Rapid optimization design method, program and equipment for propeller with surface micro-grooves and storage medium

Abstract

The invention relates to a rapid optimization design method for a propeller with a surface micro-groove, a program, equipment and a storage medium, a three-dimensional model of a blade is constructed in a three-dimensional calculation domain, related parameters of the micro-groove are used as a to-be-optimized target, for each group of related parameters of the micro-groove, three-dimensional coordinates of the micro-groove in the three-dimensional model of the blade are calculated, and the three-dimensional coordinates of the micro-groove in the to-be-optimized target are calculated; constructing a three-dimensional model of the paddle with the micro-grooves; according to the number of propeller blades, coordinate transformation is carried out on the three-dimensional model of the propeller blades with the micro-grooves to obtain a three-dimensional model of the propeller with the surface micro-grooves, and the hydrodynamic performance efficiency and the maximum noise sound pressure level of the three-dimensional model of the propeller are obtained through simulation. And establishing an objective function about the hydrodynamic performance efficiency and the maximum noise sound pressure level, performing optimization by adopting a particle swarm algorithm, representing a group of related parameters of the micro-grooves by the positions of particles, obtaining an optimal related parameter combination of the micro-grooves, and completing the optimization design of the propeller with the surface micro-grooves.

Description

Technical Field

[0001] The present invention belongs to the technical field of ship propeller design, and in particular relates to a method, program, device and storage medium for rapid optimization design of a propeller with surface micro-grooves. Background Art

[0002] The noise and hydrodynamic performance of marine propulsion systems has long been a hot research topic. Currently, there are numerous methods for improving propulsion performance, including installing hydrodynamic energy-saving devices, using specialized propulsion systems (such as ducted propellers and pump-jet propulsion), and optimizing the ship-propeller matching. In addition to these conventional approaches, bionics can be used to further enhance propulsion noise control and hydrodynamic performance. Shark skin bionics has demonstrated excellent results in reducing ship drag. Propellers can utilize shark skin bionics by creating microgrooves on their surfaces to reduce propeller drag, thereby reducing propeller torque and increasing propeller efficiency. Furthermore, these microgrooves can restructure the propeller's surface vortex structure, reducing surface vortex-induced vibrations (VIVs) and optimizing propeller noise performance. However, modeling propeller surface microgrooves currently presents a challenge. The primary modeling approach involves manually creating grooves on the propeller surface based on microgroove parameters. While this method can create microgrooves on the propeller surface, it is time-consuming, labor-intensive, and error-prone, significantly limiting the development of this technology. In addition, there is limited research on this type of propeller. Although grooved propellers can effectively reduce propeller noise and improve propeller hydrodynamic performance, it is difficult to find their optimal parameters in engineering. Therefore, the propeller design problem is also a key issue that urgently needs to be broken through in engineering. Summary of the Invention

[0003] The purpose of the present invention is to solve the problems of low accuracy and low efficiency in surface micro-groove modeling and groove propeller design in the prior art, and to provide a method, program, equipment and storage medium for rapid optimization design of propellers with surface micro-grooves.

[0004] A method for rapid optimization design of a propeller with surface micro-grooves comprises the following steps:

[0005] Take a blade of the propeller to be optimized, obtain the blade's profile table, calculate the three-dimensional coordinates of each point on the blade surface in the three-dimensional computational domain, and construct a three-dimensional model of the blade;

[0006] The relevant parameters of the micro-grooves are taken as the optimization targets. For each set of micro-groove related parameters, the three-dimensional coordinates of the micro-grooves in the three-dimensional model of the blade are calculated, and a three-dimensional model of the blade with micro-grooves is constructed. According to the number of propeller blades, the three-dimensional model of the blade with micro-grooves is transformed by coordinate transformation to obtain a three-dimensional propeller model with surface micro-grooves. The hydrodynamic performance efficiency and the maximum sound pressure level of the propeller three-dimensional model are obtained through simulation. The objective function of the hydrodynamic performance efficiency and the maximum sound pressure level of the noise is established. The particle swarm algorithm is used for optimization. The position of the particles represents a set of micro-groove related parameters. The optimal combination of micro-groove related parameters is obtained to complete the optimization design of the propeller with surface micro-grooves.

