Three-dimensional numerical simulation method for roe movement under complex hydrodynamic force of mountainous river

Abstract

The invention discloses a three-dimensional numerical simulation method for roe movement under complex water power of a mountain river, and belongs to the technical field of roe drifting numerical simulation. The method comprises the following steps: updating the density of roes at the current moment according to river water power data and hatching temperature; updating the particle size of the roe at the current moment; updating the settling velocity of the roe at the current moment according to the density of the roe at the current moment and the particle size of the roe at the current moment; generating a turbulence pulsation speed at the current moment by using random walk; according to the turbulence pulsation velocity at the current moment and the settling velocity of the roe at the current moment, updating the position of the roe at the current moment in a three-dimensional space by using a Lagrange particle tracking model; and returning to the next step of updating the position of the long roe, and ending roe movement simulation when the roe leaves the riverway area or the position of the roe is kept unchanged in the set time length or the simulation time length reaches the incubation time. The problem that an existing method has limitation in a transformed large river is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of numerical simulation of fish egg drifting, and in particular relates to a three-dimensional numerical simulation method of fish egg movement under complex hydrodynamics in mountain rivers. Background Art

[0002] The movement of drifting fish eggs is significantly affected by current velocity. In sections of river with slower currents, the eggs may hit the bottom and abort. In sections with faster currents, the higher current speeds may cause some eggs to strike rocks or structures, causing them to break. The altered hydrodynamics of the channel have made the drifting of fish eggs, a crucial developmental stage for fish, a crucial factor in protecting and controlling their populations.

[0003] The Fluvial Egg Drift Simulator (FluEgg) is a widely used three-dimensional Lagrangian tracking model that simulates the drift of common carp eggs in rivers and is used to understand the transport of invasive common carp eggs in various water bodies. FluEgg incorporates the development of egg characteristics (i.e., egg diameter and density as functions of time and temperature) and uses a one-dimensional hydrodynamic input from the river flow to drive the simulation. To account for the effects of turbulence and velocity profiles in the river channel, FluEgg uses a predefined turbulent diffusion parameterization of shear velocity and a beta function for the transverse velocity distribution. To simulate the stochastic nature of turbulence, FluEgg implements Lagrangian particle tracking using random walk and random displacement algorithms. The vertical motion of the eggs is calculated using empirical or semi-empirical eddy viscosity parameterizations, and sedimentation or buoyancy velocity is incorporated based on the density difference between the egg and the water.

[0004] FluEgg experiments in rectangular channels have demonstrated its ability to track egg drift patterns associated with hydrodynamic forces. A current scheme has successfully used FluEgg to predict the vertical distribution of eggs in a laboratory open channel. Furthermore, FluEgg's performance has been supported by field observations of carp reproduction in the Great Lakes. A current scheme has applied FluEgg to the St. Joseph River in Michigan and predicted hatching locations. A current scheme has also used FluEgg to study different silver carp egg and larvae transport scenarios in the Illinois waterway. Inverse simulations using FluEgg in the same river have enabled quantitative predictions of spawning locations. A current scheme has used FluEgg to estimate possible spawning locations in the Sandusky River in Ohio, combining egg drift with turbulence characteristics and temperature.

[0005] Although FluEgg has been widely used, a limitation of the model is that the simulator only inputs one-dimensional velocity information from hydraulic models or field data. Consequently, the missing information in the spatial dimension leads to errors and uncertainties in the three-dimensional space. Furthermore, the semi-empirical formulas for channel velocity profiles and turbulence parameterizations may not be accurate for all rivers and streams. This limitation is particularly pronounced in large, modified rivers, where local effects can arise from lateral velocity gradients, accelerating and decelerating flows, intense macroscale turbulence caused by intrachannel structures, or interactions between primary and secondary flows. FluEgg, using a simplified model, cannot well constrain the effects of cm- to m-scale turbulence on egg suspension, drift time and distance, and survival. Summary of the Invention

[0006] In response to the above-mentioned deficiencies in the prior art, the present invention provides a three-dimensional numerical simulation method for fish egg movement under complex hydrodynamics in mountain rivers, which solves the problem that the existing methods are limited in large rivers that have been transformed.

