Characteristics of acoustic wave propagation in shal- low water are more complex than that of in the deep water, because the ups and downs of the bottom of res- ervoir are analogous with the water depth. Sound reflec- tion in underwater between surface and bottom is even more than deep water. Therefore, the shallowwater acoustic modeling is more difficult. This article dis- cusses the acoustic signal analysis method based on fractal, which can be used for forecasting or targeting an underwater artificial signal. Thereby, it will reduce the difficulty of establishing acoustic propagation model of shallowwaterenvironment.
Understanding of channel propagation characteristics is a key to the optimal design of underwater acoustic communication. Generally, modelling of underwater acoustic channel is performed based on measurement result in certain site at certain times. Different sites might have different characteristics, each of which can generally be described by a model obtained by averaging measurement results at multiple points in the same environment. This paper describes a characterization of the underwater acoustic channel of tropical shallowwater in a Mangrove estuary, which has sediment up to 60 cm at the bottom. Such a channel model is beneficial for the design of communication system in an autonomous underwater vehicle, for instance. The measurement result of delay spread parameter from three different points with the distance of 14 ~ 52 m, has various values. The root mean square (RMS) of delay spread ranges between 0.0621 ~ 0.264 ms, and the maximum delay spread varies with the value of 0.187 ~ 1.0 ms. The pdf fitting shows that Rayleigh distribution describes the fading variation more accurately than Nakagami and Ricean.
Fig. 1 One single ping received by the sonar in a shallowwaterenvironment. In structured environments, specular reflection commonly occurs since the boundaries are relatively smooth. When a beam of acoustic signals reaches the edges, most energy will reflect in the specular direction and only a small amount of energy will return to the source. Therefore, if a segment in a ping has low amplitude and spread in a short distance, it may be classified into boundary reverberation. In a similar vein, if a segment has high amplitude and spreads over a wide distance, it may be caused by an object. Fig. 2 compares the difference between the boundary reverberation and a real rigid sphere (18mm in diameter).
Quite recently the SPH solutions of the ShallowWater Equations (SWEs) are gaining increasing attention. This is due to the fact that most natural flow hazards happen over a relatively large space and the practical interest is to interpret these flow characteristics in the horizontal plane rather than the detailed information along the flow depth. In this sense, the vertical 2D or 3D SPH solutions based on the Navier-Stokes equations are computationally very demanding. Thus the SPH solutions of SWEs are expected to provide a more robust tool in view of the practical engineering interest. Since the concept of SWE-SPH was originally proposed by Wang and Shen (1999) in 1D dam break flow, it has been successfully applied in more complicated 2D dam break flows (De Leffe et al., 2010), open channel flows (Chang and Chang, 2013) and flooding simulations (Vacondio et al., 2012). Most existing SWE-SPH solutions are based on the variational approach proposed by Rodriguez-Paz and Bonet (2005) and adopted a one-step solution algorithm, that is to say, the particle columns are advected to their next positions using a single-step time integration. Thus the numerical scheme is fully explicit. In this sense, computational time steps must be strictly controlled to maintain the computational stability and accuracy. To improve the numerical performance of the SWE-SPH, which finds its potentials in practical engineering fields, in this work we will propose a two-step prediction/correction solution scheme for the SWE-SPH, similar to the two-step semi-implicit incompressible SPH solutions of Shao and Lo (2003), although the nature of numerical scheme is still explicit. The advantage of this new SWE-SPH solution algorithm is that slightly larger time steps can be used, as the continuity of the fluid system is imposed at the second step. Generally speaking, the overall computational efficiency has been improved. To tentatively test the proposed SWE-SPH model in horizontal 2D flows, the model is first applied to two benchmark water flow applications, including the dam break flow passing over a horizontal rectangular channel and through a steep U-shaped channel. Then by further combining with the sediment morph- dynamic equations, the sediment bed load movement
Except for the comparative study of zooplankton in the inshore coastal waters, oblique tows were made in collecting the plankton samples: bottom to surface in D'Entrecasteaux Channel and Derwent Estuary zooplankton studies and 50m to surface in shallowwater stations and 100m to surface in deep water stations in the East Coast water masses study . For the comparative study of zooplankton in the inshore coastal waters, a Simple closing net was used to collect plankton samples at required depth s .