[0007] Furthermore, the three-dimensional coordinates of each point on the blade surface are calculated in the three-dimensional calculation domain according to the blade's type value table, specifically:

[0008] Get multiple sets of data, each set of data includes the radius r of the point, the chord distance s from the point to its guide edge, the chord distance c1 from the guide edge to the main line, the pitch value x of the point r 、The side inclination angle θ of this point s , the geometric pitch angle β of the point, the distance y from the point to the chord bf The calculation method of the three-dimensional coordinates (x, r, θ) of the point in the cylindrical coordinate system and the three-dimensional coordinates (x, y, z) in the Cartesian coordinate system is:

[0009]

[0010] y=rcosθ,z=rsinθ.

[0011] Furthermore, the relevant parameters of the micro-grooves include the arrangement radius interval [a, b] of the micro-grooves on the blade surface, the number n of the micro-grooves, the depth D of the micro-grooves, and the spacing d between the grooves.

[0012] Furthermore, for each set of micro-groove related parameters, the three-dimensional coordinates of the micro-grooves in the three-dimensional model of the blade are calculated, specifically by:

[0013] For any curve l(x) on any interval [a,b], it is considered that the curve l(x) consists of n small curves l i (x i ) is composed of, in each small interval [x i ,x i+1 ] is a cubic polynomial:

[0014] S i (x) = a i0 +a i1 x+a i2 x 2 +a i3 x3 i=0,1,...,n-1

[0015] In any interval, S(x) at any node x i The upvalues ​​are equal and the first and second derivatives exist and are continuous:

[0016]

[0017] The second-order derivative at the given boundary is zero, that is, S″0(x0)=S″ n-1 (x n )=0;

[0018] Let the sub-interval [x i ,x i+1 ] interpolation function S i (x) is:

[0019] S i (x) = a i0 +a i1 (xx i )+a i2 (xx i ) 2 +a i3 (xx i ) 3 i=0,1,...,n-1

[0020] The corresponding first-order and second-order derivatives are expressed as:

[0021]

[0022] Let d i =x i+1 -x i , at the node position:

[0023]

[0024] For the three-dimensional coordinates [x, r, θ] of the micro-groove in the cylindrical coordinate system, [x, θ] is regarded as a function of r, that is, x(r) and θ(r). The coordinate point at any position on the blade surface is solved according to the above method. Finally, the micro-groove depth D is added to the corresponding coordinate point on the blade surface to complete the three-dimensional coordinate solution of the micro-groove in the three-dimensional model of the blade.

[0025] Furthermore, according to the number of propeller blades, the three-dimensional model of the blade with micro-grooves is subjected to coordinate transformation to obtain a three-dimensional propeller model with surface micro-grooves, specifically:

[0026] Calculate the angle of rotation based on the number of propeller blades N The three-dimensional model of the blade with micro-grooves is rotated N times to obtain a complete three-dimensional model of the propeller with surface micro-grooves;

[0027]

[0028] Among them, (x2, y2, z2) is the coordinate of a point before rotation, and (x1, y1, z1) is the coordinate of the point after rotation.

[0029] Furthermore, the objective function of establishing the hydrodynamic performance efficiency and the maximum sound pressure level of noise is specifically:

[0030]

[0031] Among them, k1∈[0,1] is the weight adjustment coefficient; η and SPL are the hydrodynamic performance efficiency and the maximum sound pressure level of the propeller with surface micro-grooves constructed according to the micro-groove related parameters; max(SPL) is the maximum sound pressure level threshold of the propeller; k2 is the control coefficient.

