A Digital Twin-Based Method for Ocean Current Forecasting and Visualization

Abstract

This invention relates to the field of virtual simulation and fluid modeling technology, specifically to a digital twin-based method for ocean current forecasting and visualization, comprising the following steps: S1, setting boundary water levels and terrain elevations to calculate an initial velocity field, and generating a projected velocity field that satisfies the incompressibility condition through projection correction; S2, combining the difference between the projected field and the initial field, terrain gradient, and boundary change rate to generate a perturbation map, marking potential visual discontinuities; S3, constructing a terrain-sensitive perturbation factor to modulate the velocity input, driving the wave and particle systems, and achieving a smooth transition and consistent evolution between the physical field and the visual rendering system. This invention, by constructing a perturbation-modulated physically consistent velocity field and driving the co-evolution of the wave and particle systems, achieves a highly consistent fusion effect between the physical accuracy and visual representation of ocean current simulation under complex terrain.

Description

Technical Field

[0001] This invention relates to the field of virtual simulation and fluid modeling technology, and in particular to a method for ocean current forecasting and visualization based on digital twins. Background Technology

[0002] With the development of virtual reality, 3D visualization and smart ocean, digital twin technology for marine scenarios has made great progress. Relying on Gerstner wave algorithm and Niagara particle system, it is now possible to realize dynamic water surface and fluid particle representation. However, in areas with drastic terrain changes or complex boundaries, there are still some inconsistencies between physical calculation and visual rendering, which may affect the immersive experience and visual credibility.

[0003] Current mainstream ocean current forecasting and real-time visualization methods mostly rely on velocity field calculations based on shallow water equations to directly drive the visual system. However, after incompressible correction or boundary reconstruction, the physical velocity field may deviate from the initial velocity field in local direction or amplitude, causing problems such as abrupt changes in wave direction and discontinuous particle motion in visual perception. In addition, existing methods rarely consider the impact of terrain sensitivity factors on the smoothness of visual transitions, resulting in ocean current simulations that, although physically correct, do not appear natural or realistic in the 3D virtual scene. This not only reduces the credibility of ocean current forecasting visualization results but also affects the overall interpretability and application scalability of the system. Summary of the Invention

[0004] This invention provides a digital twin-based ocean current forecasting and visualization method. By constructing a projected velocity field that satisfies the incompressibility condition, introducing velocity difference analysis and perturbation mapping mechanisms, and further constructing a terrain-sensitive perturbation factor, the method performs consistent modulation on the Gerstner wave generation unit and the Niagara particle system. This achieves a high consistency mapping between the physical velocity field and the visual system while maintaining fluid continuity, effectively alleviating problems such as abrupt texture changes and abnormal particle distribution, and improving rendering accuracy and visual experience quality.

[0005] A digital twin-based method for ocean current forecasting and visualization includes the following steps:

[0006] S1 calculates the initial velocity field by setting the boundary water level and topographic elevation data of the simulation domain, and performs a projection correction operation on the initial velocity field to generate a projected velocity field that satisfies the fluid continuity constraint.

[0007] S2, perform difference analysis between the projected velocity field and the initial velocity field, and combine the terrain gradient, depth abrupt change region and boundary velocity change rate to generate a disturbance mapping map to describe the visual difference region of the flow field, so as to characterize the potential visual discontinuity region caused by incompressible correction.

[0008] S3, while maintaining the continuity of the projected velocity field, a set of terrain-sensitive perturbation factors are constructed to reversibly perturb and modulate the velocity input in the wave generation unit and the Niagara particle system, so as to achieve a smooth transition and consistent evolution of the flow direction and particle behavior at the visual level, and complete a highly consistent mapping from the physical velocity field to the visual rendering system.

[0009] S4, performs high-resolution visualization output on the perturbation-modulated velocity input, and supports dynamic configuration of boundary conditions such as water level and tides, realizing real-time calculation, continuous evolution simulation and visualization prediction of regional ocean current field.

