A sound barrier shape optimization method based on the isogeometric singular boundary method

Abstract

This invention belongs to the field of road traffic noise reduction technology, and relates to a sound barrier shape optimization method based on the singular boundary method of isogeometric geometry. This method combines isogeometric analysis with the singular boundary method to optimize the sound barrier shape more simply and accurately, improving optimization efficiency. Specifically, it includes the following steps: establishing a geometric model of the sound barrier based on its geometric parameters; extracting information from the established geometric model and importing it into the program to obtain the interpolation points of the geometric model boundary, which are then used as the boundary points of the singular boundary method; establishing a sound barrier shape optimization model using known acoustic control equations; calculating the set objective function and constraints using the optimization model, and iterating the results using the moving asymptote method to obtain the optimal value; and outputting the final optimized shape of the sound barrier. This method avoids repetitive modeling processes during optimization, eliminates the need for mesh generation and numerical integration, and boasts high overall speed, high efficiency, and reliable principles.

Description

Technical Field

[0001] This invention belongs to the field of road traffic noise reduction technology, and relates to a sound barrier shape optimization method based on the isogeometric singular boundary method. It can optimize the sound barrier shape more simply and accurately by combining isogeometric analysis with the singular boundary method, improve optimization efficiency, and enable the structure to achieve better noise reduction effect. Background Technology

[0002] With the continuous development of modern industrial technology and the improvement of people's living standards in my country, the number of cars and the transportation industry have shown a rapid growth trend. However, the resulting traffic noise has seriously affected the quality of life of residents living near roads. To reduce noise pollution, sound barriers are widely used as an effective noise control measure, offering advantages such as significant sound absorption, flexible and controllable protection range, and ease of maintenance. However, traditional sound barrier shapes are usually based on empirical design or simple rules, lacking optimization and customization. In such cases, problems such as poor sound barrier performance or excessive costs often arise. Therefore, researching a more effective method for optimizing sound barrier shapes is of great significance.

[0003] Analyzing the noise reduction effect of sound barriers usually requires testing by installing physical structures along roadsides. However, this experimental method often consumes a lot of time and manpower. Therefore, numerical simulation has emerged as a solution for sound barriers. Among these methods, the finite element method (FEM) and the boundary element method (BEM) are two main approaches. However, the FEM has a high cost for mesh generation, and the boundary discretization error of complex geometric models is also large. In contrast, the BEM can solve the problem in one dimension without the need for regional mesh generation. However, this method involves the troublesome and complex singular numerical integration problem. The singular boundary method, as an accurate semi-analytical meshless method (Chen Wen, Singular Boundary Method: A New, Simple, Meshless, Collocational Numerical Method for Boundary Points, Chinese Journal of Solid Mechanics, 2009, 30(6): 592-599.), has the advantages of being truly meshless, integration-free, mathematically simple, and easy to program. It has important application prospects in simulation. When optimizing the shape of a sound barrier, the shape changes with each optimization, requiring repeated modeling, which is time-consuming and laborious. The repeated modeling can be avoided by introducing isogeometric analysis (TJRHughes, JACottrell, Y. Bazilevs, Isogeometric analysis: CAD, finite elements, NURBS, exact geometry and mesh refinement, Computer Methods in Applied Mechanics and Engineering, 194(2005)4135-4195), which allows for seamless integration of CAD and CAE, thereby improving optimization efficiency. Existing literature has disclosed the combination of isogeometric analysis and boundary element method to optimize the shape of a sound barrier (C. Liu, L. Chen, W. Zhao, H. Chen, Shape optimization of sound barrier using an isogeometric fast multipole boundary element method in two dimensions, Engineering Analysis with Boundary Elements, 85(2017)142-157). However, the boundary element method involves complex singular numerical integration problems, which are computationally intensive and relatively inefficient.

