KR102661625B1 - System and method for risk assessment of wave overtopping - Google Patents

Abstract

In the wave overtopping risk assessment system, a collection unit configured to collect basic marine data including at least one of image data or meteorological data, a range value of a plurality of indicator factors for a predetermined time based on the collected basic marine data A prediction unit configured to predict wave overtopping prediction data according to the above, a calculation unit configured to calculate a wave overtopping risk index based on the predicted wave overtopping prediction data, and storing at least one of the marine basic data, the wave overtopping prediction data, and the overtopping risk index. It includes a storage unit configured to do so.

Description

Wave overtopping risk assessment system and method {SYSTEM AND METHOD FOR RISK ASSESSMENT OF WAVE OVERTOPPING}

This disclosure relates to a wave overtopping risk assessment system and method, and more specifically, to collect basic marine data, predict overtopping prediction data based on the collected basic marine data, and calculate and provide a wave overtopping risk index that measures overtopping risk. It relates to a wave overtopping risk assessment system and method.

The Korean Peninsula is a peninsula surrounded by the sea on three sides, and the coasts and sea areas on the three sides show different characteristics. The East Sea is larger than the West Sea, and the average depth of the West Sea is less than 100m, while the East Sea's water depth is more than 1,600m, making it deeper than the West Sea. Depending on the water depth, water temperature changes and tides vary. The East Sea is relatively deep, so there are severe changes in water temperature, and cold and warm currents intersect, causing severe changes in marine weather, but the tidal differences are small. The West Sea has a relatively low water depth, but is surrounded by land and has large tidal differences. There is a need to predict risks of natural disasters such as overcoming waves and typhoons based on these natural phenomena (e.g., water depth, tides, waves, and tsunamis). In addition, as the frequency and scale of natural disasters, such as sea level rise and typhoons due to climate change, increase, technology to respond to large-scale disasters is needed.

Overtopping refers to a phenomenon in which sea water goes over the crest of a breakwater or seawall due to the rising action of waves. In general, flood damage in urban areas adjacent to coastal areas occurs in a complex form that includes not only the characteristics of general urban flood damage, but also the rise in tide level and wave overtopping in the coastal area. Here, wave overturning causes coastal flooding every year and causes damage to property and human life. Therefore, it is important to predict the risk of such wave overtopping.

However, research considering the characteristics of coastal urban areas at home and abroad and monitoring of such overtopping waves are insufficient. Although there have been various studies on improving the prediction accuracy of coastal weather until recently, there is a lack of marine weather experts and marine numerical forecast models. As a result, the accuracy of coastal and marine weather is low, and there is a high possibility of coastal and marine safety accidents occurring due to low accuracy of coastal and marine weather. In addition, because overtopping waves occur instantly and suddenly due to swell waves, etc., it is difficult to predict the risk of overtopping waves, and there is a problem that a lot of time and money are required to predict the risk based on various variables. Accordingly, it is difficult to predict the risk of wave overtopping based on various variables and provide it as an indicator.

In order to solve the above problems, the present disclosure provides a wave overtopping risk assessment system and method that collects various basic marine data, generates overtopping prediction data, and predicts the risk of overtopping according to the overtopping risk index of the generated overtopping prediction data. to provide.

According to an embodiment of the present disclosure, in a wave overtopping risk assessment system, a collection unit configured to collect basic marine data including at least one of image data or meteorological data, a predetermined time based on the collected basic marine data A prediction unit configured to predict wave overtopping prediction data according to the range values of a plurality of indicator factors for, a calculation unit configured to calculate a wave overtopping risk index based on the predicted wave overtopping prediction data, and the marine basic data, the wave overtopping prediction data, and It includes a storage unit configured to store at least one of the overtopping risk indices.

According to one embodiment, the prediction unit is configured to predict the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data.

According to one embodiment, the probability of individual wave overtopping occurrence is calculated using Equation 3 below based on the wave overtopping prediction data.

According to one embodiment, the maximum individual wave overtopping amount is calculated using Equation 4 below based on the wave overtopping prediction data.

According to one embodiment, a plurality of indicator factors include wind speed, wind direction, wave height, significant wave height, wave height, incident wave height, clearance height, wave direction, wave period, peak period, duration, coastal slope, coastal water depth, visibility distance, and Contains at least one of the tide levels.

According to one embodiment, the calculation unit is a first index calculation module configured to calculate a first wave overtopping risk index using wave overtopping prediction data including a condition grade predicted based on the significant wave height and the range value of the wave period; A second index calculation module configured to calculate a second overtopping risk index based on wave overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight, based on the plurality of indicator factors, the note Each generated by applying a preset ground surface grade according to at least one of the average range value of the wave height, the wind speed, or the change value for the range value of the tidal level, and a weight according to each preset ground surface grade of the plurality of ground factors. A third index calculation module configured to calculate a third wave overtopping risk index according to a preset risk by combining overtopping prediction data, or based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth. It includes a fourth index calculation module configured to calculate the maximum impact due to ground friction and calculate the fourth overtopping risk index according to the maximum impact.

According to one embodiment, the first index calculation module is configured to calculate the condition grade based on the Douglas swell grade table and calculate the first overtopping risk index based on the calculated condition grade.

According to one embodiment, in the second index calculation module, the sensitivity index includes at least one of human sensitivity, material sensitivity, and topographical sensitivity.

According to one embodiment, the second index calculation module, the location weight includes a weight for at least one region among the East Sea, West Sea, and South Sea, and calculates the second wave overtopping risk index according to Equation 1 below: .

According to one embodiment, the third index calculation module calculates a first weight with a smaller error among a plurality of weights calculated through AHP analysis.

According to one embodiment, the fourth index calculation module includes at least two index factors among the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth collected based on the collected basic ocean data. Based on this, wave overtopping prediction data including maximum wave height and maximum wave period are calculated.

According to one embodiment, the fourth index calculation module includes at least one of the height of the breakwater, the slope of the breakwater, the breakwater friction force, the preset safety distance range, and the preset physical condition based on the collected basic marine data. .

According to one embodiment, the fourth index calculation module calculates the maximum impact due to ground friction based on the calculated overtopping prediction data, and the calculated maximum impact is calculated as the fourth overtopping risk index through an instability probability model. Calculate .

According to one embodiment, the calculation unit further includes a simulation module configured to select and calculate the overtopping risk index with a small error through simulation.

According to an embodiment of the present disclosure, in a method for monitoring wave overturning, collecting basic marine data including at least one of image data or weather data by a collection unit, and collecting basic marine data including at least one of image data or meteorological data by a prediction unit. Predicting wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on It includes storing at least one of basic data, the wave overtopping prediction data, and the wave overtopping risk index in a storage unit.

According to one embodiment, the step of predicting wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected basic marine data, by the prediction unit, includes: It is configured to predict the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the data.

According to one embodiment, the step of calculating, by the calculation unit, a wave overtopping risk index based on the predicted wave overtopping prediction data, the probability of occurrence of an individual wave overtopping amount is determined by Equation 3 below based on the overtopping prediction data. It further includes a calculating step.

According to one embodiment, the step of calculating the wave overtopping risk index based on the predicted wave overtopping prediction data by the calculation unit calculates the maximum individual wave overtopping amount using the following equation based on the overtopping prediction data. .

According to one embodiment, the plurality of indicator factors include wind speed, wind direction, wave height, significant wave height, wave height, incident wave height, clearance height, wave direction, wave period, peak period, duration, coastal slope, coastal water depth, and visibility distance. and at least one of tide level.