[0010] Optionally, S1 includes:

[0011] S11. Obtain and set the boundary water level and topographic elevation data of the simulation domain. The boundary water level time series data is used to describe the dynamic changes of the external tide level over time. The topographic elevation data is imported from the real topographic data into the virtual engine to form a bottom structure with spatial undulations. Based on the boundary water level time series data and topographic elevation data, the free water surface slope is constructed by analyzing the shallow water continuity equation and momentum equation, and the initial velocity field driving the fluid motion is calculated to reflect the physical velocity distribution state without continuity correction.

[0012] S12, based on the initial velocity field and considering the incompressibility requirement in fluid dynamics, performs a projection correction operation on the initial velocity field to generate a continuous projected velocity field.

[0013] Optionally, S11 includes:

[0014] S111, importing boundary water levels from measured or simulated platforms. Topographic elevation data of the simulated area The data is then input into the autonomous ocean current calculation method (or plugin) developed for the water system of the digital twin platform via a data interface;

[0015] S112, based on boundary water level With topographic elevation data Generate free water surface height distribution Its spatial variation forms the water surface slope field. ;

[0016] S113, water surface slope field Substituting the pressure gradient source term into the shallow water momentum equation and continuity equation, the initial velocity field without continuity correction is calculated. .

[0017] Optionally, S12 includes:

[0018] S121, for the initial velocity field Perform divergence calculations to determine whether mass conservation is satisfied. If it is not zero, it needs to be corrected, as shown below:

[0019] ;

[0020] S122, Construct the scalar potential function for correcting the velocity field. Its distribution can be solved using the Poisson equation;

[0021] S123, based on the solved scalar potential function The initial velocity field is corrected to obtain the projected velocity field that satisfies the incompressibility condition. .

[0022] Optionally, S2 includes:

[0023] S21, perform difference calculation on the same spatial grid to construct the velocity difference field between the initial velocity field and the corrected projected velocity field;

[0024] S22, based on the velocity difference field, introduces spatial features related to visual disturbances, including terrain gradient, depth abrupt change region and boundary flow velocity change rate, constructs a disturbance weight field, and superimposes it with the velocity difference field to generate the final disturbance mapping map.

[0025] Optionally, S21 includes:

[0026] S211, the initial velocity field With the corrected projected velocity field Align on the same two-dimensional spatial grid to ensure that they are at the same time step. ;

[0027] S212, at each grid point At this point, calculate the vector difference between the initial flow velocity and the corrected flow velocity, and construct the velocity difference field. ;

[0028] S213, calculate the magnitude of the velocity difference field, and generate the velocity difference magnitude field. It is used to reflect the intensity of local velocity disturbance.

[0029] Optionally, S22 includes:

[0030] S221, Calculate terrain elevation data With water depth distribution Spatial gradient, including topographic gradient field and the gradient field of water depth abrupt change The topographic gradient field is used to measure the drasticness of topographic changes, and the water depth abrupt change gradient field is used to assess the degree of abrupt changes in water depth in space. This is achieved by analyzing the topographic gradient field... With the gradient field of water depth abrupt change Weighted fusion is performed to generate a perturbation terrain weight field. ;

[0031] S222, near the boundary of the simulation domain, calculate the rate of change of the corrected projected velocity field along the boundary normal direction, defined as the boundary velocity change rate. It is used to measure the intensity of disturbances caused by changes in boundary conditions and to construct the boundary disturbance weight field. ;

[0032] S223 will perturb the terrain weight field Boundary perturbation weight field The velocity difference magnitude field, combined with the velocity difference field, forms a disturbance mapping diagram. .

[0033] Optionally, S3 includes:

[0034] S31, while ensuring the continuity of the projected velocity field, the generated perturbation map is used to construct a spatially distributed terrain-sensitive perturbation factor for local perturbation modulation of the projected velocity field.

[0035] S32 takes the perturbation-modulated projected velocity field as input and passes it to the wave generation unit based on Gerstner waves and the Niagara particle system respectively. In the wave generation unit, the terrain-sensitive perturbation factor affects the waveform direction, amplitude and propagation path. In the Niagara particle system, the terrain-sensitive perturbation factor affects the particle motion direction, velocity distribution and density aggregation area, thereby constructing a highly consistent mapping channel between the physical velocity field and the virtual vision system.

