CN117195775A - Method, system, medium and device for calculating extreme mixed wave elements of offshore water area - Google Patents
Method, system, medium and device for calculating extreme mixed wave elements of offshore water area Download PDFInfo
- Publication number
- CN117195775A CN117195775A CN202311215952.0A CN202311215952A CN117195775A CN 117195775 A CN117195775 A CN 117195775A CN 202311215952 A CN202311215952 A CN 202311215952A CN 117195775 A CN117195775 A CN 117195775A
- Authority
- CN
- China
- Prior art keywords
- wave
- different
- elements
- wind
- area
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 186
- 238000000034 method Methods 0.000 title claims abstract description 105
- 238000013461 design Methods 0.000 claims abstract description 71
- 238000006243 chemical reaction Methods 0.000 claims abstract description 45
- 238000004458 analytical method Methods 0.000 claims abstract description 37
- 238000004364 calculation method Methods 0.000 claims description 61
- 230000006870 function Effects 0.000 claims description 44
- 238000012545 processing Methods 0.000 claims description 31
- 230000000694 effects Effects 0.000 claims description 15
- 238000005259 measurement Methods 0.000 claims description 12
- 238000007781 pre-processing Methods 0.000 claims description 12
- 238000012795 verification Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 10
- 239000003643 water by type Substances 0.000 claims description 10
- 238000000605 extraction Methods 0.000 claims description 9
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 238000005553 drilling Methods 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 5
- 238000009499 grossing Methods 0.000 claims description 5
- 238000012546 transfer Methods 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims description 4
- 238000011160 research Methods 0.000 abstract description 7
- 238000010586 diagram Methods 0.000 description 16
- 238000003860 storage Methods 0.000 description 15
- 238000009826 distribution Methods 0.000 description 10
- 230000007774 longterm Effects 0.000 description 9
- 230000008859 change Effects 0.000 description 8
- 238000005315 distribution function Methods 0.000 description 8
- 239000003653 coastal water Substances 0.000 description 5
- 238000012886 linear function Methods 0.000 description 5
- 238000013178 mathematical model Methods 0.000 description 5
- 238000004088 simulation Methods 0.000 description 5
- 230000002159 abnormal effect Effects 0.000 description 4
- 238000003491 array Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000013075 data extraction Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000012216 screening Methods 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000001186 cumulative effect Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 239000006185 dispersion Substances 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 238000012067 mathematical method Methods 0.000 description 2
- 238000012821 model calculation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 238000012805 post-processing Methods 0.000 description 2
- 230000001902 propagating effect Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 238000012876 topography Methods 0.000 description 2
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012905 input function Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
- 238000001556 precipitation Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a method, a system, a medium and a device for calculating extreme mixed wave elements of a near-shore water area, which comprise the following steps: acquiring target area and analyzing wind field data; constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database with a long time sequence; extracting an external sea wave element time sequence from an ocean scale wave database of a long time sequence; calculating the external sea wave elements in different directions and in different reproduction periods based on the external sea wave element time sequence; constructing a small-scale near-shore area wave propagation numerical model and a near-shore small-wind area wave numerical model to obtain surge elements and wave elements of the near-shore area in different water levels, different directions and different reproduction periods; calculating a mixed wave element of each grid point based on the surge element and the wind wave element; and constructing a conversion function of the mixed wave elements, and calculating extreme value mixed wave elements in a certain direction and a certain reproduction period of a certain design water level at any position near the shore by using the conversion function. The application can obtain reasonable and accurate offshore mixed wave results and has more guiding significance for practical engineering design and research.
Description
Technical Field
The invention belongs to the technical field of ocean and offshore wave engineering, relates to an estimation method, and particularly relates to a method, a system, a medium and a device for estimating extreme mixed wave elements in an offshore water area.
Background
The wave elements designed on the coast are key parameters of engineering designs such as coastal embankments, ports, wind power and the like. The accurate and reliable design of wave elements is critical to engineering planning, design, construction and safe operation.
At present, the external sea wave elements are generally statistically analyzed through actual wave data measured in a long time sequence (more than 30 years), but a plurality of actual wave stations are not found near the water area of the proposed engineering, or the observation time is short, and the representativeness is not enough. In some researches, the open sea wave is calculated by constructing a long-term wave mathematical model of sea areas such as south sea, east sea or Bohai sea, but the storm wave generated by ocean monsoon or typhoon and long-period surge cannot be inverted, and the calculation result has room for further improvement.
Wave mathematical models can be divided into 3 major classes according to the basic principle of the model, namely: an energy balance model, a gentle slope equation model, and a Boussinesq equation model. The wave model based on the energy balance equation mainly reflects the macroscopic characteristic of waves, describes the change of wave energy, wave frequency and other factors, can take the wind energy input function into consideration, can also take the physical processes of white cap dissipation, wave refraction diffraction, shallow water deformation and the like into consideration, adopts a simplified algorithm for wave diffraction calculation, and is mainly used for wind wave calculation of deep sea in a large range. Wave model based on gentle slope equation presumes that the wave propagates along a main direction, and is mainly used for wave propagation numerical simulation of the coastal waters. The wave model based on Boussinesq equation describes the motion condition of water particles when wave fluctuation, is ideal in consideration of wave refraction diffraction and structure reflection, but cannot calculate stormy waves, and is long in calculation time consumption, and is mainly used for calculating the near-shore small-range wave propagation deformation of a water area with a complex hydraulic structure.
Therefore, most of current offshore wave estimation adopts a wave model based on an energy balance equation or a wave model based on a Boussinesq equation, wherein the former can consider storms, but the simulation of wave propagation deformation is not fine enough, the inside result of a shallow water area or a hydraulic structure is not accurate enough, and the latter can finely simulate wave propagation deformation, but the effect of storms in a small wind area cannot be considered, and the result is small.
The existing method for calculating the extreme value mixed wave elements of the near-shore water area is various, has no unified mode, has advantages and disadvantages, is inconvenient for extracting the result with large data volume, and lacks a set of system and accurate calculation and data processing methods.
Therefore, in the existing technology for calculating the extreme value mixed wave elements in the offshore water area, the problems of inconvenient data extraction, lack of systematicness and precision caused by no unified mode, and low accuracy, safety and stability of the offshore wave monitoring work are directly affected.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present application is directed to a method, a system, a medium and a device for calculating an extremum mixed wave element in a near-shore water area, which are used for solving the technical problems of inconvenient data extraction, lack of systematicness and precision, and further direct influence on accuracy and low safety and poor stability of marine near-shore wave monitoring work caused by lack of uniform modes in the technology for calculating the extremum mixed wave element in the near-shore water area in the prior art.
To achieve the above and other related objects, in a first aspect, the present application provides a method for estimating an extremum mixed wave element of a coastal waters, comprising the steps of: acquiring target area and analyzing wind field data; the analyzing the wind field data includes: wind speed and direction; constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database with a long time sequence; extracting wave data of the open sea feature points based on the ocean scale wave database of the long-time sequence to obtain an open sea wave element time sequence of the target area; based on the external sea wave element time sequence, calculating external sea wave elements in different directions and at different reproduction periods by adopting a Pearson III type curve fitting line method; constructing a small-scale wave propagation numerical model of the near-shore area based on the external sea wave elements in different directions and at different reproduction periods to obtain surge elements in different water levels in different directions and at different reproduction periods of the near-shore area; constructing a wave numerical model of the offshore small wind area based on engineering design wind speed and wind direction data to obtain wave elements of different water levels of the offshore area in different directions and different reproduction periods; calculating a mixed wave element for each grid point based on the swell element and the stormy element; and constructing a conversion function of the mixed wave elements, and calculating extreme value mixed wave elements of a certain design water level and a certain reproduction period in a certain direction at any position near the shore by using the conversion function.
In one implementation manner of the first aspect, constructing an ocean scale wind wave numerical model based on the analysis wind field data, to obtain an ocean scale wave database of a long time sequence includes the following steps: performing data preprocessing on the analysis wind field data to obtain preprocessed analysis wind field data; the data preprocessing comprises the following steps: any one or more of data format conversion, data cleansing, outlier processing, missing value filling and smoothing processing; constructing an ocean scale wind wave numerical model based on the preprocessed analysis wind field data, carrying out calibration verification on the model by using actual measurement wave data of satellites and buoys, and determining proper model key parameters to form a calibrated and verified ocean scale wind wave numerical model; and calculating ocean wave elements for not less than 30 years based on the rated and verified ocean scale wind wave numerical model to obtain an ocean scale wave database with long time sequence.
In one implementation manner of the first aspect, the model key parameters include: white cap dissipation factor; the white cap dissipation coefficient formula is:
C ds ＝4.5+(V-25)/6
wherein C is ds Expressed as white cap dissipation factor, dimensionless; v is expressed as wind speed in units of: m/s.
In an implementation manner of the first aspect, the step of extracting the wave data of the open sea feature points based on the ocean scale wave database of the long time sequence to obtain the time sequence of the open sea wave elements of the target area, and calculating the open sea wave elements of different reproduction periods in different directions includes the following steps: based on the ocean scale wave database of the long-time sequence, extracting wave data of the feature points of the open sea to obtain an open sea element time sequence; based on the external sea wave element time sequence, the external sea wave elements in different directions and in different reproduction periods are calculated by adopting a Pearson III type curve fitting line method.
In an implementation manner of the first aspect, the step of constructing a small-scale wave propagation numerical model of the offshore area based on the external sea wave elements in different reproduction periods in different directions to obtain the surge elements in different reproduction periods in different designed water levels in the offshore area includes the following steps: constructing a small-scale offshore area wave propagation numerical model based on the external sea wave elements in different directions and at different reproduction periods, and determining the boundary condition of the model; adopting a structural grid to manufacture a calculation terrain, inputting the external sea wave elements in different directions and at different reproduction periods as calculation boundaries, and setting different design water levels; and calculating surge elements of different designed water levels in different directions and different reproduction periods in the near-shore area based on the small-scale near-shore area wave propagation numerical model.
