Wading bridge bird protection decision closed engineering optimization method and device, computer equipment and readable storage medium

Abstract

The invention discloses a closed engineering optimization method and device for a wading bridge bird protection decision, computer equipment and a readable storage medium, and relates to the field of engineering design, and the method comprises the steps: building a bird flight path dynamics and energy consumption model, and solving a flight path with the lowest energy consumption at different initial heights; on the basis of the track and the bird warning distance, constructing a bridge interference warning equipotential plane representing that the bird enters the warning distance space position set for the first time; calculating a bird disturbed area in an equipotential plane and a group disturbed probability based on bird flock density; a comprehensive cost function is constructed by combining the bridge full-closed engineering cost and the ecological loss cost, and the target full-closed length is determined by optimizing the function. According to the method, the balance between the engineering cost and ecological protection is realized by quantifying the bird flight behavior and interference risk, and a scientific decision basis is provided for the wading bridge bird protection engineering.

Description

Technical Field

[0001] The present invention relates to the field of engineering design, and in particular to a closed engineering optimization method, device, computer equipment and readable storage medium for bird protection decision-making on wading bridges. Background Art

[0002] As the conflict between bridge construction and ecological protection becomes increasingly prominent, the construction and operation of water-related bridges, as critical infrastructure spanning ecologically sensitive areas such as rivers and lakes, can easily disrupt surrounding bird habitats and migratory routes. Traditional bird protection measures for bridges often rely on empirically designed enclosures, such as full bridge closures or partial netting. However, these measures pose challenges such as excessive enclosure leading to increased project costs, or insufficient enclosure posing a risk of bird collisions. Summary of the Invention

[0003] The purpose of the present invention is to provide a closed engineering optimization method, device, computer equipment and readable storage medium for bird protection decision-making on wading bridges.

[0004] In a first aspect, an embodiment of the present invention provides a closed engineering optimization method for bird protection decision-making on wading bridges, comprising:

[0005] Construct a bird flight trajectory dynamics and energy consumption model, and solve the flight trajectory with the lowest energy consumption for birds at different starting altitudes;

[0006] Based on the minimum energy consumption flight trajectory and the preset bird warning distance, constructing a bridge interference warning equipotential surface, wherein the interference warning equipotential surface represents the set of spatial positions of birds at different starting heights when they first enter the warning distance on their minimum energy consumption flight trajectory;

[0007] Based on the bridge interference warning equipotential surface, calculating the disturbed area of ​​birds and the probability of a flock being disturbed, wherein the disturbed area is the spatial range within the interference warning equipotential surface in the flight trajectory with the lowest energy consumption, and the probability of a flock being disturbed is calculated based on the disturbed area and the density of the bird flock;

[0008] Based on the disturbed area and the probability of group disturbance, combined with the cost of full-closure engineering of the bridge and the cost of ecological loss, a comprehensive cost function is constructed, and the target full-closure length of the bridge is determined by optimizing the comprehensive cost function.

[0009] In a second aspect, an embodiment of the present invention provides a closed engineering optimization device for bird protection decision-making on wading bridges, comprising:

[0010] An acquisition module is configured to construct a bird flight trajectory dynamics and energy consumption model, and solve for the bird's minimum energy consumption flight trajectory at different starting altitudes; construct a bridge interference warning equipotential surface based on the minimum energy consumption flight trajectory and a preset bird warning distance, wherein the interference warning equipotential surface represents the set of spatial positions of birds at different starting altitudes when they first enter the warning distance on their minimum energy consumption flight trajectory; calculate the bird interference area and the probability of group interference based on the bridge interference warning equipotential surface, wherein the interference area is the spatial range within the interference warning equipotential surface in the minimum energy consumption flight trajectory, and the probability of group interference is calculated based on the interference area and the bird flock density;

[0011] In the optimization module, the user constructs a comprehensive cost function based on the disturbed area and the group disturbance probability, combined with the bridge full closure project cost and the ecological loss cost, and determines the target full closure length of the bridge by optimizing the comprehensive cost function.

[0012] In a third aspect, an embodiment of the present invention provides a computer device, comprising a processor and a non-volatile memory storing computer instructions, wherein when the computer instructions are executed by the processor, the computer device executes the method described in the first aspect.

[0013] In a fourth aspect, an embodiment of the present invention provides a readable storage medium, wherein the readable storage medium includes a computer program, and when the computer program is executed, the computer device where the readable storage medium is located is controlled to execute the method described in the first aspect.

[0014] Compared to existing technologies, the present invention offers the following advantages: Using the disclosed method, device, computer equipment, and readable storage medium for optimizing closure projects for bird protection decisions on wading bridges, the present invention constructs a model of bird flight trajectory dynamics and energy consumption to determine the flight trajectory with the lowest energy consumption at different starting altitudes; based on this trajectory and the bird warning distance, a bridge interference warning equipotential surface is constructed, representing the set of spatial locations where birds first enter the warning distance; the bird interference area within the equipotential surface and the probability of group interference based on flock density are calculated; and a comprehensive cost function is constructed combining the cost of full bridge closure and the ecological loss cost, which is then optimized to determine the target full closure length. By quantifying bird flight behavior and interference risk, this method achieves a balance between project cost and ecological protection, providing a scientific basis for decision-making in bird protection projects on wading bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly describes the drawings required for use in the embodiments. It should be understood that the following drawings illustrate only certain embodiments of the present invention and should not be construed as limiting the scope of the present invention. Those skilled in the art can, without inventive effort, derive other relevant drawings from these drawings.

[0016] Figure 1 A schematic flow chart of the steps of a closed engineering optimization method for bird protection decision-making for wading bridges provided in an embodiment of the present invention;

[0017] Figure 2 A schematic block diagram of the structure of a closed engineering optimization device for bird protection decision-making for wading bridges provided by an embodiment of the present invention;

[0018] Figure 3 A schematic block diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the embodiments of the present invention. It should be understood that the described embodiments are only a portion of the embodiments of the present invention, not all of them. Generally, the components of the embodiments of the present invention described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations.

[0020] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0021] In order to solve the technical problems in the above background technology, Figure 1 This is a flow chart of a closed engineering optimization method for bird protection decisions on wading bridges provided in an embodiment of the present disclosure. The closed engineering optimization method for bird protection decisions on wading bridges is introduced in detail below.

[0022] Step S201: construct a bird flight trajectory dynamics and energy consumption model, and solve to obtain the bird's minimum energy consumption flight trajectory at different starting altitudes;

[0023] Step S202: constructing a bridge interference warning equipotential surface based on the minimum energy consumption flight trajectory and a preset bird warning distance, wherein the interference warning equipotential surface represents a set of spatial positions of birds at different starting altitudes when they first enter the warning distance on their minimum energy consumption flight trajectory;

[0024] Step S203, based on the bridge interference warning equipotential surface, calculating the bird interference area and the probability of the flock being disturbed, wherein the interference area is the spatial range within the interference warning equipotential surface in the minimum energy consumption flight trajectory, and the probability of the flock being disturbed is calculated based on the interference area and the bird flock density;

[0025] Step S204 : Based on the disturbed area and the group disturbance probability, a comprehensive cost function is constructed in combination with the bridge full closure engineering cost and the ecological loss cost, and the target bridge full closure length is determined by optimizing the comprehensive cost function.

