KR101668073B1 - Method and system for analyzing wave data in coastal areas - Google Patents

Abstract

According to another aspect of the present invention, there is provided a system for analyzing coastal zone wave information, comprising: a data collection module for collecting weather data including wind velocity, wind direction and wave height of an offshore wind; An external analysis module for analyzing the wave height, the wave period and the wave direction of the external sea using the gas phase data as an input value; A heuristic analysis module for analyzing extreme values of wave height, wave period, and wave direction using the values analyzed in the external analysis module as input values; And a port analysis module that divides the ports to be analyzed into a plurality of grids and analyzes the extreme values of the peaks for each grid using the extreme value analyzed by the depth analysis module as an input value.

Description

METHOD AND SYSTEM FOR ANALYZING WAVE DATA IN COASTAL AREAS BACKGROUND OF THE INVENTION [0001]

The present invention relates to a method and system for analyzing coastal waters information, and more particularly, to a method and system for analyzing coastal waters information of coastal waters. More particularly, To a method and system for calculating extreme values.

Coastal disasters, such as coastal structures, coastal flooding, oil pollution accidents, etc., are deeply related to sea conditions and seawater flow. Therefore, accurate prediction of sea level and velocity in the coastal waters is very important in the search structure and estimation of oil spill in coastal protection and marine accidents as well as in the marine industry. The flow of seawater is a result of complex action of various factors such as periodic astronomy, storm surge, tsunami, low pressure, It is also not easy to construct long-term measurements of sea conditions such as crusting, wave crushing, storm surges, tides, and tidal currents in all waters.

On the other hand, after the cutting, assembling and design work of the outer shape of the ship is completed, the ship can be launched in the port and the work such as construction of the upper structure can be carried out while moored. In this case, when a wave height of unexpected height occurs, the ship may be rolled over or damaged.

In order to prevent such a problem, it is necessary to calculate a maximum expected wave height based on past weather data, and then to prevent damage to the ship even if the wave of the maximum height affects the ship. However, if there is no preliminary weather data available at the port where the ship is moored, it is almost impossible to predict the future weather environment at present.

Accordingly, the present invention proposes a method for analyzing the weather environment data that can be generated by the reproduction cycle in a specific port by using the numerical model technique, high quality weather information and blue observation data.

It is to be understood that the description described as the background of the above-mentioned invention is merely for enhancing the understanding of the background of the present invention, and it is accepted that it corresponds to the prior art already known to those having ordinary skill in the art It should not be accepted.

It is an object of the present invention to provide a method for analyzing wave information of coastal regions, a system used therein, and a computer-readable recording medium capable of storing the generated analysis data. More specifically, it is an object of the present invention to provide a technique for collecting meteorological data of an offshore area and then analyzing extreme value of a wave in a specific port through a numerical model to output related meteorological data.

According to the present invention, the above object is achieved by a coastal state geographic information analysis system, comprising: a data collection module for collecting weather data including wind velocity, wind direction and wave height of an offshore; An external analysis module for analyzing the wave height, the wave period and the wave direction of the external sea using the gas phase data as an input value; A heuristic analysis module for analyzing extreme values of wave height, wave period, and wave direction using the values analyzed in the external analysis module as input values; And an intra-harvest analysis module that analyzes the extreme value of the digging for each of the lattices by dividing the port to be analyzed into a plurality of grids and using the extreme value analyzed by the depth analysis module as an input value .

Here, the data collection module collects meteorological data during typhoon and non-typhoon, and the extrapolation analysis module, the depth analysis module and the intra-port analysis module can analyze extreme values of typhoons and typhoons have.

Here, the data collection module collects meteorological data in a plurality of periods, and the depth analysis module, the depth analysis module and the intra-port analysis module can analyze the extreme value of the digging in each cycle.

Here, the external analysis module uses a WAM model, the inferior analysis module uses a SWAN (Simulated Waves Nearshore) model, and the intra-port analysis module uses the Boussinesq-2D model to analyze each analysis value Can be output.