In one implementation manner of the first aspect, constructing a near-shore small wind area wave numerical model based on engineering design wind speed and wind direction data to obtain wind wave elements of different water levels of different designs in different directions and different reproduction periods in the near-shore area includes the following steps: constructing a wave numerical model of the offshore small wind area based on an energy balance equation; adopting an unstructured grid to manufacture calculated terrain, determining boundary conditions of the offshore small wind area wave numerical model, adopting an open boundary, and setting different design water levels, design wind speeds and wind directions; calculating the stormy waves of the small wind area by considering the dissipation effect of the white cap, and processing the calculation result to obtain the stormy wave elements of the near-shore area in different water levels, different directions and different reproduction periods; converting the stormy wave elements in the unstructured grid data format into stormy wave elements in different water levels, different directions and different reproduction periods in the offshore area of the structured grid data format in an interpolation mode.
In one implementation of the first aspect, calculating the hybrid wave element for each grid point based on the swell element and the stormy element includes the steps of: overlapping the surge elements and the wave elements of different water levels of different designs in different directions and different reproduction periods in the near shore region of the structural grid data format, and calculating to obtain the mixed wave elements of each grid point; the calculated mixed wave elements of all grid points are led into the structural grid to obtain a mixed wave database with structural grid data formats of different water levels of different designs in the near-shore area in different directions and different reproduction periods; the calculation formula of the mixed wave elements of each grid point is as follows:
T H ＝MAX(T S ,T W )
MWD H ＝AVERAGE(MDD S ,MWD W )
Wherein H is H Representing the wave height of the hybrid wave, units: m; h S Wave height, units: m; h W Wave height, units: m; t (T) H The wave period, in units of: s; t (T) S The wave period, in units of: s; t (T) W Wave period representing stormy waves, unit: s; MWD (measurement-while-drilling) MWD (measurement-while- H Mean direction of the mixed wave, unit: a deg; MDD (minimization drive test) S Mean direction of surge, unit: a deg; MWD (measurement-while-drilling) MWD (measurement-while- W Mean wave direction of wind wave, unit: and deg.
In one implementation manner of the first aspect, constructing a conversion function of the mixed wave element, and calculating an extremum mixed wave element of a certain reproduction period in a certain direction of a certain design water level at any position near the shore by using the conversion function includes the following steps: constructing a transformation function of a mixed wave element and water level, direction, reproduction period, abscissa and ordinate of a near-shore area by a linear difference method; based on the conversion function, extreme value mixed wave elements of a certain design water level at any position near the shore in a certain direction and a certain reproduction period are calculated; the calculation formula of the conversion function is as follows:
H H ＝f 1 (E,D,N,X,Y)
T H ＝f 2 (E,D,N,X,Y)
MWD H ＝f 3 (E,D,N,X,Y)
wherein E is expressed as the water level of the offshore area in units of: m; d represents direction, unit: a deg; n is expressed as reproduction period, unit: year; x is represented by abscissa, unit: m; y is expressed in ordinate, units: m; f (f) 1 Conversion functions expressed as wave height of the offshore hybrid wave with respect to 5 parameters of water level, direction, reproduction period, abscissa and ordinate; f (f) 2 Conversion functions expressed as wave periods of the offshore hybrid waves with respect to 5 parameters of water level, direction, reproduction period, abscissa and ordinate; f (f) 3 The average wave direction of the waves, expressed as an offshore hybrid wave, is a transfer function of 5 parameters with respect to water level, direction, reproduction period, abscissa and ordinate.
In a second aspect, the application provides a system for estimating extreme mixed wave elements in a near shore water area, comprising: the acquisition module is used for acquiring the target area and analyzing wind field data; the analyzing the wind field data includes: wind speed and direction; the data processing module is used for constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database with a long time sequence; the feature extraction module is used for extracting wave data of the feature points of the open sea based on the ocean scale wave database of the long-time sequence to obtain an open sea element time sequence of the target area; based on the external sea wave element time sequence, calculating external sea wave elements in different directions and at different reproduction periods by adopting a Pearson III type curve fitting line method; the model construction module is used for constructing a small-scale wave propagation numerical model of the near-shore area based on the external sea wave elements in different directions and in different reproduction periods to obtain surge elements in different water levels in different directions and in different reproduction periods of the near-shore area; constructing a wave numerical model of the offshore small wind area based on engineering design wind speed and wind direction data to obtain wave elements of different water levels of the offshore area in different directions and different reproduction periods; the data calculation module is used for calculating the mixed wave element of each grid point based on the surge element and the wind wave element; and the conversion module is used for constructing a conversion function of the mixed wave element, and calculating the extremum mixed wave element of a certain reproduction period in a certain direction of a certain design water level at any position near the shore by using the conversion function.
In a final aspect, the application provides a device for estimating extreme mixed wave elements in a coastal water area, comprising: a processor and a memory. The memory is used for storing a computer program; the processor is connected with the memory and is used for executing the computer program stored in the memory so that the offshore water extremum mixed wave element calculating device can execute the offshore water extremum mixed wave element calculating method.
As described above, the method, system, medium and device for estimating extreme mixed wave elements in offshore waters of the present application have the following
The beneficial effects are that:
the application provides a method for calculating extreme value mixed wave elements in a near-shore water area, which is characterized in that a long-term ocean scale wave field is built on the premise of lacking long-term actual measurement wave data, ocean monsoon or typhoon generated stormy waves and long-period stormy waves can be more accurately inverted, the extremum wave extreme value analysis is carried out, extreme value calculated values are calculated to near-shore stormy waves, the stormy waves in a small wind area are calculated according to wind speeds, then the stormy waves and the stormy wave elements in different data formats on the near-shore are overlapped and calculated, a more reasonable and accurate near-shore mixed wave result is obtained, and a wave database and a conversion function are constructed, so that data required by an extraction project are more convenient, and the method has guiding significance on actual engineering design and research.
Drawings
FIG. 1 is a flow chart of an embodiment of the method for estimating the extreme mixed wave elements in a near-shore water area according to the present invention.
Fig. 2A is a schematic flow chart of S12 in the method for estimating the extreme mixed wave elements in the offshore water according to the present invention.
FIG. 2B is a schematic diagram showing calculation grids of the ocean scale storm mathematical model in the method for calculating the extreme mixed wave elements of the offshore water area.
FIG. 2C is a schematic diagram showing CFSR re-analysis of wind field data at a certain time in the method for estimating the extreme hybrid wave elements in the offshore waters of the present invention.
Fig. 3A is a schematic flow chart of S13 in the method for estimating the extreme mixed wave elements in the offshore water according to the present invention.
FIG. 3B is a schematic diagram showing a wave height time sequence of an embodiment of the method for estimating the extreme mixed wave elements in a near-shore water area according to the present invention.
FIG. 3C is a schematic diagram showing a wave cycle time sequence of an embodiment of the method for estimating the extreme mixed wave elements in a near-shore water area according to the present invention.
Fig. 4 is a schematic flow chart of S14 in the method for estimating the extreme mixed wave elements in the offshore water according to the present invention.
Fig. 5A is a schematic flow chart of S15 in the method for estimating the extreme mixed wave element in the offshore water according to the present invention.
FIG. 5B is a graph showing the calculated topography of a model for the investigation of the white cap dissipation algorithm in one embodiment of the method for estimating the extreme mixed wave elements in a near shore water area according to the present invention.
FIG. 5C is a schematic diagram showing the fitting of the white cap dissipation factor formula in an embodiment of the method for estimating the extreme mixed wave elements in the offshore waters according to the present invention.
FIG. 5D is a schematic diagram showing the verification result of the white cap dissipation factor fitting formula of the method for calculating the extreme mixed wave elements in the offshore waters according to an embodiment of the invention.
Fig. 6 is a schematic flow chart of S16 in the method for estimating the extreme mixed wave elements in the offshore water according to the present invention.
Fig. 7 is a schematic flow chart of S17 in the method for estimating the extreme mixed wave element in the offshore water according to the present invention.
FIG. 8 is a schematic diagram of an embodiment of the system for estimating the extreme hybrid wave elements in a coastal waters according to the present invention.
FIG. 9 is a schematic diagram of an embodiment of the device for estimating the extreme mixed wave elements in the offshore waters according to the present invention.
Description of element reference numerals
81. Acquisition module
82. Data processing module
83. Feature extraction module
84. Model building module
85. Data calculation module
86. Conversion module
91. Processor and method for controlling the same
92. Memory device
S11 to S17 steps
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present application with reference to specific examples. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present application by way of illustration, and only the components related to the present application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
The method for calculating the extreme value mixed wave elements of the offshore water area provided by the embodiment of the application is described in detail below with reference to the accompanying drawings in the embodiment of the application.
Referring to fig. 1, a flow chart of a method for estimating an extreme hybrid wave element in a near-shore water area according to an embodiment of the invention is shown. As shown in fig. 1, the embodiment provides a method for calculating the extreme mixed wave elements in the offshore water area.
The method for calculating the extreme value mixed wave elements of the offshore water area specifically comprises the following steps:
s11, acquiring target area analysis wind field data.
In this embodiment, the wind farm uses CFSR from the us ocean and atmospheric management agency forecasting center to analyze wind farm data.