[0026] In an exemplary embodiment of the present invention, a water-related bridge construction project is used as an application scenario. The server, acting as the execution entity, integrates bird flight characteristics, bridge structural parameters, and cost data to quantitatively optimize the length of the bird protection enclosure. The bridge is a transportation project spanning open water, with a total length of 1,500 meters and a total deck width of 30 meters. The coordinates of the bridge's highest point are (750 meters, 30 meters) (with the bridge's nearshore starting point as the origin, the horizontal extension direction being the s-axis, and the vertical height direction being the h-axis). The bridge area is a key migration corridor for a migratory bird species (hereinafter referred to as the "target bird"). The bird's average annual migration period is spring and autumn. Its typical flight altitude ranges from 10 to 100 meters, with a wingspan of approximately 1.2 meters. The population density decreases with increasing altitude. The server's core task is to determine the optimal total enclosure length that balances engineering investment and ecological protection by constructing a bird flight energy consumption model, defining the interference range, and calculating the ecological impact and comprehensive cost.

[0027] The server first initiates the process of building a bird flight trajectory dynamics and energy consumption model. It receives the target bird's physiological parameters, environmental parameters, and flight constraints through an interface. Physiological parameters include a weight of 1.5 kg, a wing area of ​​0.5 square meters, an aspect ratio of 7.5, an elliptic efficiency factor of 0.85, a zero-lift drag coefficient of 0.015, and a constant propulsion power of 15 watts during the dive phase, as determined through animal behavioral experiments. Environmental parameters include an air density of 1.225 kg / m³ and a gravitational acceleration of 9.8 m / s². Flight constraints include an endpoint altitude of 0 meters (the target bird must descend to the water or ground), a target horizontal flight distance of 500 meters (assuming the bird takes off from a nearshore habitat and needs to fly 500 meters to a feeding area on the other side), and a starting altitude range of 10 to 100 meters (19 sample points are taken at 5-meter intervals to cover the bird's primary flight altitude range). Based on this data, the server establishes a system of coupled differential equations with speed, path angle, altitude, and horizontal distance as state variables, describing the time evolution of these four variables. The rate of change of speed is affected by the propulsion power, drag, and gravity components. The rate of change of path angle is determined by the balance between lift and gravity components. The rates of change of altitude and horizontal distance are represented by the vertical and horizontal components of speed, respectively. The calculation of lift and drag requires a combination of wing area, air density, lift coefficient, drag coefficient, and induced drag factor (derived from aspect ratio and elliptic efficiency factor). The server divides the bird's flight process into a dive phase (requiring continuous propulsion power output) and a glide phase (in which power output is stopped and the bird glides using gravitational potential energy). An energy optimization function is constructed with the goal of minimizing the time integral of propulsion power consumption. The Runge-Kutta numerical method is used to iteratively solve the dynamic equations for different starting altitudes. The server sets the initial path angle, initial velocity, and the power switch time (the boundary between the dive and glide phases) and substitutes them into the equations to calculate the time evolution of altitude and horizontal distance. If the final altitude or horizontal distance constraints are not met (for an altitude of 0 meters and a horizontal distance of 500 meters), the power switch time and lift coefficient trajectory are adjusted and recalculated until the conditions are met. Ultimately, the server outputs 19 minimum energy consumption flight trajectories for different starting altitudes. Each trajectory is stored as a height-to-horizontal distance curve (hs curve). For example, at a starting altitude of 30 meters, the trajectory starts at (0 meters, 30 meters), dives at an 8° angle for 3.2 seconds, then switches to the glide phase, and finally descends to 0 meters at a horizontal distance of 500 meters, with a total energy consumption of 48 joules.

[0028] After calculating the minimum energy consumption flight trajectory, the server constructs a bridge interference warning equipotential surface based on the preset bird warning distance. Based on ecological survey data, the target bird's warning distance for large structures is set at 50 meters. This means that when the straight-line distance between a bird and the highest point of a bridge is ≤50 meters, it will deviate from the minimum energy consumption trajectory due to perceived threat. To extend the two-dimensional trajectory to three dimensions (accounting for birds potentially flying across the bridge from different lateral positions), the server, leveraging the bird's omnidirectional vision, rotates each two-dimensional hs curve about the bridge's central axis (s-axis) to generate a three-dimensional trajectory arc surface centered on the s-axis. Any point on the arc surface represents a possible flight path for a bird at a specific lateral position. The server then constructs a cylindrical warning surface with the bridge's highest point (750 meters, 30 meters) as the center and the warning distance of 50 meters as the radius. This surface is projected onto the sh plane as a circular curve, appearing in space as a cylindrical surface extending along the central axis, thus defining the spatial extent of the interference. For each three-dimensional trajectory arc surface with a starting height, the server solves the horizontal coordinates of the first time all trajectories on the arc surface touch the cylindrical warning surface through spatial distance calculation: the distance from the highest point of the bridge to any trajectory on the arc surface is calculated point by point, and the horizontal distance s value when the distance is equal to 50 meters (the position of the first entry into the warning range) is recorded, and the s value of all lateral position trajectories at the same starting height is averaged as the interference boundary position corresponding to the height. For example, when the starting height is 30 meters, the first contact position of different lateral trajectories on the three-dimensional arc surface fluctuates between 685 meters and 695 meters, and the server takes the average value of 690 meters as the interference boundary position at this height. After repeated calculations for 19 starting height sample points, the server obtains the functional relationship between the interference boundary position and the starting height through polynomial fitting (such as =-0.8h+713), this function curve is the bridge interference warning equipotential surface, which represents the spatial location set of birds at different starting heights that are first disturbed on the trajectory with the lowest energy consumption.

[0029] Based on the interference warning equipotential surface, the server further calculates the disturbed area of ​​birds and the probability of disturbance of the flock. The disturbed area is defined as the spatial range inside the equipotential surface, that is, for any starting height h, the horizontal distance s ≤ the interference boundary position The calculation of the interfered area requires the two-dimensional integration of height and horizontal distance: the server performs Integrate to get the interference area in the hs plane, then multiply it by the total width of the bridge deck (30 meters) to take into account the lateral range, and finally get the interference volume in three-dimensional space (referred to as "interference area" in the technical disclosure document). =-0.8h+713 is integrated over the interval of 10 meters to 100 meters, resulting in an hs plane interference area of ​​60,174 square meters. Multiplied by the total width of the bridge deck of 30 meters, the disturbed area is 1,805,220 cubic meters. The calculation of the probability of group disturbance is based on the bird population density distribution. The ecological data received by the server shows that the density of target birds decreases with increasing height. The density function is: =0.02-0.0002h (unit: birds / cubic meter). The server obtains the proportion of disturbed birds by integrating the density function in the disturbed area: and The product integral of the two is the probability of group disturbance. For example, the calculated probability of group disturbance is 42.3%, which means that about 42.3% of migrating birds will enter the bridge interference area.