[0007] In order to achieve the above-mentioned object, the technical solution adopted by the present invention is: a three-dimensional numerical simulation method of fish egg movement under complex hydrodynamic conditions in mountain rivers, comprising:

[0008] S1. Acquire river hydrodynamic data and river channel data, and simulate the river based on the river hydrodynamic data and river channel data;

[0009] S2, the initial parameters of the fish eggs are set, which include the initial placement position, particle size, density, incubation time and incubation temperature of the fish eggs;

[0010] S3. Update the current density of fish eggs based on river hydrodynamic data and the incubation temperature of the fish eggs;

[0011] S4, updating the particle size of the fish eggs at the current moment;

[0012] S5, according to the density of fish eggs at the previous moment and the particle size of fish eggs at the current moment, update the settling velocity of fish eggs at the current moment;

[0013] S6. Generate the turbulent pulsation velocity at the current moment using random walk according to the river hydrodynamic data;

[0014] S7. updating the position of the fish eggs at the current moment in three-dimensional space using a Lagrangian particle tracking model according to the turbulent pulsation velocity at the current moment and the settling velocity of the fish eggs at the current moment;

[0015] S8, return step S3 and enter the position update of next step long fish eggs, when fish eggs leave river channel area or fish eggs remain unchanged in position under setting length or simulation duration reaches hatching time, end fish egg motion simulation.

[0016] The present invention has the following beneficial effects: using a realistic turbulence simulation algorithm to simulate the transport process of drifting fish eggs in various turbulent environments; coupling with the three-dimensional flow velocity and turbulence of complex rivers, using Markov chain random walks to simulate the random motion of fish eggs, and combining three-dimensional hydrodynamic data to drive egg drift, thereby providing better modeling capabilities and revealing the influence of local turbulence. Using the input hydrodynamic data, each individual fish egg is tracked at each time step based on the average water velocity, turbulent kinetic energy, and settling velocity of the fish egg in the water at the location. The egg position is updated at each time step, and then the water and egg properties are updated accordingly in the next time step, recording the complete drift trajectory of the fish egg in the river. This can reveal more relevant flow state information about local turbulence and vortices affected by hydraulic structures, and better understand the influence of strong spatial variations and vortices caused by the internal structure and complex riverbed morphology in large-scale engineering rivers with changing flow states.

[0017] Furthermore, the expression of the density of fish eggs at the current moment is:

[0018]

[0019] Among them, ρ egg (t) is the density of fish eggs at time t; t is the time after the fish eggs are fertilized; ρ ∞ is the density of the completely hardened egg; ρ' is the density change due to the water hardening effect; γ is the regression coefficient; ρ" is the density compensation for temperature change; T ref is the incubation temperature of fish eggs; T water is the water temperature.

[0020] The beneficial effects of this further solution include real-time simulation of the dynamic movement of fish eggs in water flow, enabling accurate calculation of the egg density at each time step. By setting key parameters such as the initial egg density, incubation time, and incubation temperature, the present invention accurately simulates the initial state of fish eggs in a natural river environment. Dynamically updating the egg density by combining input river hydrodynamic data with the incubation temperature allows for real-time reflection of the impact of water flow and temperature changes on egg distribution and development. The dynamic updating of the parameterized egg density allows for a more realistic reflection of the accuracy of the egg development process, providing more reliable data support for river ecology and fish resource protection.

[0021] Furthermore, the expression for the particle size of the fish eggs at the current moment is:

[0022]

[0023] Among them, D egg(t) is the size of the fish eggs at time t; t is the time after the fish eggs are fertilized; α and β are regression coefficients; D egg,min is the minimum diameter of the fish eggs, that is, the particle size of the fish eggs at t=0.

[0024] The beneficial effects of the above further scheme are: real-time simulation of the dynamic movement of fish eggs in the water flow, and the ability to accurately calculate the size of the fish eggs in each time step, or the development of the fish eggs. The present invention can accurately establish an initial state model of fish eggs in a real river by setting parameters such as the initial particle size and incubation time of the fish eggs, and adjust the particle size of the fish eggs in real time according to the diameter of the fish eggs as a function of the time after fertilization. Combined with the density function, it can fully simulate the growth and change process of fish eggs from the release to the hatching stage under the influence of environmental factors such as water flow and temperature. Compared with traditional single parameter or static simulation methods, this scheme significantly improves the simulation accuracy of the fish development process, and provides more realistic data support for the study of the early development mechanism of fish.

[0025] Furthermore, the expression of the settling velocity of the fish eggs at the current moment is:

[0026]

[0027]

[0028] Among them, V egg (t) is the sedimentation velocity of the fish eggs at time t; t is the time after the fish eggs are fertilized; g is the acceleration due to gravity; D egg (t) is the particle size of fish eggs at time t; ρ egg (t) is the density of fish eggs at time t; ρ l is the density of water; C d is the drag coefficient; Re is the Reynolds number; V egg (t-Δt) is the sinking velocity of the fish eggs at time t-Δt; D egg (t-Δt) is the particle size of the fish eggs at time t-Δt; Δt is the time step; v is the kinematic viscosity of water.