The CFSR climate prediction system analyzes wind field data as a set of analysis data in NCEP (National Centers for Environmental Prediction, national environmental prediction center) with a time scale of 1979-2009. Whereas the NCEP re-analysis data was made by a combination of the United states weather forecast center and the national atmospheric research center. The method adopts the most advanced global data assimilation system and perfect database at present to carry out quality control and assimilation treatment on the observation data of various data sources (ground, ships, radiosonde, wind balloon, aircraft, satellite and the like), and the obtained complete set of analysis data set has wide range of elements and long extension period, and is a comprehensive observation data set. NCEP analysis data is lattice data formed by analyzing weather data from 1948 to the present world by using observation data, prediction modes and an assimilation system. The data variables include the earth's surface, near-earth's surface (995 sigma layer), and multiple meteorological variables for different barometric layers, such as precipitation, temperature, relative humidity, sea level barometric pressure, potential altitude, wind field, and heat flux.
And S12, constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database with a long time sequence. Referring to fig. 2A, fig. 2B, and fig. 2C, a flow chart of S12 in the method for calculating the extreme value mixed wave element in the near-shore water area of the present invention, a calculation grid diagram of the mathematical model of ocean scale stormy waves in the method for calculating the extreme value mixed wave element in the near-shore water area of the present invention, and a CFSR re-analysis wind field data diagram at a certain moment in the method for calculating the extreme value mixed wave element in the near-shore water area of the present invention are shown respectively. As shown in fig. 2A, 2B and 2C, the step S12 includes the following steps:
in the embodiment, an ocean scale wind wave numerical model (such as Pacific ocean or Atlantic ocean) based on an energy balance equation is built, CFSR analysis wind field data of the ocean and atmospheric management agency prediction center is adopted in the wind field, white dissipation coefficients in the ocean scale wind wave numerical model greatly influence calculation results, the model scale parameters are used as model scale parameters, model scale verification is carried out by using actual measurement wave data of satellites and buoys, so that proper dissipation coefficients are determined, ocean quarter wind or typhoon generated wind waves and long-period surge waves are inverted by using the well-calibrated model, verification is carried out by using actual measurement wave data of satellites and buoys, and a total calculation period is not less than 30 years, so that an ocean scale wave database with long time sequence is obtained.
A time series is defined as an array of data points arranged in time, with data points representing activities occurring over a time interval. It is typically the result of observing some potential process at a given sampling rate over equally spaced time periods. The time series data essentially reflects the trend of a random variable or random variables over time, and the core of the time series prediction method is to mine this rule from the data and use it to make an estimate of future data.
And S121, carrying out data preprocessing on the re-analysis wind field data to obtain preprocessed re-analysis wind field data. The data preprocessing comprises the following steps: any one or more of format conversion, data screening, data cleansing, outlier handling, missing value filling and smoothing.
In this embodiment, the re-analysis wind field data for a total calculated period of not less than 30 years is collected. And then preprocessing the collected historical meteorological data to ensure the accuracy and the credibility of the data. Wherein the analyzing the wind field data comprises: meteorological data such as wind speed and wind direction. The meteorological data further includes: historical meteorological data, real-time meteorological data and other relevant data. These data can ensure the accuracy of the inversion.
Specifically, historical meteorological data is preferably collected between 1980 and 2010, such as: wave height, wave direction, wave period, etc. Performing format conversion and data screening on the collected historical meteorological data, and removing invalid or redundant data; then, the screened historical meteorological data is subjected to data cleaning to remove data which does not meet the specification, such as missing values, abnormal values and the like; processing the abnormal value by a statistical method or a visual method; filling the missing values by adopting an interpolation method or a regression method and the like; and finally, carrying out smoothing treatment on the data to remove noise and improve the data quality of the historical meteorological data.
S122, constructing an ocean scale wind wave numerical model based on the preprocessed analysis wind field data, and performing calibration verification on the model by using actual measurement wave data of satellites and buoys to determine proper model key parameters so as to form the calibrated and verified ocean scale wind wave numerical model.
In this embodiment, based on the historical meteorological data in the wind farm data after preprocessing in the above steps, the method includes: and constructing an inversion model by using related data such as wave height, wave direction, wave period and the like, and inverting meteorological data. And verifying the preprocessed historical meteorological data and the inversion model to obtain a preliminary inversion result.
Specifically, a model capable of describing and calculating wind waves in the ocean is selectively built according to meteorological data, and the model is based on an energy balance equation, including the influence of kinetic energy, potential energy, coriolis force, pressure and the like. Inputting the collected and preprocessed historical meteorological data into the model, initializing the model and setting model parameters such as learning rate, iteration times and the like according to model characteristics; wave data features are then extracted from the historical weather data. And selecting inversion parameters according to the ocean scale wind wave numerical model and the historical meteorological data, inverting the wind waves and long-period swells generated by ocean monsoon or typhoons, and then gradually optimizing the results of inverting the wind waves and the long-period swells through multiple iterations. Wherein initializing the model includes setting initial conditions of the model, such as: initial wind field, wave height, wavelength, etc.; the key parameters of the model include: friction coefficient, coriolis force coefficient, white cap dissipation coefficient, etc.
It should be noted that the optimization method mentioned above may adopt optimization methods such as gradient descent and genetic algorithm to improve stability of accuracy of inversion result.
And S123, calculating ocean wave elements of not less than 30 years based on the rated and verified ocean scale wind wave numerical model, and obtaining an ocean scale wave database with long time sequence.
In this embodiment, the result obtained by inversion calculation in step S122 is verified by using the measured wave data of the satellite and the buoy, so as to ensure the authenticity and reliability thereof. After the verified inversion result is obtained, further data analysis is carried out to mine rules and meanings contained in ocean scale wave data displayed by the data, and finally the rules and meanings are displayed in a graphical mode, so that a user can better understand and analyze the inversion result.
Specifically, the acquired actual wave data of the satellite and the buoy are compared with the inversion calculated result, the accuracy of the comparison result is evaluated, the inversion result is evaluated through expert judgment, whether the actual situation is met or not is judged, and then error analysis is carried out on the inversion result. Then, analyzing the inversion result by adopting a statistical method, and carrying out data mining by utilizing measured wave data to find a rule in the inversion result; finally, the ocean scale wave database with long time sequence is obtained.
In addition, according to the user demand, the inversion result can be displayed in a graphical mode, so that the analysis result can be presented more intuitively. Presentation content includes, but is not limited to: charts, maps, etc., such as: bar graphs, line graphs, scatter graphs, etc.
And S13, extracting wave data of the open sea feature points based on the ocean scale wave database of the long-time sequence to obtain the open sea wave element time sequence of the target area, and calculating the open sea wave elements in different directions and in different reproduction periods. Referring to fig. 3A, 3B and 3C, a flow chart of S13 in the method for estimating an extremum mixed wave element in a near-shore water area of the present invention, a wave height time sequence diagram of the method for estimating an extremum mixed wave element in a near-shore water area of the present invention at a depth of 30m in an embodiment, and a wave period time sequence diagram of the method for estimating an extremum mixed wave element in a near-shore water area of the present invention at a depth of 30m in an embodiment are shown respectively. As shown in fig. 3A, 3B and 3C, the step S13 includes the following steps:
in this embodiment, wave element time sequences (wave height, wave direction, wave period) of the open sea (water depth about 30 m) of the planned target research area are extracted from the ocean scale wave database, and the open sea wave elements in different directions and in different reproduction periods are calculated by using a pearson iii-type curve fitting line method.
S131, extracting wave data of the feature points of the open sea based on the ocean scale wave database of the long time sequence to obtain an open sea wave element time sequence.
And performing data fitting based on the wave heights, wave directions and wave periods in different periods in the ocean scale wave database of the long-time sequence to obtain a probability distribution function of the ocean scale wave data.
In the embodiment, data such as medium wave height, wave direction, wave period and the like of the ocean scale wave database with long time sequence are cleaned, screened and processed to remove abnormal values and missing values; fitting is carried out according to the processed wave height, wave direction, wave period and other data, and a probability distribution function of wave elements is obtained.
Wave elements are the main physical quantities characterizing the nature and morphology of the wave motion.
Determining an overseas ocean wave element parameter according to the probability distribution function; the external sea wave element parameters include: mean, standard deviation, and skewness of the overseas wavelet elements.
In this embodiment, parameters such as mean, standard deviation, and deflection of wave elements are determined by using a maximum public likelihood estimation method according to data such as mid-wave height, wave direction, wave period, and the like of the ocean scale wave database of the long-time sequence and a probability distribution function obtained by fitting.
S132, calculating the external sea wave elements in different directions and in different reproduction periods by adopting a Pearson III type curve fitting line method based on the external sea wave element time sequence, so as to obtain the external sea wave element time sequence.
The pearson type III curve is a probability distribution curve that describes how the data is distributed around an average. This distribution is generally determined by three parameters: μ (mean), σ (standard deviation) and κ (skewness).
In the embodiment, according to the Pearson III type curve and the determined parameters such as the mean value, standard deviation, skewness and the like of the wave elements, the frequency distribution of the wave elements in different reproduction periods is established by calculating probability density functions and cumulative distribution; and then according to the frequency distribution of different reproduction periods, calculating corresponding wave elements, namely: wave height, wave direction, wave period, etc., thereby obtaining an external sea wave element time sequence.
And S14, constructing a small-scale wave propagation numerical model of the near-shore area based on the external sea wave elements in different directions and in different reproduction periods, and obtaining the surge elements in different water levels in different directions and in different reproduction periods of the near-shore area. Referring to fig. 4, a flow chart of S14 in the method for estimating the extreme hybrid wave elements in the offshore water according to the present invention is shown. As shown in fig. 4, the step S14 includes the following steps:
building a small-scale near-shore area wave propagation numerical model based on Boussinesq equation, calculating terrain by adopting structural grids, inputting the external sea wave elements in different directions and in different reproduction periods calculated by the steps of the boundary, setting different design water levels, and obtaining the surge elements (wave height, wave period and average wave direction) in different directions and different reproduction periods of the near-shore area by considering the comprehensive effects of shallow water deformation, bottom friction dissipation, hydraulic structures and the like on wave propagation deformation
S141, constructing a small-scale offshore area wave propagation numerical model based on the external sea wave elements in different directions and in different reproduction periods, and determining the boundary conditions of the model.
