WO2024011510A1

WO2024011510A1 - Sound pressure evaluation method and apparatus based on model order reduction boundary element method, and terminal device

Info

Publication number: WO2024011510A1
Application number: PCT/CN2022/105755
Authority: WO
Inventors: 谢祥
Original assignee: 中国科学院深圳先进技术研究院
Priority date: 2022-07-14
Filing date: 2022-07-14
Publication date: 2024-01-18

Abstract

A sound pressure evaluation method based on a model order reduction boundary element method, comprising: acquiring a model to be evaluated and a frequency domain of interest corresponding thereto (101); performing order reduction on the model to be evaluated, so as to generate a low-dimensional reduced-order model corresponding to the model to be evaluated (102); and performing frequency sweep computation on the low-dimensional reduced-order model on the basis of the frequency domain of interest, so as to generate a sound pressure evaluation result in the frequency domain of interest that is corresponding to the model to be evaluated (103). Sound pressure evaluation efficiency is improved. Further provided are a sound pressure evaluation apparatus based on a model order reduction boundary element method, a terminal device and a computer-readable storage medium.

Description

Sound pressure assessment method, device and terminal equipment based on model reduced order boundary element method

Technical field

This application belongs to the field of acoustic technology, and in particular relates to sound pressure assessment methods, devices, terminal equipment and storage media based on the model-reduced-order boundary element method.

Background technique

With the development of modern society, the dynamics and acoustic quality of structural systems have become important performance evaluation indicators in the fields of aerospace, military equipment, transportation, and the built environment, such as noise prediction of launch vehicle fairings and acoustic stealth of ships. performance, ride comfort of large aircraft/high-speed trains/cars, noise control of wind turbines, etc. Therefore, conducting acoustic calculations and studying acoustic characteristics of complex structures has very important theoretical analysis value and practical application significance. It is an indispensable link in noise level prediction and a prerequisite for achieving optimal acoustic performance design.

technical problem

In related technologies, since the structures of objects that need to be analyzed for acoustic problems are usually very complex, the amount of storage and calculation required for analyzing acoustic problems is too large, and the efficiency of sound pressure assessment is low.

Technical solutions

The embodiments of this application provide sound pressure assessment methods, devices, terminal equipment and storage media based on the model-reduced-order boundary element method, which can solve the problem in related technologies that objects that need to be analyzed for acoustic problems are usually very complex in structure, resulting in When analyzing acoustic problems, the amount of storage and calculation is too large, and the efficiency of sound pressure assessment is low.

A first aspect of the embodiment of the present application provides a sound pressure assessment method based on the model reduced-order boundary element method. The sound pressure assessment method based on the model-reduced boundary element method includes:

Obtain the model to be evaluated and its corresponding frequency domain of interest;

Perform reduction processing on the model to be evaluated to generate a low-dimensional reduced-order model corresponding to the model to be evaluated;

Frequency sweep calculation is performed on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.

A second aspect of the embodiment of the present application provides a sound pressure evaluation device based on the model reduced-order boundary element method. The sound pressure evaluation device based on the model-reduced boundary element method includes:

The acquisition module is used to obtain the model to be evaluated and its corresponding frequency domain of interest;

An order reduction module, used to perform order reduction processing on the model to be evaluated to generate a low-dimensional reduced order model corresponding to the model to be evaluated;

A frequency sweep module is configured to perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.

A third aspect of the embodiment of the present application provides a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program When realizing the sound pressure assessment method based on the model-reduced-order boundary element method described in the first aspect above.

A fourth aspect of the embodiments of the present application provides a computer-readable storage medium that stores a computer program. When the computer program is executed by a processor, the model-based reduction described in the first aspect is implemented. Sound pressure evaluation method using the first-order boundary element method.

The fifth aspect of the embodiments of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device executes the model-based reduced-order boundary element method described in the first aspect. Sound pressure assessment methods.

beneficial effects

Compared with the existing technology, the beneficial effects of the embodiments of the present application are: by obtaining the model to be evaluated and its corresponding frequency domain of interest, and performing reduction processing on the model to be evaluated, to generate a low-dimensional reduced order corresponding to the model to be evaluated. model, and then perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate the sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest. Therefore, by reducing the order of the model to be evaluated, the model to be evaluated is simplified, and the dimension of the system equation to be evaluated formed by the large-scale model to be evaluated is reduced, thereby reducing the memory requirements during the frequency sweep process and improving the efficiency of the frequency sweep. The calculation efficiency of the analysis is improved, thereby improving the efficiency of sound pressure assessment.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the purpose of the present application. For some embodiments, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting creative efforts.

