability on deep water occurs, provided that the relative spectral width is less than
twice the average steepness. Hence, the effect of increasing randomness is to restrict
the instability criterion, to delay the onset of modulational instability, and to reduce
the amplification rate of the modulation.
From the previous studies we could conclude that dissipation and randomness
may prevent the development of the Benjamin–Feir instability (or modulational
instability). These two effects question the occurrence of modulational instability of
water wave trains. Segur, Henderson & Hammack (2005b) speculated about the
effect of dissipation on the early development of rogue waves and asked the question:
can the Benjamin–Feir instability spawn a rogue wave? Since damping affects the
modulational instability of waves in deep water, they assumed that it might affect the
early development of rogue waves. Nevertheless, the latter study did not include wind
effect. What is the role of wind upon modulational instability when dissipative effects
are considered? Waseda & Tulin (1999) showed experimentally that the wind does not
suppress the Benjamin–Feir instability even if the naturally (unseeded experiments)
developed initial sideband energy is reduced. This finding contrasts with that of
Bliven, Huang & Long (1986) who conducted unseeded experiments and found that
sideband growth was reduced in the presence of wind.
The present paper is aimed at reporting on the behaviour of Benjamin–Feir
instability when dissipation and wind input are both taken into account. Following
Miles (1957), but within the framework of modulated wave trains, we assume the
atmospheric pressure at the interface due to wind and the water wave slope to be
in phase. The effect is to produce an exponential growth of the wave amplitude. We
remind the reader that Miles (1957) studied a linear and uniform monochromatic
wave train, whereas we are considering a weakly nonlinear modulated wave train.
In the presence of dissipation it is found that carrier waves of given frequency (or
wavenumber) may suffer modulational instability when the friction velocity is larger
than a threshold value. Conversely, for a given friction velocity it is found that only

140 C. Kharif, R. A. Kraenkel, M. A. Manna and R. Thomas
carrier waves whose frequency (or wavenumber) is less than a threshold value are
unstable. Otherwise dissipation prevents instability developing over time.
In §2, the governing equations and the wave amplification theory of Miles (1957)
are briefly presented. In §3, the NLS equation is introduced when dissipation and
wind forcing are considered and the competition between wave amplification by the
wind and stabilization due to dissipation is considered. The linear stability analysis
of the Stokes-like wave is developed in §4. The final discussion is found in §5.
2. Surface waves under the action of wind and dissipation
We will consider waves on the surface of a fluid whose viscosity is small as given
by Lamb (1993, article no. 349). If g is the acceleration due to gravity, k is the
wavenumber of the surface perturbation and ν is the viscosity, we define a non-
dimensional number L(k)=ν/
g/k
3
, and we say that a fluid is of small viscosity if
L(k) 1. (2.1)
For the free surface problem in water, viscous effects are generally weak producing
a thin rotational layer adjacent to the potential flow. The thickness of this rotational
boundary layer is O(
ν/kc), where c is the phase velocity. In this context, it was
shown by Dias, Dyachenko & Zakharov (2008) that the equations governing the
fluid’s motion can be formulated with the help of potential theory. The correction
due to viscosity they derived within the framework of the linearized equations
was heuristically generalized to the nonlinear equations. Using a similar approach,
Lundgren (1989) derived linear versions of the modified boundary equations (2.4)
and (2.5). Note that another variant of the introduction of viscous effects within the
framework of potential theory can be found in the paper by Skandrani, Kharif &
Poitevin (1996).
The fluid layer is limited above by the water surface described by z = η(x,t). We
will consider the case of infinite depth. Under these hypotheses, the Laplace equation,
the bottom boundary condition and the kinematic condition are
φ
xx
+ φ
zz
=0 for −∞6 z 6 η(x,t), (2.2)
φ 0forz →−, (2.3)
η
t
+ φ
x
η
x
φ
z
2νη
xx
=0 for z = η(x, t). (2.4)
The dynamic boundary condition is modified by wind effect too, and has the form
φ
t
+
1
2
[(φ
x
)
2
+(φ
z
)
2
]+ =
1
ρ
P
a
2νφ
zz
for z = η(x, t), (2.5)
where ρ is the fluid’s density and P
a
is the excess pressure at the free surface. As
proposed by Dias et al. (2008), (2.4) and (2.5) are simply heuristic nonlinear
generalizations of their linear versions when dissipation is introduced.
In this paper we consider water wave trains in the open ocean far from any solid
boundaries. Note that in the case of surface waves generated in wave tanks damping
due to viscous dissipation at the lateral solid boundaries must be introduced (see
Miles 1967).
The dependence of the fluctuating pressure, P
a
,onη is what defines the wind–wave
interactions. Within the framework of linearized equations, Miles (1957) assumed that
the surface elevation and aerodynamic pressure are η(x,t)=ae
ik(xct)
and P
a
=(α +
iβ)ρ
a
U
2
1
, respectively, where a denotes the amplitude, k is the wavenumber, c is