According to another aspect of the present invention, there is provided a method for analyzing coastal area information, comprising: a data collection step of collecting weather data including wind velocity, wind direction and wave height of an offshore sea; Analyzing an extreme value of an extreme wave, a wave period, and an extreme wave with the gas phase data as an input value; An inferiority analysis step of analyzing extreme values of wave height, wave period, and wave direction of the deep sea using the extreme value analyzed in the above-mentioned external analysis step as an input value; And analyzing the extreme values of the peaks for each grid by dividing the port to be analyzed into a plurality of grids and using the extreme value analyzed in the depth analysis step as an input value .

Here, the data collection step collects meteorological data at the time of typhoon and non-typhoon, and the extreme values of the digging can be analyzed by classifying the time of the typhoon and the typhoon, have.

Here, the data collection step collects meteorological data in a plurality of period units, and the extraneous water analysis step, the depth analysis step and the intra-port analysis step can analyze the extreme value of the wave height in each cycle unit.

In this case, the WAM model (wave model) is used for the external analysis step, the SWAN (Simulated Waves Nearshore) model is used for the depth analysis step, and the analytical value of each port is analyzed using the Boussinesq- Can be output.

According to the present invention, it is possible to provide a method of analyzing wave information of coastal regions, a system used therein, and a computer-readable recording medium capable of storing the generated analysis data. More specifically, it is possible to provide a technique of outputting relevant weather data by analyzing the extreme value of the wave height of a specific port through a numerical model after collecting weather data of the offshore.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of a coastal geographic information analysis system according to an embodiment of the present invention; FIG.
FIG. 2 is a schematic view illustrating a process of extracting meteorological data of a port from meteorological data of an offshore area by using a coastal waters information analysis system according to an embodiment of the present invention.
FIG. 3 illustrates an analysis result in the Jaffa port using a heuristic analysis module (SWAN).
Fig. 4 illustrates the results of the analysis in the term of the Octopus using the port analysis module (BOUSS-2D).
FIG. 5 is a flowchart of a method for analyzing coastal geographical information according to an embodiment of the present invention.

It is noted that the technical terms used herein are used only to describe specific embodiments and are not intended to limit the invention. It is also to be understood that the technical terms used herein are to be interpreted in a sense generally understood by a person skilled in the art to which the present invention belongs, Should not be construed to mean, or be interpreted in an excessively reduced sense. Further, when a technical term used herein is an erroneous technical term that does not accurately express the spirit of the present invention, it should be understood that technical terms that can be understood by a person skilled in the art are replaced. In addition, the general terms used in the present invention should be interpreted according to a predefined or prior context, and should not be construed as being excessively reduced.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals refer to like or similar elements throughout the several views, and redundant description thereof will be omitted. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. It is to be noted that the accompanying drawings are only for the purpose of facilitating understanding of the present invention, and should not be construed as limiting the scope of the present invention with reference to the accompanying drawings. The spirit of the present invention should be construed as extending to all modifications, equivalents, and alternatives in addition to the appended drawings.

FIG. 1 is a block diagram of a coastal geographic information analysis system 100 according to an embodiment of the present invention.

As shown, the coastal state geographic information analysis system 100 may include a data acquisition module 110, an external ocean analysis module 120, a heuristic analysis module 130 and a port analysis module 140, Even if some of the configurations are omitted or replaced, there is no problem in implementing the idea of the present invention.

The coastal waters wave information analysis system (100) is a numerical analysis model applicable to the coastal and harbor bases, and basically can calculate physical effects such as wave refraction, shore water, and breaking waves. The coastal state geological information analysis system 100 can calculate the wave development and propagation in the external analysis module, the refraction in the depth analysis module, the diffraction and reflection in the port analysis module, and the dynamic nesting It is possible to reproduce the oceanography of the area of interest more precisely.

On the other hand, the coastal waters information analysis system 100 can acquire analysis data in a specific port, such as wind and wave, based on the weather data acquired in the offshore region. In addition, after receiving meteorological data of the outer sea for each predetermined reproduction cycle (for example, one year, 10 years, 20 years, 50 years, 100 years, etc.), the extreme value of the wave height in each lattice in the harbor Extreme values can be extracted by distinguishing between when the typhoon occurred and when it did not.

Hereinafter, each configuration of the coastal navigation information analysis system 100 according to an exemplary embodiment of the present invention will be described in detail.