[0030] Finally, the server constructs a comprehensive cost function based on the disturbed area and the probability of group disturbance and optimizes the target full enclosure length. The enclosure project parameters are obtained from the engineering database: the unit area enclosure structure (such as a bird net) costs 200 yuan / square meter, and the total width of the bridge deck is 30 meters. The engineering cost function increases linearly with the enclosure length. The calculation formula is the unit area cost multiplied by the lateral area of ​​the enclosure structure (the circumference of a semicircle with the total width of the bridge deck as the diameter multiplied by the enclosure length). For example, the enclosure length When the project cost =200×π×(30 / 2)²× , which is simplified to 141372× (Yuan). The ecological loss cost function is constructed based on the residual interference area and the probability of group disturbance. The residual interference area refers to the disturbed area in the area not covered by the closed project. The server assumes that the closed project can completely block the interference within the coverage area. When the closed length is When , the residual disturbance area is the total disturbed area minus the disturbed area covered by the closed section. The ecological loss cost is equal to the product of the ecological value conversion coefficient of a single bird (set to 1000 yuan / bird), the bird population density, and the residual disturbance area. The comprehensive cost function is the sum of the engineering cost and the ecological loss cost, that is, The server can be used to determine the length of the enclosed (0m to 500m, 10m interval) calculation , find the smallest The cost-benefit slope (the reduction in ecological loss costs associated with a unit increase in project cost) is the key factor in determining the overall cost. For example, a calculated closure length of 280 meters results in a project cost of 39,584,160 yuan and an ecological loss cost of 15,200,000 yuan, which is the lowest overall cost. Therefore, the target full closure length is set at 280 meters.

[0031] Through the above process, the server realizes the quantitative calculation of the entire process from bird flight trajectory optimization to closure engineering decision-making, providing a scientific and economic optimization plan for the bird protection project of the wading bridge.

[0032] In an embodiment of the present invention, the construction of a bird flight trajectory dynamics and energy consumption model and the solution to obtain the bird's minimum energy consumption flight trajectory at different starting altitudes include:

[0033] Based on coupled differential equations of speed, path angle, altitude and horizontal distance, a dynamic equation for the bird's glide-dive phase is established to characterize the time evolution of the speed, path angle, altitude and horizontal distance;

[0034] With the goal of minimizing the time integral of propulsion power consumption, a piecewise power function is used to solve the bird's gliding-diving phase dynamics equation, and the flight trajectory with the lowest energy consumption at different starting altitudes is obtained.

[0035] The dynamic equation of the bird's gliding-diving stage is:

[0036]

[0037] in, is the flight speed, γ is the flight path inclination, h is the flight altitude, s is the horizontal flight distance, P is the flight power, m is the bird mass, g is the acceleration of gravity, is the lift coefficient, is the zero lift drag coefficient, ρ is the air density, S is the bird's wing area, For lift, 、 For resistance, 、 is the induced drag factor, , e is the ellipse efficiency factor, and AR is the aspect ratio.

[0038] In an embodiment of the present invention, illustratively, when executing the step of constructing a bird flight trajectory dynamics and energy consumption model, the server first receives the physiological parameters and environmental parameters of the target bird through a data interface, including basic data such as the bird's weight of 1.5 kg, wing area of ​​0.5 square meters, aspect ratio of 7.5, elliptical efficiency factor of 0.85, zero lift drag coefficient of 0.015, air density of 1.225 kg / m3, and gravitational acceleration of 9.8 m / s². Based on these parameters, the server constructs a dynamic model, which uses speed, path angle, altitude, and horizontal distance as core state variables and describes the evolution of the four over time through coupled differential equations: the rate of change of speed is determined by the propulsion power, aerodynamic drag, and gravity components; the rate of change of path angle is affected by the balance between lift and gravity components; and the rates of change of altitude and horizontal distance are calculated by the vertical and horizontal components of the speed, respectively.

[0039] During the model solution phase, the server divides the bird's flight process into a gliding phase and a diving phase. The gliding phase has zero propulsion power, while the diving phase maintains a constant propulsion power of 15 watts. With the optimization goal of minimizing the time integral of propulsion power consumption, the server numerically solves the dynamic equations using a piecewise power function. During the solution process, the server must meet the boundary conditions of an endpoint altitude of 0 meters (the bird must descend to the ground or water surface) and a horizontal flight distance of 500 meters (the length of the pre-set migration path). By iteratively adjusting the lift coefficient trajectory and the power mode switching time (i.e., the transition time between the gliding phase and the diving phase), the server calculates the total energy consumption at different starting altitudes (10 to 100 meters, with intervals of 5 meters), and ultimately selects the flight trajectory with the lowest energy consumption for each starting altitude. For example, for the working condition with a starting altitude of 30 meters, the server uses the Runge-Kutta numerical algorithm to solve the differential equations and obtains the optimal trajectory: initially diving at an 8° path angle for 3.2 seconds and then switching to gliding mode. The total energy consumption throughout the process is 48 joules, and the altitude just drops to 0 meters at a horizontal distance of 500 meters. This trajectory is stored in the database as the solution with the lowest energy consumption at this altitude.

[0040] In a possible implementation, the goal is to minimize the time integral of propulsion power consumption, and a piecewise power function is used to solve the bird's gliding-diving phase dynamic equation to obtain the flight trajectory with the lowest energy consumption at different starting altitudes. This can be implemented through the following examples.

[0041] The objective function is constructed with the goal of minimizing the time integral of propulsion power consumption:

[0042]

[0043] ;

[0044] Based on the objective function, the dynamic equation of the bird's glide-dive phase is solved by using the lift coefficient trajectory and the power mode switching time, the energy consumption index at different starting altitudes is calculated, and the flight trajectory with the lowest energy consumption is determined;

[0045] The following boundary conditions are met during the solution process: ;

[0046] The energy consumption indicators are: ;

[0047] in, is the total power consumption, T is the total flight time, d is the total width of the bridge deck, is the piecewise power function, is the power mode switching moment, t is the flight continuous time variable, is the end height, is the end distance, is the energy consumption per unit mile.

[0048] In an embodiment of the present invention, for example, when solving a flight trajectory with the lowest energy consumption by minimizing the time integral of propulsion power consumption, the server first receives the power parameters of the target bird: a constant propulsion power of 15 watts during the dive phase and zero propulsion power (no power) during the glide phase. The objective function constructed by the server is centered around minimizing total energy consumption (the integral of propulsion power over time), where total energy consumption is contributed only by the dive phase (no power consumption during the glide phase).

[0049] For each starting altitude (10 to 100 meters, with intervals of 5 meters), the server solves the dynamic equations by iteratively optimizing the lift coefficient trajectory and the power mode switching moment (the transition time between the dive and gliding phases). During the solution process, the boundary conditions are strictly met: the end altitude h(T) = 0 (the bird must descend to the ground or water surface), and the horizontal flight distance s(T) = 500 meters (the preset migration path length). For example, the server calculates the working condition with a starting altitude of 30 meters: the initial switching time is set to 3 seconds. After substituting it into the dynamic equation, it is found that the end altitude is 5 meters (not reaching 0 meters). Therefore, the lift coefficient is adjusted (from 0.8 to 0.85) and the dive time is extended to 3.2 seconds. The recalculation results in an end altitude of 0 meters and a horizontal distance of 500 meters, which meet the boundary conditions.

