CN111783368A - Method for simulating physical parameters of shallow seawater - Google Patents
Method for simulating physical parameters of shallow seawater Download PDFInfo
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- CN111783368A CN111783368A CN202010678064.2A CN202010678064A CN111783368A CN 111783368 A CN111783368 A CN 111783368A CN 202010678064 A CN202010678064 A CN 202010678064A CN 111783368 A CN111783368 A CN 111783368A
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Abstract
The invention provides a seawater physical parameter simulation method based on combination of a smooth Particle Hydrodynamics algorithm (SPH method for short hereinafter) and a Gerstner wave sea surface simulation method (Gerstner method for short hereinafter), which uses the Gerstner method to generate initial seawater particles (the seawater particles do not refer to a single water molecule or a substance consisting of a plurality of water molecules, but the seawater in a certain volume is regarded as a whole from a macroscopic angle), ensures that the seawater particles accord with common sense distribution, then uses a density estimation algorithm in the SPH method, considers the influence of an action range (namely a smooth core and a smooth radius), and combines the Particle distribution with the density of a certain point of the seawater from a physical angle. By utilizing the method, a complex and various seawater speed or density distribution model can be theoretically simulated, and data support basically consistent with the reality is provided for the research in the aspects of geophysical field simulation and the like.
Description
Technical Field
The invention relates to the technical field of wave field simulation, in particular to a method for simulating physical parameters of shallow seawater.
Background
In the previous research, researchers usually set parameters such as the speed of seawater to a fixed value to simulate the geophysical field, and although the propagation mode of the wave field in the seawater can be simulated, the influence of seawater fluctuation on the numerical simulation is not considered. And the other disadvantage of setting the seawater speed as a fixed value is the model unicity, and the test can be only carried out by changing the size and the boundary of the sound wave speed, so that the complicated and various seawater physical parameters under the real condition can not be simulated.
In order to solve the problem, the invention designs a model capable of generating the sound wave velocity and density parameter distribution of the complex shallow seawater by combining the SPH method and the Gerstner wave method, and the specific background technology is as follows.
In both the chemical and the micro-physical fields, there is a relationship between micro-particles and macro-mass, which means that from the point of view of particle motion, macro-physical parameters can be estimated in some way.
The Gerstner model was first introduced in 1986 by Fournier et al in the field of computer graphics processing, and it primarily describes, from a kinetic perspective, the state of motion of individual particles on the sea surface.
The basic idea of Gerstner waves is to consider the movement of seawater as the movement of water particles, and in non-offshore ocean locations, the movement of water particles can be regarded as circular (spherical in three dimensions), so that all water particles are displayed in a set, and the sea surface can be effectively simulated. Since the Gerstner wave describes particle motion, the basic formula describing the wave is written as a parametric equation. For the Gerstner wave, it creates a concentration of particles in the peak of the wave, i.e., it is more consistent to see a sharp peak as the wave progresses. In practice this is similar to a wave in a real large water depth environment.
The core of SPH is the smooth nucleus. The particles will always interact with their surrounding particles during their movement, and this action has a powerful effect, also including chemical actions of various kinds, and the range of this effect is called the smooth kernel, which is usually a circle or a sphere, so the radius of this geometry is the smooth kernel radius, which represents the maximum radius of influence of the particle.
Although in the SPH algorithm the fluid is considered as individually dispersed particles, in practice the fluid is continuous and if calculations are to be made from the particles, it must be considered that the contributions of all relevant particles at a certain point are combined to be the calculated value at this point.
Imagine the presence of a point in a fluid
(of course there is not necessarily a particle in this place), there are several particles within the smooth core radius h, and their corresponding positions are respectively
Then the cumulative formula for a certain attribute X at this point is:
x in the formulajFor certain attributes to be accumulated, mj，ρjAs to the mass and density of the surrounding particles,
for the position of the particle, h is the smooth kernel radius, and the function W is the smooth kernel function.
In order to generate a velocity model that is consistent with the actual velocity, the present invention combines the above two methods to generate a model.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
Therefore, the invention aims to provide a method for simulating physical parameters of shallow seawater, which can improve the operation efficiency, simulate various complex seawater speed or density distribution models and provide data support basically consistent with the actual conditions for researches in the aspects of geophysical field simulation and the like.
