Prediction method for surge dynamics of ship rolling system

Abstract

The invention provides a ship rolling system surge dynamics prediction method, and relates to the field of dynamics analysis, and the method comprises the steps: building a nonlinear dynamics model of a ship rolling system; solving the critical state of the nonlinear kinetic model by adopting an continuation targeting method to obtain an analysis result; according to the nonlinear dynamic model and the analysis result, a numerical simulation technology is combined and adopted to obtain a behavior simulation result; carrying out numerical simulation on the optimized nonlinear dynamic model by adopting a GPU parallel computing method to obtain a numerical result; and based on a numerical result and a behavior simulation result, predicting a sudden change dynamic behavior of the ship rolling system, and identifying a potential catastrophic instability phenomenon of the system. According to the technical scheme, the method has high calculation efficiency and accuracy, can be widely applied to the fields of ship rolling instability risk prediction, ship design optimization and the like, and has important engineering application value.

Description

Technical Field

[0001] The present application relates to the field of dynamics analysis, and in particular to a method for predicting the drastic dynamics of a ship's rolling system. Background Art

[0002] The rolling motion of a ship refers to the periodic motion of a ship around its longitudinal axis under the action of transverse waves. Due to the nonlinear nature and complexity of waves in the marine environment, the rolling motion of a ship under transverse waves often exhibits strong nonlinear characteristics. The amplitude and frequency of the roll are affected by multiple factors such as the intensity of the waves, the geometric parameters of the hull, and the damping effect. Especially in extreme sea conditions, wave excitation may cause the ship's rolling motion to enter an unstable state, or even trigger a drastic change phenomenon, which is manifested as the system changing from a stable periodic motion to an unstable state, resulting in violent oscillations or capsizing. In severe cases, it may cause damage to or sinking of the ship, endangering the safety of the ship. Therefore, accurately predicting the drastic behavior of the ship's roll system is of great significance to ensure the safe navigation of the ship.

[0003] Traditional ship rolling research mainly relies on numerical simulation and theoretical analysis. By establishing a mathematical model, the stability and oscillation behavior of the system are analyzed by combining wave excitation with the dynamic characteristics of the hull. However, the nonlinear characteristics of the ship rolling system make these methods inefficient and inaccurate. Existing numerical methods usually analyze dynamic responses by simplifying assumptions, but they show great limitations under complex wave conditions or nonlinear characteristics of the hull. Especially when the system parameters are close to the critical point, the occurrence of sudden changes often belongs to bifurcation phenomena. Traditional methods are inefficient in large-scale parameter scanning and critical point determination, and it is difficult to make accurate predictions within a reasonable time. Although some studies have begun to apply nonlinear dynamics and complex system theory to study ship rolling, the sudden change prediction method has not been widely used in practice, especially in the prediction of ship rolling sudden changes. Therefore, there is an urgent need for a new method that can efficiently and accurately predict the sudden change behavior of the ship rolling system, help engineers and designers identify potential instability risks in advance, and ensure the safe operation of ships in complex sea conditions. This patent is proposed to address the deficiencies in the existing technology and provides a new prediction method. By combining the extended target shooting method and GPU parallel computing, it can efficiently and accurately predict the drastic behavior of the ship's roll system, providing a theoretical basis for ship design and operation. Summary of the invention

[0004] The purpose of the present invention is to provide a method for predicting the catastrophic instability of a ship's rolling system in order to solve the technical problem that the nonlinear dynamic model of ship rolling in the prior art is insufficient in predicting catastrophic instability.

[0005] The above-mentioned purpose of the present application is achieved through the following technical solutions: S1: Establish a nonlinear dynamic model of the ship's rolling system; S2: Use the extended shooting method to solve the critical state of the nonlinear dynamic model and obtain the analysis results; S3: Based on the nonlinear dynamics model and analysis results, the behavior simulation results are obtained by combining numerical simulation technology; S4: Use GPU parallel computing method to perform numerical simulation on the optimized nonlinear dynamic model and obtain numerical results; S5: Based on the numerical results and behavioral simulation results, predict the drastic dynamic behavior of the ship's roll system and identify the potential catastrophic instability of the system.