[0032] Furthermore, the particle swarm algorithm is used for optimization, and the position of the particles represents a set of micro-groove related parameters:

[0033] X i (t)=(a i (t),b i (t),n i (t),D i (t),d i (t))

[0034] Where t is the number of iterations; i is the index of the particle;

[0035] The particle velocity is updated in each iteration as:

[0036] v id (t+1)=w(t)·v id (t)+c1·r1·(X id -x id (t))+c2·r2·(Y d -x id (t))

[0037] Where d represents the dimension index, d = 1, 2, ..., 5; w(t) is the weight factor, w max is the maximum weight factor, w min is the minimum weight factor, T is the maximum number of iterations; c1 and c2 are learning factors; r1 and r2 are random numbers between [0,1]; X id is the value of the d-th dimension parameter in the historical optimal position of the i-th particle; Y dis the value of the d-th dimension parameter in the global optimal position; x id (t) is X i The value of the d-th dimension parameter in (t);

[0038] The particle position is updated in each iteration as:

[0039] x id (t+1)=x id (t)+v id (t+1).

[0040] A computer device / equipment / system includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the above-mentioned method for rapid optimization design of a propeller with surface micro-grooves.

[0041] A computer-readable storage medium stores a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for rapid optimization design of a propeller with surface micro-grooves.

[0042] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for rapid optimization design of a propeller with surface micro-grooves.

[0043] The beneficial effects of the present invention are:

[0044] This invention designs a method for constructing a three-dimensional model of a propeller with surface microgrooves in the computational domain. Based on the relevant parameters of the microgrooves, the corresponding hydrodynamic performance efficiency and maximum noise sound pressure level can be obtained through simulation. This invention addresses the issues of premature convergence and local optimality often encountered by the standard particle swarm algorithm when optimizing complex nonlinear problems. By introducing an adaptive inertia weighting factor into the velocity update formula, this method establishes an optimization design model aimed at optimizing the noise and hydrodynamic performance of grooved propellers, accelerating iteration speed. This invention is convenient and fast, meeting engineering design requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of an embodiment of the present invention.

[0046] Figure 2 This is a three-dimensional model of micro-grooves on a propeller surface created in an embodiment of the present invention. The red line represents the radial range of the micro-grooves, reference numeral 1 represents the groove spacing, and reference numeral 2 represents the groove depth.

[0047] Figure 3 This is the overall architecture diagram of the present invention.

[0048] Figure 4This is the final optimization result diagram of the hydrodynamics in the embodiment of the present invention. T , K Q , η represent the propeller's thrust coefficient, torque coefficient, and open water efficiency, respectively. It can be seen from the figure that the efficiency has been improved.

[0049] Figure 5 Graph showing noise optimization results of a propeller in an embodiment of the present invention. Figure 5 The propeller noise monitoring results at different radial and axial positions are given in Figure 3. The noise of the optimized propeller is reduced. DETAILED DESCRIPTION

[0050] The present invention will be further described below with reference to the accompanying drawings.

[0051] A method for rapid optimization design of a propeller with surface micro-grooves comprises the following steps:

[0052] Step 1: Take a blade of the propeller to be optimized, obtain the blade's profile table, calculate the 3D coordinates of each point on the blade surface in the 3D computational domain, and construct a 3D model of the blade;

[0053] Get multiple sets of data, each set of data includes the radius r of the point, the chord distance s from the point to its guide edge, the chord distance c1 from the guide edge to the main line, the pitch value x of the point r 、The side inclination angle θ of this point s , the geometric pitch angle β of the point, the distance y from the point to the chord bf The calculation method of the three-dimensional coordinates (x, r, θ) of the point in the cylindrical coordinate system and the three-dimensional coordinates (x, y, z) in the Cartesian coordinate system is:

[0054]

[0055] y=rcosθ,z=rsinθ

[0056] Step 2: Take the micro-groove related parameters as the optimization targets, including the micro-groove layout radius interval [a, b] on the blade surface, the number of micro-grooves n, the depth of micro-grooves D, and the spacing between grooves d. Use the particle swarm algorithm to find the optimal solution. The position of the particles represents a set of micro-groove related parameters.