[0036] Optionally, S31 includes:

[0037] S311, Based on the perturbation map, the spatial rate of change of the perturbation map is calculated using a two-dimensional gradient operator to form a gradient field. The Euclidean norm of the perturbation gradient is calculated to quantify the magnitude of the perturbation gradient by setting a perturbation gradient threshold. Extract all that satisfy Spatial points are constructed into a set of terrain-sensitive points. Used to identify areas affected by abrupt terrain changes;

[0038] S312, in the set of terrain-sensitive points Surrounding spatial distribution weight map Spatial diffusion is performed using a Gaussian kernel function;

[0039] S313, based on the projected velocity field, introduces a unit vector field in the perturbation direction. The perturbation mapping is used to modulate the direction and amplitude, thereby generating a perturbation-modulated projected velocity field. .

[0040] Optionally, S32 includes:

[0041] S321, the projected velocity field after perturbation modulation It is deconstructed into direction vectors and amplitude information, which are used to control the propagation direction of Gertsner waves, respectively. ,amplitude and transmission path ;

[0042] S322, the projected velocity field after perturbation modulation As the particle velocity input field, the direction of particle motion, velocity amplitude, and density aggregation region are constructed, and their motion behavior is dynamically controlled in the Niagara system to drive the spatial position of the particles. Continuous updating and spatial distribution evolution;

[0043] S323, the propagation path output by the wave generation unit. Spatial position of particles generated by the Niagara particle system Synchronous binding is performed, and alignment is achieved through the rendering interface to form a consistent physical-visual dual-channel mapping channel. .

[0044] The beneficial effects of this invention are:

[0045] This invention constructs a free water surface slope based on boundary water level and real terrain elevation data, solves the initial velocity field by combining shallow water momentum equation and continuity equation, and introduces an incompressible projection correction method to generate a continuous projected velocity field. This can effectively improve the physical consistency and stability of the velocity field in virtual ocean current simulation, solve the problems of non-physical divergence and non-closure of disturbances in the velocity field in traditional engines, ensure that water motion meets the mass conservation condition, and improve the accuracy and reliability of calculated ocean current forecasts.

[0046] This invention, by integrating spatial disturbance features such as topographic gradient, abrupt changes in water depth, and boundary shear on the basis of the velocity difference field before and after projection correction, constructs a disturbance mapping map and introduces a gradient-sensitive region extraction and Gaussian weighted diffusion mechanism. This enables the accurate characterization of potential visual discontinuities caused by complex seabed topography and boundary response changes, solves the inconsistency problems such as directional offset and boundary jump between fluid rendering and physical calculation results in existing ocean current forecast visualization systems, and improves the visual fidelity of forecast dynamic flow fields in complex terrain environments.

[0047] This invention simultaneously transmits the perturbation-modulated velocity field input to the Gerstner wave generation unit and the Niagara particle system, driving wave propagation, particle density, and directional behavior within the forecast time series. By constructing a consistent mapping channel between the physical space and the rendering space, it can realize the linkage evolution of waveforms and particles under velocity drive, making the physical flow field and visual effects highly coupled. This improves the consistency and interactive immersion of ocean current simulation in applications such as virtual reality, underwater visualization simulation, and digital twins. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic diagram of the calculation method according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the projection velocity field construction according to an embodiment of the present invention. Detailed Implementation

[0051] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Those skilled in the art may employ other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0052] like Figures 1-2 As shown, a digital twin-based ocean current forecasting and visualization method includes the following steps:

[0053] S1 calculates the initial velocity field by setting the boundary water level and topographic elevation data of the simulation domain, and performs a projection correction operation on the initial velocity field to generate a projected velocity field that satisfies the fluid continuity constraint.

[0054] S2, perform difference analysis between the projected velocity field and the initial velocity field, and combine terrain gradient, depth abrupt change region and boundary velocity change rate to generate a perturbation mapping map to describe the visual difference region of the flow field, in order to characterize the potential visual discontinuity region caused by incompressibility correction.