[0004] In the prior art, Chinese patent CN102663199A discloses a sound barrier optimization design method based on response surface analysis, which includes the following steps: (1) calculating the diffraction sound attenuation of an infinitely long sound barrier to obtain the theoretical insertion loss of a finite-length sound barrier; (2) selecting three important variables that affect the insertion loss of the sound barrier at each sound receiving point; (3) calculating the insertion loss of the sound barrier at each sound receiving point and the cost of the sound barrier under different schemes; (4) obtaining a quadratic multiple regression model; (5) calculating the variance analysis results and significance test results; (6) conducting a significant impact analysis on each design parameter. (7) The design parameters of the sound barrier are optimized, and the optimal design parameters are obtained from the analysis of the optimization area. The sound barrier optimization design method based on response surface analysis is used to carry out noise reduction optimization research on multiple sensitive targets. Chinese patent CN112726858A discloses a noise control optimization method based on sound barriers. By measuring the noise source and its surrounding environment, the spatial location and geometric dimensions of the noise source, the noisy building, the reflective wall, the ground and the sound barrier are obtained. The noise source and its surrounding environment are simulated to obtain the simulated octave band of the noise emitted by the noise source to the receiving point. The sound pressure level is calculated, and then the theoretical octave band sound pressure level is obtained using the sound environment quality standard. Taking background noise into account, the noise reduction amount corresponding to the noisy building is determined. Simultaneously, the actual structure of the sound barrier, diffraction effect, and reflection effect are considered to calculate the sound attenuation of the noise source and the sound attenuation of the mirrored virtual sound source. Based on the relationship between the sound attenuation of the noise source and the sound attenuation of the mirrored virtual sound source and the noise reduction amount, the structure and location of the sound barrier are defined, thereby obtaining an optimized noise control scheme based on the sound barrier. Chinese patent CN112182941A discloses a topology for a spaced-contraction sound insulation structure. The optimization method involves acoustically modeling the spaced-shrink sound barrier structure based on the Helmholtz equation. A topology optimization method based on the variable density approach is employed, and a novel interpolation function is proposed for continuous material interpolation of density and bulk modulus. Constraints on the material volume fraction within the design domain are introduced. The objective function is to minimize the sum of squares of transmitted sound pressure in the target frequency band within the evaluation domain. Sensitivity analysis of the objective and constraint functions is performed using the adjoint method, and the moving asymptote method is employed to optimize the objective function, obtaining the optimal distribution of solid material within the design domain. Ultimately, broadband sound insulation of the ventilated sound barrier is achieved within a limited space. However, the aforementioned existing techniques suffer from limitations such as inability to optimize the sound barrier shape, high computational cost, and relatively cumbersome steps. These limitations prevent a simple and effective optimization of the sound barrier shape, resulting in limited noise reduction effects.

[0005] Through research and analysis, the inventors found that no existing technology discloses a method for optimizing the shape of a sound barrier by combining isogeometric analysis with the singular boundary method. Therefore, this invention proposes a sound barrier shape optimization method based on the isogeometric singular boundary method, which can improve noise reduction performance through relatively simple and efficient shape optimization of the sound barrier. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and to design a sound barrier shape optimization method based on the isogeometric singular boundary method, thereby solving the problems of the inability to achieve simple and effective optimization of sound barrier shape and the limited noise reduction effect in the prior art.

[0007] To achieve the above objectives, the present invention provides a sound barrier shape optimization method based on the isogeometric singular boundary method, which specifically includes the following steps:

[0008] (1) Establish a geometric model: Based on the geometric parameters of the sound barrier to be optimized, establish a geometric model of the sound barrier. The geometric parameters include the width, height and position of the sound barrier in space. The geometric model is described by NURBS curves.

[0009] (2) Obtaining Boundary Points: Extract the information from the constructed geometric model and import it into the program. The program obtains the interpolation points of the geometric model boundary. These interpolation points are used as the boundary points of the singular boundary method. n nodes x are configured on the boundary of the sound barrier. i For each i = 1, 2, ..., n, the extracted geometric model information includes the coordinates of control points, weights, node vectors, and the order of the curves in the geometric model.

[0010] (3) Establish an optimization model: using the known acoustic control equations and air density of 1.29 kg / m³ 3 Based on the speed of sound in the air (340 m / s), the frequency of the sound source, the selected shape design variables, and the corresponding boundary conditions, a sound barrier shape optimization model based on the isogeometric singular boundary method is established.

[0011] (4) Find the optimal value: Using the sound barrier shape optimization model based on the isogeometric singular boundary method established in step (3), calculate the set objective function, constraints and their sensitivity to shape design variables, substitute the obtained results into the moving asymptote method for iteration, and find the optimal value.