[0057] The calculation method of the particle fitness value is:

[0058] Step 2.1: For each set of micro-groove related parameters (a, b, n, D, d), calculate the three-dimensional coordinates of the micro-grooves in the three-dimensional model of the blade, and construct a three-dimensional model of the blade with micro-grooves;

[0059] For any curve l(x) on any interval [a,b], it is considered that the curve l(x) consists of n small curves li (x i ) is composed of, in each small interval [x i ,x i+1 ] is a cubic polynomial:

[0060] S i (x) = a i0 +a i1 x+a i2 x 2 +a i3 x 3 i=0,1,...,n-1

[0061] In any interval, S(x) at any node x i The upvalues ​​are equal and the first and second derivatives exist and are continuous:

[0062]

[0063] The second-order derivative at the given boundary is zero, that is, S″0(x0)=S″ n-1 (x n )=0;

[0064] Let the sub-interval [x i ,x i+1 ] interpolation function S i (x) is:

[0065] S i (x) = a i0 +a i1 (xx i )+a i2 (xx i ) 2 +a i3 (xx i ) 3 i=0,1,...,n-1

[0066] The corresponding first-order and second-order derivatives are expressed as:

[0067]

[0068] Let d i =x i+1 -x i , at the node position:

[0069]

[0070] For the three-dimensional coordinates [x, r, θ] of the micro-groove in the cylindrical coordinate system, [x, θ] is considered as a function of r, that is, x(r) and θ(r). The coordinate point at any position on the blade surface is solved according to the above method. Finally, the micro-groove depth D is added to the corresponding coordinate point on the blade surface to complete the three-dimensional coordinate solution of the micro-groove in the three-dimensional model of the blade.

[0071] Step 2.2: Based on the number of propeller blades, the three-dimensional model of the blade with micro-grooves is transformed into a three-dimensional propeller model with surface micro-grooves.

[0072] Calculate the angle of rotation based on the number of propeller blades N The three-dimensional model of the blade with micro-grooves is rotated N times to obtain a complete three-dimensional model of the propeller with surface micro-grooves;

[0073]

[0074] Among them, (x2, y2, z2) is the coordinate of a point before rotation, and (x1, y1, z1) is the coordinate of the point after rotation;

[0075] Step 2.3: Obtain the hydrodynamic performance efficiency η and the maximum noise sound pressure level SPL of the propeller 3D model through simulation, calculate the objective function, and use it as the fitness value of the particle:

[0076]

[0077] Among them, k1∈[0,1] is the weight adjustment coefficient; η and SPL are the hydrodynamic performance efficiency and the maximum sound pressure level of the propeller with surface micro-grooves constructed according to the micro-groove related parameters; max(SPL) is the maximum sound pressure level threshold of the propeller; k2 is the control coefficient.

[0078] During the optimization process of the particle swarm algorithm, the speed of the particles in each iteration is updated as follows:

[0079] v id (t+1)=w(t)·v id (t)+c1·r1·(X id -x id (t))+c2·r2·(Y d -x id (t))

[0080] Where d represents the dimension index, d = 1, 2, ..., 5; w(t) is the weight factor, w max is the maximum weight factor, w min is the minimum weight factor, T is the maximum number of iterations; c1 and c2 are learning factors; r1 and r2 are random numbers between [0,1]; Xid is the value of the d-th dimension parameter in the historical optimal position of the i-th particle; Y d is the value of the d-th dimension parameter in the global optimal position; x id (t) is X i (t)=(a i (t),b i (t),n i (t),D i (t),d i (t)) in the d-th dimension, for example, x i1 (t) = a i (t), x i2 (t) = b i (t);

[0081] Calculate the updated value x for each element in the position vector id (t+1)=x id (t)+v id (t+1), update the position of the particle to X i (t+1);

[0082] Example 1:

[0083] This embodiment addresses the issues of propeller propulsion efficiency and noise performance by incorporating microgrooves into the propeller. Fortran is used for parametric modeling, calculation of the three-dimensional coordinate points of the propeller with surface microgrooves is performed, and CATIA macros are developed for rapid and accurate modeling. This invention significantly reduces the time required to model a propeller with surface microgrooves. Based on this, a calculation strategy for the hydrodynamic and noise performance of grooved propellers is established, performing extensive calculations. Based on this data, a traditional particle swarm algorithm is then improved, accelerating its convergence rate, thereby establishing a rapid optimization design method for propellers with surface microgrooves that optimizes hydrodynamic and noise performance.