[0006] Optionally, step S1 includes: Based on the restoring moment, damping moment and wave excitation moment, the nonlinear dynamic model of the ship rolling system is constructed as follows:

[0007] in, is the total moment of inertia, is the moment of inertia related to the ship's mass, is the disturbance term of the moment of inertia, which indicates the change of the moment of inertia caused by the structural change or load change during the actual operation of the ship; Indicates the acceleration of the ship's roll; is the restoring torque, represents the roll angle; is the damping torque, is the rolling angular velocity; is the wave excitation torque, represents the amplitude of the wave excitation, Indicates the frequency of the wave.

[0008] Optionally, step S1 further includes: ; in and are the cubic and quintic nonlinear restoring moment coefficients; Indicates the change in the ship's center of buoyancy height.

[0009] Optionally, step S1 further includes:

[0010] in is the linear damping coefficient is the nonlinear cubic damping coefficient.

[0011] Optionally, step S1 further includes: Substituting the expressions for the restoring and damping moments into the general equation of motion, and dividing by After normalization, we get the nonlinear differential equation describing the ship under the action of shear waves:

[0012] in, represents the natural rolling frequency of the ship, and is the nonlinear restoring moment coefficient; is the linear damping coefficient, is the cubic damping coefficient; It is the wave excitation force; Transform the nonlinear differential equation into the following state equation:

[0013] in, represents the rolling angular velocity; Indicates the roll acceleration.

[0014] Optionally, step S2 includes: Through the extended shooting method, the search for periodic solutions of nonlinear dynamic models is transformed into the problem of solving the fixed point problem of the following Poincaré mapping, as follows:

[0015] in is the state variable; is the parameter vector; is the residual function of the Poincaré map, which is used to measure the difference between the current state of the system and the periodic solution; is the Poincaré map corresponding to the period; The fixed point problem is solved by the Newton-Raphson iterative method as follows:

[0016] in For the The state variable vector at the iteration; is the Jacobi matrix of the Poincaré mapping; is the identity matrix; For the current state Poincaré map under ; The calculation of satisfies the following initial value problem:

[0017]

[0018] in, is the dynamic equation of the system; is the time variable; is the state sensitivity vector, which indicates the direction and magnitude of the system state change; is the sensitivity vector of the initial state; Through iterative calculation, the state variables are continuously adjusted in the iterative process , so that the residual gradually decreases, and the fixed point and periodic solution are obtained. The periodic solution is the critical point of the cataclysmic change; Through the periodic solution, the distribution of Floquet multipliers is analyzed to determine the instability of the ship's roll system. When the Floquet multiplier passes through the unit circle, the ship's roll system undergoes bifurcation or drastic changes, and the bifurcation point is obtained. The analysis result is the solved critical point of drastic changes and the bifurcation point of the bifurcation phenomenon.

[0019] Optionally, step S3 includes: S31: Conducting a multi-condition experiment on the target ship or model ship to obtain measured data; the measured data includes: time domain response data of the ship's roll angle, angular velocity, angular acceleration, and wave excitation torque; S32: According to the analysis results, the numerical simulation technology is used to simulate the ship rolling system under different working conditions to obtain simulation results; the simulation results include: free decay curve, static restoring moment experimental data; S33: Compare the measured data with the simulation results to optimize the damping coefficient, stiffness coefficient and excitation torque of the nonlinear dynamic model; S34: Through the optimized nonlinear dynamic model, dynamic behavior simulation under different parameter combinations is performed to obtain behavior simulation results.

[0020] Optionally, step S4 includes: Divide the state space into small regions, each of which contains a preset number of initial conditions, as follows:

[0021] in Indicates in the region initial conditions; The state space represents the set of all possible states of the ship rolling system, and the initial condition represents the initial state selected in each small area, such as the rolling angle and the rolling angular velocity Different initial values ​​of ; All initial conditions for a small area are processed by one GPU core, including: On each GPU core, each initial condition is integrated by numerical integration and the state equation of the system is solved using the Runge-Kutta method:

[0022] in, is the time step, For time The state of the moment, is the state equation; Through the integral calculation of the preset time, the state equation of the ship's rolling system will tend to a steady-state solution, which is the attractor; By calculating the Lyapunov index of the ship's rolling system or judging whether the ship's rolling system converges to a periodic solution, stability analysis is performed to obtain the attractor type and attraction domain range of each small area; According to the attractor type and the range of the attraction domain, it is determined whether the sub-region belongs to the stable region, the drastic change region or the transition region, and the numerical result is obtained.