Figure 1 is a schematic flow chart of a sound pressure assessment method based on the model-reduced-order boundary element method provided by an embodiment of the present application;

Figure 2 is a schematic flow chart of a sound pressure assessment method based on the model-reduced-order boundary element method provided by another embodiment of the present application;

Figure 3 is a grid diagram of a partial area of the model to be evaluated provided by an embodiment of the present application;

Figure 4 is a schematic structural diagram of a sound pressure evaluation device based on the model-reduced-order boundary element method provided by an embodiment of the present application;

Figure 5 is a schematic structural diagram of a terminal device provided by an embodiment of the present application.

Embodiments of the invention

In the following description, for the purpose of explanation rather than limitation, specific details such as specific system structures and technologies are provided to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It will be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and/or components but does not exclude one or more other The presence or addition of features, integers, steps, operations, elements, components and/or collections thereof.

It will also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "once" or "in response to determining" or "in response to detecting" depending on the context. ". Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, to mean "once determined" or "in response to a determination" or "once the [described condition or event] is detected ]" or "in response to detection of [the described condition or event]".

In addition, in the description of this application and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

Reference in this specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Therefore, the phrases "in one embodiment", "in some embodiments", "in other embodiments", "in other embodiments", etc. appearing in different places in this specification are not necessarily References are made to the same embodiment, but rather to "one or more but not all embodiments" unless specifically stated otherwise. The terms “including,” “includes,” “having,” and variations thereof all mean “including but not limited to,” unless otherwise specifically emphasized.

It should be understood that the sequence number of each step in this embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

In related technologies, since the structures of objects that need to be analyzed for acoustic problems are usually very complex, the amount of storage and calculation required for acoustic problem analysis is too large, and the efficiency of sound pressure assessment is low.

This application provides a sound pressure assessment method based on the model-reduced-order boundary element method. It can obtain the model to be evaluated and its corresponding frequency domain of interest, and perform reduction processing on the model to be evaluated to generate the model corresponding to the model to be evaluated. The low-dimensional reduced-order model is then used to perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate the sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest. Therefore, by reducing the order of the model to be evaluated, the model to be evaluated is simplified, and the dimension of the system equation to be evaluated formed by the large-scale model to be evaluated is reduced, thereby reducing the memory requirements during the frequency sweep process and improving the efficiency of the frequency sweep. The calculation efficiency of the analysis is improved, thereby improving the efficiency of sound pressure assessment.

In one embodiment, referring to Figure 1, a sound pressure assessment method based on the model-reduced-order boundary element method is provided. This method is explained by taking the method applied to a terminal as an example, and includes the following steps:

Step 101: Obtain the model to be evaluated and its corresponding frequency domain of interest.

Among them, the model to be evaluated can be a sound field model to be evaluated for sound pressure, such as drawing a two-dimensional or three-dimensional structure model diagram through drawing software, such as: AutoCAD (Autodesk Computer Aided Design, automatic computer-aided design software).

The frequency domain of interest can be a preset frequency range or frequency point for frequency response analysis. In actual use, the frequency domain of interest can be set according to the requirements of sound pressure evaluation, such as 11Hz-1000Hz, which is not limited in the embodiments of the present application.

In the embodiment of the present application, the actual sound pressure assessment scenario can be used in advance to draw the corresponding model to be evaluated in the scenario through drawing software, and the frequency domain of interest can be preset based on the noise frequency range involved in the scenario.

For example, when the sound pressure evaluation scenario in the embodiment of the present application is to study the acoustic characteristics of an aircraft, CAD drawing software can be used to draw the sound field model of the aircraft as the model to be evaluated, and then based on the actual noise frequency generated by the aircraft in actual applications Range, preset frequency domain of interest.

Step 102: Perform reduction processing on the model to be evaluated to generate a low-dimensional reduced-order model corresponding to the model to be evaluated.