[0055] S3, while maintaining the continuity of the projected velocity field, constructs a set of terrain-sensitive perturbation factors to reversibly perturb and modulate the velocity input in the wave generation unit and the Niagara particle system, so as to achieve a smooth transition and consistent evolution of the flow direction and particle behavior at the visual level, and complete a highly consistent mapping from the physical velocity field to the visual rendering system.

[0056] S4 provides high-resolution visualization output for the perturbation-modulated velocity input and supports dynamic configuration of boundary conditions such as water level and tides, enabling real-time calculation, continuous evolution simulation, and visualization prediction of regional ocean current fields.

[0057] S1 includes:

[0058] S11. Obtain and set the boundary water level and topographic elevation data of the simulation domain. The boundary water level time series data is used to describe the dynamic changes of the external tide level over time. The topographic elevation data is imported from the real topographic data into the virtual engine to form a bottom structure with spatial undulations. Based on the boundary water level time series data and topographic elevation data, the free water surface slope is constructed by analyzing the shallow water continuity equation and momentum equation, and the initial velocity field driving the fluid motion is calculated to reflect the physical velocity distribution state without continuity correction.

[0059] S12, based on the initial velocity field and considering the incompressibility requirement in fluid dynamics, performs a projection correction operation on the initial velocity field to generate a continuous projected velocity field.

[0060] S11 includes:

[0061] S111, importing boundary water levels from measured or simulated platforms. Topographic elevation data of the simulated area The data is then input into the autonomous ocean current calculation method (or plugin) developed for the water system of the digital twin platform via a data interface;

[0062] S112, based on boundary water level With topographic elevation data Generate free water surface height distribution Its spatial variation forms the water surface slope field. , is represented as:

[0063] ;

[0064] in, For along Water surface slope in the direction, For along The water surface slope in the direction;

[0065] S113, water surface slope field Substituting the pressure gradient source term into the shallow water momentum equation and continuity equation, the initial velocity field without continuity correction is calculated. , is represented as:

[0066] ;

[0067] ;

[0068] in, For flow velocity vectors, The height of the free water surface. It is the acceleration due to gravity. Because of the water depth, This refers to the bottom friction term.

[0069] S12 includes:

[0070] S121, for the initial velocity field Perform divergence calculations to determine whether mass conservation is satisfied. If it is not zero, it needs to be corrected, as shown below:

[0071] ;

[0072] S122, Construct the scalar potential function for correcting the velocity field. The distribution is solved using the Poisson equation, specifically including:

[0073] (1) Define the projection correction target and the form of the Poisson equation: to make the initial velocity field The incompressibility condition must be met, that is... It is necessary to start from Subtract a certain gradient field from the middle Constructing a modified velocity field , is represented as:

[0074] ;

[0075] Substituting the above equation into the incompressible constraint condition, we get:

[0076] ;

[0077] (2) Calculate the divergence of the initial velocity field as the source term on the right-hand side of the Poisson equation: based on the input initial velocity field Calculate its divergence, expressed as:

[0078] ;

[0079] (3) Solve the Poisson equation to obtain the modified potential function. Construct the Poisson equation, expressed as:

[0080] ;

[0081] The equation is solved numerically in the simulation domain to obtain the scalar potential function. ;

[0082] S123, based on the solved scalar potential function The initial velocity field is corrected to obtain the projected velocity field that satisfies the incompressibility condition. , is represented as:

[0083] ;

[0084] Right now: ;

[0085] in, For the projected velocity field, For speed correction, For time step.

[0086] S2 includes:

[0087] S21, perform difference calculation on the same spatial grid to construct the velocity difference field between the initial velocity field and the corrected projected velocity field;

[0088] S22, based on the velocity difference field, introduces spatial features related to visual disturbances, including terrain gradient, depth abrupt change region and boundary flow velocity change rate, constructs a disturbance weight field, and superimposes it with the velocity difference field to generate the final disturbance mapping map.