Modulational instability in deep water under the action of wind and dissipation 141
the phase velocity, α and β are two coefficients depending on both k and c, ρ
a
is
the density of air and U
1
is a characteristic velocity related to the friction velocity,
u
, of wind over the water waves. In the expression of P
a
, there is a component in
phase and a component in quadrature with the water elevation. For an energy flux
to occur from the wind to the water waves, there must be a phase shift between the
fluctuating pressure and the interface. Hence, the transfer of energy is only due to
the component in quadrature with the water surface or in other words in phase with
the slope. To simplify the problem, we consider only the pressure component in phase
with the slope on the interface
P
a
(x,t)=ρ
a
βU
2
1
η
x
(x,t). (2.6)
For a logarithmic velocity profile in the turbulent boundary layer over the wave, we
have U
1
= u
,whereκ is the von K
´
arm
´
an constant. Hence,
P
a
(x,t)=Wη
x
(x,t), (2.7)
where W= ρ
a
(β/κ
2
)u
2
.
The rate of growth of the wave energy is ω(u
/c)
2
2
, where s = ρ
a
is the
air–water density ratio and ω = kc the frequency.
Miles (1957) developed an alternative derivation of the rate of growth of the wave
energy based on a linear stability analysis of the parallel shear flows. The transfer of
energy from a shear flow U (z) to a surface wave of wavenumber, k, and phase velocity,
c, is associated with a singularity at the critical layer z = z
c
at which U(z = z
c
)=c
E
∂t
= ρ
a
cπ
d
2
U
dz
2
(z
c
)/k
dU
dz
(z
c
)
w
2
(z
c
), (2.8)
where
E is the mean surface wave energy and w
2
(z
c
) is the mean-square value of
the wave-induced vertical velocity at z = z
c
. The overbar denotes an average over x.
The vertical velocity, w, is calculated from a Sturm–Liouville differential equation (or
the Rayleigh equation). The Rayleigh equation can be solved numerically once U (z),
k and c are known. Nevertheless, the presence of a singularity at the critical height,
z
c
, complicates the resolution. Conte & Miles (1959) developed a numerical method
to treat this singularity and solve the Rayleigh equation.
Writing ∂E/∂t = γE, we introduce the Miles coefficient β such as
γ =
ρ
a
ρ
kcβ
U
1
c
2
= β
U
1
c
2
, (2.9)
where γ is the rate of growth of the wave energy. Following Miles (1996), the
coefficient β is given by the following expression:
β =
π
k
(d
2
U/dz
2
)(z
c
)
|(dU/dz)(z
c
)|
w
2
(z
c
)
U
2
1
(∂η/∂x)
2
, (2.10)
where z = η(x) is the equation of the surface wave profile.
For a logarithmic profile of the atmospheric shear flow, the rate of growth γ is
γ =
ρ
a
ρ
kcβ
u
c
2
κ
2
=
s
κ
2
ωβ
u
c
2
. (2.11)
Note that in the classical theory of Miles, the interaction between the wave-induced
motion in the air flow and the turbulence is ignored. The turbulence is introduced
only to sustain a logarithmic wind profile.