The data collection module 110 collects weather data of the offshore area. At this time, it is possible to collect information about the wind speed, the wind direction, and the wave height at a specific area of at least the outer sea.

In the present specification, the external sea can mean a place where the weather data such as the wind speed, the wind direction, and the wave height are accumulated for a long time (for example, 50 years or more) by a predetermined distance or more . For example, if the system 100 is to extract data in Jaffa Port located in Geoje City, Gyeongnam, the data collection module 110 may use the weather data measured in the East Sea, Namhae, or Korea Strait several tens to several hundred km away from Jaffa Port Data can be collected.

The data collection module 110 can provide the weather data classified into the non-typhoon mode and the typhoon mode. In the non-typhoon mode, the wind data of the ECMWF is reviewed to select wind data suitable for the Korean peninsula. (ECMWF and JMA climate model data, Korea / China / Japan ground observation data, satellite exploration data, aircraft data, etc.), and the distribution of sea surface pressure and wind rapidly changes in the vicinity of the center of the typhoon. And so on).

Assuming that the number of typhoons that have influenced a specific port (for example, Okpo Port) in the last 50 years is 100, the data collection module 110 collects the wind speed, the wind direction and the peak value for 100 hours for each typhoon, A total of 10,000 hours of data can be collected. In the case of non-typhoon, ECMWF can collect data for 6-hour intervals over 35 years.

The coastal country ground wave information analysis system 100 according to the present invention is a system for analyzing coastal area information of a coastal country based on meteorological data of an outer sea using a numerical model when meteorological data accumulated in an outer sea exist, It is possible to generate weather data of the harbor.

2, when there is no weather data constructed in the last 50 years in a specific port (for example, Geoje-ok Pohang, Gyeongsangnam-do), there is no weather data outside a certain sea (for example, one area of the South Sea) Based on the collected weather data, a wave value is calculated using the external analysis module 120 (e.g., WAM), and the wave analysis module 130 (e.g., SWAN) The extreme value of the meteorological data including the wave height in the harbor can be calculated using the in-house analysis module (for example, Bouss-2D) based on the extreme value of the sea level.

Hereinafter, a process for calculating the extreme value of the wave height in the harbor using the analysis module 120, the analysis module 130 and the analysis module 140 based on the data collected by the data collection module 110 The description will be made in more detail with respect to an embodiment using a known numerical model.

The external analysis module 120 receives the weather data collected by the data collection module 110, and analyzes the values of the external sea wave, the wave period, and the wave direction using the received weather data. The coastal state geological information analysis system 100 according to the present invention can distinguish the typhoon time and the non-typhoon time and calculate the extreme value by each reproduction cycle (1 year, 2 years, 10 years, 50 years, 100 years, etc.) In the case of a typhoon, the offshore analysis module 120 calculates the extreme value 5 of the wave height and the extreme value 5 of the wave period based on the data of 10000 hours collected (data collected for 100 hours for 100 storms) , And five extreme values of the wave direction can be output.

The offshore analysis module 120 can use the deep sea wave model WAM. WAM is the first three-generation wave model developed by Hasselman et al. (1988). It simulates the input of wind energy, the attenuation of the ground wave, and the quadruplet wave interaction through the source term, And the wave propagation, refraction, and flow effects of the wave spectrum can be taken into account.

The governing equation of WAM can be written as:

[Equation 1]

Where F (λ, φ, wr, θ) is the wave energy spectrum. (λ is the longitude, φ is the latitude, w _r is the relative frequency, θ is the direction of the spectrum)

Also, c _λ , c _φ , c _θ can be calculated as follows.

&Quot; (2) "

(Where R is the radius of the earth and c _g is the velocity of the earth)

In addition, S can be defined as the sum of the following values as a source function.

&Quot; (3) "

(S _in the energy input by the wind, S _ds energy attenuation by whitecap, S _nl4 is SAFA nonlinear interaction, S _nl3 is sampa nonlinear interaction, S _bf is wave energy attenuation caused by the ground friction, S _br is the Surf Wave energy attenuation)

The off-axis analysis module 120 can calculate the extreme value for the entire simulation period in the 1/12-degree and 1/60-degree grids.