[0029] The beneficial effects of this further solution include the ability to simulate the dynamic movement of fish eggs in water in real time, and to accurately calculate the settling velocity of the eggs at each time step. By setting parameters such as the initial egg particle size, density, incubation time, and temperature, the present invention updates the egg density based on hydrodynamic data and incubation temperature, dynamically adjusts the particle size, and further calculates the settling velocity based on density and particle size. This clearly demonstrates the initial release state, growth and development status, and sedimentation of the eggs during the drifting process. This solution comprehensively covers the key dynamic changes of fish eggs in complex water flow environments, significantly improving the authenticity and completeness of ecological process simulations.

[0030] Furthermore, the expression of the turbulent pulsation velocity at the current moment is:

[0031] u i '(t)=u i '(t-Δt)exp(-Δt / τ i )+σ i (1-exp(-2Δt / τ i )) 1 / 2 ξ i

[0032] σ i =(2k / 3) 1 / 2

[0033] τ i =0.3k / ε

[0034] Among them, u i '(t) is the turbulent pulsation velocity at time t; Δt is the time step; u i '(t-Δt) is the turbulent pulsation velocity before updating, i.e. at time t-Δt; τ i is the Lagrangian time scale of the turbulent eddy; σ i is the root mean square of the instantaneous velocity in each direction; ξ i is the random nature of the turbulent velocity; k is the turbulent kinetic energy; ε is the turbulent dissipation rate.

[0035] The beneficial effects of the above further scheme are: in the simulation process, the temporal and spatial changes of water flow, the interaction between fish eggs and the surrounding environment (such as how the local characteristics of channel regulation structures affect the dispersion of fish eggs and the retention and resuspension drift of fish eggs), and the biological characteristics of fish eggs themselves (such as hatching, death, sedimentation, etc.) are fully considered to achieve a highly realistic simulation of the fish egg drift process. The present invention uses random walks to generate turbulent pulsating velocity, combined with the growth changes of fish eggs themselves, to fully cover the key physical processes of fish eggs affected by the environment in the river. Compared with traditional simulation methods, this scheme not only takes into account the drifting development of fish eggs, but also describes the random disturbance of water turbulence on the movement of fish eggs, which significantly improves the comprehensiveness and authenticity of the simulation of the dynamic process of fish egg drift. Hydrodynamic conditions and temperature drive density changes, particle size growth affects sedimentation velocity, and turbulent pulsating velocity further corrects the movement trajectory of fish eggs through random walk simulation. This method effectively overcomes the defects of isolated parameter calculation or neglect of local turbulence effects in traditional models. It can better understand the influence of strong spatial changes and eddies caused by the internal structure and complex riverbed morphology in large and changing rivers, and achieve a highly realistic simulation of the fish egg drifting process.

[0036] Furthermore, the expression for the position of the fish eggs at the current moment is:

[0037] xi (t) = x i (t-Δt)+(U i (t-Δt,x i (t-Δt))+u i '(t-Δt)+V egg (t-Δt))Δt

[0038] Among them, x i (t) is the position of the fish eggs at time t; x i (t-Δt) is the position of the fish eggs before the update, i.e. at time t-Δt; U i (t-Δt,x i (t-Δt)) is the egg position x before the update, i.e., at time t-Δt i Average flow velocity at (t-Δt); u i '(t-Δt) is the turbulent pulsation velocity before updating, i.e. at time t-Δt; V egg (t-Δt) is the sinking velocity of the fish eggs before updating, that is, at time t-Δt; Δt is the time step.

[0039] The beneficial effect of the above further scheme is that during the simulation process, the temporal and spatial changes of water flow, the interaction between fish eggs and the surrounding environment (for example, how the local characteristics of channel regulation buildings affect the dispersion of fish eggs and the retention and resuspension drift of fish eggs), and the biological characteristics of fish eggs themselves (such as hatching, death, sedimentation, etc.) are fully considered to achieve a highly realistic simulation of the fish egg drift process. The present invention ultimately locates the fish egg position in real time in three-dimensional space through a Lagrangian particle tracking model, which significantly improves the authenticity and spatial accuracy of the simulation of the movement trajectory of fish eggs in a complex river environment compared to traditional two-dimensional or static simulation methods. The full three-dimensional scale numerical simulation model of the drifting fish egg trajectory can not only couple with hydrodynamics and use the three-dimensional hydrodynamic modeling to output terrain and flow field data to study the movement of fish eggs, but also directly input measured terrain and water flow data, realizing the full utilization of data. Compared with other two-dimensional hydrodynamic models, in three-dimensional space, more complex turbulent conditions are studied, especially near regulation buildings, where local turbulent disturbances are large, to achieve a more realistic and complete simulation of the fish egg drift trajectory. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Flow chart of the method of the present invention.