[0089] S21 includes:

[0090] S211, the initial velocity field With the corrected projected velocity field Align on the same two-dimensional spatial grid to ensure that they are at the same time step. ;

[0091] S212, at each grid point At this point, calculate the vector difference between the initial flow velocity and the corrected flow velocity, and construct the velocity difference field. , is represented as:

[0092] ;

[0093] in, For the initial flow velocity field, The corrected projected velocity field, The difference between velocity components;

[0094] S213, calculate the magnitude of the velocity difference field, and generate the velocity difference magnitude field. , used to reflect the intensity of local velocity disturbance, is expressed as:

[0095] .

[0096] S22 includes:

[0097] S221, Calculate terrain elevation data With water depth distribution Spatial gradient, including topographic gradient field and the gradient field of water depth abrupt change Topographic gradient fields are used to measure the drasticness of topographic changes, while abrupt changes in water depth gradient fields are used to assess the degree of abrupt changes in water depth in space. This is achieved by analyzing the topographic gradient field... With the gradient field of water depth abrupt change Weighted fusion is performed to generate a perturbation terrain weight field. , is represented as:

[0098] ;

[0099] ;

[0100] ;

[0101] in, Let be the gradient vector of the terrain elevation. , The topographic elevations are respectively at , First-order partial derivative in the direction, Let be the gradient vector of the water depth field. , The water depth is respectively , First-order partial derivative in the direction, , These are the corresponding weight coefficients;

[0102] S222, near the boundary of the simulation domain, calculate the rate of change of the corrected projected velocity field along the boundary normal direction, defined as the boundary velocity change rate. It is used to measure the intensity of disturbances caused by changes in boundary conditions and to construct the boundary disturbance weight field. , is represented as:

[0103] ;

[0104] ;

[0105] in, Let be the spatial first derivative of the projected velocity field in the boundary normal direction. This is the weighting adjustment coefficient;

[0106] S223 will perturb the terrain weight field Boundary perturbation weight field The velocity difference magnitude field, combined with the velocity difference field, forms a disturbance mapping diagram. , is represented as:

[0107] ;

[0108] .

[0109] S3 includes:

[0110] S31, while ensuring the continuity of the projected velocity field, uses the generated perturbation map to construct a spatially distributed terrain-sensitive perturbation factor, which is used to locally perturb and modulate the projected velocity field, making the velocity input more visually dynamic near dramatic terrain changes, boundary shears or abrupt change points, while maintaining smoothness in flat areas, thus achieving adaptive flow field input under perturbation modulation.

[0111] S32 takes the perturbation-modulated projected velocity field as input and feeds it into the wave generation unit based on Gerstner waves and the Niagara particle system, respectively. In the wave generation unit, the terrain-sensitive perturbation factor affects the waveform direction, amplitude, and propagation path. In the Niagara particle system, the terrain-sensitive perturbation factor affects the particle's motion direction, velocity distribution, and density aggregation area. Through this reversible modulation mechanism, the synchronicity of physical field driving and particle behavior in visual representation and the continuity of spatial transition are ensured, thereby constructing a highly consistent mapping channel between the physical velocity field and the virtual visual system.

[0112] S31 includes:

[0113] S311, Based on the perturbation map, the spatial rate of change of the perturbation map is calculated using a two-dimensional gradient operator to form a gradient field. The Euclidean norm of the perturbation gradient is calculated to quantify the magnitude of the perturbation gradient by setting a perturbation gradient threshold. Extract all that satisfy Spatial points are constructed into a set of terrain-sensitive points. Used to identify areas affected by abrupt topographic changes, denoted as:

[0114] ;

[0115] in, , The disturbance is mapped in the horizontal direction. Vertical direction Rate of change on;

[0116] ;

[0117] in, The first value representing the gradient norm. Percentiles Set a value for the percentile;

[0118] S312, in the set of terrain-sensitive points Surrounding spatial distribution weight map Spatial diffusion is performed using a Gaussian kernel function, expressed as:

[0119] ;

[0120] in, For the coordinates of the sensitive point, The Gaussian diffusion scale factor;

[0121] S313, based on the projected velocity field, introduces a unit vector field in the perturbation direction. The perturbation mapping is used to modulate the direction and amplitude, thereby generating a perturbation-modulated projected velocity field. , is represented as:

[0122] ;

[0123] ;

[0124] in, This is the perturbation modulation intensity factor.