[0050] The server further calculates the trajectory's energy consumption per mile, which is the ratio of total energy consumption (15 watts x 3.2 seconds = 48 joules) to the product of the bird's weight, gravitational acceleration, and horizontal distance traveled (48 / (1.5 x 9.8 x 500) = 0.0065). This process is repeated for all starting altitudes. The server selects the trajectory with the lowest energy consumption per mile at each altitude and stores it as the lowest energy consumption trajectory for that altitude.

[0051] In the embodiment of the present invention, the construction of the bridge interference warning equipotential surface based on the minimum energy consumption flight trajectory and the preset bird warning distance can be implemented through the following examples.

[0052] Based on the preset bird's field of vision, the two-dimensional minimum energy consumption flight trajectory at each starting height is rotated along the central axis of the bridge to generate a three-dimensional trajectory arc surface; the coordinates of the highest point of the bridge and the preset warning radius are set to construct a cylindrical warning surface with the highest point of the bridge as the center and the warning radius as the radius;

[0053] For the three-dimensional trajectory arc surface at each starting height, solving the horizontal coordinate set when all trajectories on the corresponding arc surface first touch the cylindrical warning surface;

[0054] Data fitting is performed on all the horizontal coordinate sets and their corresponding starting heights to form bridge interference warning equipotential surfaces.

[0055] In an embodiment of the present invention, illustratively, when constructing the bridge interference warning equipotential surface, the server first receives preset parameters: the bird's field of view is processed as 360° in all directions, the preset warning distance is 50 meters, and the coordinates of the highest point of the bridge are (750 meters, 30 meters) (with the bridge's nearshore starting point as the origin, the horizontal direction as the s-axis, and the height direction as the h-axis). For the 19 two-dimensional minimum energy consumption flight trajectories (hs curves) corresponding to starting heights (10 meters to 100 meters, with intervals of 5 meters) obtained in step 1, the server rotates each curve along the bridge's central axis (s-axis), uniformly generating 100 horizontally offset trajectories, forming a three-dimensional trajectory arc surface centered on the s-axis (covering the bird's possible lateral flight range).

[0056] The server then constructs a cylindrical warning surface (a cylindrical area extending along the central axis in space) with the highest point of the bridge as the center and a radius of 50 meters. For each three-dimensional trajectory arc at a starting height, the server traverses each trajectory on the arc, calculating the spatial distance between each point on the trajectory and the highest point of the bridge, and recording the horizontal coordinate s value when the distance first reaches 50 meters (the critical point at which the bird enters the warning range). For example, on a three-dimensional arc with a starting height of 30 meters, the horizontal coordinates of 100 horizontal trajectories that first reach the warning surface range from 685 to 695 meters. The server takes the average value of 690 meters as the interference boundary at that height.

[0057] After completing the calculation of all starting heights, the server imports 19 sets of data (starting height, interference boundary position) into the curve fitting module, and uses the least squares method to perform polynomial fitting to obtain the curve relationship between the horizontal coordinate and the starting height (such as low starting height corresponds to a larger horizontal coordinate, and high starting height corresponds to a smaller horizontal coordinate). This curve is the bridge interference warning equipotential surface, which represents the set of spatial locations where birds at different heights are first disturbed.

[0058] In an embodiment of the present invention, the cylindrical warning surface is defined by the formula: Calculated;

[0059] in, It is a cylindrical warning surface. is the horizontal distance outward from the shore datum, is the flight altitude, is the coordinate of the highest point of the bridge, The preset warning radius;

[0060] The bridge interference warning equipotential surface is obtained by the formula:

[0061] Calculated;

[0062] in, For bridge interference warning equipotential surface, is the starting height, is the interference boundary position, is the minimum starting height, is the maximum starting height.

[0063] In the embodiment of the present invention, for example, when constructing the cylindrical warning surface, the server receives the bridge structure parameters: the coordinates of the highest point of the bridge are (750 meters, 30 meters) ( =750 meters is the horizontal distance, =30 meters for height), preset bird warning radius =50 meters. Based on the above parameters, the server generates a cylindrical warning surface in the spatial coordinate system. This cylindrical area, with the bridge's central axis as the axis and (750 meters, 30 meters) as the reference point, is 50 meters in radius. Any point (s, h) is included in the warning surface if the spatial distance from the reference point is 50 meters.

[0064] The server then processes the construction of the bridge interference warning equipotential surface: receiving the starting height range parameters ( =10 meters, = 100 meters), and the 19 sets of interference boundary position data calculated in step 4 (each starting height h0 corresponds to a horizontal coordinate ). For example, when h0=30 meters =690 m, h0=50 m = 670 meters. The server organizes this data into sets , where each element is (h0, ), and the value range of h0 is limited to [10 meters, 100 meters]. This set is the bridge interference warning equipotential surface, which completely covers the spatial location boundaries of birds first entering the warning range at different starting heights.

[0065] In the embodiment of the present invention, the calculation of the bird interference area and the probability of group disturbance based on the bridge interference warning equipotential surface can be implemented through the following examples.

[0066] The area where birds are disturbed is given by the formula: Calculated;

[0067] in, is the area of ​​bird disturbance, is the interference area, , is the total width of the bridge deck, The take-off altitude is The interference intercept when ;

[0068] The probability of the group being disturbed is given by the formula:

[0069] Calculated;

[0070] in, is the probability of group disturbance, is the density of bird flocks per unit area.

[0071] In the embodiment of the present invention, for example, when calculating the disturbed area of ​​birds and the probability of disturbance of a group, the server first receives the basic parameters: the total width of the bridge deck is 30 meters, the starting height range is [10 meters, 100 meters], and the interference boundary position function obtained in step 4 (For example, lower altitudes correspond to larger s values, and higher altitudes correspond to smaller s values).

[0072] For interference area calculation, the server defines the interference area For all starting heights h∈[10m, 100m], the horizontal distance s≤ The server is within the height range. Perform the integration operation to obtain the interference area in the hs plane. Integrating from 10 meters to 100 meters, we get a plane area of ​​60,174 square meters. Multiplying this area by the total width of the bridge deck of 30 meters, we get a disturbed area of ​​1,805,220 cubic meters in three-dimensional space.

[0073] To calculate the probability of a flock being disturbed, the server receives bird density data: the bird density in the area decreases with increasing altitude, and the density function shows that the density is higher at low altitudes and lower at high altitudes. The server calculates the density function and the interference boundary position within the starting altitude range [10 meters, 100 meters]. The product of the two is integrated, and the result is the probability of disturbance of the population. For example, the calculated disturbance probability is 42.3%, which means that approximately 42.3% of migrating birds will enter the bridge interference area.

[0074] In an embodiment of the present invention, based on the disturbed area and the probability of group disturbance, a comprehensive cost function is constructed in combination with the cost of full closure of the bridge project and the ecological loss cost. The target full closure length of the bridge is determined by optimizing the comprehensive cost function, which can be implemented through the following examples.

[0075] Construct the engineering cost function between the fully enclosed length of the bridge and the engineering cost: ;in, is the cost of the enclosed structure per unit area, is the total width of the bridge deck, Fully enclosed length.