[0084] S1: Calculation of smooth propeller three-dimensional coordinate points;

[0085] S101: Calculation of the three-dimensional coordinate points of the propeller includes the back and front of the propeller blade. The calculation steps include:

[0086] S10101: Using the E997A propeller as the parent propeller, first import the E997A propeller's diameter, hub-to-diameter ratio, pitch, and profile data. In the cylindrical coordinate system, the blade profile at radius r can be expressed using formula (1), where s represents the chordwise distance from the point to its leading edge; c1 represents the chordwise distance from the leading edge to the main line; x r Represents the pitch value at that point; θ s represents the side inclination angle at that point; β represents the geometric pitch angle; y b and yf Represent the distances from the blade back and blade surface points to the chord line, respectively. To import this into the modeling software for processing, it is necessary to describe it in a Cartesian coordinate system. In this case, equation (2) is used for calculation. After this calculation, all three-dimensional coordinate points on the propeller's smooth surface can be obtained.

[0087]

[0088] S102: Calculation steps for the three-dimensional coordinate points of the micro-grooves on the propeller surface:

[0089] S10201: Input relevant parameters of the micro-grooves, such as the radius interval [a, b] of the micro-grooves on the blade surface, the number n of micro-grooves, the depth t of the micro-grooves, and the spacing d between grooves.

[0090] S10202: For any curve l(x) on any interval [a,b], we can consider the curve l(x) as consisting of n small curves l i (x i ), in each small interval [x i ,x i+1 ] is a cubic polynomial (3). In addition, in any interval, the three-spline interpolation function S(x) also needs to be i The upvalues ​​are equal and the first and second derivatives exist and are continuous.

[0091] S i (x) = a i0 +a i1 x+a i2 x 2 +a i3 x 3 i=0,1,...,n-1 (3)

[0092]

[0093] From equation (3), we can see that there are four unknowns in each small interval, that is, a total of 4n unknowns need to be solved. In the equation system (4), the nodes are equal in size, which can give 2n equations, while the first-order and second-order derivatives can only give 2n-2 equations continuously. Therefore, boundary conditions need to be added at the boundaries to close the equation system. Here, the second-order derivative at the given boundary is zero, that is, S″0(x0)=S″ n-1 (x n )=0.

[0094] In order to facilitate the solution, let the subinterval [x i ,x i+1 ] interpolation function S i (x) is in the form of (5):

[0095] S i (x) = a i0 +a i1 (xx i )+a i2 (xx i ) 2 +a i3 (xx i ) 3 i=0,1,...,n-1 (5)

[0096] Then the corresponding first-order and second-order derivatives can be expressed as (6):

[0097]

[0098] Let d i =x i+1 -x i , then at the node position, according to formula (7):

[0099]

[0100] Considering natural boundary conditions at the boundaries, we can define three polynomials within each small interval. For the three-dimensional cylindrical coordinate system [x, r, θ], [x, θ] can be considered as a function of r, x(r), θ(r). This allows us to solve for the coordinates of any point on the rotor surface. Finally, we add the microgroove depth t to the corresponding coordinate point on the blade surface to construct the surface microgroove.

[0101] S10203: Calculate the rotation angle α based on the number of blades using formula (8), where N is the number of blades. For example, if the E779A has four blades, then its rotation angle can be calculated as 90° according to formula (8).

[0102]

[0103] According to formula (9), rotate N times to obtain the three-dimensional coordinate points of the propeller with a complete micro-grooved surface. (x2, y2, z2) is the coordinate of a point before rotation, and (x1, y1, z1) is the coordinate of the point after rotation.

[0104]

[0105] According to S101~S102, the complete three-dimensional coordinate points of the micro-grooves on the propeller surface can be obtained, and then imported into CATIA to obtain the three-dimensional model of the micro-grooves on the propeller surface with the help of macro commands.

[0106] S2: CATIA secondary development and model building.