[0125] S32 includes:

[0126] S321, the projected velocity field after perturbation modulation It is deconstructed into direction vectors and amplitude information, which are used to control the propagation direction of Gerstner waves, respectively. ,amplitude and transmission path , is represented as:

[0127] ;

[0128] ;

[0129] ;

[0130] in, Based on the basic wave amplitude, This is the initial position of the wave. For wavenumber vectors, Angular frequency;

[0131] S322, the projected velocity field after perturbation modulation As the particle velocity input field, the direction of particle motion, velocity amplitude, and density aggregation region are constructed, and their motion behavior is dynamically controlled in the Niagara system to drive the spatial position of the particles. The continuous updating and spatial distribution evolution can be represented as:

[0132] ;

[0133] ;

[0134] ;

[0135] ;

[0136] in, The particle velocity vector For local particle density, The default particle density. Density enhancement factor, The angle representing the direction of particle motion. , These are the components of the velocity field. This represents the inter-frame time step of the particle system.

[0137] S323, the propagation path output by the wave generation unit. Spatial position of particles generated by the Niagara particle system Synchronous binding is performed, and alignment is achieved through the rendering interface to form a consistent physical-visual dual-channel mapping channel. , is represented as:

[0138] ;

[0139] in, , These are the fusion weighting coefficients for physical simulation and visual rendering, respectively.

[0140] Specific examples are as follows:

[0141] In this embodiment, a nearshore bay digital twin scenario is selected as the simulation object. A 128×128 two-dimensional regular grid is used to establish the computational domain, and the unit spatial resolution is set to 1.0m. The actual simulation area size is 128m×128m. The seabed topography and elevation data are obtained by UAV scanning and imported into the UE5 scenario. The average seabed elevation is set to 0.0m, and the elevation of the local shallow water area is raised to 0.6m.

[0142] (a) Calculation of the initial velocity field driven by the boundary water level:

[0143] A tidal boundary condition is applied to the outer sea side boundary of the simulation domain, using tidal parameters from actual tide gauge stations:

[0144] Average water level: 1.5m;

[0145] Tide amplitude: 0.8m;

[0146] Tide period: 12h;

[0147] The boundary tide time series is then: ;

[0148] in, For simulation time, The number of seconds corresponding to 12h;

[0149] Mid-tide hour, ;

[0150] At this point, the water depth at the boundary grid is: ;

[0151] If the local subgrade elevation is: ;

[0152] This creates a significant water level gradient between the boundary and the average water depth within the domain;

[0153] Continuing to use the shallow water momentum equation:

[0154] ;

[0155] Wherein, the damping coefficient is taken as gravitational acceleration The velocity in the central region of the initial flow velocity field during the high tide phase was calculated as follows:

[0156] ;

[0157] The direction is from the port towards the bay.

[0158] (ii) Construction of the perturbation mapping diagram:

[0159] During the high tide phase, the difference between the projected velocity field and the initial flow velocity field is analyzed.

[0160] Set up a central area After projection correction The speed difference is:

[0161] ;

[0162] Further integration with local shallow water areas:

[0163] Terrain gradient: ;

[0164] abrupt changes in water depth gradient ;

[0165] Weighting coefficients: ;

[0166] but ;

[0167] Boundary perturbation weights: ;

[0168] Total weight: ;

[0169] Final perturbation mapping value: ;

[0170] This area was determined to fall within a visual discontinuity region.

[0171] (iii) Modulation of terrain-sensitive disturbances:

[0172] Based on the perturbation gradient threshold The bay mouth area and the shoal area are extracted as the sensitive point set.