The depth analysis module 120 may output the peaking, wave period, and direction in the outer sea using the above-described governing equations and topographic information to the collected weather data, Lt; / RTI >

Meanwhile, the process of outputting the governing equations and extreme values of the above-described external analysis module 120 may be implemented by a technique of analyzing the blue data of the ocean such as the WAM model.

The light intensity analysis module 130 analyzes extreme values of wave height, wave period, and wave direction corresponding to the boundary with the port to be analyzed, using the extreme values analyzed in the depth analysis module 120 as input values. Herein, the offshore area is located at a predetermined distance or more (for example, several to several tens of kilometers) from the boundary between the port to be analyzed and the sea, and corresponds to one of the middle points between the port and the above-

The light intensity analysis module 130 can use SWAN (Simulating Wave Nearshore), which is a coastal wave module. SWAN is a wave deformation numerical model that utilizes the spectrum action balance equation and is frequently used to calculate the wave of the coastal zone, lake, and estuaries from the wave spectrum at a given incident boundary, wind and sea floor conditions, and ocean current conditions.

SWAN reflects the movement of the wave in the wave propagation process, the refraction and the water effect by the depth and the flow, the transmission by the constraint factors such as the island and the island, the blocking, the reflection, and the diffraction phenomenon. In addition, consideration is given to the generation of wave energy by wind, wave energy dissipation by back wave, wave energy dissipation by breaking wave due to water depth reduction, wave energy dissipation due to bottom friction, and wave nonlinear interaction. It also applies to places where the process of deformation of the waves is indicated.

The development of the wave spectrum can be calculated by the following wave equilibrium equations.

&Quot; (4) "

Here, the first term of the left side shows the time variation of the wave action spectrum, the second and third waves propagate the wave in the geographic space, the fourth wave shows the transition of the relative frequency due to the change of the water depth and the flow, Lt; / RTI >

The wave propagation speed by the linear wave theory is as follows

&Quot; (5) "

Here, s and m are coordinates which are perpendicular to the wave line and wave line, respectively. The right-hand side of the equilibrium equation represents the source and dissipation, which may include the generation, dissipation of energy, and energy transfer by nonlinear interaction.

In Equation (4), S can be expressed by the following formula.

&Quot; (6) "

Where S _in is the energy input by the wind, S _ds is the dissipation of the wave energy, and S _nl is the nonlinear wave interaction.

FIG. 3 illustrates an analysis result in Jaffa using the heuristic analysis module 130 (SWAN).

The heaviness analysis module 130 uses the additional information such as the wave equilibrium equilibrium equation and the geographical information as described above to the value output from the depth analysis module 120, Year, 100 years), it is possible to output the peak value of 5 waves in the shallow sea, the extreme value of the wave period, and the extreme value of the wave direction, which will be input values of the port analysis module 140 .

Meanwhile, the process of outputting the governing equation and extreme value of the above-described light intensity analysis module 130 may be implemented by a technique of analyzing the wave data of the deep sea such as the SWAN model.

The port analysis module 140 analyzes the extreme value of the wave height in the port by using the extreme value analyzed in the depth analysis module 130 as an input value and outputs the final result data of the coastal state ground wave information analysis system 100 Function.

First, the port analysis module 140 divides the analysis target area into a plurality of grids. When dividing into lattices, each lattice can be divided into a regular size (about 50 m) square, and a checkerboard regular lattice can be generated.

The port analysis module 140 can generate weather data including extreme value of wave height for each grid that is separated.

The harbor analysis module 140 can use the BOUSS-2D model, a comprehensive numerical model for simulating the transmission and deformation of waveforms in offshore areas and harbors based on the time domain analysis of the Boussinesq equation.

The BOUSS-2D model is based on the Boussinesq equation as a wave model applied in the harbor. It is an equation that integrates the mass conservation equation and the momentum conservation equation by the nonlinear wave propagation at the shallow sea and the middle water depth. The BOUSS-2D model simulates the effect of breaking waves on the wave flow in the waveband and can construct the equations of motion by considering the energy attenuation by the turbulent boundary layer at the bottom.