[0041] Figure 2 This is a high-level diagram of water levels at different flow rates in an embodiment of the present invention.

[0042] Figure 3 Schematic diagram of the elevation calibration hydrodynamic model under different flow rates in an embodiment of the present invention.

[0043] Figure 4 Schematic diagram of the comparison of average velocity of a river section under different flow rates in an embodiment of the present invention.

[0044] Figure 5 Schematic diagram of the positions of fish eggs at four different times after being released into the Missouri River in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0046] like Figure 1 As shown, in one embodiment of the present invention, a three-dimensional numerical simulation method for fish egg movement under complex hydrodynamics in mountain rivers includes:

[0047] S1. Acquire river hydrodynamic data and river channel data, and simulate the river based on the river hydrodynamic data and river channel data;

[0048] S2, the initial parameters of the fish eggs are set, which include the initial placement position, particle size, density, incubation time and incubation temperature of the fish eggs;

[0049] S3. Update the current density of fish eggs based on river hydrodynamic data and the incubation temperature of the fish eggs;

[0050] S4, updating the particle size of the fish eggs at the current moment;

[0051] S5, according to the density of fish eggs at the previous moment and the particle size of fish eggs at the current moment, update the settling velocity of fish eggs at the current moment;

[0052] S6. Generate the turbulent pulsation velocity at the current moment using random walk according to the river hydrodynamic data;

[0053] S7. updating the position of the fish eggs at the current moment in three-dimensional space using a Lagrangian particle tracking model according to the turbulent pulsation velocity at the current moment and the settling velocity of the fish eggs at the current moment;

[0054] S8, return step S3 and enter the position update of next step long fish eggs, when fish eggs leave river channel area or fish eggs remain unchanged in position under setting length or simulation duration reaches hatching time, end fish egg motion simulation.

[0055] In this example, this method uses multidimensional modeling to help understand turbulence in complex river systems with meandering, interlaced, or co-channel flow structures, thereby overcoming the limitations of one-dimensional river information. Because three-dimensional hydrodynamic models provide better vertical flow information, coupling a three-dimensional Lagrangian particle tracking (LPT) model with the three-dimensional hydrodynamics significantly improves model performance by reducing the parameterization of vertical flow.

[0056] This method developed a three-dimensional fish egg particle tracking model coupled with three-dimensional computational fluid dynamics (CFD) modeling. By combining evaluations of idealized river channels with large-scale channelized river experiments, the results were extended to river channels with channel regulation structures. The model was used to predict the transport trajectories and final distribution of fish eggs in various turbulent environments with increasing channel complexity.

[0057] The expression of the density of fish eggs at the current moment is:

[0058]

[0059] Among them, ρ egg (t) is the density of fish eggs at time t; t is the time after the fish eggs are fertilized; ρ ∞ is the density of the completely hardened egg; ρ' is the density change due to the water hardening effect; γ is the regression coefficient; ρ" is the density compensation for temperature change; T ref is the incubation temperature of fish eggs; T water is the water temperature.

[0060] The expression of the particle size of the fish eggs at the current moment is:

[0061]

[0062] Among them, D egg (t) is the size of the fish eggs at time t; t is the time after the fish eggs are fertilized; α and β are regression coefficients; D egg,min is the minimum diameter of the fish eggs, that is, the particle size of the fish eggs at t=0.

[0063] The expression of the sedimentation velocity of the fish eggs at the current moment is:

[0064]

[0065] Among them, V egg (t) is the sedimentation velocity of the fish eggs at time t; t is the time after the fish eggs are fertilized; g is the acceleration due to gravity; D egg (t) is the particle size of fish eggs at time t; ρ egg (t) is the density of fish eggs at time t; ρ l is the density of water; C dis the drag coefficient; Re is the Reynolds number; V egg (t-Δt) is the sinking velocity of the fish eggs at time t-Δt; D egg (t-Δt) is the particle size of the fish eggs at time t-Δt; Δt is the time step; v is the kinematic viscosity of water.