In a possible implementation of the embodiment of the present application, the low-dimensional reduced-order model uses Taylor's theorem to expand the acoustic boundary element kernel function, and then based on the characteristic that the amplitude of the boundary element kernel function attenuates with distance, according to the preset cutoff radius Construct a sparse system matrix to quickly generate an orthogonal basis, that is, for each source point, only select a few nearby strong interaction points for integral calculation, forming a large-scale sparse rather than dense system matrix, so It avoids the need to store and solve the original large-scale full-order model for traditional model reduction. After forming the global orthogonal basis, the system matrix is formed column by column and projected onto the global orthogonal basis by considering the interaction between the source point and the collocation points on all boundaries. A low-dimensional reduced-order model is obtained from the formed subspace, and this process consumes low memory.

Step 103: Perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.

In the embodiment of this application, frequency sweep calculation is performed on the low-dimensional reduced-order model through the frequency domain of interest, and the low-dimensional reduced-order model is solved to obtain the corresponding sound pressure evaluation result of the corresponding model to be evaluated in the frequency domain of interest.

As an example, the sound pressure evaluation result can be the sound pressure value of each configuration point of the model to be evaluated; or, the sound pressure value of each configuration point of the model to be evaluated can be further analyzed to generate the corresponding sound intensity or sound pressure level. Wait for data.

As an example, the sound pressure evaluation results can also be visualized and displayed in each boundary unit of the model to be evaluated according to the sound pressure value of each configuration point, so as to clearly and directly see the sound pressure value of each area of the model to be evaluated. Sound pressure conditions.

It can be understood that by using the generated low-dimensional reduced-order model to perform frequency sweep calculations, the integral calculation only needs to be performed once for the entire frequency range considered. Therefore, the calculation efficiency is improved compared to the traditional method. The reduced-order model is much smaller than The dimensions of the original full-order model in the prior art, so the frequency sweep calculation solution can obtain results almost in real time.

In the above-mentioned sound pressure assessment method based on the model-reduced boundary element method, a low-dimensional reduced-order model corresponding to the model to be evaluated is generated by obtaining the model to be evaluated and its corresponding frequency domain of interest, and performing reduction processing on the model to be evaluated. , and then perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate the sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest. Therefore, by reducing the order of the model to be evaluated, the model to be evaluated is simplified, and the dimension of the system equation to be evaluated formed by the large-scale model to be evaluated is reduced, thereby reducing the memory requirements during the frequency sweep process and improving the efficiency of the frequency sweep. The calculation efficiency of the analysis is improved, thereby improving the efficiency of sound pressure assessment.

In one embodiment, referring to Figure 2, a schematic flow chart of another sound pressure assessment method based on the model-reduced-order boundary element method provided by the embodiment of the present application includes:

Step 201: Obtain the model to be evaluated and its corresponding frequency domain of interest.

For the specific implementation process and principle of the above step 201, reference can be made to the detailed description of the above embodiments and will not be described again here.

Step 202: Divide the boundaries of the model to be evaluated to generate a grid diagram corresponding to the model to be evaluated, where the grid diagram includes multiple boundary units, and each boundary unit has a corresponding configuration point.

Among them, dividing the boundaries of the model to be evaluated may be dividing units on the boundaries of the definition domain. The boundary element may refer to a unit formed by meshing the surface of the three-dimensional model to be evaluated, or may refer to a unit formed by meshing the envelope of the two-dimensional model to be evaluated.

For example, as shown in Figure 3, it is a local grid diagram corresponding to a model to be evaluated provided by an embodiment of the present application. In this example, the model to be evaluated is a three-dimensional model to be evaluated. The grid diagram shown in Figure 3 is the result of dividing part of the surface of the model to be evaluated. Each triangular area in Figure 3 is a boundary unit. , the dot or circle in each boundary unit is the corresponding matching point of the boundary unit.

Step 203: Determine the strong interaction unit corresponding to each boundary unit based on the coordinates of each boundary unit and the preset cutoff radius.

Among them, the preset cutoff radius can be determined based on the average unit area of all boundary units. It can be understood that for a model diagram with a two-dimensional structure to be evaluated, the preset truncation radius may be a circle radius; for a three-dimensional structure model to be evaluated, the preset truncation radius may be a spherical radius. In actual use, the preset truncation radius can also be selected according to other methods, which is not limited in the embodiments of the present application.

For example, the preset cutoff radius can be based on

Determine, where R is the preset cutoff radius, A _i is the area of the i-th boundary unit in the grid diagram, mean(A _i ) is the average area of all boundary element triangle grids, and i is the boundary in the grid diagram The serial number of the unit.