[0023] An electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a method for predicting the turbulent dynamics of a ship rolling system.

[0024] A computer-readable storage medium stores instructions. When the instructions are executed, a method for predicting the turbulent dynamics of a ship rolling system is executed.

[0025] The beneficial effects of the technical solution provided by this application are: The present invention combines nonlinear dynamic modeling with numerical calculation technology, and can accurately capture the complex dynamic behavior of the ship's roll system, especially in the prediction of catastrophic instability phenomena. By adopting the extended shooting method, the present invention can effectively track the periodic solutions and bifurcation points of the system, thereby providing an efficient tool for the bifurcation analysis of the system. In addition, by using GPU parallel computing technology, the present invention significantly improves the computational efficiency of the attraction domain analysis and meets the demand for efficient computing in practical applications. This prediction method can not only provide theoretical support for the design of ships, but also provide a scientific basis for navigation safety, and has important engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present application will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 is a method flow chart of an embodiment of the present invention; Figure 2 is a schematic diagram of ship rolling in an embodiment of the present invention; Figure 3 is a bifurcation diagram of a ship rolling system in an embodiment of the present invention; Figure 4 is the attraction domain of the ship rolling system in the embodiment of the present invention; Figure 5 is an attractor phase diagram of the ship rolling system before the sudden change point in an embodiment of the present invention; Figure 6 is an attractor phase diagram of the ship rolling system after the sudden change point in an embodiment of the present invention; Figure 7 is a Lyapunov index diagram of the ship rolling system before and after the sudden change point in an embodiment of the present invention; Figure 8 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to have a clearer understanding of the technical features, purposes and effects of the present application, the specific implementation methods of the present application are now described in detail with reference to the accompanying drawings.

[0028] An embodiment of the present application provides a method for predicting the drastic dynamics of a ship's rolling system.

[0029] Please refer to Figure 1 , Figure 1 1 is a step diagram of a method for predicting the drastic dynamics of a ship rolling system in an embodiment of the present application, comprising: S1: Establish a nonlinear dynamic model of the ship's rolling system; S2: Use the extended shooting method to solve the critical state of the nonlinear dynamic model and obtain the analysis results; As an embodiment, the nonlinear dynamic model is calculated by using the extended shooting method, wherein the critical state of the system is gradually approached by initial value setting and parameter scanning, and the critical point and bifurcation phenomenon of the sudden change are determined according to the change of the system response; S3: Based on the nonlinear dynamics model and analysis results, the behavior simulation results are obtained by combining numerical simulation technology; S4: Use GPU parallel computing method to perform numerical simulation on the optimized nonlinear dynamic model and obtain numerical results; S5: Based on the numerical results and behavioral simulation results, predict the drastic dynamic behavior of the ship's roll system and identify the potential catastrophic instability of the system.

[0030] This application adopts the above-mentioned technical solution, constructs a nonlinear dynamic model, and analyzes the periodic solution and bifurcation behavior of the ship's roll system in combination with the extended shooting method, and uses GPU parallel computing to improve the calculation efficiency, and quickly identifies the system's critical point and stability boundary. The model parameters are verified by numerical simulation, and the ship's roll motion is analyzed in an all-round way in combination with experimental data. Finally, combined with the evolution of the attraction domain and the Lyapunov exponent analysis, the present invention can effectively predict the drastic behavior of the ship's roll system in a complex wave environment, and provide a theoretical basis for ship design and navigation safety. This method has high computational efficiency and accuracy, and can be widely used in the fields of ship roll instability risk prediction, ship design optimization, etc., and has important engineering application value.

[0031] The present application adopts the above-mentioned technical solution in order to cope with the sudden changes and instability that may occur in the ship's roll system under complex wave conditions. At present, the traditional ship roll prediction method has low computational efficiency and cannot accurately predict the sudden change behavior when approaching the critical state, especially in ship design and navigation safety. There is a large technical gap. By combining the extended shooting method and GPU parallel computing, the present invention can efficiently and accurately identify the critical point of the system's sudden change, breaking through the limitations of traditional methods in large-scale parameter scanning and nonlinear system analysis. This new prediction method has significant innovation in improving computational efficiency and optimizing prediction accuracy, and can provide a scientific basis for ship design, navigation safety and marine engineering, and has important theoretical research value and practical application prospects. At the same time, the present invention fills the technical gap in this field, the technical solution is complete and the protection scope is clear, and it has significant authorization possibility and engineering application value.