[0076] According to the disturbed area and the probability of group disturbance, an ecological loss cost function is constructed between the full closure length of the bridge and the ecological loss cost: ;in, is the ecological value conversion coefficient of a single bird, The density per unit area of ​​a flock of birds in flight, is the residual interference area;

[0077] Construct a comprehensive cost function: ;

[0078] By formula:

[0079] , optimizing the comprehensive cost function to determine the target fully enclosed length of the bridge; wherein, is the cost-effectiveness slope, is the rate of decrease of ecological loss caused by changes in closure length, It is the growth rate of construction cost caused by changes in closed length.

[0080] In an embodiment of the present invention, for example, when determining the target fully enclosed length of the bridge, the server first receives engineering and ecological parameters: the unit area enclosed structure cost is 200 yuan / square meter, the total width of the bridge deck is 30 meters, the ecological value conversion coefficient of a single bird is 1,000 yuan / bird, the unit area density data of the bird flock, and the disturbed area of ​​1,805,220 cubic meters calculated in step 6.

[0081] Server construction project cost function: The enclosure is a cylindrical structure, and its lateral area is proportional to its length. The construction cost increases linearly with the length of the enclosure. For example, when the enclosure is 100 meters long, the construction cost is approximately 14.1372 million yuan; when the enclosure is 300 meters long, the cost increases to 42.4116 million yuan.

[0082] Next, we constructed an ecological loss cost function: the residual disturbance area refers to the area of ​​disturbance left untouched by the enclosure. The longer the enclosure length, the smaller the residual disturbance area. The ecological loss cost is calculated as the product of the value of a single bird, the flock density, and the residual disturbance area. For example, when the enclosure length is 0 meters, the residual disturbance area is 1,805,220 cubic meters, resulting in an ecological loss cost of approximately 4.23 million yuan. When the enclosure length is 200 meters, the residual disturbance area drops to 800,000 cubic meters, and the ecological loss cost drops to 1.88 million yuan.

[0083] The comprehensive cost function is the sum of engineering costs and ecological loss costs. The server calculates the comprehensive cost for each enclosure length (0 to 500 meters, in 10-meter intervals), focusing on the cost-benefit slope—the reduction in ecological loss costs associated with a unit increase in engineering cost. When the enclosure length increases from 270 to 280 meters, engineering costs increase by 1.4137 million yuan and ecological loss costs decrease by 350,000 yuan, resulting in a slope of 0.25 (decline in ecological loss / increase in engineering cost), the maximum value across all intervals. At this point, the comprehensive cost is lowest (39.5842 million yuan in engineering costs + 1.52 million yuan in ecological loss costs = 41.1042 million yuan), and the server determines the target full enclosure length as 280 meters.

[0084] In the embodiments of the present invention, the following implementation modes are also provided.

[0085] Determine the closure start and end positions on both sides of the bridge based on the target fully enclosed length of the bridge, so as to define the bridge length range required to be covered by the fully enclosed project;

[0086] Based on the bridge interference warning equipotential surface, determining the longitudinal boundary of the spatial range where birds are susceptible to bridge interference in the direction of bridge extension; the longitudinal boundary includes a minimum impact position close to one end of the bridge and a maximum impact position far from one end of the bridge;

[0087] Between the minimum impact position and the maximum impact position, a continuous distance segment is measured along the extension direction of the bridge, the distance of which is equal to the target full closure length;

[0088] The end point of the measured continuous distance segment close to one end of the bridge along the extension direction of the bridge is determined as the closing starting position, and the end point away from the one end of the bridge is determined as the closing ending position;

[0089] The starting position and the ending position form corresponding boundary points on both sides of the bridge in the horizontal direction respectively; the bridge length range required to be covered by the fully enclosed project is the continuous section of the bridge structure between the starting position and the ending position along the extension direction of the bridge.

[0090] In this embodiment of the present invention, after determining that the target fully enclosed length is 280 meters, the server further defines the spatial extent of the enclosed project. The server uses the bridge interference warning equipotential surface data (function relationship s = -0.8h + 713, h ∈ [10 meters, 100 meters]) to calculate the longitudinal boundary where birds are susceptible to interference.

[0091] Minimum impact location: When the starting height h is maximum (100 meters), the interference boundary location s is minimum. Substituting this into the formula, we get s_min = -0.8 × 100 + 713 = 633 meters (from the nearshore starting point).

[0092] Maximum impact location: When the starting height h is minimum (10 meters), the interference boundary location s is maximum. Substituting this into the formula, we obtain s_max = -0.8 × 10 + 713 = 705 meters (from the nearshore starting point). Therefore, the longitudinal range of bird disturbance is 633 to 705 meters (along the bridge extension).

[0093] The server intercepted a continuous segment from 633 to 705 meters longitudinally, equal to the target closure length (280 meters). Because the original interference range was only 72 meters (705-633), which did not meet the 280-meter closure requirement, the server automatically expanded the range to the nearshore side of the bridge to cover the entire migration path.

[0094] Extending from the minimum impact position (633 meters) to the nearshore side, the closure starting position is taken as 450 meters and the ending position is 450+280=730 meters (covering the 633-705 meter core interference zone and the buffer zones on both sides).

[0095] The server maps the starting position (450 meters) and the ending position (730 meters) to the horizontal sides of the bridge (the total width of the bridge deck is 30 meters), forming the four boundary points of the enclosed area:

[0096] Starting point on the nearshore side: (450m, 0m), (450m, 30m) (the s-axis is the extension direction of the bridge, and the horizontal coordinate range is 0-30m);

[0097] The far shore end points are (730m, 0m), (730m, 30m). Ultimately, the full closure project covers the continuous section of the bridge from 450m to 730m, covering the full lateral width of 30m.

[0098] In the embodiments of the present invention, the following implementation methods are also provided:

[0099] Based on the historical dominant wind direction and wind speed probability distribution data obtained in the area where the bridge is located;

[0100] Calculate the wind speed and direction corrections at the minimum impact position and the maximum impact position respectively according to the deviation law of the bird flight trajectory in the tailwind state;

[0101] superimposing the correction amount onto the original longitudinal boundary coordinates of the longitudinal boundary to obtain corrected longitudinal boundary coordinates;

[0102] Based on the corrected longitudinal boundary coordinates, the minimum influence position and the maximum influence position are re-determined.

[0103] In an embodiment of the present invention, illustratively, the server introduces meteorological factors to optimize the closed boundary to ensure the protection effect in a complex environment.

[0104] The server retrieves the meteorological data of the bridge area for the past 10 years through the interface:

[0105] Prevailing wind direction: southeast wind (frequency 65%);

[0106] Wind speed probability distribution: 5-15m / s (average 8m / s, accounting for 70%).

[0107] According to the bird flight dynamics model, a tailwind (southeast wind) will cause the bird's trajectory to shift northwest (i.e., the s value in the direction of the bridge extension decreases). The server fits the offset formula using wind tunnel test data:

[0108] Δs = -0.5 × v (v is the wind speed in m / s; the negative sign indicates a shift toward shore). Taking an average wind speed of 8 m / s, we get Δs = -0.5 × 8 = -4 meters (meaning the trajectory is shifted 4 meters toward shore).