It should be noted that the above examples are only illustrative and cannot be regarded as limiting the present application. In actual use, the preset truncation radius can be set according to actual needs and specific application scenarios, which is not limited in the embodiments of the present application.

It can be understood that based on the characteristic that the boundary element kernel function attenuates with distance, that is, the amplitude of the three-dimensional acoustic boundary element kernel function decreases in inverse proportion with the increase in distance, that is, 1/r; while the amplitude of the two-dimensional acoustic boundary element kernel function It decreases inversely with the increase of the 1/2 power of the distance, that is,

Among them, r is the distance between the source point of the boundary element and other configuration points, that is to say, the farther the distance between the source point and other configuration points, the weaker the interaction between the source point and other configuration points; conversely, the source point The closer the distance to other configuration points, the stronger the interaction between the source point and other configuration points. This relationship causes many elements in the system matrix to be non-zero, but have small amplitudes. Therefore, for each boundary unit , place a matching point in the center of the unit, and then divide the entire grid around this matching point and the preset cutoff radius into: strong interaction units and weak interaction units.

As a possible implementation method, the k-d tree search algorithm can be used to traverse each boundary unit in the grid diagram corresponding to the model to be evaluated, and determine each boundary based on the coordinates of each boundary unit and the preset truncation radius. Strongly interactive unit corresponding to the unit, where k-d tree (abbreviation of k-dimensional tree) is a data structure that organizes points in k-dimensional Euclidean space.

Further, the boundary unit whose distance from the current source point is less than or equal to a preset cutoff radius may be determined as the strong interaction unit corresponding to the current source point. That is, in a possible implementation manner of the embodiment of this application, the above step 203 may include:

Traverse the configuration points of each boundary unit as the current source point;

When the distance between the matching point of any boundary unit in the grid diagram and the current source point is less than or equal to the preset cutoff radius, any boundary unit is determined as the strongly interacting unit of the current source point.

As an example, referring to Figure 3, with the current source point as the center, select the matching point of the boundary unit whose distance from the current source point is less than or equal to the preset truncation radius. The boundary unit corresponding to the matching point is the boundary unit of the current source point. A strong interaction unit is a matching point of a boundary unit whose distance from the current source point is greater than the preset cutoff radius. The corresponding boundary unit is a weak interaction unit of the current source point.

Step 204: Determine the sparse system matrix corresponding to the model to be evaluated based on each boundary unit and the strong interaction unit corresponding to each boundary unit.

In the embodiment of the present application, for each boundary unit, since the interaction between the boundary unit and its corresponding strong interaction unit is strong and the correlation between its corresponding weak interaction unit is weak, it can be selected The strong interaction unit constructs the system matrix corresponding to the model to be evaluated, and the weak interaction unit is discarded. There is no need to calculate the weak interaction unit, thereby generating a sparse system matrix corresponding to the model to be evaluated. Compared with the traditional model in the existing technology, the order is reduced. The orthogonal basis construction process reduces the memory space and calculation amount required for the orthogonal basis construction process.

Further, the sparse system matrix corresponding to the model to be evaluated can be determined through integration. That is, in a possible implementation of the embodiment of the present application, the above step 204 may include:

According to the distance between the configuration point of each boundary unit and the corresponding configuration point of each strong interaction unit, the basic solution after Taylor expansion is integrated to generate a sparse system matrix corresponding to the model to be evaluated.

Among them, the basic solution after Taylor expansion can be Taylor expansion of the basic solution of two-dimensional or three-dimensional acoustic problems, so that the frequency domain and space domain are decoupled. The number of Taylor expansion terms of the basic solution obtained is determined by the remaining terms, that is, it depends on Depending on the size of the model considered and the frequency range considered.

It should be understood that the sparse system matrix corresponding to the model to be evaluated is generated by integrating based on the basic solution after Taylor expansion. Therefore, the sparse system matrix corresponding to the model to be evaluated is a sparse system matrix that is independent of frequency. Therefore, in the considered frequency range, the integral calculation only needs to be performed once, while the existing technology requires an integral calculation once for each frequency point of interest in the frequency domain of interest. Therefore, the calculation efficiency is improved compared to the existing technology.

It can be understood that determining the sparse system matrix corresponding to the model to be evaluated based on the strong interaction unit corresponding to each boundary unit reduces the computational complexity of solving the system matrix, and only needs to store and solve the sparse approximation of the original large-scale dense matrix. Matrix, reducing the memory requirements of the calculation process.