[0066] The expression of the turbulent pulsation velocity at the current moment is:

[0067] u i '(t)=u i '(t-Δt)exp(-Δt / τ i )+σ i (1-exp(-2Δt / τ i )) 1 / 2 ξ i

[0068] σ i =(2k / 3) 1 / 2

[0069] τ i =0.3k / ε

[0070] Among them, u i '(t) is the turbulent pulsation velocity at time t; Δt is the time step; u i '(t-Δt) is the turbulent pulsation velocity before updating, i.e. at time t-Δt; τ i is the Lagrangian time scale of the turbulent eddy; σ i is the root mean square of the instantaneous velocity in each direction; ξ i is the random nature of the turbulent velocity; k is the turbulent kinetic energy; ε is the turbulent dissipation rate.

[0071] The expression of the position of the fish eggs at the current moment is:

[0072] x i (t) = x i (t-Δt)+(U i (t-Δt,x i (t-Δt))+u i '(t-Δt)+V egg (t-Δt))Δt

[0073] Among them, x i (t) is the position of the fish eggs at time t; x i (t-Δt) is the position of the fish eggs before the update, i.e. at time t-Δt; U i (t-Δt,x i (t-Δt)) is the egg position x before the update, i.e., at time t-Δt i Average flow velocity at (t-Δt); ui '(t-Δt) is the turbulent pulsation velocity before updating, i.e. at time t-Δt; V egg (t-Δt) is the sinking velocity of the fish eggs before updating, that is, at time t-Δt; Δt is the time step.

[0074] Example 2

[0075] This embodiment, based on the method of Example 1, provides SDrift, a three-dimensional numerical simulation software for trajectories of drifting fish eggs in regulated waterways. The software comprises four modules: a data input module, a model building module, a simulation calculation module, and a post-processing analysis module. Each module contains different subsystems, each of which operates based on input files or parameters. The initial code is modified to adapt to different river channel and fish egg characteristics.

[0076] (1) Data input module: In order to drive the drift of fish eggs, three-dimensional river hydrodynamic data is required as an input file to calculate the movement of fish eggs in the river. The river channel data for fish egg drift can be provided by known river channel topography data, or it can be loaded by reading digital terrain models and geographic system data. The input river hydrodynamic data can be output by a three-dimensional hydrodynamic model (Flow 3D, Fluent, etc.) or by field measurement data from a flow velocity sensor (such as an acoustic Doppler current profiler, ADCP, etc.).

[0077] ① Hydrological data input: (i) Input processed three-dimensional river hydrodynamic data: three-dimensional spatial velocity (U, V, W), shear velocity U * , turbulence data (turbulent kinetic energy k, turbulent dissipation rate ε), etc.; (ii) measured river data: import real-time hydrological data such as river velocity, flow, water depth, etc., and support import in multiple formats such as text files and databases.

[0078] ② River channel data input: (i) Input river channel topography data (water surface, riverbed, and sidewalls, etc.); (ii) Read digital terrain model (DTM) and geographic information system (GIS) data to accurately restore the river channel topography, including information such as riverbed slope, river bend location, and riverbank shape.

[0079] During the simulation, the hydrodynamic model needs to be continuously debugged to improve the initial hydrodynamic simulation accuracy. Figure 2 and Figure 3 As shown in the figure, the x-axis is the distance along the river, the y-axis is the water surface elevation, the FLOW3D data is the red dashed line, the HEC-RAS is the reference two-dimensional model, and the black line is the field measurement value. By adjusting the model parameters, the simulated water surface elevation for each flow rate was successfully calibrated. Figure 4 As shown, the average velocity of section 10 is compared at different flow rates (the average flow velocity on the profile matches the measured value well).

[0080] (2) Model building module: Using the input hydrodynamic data, the individual fish eggs are tracked at each time step based on the average water flow velocity, turbulent fluctuations, and the settling velocity of the fish eggs in the water at the location of the fish eggs. Based on the characteristics of the fish eggs (i.e., diameter, density), the settling velocity of the local fish eggs is calculated, which is a function of the local water body characteristics and the spawning time. The properties of the water can be output from the hydrodynamic model. For well-mixed rivers, a constant temperature can be specified. The specified temperature is also required to calculate the growth and performance of the fish eggs. The position of the fish eggs is updated at each time step, and then the properties of the water and fish eggs are updated accordingly in the next time step. The above conditions are input as parameters, and considering the biological characteristics of different fish eggs, the initial parameters of the fish eggs are set, including initial water flow conditions, initial placement location of the fish eggs (latitude and longitude coordinates or position relative to the river channel), number, particle size, density, incubation time, incubation temperature range, etc. The model is coded using Python software, and all sub-models (such as fish egg characteristics, water flow characteristics, etc.) are written in modules to facilitate model updating or modification, which can be used to track the early life stages of other fish.