[0032] Step S1 includes: Based on the restoring moment, damping moment and wave excitation moment, the nonlinear dynamic model of the ship rolling system is constructed as follows:

[0033] in, is the total moment of inertia, is the moment of inertia related to the ship's mass, is the disturbance term of the moment of inertia, which indicates the change of the moment of inertia caused by the structural change or load change during the actual operation of the ship; Indicates the acceleration of the ship's roll; is the restoring torque, represents the roll angle; is the damping torque, is the rolling angular velocity; is the wave excitation torque, represents the amplitude of the wave excitation, Indicates the frequency of the wave.

[0034] Step S1 also includes: ; in and are the cubic and quintic nonlinear restoring moment coefficients; Indicates the change in the ship's center of buoyancy height.

[0035] As an example, for a small roll angle , so that the restoring moment is linear. However, as the roll angle increases, the relationship between the restoring moment and the roll angle becomes nonlinear. To take this into account, the restoring moment is usually expressed as a polynomial function of the roll angle, including both linear and nonlinear terms: and are the third and fifth order nonlinear restoring moment coefficients, which are usually determined by fitting the static stability curve of the ship.

[0036] Step S1 also includes:

[0037] in is the linear damping coefficient is the nonlinear cubic damping coefficient; As an example, the linear plus cubic damping model can more accurately reflect the damping effect of the ship's side than other models because it can capture the nonlinear damping behavior without the need for absolute value terms.

[0038] Step S1 also includes: Substituting the expressions for the restoring and damping moments into the general equation of motion, and dividing by After normalization, we get the nonlinear differential equation describing the ship under the action of shear waves:

[0039] in, represents the natural rolling frequency of the ship, and is the nonlinear restoring moment coefficient; is the linear damping coefficient, is the cubic damping coefficient; It is the wave excitation force; Transform the nonlinear differential equation into the following state equation:

[0040] in, represents the rolling angular velocity; Indicates the roll acceleration.

[0041] Step S2 includes: Through the extended shooting method, the search for periodic solutions of nonlinear dynamic models is transformed into the problem of solving the fixed point problem of the following Poincaré mapping, as follows:

[0042] in is the state variable; is the parameter vector; is the residual function of the Poincaré map, which is used to measure the difference between the current state of the system and the periodic solution; is the Poincaré map corresponding to the period; The fixed point problem is solved by the Newton-Raphson iterative method as follows:

[0043] in For the The state variable vector at the iteration; is the Jacobi matrix of the Poincaré mapping; is the identity matrix; For the current state Poincaré map under ; The calculation of satisfies the following initial value problem:

[0044]

[0045] in, is the dynamic equation of the system; is the time variable; is the state sensitivity vector, which indicates the direction and magnitude of the system state change; is the sensitivity vector of the initial state; Through iterative calculation, the state variables are continuously adjusted in the iterative process , so that the residual gradually decreases, and the fixed point and periodic solution are obtained. The periodic solution is the critical point of the cataclysmic change; As an embodiment, the iterative process continuously adjusts the state variables so that the residual gradually decreases and eventually a fixed point is found.

[0046] Through the periodic solution, the distribution of Floquet multipliers is analyzed to determine the instability of the ship's roll system. When the Floquet multiplier passes through the unit circle, the ship's roll system undergoes bifurcation or drastic changes, and the bifurcation point is obtained. The analysis result is the solved critical point of drastic changes and the bifurcation point of the bifurcation phenomenon.

[0047] As an example, in this process, the stability of the system is determined by analyzing the distribution of Floquet multipliers. When the Floquet multipliers cross the unit circle, the system undergoes bifurcation or catastrophic changes. The bifurcation diagram of the change is Figure 3 As shown. The point is a fork bifurcation point. Dot and The point is a saddle-node bifurcation point, and the system is accompanied by the appearance of delayed bifurcation, and its jump point is and . Hysteresis loop It consists of a stable red period 1 attractor, a period doubling sequence of a stable black period 1 attractor, and an unstable sky blue period 1 attractor.