Step 205: Determine the global orthogonal basis of the sparse system matrix and the frequency expansion point, where the frequency expansion point is selected from the frequency domain of interest.

Among them, the frequency expansion point can be a frequency point selected in advance from the frequency domain of interest; it can also be automatically selected through the adaptive process; or it can be set by the user according to actual usage requirements. In actual use, the number of frequency expansion points can be selected according to actual conditions, such as 3, 5, etc., which is not limited in the embodiments of the present application.

As a possible implementation method, the orthogonal basis of the sparse system matrix and each frequency expansion point can be determined first, and then the global orthogonal basis can be determined based on the local orthogonal basis of the sparse system matrix and each frequency expansion point. That is, the above step 205 may include:

Determine the local orthogonal basis of each frequency spread point and the sparse system matrix;

Orthogonalize each local orthogonal basis to generate a global orthogonal basis.

Among them, the local orthogonal basis can be an orthogonal basis constructed from a frequency expansion point and a sparse system matrix. The orthogonal basis is the result of pairwise orthogonality of elements. Then, by orthogonalizing each local orthogonal basis, a global orthogonal basis can be generated.

As an example, the second-order Arnoldi method can be used to determine the local orthogonal basis of each frequency expansion point and the sparse system matrix, whose dimensions are determined by the condition number of the upper Hessenberg matrix (ie: Heisenberg matrix).

It should be understood that constructing an orthogonal basis is not limited to the second-order Arnoldi method. The traditional Proper Orthogonal Decomposition (POD) method can also be used. The calculation principles are the same and will not be described again here.

In one embodiment, orthogonalizing each local orthogonal basis to generate a global orthogonal basis may include:

Perform singular value decomposition on each local orthogonal basis to generate a global orthogonal basis.

Among them, singular value decomposition can decompose features on any matrix.

Step 206: Use the configuration point of each boundary unit as a source point in turn, and integrate the basic solution after Taylor expansion according to the distance between the source point and the configuration point of each boundary unit in the grid diagram. To generate a column vector corresponding to each boundary unit.

It should be understood that the column vector corresponding to each boundary unit is generated by integrating based on the basic solution after Taylor expansion. Therefore, the column vector corresponding to each boundary unit is a column vector independent of frequency. Therefore, in the considered frequency range, the integral calculation only needs to be performed once, while the existing technology requires an integral calculation once for each frequency point of interest in the frequency domain of interest. Therefore, the calculation efficiency is improved compared to the existing technology.

Step 207: Project the column vector corresponding to each boundary unit into the subspace spanned by the global orthogonal basis to generate a low-dimensional reduced-order model.

Among them, the column vector corresponding to each boundary unit can be projected into the subspace spanned by the global orthogonal basis in a column-by-column assembly projection manner.

It should be noted that the strong interaction unit corresponding to each boundary unit is determined through the preset truncation radius, and then the sparse system matrix corresponding to the model to be evaluated is determined based on the strong interaction unit corresponding to each boundary unit. When solving the global orthogonal basis It is no longer necessary to store and solve the original large-scale full-order model. Instead, only the sparse approximation matrix of the original large-scale dense matrix is stored and solved, which reduces the memory requirements of the calculation process.

Further, the above step 207 may include:

Traverse the source points of each boundary unit, and left-project the column vector formed by the source point of each boundary unit and all configuration points into the subspace formed by the global orthogonal basis, until the source points of all boundary units are traversed; The matrix obtained by column left projection is right projected into the subspace spanned by the global orthogonal basis to generate a low-dimensional reduced-order model.

As a possible implementation, every time a column vector corresponding to a boundary unit is generated, the column vector is left-projected into the subspace spanned by the global orthogonal basis; the collocation points that traverse other boundary units are returned as source points for the grid The collocation points of all boundary units in the figure are integrated to generate the column vector corresponding to each boundary unit, and then the column vector is left-projected into the subspace formed by the global orthogonal basis; until the column vectors corresponding to all boundary units are After the projection is completed, all column vectors are left-projected to obtain the matrix and right-projected into the subspace spanned by the global orthogonal basis to generate a low-dimensional reduced-order model. The entire process does not form a dense matrix, which reduces memory requirements and eliminates the need for storage. By calculating the original large-scale full-order model, the calculation efficiency is further improved, and larger-scale acoustic boundary element problems can be solved.

Step 208: Perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.