[0012] (5) Output final shape: Output the final optimized shape of the sound barrier and evaluate the performance of the result.

[0013] The present invention relates to a sound barrier shape optimization method based on the isogeometric singular boundary method, wherein the procedure described in step (2) is as follows:

[0014] Substitute the control point coordinates, weights, node vectors, and curve order from the extracted geometric model into the boundary curve expression:

[0015]

[0016] Where P is the i-th control point, and n is the number of control points. NURBS spline basis functions, N i,p (ξ) is the p-th degree B-spline basis function, ω i Let ξ be the weight of the i-th control point, and ξ be the coordinates in the parameter space.

[0017] The sound barrier shape optimization method based on the isogeometric singular boundary method involved in this invention, wherein the acoustic control equation used in step (3) is:

[0018] ▽ 2 p(x)+k 2 p(x) = 0, x ∈ Ω

[0019] Among them ▽ 2 For the Laplace operator, Let ω be the wave number, ω = 2πf be the angular frequency, c be the speed of sound, f be the frequency, Ω represent the sound field region, x be the spatial coordinate, and p(x) be the sound pressure amplitude at x.

[0020] For the above governing equations, the Dirichlet conditions and Newman boundary conditions are usually considered:

[0021]

[0022]

[0023] in For the boundary Γ p The known sound pressure level above, For the boundary Γ v The known normal velocity on the surface, ρ is the density of air.

[0024] The present invention relates to a sound barrier shape optimization method based on the isogeometric singular boundary method, wherein step (3) of establishing the isogeometric singular boundary optimization model includes:

[0025] (31) Define the objective function and constraints, select shape design variables, give their upper and lower limits, set the maximum number of iterations and convergence parameters, where the objective function is set as the total sound pressure in the observation area, and the observation area is specifically selected according to the actual situation.

[0026] (32) Representing the numerical solution at each boundary point as a linear summation of the fundamental solutions, the fundamental solution corresponding to the two-dimensional Helmholtz equation is:

[0027]

[0028] in It is a zeroth-order Hankel function of the first kind, ||xs||² is the distance between the field point x and the source point s, and s' is the mirror image of the source point s with respect to the ground. Combining all the equations, we obtain the linear equation system of the singular boundary method:

[0029]

[0030] Right now:

[0031] Aα=b

[0032] in:

[0033]

[0034] (33) Since the source point and field point coincide in the singular boundary method, the diagonal of this system of equations will exhibit singularity. Therefore, a source point intensity factor is introduced:

[0035]

[0036]

[0037] Where γ is Euler's constant. L is a fundamental solution to the Laplace equation. j Represents the source point s j The range of influence, i.e., the source point s on the physical boundary. j-1 and source point s j+1 The semi-circular length between them.

[0038] The method for optimizing the shape of a sound barrier based on the isogeometric singular boundary method involved in this invention includes the following specific method for calculating the set objective function, constraints, and their sensitivity to the shape design variables in step (4):

[0039] Solve the system of linear equations established in step (3) to obtain all source point densities α, and then calculate the function value at any point in the domain according to the following equation:

[0040] x∈Ω,s j ∈Γ

[0041] Calculate the set objective function, constraints, and their sensitivity to shape design variables.

[0042] The present invention relates to a sound barrier shape optimization method based on the isogeometric singular boundary method, wherein the optimization effect of the sound barrier in step (5) is mainly measured by the change in sound pressure or sound pressure level at the observation points in the observation area. A line graph is plotted on the change in sound pressure level at the observation points in the observation area in step (4), and the change is observed. If the sound pressure level generally decreases, the optimization effect is significant; if no significant change is observed, the optimization effect is poor.

[0043] Compared with the prior art, the present invention has the following advantages: (1) The present invention adopts isogeometric analysis and singular boundary method, directly uses the semi-analytical basic solution of acoustic problem as kernel function, and combines the moving asymptote method to optimize the shape of sound barrier. Compared with the traditional CAE software core algorithm finite element and boundary element, it has the advantages of no meshing required, fast calculation speed and simple programming; (2) By introducing isogeometry, that is, using NURBS function to represent geometric boundary, CAD and CAE are seamlessly connected, avoiding the meshing stage in the optimization process, improving the accuracy and efficiency of sound barrier optimization, and can accurately and efficiently optimize the shape of sound barrier, providing a new, simple and efficient technical route for sound barrier shape optimization. Attached Figure Description

[0044] Figure 1 This invention relates to a process flow diagram of a sound barrier shape optimization method based on the isogeometric singular boundary method.