In BOUSS-2D model, when two waves whose amplitudes are α1 and α2 and whose frequency is ω2, ω2, and wave number is k1, k2 proceed in the direction of θ1, θ2, the sea surface elevation can be expressed as follows.

&Quot; (7) "

In addition to Equation (7), the respective equations of motion and the like used in the BOUSS-2D model may be the same as those already known.

FIG. 4 illustrates the results of the analysis in the term of the Octopus using the port analysis module 140 (BOUSS-2D).

In this way, the coastal waters analysis information analysis system 100 analyzes the coastal waters information analysis system 100 according to the reproduction cycle (1 year, 1 year, and 1 year) at the positions corresponding to the respective lattices of the analysis target sea area during the typhoon and non- 2 years, 10 years, 50 years, 100 years).

That is, even if the weather data in the analysis target area is not collected in advance, the weather data in the external sea is nested by the numerical model to confirm the extreme value of the wave height in the analysis target area where the weather data does not exist .

As a result of the analysis of the coastal waters wave information analysis system 100 as described above, extreme values of eight directions (N, NE, E, SE, S, SW, W, and NW) Can be confirmed by the reproduction cycle. Also, in the case of non-typhoon, it is possible to confirm the value of monthly total azimuth by each reproduction cycle.

Meanwhile, the coastal state geographic information analysis system 100 according to the present invention applies the least squares method, the normal moment method, and the parameter estimation method of the probability weighted method to the extreme statistical models of the Gumbel model, the Weibull model, and the GEV The extreme value can be obtained, and reliability of the extreme value can be secured through the probability method, the χ2 test, and the Kolmogorov-Smirnov test.

FIG. 5 is a flowchart of a method for analyzing coastal geographical information according to an embodiment of the present invention.

The illustrated method can be performed by the coastal waters information analysis system described above, and the description of the technical features described above will be omitted.

First, the coastal waters wave information analysis system collects weather data including the wind velocity, wind direction and wave height of the offshore sea (S11). At this time, weather data can be provided separately in non-typhoon mode and typhoon mode. Assuming that the number of typhoons that have influenced a specific port (for example, Okpo Port) in the last 50 years is 100, Wind speed, wind direction and peak value during the period can be collected and a total of 10000 hours of data can be collected. In the case of non-typhoon, ECMWF can collect data for 6-hour intervals over 35 years.

Next, the coastal waters wave information analysis system analyzes the extreme value of the digging, wave period, and wave direction of the offshore by using the collected weather data as an input value (S12).

The extreme value can be calculated for each repetition cycle (1 year, 2 years, 10 years, 50 years, 100 years, etc.) by dividing the typhoon and non-typhoon times. In case of typhoon, Based on the data (data collected for 100 hours for 100 typhoons), it is possible to output 5 extreme values of wave height, 5 extreme values of wave period, and 5 extreme values of wave direction.

In this step, the deep sea wave model WAM can be used, as described above.

Next, the coastal waters wave information analysis system analyzes extreme value of wave height, wave period, and wave direction using the extreme value analyzed in the external analysis stage as an input value (S13). At this time, five extreme values of wave height in the shallow sea, five extreme values of the wave period, and five extreme values of the wave in each recurrence cycle (1 year, 2 years, 10 years, 50 years, 100 years) Can be output.

In this step, SWAN (Simulating Wave Nearshore), a coastal wave module, can be used, as described above.

Next, the coastal waters wave information analysis system divides the port to be analyzed into a plurality of grids, and analyzes the extreme value of the wave height for each grid using the extreme values analyzed in the depth analysis step (S14).

In this step, when the analysis target sea area is divided into each grid, it is possible to generate a checkerboard regular grid by dividing each grid into a predetermined size (about 50 m) square.

In this step, we can use the BOUSS-2D model, a comprehensive numerical model for simulating the transmission and deformation of waveforms in offshore areas and harbors based on the time domain analysis of the Boussinesq equation, as described above.

As a result of performing the method of analyzing the information of the coastal terrain wave information according to the present invention, the extreme values of the eight directions (N, NE, E, SE, S, SW, W, and NW) Can be confirmed by the repetition cycle. In the case of non-typhoon, it is also possible to confirm the value of the monthly total azimuth by each reproduction cycle.