For the specific implementation process and principle of the above step 208, reference can be made to the detailed description of the above embodiments and will not be described again here.

In the above-mentioned sound pressure assessment method based on the model-reduced-order boundary element method, the model to be evaluated and its corresponding frequency domain of interest are obtained, and a grid diagram corresponding to the model to be evaluated is generated, and then according to the coordinates of each boundary unit and The preset truncation radius is used to determine the strong interaction unit corresponding to each boundary unit, and then the sparse system matrix corresponding to the model to be evaluated is constructed through the strong interaction unit, and then the local orthogonal basis of the sparse system matrix and the frequency expansion point is determined, and through the All local orthogonal bases are orthogonalized to obtain the global orthogonal base. The configuration points of each boundary unit are used as source points to integrate the configuration points of all boundary units in the grid diagram to generate the column vector corresponding to each boundary unit. Then, the column vector corresponding to each boundary unit is projected into the subspace spanned by the global orthogonal basis to generate a low-dimensional reduced-order model, and then a frequency sweep calculation is performed on the low-dimensional reduced-order model according to the frequency domain of interest to generate The corresponding sound pressure evaluation results of the model to be evaluated in the frequency domain of interest. Therefore, through the preset truncation radius, a sparse system matrix corresponding to the model to be evaluated is constructed for the construction of the local orthogonal basis, and the second-order Arnoldi method is selected to construct the local orthogonal basis. Compared with the traditional model reduction method, The process of constructing an orthogonal basis reduces the memory space and calculation amount required to construct an orthogonal basis. Then, based on the constructed global orthogonal basis, the model to be evaluated can be quickly reduced in order, simplifying the model to be evaluated and reducing the cost of large-scale The dimension of the system equation to be evaluated formed by the model to be evaluated reduces the memory requirements during the frequency sweep process, improves the calculation efficiency of frequency sweep analysis, and thereby improves the efficiency of sound pressure evaluation.

It should be understood that although the various steps in the flowcharts of Figures 1-2 are shown in sequence as indicated by arrows, these steps are not necessarily executed in the order indicated by arrows. Unless explicitly stated in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in Figures 1-2 may include multiple steps or stages. These steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution of these steps or stages The sequence is not necessarily sequential, but may be performed in turn or alternately with other steps or at least part of steps or stages in other steps.

In one embodiment, as shown in Figure 4, a sound pressure evaluation device based on the model-reduced-order boundary element method is provided. The device can adopt a software module or a hardware module, or a combination of the two to become part of a computer device. , the device specifically includes: an acquisition module 410, an order reduction module 420 and a frequency sweep module 430, wherein:

The acquisition module 410 is used to acquire the model to be evaluated and its corresponding frequency domain of interest.

The order reduction module 420 is used to reduce the order of the model to be evaluated, so as to generate a low-dimensional reduced order model corresponding to the model to be evaluated.

The frequency sweep module 430 is used to perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.

In one embodiment, the order reduction module 420 is also used to: divide the boundaries of the model to be evaluated to generate a grid diagram corresponding to the model to be evaluated, wherein the grid diagram includes multiple boundary units, each boundary unit having Corresponding configuration points; determine the strong interaction unit corresponding to each boundary unit based on the coordinates of each boundary unit and the preset cutoff radius; determine the model to be evaluated based on each boundary unit and the strong interaction unit corresponding to each boundary unit The corresponding sparse system matrix; determine the local orthogonal basis of the sparse system matrix and the frequency extension point, and orthogonalize all local orthogonal basis to obtain the global orthogonal basis, where the frequency extension point is selected from the frequency domain of interest ; Use the configuration point of each boundary unit as a source point in turn, and integrate the basic solution after Taylor expansion according to the distance between the source point and the configuration point of each boundary unit in the grid diagram to generate The column vector corresponding to each boundary unit; project the column vector corresponding to each boundary unit into a subspace spanned by a global orthogonal basis to generate a low-dimensional reduced-order model.

In one embodiment, the order reduction module 420 is also used to: traverse the configuration points of each boundary unit as the current source point; the distance between the configuration point of any boundary unit in the grid diagram and the current source point is less than or equal to a predetermined value. If the truncation radius is set, any boundary unit is determined as the strong interaction unit of the current source point.

In one embodiment, the order reduction module 420 is also used to perform the following steps on the basic solution after Taylor expansion based on the distance between the configuration point of each boundary unit and the corresponding configuration point of each strong interaction unit. Integrate to generate a sparse system matrix corresponding to the model to be evaluated.