142 C. Kharif, R. A. Kraenkel, M. A. Manna and R. Thomas
3. The perturbed NLS equation: amplification versus depletion
In this section, we consider both effects of dissipation and wind amplification
on the Benjamin–Feir instability. In the absence of viscosity and wind action, the
Benjamin–Feir instability may be investigated via an asymptotic expansion leading
to the well-known NLS equation. Our aim is to extend the works of Segur et al.
(2005a) and Leblanc (2007) who investigated this problem by considering damping
and wind effects separately. The derivation of the damped and forced NLS equation
does not present any conceptual difficulty. Hence, the expression of the perturbed
NLS equation can be stated as
i(ψ
t
+
x
)
0
8k
2
0
ψ
xx
2
0
k
2
0
|ψ|
2
ψ i
W
0
k
0
2
ψ = 2iνk
2
0
ψ, (3.1)
where k
0
and
0
are the wavenumber and frequency of the carrier wave, respectively,
satisfying the linear dispersion relation
2
0
= gk
0
and V =
0
/2k
0
is the group velocity
of the carrier wave. Equation (3.1) describes the spatial and temporal evolution of the
envelope, ψ, of the surface elevation, η, of weakly nonlinear and dispersive gravity
waves on deep water when damping and amplification effects are considered. The free
surface elevation is written as follows:
η(x, t)=ψ(x,t)exp[i(k
0
x
0
t)] + c.c. + O(
2
), (3.2)
where c.c. denotes the complex conjugate. The parameter, , is a small parameter
( 1) used to carry out the multiple scale analysis leading to (3.1). The elevation,
η, and envelope, ψ, are of order O(). We have assumed that the fluid viscosity, ν,
and density ratio, ρ
a
, are small: ν/
g/k
3
=
2
and ρ
a
=
2
. These assumptions
are generally used for water and air/sea interface.
We rewrite (3.1) in a standard form by using the following transformations:
ξ =2k
0
(x Vt)=
0
t, Ψ =
2k
0
ψ, (3.3)
leading to the following perturbed NLS:
ıΨ
τ
1
2
Ψ
ξξ
−|Ψ |
2
Ψ = ıKΨ, (3.4)
with
K =
Wk
0
2
2
νk
2
0
0
. (3.5)
The sign of K determines the nature of the perturbation. If K>0wehave
amplification of waves and if K<0 we have depletion. For K<0, this perturbed
NLS equation is similar to the NLS equation considered by Segur et al. (2005a).
It is also similar to the NLS equation used by Bridges & Dias (2007) when their
coefficients a and c vanish. In that case the latter authors demonstrated that there is
no enhancement of the modulational instability, whereas when a>0 the instability is
enhanced.
The condition K>0 implies that
4νκ
2
0
βsu
2
< 1. (3.6)
For a given friction velocity, this condition states that only carrier wave with frequency
or wavenumber less than a threshold value may suffer modulational instability. Within
the framework of the NLS equation, we consider weakly modulated wave train. Hence,
we can assume that β depends on the frequency (or wavenumber) and phase velocity

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Abstract: Instabilities are common phenomena frequently observed in nature, sometimes leading to unexpected catastrophes and disasters in seemingly normal conditions. One prominent form of instability in a distributed system is its response to a harmonic modulation. Such instability has special names in various branches of physics and is generally known as modulation instability (MI). The MI leads to a growth-decay cycle of unstable waves and is therefore related to Fermi-Pasta-Ulam (FPU) recurrence since breather solutions of the nonlinear Schrodinger equation (NLSE) are known to accurately describe growth and decay of modulationally unstable waves in conservative systems. Here, we report theoretical, numerical and experimental evidence of the effect of dissipation on FPU cycles in a super wave tank, namely their shift in a determined order. In showing that ideal NLSE breather solutions can describe such dissipative nonlinear dynamics, our results may impact the interpretation of a wide range of new physics scenarios.