According to one embodiment, the step of calculating, by the calculation unit, a wave overtopping risk index based on the predicted wave overtopping prediction data, is based on the range values of the significant wave height and the wave period by the first index calculation module. A step of calculating a first overtopping wave risk index by overtopping wave prediction data including a condition grade predicted by a second index calculation module, including a condition grade predicted based on the significant wave height, sensitivity index, and location weight. Calculating a second wave overtopping risk index based on wave overtopping prediction data, using a third index calculation module to determine the average range value of the significant wave height, the wind speed, or the range value of the tide level, based on the plurality of index factors. The third wave overtopping risk index is calculated according to the preset risk by adding the preset indicator grade according to at least one of the change values and the respective overtopping prediction data generated by applying the weight according to each preset indicator grade of the plurality of indicator factors. By the calculating step or the fourth index calculation module, the maximum impact due to ground friction is calculated based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth, and the maximum impulse It includes the step of calculating the fourth wave overtopping risk index according to .

According to one embodiment, the step of calculating the first wave overtopping risk index by the first index calculation module using wave overtopping prediction data including a condition grade predicted based on the significant wave height and the range value of the wave period. , the condition grade is calculated based on the Douglas swell grade table, and further includes calculating the first overtopping risk index based on the calculated condition grade.

According to one embodiment, the step of calculating a second overtopping risk index by the second index calculation module using overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight, The sensitivity index includes at least one of human sensitivity, material sensitivity, or topographical sensitivity.

According to one embodiment, the step of calculating a second overtopping risk index by the second index calculation module using overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight, The location weight includes a weight for at least one of the East Sea, West Sea, and South Sea, and further includes calculating a second wave overtopping risk index using the following equation.

According to one embodiment, the third index calculation module determines in advance according to at least one of the average range value of the significant wave height, the wind speed, or the change value of the range value of the tidal level, based on the plurality of index factors. The step of calculating a third wave overtopping risk index according to a preset risk by adding up each wave overtopping prediction data generated by applying a set indicator grade and a weight according to each preset indicator grade of the plurality of indicator factors, the weight is It further includes calculating a first weight with a smaller error among the plurality of weights through AHP analysis.

According to one embodiment, the fourth index calculation module calculates the maximum impact due to ground friction based on at least one of the significant wave height, the peak period, the duration, the coastal slope, and the coastal water depth, The step of calculating the fourth wave overtopping risk index according to the maximum impact includes at least two of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth collected based on the collected marine basic data. It further includes calculating wave overtopping prediction data including maximum wave height and maximum wave period based on the indicator factors.

According to one embodiment, the fourth index calculation module calculates the maximum impact due to ground friction based on at least one of the significant wave height, the peak period, the duration, the coastal slope, and the coastal water depth, The step of calculating the fourth overtopping risk index according to the maximum impact amount is based on the collected basic marine data, at least one of the height of the breakwater, the slope of the breakwater, the friction of the breakwater, a preset safety distance range, or a preset physical condition. It further includes a step of calculating overtopping prediction data.

According to one embodiment, the fourth index calculation module calculates the maximum impact due to ground friction based on at least one of the significant wave height, the peak period, the duration, the coastal slope, and the coastal water depth, The step of calculating the fourth wave overtopping risk index according to the maximum impact calculates the maximum impact due to ground friction based on the calculated overtopping prediction data, and the calculated maximum impact is calculated as the fourth overtopping wave through an instability probability model. It further includes the step of calculating the risk index.

According to one embodiment, the step of calculating, by the calculation unit, a wave overtopping risk index based on the predicted wave overtopping prediction data, the calculated wave overtopping risk index is calculated by the simulation module to be a wave overtopping risk index with a small error through simulation. It further includes a step of selecting and calculating an index.

According to an embodiment of the present disclosure, the above-described wave overtopping risk assessment method is stored in a computer-readable recording medium in order to be executed in the user terminal.

According to various embodiments of the present disclosure, the risk is predicted by calculating overtopping prediction data (e.g., flow velocity of overtopping waves and thickness or height of the ground and water surface at the time of overtopping) based on basic marine data, thereby predicting the risk. It can reduce human and material damage.

According to various embodiments of the present disclosure, a wave overtopping risk index with a small error is selected by simulating the overtopping risk index calculated according to various variables based on a plurality of overtopping prediction data through a plurality of indicator calculation modules configured in the calculation unit. By doing so, the accuracy of the wave overtopping risk index can be increased.

The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, in which like reference numerals indicate like elements, but are not limited thereto.
1 is a block diagram of a wave overtopping risk assessment system according to an embodiment of the present disclosure.
Figure 2 is an internal configuration of a wave overtopping risk assessment system according to an embodiment of the present disclosure.
Figure 3 is a block diagram of a calculation unit configured in the wave overtopping risk assessment system according to an embodiment of the present disclosure.
Figure 4 is a diagram showing a first embodiment of calculating a wave overtopping risk index from wave overtopping prediction data predicted through a calculation unit configured in a wave overtopping risk assessment system according to an embodiment of the present disclosure.
Figure 5 is a diagram showing a second embodiment of calculating the wave overtopping risk index through a calculation unit configured in the wave overtopping risk assessment system according to an embodiment of the present disclosure.
Figure 6 is a diagram showing a third embodiment of calculating the wave overtopping risk index through a calculation unit configured in the wave overtopping risk assessment system according to an embodiment of the present disclosure.
Figure 7 is a diagram showing an example of generating a UI that provides a wave overtopping risk assessment system to the user through a UI generation unit based on marine basic data, wave overtopping prediction data, and overtopping risk index stored in the storage unit according to an embodiment of the present disclosure. am.
Figure 8 is a flowchart of a wave overtopping risk assessment method according to an embodiment of the present disclosure.
Figure 9 is a flowchart showing a first embodiment of calculating a wave overtopping risk index from wave overtopping prediction data through a wave overtopping risk assessment method according to an embodiment of the present disclosure.
Figure 10 is a flowchart showing a second embodiment of calculating a wave overtopping risk index through a wave overtopping risk assessment method according to an embodiment of the present disclosure.

Hereinafter, specific details for implementing the present disclosure will be described in detail with reference to the attached drawings. However, in the following description, detailed descriptions of well-known functions or configurations will be omitted if there is a risk of unnecessarily obscuring the gist of the present disclosure.

In the accompanying drawings, identical or corresponding components are given the same reference numerals. Additionally, in the description of the following embodiments, overlapping descriptions of identical or corresponding components may be omitted. However, even if descriptions of components are omitted, it is not intended that such components are not included in any embodiment.

Advantages and features of the disclosed embodiments and methods for achieving them will become clear by referring to the embodiments described below in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the present disclosure is complete and that the present disclosure does not fully convey the scope of the invention to those skilled in the art. It is only provided to inform you.

Terms used in this specification will be briefly described, and the disclosed embodiments will be described in detail. The terms used in this specification are general terms that are currently widely used as much as possible while considering the functions in the present disclosure, but this may vary depending on the intention or precedent of a technician working in the related field, the emergence of new technology, etc. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the relevant invention. Therefore, the terms used in this disclosure should be defined based on the meaning of the term and the overall content of this disclosure, rather than simply the name of the term.

In this specification, singular expressions include plural expressions, unless the context clearly specifies the singular. Additionally, plural expressions include singular expressions, unless the context clearly specifies plural expressions. When it is said that a part 'includes' a certain element throughout the specification, this means that it does not exclude other elements, but may further include other elements, unless specifically stated to the contrary.

Additionally, the term 'module' or 'unit' used in the specification refers to a software or hardware component, and the 'module' or 'unit' performs certain roles. However, 'module' or 'part' is not limited to software or hardware. A 'module' or 'unit' may be configured to reside on an addressable storage medium and may be configured to run on one or more processors. Therefore, as an example, a 'module' or 'part' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, properties, It may include at least one of procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, or variables. Components and 'modules' or 'parts' may be combined into smaller components and 'modules' or 'parts' or further components and 'modules' or 'parts'. Could be further separated.

According to an embodiment of the present disclosure, a 'module' or 'unit' may be implemented with a processor and memory. 'Processor' should be interpreted broadly to include general-purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, etc. In some contexts, 'processor' may refer to an application-specific integrated circuit (ASIC), programmable logic device (PLD), field programmable gate array (FPGA), etc. 'Processor' refers to a combination of processing devices, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in combination with a DSP core, or any other such combination of configurations. You may. Additionally, 'memory' should be interpreted broadly to include any electronic component capable of storing electronic information. 'Memory' refers to random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable-programmable read-only memory (EPROM), May also refer to various types of processor-readable media, such as electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, etc. A memory is said to be in electronic communication with a processor if the processor can read information from and/or write information to the memory. The memory integrated into the processor is in electronic communication with the processor.

1 is a block diagram of a wave overtopping risk assessment system according to an embodiment of the present disclosure. The wave overtopping risk assessment system 100 may include a memory 210, a processor 220, a communication module 230, and an input/output interface 240. As shown in FIG. 1, the wave overtopping risk assessment system 100 may be configured to communicate information and/or data through a network using the communication module 230.

Memory 210 may include any non-transitory computer-readable recording medium. According to one embodiment, the memory 210 is a non-permanent mass storage device such as random access memory (RAM), read only memory (ROM), disk drive, solid state drive (SSD), flash memory, etc. mass storage device). As another example, non-perishable mass storage devices such as ROM, SSD, flash memory, disk drive, etc. may be included in the wave overtopping risk assessment system 100 as a separate persistent storage device that is distinct from memory. In addition, the memory 210 includes an operating system and at least one program code (e.g., a program for calculating wave overtopping prediction data, calculating range values and weights of each index factor, a program for calculating a wave overtopping risk index, and a plurality of index calculation modules. Calculate wave overtopping prediction data based on each of the range values of at least one indicator factor selected from among a plurality of indicator factors, calculate the wave overtopping risk index through the calculated wave overtopping prediction data, and simulate overtopping waves with less error through simulation. A program that calculates the risk index, calculates the overtopping risk index by applying the weight calculated for each of the range values of the plurality of indicator factors from each of the plurality of index calculation modules to each of the plurality of indicator factors, and calculates the overtopping risk index and calculates the error through simulation. Codes for programs that calculate a small overtopping risk index, a program that corrects the standard value of preset overtopping expected data to calculate the overtopping risk index by comparing the predicted value of the overtopping risk index and the actual value, etc.) can be stored. .

These software components may be loaded from a computer-readable recording medium separate from the memory 210. Such separate computer-readable recording media may include recording media directly connectable to the overtopping risk assessment system 100, for example, floppy drives, disks, tapes, DVD/CD-ROM drives, and memory cards. It may include a recording medium that can be read by a computer, such as a computer. As another example, software components may be loaded into the memory 210 through the communication module 230 rather than a computer-readable recording medium. For example, at least one program is a computer program installed by files provided through the communication module 230 by developers or a file distribution system that distributes the installation file of the application (e.g., calculation of wave overtopping prediction data). A program for calculating the range values and weights of each indicator factor, a program for calculating the wave overtopping risk index, and wave overtopping prediction data based on each of the range values of at least one indicator factor selected among a plurality of indicator factors from each of the plurality of index calculation modules. A program that calculates a wave overtopping risk index with a small error through simulation and simulation by calculating a wave overtopping risk index through the calculated wave overtopping prediction data. A program that calculates a wave overtopping risk index with a small error through simulation, each of a plurality of index factor range values from each of a plurality of index calculation modules. A program that calculates the overtopping risk index with a small error through simulation and simulation by applying the weight calculated for each of the plurality of index factors to calculate the overtopping risk index, comparing the predicted value of the overtopping risk index with the actual value to calculate the overtopping risk index. It can be loaded into the memory 210 based on a code for a program that corrects the reference value of the preset expected wave overturning data to calculate .

The processor 220 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Commands may be provided to a user terminal (not shown) or another external system by the memory 210 or the communication module 230. For example, processor 220 may be configured to execute received instructions according to program code stored in a recording device such as memory 210.

The communication module 230 may provide a configuration or function for the user terminal, the image capture device, and/or the wave overtopping risk assessment system 100 to communicate with each other through a network, and the wave overtopping risk assessment system 100 may be configured to use a storage device and /Or it may provide a configuration or function for communicating with another system (for example, a separate cloud system, etc.). In one embodiment, control signals, commands, data, etc. provided under the control of the processor 220 of the wave overtopping risk assessment system 100 are transmitted to the user terminal through the communication module 230 and the network. can be provided. For example, the wave overtopping risk assessment system 100 receives marine survey data (e.g., digital tide chart, ocean currents and tide tables, etc.), ocean basic data (e.g., information on significant wave height, peak period, duration, coastal slope or coastal water depth, etc. for a predetermined time based on ocean basic data), ocean and/or coastal An image containing information and/or an image containing weather information may be received. Additionally, the overtopping risk assessment system 100 includes at least one of the vessel operation convergence index calculated through the communication module 230, marine basic data and/or overtopping prediction data for a plurality of indicator factors, or overtopping risk index. Data (e.g., graphs, maps, and/or received image data generated based on marine basic data, overtopping prediction data, and/or overtopping risk index, etc.) may be provided to the user terminal.

In addition, the input/output interface 240 of the overtopping risk assessment system 100 is connected to the overtopping risk assessment system 100 or is an interface with a device (not shown) for input or output that the overtopping risk assessment system 100 may include. It may be a means for. In FIG. 1 , the input/output interface 240 is shown as an element configured separately from the processor 220, but the present invention is not limited thereto, and the input/output interface 240 may be included in the processor 220. The wave overtopping risk assessment system 100 may include more components than those shown in FIG. 1 . However, there is no need to clearly show most prior art components.

The processor 220 of the wave overtopping risk assessment system 100 may be configured to manage, process, and/or store information and/or data received from a plurality of user terminals and/or a plurality of external systems. In one embodiment, the processor 220 stores, processes, and transmits the received basic marine data, wave overtopping prediction data, wave overtopping risk index, images containing marine and/or coastal information, and/or images containing meteorological information, etc. You can. For example, the processor 220 provides ocean basic data, significant wave height for a predetermined time based on the received ocean basic data, peak period, duration, wave overtopping prediction data for coastal slope or coastal water depth, and a plurality of indicators. The range values and weights of each factor can be calculated. Additionally, the processor 220 may calculate wave overtopping prediction data based on each of the range values of at least one indicator factor selected from among the plurality of indicator factors from each of the plurality of index calculation modules. In addition, the processor 220 can calculate the overtopping risk index through the calculated overtopping prediction data, verify the error through simulation, and calculate the overtopping risk index with a small error. In addition, the processor 220 calculates the overtopping risk index by applying the weight calculated for each of the range values of the plurality of indicator factors from each of the index calculation modules to each of the plurality of indicator factors, and verifies the error through simulation and simulation. By calculating the overtopping risk index with a small error and comparing the predicted value of the overtopping risk index with the actual value, the standard value of the preset expected overtopping data to calculate the overtopping risk index can be corrected. In addition, the processor 220 may transmit visual data including graphs, maps, and/or received image data generated based on the calculated basic marine data, overtopping prediction data, and/or overtopping risk index to the user terminal. .

Figure 2 is an internal configuration of a wave overtopping risk assessment system according to an embodiment of the present disclosure. Referring to FIG. 1 , the wave overtopping risk assessment system 100 may include a processor 220 and a memory 210 . The processor 220 may include a collection unit 110, a prediction unit 130, and a calculation unit 150, and the memory 210 may include a storage unit 190. Additionally, the processor 220 may further include a UI generator (not shown).

The collection unit 110 may be configured to collect basic ocean data including at least one of image data or meteorological data. The image data may be at least one of an image capture device installed to capture at least one of the ocean or the coast, or data periodically photographed of at least one of the ocean or the coast using a drone. Additionally, image data can be collected from historical and real-time image data observed through observation agencies such as the Korea Meteorological Administration.

The weather data may be quantified data about at least one weather condition of the ocean or the coast. For example, meteorological data may include a plurality of indicator factors and may include numerical values (hereinafter referred to as ‘range values’) for the plurality of indicator factors.

Additionally, meteorological data is numerical data that measures the height, period, and direction of waves using a wave gauge and/or wave gauge to measure wave data, and determines the waves through statistical and spectral analysis, or measures incident waves on a breakwater. It may be numerical data. Here, the wave height gauge may include an ultrasonic wave height gauge, a hydraulic wave direction gauge, etc., and the wave direction gauge may include a buoy type wave gauge, an ultrasonic wave direction gauge, and a buoy type wave direction gauge. An ultrasonic wave gauge installs an ultrasonic transmitter and receiver on the seafloor and measures the distance to the surface to measure the surface waveform, while a hydraulic wavemeter installs a sensing unit on the seafloor and measures the change in underwater pressure caused by waves to indirectly measure the surface waveform. It can be measured. The buoy-type wave meter can check the source of waves using a measuring instrument installed inside based on the behavior of the buoy on the sea surface.

Additionally, weather data may collect numerical data including historical, real-time and/or forecast data observed through observation agencies such as the Korea Meteorological Administration. Additionally or alternatively, the meteorological data may be data collected from marine survey data, including digital tide charts, current charts, and tide tables, and quantified through the collected marine survey data. Here, the tidal current diagram schematically shows the changes in tidal currents in a specific sea area or peak, and the numerical tidal diagram may be a combination of harmonic constants obtained in advance for each subdivision to predict and display the tidal currents at a desired time. Harmonic constants for each tidal wave can be calculated by analyzing the results of simulating tides using a tidal numerical model. An ocean current map is a map showing the type, direction, and speed of ocean currents, and a tide table may be a table expressing forecast values for the times and heights of daily high water and low water.

The plurality of index factors include at least one of wind speed, wind direction, wave height, significant wave height, wave height, incident wave height, clearance height, wave direction, wave period, peak period, duration, coastal slope, coastal water depth, visibility distance, and tide level. can do. Wave height is the height from the trough (or trough) to the crest (or wave peak), and the wave period is the time it takes from the passage of a crest or trough at a specific point on the water until the next crest or trough passes. It could be a cycle. Wave height can be the height of a wave. The peak period may represent the period corresponding to the maximum energy in the wave spectrum, the duration may be the duration of the overcoming wave, and the tide level is constant except for short-term sea level rise and fall due to wind and wave, swell, or natural vibration of the port, etc. It may be the height when measured from the reference surface to sea level.

The prediction unit 130 may be configured to predict wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected basic marine data. In one embodiment, the wave overtopping prediction data includes wave overtopping prediction data for a predetermined time through the ocean circulation model (ROMS), weather prediction model (WRF), wave prediction model (WW3), and SWAN model (Simulating Wave Nearshore Model). It can be configured to predict and generate. The prediction unit 130 applies the basic ocean data of the target area to the ocean circulation model (ROMS) to determine the direction (direction of the current, direction of the ocean current) and current speed (e.g., the speed of the current, speed of ocean currents) can be predicted. In addition, the prediction unit 130 applies basic marine data of the target area to the weather prediction model (WRF) to predict the wind speed and wind direction for a predetermined time, and applies it to the wave prediction model (WW3) to predict the wind speed and direction in advance. It can be configured to predict the height of waves for a determined time and predict waves in coastal areas and local areas through the SWAN model. Meanwhile, the prediction unit 130 predicts wave overtopping data for a predetermined time by the ocean circulation model (ROMS), weather prediction model (WRF), wave prediction model (WW3), and SWAN model (Simulating Wave Nearshore Model). Although it has been described above that it can be configured, it is not limited to this. Additionally, the prediction unit 130 may be configured to predict overtopping wave prediction data including the flow velocity and thickness of overtopping waves based on the collected basic marine data. In addition, the prediction unit 130 may be configured to predict the maximum wave height, wave period, height of the breakwater, slope of the breakwater, frictional force of the breakwater, preset physical condition, and preset safety distance range based on marine basic data. In addition, the prediction unit 130 predicts the clearance height based on the height, wave height, incident wave height, and/or water level of the breakwater in the target area, or based on significant wave height, peak period, duration, coastal slope, and/or water depth. The maximum wave height and/or wave period can be predicted.

The calculation unit 150 may be configured to calculate the wave overtopping risk index based on the predicted wave overtopping prediction data. In one embodiment, the wave overtopping risk index may be calculated based on wave overtopping prediction data including the flow velocity and thickness of the overtopping wave predicted from the prediction unit 130. Additionally, the calculation unit 150 may be configured to variably calculate the overtopping risk index of the flow velocity and thickness of the overtopping wave according to preset physical conditions and/or preset safety ranges included in the overtopping prediction data. In addition, the calculation unit 150 determines the maximum wave height, wave period, height of the breakwater, slope of the breakwater, frictional force of the breakwater, preset physical condition, and/or preset safety distance range included in the wave overtopping prediction data. It can be configured to calculate the overtopping risk index by calculating the impact amount.

The storage unit 190 may be configured to store at least one of basic marine data, wave overtopping prediction data, and wave overtopping risk index. Additionally, it may be configured to store range values of a plurality of indicator factors, an indicator of a wave overtopping risk index classified according to each of the range values of a plurality of indicator factors, and a calculated weight for at least one of the plurality of indicator factors. In addition, the UI generator generates visual data including graphs, maps, and/or received image data generated by at least one of basic marine data, wave overtopping prediction data, and wave overtopping risk index stored in the storage unit 190, so that the user can It can be provided through a terminal.

Figure 3 is a block diagram of a calculation unit configured in the wave overtopping risk assessment system according to an embodiment of the present disclosure. As shown, the calculation unit 150 includes a first index calculation module 151, a second index calculation module 153, a third index calculation module 155, and/or a fourth index calculation module 157. can do.

The first index calculation module 151 may be configured to calculate the first wave overtopping risk index using wave overtopping prediction data including a condition grade predicted based on the range values of significant wave height and wave period. In one embodiment, the first index calculation module 151 may be configured to calculate the condition grade based on the Douglas swell scale (Douglas sea scale) and calculate the first overtopping risk index based on the calculated condition grade. there is. In one embodiment, the Douglas swell rating table can be divided into 10 condition grades, and can be classified into condition grades from level 0 to level 9 depending on the wave height. The first overtopping risk index can be calculated based on the classified condition level. Additionally or alternatively, the first index calculation module 151 may calculate the first wave overtopping risk index according to the respective range values of the significant wave height and wave period. In addition, the first wave overtopping risk index may be composed of five levels, for example, 'serious', 'caution', 'caution', 'concern', and 'good'. there is. For example, if the condition grade is classified as the 8th to 9th stage of the Douglas swell grade table, the significant wave height is 4 m or more, and the wave period is greater than 11 seconds, the first index calculation module 151 is the first index calculation module 151. The wave overtopping risk index can be set to the ‘severe’ level. Meanwhile, it is described in detail that the first wave overtopping risk index calculated through the first index calculation module 151 can be classified into five levels: 'Severe', 'Warning', 'Caution', 'Concern', and 'Good'. However, it is not limited to this, and for example, the first wave overtopping risk index may be configured differently in numerical form. In addition, the first index calculation module 151 has been described in detail as calculating the condition grade based on the Douglas swell grade table and calculating the first overtopping risk index based on the calculated condition grade, but the swell condition is not limited to this. Based on the significant wave height, period, and damage status data observed at the time of wave occurrence, the first wave overtopping risk index can be calculated according to the Douglas swell rating table and the standards presented in various previous studies.

The second index calculation module 153 may be configured to calculate the second overtopping risk index using wave overtopping prediction data including a condition grade predicted based on significant wave height, sensitivity index, and location weight. Here, the sensitivity index may include at least one of human sensitivity, material sensitivity, or topographical sensitivity. Human sensitivity may include the population, elderly population, disabled population, etc. of the target area. Physical sensitivity may include coastal buildings, port complexes, industrial complexes, roads, fish farms, etc. of the target area. Geographical sensitivity may include the target area. It may include flooded areas, large trucks, etc. The second index calculation module 153 can calculate the second wave overtopping risk index using Equation 1 below.

Here, a and b may be location weights, and the location weight may be a weight for at least one region among the East Sea, West Sea, and South Sea. For example, in the case of location weights, the East Sea may have a = 0.67, b = 0.33, the West Sea may have a = 0.60, b = 0.40, and the South Sea may have a = 0.65, b = 0.35.

The third index calculation module 155 is based on a plurality of indicator factors, a preset indicator grade according to at least one of the average range value of the significant wave height, the change value of the range value of wind speed or tide level, and each of the plurality of indicator factors. It can be configured to calculate the third wave overtopping risk index according to the preset risk by summing each wave overtopping prediction data generated by applying a weight according to the preset indicator grade. In one embodiment, the weight according to each preset indicator grade is calculated by calculating the first weight with less error among the plurality of weights calculated through AHP analysis and applying it to each preset indicator grade to predict wave overtopping prediction data, The third overtopping risk index can be calculated using a preset indicator according to the sum of each predicted overtopping prediction data. The third index calculation module 155 can calculate the third wave overtopping risk index using Equation 2 below.

Here, the plurality of indicator factors may calculate an indicator grade according to a range value of at least one of tide level, significant wave height, wind speed, or sea fog, and the indicator grade may be classified according to the standard of the range value of the indicator factor set in advance. In one embodiment, the indicator grades are classified into the first to the ninth indicator grades, and for each indicator grade, a range for the range value of the indicator factor may be set. For example, in the case of significant wave height (or average significant wave height) among multiple indicator factors, each indicator grade can be set to a value that increases at intervals of 0.4m based on less than 0.2m, which is the range value of the first indicator grade. And the range value of the 9th indicator grade can be set to 3.0 m or more. In the case of wind speed among multiple indicator factors, each indicator grade can be set to a value that increases at intervals of 1.8 m/s based on less than 1.4 m/s, which is the range value of the 1st indicator grade, and the 9th indicator grade The range value can be set to 14.0 m/s or higher. In the case of tide level (rising speed) among a plurality of indicator factors, it can be set as a value that increases at intervals of 10 cm/h up to the 5th indicator grade based on less than 10 cm/h, which is the range value of the 1st indicator grade, and accordingly, The 5th indicator grade may be based on a range of values from 40 cm/h to 50 cm/h, and from the 6th indicator grade to the 9th indicator grade, the values can be set in increasing intervals of 15 cm/h, and the 9th indicator grade The range value can be set to 95cm/h or more. In the case of sea fog (or visibility distance) among a plurality of indicator factors, the visibility distance can be set to a value deducted at intervals of 200m up to the 5th indicator grade based on the range value of 1000m or more of the 1st indicator grade, and accordingly, The fifth indicator level may be based on a range of values from 200m to 400m. In the case of sea fog among multiple indicator factors, the range value of the 6th indicator class is 100m to less than 200m, the range value of the 7th indicator class is 40m to less than 100m, the range value of the 8th indicator class is 20m to 40m, 9th The range value of the surface level can be set to less than 20m.

When calculating the overtopping risk index based on the indicator grade set as above, each indicator grade of a plurality of indicator factors can be calculated, and a weight corresponding to each of the plurality of indicator factors can be applied. For example, the third index calculation module 155 multiplies the index grade and weight of each index factor, and calculates the value according to a preset index based on the total value of the sum of the values obtained by multiplying the index grade and weight of a plurality of index factors. It can be configured to calculate the third wave overtopping risk index.

The fourth index calculation module 157 calculates the maximum impact due to ground friction based on at least one of significant wave height, peak period, duration, coastal slope, or coastal water depth, and calculates the fourth overtopping risk index according to the maximum impact. It can be configured to do so. The fourth index calculation module 157 includes the maximum wave height and maximum wave period based on at least two indicator factors of significant wave height, peak period, duration, coastal slope, or coastal water depth collected based on the collected marine basic data. It can be configured to calculate wave overtopping prediction data. The fourth index calculation module 157 calculates wave overtopping prediction data including at least one of the height of the breakwater, the slope of the breakwater, the friction of the breakwater, a preset safety distance range, or a preset physical condition based on the collected marine basic data. It can be configured. In this way, the fourth index calculation module 157 calculates the maximum impact due to ground friction based on the calculated overtopping prediction data, and the calculated maximum impact is configured to calculate the fourth overtopping risk index by the instability probability model. You can.

The calculation unit 150 may further include a simulation module 159 configured to simulate the wave overtopping risk index calculated through at least one of the first to fourth index calculation modules 151, 153, 155, and 157. It can be configured to select and calculate a wave overtopping risk index with a small error through the simulation module 159. Examples of each simulation of the overtopping risk index through the simulation module 159 will be described later in FIG. 6.

Figure 4 is a diagram showing a first embodiment of calculating a wave overtopping risk index from wave overtopping prediction data predicted through a calculation unit configured in a wave overtopping risk assessment system according to an embodiment of the present disclosure. The prediction unit is configured to predict wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected basic ocean data. For example, wave overtopping (W) based on the collected basic ocean data. It can be configured to predict overtopping prediction data including the flow velocity (V) and thickness (D), and additionally, the overtopping risk index can be calculated by applying different risk indicators depending on the physical condition of the pedestrian (m). . Here, the thickness (D) can refer to the height between the ground surface and the water surface where the pedestrian (m) is located, and the physical condition of the pedestrian (m) includes the pedestrian's (m) height, weight, musculoskeletal mass, etc. can do.

In one embodiment, the flow velocity (V) and thickness of the overtopping wave according to the range values of a plurality of indicator factors for a predetermined time based on marine basic data including at least one of image data or meteorological data collected by the collection unit. Wave overtopping prediction data including (D) can be predicted. For example, predict the height of the breakwater included in the collected image data, the height of the wave exceeding the height of the breakwater, and apply the wave direction, wave speed, and wind direction included in the collected meteorological data to determine the flow velocity of the overtopping wave (V ) and thickness (D) can be predicted.

In one embodiment, the risk index may be set differently depending on the values for the water velocity (V) and thickness (D) predicted in the event of an overtopping wave (W), and may also be set differently depending on the physical condition of the pedestrian (m). Accordingly, the overtopping risk index can be calculated by applying different risk indicators. For example, if the water velocity (V) and thickness (D) of the overtopping wave are the same, the overtopping risk index can be calculated by applying different risk indicators depending on the physical condition of the pedestrian (m).

In one embodiment, the overtopping risk index is calculated by calculating and applying a weight according to the physical condition of the pedestrian (m) to the values of water velocity (V) and thickness (D) predicted in the event of a overtopping wave (W). can do. In addition, the overtopping risk index is based on at least one physical condition (e.g., height, weight, musculoskeletal mass, etc.) of the pedestrian (m) relative to the water velocity (V) and thickness (D) values predicted in the event of a overtopping wave (W). The weight can be calculated according to the range value.

In addition, the prediction unit predicts wave overtopping prediction data related to the individual wave overtopping amount, and the calculation unit can calculate the probability of occurrence of the individual wave overtopping amount and the maximum individual wave overtopping amount to calculate an empirical formula for the individual wave overtopping amount.

In one embodiment, the calculation unit may calculate the probability of individual wave overtopping occurrence using Equation 3 below based on wave overtopping prediction data.

Here, P _v may be the probability of occurrence of an individual wave overtopping amount, a may be a scale parameter (scale parameter), and b may be a shape parameter (shape parameter).

In one embodiment, the calculation unit may calculate the maximum individual wave overtopping amount using Equation 4 below based on wave overtopping prediction data.

Here, V _max is the maximum individual wave overtopping amount, a is a scale parameter (scale parameter), b is a shape parameter (shape parameter), and N _ow may be the frequency of overtopping occurrence.

It can be configured to calculate the overtopping risk index based on the probability of occurrence of individual wave overtopping calculated by Equation 3 described above and/or the maximum individual overtopping amount calculated by Equation 4.

Figure 5 is a diagram showing a second embodiment of calculating the wave overtopping risk index through a calculation unit configured in the wave overtopping risk assessment system according to an embodiment of the present disclosure, and Figure 6 is a view showing a wave overtopping risk assessment system according to an embodiment of the present disclosure. This is a diagram showing a third embodiment of calculating the overtopping risk index through the calculation unit configured in .

The calculation unit 150 may include a first index calculation module 151, a second index calculation module 153, a third index calculation module 155, and/or a fourth index calculation module 157. Additionally, the calculation unit 150 may further include a simulation module 159 configured to simulate the wave overtopping risk index calculated through at least one of the first to fourth index calculation modules 151, 153, 155, and 157. .

In one embodiment, referring to FIG. 5, the simulation module 159 compares at least one past predicted wave overtopping risk index (192_1) and the past actual overtopping risk index (192_2) to determine the range value of at least one indicator factor. A correction value that corrects each difference can be calculated. At least one past predicted wave overtopping risk index (192_1) and the past actual overtopping risk index (192) can be configured to increase accuracy by calculating a past data-based overtopping risk index (192_3) through the calculated correction value.

Referring to FIG. 6, the first index calculation module 151 is configured to calculate the first wave overtopping risk index (152_1) using wave overtopping prediction data including a condition grade predicted based on the range values of significant wave height and wave period. It can be. The second index calculation module 153 may be configured to calculate the second overtopping risk index 154_1 using wave overtopping prediction data including a condition grade predicted based on significant wave height, sensitivity index, and location weight. The third index calculation module 155 is based on a plurality of indicator factors, a preset indicator grade according to at least one of the average range value of the significant wave height, the change value of the range value of wind speed or tide level, and each of the plurality of indicator factors. It can be configured to calculate the third wave overtopping risk index (156_1) according to the preset risk by summing each wave overtopping prediction data generated by applying a weight according to the preset indicator grade. The fourth index calculation module 157 calculates the maximum impact due to ground friction based on at least one of significant wave height, peak period, duration, coastal slope, or coastal water depth, and calculates the fourth overtopping risk index according to the maximum impact. It can be configured to do so.

In one embodiment, the calculation unit 150 calculates the first to fourth wave overtopping risk indices (152_1, 154_1, 156_1, 158_1) calculated from each of the first to fourth index calculation modules (151, 153, 155, and 157). Each of can be simulated and compared through the simulation module 159 to select the nth wave overtopping risk index 160 with a small error.

In one embodiment, the calculation unit 150 calculates the first to fourth wave overtopping risk indices (152_1, 154_1, 156_1, 158_1) calculated from each of the first to fourth index calculation modules (151, 153, 155, and 157). The nth overtopping risk index (160) with a small error can be selected by simulating and comparing with the average overtopping risk index (192_4) based on past data through the simulation module (159).

In one embodiment, referring to FIGS. 5 and 6, the calculation unit 150 calculates the first to fourth wave overtopping risk indices calculated from each of the first to fourth index calculation modules 151, 153, 155, and 157. (152_1, 154_1, 156_1, 158_1) can be simulated and compared with the past data-based wave overtopping risk index (192_3) through the simulation module 159 to select the nth wave overtopping risk index (160) with a small error.

Figure 7 is a diagram showing an example of generating a UI that provides a wave overtopping risk assessment system to the user through a UI generation unit based on marine basic data, wave overtopping prediction data, and overtopping risk index stored in the storage unit according to an embodiment of the present disclosure. am.

The overtopping risk assessment system may further include a UI generation unit 170, and the UI generating unit 170 may select among the basic marine data 112, overtopping prediction data 132, and overtopping risk index 162 stored in the storage unit. Visual data (UI) including at least one generated graph, map, and/or received image data may be generated and provided to the user terminal.

In one embodiment, the visual data (UI) may include real-time image data including at least one of the ocean or coast of a plurality of target areas for providing wave overtopping observations. Here, the image data may be an installed image capture device (e.g., CCTV, etc.) to capture at least one of the ocean or coast of a plurality of target areas, or a mobile image capture device (e.g., a mobile image capture device that periodically captures at least one of the ocean or coast). For example, it may be data captured through a drone, etc.).

In one embodiment, the visual data (UI) may output an analysis image or an analysis image that performs analysis on at least one of image data including at least one of the ocean or coast of a plurality of target areas. For example, when a wave overturning occurs, if the wave height is higher than the height of the breakwater based on the analysis image or analysis video, the wave overtopping area may be displayed as a specific area of interest and may be configured to display the value of the wave height or the thickness of the wave overtopping. .

In one embodiment, the visual data (UI) may include a graph for wave overtopping observations based on at least one or a combination of a plurality of indicator factors of the weather data collected from the collection unit. For example, a graph for overtopping wave observations may be configured to display information about surface water elevation and wave run-up as a time series graph. Here, the time series graph for water surface elevation may be a graph representing water level by hour, and the time series graph for wave run-up may be a graph representing wave rise height by hour.

In one embodiment, the visual data (UI) is an hourly value (or range value) for at least one of a plurality of indicator factors of weather data collected from the collection unit, a maximum value for a preset period, or a preset period. It may be configured to display text representing at least one of a minimum value for the index and at least one real-time value among a plurality of indicator factors.

Figure 8 is a flowchart of a wave overtopping risk assessment method 800 according to an embodiment of the present disclosure, and Figure 9 is a flowchart of a wave overtopping risk assessment method according to an embodiment of the present disclosure, which calculates a wave overtopping risk index from wave overtopping prediction data. 1 is a flowchart showing an embodiment 900, and FIG. 10 is a flowchart showing a second embodiment of calculating a wave overtopping risk index through the wave overtopping risk assessment method 800 according to an embodiment of the present disclosure. The overtopping risk assessment method 800 may be initiated by collecting basic marine data including at least one of image data or meteorological data by a collection unit (S810).

Next, the prediction unit may predict wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected basic marine data (S830). Here, the plurality of indicator factors is at least one of wind speed, wind direction, wave height, significant wave height, wave height, incident wave height, clearance height, wave direction, wave period, peak period, duration, coastal slope, coastal water depth, visibility distance, and tide level. may include. Additionally, the prediction unit may be configured to predict overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data.

Next, the calculation unit can calculate the wave overtopping risk index based on the predicted wave overtopping prediction data.

Referring to FIG. 9, the prediction unit predicts the wave overtopping prediction data related to the individual wave overtopping amount (S910), and the calculation unit calculates the probability of occurrence of the individual wave overtopping amount and the maximum individual wave overtopping amount (S930) to obtain an empirical formula for the individual wave overtopping amount. The overtopping risk index can be calculated through the first embodiment 900 of calculating (S950).

In one embodiment, referring to FIG. 9, the calculation unit may calculate the probability of individual wave overtopping occurrence using Equation 3 described above in FIG. 4 based on wave overtopping prediction data. Here, Pv may be the probability of occurrence of individual wave overtopping, a may be a scale parameter (scale parameter), and b may be a shape parameter (shape parameter). In addition, the calculation unit can calculate the maximum individual wave overtopping amount using Equation 4 described above in FIG. 4 based on the wave overtopping prediction data. Here, Vmax may be the maximum individual wave overtopping amount, a may be a scale parameter (scale parameter), b may be a shape parameter (shape parameter), and Now may be the frequency of wave overtopping occurrence.

Referring to FIG. 10, the overtopping risk index can be calculated through the second embodiment (1000) of calculating the overtopping risk index through the overtopping risk assessment method (800).

In one embodiment, the calculation unit may calculate the first wave overtopping risk index using wave overtopping prediction data including a condition grade predicted based on the range values of significant wave height and wave period by the first index calculation module. Here, in the first index calculation module, the condition grade is calculated based on the Douglas swell grade table, and the first overtopping risk index can be calculated based on the calculated condition grade.

In one embodiment, the calculation unit may calculate the second overtopping risk index by the second index calculation module using overtopping prediction data including a condition grade predicted based on significant wave height, sensitivity index, and location weight. Here, the sensitivity index includes at least one of human sensitivity, material sensitivity, or topographical sensitivity, and the location weight includes a weight for at least one region among the East Sea, West Sea, and South Sea, and by Equation 1 described above in FIG. 3 The second overtopping risk index can be calculated.

In one embodiment, by the third index calculation module, based on a plurality of indicator factors, a preset indicator grade according to at least one of the average range value of the significant wave height, the change value of the range value of wind speed or tide level, and a plurality of indicator factors The third wave overtopping risk index can be calculated according to the preset risk by summing each wave overtopping prediction data generated by applying the weight according to each preset indicator grade of the indicator factor. Here, the first weight with the smallest error among the plurality of weights can be calculated through AHP analysis.

In one embodiment, the fourth index calculation module calculates the maximum impulse due to ground friction based on at least one of significant wave height, peak period, duration, coastal slope, or coastal water depth, and calculates the fourth overtopping wave according to the maximum impulse. The risk index can be calculated. In detail, calculation of wave overtopping prediction data including maximum wave height and maximum wave period based on at least two indicator factors of significant wave height, peak period, duration, coastal slope, or coastal water depth collected based on the collected marine basic data ( S1010) You can. Next, based on the basic marine data collected by the calculation unit, calculate wave overtopping prediction data including at least one of the height of the breakwater, the slope of the breakwater, the breakwater friction force, the preset safety distance range, or the preset physical condition (S1030) can do. Next, the calculation unit calculates the maximum impact due to ground friction based on the calculated overtopping prediction data, and the calculated maximum impact can be used to calculate the fourth overtopping risk index through an instability probability model (S1050).

Next, the storage unit may store at least one of the basic marine data collected by the collection unit, the wave overtopping prediction data predicted by the prediction unit, and the wave overtopping risk index calculated by the calculation unit.

Additionally, the overtopping risk assessment system further includes a simulation module, and the overtopping risk index calculated by the simulation module can be calculated by selecting a overtopping risk index with a small error through simulation.

The preceding description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications of the present disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to the various modifications without departing from the spirit or scope of the present disclosure. Accordingly, this disclosure is not intended to be limited to the examples shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Although example implementations may refer to utilizing aspects of the presently disclosed subject matter in the context of one or more standalone computer systems, the subject matter is not so limited, but rather in conjunction with any computing environment, such as a network or distributed computing environment. It can also be implemented. Furthermore, aspects of the presently disclosed subject matter may be implemented in or across multiple processing chips or devices, and storage may be similarly effected across the multiple devices. These devices may include PCs, network servers, and handheld devices.

Although the present disclosure has been described in relation to some embodiments in the specification, it should be noted that various modifications and changes can be made without departing from the scope of the present disclosure as can be understood by those skilled in the art. something to do. Moreover, such modifications and variations are to be considered as falling within the scope of the patent claims appended hereto.

100: Wave overtopping risk assessment system 110: Collection unit
112: Basic ocean data 130: Forecast unit
132: Wave overtopping prediction data 150: Calculation unit
151: 1st index calculation module 152_1: 1st overtopping risk index
153: Second index calculation module 154_1: Second overtopping risk index
155: Third index calculation module 156_1: Third wave overtopping risk index
157: Fourth index calculation module 158_1: Fourth wave overtopping risk index
159: Simulation module 160, 162: Wave overtopping risk index
170: UI creation unit 190: Storage unit
192_1: Past predicted wave overtopping risk index 192_2: Past actual wave overtopping risk index
192_3: Wave overtopping risk index based on past data
192_4: Average wave overtopping risk index based on past data
210: memory 220: processor
230: Communication module 240: Input/output interface

Claims (29)

In the wave overtopping risk assessment system,
A collection unit configured to collect basic ocean data including at least one of image data or meteorological data;
a prediction unit configured to predict wave overtopping prediction data according to range values of a plurality of indicator factors for a predetermined time based on the collected basic marine data;
A calculation unit configured to calculate a wave overtopping risk index based on the predicted wave overtopping prediction data; and
A storage unit configured to store at least one of the basic marine data, the wave overtopping prediction data, and the wave overtopping risk index.
Including,
The plurality of indicator factors include at least one of wind speed, wind direction, wave height, significant wave height, wave height, incident wave height, clearance height, wave direction, wave period, peak period, duration, coastal slope, coastal water depth, visibility distance, and tide level. Contains,
The prediction unit is configured to predict the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data,
The calculation unit,
a first index calculation module configured to calculate a first wave overtopping risk index based on wave overtopping prediction data including a condition grade predicted based on the significant wave height and the range value of the wave period;
a second index calculation module configured to calculate a second overtopping risk index based on wave overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight;
Based on the plurality of indicator factors, a preset indicator grade according to at least one of the average range value of the significant wave height, the change value for the wind speed or the range value of the tidal level, and each preset indicator of the plurality of indicator factors A third index calculation module configured to calculate a third wave overtopping risk index according to a preset risk by summing each wave overtopping prediction data generated by applying weights according to the grade; or
A system configured to calculate the maximum impact due to ground friction based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth, and calculate the fourth wave overtopping risk index according to the maximum impact. 4 Index calculation module
Including, an overtopping risk assessment system.
delete In the wave overtopping risk assessment system,
A collection unit configured to collect basic ocean data including at least one of image data or meteorological data;
a prediction unit configured to predict wave overtopping prediction data according to range values of a plurality of indicator factors for a predetermined time based on the collected basic marine data;
A calculation unit configured to calculate a wave overtopping risk index based on the predicted wave overtopping prediction data; and
A storage unit configured to store at least one of the basic marine data, the wave overtopping prediction data, and the wave overtopping risk index.
Including,
The prediction unit is configured to predict the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data,
Based on the above overtopping prediction data, the probability of individual overtopping amount is calculated by the following equation - where P _v is the probability of individual overtopping amount occurring, a is a scale parameter (scale parameter), and b is a shape parameter (shape parameter). Parameter)Im -,

Wave overtopping risk assessment system.
In the wave overtopping risk assessment system,
A collection unit configured to collect basic ocean data including at least one of image data or meteorological data;
a prediction unit configured to predict wave overtopping prediction data according to range values of a plurality of indicator factors for a predetermined time based on the collected basic marine data;
A calculation unit configured to calculate a wave overtopping risk index based on the predicted wave overtopping prediction data; and
A storage unit configured to store at least one of the basic marine data, the wave overtopping prediction data, and the wave overtopping risk index.
Including,
The prediction unit is configured to predict the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data,
Based on the above overtopping prediction data, the maximum individual overtopping amount is calculated by the equation below - V _max is the maximum individual overtopping amount, a is the scale parameter (scale parameter), b is the shape parameter (shape parameter), N _ow is the frequency of overlapping waves -,

Wave overtopping risk assessment system.
delete delete According to paragraph 1,
The first index calculation module is,
The condition grade is calculated based on the Douglas swell grade table, and the overtopping risk assessment system is configured to calculate the first overtopping risk index based on the calculated condition grade.
According to paragraph 1,
The second index calculation module,
The sensitivity index includes at least one of human sensitivity, material sensitivity, and topographical sensitivity.
According to paragraph 1,
The second index calculation module,
The location weight includes a weight for at least one of the East Sea, West Sea, and South Sea, and calculates the second wave overtopping risk index using the following equation - where, a = 0.67, b = 0.33 for the East Sea, and a = 0.33 for the West Sea. a=0.60, b=0.40, Namhae has weights of a=0.65, b=0.35 -,