[0107] S201: completing the development of the modeling software by calling the macro command socket of the 3D modeling software CATIA;

[0108] S20201: Export the three-dimensional coordinate points of the propeller surface micro-grooves obtained in S102 in a macro command format, and then import them into CATIA to automatically generate splines of the propeller surface micro-grooves;

[0109] S20202: Connect the leading edge and the trailing edge of the propeller according to the spline formed in S20201 to form a contour curve of the propeller;

[0110] S20203: Use the contour line as a guide line to connect the splines on the blade surface to form a multi-section surface;

[0111] S20204: Fill the blade tip and root, and combine them with the multi-section surface obtained in S20203 to obtain a three-dimensional propeller model with surface micro-grooves.

[0112] like Figure 2 As shown, the propeller with surface micro-grooves obtained by automatic modeling of the present invention can quickly and automatically fit the blade surface without human intervention. The obtained micro-groove blade is efficient and accurate, which greatly reduces the error rate of manual modeling in the calculation, import, and modeling links, and also reduces the time cost of modeling.

[0113] S3: Establishment of an optimization design model for the hydrodynamic and noise performance of grooved propellers.

[0114] S301: Establishing a calculation strategy for the hydrodynamic performance and noise performance of the grooved propeller model obtained in step S2 using commercial CFD software.

[0115] S302: Establishing a groove propeller optimization design model based on a particle swarm algorithm.

[0116] S30201: Determine the optimal range of groove propeller parameters. The parameters here are the groove parameters in step S10201, such as the blade surface layout radius interval [a, b], the number of micro grooves n, the micro groove depth t, and the spacing d between grooves.

[0117] The groove parameters are as follows: the radius of the blade surface is in the range of [0.4, 0.9], the number of grooves n is 20 to 50, the groove depth t is between 0.3 mm and 1.0 mm, and the spacing d between grooves is between 0.3 mm and 1.0 mm.

[0118] S30202: Particle swarm initialization and parameter setting.

[0119] Set the particle swarm to 50 particles and randomly initialize the particle velocity to 10% of the particle optimization range. For example, if parameter A is updated in the range [0.4, 0.9], then the particle velocity of A is [-0.05, 0.05]. Each particle's initial position is taken as its individual extreme value X. Then, find the particle position with the optimal hydrodynamic and noise performance in the entire particle swarm and use it as the initial global extreme value Y.

[0120] S30203: Establish objective function.

[0121] Establish the objective function for the optimization of the groove propeller. With the particle parameters of step S30202 as the target, a large number of models are quickly established through the modeling method established from step S1 to step S2. Then, the calculation strategy established in step S301 is used to calculate the hydrodynamic performance and noise performance of these models, where the hydrodynamic performance is judged by the efficiency η and the noise performance is judged by the maximum sound pressure level SPL. Usually, the efficiency and the maximum sound pressure level are not in the same order of magnitude, and the sound pressure level needs to be processed to a certain extent, and the sound pressure level requirement is lower while the efficiency requirement is higher. The objective function finally established is shown in formula (10):

[0122]

[0123] In the formula, k1 is the weight adjustment coefficient, which ranges between [0,1]. The larger it is, the more emphasis is placed on the optimization results of efficiency, and vice versa. In addition, in order to make the value range of SPL consistent with η, it is adjusted to within [0,1] and the hyperbolic tangent function is used. And because the growth of SPL is not a linear distribution, the hyperbolic tangent function is more in line with its characteristics. max(SPL) is the maximum sound pressure level in the preprocessed data. The sound pressure level distribution is mapped one by one from the maximum to the minimum value of the original data to [0,1] by formula (10). Among them, k2 is the control coefficient, which is used to better grasp the range of the sound pressure level processing results, and is generally taken as 3.

[0124] S30204: Perform optimization cycle process.

[0125] Using the objective function established in step S30203, calculate the fitness value of each particle. Compare each particle's current fitness value with the fitness value corresponding to its individual extreme value. If the current value is better, update the individual extreme value. Then, find the position of the particle with the best fitness value in the entire particle swarm and update the global extreme value. The speed update formula is shown in Equation (11).