In the embodiment, a small-scale near-shore area wave propagation numerical model based on a Boussinesq equation is built, and model parameters and boundary conditions are determined.
The Boussinesq equation is a partial differential equation describing wave motion and contains information about the speed, altitude, period, etc. of wave propagation.
Specifically, according to the fundamental theory of fluid dynamics and wave propagation, establishing a Boussinesq equation; and determining parameters and boundary conditions of the model according to the overseas wavelet element time sequence. Then, a numerical method is adopted to construct a small-scale near-shore area wave propagation numerical model of the Boussinesq equation, verification and parameter tuning are carried out on the model, and the accuracy and reliability of the model are improved.
It should be noted that the numerical method may be implemented by using a finite element method, a finite difference method, or the like.
S142, adopting a structural grid to manufacture a calculated terrain, inputting the external sea wave elements with different reproduction periods in different directions as a calculated boundary, and setting different design water levels.
The computational grid can be divided into adjacencies between grid points: structured grids and unstructured grids. The adjacency between grid points of the structural grid is ordered and regular, and the cells are quadrilaterals of two dimensions and hexahedrons of three dimensions. The adjacency between non-structural grid points is disordered and irregular, each grid point can have different adjacency grid numbers, and the units have various shapes such as two-dimensional triangles, quadrilaterals, three-dimensional tetrahedrons, hexahedrons, triangular prisms, pyramids and the like.
The CFD calculation method of the structural grid is advanced, high in calculation precision, high in calculation efficiency, good in calculation stability, low in requirement on hardware resources such as a computer memory and the like, and the number of required grid points is less than that of the unstructured grid in the same physical space. Because the structural grid can easily generate the viscous grid with a large length-width ratio, the required precision can be basically ensured during calculation, and therefore, the viscous areas such as a boundary layer and the like can be accurately and efficiently simulated.
In the embodiment, uniformly dividing the boundary of the target area dividing model according to a proportion, and setting the grid density; setting calculation parameters, selecting proper calculation precision, iteration calculation times and the like; and then carrying out numerical calculation by utilizing the structural grid and the set parameters so as to simulate wave change. Meanwhile, different design water levels are set; and the comprehensive effects of shallow water deformation, bottom friction dissipation, hydraulic structures and the like on wave propagation deformation are considered. Then, comparing wave change conditions at different moments, and analyzing wave change trend; adjusting calculation parameters and grid division through the fitting degree of the evaluation result and the actual waves; the positions of the grid points may be further adjusted to improve the accuracy of the calculation.
S143, calculating the surge elements of different designed water levels in the near-shore area in different directions and in different reproduction periods based on the small-scale near-shore area wave propagation numerical model.
In this embodiment, based on the established small-scale near-shore area wave propagation numerical model, surge elements with different design water levels and different directions are calculated, for example: wave height, period, direction, etc. These elements can be obtained by analyzing the simulation result. And then analyzing the calculated surge elements, and comparing differences of the surge elements in different design water levels and different directions. Meanwhile, the propagation rule and influence factors of the surge can be analyzed.
And S15, constructing a wave numerical model of the offshore small wind area based on the engineering design wind speed and wind direction data, and obtaining wind wave elements of different water levels in different directions and different reproduction periods in the offshore area. Referring to fig. 5A, a flow chart of S15 in the method for estimating the extreme hybrid wave elements in the offshore waters according to the present invention is shown. As shown in fig. 5A, the step S15 includes the following steps:
building an energy balance equation-based near-shore small wind area wave numerical model, calculating terrain by adopting unstructured grids, setting different design water levels by taking wind speeds in different directions and different reproduction periods into consideration for input conditions, taking effects such as white dissipation and the like into consideration, calculating small wind area waves by adopting the results in the steps for dissipation coefficients, and obtaining wave elements (wave height, wave period and average wave direction) in different directions and different reproduction periods of different design water levels in the near-shore area.
S151, constructing a wave numerical model of the offshore small wind area based on an energy balance equation.
In this embodiment, an energy balance equation and a substance derivative equation are determined, as well as a boundary condition and an initial condition, and then the energy balance equation and the substance derivative equation are discretized.
S152, adopting an unstructured grid to manufacture calculated terrain, determining boundary conditions of the offshore small wind area wave numerical model, adopting an open boundary, and setting different design water levels, design wind speeds and wind directions.
In this embodiment, a suitable terrain unstructured grid is selected, so that complex terrain features of the offshore area can be accurately described. The boundary conditions are input while the wind speeds in different directions and in different reproduction periods are considered. Setting different design water levels according to the user demands, such as: tide level, storm tide level, etc.
The non-structural grid has good distribution controllability of nodes and units due to elimination of structural limitation of nodes in the structural grid, thus being capable of better processing boundaries and easily controlling the size of the grid and the density of the nodes. Once the distribution of grids is specified on the boundaries, grids can be automatically generated between the boundaries, the whole grids and the whole solution can be always generated without the intervention of block partition or users, information is not required to be transferred between subdomains, and the accuracy loss caused by interpolation is avoided like the nesting of the structural grid partition. Grid partitioning based on unstructured grids and parallel computing are more straightforward than structured grids due to its random data structure. The biggest advantage of the unstructured grid is its almost ubiquitous geometric adaptability, namely the strong flexibility to complex configurations, and its grid generation is simple, especially the manual work of grid generation is little.
And S153, calculating the wind waves of the small wind area by considering the dissipation effect of the white cap, and processing the calculation result to obtain the wind wave elements of different water levels of different designs in different directions and different reproduction periods in the near-shore area.
In this embodiment, a dissipation factor model such as a Smith model or a Munk model is used to simulate the effect of white cap dissipation. Calculating the wind wave of the small wind area by calculating the energy balance equation after dispersion; and post-processing the calculation results, such as drawing wave images, calculating statistics of wave heights, wave periods, average wave directions and the like.
Specifically, the white cap dissipation factor formula is:
C ds ＝4.5+(V-25)/6
wherein C is ds Expressed as white cap dissipation factor, dimensionless; v is expressed as wind speed in units of: m/s.
The derivation of the formula is as follows: at present, an SMB formula and a Putian formula are commonly used at home and abroad to calculate stormy waves, the result is related to factors such as wind speed, wind area length and the like, and the result is reliable through many practical tests, but the method is only applicable to simple terrains, and the wave calculation under the condition of complex terrains is not a mathematical model.
Further, the formula of Putian used is:
the SMB formula is:
wherein,expressed as average wave height, units: m; h S Representing the effective wave height in units of: m and F represent the length of the wind area, unit: m, d represent the water depth, unit: m and g represent gravitational acceleration in units of: m/s 2 V represents wind speed, unit: m/s.
The result of the offshore small wind area wave numerical model based on the energy balance equation is greatly influenced by the white cap dissipation coefficient, but is superior to an empirical formula in the aspects of simulating complex terrain, calculating speed, visualizing and the like.
S154, converting the stormy wave elements in the unstructured grid data format into stormy wave elements in different water levels, different directions and different reproduction periods in the near-shore region of the structured grid data format in an interpolation mode.
In this embodiment, interpolation is used to convert the wind wave element data of the unstructured grid into the wind wave element data of the structured grid.
Specifically, the near-shore area is divided into a plurality of structural grids according to the designed water level and direction. And then interpolating calculation is carried out according to the unstructured grid data, so as to obtain the wind wave element values on the structured grid. Analyzing and adjusting the interpolation calculation result to obtain the stormy wave elements in different water levels of different designs in different directions and in different reproduction periods in the near-shore region. The wind wave element data has the characteristics of everywhere, smoothness and the like.
For example: taking a simple regular terrain as an example, comparing and analyzing the simulation result of the near shore small wind area wave numerical model based on the energy balance equation with the calculated values of two more common empirical formulas at home and abroad.
Referring to fig. 5B and fig. 5C, a model calculation topographic map for researching a white cap dissipation algorithm in an embodiment of the method for calculating the extreme value mixed wave element in a near-shore water area according to the present invention and a white cap dissipation coefficient formula fitting schematic diagram in an embodiment of the method for calculating the extreme value mixed wave element in a near-shore water area according to the present invention are shown respectively.
Due to different working conditions, the white cap dissipation coefficient is adjusted according to the result of the empirical formula, so that the results of the model and the empirical formula are identical, a linear relationship between the white cap dissipation coefficient and the wind speed is found in the debugging process, the data is fitted, and the following formula is obtained:
C ds ＝4.5+(V-25)/6
wherein V represents wind speed, unit: m/s; c (C) ds Representing the white cap dissipation factor.
Then, aiming at slope topography, calculating the accurate value of the white cap dissipation coefficient according to different wind speeds, inputting the accurate value into a model, and calculating the along-way change of the effective wave height. Referring to fig. 5D, a schematic diagram of a verification result of a white cap dissipation factor fitting formula of an embodiment of the method for estimating an extreme hybrid wave element in a near-shore water area according to the present invention is shown.
Adjusting the model according to a fitting formulaWhite cap dissipation factor C ds The result obtained by the model calculation is better matched with the calculated value of the empirical formula. Therefore, when the storm model is applied to actual engineering, the white cap dissipation coefficient C ds The value of (C) may be according to the white cap dissipation formula C above ds =4.5+ (V-25)/6.
Therefore, the small wind area wind wave can be calculated by adopting the set models with different working conditions, and the wind wave elements (wave height, wave period and average wave direction) with different water levels in different directions and different reproduction periods in different designed water levels in the near-shore area can be obtained.