In view of the above, it has become clear that an important addition to the Galewsky et al. (2004) and Polvani et al. (2004) benchmark solutions should consist of a numerical converged solution to the inviscid equations of motion in an appropriately defined time interval, over which sufficient nonlinearity and small-scale flow features develop, but over which solutions also remain sufficiently regular that a numerically converged inviscid solution may be obtained. Because of the tendency for rapid intensification of flow gradients in typical nonlinear flow fields, satisfying these two constraints turns out to be challenging, requiring computation at significantly higher resolutions than for the case of explicit diffusion. In the shallowwater system, which will form the focus of this paper, sufficient resolutions may be reached with relative ease on current computers. The primitive equation case appears significantly more demanding, both on account of the need to increase simultaneously both horizontal and vertical resolution, and because small-scale development is considerably more active by virtue of the nature of the dynamics at the horizontal boundaries (e.g. Juckes 1995; Scott 2011).
The genetic makeup of a population is heavily impacted by sexual selection. The selection of a mate is based on the beneficial outcome that results from mating with a certain individual. Females have to weigh the perceived benefits against any possible costs of mating with a specific male. Often female organisms can choose a male mate based on material gain such a food offering or a preferred trait that is most beneficial in a certain environment. The preferred trait can contribute to the survival rate of the female’s offspring. The benefit of this trait to the offspring may be stronger in certain environmental conditions than in others. Thus, the desired trait may differ completely according to the environmental conditions the offspring will encounter, causing a change in female preference. This preference can change the makeup of a population and it is important to understand the factors impacting the selection of a mate and what causes this preference to change.
When considering river flows with an essential lack of transversal velocity component, the obvious choice to calculate the discharge and the pollutant concentrations is to use a 1D shallowwater (SW) model. One dimensional schemes are still a practical tool for modeling river flows, in particular for simulations over extended time . For flow essentially 2D, of course, a fully 2D shallowwater model should be considered . In literature, exists a large amount of numerical models used for the solution of the systems of partial differential equations, they are traditionally based on finite element, finite difference or finite volume approximations in space and on implicit or explicit schemes in time . We adopt for the solution of the SW system a fractional step scheme in time and a finite element (FE) approximation in space [2, 15]. In particular, the choice of the fractional step afford, at every time step, to decouple the physical contributions so that waves traveling at speed of √gh can be calculated implicitly, with a low computational cost. In order to save computational time, moreover, the non-linear part of the momentum equation (and also the total derivative of the chemical pollutant transport equations) is solved using the characteristics method, so that the most onerous
The local well-posedness for the Cauchy problem of a nonlinear shallowwater equation is established. The wave-breaking mechanisms, global existence, and inﬁnite propagation speed of solutions to the equation are derived under certain assumptions. In addition, the eﬀects of coeﬃcients λ , β , a, b, and index k in the equation are illustrated.
The value of Electrical conductivity (EC) and Sodium adsorption ratio (SAR) values were plotted on US salinity diagram that in the zone of C2-S1, C3-S1 and C4-S1, salinity and sodicity of water were indicated by C and S respectively. Salinity of water indicate very high- salinity hazards (C4), high -salinity hazards (C3) Medium – salinity hazards (C2), and low sodium hazards (S1), Medium – sodium hazards (S2), High -sodium hazards (S3), and very –high sodium hazards through (S4). The calculated water samples of the shallow tub well was categorised in pre -monsoon and found 26.66 Percentage (%) (Table.3) of water samples are under very high – saline range sample no. 4, 12,14, 15 (Table.4) and category under (C4-S1), it’s not suitable for irrigation, another 73.33 percentage (%) (Table.3) shallow tube well water samples in pre- monsoon high saline range samples no. 1,2,3,5,6,7,8,9,10,11,13 (Table.4) and category (C3- S1),which required special management practices. Water samples of shallow tube well in post- monsoon 53.33 percentage (%) (Table.3) of samples under high saline range sample no.2,5,7,8,10.11,12,14 (Table.4) and category (C3-S1) its required few management . The remaining 46.66 percentage (%) (Table.3) of water samples are found medium – saline range, sample no. 1, 3, 4, 6, 9, 13, 15 (Table.4) and its categorised under (C2-S1), this rank of water samples suitable for irrigation purposes. The improvement of water quality was found after monsoon due to the rainwater and dissolved the ions concentration (Swati et al. 2012).
The incident wave power decreases in shallowwater because of energy losses due to seabed friction and wave breaking (Department of Energy 1992). The amount of energy lost depends on both the bathymetry and the wave characteristics. A gently shelving seabed will increase the amount of energy lost because of seabed friction due to the increased length over which there is significant water particle motion at the seabed creating shear. A rough and/or highly vegetated seabed will similarly increase the amount of energy lost. Energy losses due to seabed friction will also increase with large and long period waves because of increased water particle motion at the seabed. Signficant energy loss due to wave breaking occurs when the wave heights are greater than approximately 0.5 of the water depth and thus is uncommon except in very high-power seas or in very shallowwater.