[0109] The server adds the correction amount to the original longitudinal boundary:

[0110] The minimum impact position after correction is: 633 meters + (-4 meters) = 629 meters;

[0111] The maximum impact position after correction is: 705 meters + (-4 meters) = 701 meters.

[0112] Based on the corrected boundary (629m to 701m), the server re-intercepted the 280m closed segment:

[0113] The closure start position was adjusted to 446 meters (450 meters - 4 meters), and the end position was adjusted to 726 meters (730 meters - 4 meters) to ensure that the bird tracks were still fully covered after the offset.

[0114] Final output: The full closure project of the bridge extends from 446 meters to 726 meters (along the extension direction), with a horizontal coverage of 0-30 meters in width, taking into account both project costs and ecological protection needs under meteorological interference.

[0115] In order to more clearly describe the solution provided by the embodiment of the present invention, a more complete implementation method is provided below.

[0116] 1. Construct the bird flight trajectory dynamics module and energy consumption module. Based on this, simulate the bird behavior. First, use the point mass center four-state equation (speed , path inclination , vertical displacement , horizontal displacement ) describes the kinematics of the glide-dive phase; then, lift and drag are split into induced drag and zero-lift drag, and a piecewise power function is introduced to distinguish between the two working conditions of constant propulsion in the dive and no propulsion in the glide; finally, the power-time integral minimization is used as the control objective to solve the problem of different takeoff heights. The optimal descent trajectory under the condition of Quantify the "efficiency surface". This module provides a unified dynamics and energy consumption coordinate system for all subsequent quantitative evaluations.

[0117] 2. Construct the interference warning equipotential surface module for wading bridges. Couple the spatial vision with the three-dimensional geometry to extract the interference equipotential surface. Combined with the bird's vision, the two-dimensional optimal trajectory is rotated to generate a three-dimensional "trajectory arc surface"; the highest point of the bridge is the As the center of the circle and the warning radius as the radius, a cylindrical warning surface is constructed. ; For each takeoff altitude , find the horizontal coordinate of the first time the trajectory touches the warning surface , thus splicing out the interference equipotential surface This surface describes the location boundary where birds at different altitudes first enter the warning distance during flight.

[0118] 3. Construct a module for calculating the area and probability of bird disturbance. Use the integral geometry method to calculate the disturbance area and map it to the probability of group disturbance. The area superimposed with the arc of the bird's flight path is identified as the area where the wading bridge interferes with the birds. Calculate the interference area ; then multiply by the bird flock surface density , or introduce a height distribution function , we can get the probability of group disturbance , which assesses the ecological loss risk of birds and serves as a loss calculation condition in ecological design.

[0119] 4. Optimize the bridge closure length strategy. Couple the ecological loss with the construction cost to build a comprehensive cost-ecological loss benefit analysis model for bridge closure. Assume the total width of the bridge deck is , the fully enclosed length from the shore is , the unit cost of the structure is , the corresponding project cost is The enclosing measures reduce the interference area to ; Multiply by the ecological value conversion coefficient and bird density , and obtain ecological losses The sum of the two forms the comprehensive cost function By calculating the differential ratio, the marginal ecological benefit efficiency is defined , and find its maximum point , thereby identifying the optimal closure length for "maximum ecological benefit per unit investment." This analysis supports engineering decision-making. It provides intuitive comparison and sensitivity diagnosis of closure strategies under different bridge types, bird population densities, or ecological value scenarios, ensuring that the selected closure length meets ecological protection thresholds while balancing project cost control and technical feasibility.

[0120] Implementation process:

[0121] S1. Bird flight trajectory dynamics module and energy consumption module

[0122] Bird Flight Trajectory Dynamics Module: This model uses the dynamic equations of the point center of mass to describe the dynamic evolution of a bird's velocity, path angle, altitude, and horizontal distance during the glide-dive phase. The system consists of four coupled differential equations, describing the time evolution of flight velocity, inclination angle, and vertical and horizontal displacement. Lift and drag depend on velocity, lift coefficient, and air density, with drag comprising induced drag and zero-lift drag. Power is modeled using a piecewise function, representing two operating conditions: constant propulsion during the dive phase and no propulsion required during the glide phase. This dynamic system provides the foundation for subsequent energy optimization and interference modeling.

[0123] Evolution of bird gliding-diving flight trajectories:

[0124]

[0125] Among them, the lift and drag models are:

[0126]

[0127] The power is set as a piecewise function:

[0128]

[0129] The switching point between the dive phase and the glide phase Introduced as an optimization variable.

[0130] Where: V is the flight speed (m / s); γ is the flight path inclination (rad); h is the flight altitude (m); s is the horizontal flight distance (m); P is the flight power (W); m is the mass of the bird (kg); g is the acceleration due to gravity (9.81m / s²); is the lift coefficient (dimensionless); is the zero lift drag coefficient; ρ is the air density (kg / m³); S is the wing area (m²); e and AR are the elliptical efficiency factor and aspect ratio.

[0131] Bird space flight trajectory energy consumption optimization module: The descent height of birds varies in different scenarios. This part aims to solve the problem of birds flying from any height. The optimal energy consumption curve for reaching the ground is obtained by making the propulsion power consumption The time integral of the equation is minimized to simulate the actual descent process of different types of birds from different heights. The control variables are the lift coefficient trajectory and the power mode switching time to ensure the convergence and feasibility of the solution. The final energy consumption index Expressed as the energy ratio of unit gravitational potential energy multiplied by horizontal distance, it quantifies the "efficiency" of bird migration paths. Because birds' descents follow the most efficient descent path, quantifying the efficiency of their migration paths can express their descent trajectories. Birds have a visual range of 300°, which allows them to convert flight paths into arcs.

[0132] For a given starting height Horizontal distance , construct the minimum energy consumption trajectory optimization problem:

[0133]

[0134] Satisfy the state equation and boundary conditions:

[0135]

[0136] The final calculation of energy consumption per unit horizontal mileage is:

[0137]

[0138] in: is the total energy consumption (J); is the energy consumption per unit mileage (J / N); is the total flight time (s); For control quantity, including and switching time .

[0139] S2. Water bridge warning equipotential surface module

[0140] Interference equipotential lines are used to mark the boundaries of areas that may be interfered with by bridge structures during flight. By setting a "warning surface" height and back-substituting the trajectory equation to solve the corresponding horizontal distance, the warning surface contact position at each starting height can be obtained. These points constitute the interference equipotential lines , providing spatial boundaries for subsequent regional integration and probability evaluation.

[0141] Assume the highest point of the bridge is , plus the bird warning height of 12 meters, the warning surface is defined as the three-dimensional equidistant surface where the bird first reaches 12 meters from the highest point of the bridge during its descent. Because the highest point of the bridge is horizontally located within the same cross section, this three-dimensional equidistant surface is the outer shell of a cylinder:

[0142]

[0143] Where: horizontal axis is the horizontal distance from the shore datum; the vertical coordinate is the flight altitude; It is the horizontal position of the highest point of the bridge within the same section; is the height of the highest point of the bridge; This is a fixed warning distance. is the center and radius The arc represents the set of positions at the first warning distance from the highest point of the bridge.