S16, calculating the mixed wave element of each grid point based on the surge element and the stormy wave element. Referring to fig. 6, a flow chart of S16 in the method for estimating the extreme hybrid wave elements in the offshore water according to the present invention is shown. As shown in fig. 6, the step S16 includes the following steps:
and S161, overlapping the surge elements and the wave elements of different reproduction periods in different directions of different design water levels in the offshore area of the structural grid data format, and calculating to obtain the mixed wave elements of each grid point.
In this embodiment, when two series of waves of the swell and the stormy waves meet, a mixed swell is formed, and the swell wave elements and the stormy wave elements of different reproduction periods in different directions of different design water levels in the near-shore area of the structural grid data format are subjected to superposition calculation, so that the mixed swell wave elements of each grid point are obtained.
And the calculation formula of the mixed wave element of each grid point is as follows:
T H ＝MAX(T S ,T W )
MWD H ＝AVERAGE(MDD S ,MWD W )
Wherein H is H Representing the wave height of the hybrid wave, units: m; h S Wave height, units: m; h W Wave height, units: m; t (T) H Representing a mixWave period of the wave, unit: s; t (T) S The wave period, in units of: s; t (T) W Wave period representing stormy waves, unit: s; MWD (measurement-while-drilling) MWD (measurement-while- H Mean direction of the mixed wave, unit: a deg; MDD (minimization drive test) S Mean direction of surge, unit: a deg; MWD (measurement-while-drilling) MWD (measurement-while- W Mean wave direction of wind wave, unit: and deg.
And S162, leading the calculated mixed wave elements of each grid point into a structural grid to obtain a mixed wave database in a structural grid data format with different water levels in different directions and different reproduction periods in a near-shore area.
In this embodiment, the calculated wave mixing elements (such as wave height, wave period, and average wave direction of the mixed waves) of each grid point are imported into the structural grid to obtain the mixed wave database with structural grid data formats of different water levels of different designs in the near-shore area in different directions and different reproduction periods.
S17, constructing a conversion function of the mixed wave elements, and calculating extreme value mixed wave elements of a certain reproduction period in a certain direction of a certain design water level at any position near the shore by using the conversion function. Fig. 7 is a flowchart of S17 in the method for estimating the extreme hybrid wave elements in the offshore water according to the present invention. As shown in fig. 7, the step S17 includes the steps of:
S171, constructing a transformation function of the wave elements and water level, direction, reproduction period, abscissa and ordinate of the mixed wave in the offshore area by a linear difference method.
In this embodiment, the conversion relationship between the offshore area hybrid wave elements and the water level, direction, reproduction period, abscissa and ordinate is determined by a linear function. The form of its linear function may take the form of, for example: y=ax+b, where y is the wave element, x is the water level, direction, reproduction period, abscissa or ordinate, and a and b are the coefficients to be determined. Then, a linear difference model is built according to the linear function, and solving is carried out through a least square method and other mathematical methods, so that the values of the coefficients a and b are obtained. And then the wave elements of the mixed waves in the actual near-shore area, the water level, the direction, the reproduction period, the abscissa and the ordinate are input into the model, so as to calculate the extreme value mixed wave elements of a certain designed water level at any near-shore position in a certain direction and a certain reproduction period.
The calculation formula of the conversion function is as follows:
H H ＝f 1 (E,D,N,X,Y)
T H ＝f 2 (E,D,N,X,Y)
MWD H ＝f 3 (E,D,N,X,Y)
wherein E is expressed as the water level of the offshore area in units of: m; d represents direction, unit: a deg; n is expressed as reproduction period, unit: years of life; x is represented by abscissa, unit: m; y is expressed in ordinate, units: m; f (f) 1 Conversion functions expressed as wave height of the offshore hybrid wave with respect to 5 parameters of water level, direction, reproduction period, abscissa and ordinate; f (f) 2 Conversion functions expressed as wave periods of the offshore hybrid waves with respect to 5 parameters of water level, direction, reproduction period, abscissa and ordinate; f (f) 3 The average wave direction of the waves, expressed as an offshore hybrid wave, is a transfer function of 5 parameters with respect to water level, direction, reproduction period, abscissa and ordinate.
S172, based on the conversion function, extreme value mixed wave elements of a certain design water level and a certain reproduction period in a certain direction at any position near the shore are calculated.
According to the method for calculating the extreme value mixed wave elements of the offshore water area, provided by the application, on the premise of lacking long-term actual measurement wave data, a long-term ocean scale wave field is built, the ocean scale wave field can be more accurately inverted, the storm wave generated by the ocean monsoon or typhoon and the long-period storm wave are more accurately analyzed, the extreme value calculated value is converted into the offshore calculated storm wave, the storm wave of a small storm area is calculated according to the wind speed, then the storm wave and the storm wave elements in different data formats on the offshore are subjected to superposition calculation, a more reasonable and accurate offshore mixed wave result is obtained, and a wave database and a conversion function are built, so that the data required by the extraction engineering are more convenient.
The protection scope of the method for calculating the extreme value mixed wave elements of the offshore water area according to the embodiment of the application is not limited to the execution sequence of the steps listed in the embodiment, and all the schemes of step increase and decrease and step replacement in the prior art according to the principles of the application are included in the protection scope of the application.
The present embodiment additionally provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a method for estimating an extreme mixed wave element of a coastal waters as described in fig. 1.
The present application may be a system, method and/or computer program product at any possible level of technical details. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present application.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device. Computer program instructions for carrying out operations of the present application may be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and a procedural programming language such as the "C" language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on the computer or entirely on the computer or server. In the case of a computer, the computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (e.g., connected through the internet using an internet service provider). In some embodiments, aspects of the present application are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information for computer readable program instructions, which can execute the computer readable program instructions.
The embodiment of the application also provides a system for calculating the extreme value mixed wave elements of the near-shore water area, which can realize the method for calculating the extreme value mixed wave elements of the near-shore water area, but the device for realizing the method for calculating the extreme value mixed wave elements of the near-shore water area comprises, but is not limited to, the structure of the system for calculating the extreme value mixed wave elements of the near-shore water area, and all the structural deformation and replacement of the prior art according to the principle of the application are included in the protection scope of the application.
The following describes the system for estimating the extreme mixed wave elements in the offshore water area provided by the present embodiment in detail with reference to the drawings.
The embodiment provides a system for calculating extreme mixed wave elements of a near-shore water area, which comprises:
referring to fig. 8, a schematic structural diagram of an offshore water extremum mixed wave element estimating system according to an embodiment of the application is shown. As shown in fig. 8, the system for estimating the extreme mixed wave elements in the offshore water area comprises: an acquisition module 81, a data processing module 82, a feature extraction module 83, a model construction module 84, a data calculation module 85, and a conversion module 86.
The acquiring module 81 is used for acquiring analysis wind field data of a target area; the analyzing the wind field data includes: wind speed and direction.
In this embodiment, the target area is acquired and wind field data is analyzed.
In this embodiment, the wind farm uses CFSR from the us ocean and atmospheric management agency forecasting center to analyze wind farm data.
The data processing module 82 is connected to the obtaining module 81, and is configured to construct an ocean scale wind wave numerical model based on the analysis wind field data, so as to obtain an ocean scale wave database with a long time sequence.
In the embodiment, an ocean scale wind wave numerical model based on an energy balance equation is built, CFSR analysis wind field data of the ocean and atmosphere management agency prediction center is adopted in the wind field, white dissipation coefficients in the ocean scale wind wave numerical model greatly affect calculation results, the wind field data are used as model rating parameters, model rating verification is carried out by using actual measurement wave data of satellites and buoys, accordingly, proper dissipation coefficients are determined, ocean quarter wind or typhoon generated wind waves and long-period surge waves are inverted by using the rated models, verification is carried out by using actual measurement wave data of the satellites and buoys, and the total calculation period is not less than 30 years, so that an ocean scale wave database with long time sequence is obtained.
And carrying out data preprocessing on the analysis wind field data to obtain preprocessed analysis wind field data. The data preprocessing comprises the following steps: any one or more of data conversion, data screening, data cleansing, outlier handling, missing value filling and smoothing.
In this embodiment, the re-analysis wind field data for a total calculated period of not less than 30 years is collected. And then preprocessing the collected historical meteorological data to ensure the accuracy and the credibility of the data. Wherein the analyzing the wind field data comprises: meteorological data such as wind speed and wind direction. The meteorological data further includes: historical meteorological data, real-time meteorological data and other relevant data. These data can ensure the accuracy of the inversion.
And constructing an ocean scale wind wave numerical model based on the preprocessed analysis wind field data, and performing calibration verification on the model by using actual measurement wave data of satellites and buoys, and determining proper model key parameters to form the calibration verified ocean scale wind wave numerical model.
In this embodiment, based on the historical meteorological data in the wind farm data after preprocessing in the above steps, the method includes: and constructing an inversion model by using related data such as wave height, wave direction, wave period and the like, and inverting meteorological data. And verifying the preprocessed historical meteorological data and the inversion model to obtain a preliminary inversion result.
And calculating ocean wave elements for not less than 30 years based on the rated and verified ocean scale wind wave numerical model to obtain an ocean scale wave database with long time sequence.
In this embodiment, the result obtained by inversion calculation is verified by using the measured wave data of the satellite and the buoy, so as to ensure the authenticity and reliability of the result. After the verified inversion result is obtained, further data analysis is carried out to mine rules and meanings contained in ocean scale wave data displayed by the data, and finally the rules and meanings are displayed in a graphical mode, so that a user can better understand and analyze the inversion result.
The feature extraction module 83 is configured to extract wave data of feature points of the open sea based on the ocean scale wave database of the long time sequence, obtain a time sequence of the open sea elements of the target area, and calculate the open sea elements of different reproduction periods in different directions.