[0173] Gaussian diffusion scale: ;

[0174] Disturbance intensity coefficient: ;

[0175] The velocity field after the disturbance is: ;

[0176] Calculations were performed in the bay area as follows: ;

[0177] It is significantly higher than that of ordinary areas.

[0178] (iv) Dynamic simulation plugin operation:

[0179] The plugin supports the following real-time boundary conditions:

[0180] Tide level drive;

[0181] Water level driven;

[0182] Wind farm driven;

[0183] The wind speed range in this embodiment is taken as follows: Wind direction range Number of local correction volumes: indivual;

[0184] They are respectively located at the mouth of the bay and the boundary of the restoration area;

[0185] Running Subsequently, the flow velocity in the central region evolved as follows: ;

[0186] It fully embodies the three-stage process of rising tide, slack tide, and ebb tide.

[0187] The particle density in the Niagara particle system is: ;

[0188] Bayou area: ;

[0189] It creates a distinct visual effect of converging currents.

[0190] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0191] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for ocean current forecasting and visualization based on digital twins, characterized in that, Includes the following steps: S1, by setting the boundary water level and topographic elevation data of the simulation domain, the initial velocity field is calculated. Taking into account the incompressibility requirement in fluid dynamics, a projection correction operation is performed on the initial velocity field to generate a projected velocity field that satisfies the fluid continuity constraint. S2, perform difference analysis between the projected velocity field and the initial velocity field, and combine the terrain gradient, depth abrupt change region and boundary velocity change rate to generate a disturbance mapping map to describe the visual difference region of the flow field, so as to characterize the potential visual discontinuity region caused by incompressible correction. S3, while maintaining the continuity of the projected velocity field, a set of terrain-sensitive perturbation factors are constructed to reversibly modulate the velocity input in the wave generation unit and the Niagara particle system, achieving a smooth transition and consistent evolution of flow direction and particle behavior at the visual level, completing a highly consistent mapping from the physical velocity field to the visual rendering system; specifically including: S31, while ensuring the continuity of the projected velocity field, the generated perturbation map is used to construct a spatially distributed terrain-sensitive perturbation factor for local perturbation modulation of the projected velocity field. S32 takes the perturbation-modulated projected velocity field as input and passes it into the wave generation unit based on Gerstner waves and the Niagara particle system respectively. In the wave generation unit, the terrain-sensitive perturbation factor affects the waveform direction, amplitude and propagation path. In the Niagara particle system, the terrain-sensitive perturbation factor affects the particle motion direction, velocity distribution and density aggregation area, thereby constructing a highly consistent mapping channel between the physical velocity field and the virtual vision system. S31 specifically includes: S311, Based on the perturbation map, the spatial rate of change of the perturbation map is calculated using a two-dimensional gradient operator to form a gradient field. The Euclidean norm of the perturbation gradient is calculated to quantify the magnitude of the perturbation gradient by setting a perturbation gradient threshold. Extract all that satisfy Spatial points are constructed into a set of terrain-sensitive points. Used to identify areas affected by abrupt terrain changes; S312, in the set of terrain-sensitive points Surrounding spatial distribution weight map Spatial diffusion is performed using a Gaussian kernel function; S313, based on the projected velocity field, introduces a unit vector field in the perturbation direction. The perturbation mapping is used to modulate the direction and amplitude, thereby generating a perturbation-modulated projected velocity field. ; S4, performs high-resolution visualization output on the perturbation-modulated velocity input, and supports dynamic configuration of boundary conditions such as water level and tides, realizing real-time calculation, continuous evolution simulation, ocean current forecasting and visualization prediction of regional ocean current field.

2. The ocean current forecasting and visualization method based on digital twins according to claim 1, characterized in that, S1 includes: S11. Obtain and set the boundary water level and topographic elevation data of the simulation domain. The boundary water level time series data is used to describe the dynamic changes of the external tide level over time. The topographic elevation data is imported from the real topographic data into the digital twin platform to form a bottom structure with spatial undulations. Based on the boundary water level time series data and topographic elevation data, the free water surface slope is constructed by analyzing the shallow water continuity equation and momentum equation, and the initial velocity field driving the fluid motion is calculated to reflect the physical velocity distribution state without continuity correction. S12, based on the initial velocity field and considering the incompressibility requirement in fluid dynamics, performs a projection correction operation on the initial velocity field to generate a continuous projected velocity field.