[0048] As an embodiment, the target shooting method selects a series of discrete points in the state space and constructs a target function of multiple calculations to approximate the critical point of the roll system, and optimizes the initial conditions and parameter settings through sensitivity analysis of the bifurcation points of the system and its related parameters.

[0049] Step S3 includes: S31: Conducting a multi-condition experiment on the target ship or model ship to obtain measured data; the measured data includes: time domain response data of the ship's roll angle, angular velocity, angular acceleration, and wave excitation torque; As an example, based on the nonlinear dynamic model, numerical simulation technology is used to fully verify and optimize the dynamic behavior of the ship's roll system under different working conditions. First, the measured data is obtained, and multi-condition experiments are carried out on the target ship or model ship to collect the time domain response data of the ship's roll angle, angular velocity, angular acceleration, and wave excitation torque. Ensure that the measured data covers the transition area from stable state to drastic change to provide a complete verification range.

[0050] S32: According to the analysis results, the numerical simulation technology is used to simulate the ship rolling system under different working conditions to obtain simulation results; the simulation results include: free decay curve, static restoring moment experimental data; S33: Compare the measured data with the simulation results to optimize the damping coefficient, stiffness coefficient and excitation torque of the nonlinear dynamic model; As an embodiment, the relevant parameters are optimized, the measured data are compared with the simulation results, and the following parameters are adjusted: the damping coefficient, the damping component is fitted by the free decay curve obtained by the simulation experiment; the stiffness coefficient, the polynomial form is fitted by the static restoring moment experimental data; the excitation torque, the excitation frequency and amplitude are determined by experimental data.

[0051] S34: Through the optimized nonlinear dynamic model, dynamic behavior simulation under different parameter combinations is performed to obtain behavior simulation results.

[0052] As an example, different parameter combinations include: nonlinear restoring moment coefficient and , damping moment coefficient and .

[0053] As an embodiment, based on the optimized model, dynamic behavior simulations under different parameter combinations are further performed, with special attention paid to the following key characteristics: 1. The amplitude and frequency of the periodic solution to ensure that the optimized model can accurately reflect the periodic behavior of the system in a stable state; 2. The emergence of chaotic orbits and their characteristics, such as the matching of Lyapunov exponents and bifurcation diagrams. In addition, combined with the bifurcation phenomenon observed in the experiment, the model's ability to predict period doubling bifurcations, saddle-node bifurcations, and chaotic attractor transitions is verified. By drawing phase diagrams and comparing them one by one with the measured data, the effectiveness and accuracy of the model and algorithm are further verified.

[0054] As an embodiment, by introducing changes in physical quantities such as external wave excitation and ship structure stiffness, the complex nonlinear characteristics of the ship rolling system are further considered to improve the prediction accuracy.

[0055] As an example, the measured data of the ship, including roll angle, angular velocity and wave excitation, are used to simulate different working conditions to verify the model's ability to predict different types of bifurcation phenomena and the effectiveness of the extended shooting method in identifying the inflection point. Pay attention to the amplitude and frequency of the periodic solution to ensure that the model can accurately reflect the rolling behavior of the ship under normal working conditions. It is also necessary to pay attention to whether there is a chaotic orbit in the system, especially when the system is close to the inflection point, and analyze the behavior of the system through methods such as phase diagrams and Lyapunov exponents.

[0056] Step S4 includes: As an example, through GPU parallelization, the integration of a large number of initial conditions can be completed in a short time, and the attractor type and attraction domain boundary of each region can be quickly obtained, so as to predict the conditions and possibility of the occurrence of catastrophic behavior. In GPU parallel computing, each small area of ​​the state space can be regarded as an independent task, and each task is assigned to a different GPU core.

[0057] Divide the state space into small regions, each of which contains a preset number of initial conditions, as follows:

[0058] in Indicates in the region initial conditions; The state space represents the set of all possible states of the ship rolling system, and the initial condition represents the initial state selected in each small area, such as the rolling angle and the rolling angular velocity Different initial values ​​of ; All initial conditions for a small area are processed by one GPU core, including: On each GPU core, each initial condition is integrated by numerical integration and the state equation of the system is solved using the Runge-Kutta method:

[0059] in, is the time step, For time The state of the moment, is the state equation; Through the integral calculation of the preset time, the state equation of the ship's rolling system will tend to a steady-state solution, which is the attractor; In one embodiment of the present application, if the system state converges to a specific periodic solution or chaotic attractor within a sufficiently long time, the initial condition is considered to belong to the attractor.