In this embodiment, the wave element time sequence (wave height, wave direction, wave period) of the open sea of the quasi-target research area is extracted from the ocean scale wave database, and the open sea wave elements in different directions and in different reproduction periods are calculated by using a pearson iii-type curve fitting line method.
And extracting wave data of the feature points of the open sea based on the ocean scale wave database of the long-time sequence to obtain an open sea wave element time sequence.
And performing data fitting based on the wave heights, wave directions and wave periods in different periods in the ocean scale wave database of the long-time sequence to obtain a probability distribution function of the ocean scale wave data.
In the embodiment, data such as medium wave height, wave direction, wave period and the like of the ocean scale wave database with long time sequence are cleaned, screened and processed to remove abnormal values and missing values; fitting is carried out according to the processed wave height, wave direction, wave period and other data, and a probability distribution function of wave elements is obtained.
Determining an overseas ocean wave element parameter according to the probability distribution function; the external sea wave element parameters include: mean, standard deviation, and skewness of the overseas wavelet elements.
In this embodiment, parameters such as mean, standard deviation, and deflection of wave elements are determined by using a maximum public likelihood estimation method according to data such as mid-wave height, wave direction, wave period, and the like of the ocean scale wave database of the long-time sequence and a probability distribution function obtained by fitting.
Based on the external sea wave element time sequence, an external sea wave element time sequence of different reproduction periods in different directions is calculated by adopting a Pearson III type curve fitting line method, so that the external sea wave element time sequence is obtained.
In the embodiment, according to the Pearson III type curve and the determined parameters such as the mean value, standard deviation, skewness and the like of the wave elements, the frequency distribution of the wave elements in different reproduction periods is established by calculating probability density functions and cumulative distribution; and then according to the frequency distribution of different reproduction periods, calculating corresponding wave elements, namely: wave height, wave direction, wave period, etc., thereby obtaining an external sea wave element time sequence.
The model construction module 84 is configured to construct a small-scale wave propagation numerical model of the offshore area based on the time series of the external sea wave elements in different reproduction periods in different directions, so as to obtain the surge elements in different reproduction periods in different designed water levels in the offshore area; and constructing a wave numerical model of the offshore small wind area based on the engineering design wind speed and wind direction data to obtain wind wave elements of different water levels of the offshore area in different directions and different reproduction periods.
Building a small-scale near-shore area wave propagation numerical model based on Boussinesq equation, calculating terrain by adopting structural grids, inputting the external sea wave elements in different directions and in different reproduction periods calculated by the steps of the boundary, setting different design water levels, and obtaining the surge elements (wave height, wave period and average wave direction) in different directions and different reproduction periods of the near-shore area by considering the comprehensive effects of shallow water deformation, bottom friction dissipation, hydraulic structures and the like on wave propagation deformation
In the embodiment, a small-scale near-shore area wave propagation numerical model based on a Boussinesq equation is built, and model parameters and boundary conditions are determined. And (3) adopting a structural grid to manufacture a calculated terrain, inputting the external sea wave elements in different directions and in different reproduction periods as calculated boundaries, and setting different design water levels. And calculating surge elements of different designed water levels in different directions and different reproduction periods in the near-shore area based on the small-scale near-shore area wave propagation numerical model.
Specifically, according to the fundamental theory of fluid dynamics and wave propagation, establishing a Boussinesq equation; and determining parameters and boundary conditions of the model according to the overseas wavelet element time sequence. Then, a numerical method is adopted to construct a small-scale near-shore area wave propagation numerical model of the Boussinesq equation, verification and parameter tuning are carried out on the model, and the accuracy and reliability of the model are improved.
Uniformly dividing grids according to a proportion on the boundary of the target region division model, and setting grid density; setting calculation parameters, selecting proper calculation precision, iteration calculation times and the like; and then carrying out numerical calculation by utilizing the structural grid and the set parameters so as to simulate wave change. Meanwhile, different design water levels are set; and the comprehensive effects of shallow water deformation, bottom friction dissipation, hydraulic structures and the like on wave propagation deformation are considered. Then, comparing wave change conditions at different moments, and analyzing wave change trend; adjusting calculation parameters and grid division through the fitting degree of the evaluation result and the actual waves; the positions of the grid points may be further adjusted to improve the accuracy of the calculation.
Based on the established small-scale near-shore area wave propagation numerical model, calculating surge elements with different design water levels and different directions, such as: wave height, period, direction, etc. These elements can be obtained by analyzing the simulation result. And then analyzing the calculated surge elements, and comparing differences of the surge elements in different design water levels and different directions. Meanwhile, the propagation rule and influence factors of the surge can be analyzed.
And constructing a wave numerical model of the near-shore small wind area to obtain wind wave elements of different design water levels in different directions and different reproduction periods in the near-shore area.
Building an energy balance equation-based near-shore small wind area wave numerical model, manufacturing and calculating a terrain by adopting a non-structural grid, setting different design water levels by taking wind speeds in different directions and different reproduction periods into consideration for input conditions, taking effects of white dissipation and the like into consideration, calculating small wind area waves by adopting the results in the steps of dissipation coefficients, and obtaining wave elements (wave height, wave period and average wave direction) in different directions and different reproduction periods of different design water levels in the near-shore area.
In the embodiment, an offshore small wind area wave numerical model is constructed based on an energy balance equation. And adopting an unstructured grid to manufacture a calculated terrain, determining boundary conditions of the offshore small wind area wave numerical model, adopting an open boundary, and setting different design water levels, design wind speeds and wind directions. And calculating the stormy waves of the small wind area by considering the dissipation effect of the white cap, and processing the calculation result to obtain the stormy wave elements of different water levels in different directions and different reproduction periods in the near-shore area. Converting the stormy wave elements in the unstructured grid data format into stormy wave elements in different water levels, different directions and different reproduction periods in the offshore area of the structured grid data format in an interpolation mode.
Specifically, an energy balance equation and a substance derivative equation are determined, as well as boundary conditions and initial conditions, and then discretized.
The selection of a suitable terrain non-structural grid enables accurate characterization of complex terrain features in the near shore region. The boundary conditions are input while the wind speeds in different directions and in different reproduction periods are considered. Setting different design water levels according to the user demands, such as: tide level, storm tide level, etc.
A dissipation ratio model, such as the Smith model or Munk model, was used to simulate the effects of white cap dissipation. Calculating the wind wave of the small wind area by calculating the energy balance equation after dispersion; and post-processing the calculation results, such as drawing wave images, calculating statistics of wave heights, wave periods, average wave directions and the like.
The result of the offshore small wind area wave numerical model based on the energy balance equation is greatly influenced by the white cap dissipation coefficient, but is superior to an empirical formula in the aspects of simulating complex terrain, calculating speed, visualizing and the like.
And converting the wind wave element data of the unstructured grid into the wind wave element data of the structured grid by adopting an interpolation method. The offshore area is divided into a plurality of structural grids according to the designed water level and direction. And then interpolating calculation is carried out according to the unstructured grid data, so as to obtain the wind wave element values on the structured grid. Analyzing and adjusting the interpolation calculation result to obtain the stormy wave elements in different water levels of different designs in different directions and in different reproduction periods in the near-shore region. The wind wave element data has the characteristics of everywhere, smoothness and the like.
Therefore, the small wind area wind wave can be calculated by adopting the set models with different working conditions, and the wind wave elements (wave height, wave period and average wave direction) with different water levels in different directions and different reproduction periods in different designed water levels in the near-shore area can be obtained.
The data calculation module 85 is configured to calculate a mixed wave element for each grid point based on the swell element and the stormy element.
And superposing the surge elements and the wave elements of different water levels of different designs in different directions and different reproduction periods in the near-shore area of the structural grid data format, and calculating to obtain the mixed wave elements of each grid point. And leading the calculated mixed wave elements of each grid point into a structural grid to obtain a mixed wave database in a structural grid data format with different design water levels, different directions and different reproduction periods in a near-shore area.
In this embodiment, when two series of waves of the swell and the stormy waves meet, a mixed swell is formed, and the swell wave elements and the stormy wave elements of different reproduction periods in different directions of different design water levels in the near-shore area of the structural grid data format are subjected to superposition calculation, so that the mixed swell wave elements of each grid point are obtained. And (3) leading the calculated mixed wave elements (such as wave height, wave period and average wave direction of the mixed waves) of each grid point into the structural grid to obtain a mixed wave database in the structural grid data format of different water levels of different design in the near-shore region in different directions and different reproduction periods.
The conversion module 86 is configured to construct a conversion function of the mixed wave element, and calculate an extremum mixed wave element of a certain reproduction period in a certain direction of a certain design water level at any position near shore by using the conversion function.
And constructing the transformation functions of the wave elements, the water level, the direction, the reproduction period, the abscissa and the ordinate of the mixed waves in the offshore area by a linear difference method. And calculating extreme value mixed wave elements of a certain reproduction period in a certain direction of a certain design water level at any position near the shore based on the conversion function.
In this embodiment, the conversion relationship between the offshore area hybrid wave elements and the water level, direction, reproduction period, abscissa and ordinate is determined by a linear function. Then, a linear difference model is built according to the linear function, and the coefficient value is obtained through solving by means of a least square method and other mathematical methods. And then the wave elements of the mixed waves in the actual near-shore area, the water level, the direction, the reproduction period, the abscissa and the ordinate are input into the model, so as to calculate the extreme value mixed wave elements of a certain designed water level at any near-shore position in a certain direction and a certain reproduction period.