[0045] Figure 2 This is a two-dimensional model schematic diagram of the relevant upright sound barrier involved in the present invention.

[0046] Figure 3 This is a schematic diagram of the final optimized model of the sound barrier at frequencies of 400Hz and 700Hz as involved in the present invention.

[0047] Figure 4 This is a schematic diagram illustrating the iterative changes of the objective function and area during the optimization process at frequencies of 400Hz and 700Hz, as per the present invention.

[0048] Figure 5 This is a schematic diagram illustrating the sound pressure level changes at observation points at frequencies of 400Hz and 700Hz, as per the present invention.

[0049] Figure labeling: A, Sound source; B, Edge to be optimized; C, Observation area; D, Iterative change line of area; E, Iterative change line of objective function; a, Initial sound barrier model; b, Final optimized sound barrier model at 400Hz; c, Final optimized sound barrier model at 700Hz; d, Schematic diagram of iterative changes of objective function and area during optimization at 400Hz; e, Schematic diagram of iterative changes of objective function and area during optimization at 700Hz; f, Schematic diagram of sound pressure level change at observation point at 400Hz; g, Schematic diagram of sound pressure level change at observation point at 700Hz. Detailed Implementation

[0050] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0051] Example 1:

[0052] This embodiment relates to a sound barrier shape optimization method based on the isogeometric singular boundary method, including the following steps:

[0053] (3) Establish a geometric model: Based on the geometric parameters of the sound barrier to be optimized, establish a geometric model of the sound barrier. The geometric parameters include the width, height and position of the sound barrier in space. The geometric model is described by NURBS curves.

[0054] (4) Obtaining Boundary Points: Extract the information from the constructed geometric model and import it into the program. The program obtains the interpolation points of the geometric model boundary. These interpolation points are used as the boundary points of the singular boundary method. n nodes x are configured on the boundary of the sound barrier. i For each i = 1, 2, ..., n, the extracted geometric model information includes the coordinates of control points, weights, node vectors, and the order of the curves in the geometric model.

[0055] (3) Establish an optimization model: using the known acoustic control equations and air density of 1.29 kg / m³ 3 Based on the speed of sound in the air (340 m / s), the frequency of the sound source, the selected shape design variables, and the corresponding boundary conditions, a sound barrier shape optimization model based on the isogeometric singular boundary method is established.

[0056] (4) Find the optimal value: Using the sound barrier shape optimization model based on the isogeometric singular boundary method established in step (3), calculate the set objective function, constraints and their sensitivity to shape design variables, substitute the obtained results into the moving asymptote method for iteration, and find the optimal value.

[0057] (5) Output final shape: Output the final optimized shape of the sound barrier and evaluate the performance of the result.

[0058] The sound barrier shape optimization method based on the isogeometric singular boundary method involved in this embodiment includes the following procedure in step (2):

[0059] Substitute the control point coordinates, weights, node vectors, and curve order from the extracted geometric model into the boundary curve expression:

[0060]

[0061] Where P is the i-th control point, and n is the number of control points. For NURBS spline basis functions, N i,p (ξ) is the p-th degree B-spline basis function, ω i Let ξ be the weight of the i-th control point, and ξ be the coordinates in the parameter space.

[0062] The sound barrier shape optimization method based on the isogeometric singular boundary method involved in this embodiment uses the acoustic control equation in step (3) as follows:

[0063]

[0064] in For the Laplace operator, Let ω be the wave number, ω = 2πf be the angular frequency, c be the speed of sound, f be the frequency, Ω represent the sound field region, x be the spatial coordinate, and p(x) be the sound pressure amplitude at x.

[0065] For the above governing equations, the Dirichlet conditions and Newman boundary conditions are usually considered:

[0066] p(x)=(x),x∈Γ p

[0067]

[0068] in For the boundary Γ p The known sound pressure level above, For the boundary Γ v The known normal velocity on the surface, ρ is the density of air.