[0060] By calculating the Lyapunov index of the ship's rolling system or judging whether the ship's rolling system converges to a periodic solution, stability analysis is performed to obtain the attractor type and attraction domain range of each small area; According to the attractor type and the range of the attraction domain, it is determined whether the sub-region belongs to the stable region, the drastic change region or the transition region, and the numerical result is obtained.

[0061] As an embodiment, stability determination is usually achieved by calculating the Lyapunov exponent or determining whether the system converges to a periodic solution. The attractor type of each small area is determined by long-term integration and stability analysis. Each GPU core outputs the attractor type of the area and its corresponding attraction domain range. Figure 4 It is the attraction domain corresponding to the coexistence of two periodic three-attractors and one periodic one-attractor. According to different attractor types, it can be further determined whether the area belongs to the stable zone, the drastic change zone or the transition zone.

[0062] As an example, the prediction of catastrophic behavior identifies the critical parameter range of the system by performing evolution analysis on the attraction domain, and further confirms possible catastrophic regions using bifurcation diagram and phase diagram analysis.

[0063] As an embodiment, by integrating numerical results and behavioral simulation results, the present invention can accurately predict the drastic behavior of a ship's roll system in a complex wave environment and identify the stability boundary of the system. Figure 5 and Figure 6 is the phase diagram before and after the cataclysm, Figure 7 By analyzing the Lyapunov exponent diagrams before and after the sudden change, it is observed that when the ship rolling system approaches the sudden change point, the attractor of the system changes from a stable periodic solution to a chaotic attractor. Therefore, combined with meteorological and oceanographic data, the ship rolling model and sudden change dynamics can be used to predict the arrival of severe sea conditions in advance, plan safe routes, avoid possible sudden changes and instability areas, and ensure the safety of ship navigation.

[0064] As an embodiment, by comparing the changes in the system attraction domain at different times and working conditions, the critical moment of the system is determined, and a theoretical basis is provided for ship roll control and potential instability.

[0065] The present application also discloses an electronic device. Figure 8 , Figure 8 The electronic device 500 may include: at least one processor 501 , at least one network interface 504 , a user interface 503 , a memory 505 , and at least one communication bus 502 .

[0066] The communication bus 502 is used to realize the connection and communication between these components.

[0067] The user interface 503 may include a display screen, and the optional user interface 503 may also include a standard wired interface or a wireless interface.

[0068] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0069] The present application also discloses a computer-readable storage medium storing a plurality of instructions, wherein the instructions are suitable for a processor to load to execute the above-mentioned method for predicting the drastic dynamics of a ship rolling system.

[0070] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure.

[0071] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for predicting the turbulent dynamics of a ship rolling system, characterized in that: The method comprises the following steps: S1: Establish a nonlinear dynamic model of the ship's rolling system; S2: Use the extended shooting method to solve the critical state of the nonlinear dynamic model and obtain the analysis results; S3: Based on the nonlinear dynamics model and analysis results, the behavior simulation results are obtained by combining numerical simulation technology; S4: Use GPU parallel computing method to perform numerical simulation on the optimized nonlinear dynamic model and obtain numerical results; S5: Based on the numerical results and behavioral simulation results, predict the drastic dynamic behavior of the ship's roll system and identify the potential catastrophic instability of the system.

2. A method for predicting the turbulent dynamics of a ship rolling system according to claim 1, characterized in that: Step S1 includes: Based on the restoring moment, damping moment and wave excitation moment, the nonlinear dynamic model of the ship rolling system is constructed as follows: in, is the total moment of inertia, is the moment of inertia related to the ship's mass, is the disturbance term of the moment of inertia, which indicates the change of the moment of inertia caused by the structural change or load change during the actual operation of the ship; Indicates the acceleration of the ship's roll; is the restoring torque, represents the roll angle; is the damping torque, is the rolling angular velocity; is the wave excitation torque, represents the amplitude of the wave excitation, Indicates the frequency of the wave.

3. A method for predicting the turbulent dynamics of a ship rolling system according to claim 2, characterized in that: Step S1 also includes: ； in and are the cubic and quintic nonlinear restoring moment coefficients; Indicates the change in the ship's center of buoyancy height.

4. A method for predicting the turbulent dynamics of a ship rolling system according to claim 3, characterized in that: Step S1 also includes: in is the linear damping coefficient is the nonlinear cubic damping coefficient.

5. A method for predicting the turbulent dynamics of a ship rolling system according to claim 4, characterized in that: Step S1 also includes: Substituting the expressions for the restoring and damping moments into the general equation of motion, and dividing by After normalization, we get the nonlinear differential equation describing the ship under the action of shear waves: in, represents the natural rolling frequency of the ship, and is the nonlinear restoring moment coefficient; is the linear damping coefficient, is the cubic damping coefficient; It is the wave excitation force; Transform the nonlinear differential equation into the following state equation: in, represents the rolling angular velocity; Indicates the roll acceleration.

6. A method for predicting the turbulent dynamics of a ship rolling system according to claim 5, characterized in that: Step S2 includes: Through the extended shooting method, the search for periodic solutions of nonlinear dynamic models is transformed into the problem of solving the fixed point problem of the following Poincaré mapping, as follows: in is the state variable; is the parameter vector; is the residual function of the Poincaré map, which is used to measure the difference between the current state of the system and the periodic solution; is the Poincaré map corresponding to the period; The fixed point problem is solved by the Newton-Raphson iterative method as follows: in For the The state variable vector at the iteration; is the Jacobi matrix of the Poincaré mapping; is the identity matrix; For the current state Poincaré map under ; The calculation of satisfies the following initial value problem: in, is the dynamic equation of the system; is the time variable; is the state sensitivity vector, which indicates the direction and magnitude of the system state change; is the sensitivity vector of the initial state; Through iterative calculation, the state variables are continuously adjusted in the iterative process , so that the residual gradually decreases, and the fixed point and periodic solution are obtained. The periodic solution is the critical point of the cataclysmic change; Through the periodic solution, the distribution of Floquet multipliers is analyzed to determine the instability of the ship's roll system. When the Floquet multiplier passes through the unit circle, the ship's roll system undergoes bifurcation or drastic changes, and the bifurcation point is obtained. The analysis result is the solved critical point of drastic changes and the bifurcation point of the bifurcation phenomenon.

7. A method for predicting the turbulent dynamics of a ship rolling system according to claim 1, characterized in that: Step S3 includes: S31: Conducting a multi-condition experiment on the target ship or model ship to obtain measured data; the measured data includes: time domain response data of the ship's roll angle, angular velocity, angular acceleration, and wave excitation torque; S32: According to the analysis results, the numerical simulation technology is used to simulate the ship rolling system under different working conditions to obtain simulation results; the simulation results include: free decay curve, static restoring moment experimental data; S33: Compare the measured data with the simulation results to optimize the damping coefficient, stiffness coefficient and excitation torque of the nonlinear dynamic model; S34: Through the optimized nonlinear dynamic model, dynamic behavior simulation under different parameter combinations is performed to obtain behavior simulation results.

8. The method for predicting the catastrophic dynamics of a ship rolling system according to claim 1, characterized in that: Step S4 includes: Divide the state space into small regions, each of which contains a preset number of initial conditions, as follows: in Indicates in the region initial conditions; The state space represents the set of all possible states of the ship rolling system, and the initial condition represents the initial state selected in each small area, such as the rolling angle and the rolling angular velocity Different initial values ​​of ; All initial conditions for a small area are processed by one GPU core, including: On each GPU core, each initial condition is integrated by numerical integration and the state equation of the system is solved using the Runge-Kutta method: in, is the time step, For time The state of the moment, is the state equation; Through the integral calculation of the preset time, the state equation of the ship's rolling system will tend to a steady-state solution, which is the attractor; By calculating the Lyapunov index of the ship's rolling system or judging whether the ship's rolling system converges to a periodic solution, stability analysis is performed to obtain the attractor type and attraction domain range of each small area; According to the attractor type and the range of the attraction domain, it is determined whether the sub-region belongs to the stable region, the drastic change region or the transition region, and the numerical result is obtained.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by a computer, the method according to any one of claims 1 to 8 is executed.

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