The system for calculating the extreme value mixed wave elements of the offshore water area is built by the model for calculating the extreme value mixed wave elements of the offshore water area, a long-term ocean scale wave field can be built on the premise of lacking long-term actual measurement wave data, ocean storm and long-period storm generated by ocean storm or typhoon can be inverted more accurately, the analysis of the extreme value of the ocean waves can be carried out, the extreme value calculated to the offshore calculation storm, the storm of a small storm area can be calculated according to the wind speed, then the storm and the storm elements with different data formats on the offshore are overlapped and calculated, a more reasonable and accurate offshore mixed wave result is obtained, and a wave database and a conversion function are built, so that data required by an extraction project are more convenient, guidance significance is provided for actual engineering design and research, and the problems of low accuracy and safety and poor stability of ocean offshore wave monitoring work in the prior art are solved.
It should be noted that, it should be understood that the division of the modules of the above system is merely a division of a logic function, and may be fully or partially integrated into a physical entity or may be physically separated. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; the method can also be realized in a form of calling software by a processing element, and the method can be realized in a form of hardware by a part of modules. For example, the x module may be a processing element that is set up separately, may be implemented in a chip of the system, or may be stored in a memory of the system in the form of program code, and the function of the x module may be called and executed by a processing element of the system. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.
The above modules may be one or more integrated circuits configured to implement the above methods, for example: one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more microprocessors (digital signal processor, abbreviated as DSP), or one or more field programmable gate arrays (FieldProgrammable Gate Array, abbreviated as FPGA), or the like. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Referring to fig. 9, a schematic structural diagram of an apparatus for estimating an extreme hybrid wave element in a near-shore water area according to an embodiment of the invention is shown. As shown in fig. 9, the present embodiment provides a device for estimating an extremum mixed wave element in a near-shore water area, the device for estimating an extremum mixed wave element in a near-shore water area comprising: a processor 91 and a memory 92; the memory 92 is used for storing a computer program; the processor 91 is connected to the memory 92 and is configured to execute a computer program stored in the memory 92, so that the device for estimating the extreme mixed wave element of the offshore waters performs the steps of the method for estimating the extreme mixed wave element of the offshore waters as described above.
Preferably, the memory may comprise random access memory (Random Access Memory, abbreviated as RAM), and may further comprise non-volatile memory (non-volatile memory), such as at least one magnetic disk memory.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field programmable gate arrays (Field Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
In summary, the method, the system, the medium and the device for calculating the extreme mixed wave elements in the offshore water area provided by the application have the following beneficial effects:
according to the method for calculating the extreme value mixed wave elements of the offshore water area, provided by the application, on the premise of lacking long-term actual measurement wave data, a long-term ocean scale wave field is built, the ocean scale wave field can be more accurately inverted, the storm wave generated by the ocean cross wind or typhoon and the long-period storm wave are more accurately analyzed, the extreme value calculated value is converted to the offshore calculated storm wave, the storm wave of a small wind area is calculated according to the wind speed, then the storm wave and the storm wave elements in different data formats on the offshore are subjected to superposition calculation, a more reasonable and accurate offshore mixed wave result is obtained, and a wave database and a conversion function are built, so that the data required by the extraction engineering are more convenient, and the method has more guiding significance on actual engineering design and research. The application improves the convenience, systematicness and data precision of data extraction in the technology of calculating the extreme value mixed wave elements in the offshore water area, and improves the accuracy, safety and stability of the offshore wave monitoring work.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. Accordingly, it is intended that all equivalent modifications and variations of the invention be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (10)
1. A method for calculating extreme mixed wave elements of a near-shore water area is characterized by comprising the following steps:
acquiring target area and analyzing wind field data; the analyzing the wind field data includes: wind speed and direction;
constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database with a long time sequence;
extracting wave data of the open sea feature points based on the ocean scale wave database of the long-time sequence to obtain an open sea wave element time sequence of the target area; based on the external sea wave element time sequence, calculating external sea wave elements in different directions and at different reproduction periods by adopting a Pearson III type curve fitting line method;
Constructing a small-scale wave propagation numerical model of the near-shore area based on the external sea wave elements in different directions and at different reproduction periods to obtain surge elements in different water levels in different directions and at different reproduction periods of the near-shore area;
constructing a wave numerical model of the offshore small wind area based on engineering design wind speed and wind direction data to obtain wave elements of different water levels of the offshore area in different directions and different reproduction periods;
calculating a mixed wave element for each grid point based on the swell element and the stormy element;
and constructing a conversion function of the mixed wave elements, and calculating extreme value mixed wave elements of a certain design water level and a certain reproduction period in a certain direction at any position near the shore by using the conversion function.
2. The method for estimating extreme mixed wave elements in a near shore water area according to claim 1, wherein constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database of a long time sequence comprises the following steps:
performing data preprocessing on the analysis wind field data to obtain preprocessed analysis wind field data; the data preprocessing comprises the following steps: any one or more of data format conversion, data cleansing, outlier processing, missing value filling and smoothing processing;
Constructing an ocean scale wind wave numerical model based on the preprocessed analysis wind field data, carrying out calibration verification on the model by using actual measurement wave data of satellites and buoys, and determining proper model key parameters to form a calibrated and verified ocean scale wind wave numerical model;
and calculating ocean wave elements for not less than 30 years based on the rated and verified ocean scale wind wave numerical model to obtain an ocean scale wave database with long time sequence.
3. The method for calculating the extreme mixed wave elements of the offshore water area according to claim 2, wherein the key parameters of the model comprise: white cap dissipation factor; the white cap dissipation coefficient formula is:
C ds ＝4.5+(V-25)/6
wherein C is ds Expressed as white cap dissipation factor, dimensionless; v is expressed as wind speed in units of: m/s.
4. The method for calculating the extreme value mixed wave elements of the offshore water area according to claim 1, wherein the step of extracting the wave data of the feature points of the open sea based on the ocean scale wave database of the long time sequence to obtain the time sequence of the open sea elements of the target area and calculating the open sea elements of different reproduction periods in different directions comprises the following steps:
based on the ocean scale wave database of the long-time sequence, extracting wave data of the feature points of the open sea to obtain an open sea element time sequence;
Based on the external sea wave element time sequence, the external sea wave elements in different directions and in different reproduction periods are calculated by adopting a Pearson III type curve fitting line method.
5. The method for calculating the extreme value mixed wave elements of the offshore water area according to claim 1, wherein the step of constructing a small-scale wave propagation numerical model of the offshore area based on the external sea wave elements in different directions and different reproduction periods to obtain the surge elements in different directions and different reproduction periods of different design water levels of the offshore area comprises the following steps:
constructing a small-scale offshore area wave propagation numerical model based on the external sea wave elements in different directions and at different reproduction periods, and determining the boundary condition of the model;
adopting a structural grid to manufacture a calculation terrain, inputting the external sea wave elements in different directions and at different reproduction periods as calculation boundaries, and setting different design water levels;
and calculating surge elements of different designed water levels in different directions and different reproduction periods in the near-shore area based on the small-scale near-shore area wave propagation numerical model.
6. The method for calculating the extreme value mixed wave elements of the offshore water area according to claim 1, wherein the method for constructing the wave numerical model of the offshore small wind area based on the engineering design wind speed and wind direction data to obtain the wave elements of the offshore area with different design water levels, different directions and different reproduction periods comprises the following steps:
Constructing a wave numerical model of the offshore small wind area based on an energy balance equation;
adopting an unstructured grid to manufacture calculated terrain, determining boundary conditions of the offshore small wind area wave numerical model, adopting an open boundary, and setting different design water levels, design wind speeds and wind directions;
calculating the stormy waves of the small wind area by considering the dissipation effect of the white cap, and processing the calculation result to obtain the stormy wave elements of the near-shore area in different water levels, different directions and different reproduction periods;
converting the stormy wave elements in the unstructured grid data format into stormy wave elements in different water levels, different directions and different reproduction periods in the offshore area of the structured grid data format in an interpolation mode.
7. The method for estimating an extreme mixed wave element in a near shore water area according to claim 1, wherein calculating the mixed wave element for each grid point based on the swell element and the stormwater element comprises the steps of:
overlapping the surge elements and the wave elements of different water levels of different designs in different directions and different reproduction periods in the near shore region of the structural grid data format, and calculating to obtain the mixed wave elements of each grid point;
the calculated mixed wave elements of all grid points are led into the structural grid to obtain a mixed wave database with structural grid data formats of different water levels of different designs in the near-shore area in different directions and different reproduction periods;
The calculation formula of the mixed wave elements of each grid point is as follows:
T H ＝MAX(T S ,T W )
MWD H ＝AVERAGE(MDD S ,MWD W )
wherein H is H Representing the wave height of the hybrid wave, units: m; h S Wave height, units: m; h W Wave height, units: m; t (T) H The wave period, in units of: s; t (T) S The wave period, in units of: s; t (T) W Wave period representing stormy waves, unit: s; MWD (measurement-while-drilling) MWD (measurement-while- H Mean direction of the mixed wave, unit: a deg; MDD (minimization drive test) S Mean direction of surge, unit: a deg; MWD (measurement-while-drilling) MWD (measurement-while- W Mean wave direction of wind wave, unit: and deg.
8. The method for estimating an extreme mixed wave element in a near-shore water area according to claim 1, wherein constructing a transfer function of the mixed wave element, calculating the extreme mixed wave element in a certain direction and a certain reproduction period of a certain designed water level at any position near shore by using the transfer function comprises the following steps:
constructing a transformation function of a mixed wave element and water level, direction, reproduction period, abscissa and ordinate of a near-shore area by a linear difference method;
based on the conversion function, extreme value mixed wave elements of a certain design water level at any position near the shore in a certain direction and a certain reproduction period are calculated;
The calculation formula of the conversion function is as follows:
H H ＝f 1 (E,D,N,X,Y)
T H ＝f 2 (E,D,N,X,Y)
MWD H ＝f 3 (E,D,N,X,Y)
wherein E is expressed as the water level of the offshore area in units of: m; d represents direction, unit: a deg; n is expressed as reproduction period, unit: year; x is represented by abscissa, unit: m; y is expressed as the vertical directionCoordinates, units: m; f (f) 1 Conversion functions expressed as wave height of the offshore hybrid wave with respect to 5 parameters of water level, direction, reproduction period, abscissa and ordinate; f (f) 2 Conversion functions expressed as wave periods of the offshore hybrid waves with respect to 5 parameters of water level, direction, reproduction period, abscissa and ordinate; f (f) 3 The average wave direction of the waves, expressed as an offshore hybrid wave, is a transfer function of 5 parameters with respect to water level, direction, reproduction period, abscissa and ordinate.