120 citations

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TL;DR: In this article, the authors considered the effect of the wind and the dissipation on the nonlinear stages of the modulational instability and applied a suitable transformation to map the forced/damped nonlinear Schrodinger (NLS) equation into the standard NLS with constant coefficients.

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  • ...0004 (the same value has been used in [15])....

    [...]

  • ...Note that we use a different definition of the surface elevation from the one in [15] where the 1/2 factor is not included (the consequence is that the coefficient in the nonlinear term in equation (2) differs by a factor of 4 from the one in equation (3....

    [...]

  • ...In [15] the equation is written in a nondimensional form and the coefficient K = Γ/ω0 is introduced)....

    [...]

  • ...We considered the NLS equation discussed in [15]...

    [...]

  • ...More recently, the role of dissipation and wind in the modulational instability has been considered together within the NLS equation, [15] (then confirmed by fully nonlinear simulations, [16])....

    [...]

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  • ...The case ΓM/ f = O( 2) gives rise to the following damped/forced nonlinear Schrödinger equation [11, 8, 12]...

    [...]

  • ...For a logarithmic velocity profile in the boundary layer, the Miles growth rate ΓM results in [4, 7, 8]...

    [...]

  • ...The pressure P induced at the water surface then depends on the surface elevation η as follows [4, 8] 1 ρw P(x, t) = ΓM f c(2)p 2π ηx(x, t) (2)...

    [...]

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TL;DR: In this paper, it is shown that the adiabatically slow pumping (the time scale of forcing is much longer than the nonlinear time scale) results in selective enhancement of the solitary part of the wave ensemble.

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Cites background from "The modulational instability in dee..."

  • ... (2014). New terms which appear in that modification of the NLS equation may be eliminated after appropriate change of variables, and then the equation turns to the form considered in (Leblanc, 2007; Kharif et al, 2010; Onorato &amp; Proment, 2012). Numerical simulations of individual wave groups affected by wind were performed within different frameworks in (Yan and Ma, 2010; Adcock and Taylor, 2011). Laboratory a...

    [...]

References
More filters
Journal ArticleDOI

56 citations


"The modulational instability in dee..." refers methods in this paper

  • ...Conte & Miles (1959) developed a numerical method to treat this singularity and solve the Rayleigh equation....

    [...]

  • ...Conte & Miles (1959) computed the values of β as a function of κc0/u∗ for a logarithmic wind profile of the form U (z) = u∗ κ ln(z/z0), (3.7) where z0 is the roughness length given by z0 = αchu 2 ∗/g (αch is the Charnock constant ≈0.011–0.018)....

    [...]

Journal ArticleDOI
TL;DR: In this article, a quadratic function for the energy transfer over a deep-water sinusoidal gravity wave is derived and a corresponding Galerkin approximation that is based on independent variational approximations for outer and inner domains yields an energy-transfer parameter β that is comparable in magnitude with that of the quasi-laminar model (Miles 1957) and those calculated by Townsend (1972 and Gent & Taylor (1976) through numerical integration of the Reynolds-averaged equations.
Abstract: The Reynolds-averaged equations for turbulent flow over a deep-water sinusoidal gravity wave, z = acoskx ≡ h0(x), are formulated in the wave-following coordinates ζ, η, where x = ζ, z =η + h(ζ, η), h(ζ, 0) = h0(ζ) and h is exponentially small for kη [Gt ] 1, and closed by a viscoelastic consitutive equation (a mixing-length model with relaxation). This closure is derived from Townsend's boundary-layer-evolution equation on the assumptions that: the basic velocity profile is logarithmic in η + z0, where z0 is a roughness length determined by Charnock's similarity relation; the lateral transport of turbulent energy in the perturbed flow is negligible; the dissipation length is proportional to η + z0. A counterpart of the Orr-Sommerfeld equation for the complex amplitude of the perturbation stream function is derived and used to construct a quadratic functional for the energy transfer to the wave. A corresponding Galerkin approximation that is based on independent variational approximations for outer (quasi-laminar) and inner (shear-stress) domains yields an energy-transfer parameter β that is comparable in magnitude with that of the quasi-laminar model (Miles 1957) and those calculated by Townsend (1972) and Gent & Taylor (1976) through numerical integration of the Reynolds-averaged equations. The calculated limiting values of β for very slow waves, with Charnock's relation replaced by kz0 = constant, are close to those inferred from observation but about three times the limiting values obtained through extrapolation of Townsend's results.