[0126] v id (t+1)=w(t)·v id (t)+c1·r1·(X id -x id(t))+c2·r2·(Y d -x id (t)) (11)

[0127] Where, the subscript id represents the i-th particle in the d-th dimension space, and the number in the brackets represents the number of iterations. v represents the iteration speed; w represents the inertia weight factor, and its calculation expression is shown in (12), w max is the maximum weight factor, w min is the minimum weight factor, T is the maximum number of iteration steps, and t is the current number of iteration steps; X id is the value of the d-th dimension parameter in the historical optimal position of the i-th particle; Y d is the value of the d-th dimension parameter in the global optimal position; c1 and c2 are learning factors, usually 2; r1 and r2 are random numbers between [0,1];

[0128]

[0129] x id (t+1)=x id (t)+v id (t+1) (13)

[0130] S303: Repeat the iteration until the convergence condition is met or the maximum number of iterations is reached.

[0131] Repeat step S302 and perform iterative calculation until the result converges or exceeds the maximum number of iterations, and output the groove parameters of the groove propeller corresponding to the optimal efficiency and the optimal noise respectively. This is the groove propeller parameter under the optimal parameters.

[0132] This embodiment uses Fortran language to conduct research on rapid parametric modeling of propeller surface micro-grooves, develops a rapid modeling program, and realizes the automation of propeller surface micro-grooves from propeller parameters, micro-groove parameter input to model value calculation and then to three-dimensional model establishment.

[0133] In the design and modeling of propellers with surface micro-grooves, if the propeller parameters change, it is only necessary to change the input parameters of the propeller; if the micro-groove parameters change, such as the spacing between the grooves, the depth of the micro-grooves, the range of the micro-grooves, the number of micro-grooves, and other parameters, it is only necessary to modify them in the program interface. The present invention is convenient and fast, and meets the requirements of engineering design. In view of the problems that the standard particle swarm algorithm is prone to premature convergence and local optimality when optimizing complex nonlinear problems, the present invention improves the particle swarm algorithm. An adaptive inertia weight factor is introduced into the speed update formula. Based on the algorithm, an optimization design model is established with the goal of optimizing the noise and hydrodynamic performance of the grooved propeller, which speeds up the iteration speed.

[0134] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for rapid optimization design of a propeller with surface micro-grooves, characterized by: Take a blade of the propeller to be optimized, obtain the blade's profile table, calculate the three-dimensional coordinates of each point on the blade surface in the three-dimensional computational domain, and construct a three-dimensional model of the blade; The relevant parameters of the micro-grooves are taken as the optimization targets. For each set of micro-groove related parameters, the three-dimensional coordinates of the micro-grooves in the three-dimensional model of the blade are calculated, and a three-dimensional model of the blade with micro-grooves is constructed. According to the number of propeller blades, the three-dimensional model of the blade with micro-grooves is transformed by coordinate transformation to obtain a three-dimensional propeller model with surface micro-grooves. The hydrodynamic performance efficiency and the maximum sound pressure level of the propeller three-dimensional model are obtained through simulation. The objective function of the hydrodynamic performance efficiency and the maximum sound pressure level of the noise is established. The particle swarm algorithm is used for optimization. The position of the particles represents a set of micro-groove related parameters. The optimal combination of micro-groove related parameters is obtained to complete the optimization design of the propeller with surface micro-grooves.

2. The method for rapid optimization design of a propeller with surface micro-grooves according to claim 1, characterized in that: The three-dimensional coordinates of each point on the blade surface are calculated in the three-dimensional calculation domain according to the blade's type value table, specifically: Get multiple sets of data, each set of data includes the radius r of the point, the chord distance s from the point to its guide edge, the chord distance c1 from the guide edge to the main line, the pitch value x of the point r 、The side inclination angle θ of this point s , the geometric pitch angle β of the point, the distance y from the point to the chord bf The calculation method of the three-dimensional coordinates (x, r, θ) of the point in the cylindrical coordinate system and the three-dimensional coordinates (x, y, z) in the Cartesian coordinate system is: x=x r +(-c1+s)sinβ-y bf cosβ, y=rcosθ,z=rsinθ.