Meanwhile, the concept of the present invention can be embodied as a computer-readable recording medium for storing data generated by the above-described coastal state geographic information analysis method. It may also be embodied as a computer-readable recording medium including instructions for performing the steps described above. Here, the computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter that affects the machine readable propagation type signal, or a combination of one or more of the foregoing.

Implementations of the functional operations and the subject matter described herein may be implemented in digital electronic circuitry, or may be implemented in computer software, firmware, or hardware, including the structures disclosed herein, and structural equivalents thereof, It can be implemented. Implementations of the subject matter described herein may be implemented as one or more computer program products, i. E. One or more modules relating to computer program instructions encoded on a type of program storage medium for execution by, or control of, the operation of the processing system Can be implemented.

A computer program (also known as a program, software, software application, script or code) may be written in any form of programming language, including compiled or interpreted language, a priori or procedural language, Components, subroutines, or other units suitable for use in a computer environment. A computer program does not necessarily correspond to a file in the file system. The program may be stored in a single file provided to the requested program, or in multiple interactive files (e.g., a file storing one or more modules, subprograms, or portions of code) (E.g., one or more scripts stored in a markup language document). A computer program may be deployed to run on multiple computers or on one computer, located on a single site or distributed across multiple sites and interconnected by a communications network.

On the other hand, computer readable media suitable for storing computer program instructions and data include semiconductor memory devices such as, for example, EPROM, EEPROM and flash memory devices, such as magnetic disks such as internal hard disks or external disks, Non-volatile memory, media and memory devices, including ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuits.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

100: Coastal Information System
110: Data acquisition module
120: external analysis module
130: Weather analysis module
140: Port Analysis Module

Claims (10)

In coastal geographic information analysis systems,
A data collection module for collecting meteorological data of the offshore in the case where meteorological data including the wind speed, the direction and the wave height are not present in relation to the port to be analyzed;
An external analysis module for analyzing extreme values of wave height, wave period, and wave direction in the external sea on the basis of a WAM model (Wave Model) using the above-mentioned weather data as input values;
A heuristic analysis module for analyzing an extreme value of wave height, wave period, and wave direction in a shallow sea based on a SWAN (Simulated Waves Nearshore) model in which extreme values of wave height, wave period, And
An analysis module for analyzing extreme value of wave height for each of a plurality of grids for classifying the port to be analyzed on the basis of a Boussinesq-2D model in which the extreme values of wave height, wave period, System.
The method according to claim 1,
The data collection module collects weather data at the time of typhoons and non-typhoons,
Wherein the depth analysis module, the depth analysis module, and the intra-port analysis module analyze the extreme value of the digging by classifying the typhoon time and the typhoon time.
3. The method of claim 2,
The data collection module collects meteorological data in a plurality of periods,
Wherein the depth analysis module, the depth analysis module, and the intra-flight analysis module analyze the extreme value of the wave height in the plurality of periods.
delete In coastal geographic information analysis methods,
A data collecting step of collecting meteorological data of an offshore area when no meteorological data including a wind speed, a direction and a crest are present in relation to a port to be analyzed;
An external analysis step of analyzing extreme values of wave height, wave period, and wave direction in the external sea on the basis of a WAM model (Wave Model) having the input of the sea level data of the external sea;
An inferiority analysis step of analyzing extreme value of wave, wave period and wave in the sea based on a SWAN (Simulated Waves Nearshore) model in which extreme values of wave height, wave period, and wave direction in the outer sea are used as input values; And
And analyzing an extreme value of a wave height for each of a plurality of grids that divides the port under analysis based on a Boussinesq-2D model in which the extreme values of the wave height, wave period, How to.
6. The method of claim 5,
The data collecting step collects meteorological data during typhoon and non-typhoon,
Wherein the extraneous water analysis step, the deep sea analysis step, and the intra-harbor analysis step are divided into typhoon time and non-typhoon time to analyze the extreme value of the wave height.
The method according to claim 6,
The data collection step collects weather data in a plurality of period units,
Wherein the depth analysis step and the intra-portal analysis step analyze the extreme value of the wave height in the plurality of period units.
delete A computer-readable medium having instructions for performing the steps of the method according to any one of claims 5 to 7.
delete

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