9. An offshore water extremum mixed wave element reckoning system, comprising:
the acquisition module is used for acquiring the target area and analyzing wind field data; the analyzing the wind field data includes: wind speed and direction;
the data processing module is used for constructing an ocean scale wind wave numerical model based on the analysis wind field data to obtain an ocean scale wave database with a long time sequence;
the feature extraction module is used for extracting wave data of the feature points of the open sea based on the ocean scale wave database of the long-time sequence to obtain an open sea element time sequence of the target area; based on the external sea wave element time sequence, calculating external sea wave elements in different directions and at different reproduction periods by adopting a Pearson III type curve fitting line method;
The model construction module is used for constructing a small-scale wave propagation numerical model of the near-shore area based on the external sea wave elements in different directions and in different reproduction periods to obtain surge elements in different water levels in different directions and in different reproduction periods of the near-shore area; constructing a wave numerical model of the offshore small wind area based on engineering design wind speed and wind direction data to obtain wave elements of different water levels of the offshore area in different directions and different reproduction periods;
the data calculation module is used for calculating the mixed wave element of each grid point based on the surge element and the wind wave element;
and the conversion module is used for constructing a conversion function of the mixed wave element, and calculating the extremum mixed wave element of a certain reproduction period in a certain direction of a certain design water level at any position near the shore by using the conversion function.
10. An offshore water extremum mixed wave element calculating device, which is characterized by comprising: a processor and a memory;
the memory is used for storing a computer program;
the processor is connected to the memory, and is configured to execute a computer program stored in the memory, so that the device for estimating the extreme value mixed wave element in the offshore waters performs the method for estimating the extreme value mixed wave element in the offshore waters according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311215952.0A CN117195775B (en) | 2023-09-20 | 2023-09-20 | Method, system, medium and device for calculating extreme mixed wave elements of offshore water area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311215952.0A CN117195775B (en) | 2023-09-20 | 2023-09-20 | Method, system, medium and device for calculating extreme mixed wave elements of offshore water area |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117195775A true CN117195775A (en) | 2023-12-08 |
| CN117195775B CN117195775B (en) | 2024-04-05 |
Family
ID=88986785
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311215952.0A Active CN117195775B (en) | 2023-09-20 | 2023-09-20 | Method, system, medium and device for calculating extreme mixed wave elements of offshore water area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117195775B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104331599A (en) * | 2014-09-30 | 2015-02-04 | 江苏省交通规划设计院股份有限公司 | Unstructured grid nesting wave numerical simulation method |
| CN105389468A (en) * | 2015-11-06 | 2016-03-09 | 中国海洋大学 | Rip current forecasting method |
| CN105787281A (en) * | 2016-03-24 | 2016-07-20 | 国家海洋环境预报中心 | Fusion inversion method and device for sea wave significant wave height field |
| CN106844859A (en) * | 2016-12-21 | 2017-06-13 | 河海大学 | A kind of Simulations of Water Waves Due To Landslides computational methods |
| CN108920877A (en) * | 2018-08-02 | 2018-11-30 | 中交第四航务工程勘察设计院有限公司 | A kind of global wave method for numerical simulation based on MIKE21-SW model |
| CN110728042A (en) * | 2019-09-29 | 2020-01-24 | 河海大学 | Method for rapidly forecasting long-time scale coast wave elements |
| CN114818543A (en) * | 2022-05-20 | 2022-07-29 | 中国科学院南京地理与湖泊研究所 | Shallow lake typical recurrence period characteristic wind wave calculation method |
| CN115114564A (en) * | 2022-08-04 | 2022-09-27 | 中国海洋大学 | Method and system for separating wind waves and surge waves in sea wave data |
| CN115828637A (en) * | 2023-01-09 | 2023-03-21 | 交通运输部天津水运工程科学研究所 | Method and system for determining extreme parameters by combining multiple factors of offshore wind, wave and tide level |
-
2023
- 2023-09-20 CN CN202311215952.0A patent/CN117195775B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104331599A (en) * | 2014-09-30 | 2015-02-04 | 江苏省交通规划设计院股份有限公司 | Unstructured grid nesting wave numerical simulation method |
| CN105389468A (en) * | 2015-11-06 | 2016-03-09 | 中国海洋大学 | Rip current forecasting method |
| CN105787281A (en) * | 2016-03-24 | 2016-07-20 | 国家海洋环境预报中心 | Fusion inversion method and device for sea wave significant wave height field |
| CN106844859A (en) * | 2016-12-21 | 2017-06-13 | 河海大学 | A kind of Simulations of Water Waves Due To Landslides computational methods |
| CN108920877A (en) * | 2018-08-02 | 2018-11-30 | 中交第四航务工程勘察设计院有限公司 | A kind of global wave method for numerical simulation based on MIKE21-SW model |
| CN110728042A (en) * | 2019-09-29 | 2020-01-24 | 河海大学 | Method for rapidly forecasting long-time scale coast wave elements |
| CN114818543A (en) * | 2022-05-20 | 2022-07-29 | 中国科学院南京地理与湖泊研究所 | Shallow lake typical recurrence period characteristic wind wave calculation method |
| CN115114564A (en) * | 2022-08-04 | 2022-09-27 | 中国海洋大学 | Method and system for separating wind waves and surge waves in sea wave data |
| CN115828637A (en) * | 2023-01-09 | 2023-03-21 | 交通运输部天津水运工程科学研究所 | Method and system for determining extreme parameters by combining multiple factors of offshore wind, wave and tide level |
Non-Patent Citations (5)
| Title |
|---|
| 应王敏;郑桥;朱陈陈;朱业;车助镁;楚栋栋;张继才;: "基于SWAN模式的"灿鸿"台风浪数值模拟", 海洋科学, no. 04, 15 April 2017 (2017-04-15) * |
| 李绍武;梁超;庄茜;: "SWAN风浪成长模型在近海设计波浪要素推算中的应用", 港工技术, no. 02, 15 April 2012 (2012-04-15) * |
| 王岳峰: "深水航道工程对长江口波浪影响研究及多年一遇波浪要素计算", 《中国优秀硕士学位论文全文数据库 基础科学辑》, no. 03, 15 March 2018 (2018-03-15), pages 010 - 52 * |
| 王科华;张军;: "以长周期涌浪影响为主的海域近岸极值波浪推算方法", 中国港湾建设, no. 08, 25 August 2016 (2016-08-25) * |
| 陈晓斌;周林;史文丽;李靖;陈璇;: "台风"梅花"风浪场和涌浪场特征分析", 海洋科学进展, no. 01, 15 January 2013 (2013-01-15) * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117195775B (en) | 2024-04-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guedes Soares et al. | An operational wave forecasting system for the Portuguese continental coastal area | |
| Mateo et al. | Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods | |
| Shimada et al. | Accuracy and characteristics of offshore wind speeds simulated by WRF | |
| AU2017352549A1 (en) | Method and device for calculating power generation of wind farm | |
| Wei et al. | Trivariate joint probability model of typhoon-induced wind, wave and their time lag based on the numerical simulation of historical typhoons | |
| Tshimanga | Hydrological uncertainty analysis and scenario-based streamflow modelling for the Congo River Basin | |
| CN114049545B (en) | Typhoon intensity determining method, system, equipment and medium based on point cloud voxels | |
| CN110347671A (en) | The method for constructing wind energy on the sea data bank and offshore wind power generation amount database | |
| CN115238947A (en) | Social and economic exposure degree estimation method for drought, waterlogging and sudden turning event under climate change | |
| KR20160073604A (en) | Method and system for analyzing ocean circulation in coastal areas | |
| Sheng et al. | A regional testbed for storm surge and coastal inundation models—an overview | |
| CN117195775B (en) | Method, system, medium and device for calculating extreme mixed wave elements of offshore water area | |
| Robertson | Wave energy assessments: quantifying the resource and understanding the uncertainty | |
| Mortensen | 46200 Planning and Development of Wind Farms: Wind resource assessment using the WAsP software | |
| KR102337369B1 (en) | Device and method for dynamic-oriented diagnostics of climate prediction model on a subseasonal scale | |
| Taflanidis et al. | Probabilistic hurricane surge risk estimation through high-fidelity numerical simulation and response surface approximations | |
| Marinho et al. | Wave regime characterization in the northern sector of Patos Lagoon, Rio Grande do Sul, Brazil | |
| Qin et al. | Topological Guided Detection of Extreme Wind Phenomena: Implications for Wind Energy | |
| Stefanakos et al. | Climatic forecasting of wind and waves using fuzzy inference systems | |
| Anuruddhika et al. | Forecasting flood inundation areas of Attanagalu Oya | |
| Petrukhina et al. | A technology for predictive estimation of meteorological parameters on the basis of the global climate model CFSv2 | |
| Christakis et al. | A Computational Methodology for Assessing Wind Potential | |
| CN118332964A (en) | Prediction method and system for ocean near-inertial flow | |
| Melby et al. | Hurricane water level prediction using surrogate modeling | |
| Wang et al. | Current Effect on Wave Condition around Island in the South China Sea |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |