JP7286132B2 - Wave response estimation method for ship and wave response estimation program - Google Patents

Description

The present invention relates to a ship wave response estimation method and a wave response estimation program.

In designing a ship, consideration is given to the response of the ship when subjected to waves. This wave response (hull response) includes, for example, vertical acceleration of the ship, motion relative to the wave surface, water pressure acting on the hull skin, tank and hold internal pressure caused by the inertial force of the cargo, and acting on the cross section of the hull. Shear forces, bending moments, etc. are included. For example, conventionally, an empirically determined bending moment is used as the design load (upper limit of load capacity).

Further, in Patent Literature 1, a fatigue crack propagation analysis of a hull structure is performed. The analysis assumes latent microscopic flaws (initial cracks) that cannot be detected/completely removed at the time of manufacture, and the state in which the microcracks grow and propagate due to repeated stress (stress due to encountered sea conditions) is monitored moment by moment. By simulating, the amount of crack growth in the future is estimated.

Further, Patent Document 2 discloses a driving support system that estimates the structural load of a ship and uses it for navigation support. The system comprises environmental detection means for displaying sea wave motion. Based on the detected sea wave motion, the ship's structural loads due to direct wave excitation are estimated.

Further, Patent Document 3 discloses an individual wave prediction/warning device for estimating the behavior and load of a ship due to individual waves that the ship or offshore structure will encounter after a predetermined time, and determining the safety or danger of the ship.

JP 2007-78376 A JP 2018-509327 A JP-A-2004-338580

By the way, when a designer determines a design load based on empirical rules, the design load is sometimes determined based on a wave response that a ship would never receive in an actual navigation environment. For example, the design wave height is determined as the maximum wave height based on past data in the sea area in which the vessel to be designed is scheduled to navigate. Further, the wave response (for example, bending moment) is obtained when the ship is proceeding head-on against the wave at the ship speed at which the engine is normally output and the wave of the design wave height is the oncoming wave. Furthermore, the design load is determined by multiplying the obtained bending moment by a predetermined safety factor.

However, in actual navigation, countermeasures such as slowing down and avoiding rough weather are taken against bad sea conditions. There is room for streamlining the ship design process, which is based on highly unlikely wave responses.

In a ship wave response estimation method corresponding to claim 1, ship information and wave data , which are information based on ship AIS data including ship position data, are acquired, and only necessary data is extracted from the acquired AIS data. Perform data cleansing, search for wave data closest to the position data to obtain encounter wave data of the ship, apply the encounter wave data to the previously obtained wave response function of the ship, and estimate the wave response of the ship. . As a result, the wave response is estimated based on the encountered wave data, which is the waves actually encountered by the ship, so that the wave response can be estimated more rationally than in the past.

Further, it is preferable to create a database of encountering wave data and ship maneuvering conditions of ships based on AIS data and wave data.

In addition, it is preferable to obtain an index relating to safe operation of the ship based on the data of the encountered waves of the ship, the maneuvering situation, and the wave response, which are stored in a database.

Further, in the ship wave response estimation method corresponding to claim 4, ship information including position data of the ship and wave data are acquired, and wave data at a position closest to the position data is searched for encountering wave data of the ship. applying the encountered wave data to the previously obtained wave response function of the ship, estimating the wave response of the ship, and obtaining the history of the wave response based on the ship information and the wave data .

Also, it is preferable to determine the fatigue soundness of the ship based on the wave response history.

Moreover, it is preferable to estimate the wave response for each individual ship for a plurality of ships.

In a ship wave response estimation method corresponding to claim 7, ship information including position data of the ship and wave data are acquired, and wave data at a position closest to the position data is searched to obtain encounter wave data of the ship. and applying the encountered wave data to the wave response function of the ship obtained in advance to estimate the wave response of the ship. Set the design load by statistically processing the wave response .

Further, it is preferable to improve the accuracy of estimating the wave response using vessel operation information and/or design information.

Further, the wave response function is preferably obtained as a response function in irregular waves corresponding to the ship type and length of the ship.

Further, in a ship wave response estimation program corresponding to claim 10 , a data input step of inputting ship information and wave data , which is information based on ship AIS data including acquired position data of the ship, into the computer; A data cleansing step of extracting only necessary data from the acquired AIS data; an encountered wave data acquisition step of searching for wave data at a position closest to the input position data to find the encountered wave data of the vessel; and an encountered wave data acquisition step. A wave response function application step of applying the data to the wave response function of the ship obtained in advance and a wave response estimation step of estimating the wave response of the ship based on the wave response function are executed. As a result, the wave response is estimated based on the encountered wave data, so that the wave response can be estimated more rationally than before.

Further, in the ship wave response estimation program corresponding to claim 11, there is provided a data input step of inputting ship information including acquired position data of the ship and wave data into the computer; a wave response function application step of applying the encountered wave data to a previously obtained wave response function of the ship; A wave response estimation step of estimating a wave response is executed, and in the encounter wave data acquisition step, the encounter wave data of the ship is obtained for each time. A wave response history recording step to be stored as is further executed .

Moreover, it is preferable to further include a ship fatigue soundness evaluation step of obtaining the fatigue soundness of the ship based on the wave response history recorded in the wave response history recording step.

Moreover, it is preferable to further include a vessel designation step of designating an individual vessel from among a plurality of vessels and selecting vessel information of the designated vessel from among the vessel information.

Moreover, it is preferable to further include a statistical evaluation step of performing statistical evaluation based on the wave response as a history recorded in the wave response history recording step.

According to the ship wave response estimation method of the present invention, ship information and wave data , which are information based on ship AIS data including ship position data, are acquired, and only necessary data is extracted from the acquired AIS data. Data cleansing is performed, the wave data closest to the position data is searched to obtain the encounter wave data of the ship, and the encounter wave data is applied to the previously obtained wave response function of the ship to estimate the wave response of the ship. As a result, the wave response is estimated based on the encountered wave data, in other words, the wave data that the ship has not encountered is excluded, so that the wave response can be estimated more rationally than before.

Also, based on the AIS data and wave data, it is possible to examine the appropriateness of ship maneuvering judgments and route settings by creating a database of ship encounter wave data and ship maneuvering situations.

In addition, it is possible to operate with high safety by obtaining an index for safe operation of the ship based on the data of the encountered waves of the ship, the maneuvering situation, and the response to the wave, which are stored in a database.

Further, according to the ship wave response estimation method of the present invention, ship information including ship position data and wave data are acquired, and wave data at a position closest to the position data is searched to obtain encounter wave data of the ship. , applying the encountered wave data to the wave response function of the ship obtained in advance, estimating the wave response of the ship, obtaining the history of the wave response based on the ship information and wave data, and obtaining the wave response history along the actual route Changes in response can be confirmed.

In addition, by obtaining the fatigue soundness of the ship based on the wave response history, it is possible to improve the accuracy of planning inspections, setting the sales price of a second-hand ship, and setting insurance premiums.

In addition, by estimating the wave response for each individual ship, it is possible to confirm the wave response on an individual ship basis.

Further, according to the ship wave response estimation method of the present invention, ship information including ship position data and wave data are acquired, and wave data at a position closest to the position data is searched to obtain encounter wave data of the ship. , apply the encountered wave data to the wave response function of the ship obtained in advance, estimate the wave response of the ship, estimate the wave response for each individual ship, and estimate the estimated wave for each ship. By statistically processing the responses and setting the design load, it is possible to set the design load based on the wave response received by the actual ship.

In addition, by estimating wave response using ship operation information and/or design information, information such as ship stowage and engine output data will be reflected in wave response estimation, resulting in more accurate wave response estimation. Response estimation is possible.

Further, the wave response function can be obtained as a response function in irregular waves corresponding to the ship type and length of the ship, thereby obtaining a response function in irregular waves for each individual ship.

Further, according to the ship wave response estimation program of the present invention, a data input step of inputting ship information and wave data, which is information based on ship AIS data including acquired ship position data, into a computer; a data cleansing step of extracting only necessary data from the AIS data obtained; an encountering wave data acquiring step of searching for wave data at a position closest to the input position data to find the encountering wave data of the ship; and an encountering wave data to a previously obtained wave response function of the ship, and a wave response estimation step of estimating the wave response of the ship based on the wave response function. As a result, the wave response is estimated based on the encountered wave data, so that the wave response can be estimated more rationally than before.

Further, according to the ship wave response estimation program of the present invention, there are provided a data input step of inputting ship information including obtained ship position data and wave data into a computer, Encountered wave data acquisition step of searching data to obtain encountered wave data of the ship; wave response function application step of applying the encountered wave data to a previously obtained wave response function of the ship; and wave response function of the ship based on the wave response function. A wave response estimation step of estimating a response is executed, and the encountered wave data of the ship is obtained for each time in the encountered wave data acquisition step, and the wave response estimated for each time in the wave response estimation step is recorded as a history for each time. By further executing the wave response history recording step to be stored, it becomes possible to confirm changes in the wave response along the actual route.

In addition, based on the wave response history recorded in the wave response history recording step, by further providing a ship fatigue soundness evaluation step that seeks the ship's fatigue soundness, it is possible to formulate an inspection plan and sell the ship price as a second-hand ship. , and the accuracy of setting insurance premiums can be improved.

In addition, by further including a ship designation step of designating an individual ship from among a plurality of ships and selecting the ship information of the designated ship from among the ship information, it becomes possible to check the wave response on an individual ship basis. .

Further, by further providing a statistical evaluation step of performing a statistical evaluation based on the wave response as a history recorded in the wave response history recording step, the design load based on the wave response received by the actual ship can be estimated. can be set.

1 is a block diagram illustrating a ship wave response estimation system according to an embodiment; FIG. It is a flowchart which illustrates the wave response estimation flow (simplified method) of the ship which concerns on this embodiment. 10 is a flowchart illustrating a search flow for a response function in irregular waves in the wave response estimation flow (simplified method) of a ship according to the present embodiment; It is a figure explaining the memory content of an AIS database. It is a figure explaining the memory content of a wave database. It is a figure explaining the time-history data of the encounter wave of a ship. It is an example of a response function in regular waves, and is a diagram illustrating a stress frequency response function (stress RAO) for each ship speed (V=Vs, V=0.75Vs). It is an example of a response function in regular waves, and is a diagram illustrating a stress frequency response function (stress RAO) for each ship speed (V=0.5Vs, V=0.25Vs). FIG. 4 illustrates a wave spectrum; FIG. 4 illustrates a hull response characteristic during short-term sea conditions, which is an irregular wave response function; FIG. 5 illustrates the process of estimating vessel response to encountered waves using vessel response characteristics during short-term sea conditions. FIG. 4 is a diagram illustrating a short-term distribution (Rayleigh distribution) of stress amplitude; FIG. 10 is a diagram showing an example of when the history of encountered waves is displayed on the display; FIG. 10 is a diagram showing an example of displaying a history of vessel responses on a display; FIG. 5 is an example of long-term forecasting and illustrates longitudinal stresses on a container ship deck; FIG. 4 is a diagram illustrating the relationship between a long-term frequency distribution of stress ranges and an SN diagram; FIG. 4 is a diagram illustrating an SN diagram; FIG. 4 illustrates long-term predicted loads for vertical bending moments applied to a ship; It is a figure which illustrates the wave occurrence frequency table of the North Atlantic sea area (area 8, 9, 15, 16 of GWS) recommended by IACS (International Federation of Classification Societies). FIG. 20 is a diagram exemplifying a wave occurrence frequency table of sea phenomena encountered in the same sea area as in FIG. 19 according to the present embodiment; FIG. 10 is a diagram illustrating a joint probability distribution of wave height and wave period created along with accumulation of data of waves encountered by ships; 21. It is a figure which extracts the dashed-line frame of FIG. 21, and is a figure which illustrates the simultaneous probability distribution of a wave height, a wave period, and a relative wave direction. FIG. 23 is an enlarged view of a predetermined cell of the joint probability distribution of FIG. 22 and illustrates joint probability distributions of wave height, wave period, relative wave direction, and ship speed. It is a flowchart which illustrates the wave response estimation flow (short-term ocean wave spectrum method) of the ship which concerns on this embodiment. FIG. 4 illustrates the wave response estimation process using the short-term ocean wave spectrum method;

FIG. 1 illustrates a ship wave response estimation system according to this embodiment. The system includes a storage device 100 , an arithmetic device 200 and a display device 300 . The storage device 100, the arithmetic device 200, and the display device 300 are composed of, for example, a computer.

The storage device 100 is composed of, for example, a hard disk or memory of a computer. The storage device 100 comprises a RAO database 110 , an AIS database 120 , a wave database 130 and a wave response estimation database 140 .

The RAO database 110 stores RAOs (Response Amplitude Operators, frequency response characteristics) of hull structural members. The RAOs stored in the RAO database 110 may be referred to as regular wave response functions, as compared with the random wave response functions of FIG. 10, which will be described later.

The RAO is a function representing the amplitude value of the hull response in regular waves on a wave frequency or wavelength basis. For example, in RAO, it is represented by a value obtained by dividing the response amplitude by the wave amplitude or by a dimensionless value. For example, the hull stress σ is represented by σ/h, and the vertical bending moment VBM is dimensionally represented by VBM/(ρgL̂2Bh). Note that ρ is water (seawater) density, g is gravitational acceleration, L is ship length, B is ship width, and h is wave amplitude.

Since the vertical bending moment VBM is dimensionless with the ship length L and the ship width B, the RAO changes according to the ship type and ship length of the target ship. Also, the wave response changes according to the ship speed. Therefore, the RAO database 110 stores a plurality of types of RAOs according to ship type, ship length, and ship speed.

It is known that the RAO can extend the RAO of a standard ship of arbitrary length according to the length of the ship by applying the law of similarity to the length of the ship, for example. Therefore, instead of storing RAOs corresponding to ship lengths, the RAO database may store only RAOs of standard ships having a predetermined ship length.

7 and 8 show examples of RAO. In each graph, the horizontal axis indicates the wave frequency ω, and the vertical axis indicates the stress amplitude at a unit wave amplitude (wave amplitude: 1 m, wave height: 2 m). The ship type is a post-Panamax container ship, and the stress shown in FIGS. 7 and 8 is the stress in the longitudinal direction of the upper deck plate of the ship.

7 and 8 exemplify the stress RAO, the RAO stored in the RAO database 110 is not limited to the stress RAO. That is, the RAO database 110 stores various RAOs that indicate wave responses of ships. Wave responses include vertical acceleration of the ship, motion relative to the wave front, fluctuating pressure acting on the hull, shear forces, and bending moments.

The upper part of FIG. 7 shows a graph of the stress RAO at the service speed Vs, ie the speed obtained by allowing for a certain sea margin in the service power of the engine in full voyage conditions (for example the maximum speed). A graph of the stress RAO at 75% of the sailing speed (V=0.75Vs) is shown in the lower part of the figure.

In addition, characteristic lines for each wave direction are shown in both the upper and lower stages of FIG. Specifically, characteristic lines are shown in increments of 60° from 0° to 360°, where the angle of encounter χ (heading angle) of the ship with respect to waves is 0° to 360°. Here, the wave encounter angle χ=180° indicates an oncoming wave that receives the wave from the bow direction, and the wave encounter angle χ=0° indicates the following wave that receives the wave from the stern direction.

The upper part of FIG. 8 shows a graph of the stress RAO at 50% of the sailing speed Vs (V=0.5Vs), similar to FIG. A graph of the stress RAO at 25% of the sailing speed Vs (V=0.25Vs) is shown in the lower part of the figure.

Such a stress RAO can be obtained in advance by performing a series analysis of FE stress analysis by applying an external force predicted by the strip method, panel method, or the like to the FE model. In addition, a stress RAO and other wave response RAOs can be obtained by model experiments in waves.

As will be described later, in the wave response estimation process according to the present embodiment, ship information including position data of the ship to be estimated and an RAO (regular wave response function) corresponding to the encountered sea conditions are used.

The AIS database 120 stores AIS (Automatic Identification System) data. As AIS data, various ship information including ship position data is stored in the AIS database 120 . AIS data can be roughly divided into static information, dynamic information, voyage-related information, and safety-related messages.

The static information includes the IMO number of the ship, which is the ID of the ship (ship ID), the signal code and name of the ship, the length of the ship (captain), the width of the ship, the type of ship (type of ship), and the ship Top positioning system antenna positions are included.

The dynamic information includes position (latitude, longitude), UTC (Universal Time Coordinated) time, course (course over ground), speed over ground, heading, rate of turn, angle of inclination, pitch, roll, and the like.

The voyage-related information includes the draft of the vessel, dangerous cargo, port of destination, estimated time of arrival (ETA), voyage plan, and the like.

The safety-related message includes, for example, a message including navigation information, weather, oceanographic information, or warnings during ship maneuvering assistance.

As exemplified in FIG. 4, the AIS database 120 stores the above-described AIS data of ships passing through the sea area (evaluation target sea area) where wave response estimation is performed, for example, in chronological order for each ship ID. .

For example, Finnish company Napa has a data provision service called NAPA Fleet Intelligence that provides AIS data, and it is possible to acquire AIS data for all ships that sail in the sea area to be evaluated and are equipped with an AIS system. .

For example, GWS (Global Wave Statistics) areas 8, 9, 15, and 16 are the evaluation target sea areas. The area extends from the southern tip of Greenland in the north to the west coast of Ireland in the east. In addition, ships on the East Asia-Suez Canal-Europe route are included in the assessment area off the coast of Portugal.

Time-series data is used to estimate the wave response. For example, the AIS data of all ships navigating the above area is acquired at intervals of one hour starting from 1:00 on September 30, 2016 and ending at 00:00 on October 1, 2017, and is stored in the AIS database 120. stored in

Note that the start time and end time of the time-series data are not limited to the above examples. For example, since the service life of a ship is generally assumed to be 25 years, the AIS database 120 may store AIS data for 25 years in the sea area to be evaluated.

FIG. 4 lists specific examples of vessel information including vessel position information stored in the AIS database 120 . That is, the AIS database 120 stores time-series data such as ship ID, ship type, ship length, time, longitude, latitude, course, ship speed, heading angle, and the like.

Returning to FIG. 1, the wave database 130 stores wave data for the entire sea area to be evaluated. For example, according to the global wave estimation database of the Japan Weather Association, wave height, period, Data on wave direction, wind direction, and wind speed are converted into data in 1-hour increments. For example, the wave data of the same sea area (GWS areas 8, 9, 15, 16) and the same period (1:00 on September 30, 2016 to 0:00 on October 1, 2017) as the AIS data are stored in the wave database 130. remembered.

Hereinafter, the sea conditions for each time interval (one hour) of the wave data are referred to as short-term sea conditions. Short-term sea state refers to the state of the sea state in the time when the statistical properties of ocean waves (wind waves) are constant and similar sea surface conditions persist. Short-term ocean conditions are represented by a combination of three types of data: significant wave height, mean wave period (or significant wave height), and possibly wave direction. Generally, the duration of short-term ocean phenomena is considered to be 1-2 hours, which corresponds to about 1000 encounter waves.

Further, in the above explanation, the significant wave height refers to the wave height obtained by taking the average of the highest ⅓ of N waves continuously passing through a certain point. Significant wave height is known to be close to the observed wave height, and is generally used as a representative value of wave height. For example, Hs (significant) is used as a parameter of significant wave height. Also, Hs [m] is used as a unit. Further, the significant period means the period obtained by averaging 1/3 of the highest waves when N waves continuously passing through a certain point are observed.

In the above description, the average wave period is based on, for example, Recommendation 34 of IACS (International Association of Classification Societies), zero up-cross average wave period Tz, that is, the time history waveform of the wave zero up-crosses Time interval averages are used. For example, second [s] is used as the unit of the mean wave period Tz.

Specific examples of wave data stored in the wave database 130 are listed in FIG. That is, the wave database 130 stores time-series data such as time, longitude, latitude, significant wave height, significant period, and wave direction.

Returning to FIG. 1, the wave response estimation database 140 stores the hull response data (see FIG. 11) to the encountered waves calculated by the calculator 220. FIG. This will be discussed later.

Referring to FIG. 1 , arithmetic device 200 includes input unit 210 , arithmetic unit 220 , and analysis unit 230 . Arithmetic device 200 may be, for example, a CPU of a computer.

The input unit 210 receives vessel information including position data of vessels navigating the evaluation target sea area from the AIS database 120 . Along with this, the input unit 210 receives wave data of the evaluation target sea area from the wave database 130 .

The calculation unit 220 acquires the RAO of the ship from the RAO database 110 in addition to the ship information including the position data of the ship and the wave data input to the AIS database 120, and based on these, the ship encounters waves. Estimate the wave response (short-term ocean wave response).

The analysis unit 230 acquires the short-term wave responses of multiple ships over a plurality of periods calculated by the calculation unit 220, analyzes the ship maneuvering pattern for each ship, statistically processes the applied load, and estimates fatigue damage for each ship. conduct. Through such statistical processing of acting loads and estimation of fatigue damage for each ship, the long-term frequency distribution of wave responses received by ships can be estimated. Based on this estimation, it is possible to estimate the maximum wave height that the ship will encounter in its lifetime, and it is possible to determine a reasonable design load, such as determining the design load based on the estimated maximum wave height.

The display device 300 can output the computation result of the computation unit 220 and the analysis result of the analysis unit 230 . The display 300 is composed of, for example, a computer display.

<Ship wave response estimation flow>
FIG. 2 illustrates a ship wave response estimation flow according to the present embodiment. Further, FIG. 3 illustrates a flow for calculating the response function in irregular waves, which is a part of the same flow. A program that allows the computer to function as the storage device 100, the arithmetic device 200, and the display device 300 of FIG. 1 and that can execute each step of the flow of FIGS. executed.

For example, by reading a recording medium such as a CD storing the program, the computer functions as the storage device 100, the arithmetic device 200, and the display device 300 in FIG. Each step can be executed.

First, a data input step (S100, S200) is performed in which AIS data and wave data are input to the input unit 210. FIG.

From the AIS database 120, the AIS data of a plurality of ships (evaluation target ship group) navigating the evaluation target sea area during the period described above is input to the input unit 210 (S100). As described above, AIS data is vessel information including vessel position data, and includes vessel ID, vessel type, vessel length, vessel width, time, latitude, longitude, course, and speed data. Also, for example, the sampling interval of AIS data is set to 1 hour, which indicates the period of short-term sea conditions.

When inputting AIS data, data cleansing may be performed to extract only necessary data from the acquired AIS data. For example, the target to be extracted as a group of ships to be evaluated is basically all ships navigating the sea area to be evaluated. AIS data of ships recognized as In addition, the AIS data of vessels whose wakes are clearly different from those of the majority of other vessels navigating the evaluation target sea area are also excluded from acquisition targets as noise.

When the AIS data for each of the group of ships to be evaluated is input to the computing device 200, next, wave data from the wave database 130 is input to the computing device 200 via the input unit 210 (S200). For example, the wave data of the evaluation target sea area for the period described above is input to the input unit 210 . Wave data includes, for example, time, longitude, latitude, significant wave height, significant period, and wave direction. Also, for example, the sampling interval of wave data is set to 1 hour, which indicates the period of short-term sea conditions.

Next, the operation section 220 executes the encountered wave data acquisition step (S300, S400). In the encounter wave step, the wave data actually encountered by the evaluation target ship are extracted from the wave data of the evaluation target sea area.

Conceptually, among the wave data of the sea area to be evaluated, the AIS data of the ship to be evaluated is overlapped with the encountered wave data. The calculation unit 220 selects an arbitrary ship (selected ship) for which calculation has not yet been performed from among the group of ships to be evaluated, and extracts the AIS data (AIS data group of the selected ship). Furthermore, the calculation unit 220 extracts the oldest AIS data from among the AIS data group of the selected ship while the ship is navigating the evaluation target sea area. Furthermore, the calculation unit 220 extracts the wave data closest to the position (latitude, longitude) of the extracted AIS data (S300).

Next, the computing unit 220 extracts the wave data at the same time as the AIS data from among the wave data closest to the position of the extracted AIS data, and obtains the time history data (S400). FIG. 6 exemplifies the time history data of the waves encountered by the selected vessel. The time history data is obtained by adding each item of AIS data and wave data, and includes, for example, ship ID, ship type, ship length, time, longitude, latitude, significant wave height, significant period, relative wave angle), ship speed, etc. are recorded. The time-history data of the encountered waves, which includes the encountered wave data and the vessel maneuvering situation, is recorded in, for example, the wave response estimation database 140 (see FIG. 1) and made into a database.

Next, the calculation unit 220 obtains a response function in irregular waves according to the type of the selected ship and the length of the ship (S500). In this step S500, a wave response is predicted in short-term sea conditions in which wave conditions are considered to be substantially constant. In estimating such a wave response, a response function in irregular waves is obtained.

FIG. 3 illustrates a flow for obtaining an irregular wave response function. The flow in FIG. 3 is roughly divided into two steps. As the first step, a wave response function application step consisting of S510 and S520 is executed. Furthermore, as the next step, a wave response estimation step including S530 to S550 and S600 in FIG. 2 is executed.

In the wave response function application step (S510, S520), a response function in regular waves to be applied to the selected vessel is obtained. First, the calculation unit 220 refers to the RAO database 110 to obtain a standard ship response function in regular waves, which is a wave response function obtained in advance (S510). 7 and 8 show an example of stress RAO, which is a regular wave response function. Since these have been described above, their description is omitted here.

Next, the calculation unit 220 applies this predetermined regular wave response function of the standard ship to the selected ship. Specifically, under the assumption that the standard ship and the selected ship have similar shapes, the response function in regular waves of the standard ship is expanded to obtain the response function in regular waves of the selected ship (S520). Furthermore, the calculation unit 220 acquires the wave spectrum Sw(ω) from the wave response estimation database 140 (S530).

FIG. 9 exemplifies wave spectra used for fatigue evaluation of general merchant ships. Here, the wave spectrum Sw(ω) represents the wave energy according to the period of the wave for each angular frequency ω of the wave, and is expressed by the following formula (1).

By performing linear superposition using the response function in regular waves obtained in step S520 and the wave spectrum of the above formula (1), the response function in irregular waves for the selected vessel is obtained (S540). By integrating this response function in random waves, the standard deviation _RL of the stress in the long-wave term (single-wave direction) random waves can be obtained as in the following formula (2).

Here, the following formula (3) holds for the function S(ω, χ:H _s , T _z ) in the square root.

Also, the standard deviation R in the short-wavelength random waves can be obtained using the following formula (4) that takes into account the directional dispersion β of the random waves (S550). This standard deviation R is a value representative of short-term sea conditions and is also called a short-term parameter.

FIG. 10 exemplifies the response function of the standard deviation R determined from Equation (4). The horizontal axis indicates the average wave period Tz [s]. The parameters on the vertical axis indicate, in order, standard deviation R, water density ρ (RHO), gravitational acceleration G, ship length L, ship breadth B, and significant wave height Hs (H). Parameters other than standard deviation R and significant wave height H are fixed values that do not fluctuate due to short-term sea conditions once the ship is determined. The legend also indicates the ship's relative angle of encounter χ with respect to the waves. That is, in the graph of FIG. 10, the significant wave height Hs, the mean wave period Tz, and the angle of encounter χ with the wave are used as input variables, and the standard deviation R can be obtained as the output.

For example, by applying the angle of encounter χ with the wave, the mean wave period Tz, and the significant wave height Hs of the time history data of the encountered waves obtained in step S400 (see FIG. 6) to the graph of FIG. A standard deviation R corresponding to the data is obtained (FIG. 11, FIG. 2 S600).

Once the standard deviation R, which is a short-term parameter, is obtained, the distribution of response amplitudes in the short-term sea conditions can be obtained. It is generally known that the probability distribution of response amplitudes can be assumed to be approximated by the Rayleigh distribution. A probability density distribution p(x) that follows the Rayleigh distribution is shown in the following formula (5).

Further, FIG. 12 shows a short-term sea phenomenon probability distribution of stress amplitude (σA) as an example of Rayleigh distribution. In this figure, the standard deviation R=0.8.

The probability q that the response amplitude in a short-term ocean phenomenon exceeds a certain value _x1 is given by the following formula (6) using the standard deviation R.

Generally, it is known that the number of times a ship encounters waves during one period of short-term sea conditions (approximately one hour) is 1000 times. , the maximum value (representative value) of the wave response to the encountered sea condition obtained in step S400. It is known that the maximum expected value of 1/1000 is 3.87 times the standard deviation R in the Rayleigh distribution. Based on the above calculations, the calculation unit 220 obtains the wave response value (3.87R) corresponding to the time history data of the encountered waves obtained in step S400 (see FIG. 6).

Next, the calculation unit 220 acquires the next oldest AIS data after the time history data of the encountered waves obtained in step S400 for the selected vessel, and returns to step S300. In this way, the calculation unit 220 repeats the processing from step S300 to step S600 for the AIS data of all times for the selected vessel, and obtains the wave response history for the selected vessel (S700). The obtained wave response history is stored in the wave response estimation database 140 (wave response history recording step).

When the wave response of all wakes in the evaluation target sea area is obtained for the selected vessel, the calculation unit 220 causes the display 300 to display the encountered wave map as illustrated in the lower part of FIG. With reference to the lower part of FIG. 13, plots indicated by white circles (◯) indicate encounter wave data. The surrounding shading indicates the wave height distribution in the surrounding sea area. In this way, by two-dimensionally displaying the encountered wave data and the wave data of the surrounding sea area, it is possible to confirm the course of the ship to avoid rough weather and the sea conditions to be avoided.

Further, FIG. 14 illustrates a two-dimensional map (wave response map) in which the wave response is reflected in the encountered wave map of FIG. Compared to FIG. 13, the size of the plot has changed, and the size of this plot indicates the wave response amount (for example, wave load). That is, the wave response map indicates the history of the wave response of the selected vessel. After creating the encountered wave map, the computing unit 220 creates a wave response map and causes the display 300 to display it.

Further, when the wave response of all wakes of the selected ship in the evaluation target sea area is obtained, the calculation unit 220 calculates the maximum response during the service period of the selected ship (maximum response during service), the worst sea condition (worst sea condition during service), And the degree of fatigue damage is obtained (S800).

The maximum response during the service period corresponds to the maximum value of the wave response amount obtained for the selected vessel. That is, as described above, when obtaining the wave response of the ship in the short-term sea state in step S600, the wave response is obtained based on the wave that occurs once in 1000 times, that is, the worst sea state in the short-term sea state. be done. The wave response map in FIG. 14 is obtained by obtaining this over the entire wake of the evaluation target sea area. Therefore, in this step S800, the wave response in the most severe sea condition (especially the worst sea condition among the worst sea conditions) among the worst sea conditions of the short-term sea conditions in each track becomes the maximum response during the in-service period.

Also, the worst sea condition during the in-service period corresponds to the encountering wave, for example, the maximum significant wave height Hs. Since the wave response varies depending on the average wave period Tz, the angle of encounter with the wave χ, and the ship speed, the position (longitude, latitude) where the maximum value of the wave response is obtained and the worst sea condition during the in-service period are determined. position may not be the same.

In-service refers to the operation of a vessel on a route within the sea area subject to evaluation, and in-service period refers to the period of operation on the route. Therefore, as described above, if the sampling period of AIS data and wave data is limited from 1:00 on September 30, 2016 to 0:00 on October 1, 2017, before 1:00 on September 30, 2016 and , the operation period after 00:00 on October 1, 2017 will be excluded. Considering that the life of a ship is generally 25 years, the sampling period of AIS data and wave data is at least 25 years in estimating the maximum response during the service period, the worst sea condition during the service period, and the degree of fatigue damage described later. is preferred.

When the maximum response during the service period and the worst sea conditions during the service period of the selected vessel are obtained, the calculation unit 220 selects another vessel that is stored in the AIS data and whose wave response has not yet been obtained, returns to step S300 again, For the ship concerned, the wave response is obtained over the entire time.

In step S800, when the encountered wave data, the standard deviation R, the wave response amount, the maximum response during the service period, and the worst sea conditions during the service period are obtained for all ships included in the group of ships to be evaluated, the calculation unit 220 processes these data. is sent to the analysis unit 230 . The analysis unit 230 performs various analyzes on ships navigating in the evaluation target sea area based on the received various data. The above various data are also sent to and stored in the wave response estimation database 140 .

When the waves encountered by the group of ships to be evaluated are obtained, a frequency table of occurrences of waves encountered in the sea area to be evaluated, such as that shown in FIG. 20, is obtained. In FIG. 20, the horizontal axis indicates the mean wave period Tz, and the vertical axis indicates the significant wave height Hs. Numerical values in a cell indicate the probability of occurrence of a short-term sea phenomenon, which is the significant wave height Hs next to the cell and the mean wave period Tz on the cell.

With reference to the encounter wave occurrence frequency table in FIG. Tz], the long-term exceedance probability Q of the wave response can be obtained.

Specifically, the long-term exceedance probability Q is represented by the following formula (7) using the short-term exceedance probability q and the short-term ocean phenomenon occurrence probability q (Hs, Tz).

Furthermore, by using the following formula (8) using the wave direction (relative wave direction) probability w(χ), the long-term probability distribution Q in consideration of the wave direction can be obtained.

FIG. 15 shows an example of long-term exceedance probability. The horizontal axis indicates the logarithm of the exceedance probability Q, and the vertical axis indicates the stress amplitude (S/2) as an example of the response amplitude. The wave direction probabilities have a uniform distribution (All headings).

Generally, it is known that the number of waves that a ship encounters in its lifetime is close to ¹⁰⁸ times. Therefore, in obtaining the design stress of the ship, referring to FIG. 15, the stress σ when receiving a large wave once in 10 ⁸ times (−logQ=8) should be determined as the design stress of the ship. For example, when the relative wave direction is All Heading, σ=185 Mpa corresponding to −logQ=8, or a value obtained by multiplying this by a predetermined safety factor, is determined as the design stress. Thus, through statistical processing of the loads acting on the hull based on the estimation of the hull response, it is possible to determine an appropriate design load based on the encountered waves (statistical evaluation step).

The maximum load distribution obtained by the above procedure is illustrated in FIG. The horizontal axis is the ship length L [m], and the vertical axis is normalized by dividing the vertical bending moment VBM by the water density ρ (RHO), the gravitational acceleration g, the ship length L, and the ship width B.

In obtaining the distribution, we assumed a constant ship speed (75% of maximum sea speed) and a uniform wave direction. The distribution of the maximum load based on the long-term prediction, that is, the distribution of the maximum load based on a big wave that occurs once every 10 ⁸ times is shown in the black circle plot (●) and the solid line connecting the plots (Longterm pred. 75% vs, Allheadings, AIS + Hindcast). is indicated by

In addition, the black triangle plot (▲) plotted above this AIS + Hindcast curve and the dashed line connecting the plots (Longterm pred. 75% vs. Allheadings, Hindcast) are the entire sea area to be evaluated, that is, the sea conditions other than the sea conditions encountered by the ship. The distribution of the maximum load based on the worst sea conditions extracted from the short-term sea conditions including the As can be understood by comparing the two, the maximum load based on the actual waves encountered by the ship is lower than the maximum load based on the short-term sea conditions of the entire sea area to be evaluated.

The white circle plots (○) scattered at the bottom of the graph indicate the sampling period of the AIS data and wave data mentioned above, which was narrowed down from 1:00 on September 30, 2016 to 0:00 on October 1, 2017. Indicates the maximum load of an individual ship when Both values are lower than those of the AIS+Hindcast curve, and the validity of the design load by the AIS+Hindcast curve is recognized.

In addition, using the above-described long-term prediction, it becomes possible to predict the degree of fatigue damage to the ship (ship fatigue soundness evaluation step). For example, converting the above formula (8) into the probability distribution function P results in the following formula (9).

By differentiating P(x) with respect to x, the probability density function p(x) shown in the following formula (10) is obtained.

The long-term frequency distribution of the stress range Δσ can be obtained by multiplying p(x) by the total number N of repetitions of the response (stress), that is, the number of waves (N=10 ⁸ ) that the ship encounters during its lifetime. An example of the long-term frequency distribution of Δσ is shown in FIG. 16 by solid square plots (▪). Also, the long-term frequency distribution in FIG. 16 is shown in a log-log graph.

Using this long-term frequency distribution, it is possible to estimate the degree of fatigue damage based on long-term prediction. The degree of fatigue damage D can be obtained from the stress range Δσ of wave stress included in one type of wave response, the SN diagram shown in FIG. 16, and the following formula (11). In FIG. 16, the horizontal axis indicates the frequency (log(N)) and the vertical axis indicates the stress range Δσ.

In Expression (11), n _i indicates the number of repetitions in the stress range S _i (=Δσ), and N _i indicates the number of repetitions until fracture in the stress range S _i (=Δσ). The number of repetitions N in the stress range S is represented by the following formula (12) from the SN diagram.

In formula (12), S is the stress range, N is the number of stress repetitions until fracture, and M and K are constants of the SN diagram. The constants M and K are determined by the material, welding, construction mode, and the like. FIG. 17 shows an SN diagram used for fatigue evaluation of general merchant ships. B to W in the figure are properly used depending on the welding and structural style of the target structure. For example, when evaluating fatigue cracks in the base material, a B diagram is used, and when evaluating fatigue cracks in butt welds, a D diagram is used.

By using the method for calculating the degree of fatigue damage, it is possible to estimate the degree of fatigue damage of a ship in one voyage, for example. For example, referring to Equation (11), if the total number of stress repetitions _ni is considered to be the total number of waves received by the ship during one voyage, then the total number of waves received by the ship during one voyage can be calculated (1000 per period ₎ . The value obtained by multiplying the number of short-term sea phenomena by 1000 is the total number of stress repetitions Σn _i . Further, from the encounter wave appearance frequency distribution in FIG. 20, the number of stress repetitions n _i corresponding to the stress range Δσ _i is distributed according to the ratio of each cell. As a result, the degree of fatigue damage D in one voyage can be obtained.

Further, for example, when the starting point of the sampling period of the AIS data and the wave data is before the start of service of a predetermined ship, the degree of fatigue damage can be obtained based on the wave response received by the ship from the start of service.

For example, the degree of fatigue damage is obtained based on the wave response that the ship has received from the start of service, and this is used as an index of the fatigue soundness of the ship. For example, when selling the ship as a second-hand ship, the selling price can be appropriately set based on the fatigue soundness.

In addition, the fatigue life of the ship can be estimated based on the calculation result described above. The fatigue life Fatigue life [year] is expressed by the following formula using the rupture life DCR. Generally DCR=1 is used. The design life corresponds to the statistical parameter N of the long-term prediction, and for general commercial ships, for example, it is assumed to be 25 years (N=10 ⁸ times). Fatigue evaluation is performed by comparing the design life and the fatigue life.

As described above, as shown in FIG. 20, by obtaining encounter wave data for all ships to be evaluated, the occurrence frequency of encounter waves (occurrence frequency of encounter waves) of short-term sea conditions in the evaluation target sea area can be calculated. Obtainable. For example, this encounter wave occurrence frequency table is stored in the wave response estimation database 140 (see FIG. 1).

On the other hand, FIG. 19 shows the wave occurrence frequency in the North Atlantic sea area (wave occurrence frequency in the entire sea area), including the evaluation target sea area that is the basis of the frequency table in FIG. are summarized in the table. This table is based on IACS Recommendation No. 34. As in FIG. 20, the vertical axis indicates the significant wave height Hs, and the horizontal axis indicates the mean wave period Tz.

Compared to FIG. 19, which is based on the wave data of the entire sea area including the encountered waves, FIG. The maximum value of the period Tz is relatively low. 20 (occurrence frequency of waves encountered), cells with the highest probability of occurrence are assigned to lower significant wave heights in FIG. .

In this way, the short-term sea conditions based on the encountered wave data were milder than the short-term sea conditions of the entire evaluation sea area, and it is considered that the influence of ship maneuvering such as avoidance of rough weather was taken into account. As will be described later, by estimating the wave response using the wave occurrence frequency that takes into account the influence of ship maneuvering as shown in FIG. Rational (realistic) wave response estimation can be performed as compared with the case of performing

In addition, along with the creation of the encountered wave data, the simultaneous ship maneuvering/wave probability distributions shown in FIGS. 21 to 23 are obtained. These data are stored in the wave response estimation database 140 (see FIG. 1). In addition, as will be described below, it is possible to obtain an index relating to the safe operation of the ship based on the encountered wave data, ship maneuvering situation, and wave response.

FIG. 21 illustrates an encounter wave occurrence frequency table similar to FIG. The vertical axis indicates the significant wave height Hs, and the horizontal axis indicates the mean wave period Tz. FIG. 22 exemplifies a table obtained by extracting the portion surrounded by the dashed frame in FIG. 21 . Each cell shows a pie chart of joint probability distributions.

FIG. 23 exemplifies the cell surrounded by the dashed frame in FIG. 22, that is, the cell with significant wave height Hs=16.5, mean wave period Tz=11.5, and frequency of occurrence 0.2. Numbers attached to the circumference indicate relative wave directions. Also, the farther away from the center of the circle, the higher the frequency of occurrence. Furthermore, a plurality of characteristic lines are illustrated within the circle. These indicate ship speeds when encountering short-term sea conditions with significant wave height Hs = 16.5 [m] and mean wave period Tz = 11.5 [s]. Probabilities of occurrence of ship speeds in the ranges of 0 to 0.25 Vs, 0.25 to 0.5 Vs, 0.5 to 0.75 Vs, and 0.75 to 1 Vs are shown.

With reference to FIG. 23, it is understood that many vessels tend to slow down or stop to let the waves pass by as large as Hs=16.5m. Also, it is understood that the sea conditions are dealt with at a relative wave direction of 150° at any ship speed.

In this way, in addition to the probability of occurrence of significant wave height Hs and mean wave period Tz, the probability distribution of relative wave direction and ship speed can be obtained, so that the design load can be set in consideration of actual ship maneuvering in stormy weather. can be done. Alternatively, it can be used for assisting ship maneuvering, etc., with reference to previous cases of actual ship maneuvering in stormy weather. In addition, it is possible to predict the sea conditions along the course and propose to the ship the optimum speed and course for safety. Furthermore, it will be possible to create a safe operation manual that proposes ship speed and angle of encounter with waves (course direction) according to short-term sea conditions.

<Short-term ocean wave spectrum method>
In the wave response estimation flow exemplified in FIG. 2, the response function in irregular waves is obtained according to the ship type and length (S500), and the wave response is obtained based on the response function in irregular waves. It is not limited to this form. For example, as exemplified in FIG. 24, the wave spectrum of short-term sea conditions may be used to determine the hull response to the encountered waves.

FIG. 24 is obtained by replacing S200, S500 and S600 of FIG. 2 with S1200, S1500 and S1600. In describing the flow of FIG. 24, the description of the same processes as in FIG. 2 will be omitted as appropriate. In step S1200, in addition to the time, longitude, latitude, significant wave height, significant period, and wave direction, the short-term ocean wave spectrum is stored in the wave database 130 as wave data.

FIG. 25 shows an example of a short-term ocean wave spectrum. Short-term ocean wave spectra are available from, for example, the Japan Weather Association. The short-term ocean wave spectrum is a two-dimensional (polar coordinate system) graph in the shape of a circle with regions bounded by rays from the center and concentric circles. The angles swung around the circumference indicate the ship's heading relative to the waves. The vertical axis passing through the center indicates the wave wavelength [m], and the horizontal axis indicates the period [s].

The short-term ocean wave spectrum shows the distribution of wave energy two-dimensionally. The denser the dot hatching, the higher the wave energy.

From this short-term ocean wave spectrum, it is possible to derive the wave response actually experienced by the ship. Specifically, at step S1500 in FIG. 24, the calculation unit 220 acquires the short-term oceanographic wave spectrum at the same position and time as the AIS data of the selected vessel at the predetermined time (S1500). Further, the wave energy within the short-term ocean wave spectrum in the course direction of the AIS data is determined, and the wave response is determined accordingly (S1600).

For example, in the simplified method shown in FIG. 2, based on the response function in irregular waves (FIG. 10) and Rayleigh distribution (FIG. 12), based on the worst sea state (1 big wave in 1000 times) during the short-term sea state period However, in this short-term ocean wave spectrum method, the sea surface is set based on the sea conditions actually encountered by the ship, and the time history response on the irregular sea surface and the wave response distribution based on this are obtained. can be done.

<Wave response estimation for ship maneuvering support>
In FIGS. 2 and 24, the wave response is hintcast based on the waves actually encountered by the ship, but the present invention is not limited to this form. For example, a short-term hydrographic forecast for the planned position based on the planned route of the ship may be obtained and used to aid ship maneuvering.

For example, in step S100 of FIG. 2, the calculation unit 220 specifies the planned position (latitude, longitude) ahead (for example, one hour later) from the current position as AIS data based on the route plan of the selected ship. Furthermore, in step S400, the calculation unit 220 obtains wave data one hour after the current time, and obtains time history data of waves expected to be encountered by the selected vessel.

Furthermore, the calculation unit 220 obtains a hull response based on the expected waves to be encountered in step S600 or step S1600 (FIG. 24). The calculation unit 220 determines whether or not the expected wave load based on this hull response falls within the allowable value (design load). If the planned wave load exceeds the allowable value, send a message to the selected vessel to avoid heavy weather.

<Wave response estimation using other vessel information>
In the above-described embodiment, AIS data is used as ship information, but in addition to this, ship information that is not included in AIS data may be used to obtain the wave response of the ship.

For example, if the group of ships to be evaluated includes ships equipped with strain gauges, etc., the stress associated with the wave load detected by the strain gauges and the estimated stress values obtained in Figures 2 and 24 An imputation value may be calculated based on the difference in , and applied to the stress estimate above. This improves the estimation accuracy of the wave response.

In addition, the stowage (loading) information of the ship and the engine output data may be taken into consideration when obtaining the ship maneuvering support and the soundness index of the hull in step S800 of FIGS. 2 and 24 . For example, when dangerous goods are included in the cargo, ship maneuvering support can be provided by suggesting a route with low wave response, prioritizing observance of the scheduled port entry date and reducing fuel consumption. In addition, by using the engine output data, it is possible to estimate the degree of fatigue of the engine, making it possible to set the selling price of the used ship more appropriately.

The present invention estimates the wave environment encountered by the ship, and based on this, it is possible to rationally set the design load of the ship and rationally set standards for safe operation support and maintenance.

100 storage device, 110 RAO database, 120 AIS database, 130 wave database, 140 wave response estimation database, 200 arithmetic device, 210 input unit, 220 arithmetic unit, 230 analysis unit, 300 display device.

Claims (14)

Ship information and wave data, which are information based on the AIS data of the ship including the position data of the ship, are acquired, data cleansing is performed to extract only the necessary data from the acquired AIS data, and the data is closest to the position data. Obtaining the encountering wave data of the ship by searching the wave data of the position, applying the encountering wave data to the previously obtained wave response function of the ship, and estimating the wave response of the ship, A ship wave response estimation method. 2. A wave response estimation method according to claim 1, wherein said encountered wave data and ship maneuvering conditions of said ship are made into a database based on said AIS data and said wave data. 3. A wave response estimation method according to claim 2, wherein an index relating to safe operation of said ship is obtained based on said encountered wave data of said ship stored in said database, said ship maneuvering situation, and said wave response. Obtaining ship information including position data of the ship and wave data, searching for the wave data at a position closest to the position data to obtain the encounter wave data of the ship, and obtaining the encounter wave data in advance of the ship. A method for estimating a wave response, comprising applying a wave response function to estimate a wave response of the ship, and obtaining a history of the wave response based on the ship information and the wave data. 5. A wave response estimation method according to claim 4, wherein the fatigue soundness of the ship is determined based on the history of the wave response. The wave response estimation method according to any one of claims 1 to 5, wherein the wave response is estimated for each of the plurality of ships. Obtaining ship information including position data of the ship and wave data, searching for the wave data at a position closest to the position data to obtain the encounter wave data of the ship, and obtaining the encounter wave data in advance of the ship. applied to a wave response function to estimate the wave response of the ship, estimate the wave response for each of the plurality of ships, and statistically process the estimated wave response for each of the ships; A wave response estimation method, characterized in that the design load is set by The wave response estimation method according to any one of claims 1 to 7, wherein the accuracy of estimating the wave response is improved using operational information and/or design information of the ship. The wave response estimation method according to any one of claims 1 to 8, wherein the wave response function is obtained as a response function in irregular waves corresponding to the ship type and length of the ship. to the computer,
a data input step of inputting ship information and wave data, which is information based on the AIS data of the ship including the acquired position data of the ship;
a data cleansing step of extracting only necessary data from the acquired AIS data;
an encountered wave data obtaining step of searching for the wave data at a position closest to the input position data to obtain the encountered wave data of the ship;
a wave response function applying step of applying the encountered wave data to a wave response function of the ship obtained in advance;
and a wave response estimation step of estimating the wave response of the vessel based on the wave response function. to the computer,
a data input step of inputting ship information including acquired ship position data and wave data;
an encountered wave data obtaining step of searching for the wave data at a position closest to the input position data to obtain the encountered wave data of the ship;
a wave response function applying step of applying the encountered wave data to a wave response function of the ship obtained in advance;
executing a wave response estimation step of estimating a wave response of the ship based on the wave response function;
A wave response history recording step of obtaining the encountered wave data of the ship at each time in the encountered wave data acquisition step, and storing the wave response estimated at each time at the wave response estimation step as a history at each time. A wave response estimation program characterized by further executing. 12. The wave according to claim 11 , further comprising a ship fatigue soundness evaluation step of determining the fatigue soundness of the ship based on the history of the wave response recorded in the wave response history recording step. Response estimation program. from claim 10, further comprising a vessel designation step of designating an individual said vessel from among a plurality of said vessels and selecting said vessel information of said designated vessel from among said vessel information; A wave response estimation program according to any one of claims 12 to 14. Claim 11, Claim 12, and further comprising a statistical evaluation step of performing statistical evaluation based on the wave response as the history recorded in the wave response history recording step. 14. A wave response estimation program according to any one of claims 13 citing claim 11.

Images