[0144] For each starting height , solve the horizontal distance of the first time to reach the warning height in the flight trajectory, that is, find the minimum time make:

[0145]

[0146] The corresponding horizontal coordinates at this time , construct interference equipotential lines:

[0147]

[0148] in: is the height of the interference surface (m); is the interference boundary position at the corresponding height (m); is the set of interference equipotential lines.

[0149] S3. Bird disturbance area and probability calculation module

[0150] Calculating the interference zone area: After constructing the interference boundary, the area of ​​the interference zone on the efficiency surface must be integrated to determine its area. The boundaries of this zone are determined by the interference equipotential lines, and the integration range is limited to the vertical height and the corresponding horizontal intercept. Integration methods can use the composite trapezoidal method, Gauss-Legendre integration, or triangulation to ensure numerical accuracy even with complex geometries. The area value reflects the spatial range of interference that birds may encounter on the flight efficiency surface.

[0151] The interference region is defined as:

[0152]

[0153] The regional area calculation formula is:

[0154]

[0155] in: is the interference area, i.e., the efficiency domain below the bridge projection; is the area of ​​the region (m²).

[0156] Disturbance probability: The disturbance probability is calculated by multiplying the area of ​​the disturbed area by the number of birds per unit area. This metric captures the potential level of ecological disturbance at the population level. If altitude density is considered, a weighted integral of the density function and the disturbance contours is necessary to make the probability assessment more realistic. This probability is an important quantitative risk metric that must be minimized in bridge design.

[0157] If the density of the flock is constant :

[0158]

[0159] If the density varies with height :

[0160]

[0161] in: is the probability of birds being disturbed; is the bird population density (birds / m²); is the interference horizontal intercept corresponding to each height.

[0162] S4. Optimization of bridge full closure length strategy

[0163] Completely close the bridge from the shore meters, forming a closed structure with a circular cross section. If the bridge deck width is , then the required enclosed area per linear meter is The total construction cost is shown in the following formula. On the other hand, the interference of bridge structure on bird flight can be explained by “interference intercept”. Description, while the closed length The increase in shifts the intercept to the left, thereby reducing the area where birds may cross the interference height region, recorded as The area is multiplied by the bird density per unit area. The ecological value conversion coefficient of each bird , which is the ecological and economic loss. The comprehensive cost function is obtained by adding up the two costs. This function can be used to draw a cost-benefit curve, revealing the Pareto relationship that the increase in closed length brings about "rapid decline in ecological losses and linear increase in engineering costs", which makes it easier for decision makers to choose the optimal length based on marginal benefits.

[0164] In order to find the most cost-effective bridge closure length, we need to pay attention to the rate of change of ecological benefits per unit investment. The following definition of closure length Cost-effectiveness slope , its physical meaning is: for every additional yuan of engineering investment, how much ecological loss can be reduced. Therefore, the larger the slope value, the higher the ecological protection benefit per unit closure cost. This formula can be obtained by deriving the ratio of the closure length to the rate of change of ecological loss and engineering cost, where the numerator is It is usually negative (because ecological loss decreases with increasing closure length), and the denominator is a constant positive value, so the overall slope is positive, and at the initial It is usually larger when smaller and then decreases.

[0165] In actual engineering, it can be drawn and The relationship curve of The maximum value corresponds to , which is the closed length with the "most significant marginal ecological benefit" and is the recommended value in policy or engineering design.

[0166] (1) Cost of fully enclosed project: ;

[0167] (2) Ecological and economic losses to birds: ;

[0168] (3) Comprehensive cost-benefit curve: ;

[0169] Among them, the interference area is within the full closed length of the bridge The remaining area under is: ;

[0170] (4) Solving the marginal efficiency of bridge closure measures:

[0171] .

[0172] The parameter descriptions of the above formulas can be found in Table 1.

[0173] Table 1

[0174]

[0175] Please refer to Figure 2 , Figure 2An embodiment of the present invention provides a closed engineering optimization device 110 for bird protection decision-making on wading bridges, including:

[0176] Acquisition module 1101 is used to construct a bird flight trajectory dynamics and energy consumption model, and solve to obtain the minimum energy consumption flight trajectory of birds at different starting altitudes; based on the minimum energy consumption flight trajectory and a preset bird warning distance, construct a bridge interference warning equipotential surface, wherein the interference warning equipotential surface represents the set of spatial positions of birds at different starting altitudes when they first enter the warning distance on their minimum energy consumption flight trajectory; based on the bridge interference warning equipotential surface, calculate the bird interference area and the probability of group interference, wherein the interference area is the spatial range within the interference warning equipotential surface in the minimum energy consumption flight trajectory, and the probability of group interference is calculated based on the interference area and the bird flock density;

[0177] In the optimization module 1102 , the user constructs a comprehensive cost function based on the disturbed area and the group disturbance probability, combined with the bridge full closure engineering cost and the ecological loss cost, and determines the target full closure length of the bridge by optimizing the comprehensive cost function.

[0178] It should be noted that the implementation principles of the aforementioned closed-project optimization device 110 for bird protection decisions on wading bridges can be referenced from the implementation principles of the aforementioned closed-project optimization method for bird protection decisions on wading bridges, and will not be elaborated upon here. It should be understood that the division of the various modules of the aforementioned device is merely a division of logical functions. In actual implementation, they can be fully or partially integrated into a single physical entity, or physically separated. Furthermore, these modules can be implemented entirely as software invoked by a processing element, or entirely as hardware. Alternatively, some modules can be implemented as software invoked by a processing element, while others can be implemented as hardware. For example, the closed-project optimization device 110 for bird protection decisions on wading bridges can be a separate processing element, or integrated into a chip of the aforementioned device. Furthermore, it can be stored in the form of program code in the memory of the aforementioned device, with a processing element of the aforementioned device invoking and executing the functions of the closed-project optimization device 110 for bird protection decisions on wading bridges. The implementation of the other modules is similar. Furthermore, these modules can be fully or partially integrated together, or implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. During implementation, each step of the above method or each module above may be completed by an integrated logic circuit of hardware in a processor element or by instructions in the form of software.

[0179] For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs). For another example, when a module is implemented by scheduling program code on a processing element, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0180] The embodiment of the present invention provides a computer device 100, which includes a processor and a non-volatile memory storing computer instructions. When the computer instructions are executed by the processor, the computer device 100 executes the aforementioned closed engineering optimization device 110 for bird protection decision-making of wading bridges. Figure 3 As shown, Figure 3 This is a block diagram of a computer device 100 according to an embodiment of the present invention. The computer device 100 includes a closed engineering optimization device 110 for bird protection decision-making on wading bridges, a memory 111 , a processor 112 , and a communication unit 113 .

[0181] In order to achieve data transmission or interaction, the memory 111, the processor 112 and the communication unit 113 are electrically connected to each other directly or indirectly. For example, the electrical connection between these components can be achieved through one or more communication buses or signal lines. The closed engineering optimization device 110 for bird protection decision-making on wading bridges includes at least one software function module that can be stored in the memory 111 in the form of software or firmware or solidified in the operating system (OS) of the computer device 100. The processor 112 is used to execute the closed engineering optimization device 110 for bird protection decision-making on wading bridges stored in the memory 111, such as the software function modules and computer programs included in the closed engineering optimization device 110 for bird protection decision-making on wading bridges.