[0069] The sound barrier shape optimization method based on the isogeometric singular boundary method involved in this embodiment includes the following steps in step (3) of establishing the isogeometric singular boundary optimization model:

[0070] (31) Define the objective function and constraints, select shape design variables, give their upper and lower limits, set the maximum number of iterations and convergence parameters, where the objective function is set as the total sound pressure in the observation area, and the observation area is specifically selected according to the actual situation.

[0071] (32) Representing the numerical solution at each boundary point as a linear summation of the fundamental solutions, the fundamental solution corresponding to the two-dimensional Helmholtz equation is:

[0072]

[0073] in It is a zeroth-order Hankel function of the first kind, ||xs||² is the distance between the field point x and the source point s, and s' is the mirror image of the source point s with respect to the ground. Combining all the equations, we obtain the linear equation system of the singular boundary method:

[0074]

[0075] Right now:

[0076] Aα=b

[0077] in:

[0078]

[0079] (33) Since the source point and field point coincide in the singular boundary method, the diagonal of this system of equations will exhibit singularity. Therefore, a source point intensity factor is introduced:

[0080]

[0081]

[0082] Where γ is Euler's constant. L is a fundamental solution to the Laplace equation. j Represents the source point s j The range of influence, i.e., the source point s on the physical boundary. j-1 and source point s j+1 The semi-circular length between them.

[0083] The sound barrier shape optimization method based on the isogeometric singular boundary method involved in this embodiment, wherein the specific method for calculating the set objective function, constraints and their sensitivity with respect to the shape design variables in step (4) is as follows:

[0084] Solve the system of linear equations established in step (3) to obtain all source point densities α, and then calculate the function value at any point in the domain according to the following equation:

[0085] x∈Ω,s j ∈Γ

[0086] Calculate the set objective function, constraints, and their sensitivity to shape design variables.

[0087] The moving asymptote method involved in this embodiment is a numerical optimization algorithm for nonlinear optimization problems. This algorithm has been widely applied in engineering design, structural optimization, machine learning, and other fields. It employs a moving asymptote strategy for optimization. It transforms the objective function and constraints into corresponding parameter functions. In each iteration, based on the current values ​​of the design variables and the parameter functions, the values ​​of the parameter functions are updated, ensuring that the parameter functions achieve their minimum values ​​while satisfying the constraints. Thus, within a certain number of iterations, the moving asymptote method can gradually narrow the range of design variable values ​​until a preset accuracy requirement is met.

[0088] This embodiment involves a sound barrier shape optimization method based on the isogeometric singular boundary method. In step (5), the optimization effect of the sound barrier is mainly measured by the change in sound pressure or sound pressure level at the observation points in the observation area. A line graph is plotted on the change in sound pressure level at the observation points in the observation area in step (4). If the sound pressure level generally decreases, the optimization effect is significant; if no significant change is observed, the optimization effect is poor.

[0089] Example 2:

[0090] This embodiment relates to specific information on a sound barrier shape optimization method based on the isogeometric singular boundary method, with an air density of 1.29 kg / m³. 3 The speed of sound in air is 340 m / s, such as Figure 2 As shown, the width of a certain vertical sound barrier is L. x =0.2m, height is L y =3m. The NURBS information of this upright sound barrier model is shown in Table 1. Point sound source A is placed at a height of 1m above the ground. Assuming that both the ground and the sound barrier boundary are Newman boundary conditions, the objective function is defined as minimizing the total sound pressure value of all observation points in the observation area C. The constraint is defined as the area constraint of the sound barrier. The left boundary of the sound barrier is selected as the edge to be optimized, B. Fifteen new control points are inserted between control points P5 and P6 through h refinement. The horizontal coordinates of these 15 control points are used as shape design variables, with an upper limit of 5.1 and a lower limit of 4.9. The convergence parameter is set to 10. -4 The maximum number of iterations is 50. An optimization model based on the singular boundary method with equal geometry is established to optimize the sound barrier.

[0091] Table 1:

[0092]

[0093] Figure 3 The final optimization models b and c for the sound barrier at 400Hz and 700Hz are given respectively. Figure 4 The iterative variation curves d and e of the objective function and area at frequencies of 400 Hz and 700 Hz are given. Figure 5 As shown, the sound pressure levels at the observation points at both 400Hz and 700Hz frequencies were significantly reduced after optimization.