[0081] ① Model setup: (i) 3D Lagrangian tracking model: The full-scale turbulent kinetic energy and dissipation rate are used to update the Lagrangian particle tracking model in 3D space; (ii) Markov chain random walk algorithm: Using the Markov chain equation, a random walk can be used to generate realistic turbulent fluctuations associated with local river turbulence.

[0082] The Lagrangian fish egg tracking equation can be written as:

[0083] x i (t+Δt)=x i (t)+(U i (t,x i )+u i '(t,x i )+u i,egg (t))Δt

[0084] The equivalent Markov chain equation of the continuous random walk (CRW) model is:

[0085] u′ i (t+Δt)=u′ i (t)exp(-Δt / τ i )+σ i (1-exp(-2Δt / τ i )) 1 / 2 ξ i

[0086] In this model, σ i and τ iModeled by the turbulent kinetic energy (k) and its dissipation rate (ε):

[0087] σ i =(2k / 3) 1 / 2

[0088] τ i =0.3k / ε

[0089] ② Main parameter settings: (i) Simulation parameter settings: Set the time step, simulation time, and maximum computation time; (ii) Egg parameter settings: Based on the biological characteristics of different fish species, set the initial parameters of the eggs, including initial water flow conditions, initial egg placement location (latitude and longitude coordinates or position relative to the river channel), quantity, particle size, density, incubation time, incubation temperature range, and other parameters. Users can also group different batches of eggs to distinguish and track egg populations of different sources or characteristics during the simulation; (iii) Parameter adjustment: The model is coded in Python software, and all sub-models (such as egg characteristics, water flow characteristics, etc.) are written as modules to facilitate model updates or modifications.

[0090] Diameter of fish eggs D egg The equation for (t) as a function of time t after fertilization is:

[0091]

[0092] Uses the same egg density parameterization as FluEgg, and compensates for the effects of water temperature:

[0093]

[0094] The equation for the settling velocity of fish eggs is:

[0095]

[0096] Here, the Reynolds number is defined as:

[0097] ③ The main parameters of the fish egg transport model are summarized in Table 1 (the following parameters are only used for debugging and can be updated and modified according to actual conditions)

[0098] Table 1

[0099]

[0100] (3) Model operation module: The model uses the solution of random differential equations to simulate the real turbulent velocity and combines it with three-dimensional hydrodynamic data to drive the drift of fish eggs, so as to have better modeling capabilities to reveal the influence of local turbulence. The model simulates the influence of turbulence on the drift of fish eggs based on the selected Markov chain continuous random walk, and characterizes the inherent properties of turbulent fluctuations in the fluid based on the continuous basis, which takes into account the autocorrelation behavior of velocity fluctuations. Therefore, it has the ability to simulate the dynamic movement process of fish eggs in the water flow in real time, and can accurately calculate the position, velocity, state change and other information of the fish eggs in each time step. In addition, the three-dimensional fish egg particle tracking model is coupled with the three-dimensional computational fluid dynamics (CFD) model to better understand the influence of strong spatial changes and vortices caused by the internal structure of the river and the complex riverbed morphology in the changing large rivers, and achieve a highly realistic simulation of the fish egg drift process.

[0101] ① Real-time dynamic simulation: The system has the ability to simulate the dynamic movement of fish eggs in the water in real time, accurately calculating the position, velocity, state changes, and other information of the eggs at each time step. During the simulation process, the system fully considers the spatiotemporal changes of the water flow, the interaction between the fish eggs and the surrounding environment (for example, how the local characteristics of the channel regulation structures affect the dispersion of fish eggs and the retention and resuspension of fish eggs), and the biological characteristics of the fish eggs themselves (such as hatching, death, sedimentation, etc.), achieving a highly realistic simulation of the fish egg drift process.

[0102] ② Turbulence parameters applicable to the three-dimensional fish egg particle tracking model: This method is based on a full three-dimensional model and utilizes the full capabilities of SDrift simulation, that is, initializing three-dimensional tracking with three-dimensional velocity at any given position (x, y, z).