42 citations


"The modulational instability in dee..." refers methods in this paper

  • ...Following Miles (1996), the coefficient β is given by the following expression: β = −π k (d2U/dz2)(zc) |(dU/dz)(zc)| w2(zc) U 21 (∂η/∂x) 2 , (2.10) where z = η(x) is the equation of the surface wave profile....

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Journal ArticleDOI
TL;DR: In this paper, a weakly nonlinear analysis is conducted to study the evolution of slowly varying wavepackets with small but finite amplitudes, that evolve at the interface between air and water under the effect of wind.
Abstract: A weakly nonlinear analysis is conducted to study the evolution of slowly varying wavepackets with small but finite amplitudes, that evolve at the interface between air and water under the effect of wind. In the inviscid assumption, wave envelopes are governed by cubic nonlinear Schrodinger or Davey-Stewartson equations forced by a linear term corresponding to Miles’ mechanism of wave generation. Under fair wind, it is shown that Stokes waves grow exponentially and that Benjamin-Feir instability becomes explosive.

41 citations


"The modulational instability in dee..." refers background or methods or result in this paper

  • ...In the regime we are considering, we have shown that the effect of the wind is contrary, as expected (Leblanc 2007)....

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  • ...Our aim is to extend the works of Segur et al. (2005a) and Leblanc (2007) who investigated this problem by considering damping and wind effects separately....

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  • ...To study the modulational stability of this solution we follow Segur et al. (2005a) and Leblanc (2007), and we superimpose to the solution (4.1) a small perturbation Ψ = Ψs(1 + δζ (ξ, τ )), (4.4) where δ 1....

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Frequently Asked Questions (10)
Q1. What contributions have the authors mentioned in the paper "The modulational instability in deep water under the action of wind and dissipation" ?

Kharif et al. this paper showed that when the amplitude of the sidebands can grow for a while and then oscillate in time, the region of instability shrinks as time increases. 

The evolution of a two-dimensional nonlinear wave train on deep water, in the absence of dissipative effects, exhibits the Fermi–Pasta–Ulam recurrence phenomenon. 

Since damping affects the modulational instability of waves in deep water, they assumed that it might affect the early development of rogue waves. 

For an energy flux to occur from the wind to the water waves, there must be a phase shift between the fluctuating pressure and the interface. 

The present paper is aimed at reporting on the behaviour of Benjamin–Feir instability when dissipation and wind input are both taken into account. 

In the presence of wind and dissipation, the unstable domain shrinks for low-frequency regime: this means that young waves are more sensitive to modulational instability than old waves. 

Email address for correspondence: kharif@irphe.univ-mrs.frnearly uniform wave trains become modulated and then demodulated until they are again nearly uniform. 

when the perturbations are small initially, they cannot grow large enough for nonlinear resonant interaction between the carrier and the sidebands to become important. 

Since Stokes (1847), it is well known that the potential water wave problem admits as solutions uniform wave trains of two-dimensional progressive waves. 

This situation was discussed by Segur et al. (2005a, see their comment (iii) p. 238), and it was claimed that even with substantial growth of the perturbation, the Stokes solution of (3.4) is still linearly stable: it is always possible to find a gap (denoted ∆) between unperturbed and perturbed solution that satisfies the linear stability criterion.