To solve the above technical problem, according to an aspect of the present invention, the present invention provides the following technical solutions:
a method of shallow seawater physical parameter simulation, comprising: the method comprises the following steps:
the method comprises the following steps: generating a random fluid particle distribution using a Gerstner wave method;
step two: setting an attenuation function;
step three: calculating the physical parameter value of each grid point by using an SPH method point by point;
step four: obtaining the data before boundary removal of the density distribution of the shallow seawater, obtaining the density distribution by removing the boundary effect, and obtaining the acoustic velocity distribution data of the shallow seawater by using the density distribution data, neglecting the pressure change of the shallow seawater and through an empirical calculation formula of the acoustic velocity of the seawater.
As a preferred embodiment of the method for simulating physical parameters of shallow seawater according to the present invention, wherein: the method comprises the following steps: the sea surface morphology is displayed by the distribution of the fluid particles, and a random phase adding mode is adopted during generation, so that the model is more consistent with common knowledge.
As a preferred embodiment of the method for simulating physical parameters of shallow seawater according to the present invention, wherein: step two: and setting an attenuation function and selecting an inverse proportional function for attenuation.
As a preferred embodiment of the method for simulating physical parameters of shallow seawater according to the present invention, wherein: step three: the physical parameter calculated is the average value in the smooth kernel range.
Compared with the prior art, the method has the advantages that initial seawater particles are generated by using a Gerstner method (the seawater particles do not refer to a single water molecule or a substance consisting of a plurality of water molecules, but the seawater in a certain volume is regarded as a whole from a macroscopic angle), the seawater particles are guaranteed to be in accordance with common sense distribution, then the influence of an action range (namely a smooth core and a smooth radius) is considered by using a density estimation algorithm in an SPH method, the particle distribution and the density at a certain point of the seawater are combined from a physical angle, the operation efficiency is improved, a complex and various seawater speed or density distribution model is simulated, and data support basically in accordance with the reality is provided for researches in the aspects of geophysical field simulation and the like.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail with reference to the accompanying drawings and detailed embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise. Wherein:
FIG. 1 is a simulation flow chart of the present invention;
FIG. 2 is a diagram of a Gerstner basic waveform of the present invention;
FIG. 3 is a morphogram of a lubricious core of the present invention;
FIG. 4 is a simulated seawater density distribution plot for a wind speed of 8 units according to the present invention;
FIG. 5 is a simulated sea water sound velocity distribution diagram when the wind speed is 8 units according to the present invention;
FIG. 6 is a simulated (small) diagram of the sound wave velocity distribution of seawater at a wind speed of 15 units according to the present invention;
FIG. 7 is a simulated (enlarged) diagram of the sound wave velocity distribution of seawater at a wind speed of 15 units according to the present invention;
fig. 8 is a diagram of the simulated sea water sound wave velocity distribution (including sea surface fluctuation) when the wind speed is 20 units.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and it will be apparent to those of ordinary skill in the art that the present invention may be practiced without departing from the spirit and scope of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Next, the present invention will be described in detail with reference to the drawings, wherein for convenience of illustration, the cross-sectional view of the device structure is not enlarged partially according to the general scale, and the drawings are only examples, which should not limit the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The invention provides a method for simulating physical parameters of shallow seawater, which can improve the operation efficiency, simulate various complex seawater speed or density distribution models, and provide data support basically consistent with the reality for the research in the aspects of geophysical field simulation and the like, please refer to fig. 1-8, and the method comprises the following steps:
the method comprises the following steps: the Gerstner wave method is used for generating random fluid particle distribution, the Gerstner wave is a gravity wave in a mathematical description meaning, so that sea surface morphology can be basically displayed, and a random phase adding form is adopted during generation, so that the model is more consistent with common knowledge. The Gerstner wave is generated through a parameter equation, and the position of each water particle is calculated, so that the sea surface fluctuation condition is obtained;
step two: giving an attenuation function, assuming that the seawater energy is attenuated according to a certain rule from top to bottom, which is the key for converting the water surface to the water body, wherein an inverse proportion function is selected for attenuation, namely the rule that the energy is reduced along with the depth is the change rule of the inverse proportion function;
step three: the physical parameter value of each grid point is calculated point by using an SPH method, and in the SPH method, a method for calculating the physical parameter by using water particle distribution is given. It is worth mentioning that there is not necessarily a particle at each grid point, i.e. the physical parameter calculated is simply an average value in the smooth kernel range. During calculation, a density calculation formula in an SPH method is utilized;
step four: obtaining the data before boundary removal of the density distribution of the shallow seawater, obtaining the density distribution by removing the boundary effect, neglecting the pressure change of the shallow seawater by using the density distribution data, obtaining the sound wave velocity distribution data of the shallow seawater by using a seawater sound wave velocity empirical calculation formula, wherein the sound wave calculation is calculated by using the empirical formula commonly used in the ocean science, and the pressure is regarded as a constant value (the assumption is made because of the shallow seawater).