[0182] An embodiment of the present invention provides a readable storage medium, which includes a computer program. When the computer program is running, it controls the computer device where the readable storage medium is located to execute the aforementioned closed engineering optimization device 110 for bird protection decision-making on wading bridges.

[0183] For illustrative purposes, the foregoing description has been made with reference to specific embodiments. However, the above illustrative discussion is not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed. Numerous modifications and variations are possible in light of the above teachings. These embodiments have been selected and described in order to best illustrate the principles of the present disclosure and its practical application, thereby enabling those skilled in the art to best utilize the present disclosure and to utilize various embodiments with various modifications as appropriate for the specific application contemplated.

Claims

1. A closed engineering optimization method for bird protection decision-making on wading bridges, characterized by: include: Construct a bird flight trajectory dynamics and energy consumption model, and solve the flight trajectory with the lowest energy consumption for birds at different starting altitudes; Based on the minimum energy consumption flight trajectory and the preset bird warning distance, constructing a bridge interference warning equipotential surface, wherein the interference warning equipotential surface represents the set of spatial positions of birds at different starting heights when they first enter the warning distance on their minimum energy consumption flight trajectory; Based on the bridge interference warning equipotential surface, calculating the disturbed area of ​​birds and the probability of a flock being disturbed, wherein the disturbed area is the spatial range within the interference warning equipotential surface in the flight trajectory with the lowest energy consumption, and the probability of a flock being disturbed is calculated based on the disturbed area and the density of the bird flock; Based on the disturbed area and the probability of group disturbance, combined with the cost of full-closure engineering of the bridge and the cost of ecological loss, a comprehensive cost function is constructed, and the target full-closure length of the bridge is determined by optimizing the comprehensive cost function.

2. The method according to claim 1, characterized in that The step of constructing a bridge interference warning equipotential surface based on the minimum energy consumption flight trajectory and the preset bird warning distance includes: Based on the preset bird's field of vision, the two-dimensional minimum energy consumption flight trajectory at each starting height is rotated along the central axis of the bridge to generate a three-dimensional trajectory arc surface; the coordinates of the highest point of the bridge and the preset warning radius are set to construct a cylindrical warning surface with the highest point of the bridge as the center and the warning radius as the radius; For the three-dimensional trajectory arc surface at each starting height, solving the horizontal coordinate set when all trajectories on the corresponding arc surface first touch the cylindrical warning surface; Data fitting is performed on all the horizontal coordinate sets and their corresponding starting heights to form bridge interference warning equipotential surfaces.

3. The method according to claim 2, characterized in that The cylindrical warning surface is defined by the formula: Calculated; in, It is a cylindrical warning surface. is the horizontal distance outward from the shore datum, is the flight altitude, is the coordinate of the highest point of the bridge, The preset warning radius; The bridge interference warning equipotential surface is obtained by the formula: Calculated; in, For bridge interference warning equipotential surface, is the starting height, is the interference boundary position, is the minimum starting height, is the maximum starting height.

4. The method according to claim 1, wherein The calculation of the bird interference area and the probability of bird group interference based on the bridge interference warning equipotential surface includes: The area where birds are disturbed is given by the formula: Calculated; in, is the area of ​​bird disturbance, is the interference area, , is the total width of the bridge deck, The take-off altitude is The interference intercept when ; The probability of the group being disturbed is given by the formula: Calculated; in, is the probability of group disturbance, is the density of bird flocks per unit area.

5. The method according to claim 1, wherein The method of constructing a comprehensive cost function based on the disturbed area and the probability of group disturbance, combined with the cost of full bridge closure engineering and the ecological loss cost, and determining the target full bridge closure length by optimizing the comprehensive cost function includes: Construct the engineering cost function between the fully enclosed length of the bridge and the engineering cost: ;in, is the cost of the enclosed structure per unit area, is the total width of the bridge deck, It is the fully enclosed length; According to the disturbed area and the probability of group disturbance, an ecological loss cost function is constructed between the full closure length of the bridge and the ecological loss cost: ;in, is the ecological value conversion coefficient of a single bird, The density per unit area of ​​a flock of birds in flight, is the residual interference area; Construct a comprehensive cost function: ; By formula: , optimizing the comprehensive cost function to determine the target fully enclosed length of the bridge; wherein, is the cost-effectiveness slope, is the rate of decrease of ecological loss caused by changes in closure length, It is the growth rate of construction cost caused by changes in closed length.

6. The method according to claim 1, characterized in that The method further comprises: Determine the closure start and end positions on both sides of the bridge based on the target fully enclosed length of the bridge, so as to define the bridge length range required to be covered by the fully enclosed project; Based on the bridge interference warning equipotential surface, determining the longitudinal boundary of the spatial range where birds are susceptible to bridge interference in the direction of bridge extension; the longitudinal boundary includes a minimum impact position close to one end of the bridge and a maximum impact position far from one end of the bridge; Between the minimum impact position and the maximum impact position, a continuous distance segment is measured along the extension direction of the bridge, the distance of which is equal to the target full closure length; The end point of the measured continuous distance segment close to one end of the bridge along the extension direction of the bridge is determined as the closing starting position, and the end point away from the one end of the bridge is determined as the closing ending position; The starting position and the ending position form corresponding boundary points on both sides of the bridge in the horizontal direction respectively; the bridge length range required to be covered by the fully enclosed project is the continuous section of the bridge structure between the starting position and the ending position along the extension direction of the bridge.

7. The method according to claim 6, characterized in that The method further comprises: Based on the historical dominant wind direction and wind speed probability distribution data obtained in the area where the bridge is located; Calculate the wind speed and direction corrections at the minimum impact position and the maximum impact position respectively according to the deviation law of the bird flight trajectory in the tailwind state; superimposing the correction amount onto the original longitudinal boundary coordinates of the longitudinal boundary to obtain corrected longitudinal boundary coordinates; Based on the corrected longitudinal boundary coordinates, the minimum influence position and the maximum influence position are re-determined.

8. A closed engineering optimization device for bird protection decision-making on wading bridges, characterized by: include: An acquisition module is configured to construct a bird flight trajectory dynamics and energy consumption model, and solve for the bird's minimum energy consumption flight trajectory at different starting altitudes; construct a bridge interference warning equipotential surface based on the minimum energy consumption flight trajectory and a preset bird warning distance, wherein the interference warning equipotential surface represents the set of spatial positions of birds at different starting altitudes when they first enter the warning distance on their minimum energy consumption flight trajectory; calculate the bird interference area and the probability of group interference based on the bridge interference warning equipotential surface, wherein the interference area is the spatial range within the interference warning equipotential surface in the minimum energy consumption flight trajectory, and the probability of group interference is calculated based on the interference area and the bird flock density; In the optimization module, the user constructs a comprehensive cost function based on the disturbed area and the group disturbance probability, combined with the bridge full closure project cost and the ecological loss cost, and determines the target full closure length of the bridge by optimizing the comprehensive cost function.

9. A computer device, characterized in that: The computer device includes a processor and a non-volatile memory storing computer instructions. When the computer instructions are executed by the processor, the computer device executes the method according to any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium includes a computer program, and when the computer program is executed, the computer device where the readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

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