3. The ocean current forecasting and visualization method based on digital twins according to claim 2, characterized in that, S11 includes: S111, importing boundary water levels from measured or simulated platforms. Topographic elevation data of the simulated area The data is then input into the autonomous calculation method for ocean currents developed based on the digital twin platform water system via a data interface. S112, based on boundary water level With topographic elevation data Generate free water surface height distribution Its spatial variation forms the water surface slope field. ; S113, the water surface slope field Substituting the pressure gradient source term into the shallow water momentum equation and continuity equation, the initial velocity field without continuity correction is calculated. .

4. The ocean current forecasting and visualization method based on digital twins according to claim 3, characterized in that, S12 includes: S121, for the initial velocity field Perform divergence calculations to determine whether mass conservation is satisfied. If it is not zero, it needs to be corrected, as shown below: ； S122, Construct the scalar potential function for correcting the velocity field. Its distribution can be solved using the Poisson equation; S123, based on the solved scalar potential function The initial velocity field is corrected to obtain the projected velocity field that satisfies the incompressibility condition. .

5. The ocean current forecasting and visualization method based on digital twins according to claim 4, characterized in that, S2 includes: S21, perform difference calculation on the same spatial grid to construct the velocity difference field between the initial velocity field and the corrected projected velocity field; S22, based on the velocity difference field, introduces spatial features related to visual disturbances, including terrain gradient, depth abrupt change region and boundary flow velocity change rate, constructs a disturbance weight field, and superimposes it with the velocity difference field to generate the final disturbance mapping map.

6. The ocean current forecasting and visualization method based on digital twins according to claim 5, characterized in that, S21 includes: S211, the initial velocity field With the corrected projected velocity field Align on the same two-dimensional spatial grid to ensure that they are at the same time step. ; S212, at each grid point At this point, calculate the vector difference between the initial flow velocity and the corrected flow velocity, and construct the velocity difference field. ; S213, calculate the magnitude of the velocity difference field, and generate the velocity difference magnitude field. It is used to reflect the intensity of local velocity disturbance.

7. The ocean current forecasting and visualization method based on digital twins according to claim 6, characterized in that, S22 includes: S221, Calculate terrain elevation data With water depth distribution Spatial gradient, including topographic gradient field and the gradient field of water depth abrupt change The topographic gradient field is used to measure the drasticness of topographic changes, and the water depth abrupt change gradient field is used to assess the degree of abrupt changes in water depth in space. This is achieved by analyzing the topographic gradient field... With the gradient field of water depth abrupt change Weighted fusion is performed to generate a perturbation terrain weight field. ; S222, near the boundary of the simulation domain, calculate the rate of change of the corrected projected velocity field along the boundary normal direction, defined as the boundary velocity change rate. It is used to measure the intensity of disturbances caused by changes in boundary conditions and to construct the boundary disturbance weight field. ; S223 will perturb the terrain weight field Boundary perturbation weight field The velocity difference magnitude field, combined with the velocity difference field, forms a disturbance mapping diagram. .

8. The ocean current forecasting and visualization method based on digital twins according to claim 1, characterized in that, S32 includes: S321, the projected velocity field after perturbation modulation It is deconstructed into direction vectors and amplitude information, which are used to control the propagation direction of Gerstner waves, respectively. ,amplitude and transmission path ; S322, the projected velocity field after perturbation modulation As the particle velocity input field, the direction of particle motion, velocity amplitude, and density aggregation region are constructed, and their motion behavior is dynamically controlled in the Niagara system to drive the spatial position of the particles. Continuous updating and spatial distribution evolution; S323, the propagation path output by the wave generation unit. Spatial position of particles generated by the Niagara particle system Synchronous binding is performed, and alignment is achieved through the rendering interface to form a consistent physical-visual dual-channel mapping channel. .

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