Read et al.  reproduced multiple zonal jets on the β-plane in a convectively driven laboratory flow at the large-scale Coriolis facility, in Grenoble. They produced a turbulent flow gently and continuously spraying dense salty water onto the surface of a cylindrical tank (13m in diame- ter). The β-effect is obtained by means of a conically slop- ing bottom and the small deformations of the free surface due to the rotation. After several hours, they observed a zonally banded large-scale flow pattern (Fig. 4) characte- rized by spectral anisotropization. The flow has been iden- tified as marginally zonostrophic (R β = 0.5-2). From an
An operating surveying platform for bathymetry data acquisition in the shallowwater area, which is defined as an area having a depth less than 15 meters, is always considered to be a high operational risk due to limited navigation availability. The shipborne soundings commonly in use is a Singlebeam Echo Sounder System (SBES) that often produces a low spatial resolution (Lyzenga, et al., 2006; Kanno, et al., 2011). Hence, considering the limitation of the shipborne acquisition remotely sensed data technique, either the active technique (airborne) or the passive technique (space-borne) would be the best available option to be utilised instead. In addition, bathymetry data derived from the remote sensing platform is not something new for hydrographic application (Gould et al., 2001; Stumpf et al., 2003; Louchard et al., 2003; Brando and Dekker, 2003; Lyzenga et al., 2006; Albert and Gege, 2006; Su et al., 2008; Bachmann et al., 2012; Flener et al., 2012; Doxani et al., 2012; Bramante et al., 2013; Tang and Pradhan, 2015; Su et al., 2015; Vinayaraj et al., 2015; Guzinski et al., 2016; Toming et al., 2016; Jegat et al., 2016; Chybicki et al., 2018).
As can be seen from Figures 9 and 10, the transfer functions, obtained using our URANS approach, are in fairly good agreement with the related experimental results. The discrepancies between our numerical results and the experimental results are more pronounced at δ=1.2, which corresponds to the most shallowwater condition. Since the keel is very close to the sea bed in this condition, a much finer mesh may have been needed to better capture the hydrodynamic effects between the keel and the sea floor. Additionally, it is clearly visible from the figures that in both motion modes the potential flow panel methods over-predict the motion responses compared to the experiments. When the CFD results are compared to those obtained from the panel methods, it can be concluded that the CFD method predicts the motion responses much better than potential flow theory, particularly for pitch motion. It should be mentioned that the differences between the experimental results and the panel methods may stem from the coarse panel generation and the assumptions made in the potential flow theory. It should also be borne in mind that the most recently developed 3-D potential flow theory-based codes, such as the Rankine source panel methods, may give more successful motion predictions than those presented in this paper.
From the previous test, it is proven that the modified 2D RKDG2 scheme can provide satisfactorily agreeable solution over a flat and frictionless topography. In this second test, the modified 2D RKDG2 scheme is further tested to assess its ability in preserving the well-balanced property over a frictionless uneven topography. This involves simulating a still water flow in a 75 m × 30 m confined pool while resolving three different flow cases involving the presence of a wet/dry front (the peak of the hump is above water surface), a critically wet (h = 0 at the peak), and a fully wet topography (the peak is submerged underwater). The full 2D topography approximation is illustrated in Figure 3 and described in Eq. (7):
Meanwhile, we also present the numerical results from CFD simulation. The simulations are carried out using the commercial CFD software StarCCM+ developed by CD-Adapco. An unsteady RANS approach is applied, using the Realizable Two-Layer k-ε turbulence model. The free surface is simulated using the Volume of Fluid (VoF) surface capturing method, and the calm water is simulated using a flat wave. In order to simulate the sinkage and trim of KVLCC2 a Dynamic Fluid Body Interaction (DFBI) approach is applied, with the vessel free to translate in the z direction (sinkage) and rotate about the y axis (trim). As the motions are expected to be small, no additional meshing approaches are applied. For comparison purposes, the same simulations are also carried out with the vessel static at even keel.
Various dynamic properties for Eq. () have been acquired by many scholars. Escher et al.  and Yin  studied the global weak solutions and blow-up structures for Eq. (), while the blow-up structure for a generalized periodic Degasperis-Procesi equation was obtained in . Lin and Liu  established the stability of peakons for Eq. () under certain assumptions on the initial value. For other dynamic properties of the Degasperis-Procesi () and other shallowwater models, the reader is referred to [–] and the references therein.