3. The method for rapid optimization design of a propeller with surface micro-grooves according to claim 1, characterized in that: The relevant parameters of the micro grooves include the arrangement radius interval [a, b] of the micro grooves on the blade surface, the number n of the micro grooves, the depth D of the micro grooves, and the spacing d between the grooves.

4. The method for rapid optimization design of a propeller with surface micro-grooves according to claim 3, characterized in that: For each set of micro-groove related parameters, the three-dimensional coordinates of the micro-grooves in the three-dimensional model of the blade are calculated. The specific method is: For any curve l(x) on any interval [a,b], it is considered that the curve l(x) consists of n small curves l i (x i ) is composed of, in each small interval [x i ,x i+1 ] is a cubic polynomial: S i (x)=a i0 +a i1 x+a i2 x 2 +a i3 x 3 i=0,1,...,n-1 In any interval, S(x) at any node x i The upvalues ​​are equal and the first and second derivatives exist and are continuous: The second-order derivative at the given boundary is zero, that is, S″0(x0)=S″ n-1 (x n )=0; Let the sub-interval [x i ,x i+1 ] interpolation function S i (x) is: S i (x)=a i0 +a i1 (x-x i )+a i2 (x-x i ) 2 +a i3 (x-x i ) 3 i=0,1,...,n-1 The corresponding first-order and second-order derivatives are expressed as: Let d i =x i+1 -x i , at the node position: For the three-dimensional coordinates [x, r, θ] of the micro-groove in the cylindrical coordinate system, [x, θ] is regarded as a function of r, that is, x(r) and θ(r). The coordinate point at any position on the blade surface is solved according to the above method. Finally, the micro-groove depth D is added to the corresponding coordinate point on the blade surface to complete the three-dimensional coordinate solution of the micro-groove in the three-dimensional model of the blade.

5. The method for rapid optimization design of a propeller with surface micro-grooves according to claim 1, characterized in that: According to the number of propeller blades, the three-dimensional model of the blade with micro grooves is transformed by coordinates to obtain a three-dimensional propeller model with surface micro grooves, specifically: Calculate the angle of rotation based on the number of propeller blades N The three-dimensional model of the blade with micro-grooves is rotated N times to obtain a complete three-dimensional model of the propeller with surface micro-grooves; Among them, (x2, y2, z2) is the coordinate of a point before rotation, and (x1, y1, z1) is the coordinate of the point after rotation.

6. The method for rapid optimization design of a propeller with surface micro-grooves according to claim 3, characterized in that: The objective function of establishing the hydrodynamic performance efficiency and the maximum sound pressure level of noise is specifically: Among them, k1∈[0,1] is the weight adjustment coefficient; η and SPL are the hydrodynamic performance efficiency and the maximum sound pressure level of the propeller with surface micro-grooves constructed according to the micro-groove related parameters; max(SPL) is the maximum sound pressure level threshold of the propeller; k2 is the control coefficient.

7. The method for rapid optimization design of a propeller with surface micro-grooves according to claim 3, characterized in that: The particle swarm algorithm is used for optimization, and the position of the particles represents a set of micro-groove related parameters: X i (t)=(a i (t),b i (t),n i (t),D i (t),d i (t)) Where t is the number of iterations; i is the index of the particle; The particle velocity is updated in each iteration as: v id (t+1)=w(t)·v id (t)+c1·r1·(X id -x id (t))+c2·r2·(Y d -x id (t)) Where d represents the dimension index, d = 1, 2, ..., 5; w(t) is the weight factor, w max is the maximum weight factor, w min is the minimum weight factor, T is the maximum number of iterations; c1 and c2 are learning factors; r1 and r2 are random numbers between [0,1]; X id is the value of the d-th dimension parameter in the historical optimal position of the i-th particle; Y d is the value of the d-th dimension parameter in the global optimal position; x id (t) is X i The value of the d-th dimension parameter in (t); The particle position is updated in each iteration as: x id (t+1)=x id (t)+v id (t+1)。 8. A computer device / apparatus / system comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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