Claims

1. A method for optimizing the shape of a sound barrier based on the isogeometric singular boundary method, characterized in that, Includes the following steps: (1) Establish a geometric model: Based on the geometric parameters of the sound barrier that need to be optimized, establish a geometric model of the sound barrier; (2) Obtaining boundary points: Extract the information of the constructed geometric model and import the information into the program. Obtain the interpolation points of the geometric model boundary through the program. Use these interpolation points as the boundary points of the singular boundary method and configure them on the boundary of the sound barrier. Nodes ; (3) Establish an optimization model: Using the known acoustic control equations, air density, sound speed in the air, frequency of the sound source, as well as the selected shape design variables and corresponding boundary conditions, establish a sound barrier shape optimization model based on the isogeometric singular boundary method. (4) Find the optimal value: Using the sound barrier shape optimization model based on the isogeometric singular boundary method established in step (3), calculate the set objective function, constraints and their sensitivity with respect to the shape design variables, substitute the obtained results into the moving asymptote method for iteration, and find the optimal value. (5) Output final shape: Output the final optimized shape of the sound barrier and evaluate the performance of the results; The steps in step (3) of establishing the optimization model for the singular boundary with equal geometry include: (31) Define the objective function and constraints, select shape design variables, give their upper and lower limits, set the maximum number of iterations and convergence parameters, where the objective function is set as the total sound pressure in the observation area, and the observation area is specifically selected according to the actual situation; (32) Representing the numerical solution at each boundary point as a linear summation of the fundamental solutions, the fundamental solution corresponding to the two-dimensional Helmholtz equation is: in It is a zeroth-order Hankel function of the first kind. It is a venue With the source The distance between them It is the source point Regarding the mirror point on the ground, arrive The combination of , Given the source point density, combining all the equations yields the linear equation system of the singular boundary method: Right now: in: ； (33) Since the source point and field point coincide in the singular boundary method, the diagonal of this system of equations will exhibit singularity. Therefore, a source point intensity factor is introduced: in Let Euler's constant be 1. This is a fundamental solution to the Laplace equation. Represents the source point The range of influence, i.e., the source point on the physical boundary. and source point The semi-circular length between them.

2. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The geometric parameters mentioned in step (1) include the width, height, and position of the sound barrier in space.

3. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The geometric model described in step (1) is described by NURBS curves.

4. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The procedure described in step (2) is as follows: Substitute the control point coordinates, weights, node vectors, and curve order from the extracted geometric model into the boundary curve expression: in Let n be the i-th control point, and n be the number of control points. For NURBS spline basis functions, Let p be the B-spline basis functions. Let i be the weight of the i-th control point. These are the coordinates in the parameter space.

5. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The information of the extracted geometric model mentioned in step (2) includes the coordinates of the control points, weights, node vectors, and order of the curves in the geometric model.

6. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The acoustic control equation used in step (3) is: in For the Laplace operator, For wave number, Angular frequency, For the speed of sound, For frequency, Indicates the sound field region. For spatial coordinates, for The sound pressure amplitude at that location; For the above governing equations, the Dirichlet conditions and Newman boundary conditions are usually considered: in For the boundary The known sound pressure level above, For the boundary The known normal velocity on the surface, , For the density of air, Let x be the normal vector at point x.

7. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The air density mentioned in step (3) is The speed of sound in air is .

8. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The specific method for calculating the set objective function, constraints, and their sensitivity to shape design variables in step (4) is as follows: Solve the linear equation system established in step (3) to obtain all source point densities. Then, the function value at any point in the domain is calculated according to the following equation: Calculate the set objective function, constraints, and their sensitivity to shape design variables.

9. The sound barrier shape optimization method based on the isogeometric singular boundary method according to claim 1, characterized in that: The optimization effect of the sound barrier in step (5) is measured by the change in sound pressure or sound pressure level at the observation point in the observation area. Plot the change in sound pressure level at the observation point in the observation area in step (4) as a line graph and observe the change. If the sound pressure level generally decreases, the optimization effect is significant; if no significant change is observed, the optimization effect is poor.

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