To better illustrate the effects of the above embodiments, a specific example is given below:
example (c): assuming that the wind speed in a certain sea area is 8 units and 15 units (the grid interval is set to be 0.1m × 0.1m), the method is used for programming calculation, the grid size is set to be 100 × 100, after the boundary clipping processing, the obtained grid size is 42 × 37, and through an empirical calculation formula of density to sound wave speed, the sound wave speed distribution can be obtained, and the simulation process is as shown in fig. 1. The density distribution of 8 unit wind speeds is shown in fig. 4, the sound velocity distribution of 8 unit wind speeds is shown in fig. 5, the sound velocity distribution of 15 unit wind speeds is shown in fig. 6, the sound velocity enlarged view of 15 unit wind speeds is shown in fig. 7, and the model containing the undulating sea surface is shown in fig. 8. (all abscissas in the figure represent lateral extent and the ordinates represent longitudinal depth).
While the invention has been described above with reference to an embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the various features of the disclosed embodiments of the invention may be used in any combination, provided that no structural conflict exists, and the combinations are not exhaustively described in this specification merely for the sake of brevity and resource conservation. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (4)
1. A method for simulating physical parameters of shallow seawater is characterized by comprising the following steps:
the method comprises the following steps: generating a random fluid particle distribution using a Gerstner wave method;
step two: setting an attenuation function;
step three: calculating the physical parameter value of each grid point by using an SPH method point by point;
step four: obtaining the data before boundary removal of the density distribution of the shallow seawater, obtaining the density distribution by removing the boundary effect, and obtaining the acoustic velocity distribution data of the shallow seawater by using the density distribution data, neglecting the pressure change of the shallow seawater and through an empirical calculation formula of the acoustic velocity of the seawater.
2. The method for simulating physical parameters of shallow seawater according to claim 1, wherein the first step comprises: the sea surface morphology is displayed by the distribution of the fluid particles, and a random phase adding mode is adopted during generation, so that the model is more consistent with common knowledge.
3. The method for simulating physical parameters of shallow seawater according to claim 1, wherein the second step comprises: and setting an attenuation function and selecting an inverse proportional function for attenuation.
4. The method for simulating physical parameters of shallow seawater according to claim 1, wherein the third step comprises: the physical parameter calculated is the average value in the smooth kernel range.
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| CN101329772A (en) * | 2008-07-21 | 2008-12-24 | 北京理工大学 | Emulation modelling method interacted with movable object and water based on SPH |
| CN102789650A (en) * | 2012-07-19 | 2012-11-21 | 中国科学院软件研究所 | Sea surface track parallel simulation method based on particle system |
| CN102930583A (en) * | 2012-10-17 | 2013-02-13 | 中国科学院自动化研究所 | Method for interactively generating droplet effect |
| CN110598283A (en) * | 2019-08-29 | 2019-12-20 | 江苏大学 | Fluid simulation method based on SPH kernel function |
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Patent Citations (4)
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| CN101329772A (en) * | 2008-07-21 | 2008-12-24 | 北京理工大学 | Emulation modelling method interacted with movable object and water based on SPH |
| CN102789650A (en) * | 2012-07-19 | 2012-11-21 | 中国科学院软件研究所 | Sea surface track parallel simulation method based on particle system |
| CN102930583A (en) * | 2012-10-17 | 2013-02-13 | 中国科学院自动化研究所 | Method for interactively generating droplet effect |
| CN110598283A (en) * | 2019-08-29 | 2019-12-20 | 江苏大学 | Fluid simulation method based on SPH kernel function |
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