[0103] Post-processing analysis module: Two-dimensional visualization: The software can generate two-dimensional graphics of the distribution and movement of fish eggs. By selecting different time steps and observation areas, the drifting trajectory, density distribution and other information of the fish eggs can be viewed. A variety of visualization options are provided (such as curve graphs, scatter plots, vector graphs, etc.); Three-dimensional visualization: The software uses three-dimensional graphics technology to display the movement trajectory and distribution of fish eggs in the river. The three-dimensional scene can be observed from different angles, and it supports animation display functions to dynamically present the drifting process of fish eggs. In this embodiment, the simulation results are as follows: Figure 5 Shown are the locations of fish eggs at four different times after release in the Missouri River. The red line indicates the release location of the eggs; the green dots represent eggs in motion; and the black dots represent eggs captured by the riverbed or sidewalls, including the levees of hydraulic structures within the river.

[0104] Example 3

[0105] A three-dimensional numerical simulation method for the trajectory of drifting fish eggs in a regulated waterway, comprising the following specific steps:

[0106] Step 1: Build a model. The model is coded using Python software to generate a three-dimensional Lagrangian tracking model. By tracking the motion of individual particles in the fluid, considering information such as the position, velocity, and acceleration of the particles in three-dimensional space, the position and state of the particles at different times can be accurately calculated.

[0107] In step 2, two random walk algorithms are encoded in the model, one is a traditional random algorithm, and the other is the improved Markov chain random walk algorithm described in Example 2. The longitudinal and lateral movements are calculated using the random walk method, and the model calculation time depends on the tracking time of each fish egg. During the specific simulation, the traditional algorithm can be compared with the improved algorithm of Example 2.

[0108] Traditional random walk algorithm:

[0109]

[0110] in, 和 are the positions of the fish eggs in the X, Y and Z directions at time t; u, v, w are the flow velocities in the X, Y and Z directions respectively; Δt is the time step; R is the random term affected by turbulence; V s is the settling velocity of fish eggs.

[0111] The improved algorithm described in Example 1 is an improved fish egg migration algorithm based on the random walk. A drawback of the random walk algorithm is that its random term generation is discrete, which causes the particles to have a true random motion that is independent of time. This phenomenon is often inconsistent with the actual situation of nature. In order to introduce temporal information, a Markov chain random walk is used to convolve the influence mechanism of turbulence on fish eggs in the time direction, thereby making the random behavior of fish eggs also continuous and predictable to a certain extent. This is particularly applicable to the movement process of millimeter-scale particles such as fish eggs.

[0112] Step 3: Use FLOW-3D software to build a hydrodynamic mathematical model and output three-dimensional hydrodynamic data, including turbulent energy, turbulent energy dissipation, water level, speed in the x, y, and z directions, and terrain elevation data;

[0113] Step 4: Input the processed 3D hydrodynamic data or measured river data in *.txt format. 3D hydrodynamic data can be output from a 3D hydrodynamic model (e.g., Flow 3D, Fluent), or from field measurements using a flow sensor (e.g., Acoustic Doppler Current Profiler, ADCP, etc.).

[0114] Step 5: Input the river data of the fish eggs drifting. This data should be input in *.txt text format. This can be provided by known river terrain data (measured water surface, riverbed, sidewalls, etc.), or by reading digital terrain models and geographic system data (GIS system);

[0115] Step 6: Set the numerical model parameters, including simulation parameters and egg parameters. Simulation parameters include time step and simulation time; egg parameters include water flow conditions, temperature, and egg characteristics (egg placement location, quantity and density, diameter, etc.).

[0116] Step seven, calculate the settling velocity of local fish eggs based on the characteristics of the fish eggs (density, diameter), which is a function of the local water characteristics and the spawning time.

[0117] Step 8: Using the input hydrodynamic data, track the individual fish eggs at each time step based on the average water flow velocity, turbulent fluctuations, and the settling speed of the fish eggs in the water at the location of the fish eggs.

[0118] Step nine: terminate the fish egg tracking. There are two termination criteria: the fish eggs leave the calculation area during the drifting process; the fish eggs remain stationary at a certain position for a certain period of time. This model uses 30 seconds as the judgment criterion.

[0119] Step 10: Finally, Matlab software is used to perform corresponding post-processing to obtain visualization results.

[0120] The three-dimensional Lagrangian model used in this method is an improved and efficient fish egg drifting model, which is improved from a low-dimensional model to a three-dimensional model.

[0121] This method uses the hydrodynamic data output by the hydrodynamic model to input the three-dimensional numerical model of the trajectory of drifting fish eggs in the regulated channel, forming an egg transport model (i.e., SDrift software) that couples the three-dimensional egg tracking model with the three-dimensional computational fluid dynamics (CFD) model.