Wave overtopping risk assessment system.
According to paragraph 1,
The third index calculation module is,
The weight is a wave overtopping risk assessment system that calculates the first weight with less error among the plurality of weights calculated through AHP analysis.
According to paragraph 1,
The fourth index calculation module is,
Wave overtopping prediction data including maximum wave height and maximum wave period based on at least two indicator factors of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth collected based on the collected marine basic data. A wave overtopping risk assessment system that calculates .
According to clause 11,
The fourth index calculation module is,
A wave overtopping risk assessment system that calculates wave overtopping prediction data including at least one of the height of the breakwater, the slope of the breakwater, the friction of the breakwater, a preset safety distance range, or a preset physical condition based on the collected basic marine data.
According to paragraph 1,
The fourth index calculation module is,
A wave overtopping risk assessment system that calculates the maximum impact due to ground friction based on the calculated overtopping prediction data, and calculates the fourth overtopping risk index using the calculated maximum impact through an instability probability model.
According to paragraph 1,
The calculation unit,
The calculated wave overtopping risk index is a simulation module configured to select and calculate the overtopping risk index with a small error through simulation.
An overtopping risk assessment system that further includes.
In the wave overtopping risk assessment method,
Collecting basic marine data including at least one of image data or meteorological data by a collection unit;
Predicting, by a prediction unit, wave overtopping prediction data according to range values of a plurality of indicator factors for a predetermined time based on the collected marine basic data;
Calculating, by a calculation unit, a wave overtopping risk index based on the predicted wave overtopping prediction data; and
Storing at least one of the basic marine data, the wave overtopping prediction data, and the wave overtopping risk index in a storage unit.
Including,
The plurality of indicator factors include at least one of wind speed, wind direction, wave height, significant wave height, wave height, incident wave height, clearance height, wave direction, wave period, peak period, duration, coastal slope, coastal water depth, visibility distance, and tide level. Contains,
The step of predicting wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected basic ocean data, by the prediction unit, includes predicting wave overtopping data based on the collected basic ocean data. Comprising the step of predicting the wave overtopping prediction data including flow velocity and thickness,
The step of calculating, by the calculation unit, the wave overtopping risk index based on the predicted wave overtopping prediction data,
Calculating, by a first index calculation module, a first wave overtopping risk index using wave overtopping prediction data including a condition grade predicted based on the significant wave height and the range value of the wave period;
Calculating a second overtopping risk index using wave overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight, by a second index calculation module;
By the third index calculation module, based on the plurality of index factors, a preset index grade according to at least one of the average range value of the significant wave height, the change value for the wind speed or the range value of the tide level, and the plurality of index factors. Calculating a third wave overtopping risk index according to a preset risk by adding up each wave overtopping prediction data generated by applying weights according to each preset indicator grade of the indicator factors; or
By the fourth index calculation module, the maximum impact due to ground friction is calculated based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth, and the fourth according to the maximum impulse Steps to calculate the wave overtopping risk index
Including, overtopping risk assessment method.
delete In the wave overtopping risk assessment method,
Collecting basic marine data including at least one of image data or meteorological data by a collection unit;
Predicting, by a prediction unit, wave overtopping prediction data according to range values of a plurality of indicator factors for a predetermined time based on the collected marine basic data;
Calculating, by a calculation unit, a wave overtopping risk index based on the predicted wave overtopping prediction data; and
Storing at least one of the basic marine data, the wave overtopping prediction data, and the wave overtopping risk index in a storage unit.
Including,
The step of predicting wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected marine basic data by the prediction unit,
Comprising the step of predicting the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data,
The step of calculating, by the calculation unit, the wave overtopping risk index based on the predicted wave overtopping prediction data,
Calculating the probability of occurrence of an individual wave overtopping amount by the following equation based on the overtopping prediction data - where P _v is the probability of occurrence of an individual overtopping amount, a is a scale parameter (scale parameter), and b is a shape parameter ( shape parameter) is -,

Further comprising a wave overtopping risk assessment method.
In the wave overtopping risk assessment method,
Collecting basic marine data including at least one of image data or meteorological data by a collection unit;
Predicting, by a prediction unit, wave overtopping prediction data according to range values of a plurality of indicator factors for a predetermined time based on the collected marine basic data;
Calculating, by a calculation unit, a wave overtopping risk index based on the predicted wave overtopping prediction data; and
Storing at least one of the basic marine data, the wave overtopping prediction data, and the wave overtopping risk index in a storage unit.
Including,
The step of predicting, by the prediction unit, wave overtopping prediction data according to the range values of a plurality of indicator factors for a predetermined time based on the collected basic ocean data,
Comprising the step of predicting the overtopping wave prediction data including the flow velocity and thickness of the overtopping wave based on the collected basic marine data,
The step of calculating, by the calculation unit, the wave overtopping risk index based on the predicted wave overtopping prediction data,
Based on the above overtopping prediction data, the maximum individual overtopping amount is calculated by the equation below - V _max is the maximum individual overtopping amount, a is the scale parameter (scale parameter), b is the shape parameter (shape parameter), N _ow is the frequency of wave overflow -,
Including, overtopping risk assessment method.
delete delete According to clause 15,
The step of calculating a first wave overtopping risk index by the first index calculation module using wave overtopping prediction data including a condition grade predicted based on the significant wave height and the range value of the wave period,
The condition grade is calculated based on the Douglas swell grade table, and the first overtopping risk index is calculated based on the calculated condition grade.
Further comprising a wave overtopping risk assessment method.
According to clause 15,
The step of calculating a second overtopping risk index by the second index calculation module using overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight,
The sensitivity index includes at least one of human sensitivity, material sensitivity, or topographic sensitivity.
According to clause 15,
The step of calculating a second overtopping risk index by the second index calculation module using overtopping prediction data including a condition grade predicted based on the significant wave height, sensitivity index, and location weight,
The location weight includes a weight for at least one of the East Sea, West Sea, and South Sea, and calculating the second wave overtopping risk index using the following equation - where a = 0.67, b = 0.33 for the East Sea, and a = 0.33 for the West Sea. is a = 0.60, b = 0.40, Namhae is a = 0.65, b = 0.35 -,

Further comprising a wave overtopping risk assessment method.
According to clause 15,
By the third index calculation module, based on the plurality of indicator factors, a preset indicator grade according to at least one of the average range value of the significant wave height, the change value for the wind speed or the range value of the tidal level, and the plurality of indicators The step of calculating the third wave overtopping risk index according to the preset risk by summing each wave overtopping prediction data generated by applying weights according to each preset indicator grade of the indicator factors,
The weight is calculated through AHP analysis as a first weight with less error among a plurality of weights.
Further comprising a wave overtopping risk assessment method.
According to clause 15,
By the fourth index calculation module, the maximum impact due to ground friction is calculated based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth, and the maximum impulse is calculated according to the maximum impulse. 4 The steps for calculating the overtopping risk index are:
Wave overtopping prediction data including maximum wave height and maximum wave period based on at least two indicator factors of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth collected based on the collected marine basic data. Steps to calculate
Further comprising a wave overtopping risk assessment method.
According to clause 25,
By the fourth index calculation module, the maximum impact due to ground friction is calculated based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth, and the maximum impulse is calculated according to the maximum impulse. 4 The steps for calculating the overtopping risk index are:
Calculating wave overtopping prediction data including at least one of the height of the breakwater, the slope of the breakwater, the friction of the breakwater, a preset safety distance range, or a preset physical condition based on the collected basic marine data.
Further comprising a wave overtopping risk assessment method.
According to clause 15,
By the fourth index calculation module, the maximum impact due to ground friction is calculated based on at least one of the significant wave height, the peak period, the duration, the coastal slope, or the coastal water depth, and the maximum impulse is calculated according to the maximum impulse. 4 The steps for calculating the overtopping risk index are:
Calculating the maximum impact due to ground friction based on the calculated overtopping prediction data, and calculating the fourth overtopping risk index using the calculated maximum impact through an instability probability model.
Further comprising a wave overtopping risk assessment method.
According to clause 15,
The step of calculating, by the calculation unit, the wave overtopping risk index based on the predicted wave overtopping prediction data,
By the simulation module, the calculated wave overtopping risk index is calculated by selecting a wave overtopping risk index with a small error through simulation.
Further comprising a wave overtopping risk assessment method.
A computer program stored in a computer-readable recording medium for executing the wave overtopping risk assessment method according to any one of claims 15, 17, 18, and 21 to 28 on a user terminal.