In one embodiment, the order reduction module 420 is also used to: traverse the source points of each boundary unit, and left-project the column vector formed by the source point of each boundary unit and all configuration points to the subspace spanned by the global orthogonal basis. , until the source points of all boundary units are traversed; the matrix obtained by column-by-column left projection is right-projected into the subspace spanned by the global orthogonal basis to generate a low-dimensional reduced-order model.

In one embodiment, the order reduction module 420 is also used to: determine the local orthogonal basis of each frequency expansion point and the sparse system matrix; orthogonalize each local orthogonal basis to generate the global orthogonal basis.

In one embodiment, the order reduction module 420 is also used to perform singular value decomposition on each local orthogonal basis to generate a global orthogonal basis.

Among them, the preset cutoff radius is determined based on the average area of all boundary cells.

Regarding the specific limitations of the sound pressure evaluation device based on the model-reduced boundary element method, please refer to the limitations on the sound pressure evaluation method based on the model-reduced boundary element method mentioned above, which will not be described again here. Each module in the above-mentioned sound pressure evaluation device based on the model-reduced-order boundary element method can be implemented in whole or in part by software, hardware, and combinations thereof. Each of the above modules may be embedded in or independent of the processor of the computer device in the form of hardware, or may be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, FIG. 5 is a schematic structural diagram of a terminal device provided by this application. As shown in Figure 5, the terminal device 700 of this embodiment includes: at least one processor 710 (only one is shown in Figure 5), a memory 720, and a processor stored in the memory 720 and capable of processing in the at least one The computer program 721 runs on the processor 710. When the processor 710 executes the computer program 721, the steps in the above sound pressure assessment method embodiment based on the model reduced-order boundary element method are implemented.

The terminal device 700 may be a computing device such as a desktop computer, a notebook, a handheld computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 710 and a memory 720 . Those skilled in the art can understand that FIG. 5 is only an example of the terminal device 700 and does not constitute a limitation on the terminal device 700. It may include more or fewer components than shown in the figure, or some components may be combined, or different components may be used. , for example, it may also include input and output devices, network access devices, etc.

The so-called processor 710 can be a central processing unit (Central Processing Unit, CPU). The processor 710 can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit). , ASIC), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

The memory 720 may be an internal storage unit of the terminal device 700 in some embodiments, such as a hard disk or memory of the terminal device 700 . In other embodiments, the memory 720 may also be an external storage device of the terminal device 700, such as a plug-in hard disk, a smart memory card (SMC), or a secure digital card equipped on the terminal device 700. (Secure Digital, SD) card, flash card (Flash Card), etc. Further, the memory 720 may also include both an internal storage unit of the terminal device 700 and an external storage device. The memory 720 is used to store operating systems, application programs, boot loaders (Boot Loaders), data, and other programs, such as program codes of the computer programs. The memory 720 can also be used to temporarily store data that has been output or is to be output.

Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above functional units and modules is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs. Module completion means dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be hardware-based. It can also be implemented in the form of software functional units. In addition, the specific names of each functional unit and module are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present application. For the specific working processes of the units and modules in the above system, please refer to the corresponding processes in the foregoing method embodiments, and will not be described again here.

In the above embodiments, each embodiment is described with its own emphasis. For parts that are not detailed or documented in a certain embodiment, please refer to the relevant descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/terminal equipment and methods can be implemented in other ways. For example, the device/terminal equipment embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units. Or components can be combined or can be integrated into another system, or some features can be omitted, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units.

If the integrated module/unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the processes in the methods of the above embodiments, which can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer can When the program is executed by the processor, the steps of each of the above method embodiments can be implemented. Wherein, the computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (Read-Only Memory, ROM) , Random Access Memory (RAM), electrical carrier signals, telecommunications signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately added or deleted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium Excludes electrical carrier signals and telecommunications signals.

This application implements all or part of the processes in the methods of the above embodiments, and can also be completed through a computer program product. When the computer program product is run on a terminal device, the above methods can be implemented when the terminal device executes it. Steps in Examples.

The above-described embodiments are only used to illustrate the technical solution of the present application, but are not intended to limit it. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent substitutions for some of the technical features; and these Modifications or substitutions will not deviate from the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of this application, and shall be included in the protection scope of this application.