Claims

1. A three-dimensional numerical simulation method for fish egg movement under complex hydrodynamic conditions in mountain rivers, characterized by: include: S1. Acquire river hydrodynamic data and river channel data, and simulate the river based on the river hydrodynamic data and river channel data; S2, the initial parameters of the fish eggs are set, which include the initial placement position, particle size, density, incubation time and incubation temperature of the fish eggs; S3. Update the current density of fish eggs based on river hydrodynamic data and the incubation temperature of the fish eggs; S4, updating the particle size of the fish eggs at the current moment; S5, according to the density of fish eggs at the previous moment and the particle size of fish eggs at the current moment, update the settling velocity of fish eggs at the current moment; S6. Generate the turbulent pulsation velocity at the current moment using random walk according to the river hydrodynamic data; S7. updating the position of the fish eggs at the current moment in three-dimensional space using a Lagrangian particle tracking model according to the turbulent pulsation velocity at the current moment and the settling velocity of the fish eggs at the current moment; S8, return step S3 and enter the position update of next step long fish eggs, when fish eggs leave river channel area or fish eggs remain unchanged in position under setting length or simulation duration reaches hatching time, end fish egg motion simulation.

2. The three-dimensional numerical simulation method for fish egg movement under complex hydrodynamic conditions in mountain rivers according to claim 1 is characterized in that: The expression of the density of fish eggs at the current moment is: Among them, ρ egg (t) is the density of fish eggs at time t; t is the time after the fish eggs are fertilized; ρ ∞ is the density of the completely hardened egg; ρ' is the density change due to the water hardening effect; γ is the regression coefficient; ρ" is the density compensation for temperature change; T ref is the incubation temperature of fish eggs; T water is the water temperature.

3. The three-dimensional numerical simulation method for fish egg movement under complex hydrodynamic conditions in mountain rivers according to claim 1 is characterized in that: The expression of the particle size of the fish eggs at the current moment is: Among them, D egg (t) is the size of the fish eggs at time t; t is the time after the fish eggs are fertilized; α and β are regression coefficients; D egg,min is the minimum diameter of the fish eggs, that is, the particle size of the fish eggs at t=0.

4. The three-dimensional numerical simulation method for fish egg movement under complex hydrodynamic conditions in mountain rivers according to claim 1 is characterized in that: The expression of the sedimentation velocity of the fish eggs at the current moment is: Among them, V egg (t) is the sedimentation velocity of the fish eggs at time t; t is the time after the fish eggs are fertilized; g is the acceleration due to gravity; D egg (t) is the particle size of fish eggs at time t; ρ egg (t) is the density of fish eggs at time t; ρ l is the density of water; C d is the drag coefficient; Re is the Reynolds number; V egg (t-Δt) is the sinking velocity of the fish eggs at time t-Δt; D egg (t-Δt) is the particle size of the fish eggs at time t-Δt; Δt is the time step; v is the kinematic viscosity of water.

5. The three-dimensional numerical simulation method for fish egg movement under complex hydrodynamic conditions in mountain rivers according to claim 1 is characterized in that: The expression of the turbulent pulsation velocity at the current moment is: you i '(t)=u i '(t-Δt)exp(-Δt / τ i )+s i (1-exp(-2Δt / τ) i )) 1 / 2 x i s i =(2k / 3) 1 / 2 t i =0.3k / e Among them, u i '(t) is the turbulent pulsation velocity at time t; Δt is the time step; u i '(t-Δt) is the turbulent pulsation velocity before updating, i.e. at time t-Δt; τ i is the Lagrangian time scale of the turbulent eddy; σ i is the root mean square of the instantaneous velocity in each direction; ξ i is the random nature of the turbulent velocity; k is the turbulent kinetic energy; ε is the turbulent dissipation rate.

6. The three-dimensional numerical simulation method for fish egg movement under complex hydrodynamic conditions in mountain rivers according to claim 1 is characterized in that: The expression of the position of the fish eggs at the current moment is: x i (t)=x i (t-Δt)+(U i (t-Δt,x i (t-Δt))+u i '(t-Δt)+V egg (t-Δt))Δt Among them, x i (t) is the position of the fish eggs at time t; x i (t-Δt) is the position of the fish eggs before the update, i.e. at time t-Δt; U i (t-Δt,x i (t-Δt)) is the egg position x before the update, i.e., at time t-Δt i Average flow velocity at (t-Δt); u i '(t-Δt) is the turbulent pulsation velocity before updating, i.e. at time t-Δt; V egg (t-Δt) is the sinking velocity of the fish eggs before updating, that is, at time t-Δt; Δt is the time step.

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