Claims

A sound pressure assessment method based on the model-reduced-order boundary element method, which is characterized by including:

Obtain the model to be evaluated and its corresponding frequency domain of interest;

Perform reduction processing on the model to be evaluated to generate a low-dimensional reduced-order model corresponding to the model to be evaluated;

Frequency sweep calculation is performed on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.
The sound pressure assessment method based on the model-reduced boundary element method according to claim 1, characterized in that the model to be evaluated is subjected to order reduction processing to generate a low-dimensional reduced-order model corresponding to the model to be evaluated. Models, including:

Divide the boundaries of the model to be evaluated to generate a grid diagram corresponding to the model to be evaluated, wherein the grid diagram includes a plurality of boundary units, and each boundary unit has a corresponding configuration point;

Determine the strong interaction unit corresponding to each boundary unit according to the coordinates of each boundary unit and the preset cutoff radius;

Determine the sparse system matrix corresponding to the model to be evaluated according to each of the boundary units and the strong interaction unit corresponding to each of the boundary units;

Determine a global orthogonal basis of the sparse system matrix and a frequency extension point, wherein the frequency extension point is selected from the frequency domain of interest;

The configuration points of each boundary unit are used as source points in turn, and the basic solution after Taylor expansion is integrated according to the distance between the source point and the configuration points of each boundary unit in the grid diagram to generate each A column vector corresponding to the boundary unit;

Project the column vector corresponding to each boundary unit into the subspace spanned by the global orthogonal basis to generate the low-dimensional reduced-order model.
The sound pressure assessment method based on the model-reduced-order boundary element method according to claim 2, characterized in that, each boundary unit is determined based on the coordinates of each boundary unit and a preset cutoff radius. Corresponding strong interaction units include:

Traverse the matching points of each boundary unit as the current source point;

When the distance between the matching point of any boundary unit in the grid diagram and the current source point is less than or equal to the preset truncation radius, the any boundary unit is determined as the current source point. Strong interaction unit.
The sound pressure assessment method based on the model-reduced-order boundary element method according to claim 2, characterized in that, according to each of the boundary units and the strong interaction units corresponding to each of the boundary units, the Describe the sparse system matrix corresponding to the model to be evaluated, including:

According to the distance between the configuration point of each boundary unit and the corresponding configuration point of each strong interaction unit, the basic solution after Taylor expansion is integrated to generate a sparse system matrix corresponding to the model to be evaluated.
The sound pressure assessment method based on the model-reduced boundary element method according to claim 2, characterized in that the column vector corresponding to each boundary unit is projected into a subspace spanned by the global orthogonal basis. to generate the low-dimensional reduced order model, including:

Traverse the source point of each boundary unit, and left-project the column vector formed by the source point and all configuration points of each boundary unit into the subspace spanned by the global orthogonal basis until all boundary units are traversed. the source point;

Right-project the matrix obtained by column-by-column left projection into the subspace spanned by the global orthogonal basis to generate a low-dimensional reduced-order model.
The sound pressure assessment method based on the model-reduced boundary element method according to claim 2, wherein the determination of the global orthogonal basis of the sparse system matrix and the frequency expansion point includes:

Determine the local orthogonal basis of each frequency spreading point and the sparse system matrix;

Orthogonalize each local orthogonal basis to generate the global orthogonal basis.
The sound pressure assessment method based on the model-reduced-order boundary element method according to claim 6, wherein said orthogonalizing each of the local orthogonal bases to generate the global orthogonal base includes:

Singular value decomposition is performed on each local orthogonal basis to generate the global orthogonal basis.
The sound pressure evaluation method based on the model-reduced-order boundary element method according to any one of claims 2 to 7, wherein the preset cutoff radius is determined based on the average area of all boundary units.
A sound pressure evaluation device based on the model-reduced-order boundary element method, which is characterized by including:

The acquisition module is used to obtain the model to be evaluated and its corresponding frequency domain of interest;

An order reduction module, used to perform order reduction processing on the model to be evaluated to generate a low-dimensional reduced order model corresponding to the model to be evaluated;

A frequency sweep module is configured to perform frequency sweep calculation on the low-dimensional reduced-order model according to the frequency domain of interest to generate sound pressure evaluation results corresponding to the model to be evaluated in the frequency domain of interest.
A terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, it implements claims 1 to 1 The method described in any one of 8.
A computer-readable storage medium stores a computer program, characterized in that when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.