Long-channel building sound field modeling method and system based on sound infinitesimal body

Abstract

The invention discloses a long-channel building sound field modeling method and system based on an acoustic infinitesimal body, and is applied to the field of architectural acoustics. Unified modeling of different types of sound sources in a building is realized by abstracting sound transmission into a transportation process of an infinitesimal body with energy. By designing a corresponding calculation framework, the transportation process of the sound infinitesimal body can be described microcosmically, and the dynamic change of the whole sound field in the building can be described in the macroscopic level. The framework comprises a sound source model used for describing sound infinitesimal body characteristics corresponding to a sound source; the space model is used for describing the size and wall surface conditions of the building space; the probability model accelerates calculation by designing a parallel calculation strategy to obtain the transmission and redistribution probability of the acoustic infinitesimal body; the acoustic dynamics algorithm is used for calculating dynamic evolution of a sound field in the building; and finally, outputting the distribution and dynamic change of the sound field in the building. The method is simple, effective, good in robustness and wide in application prospect.

Description

Technical Field

[0001] The invention relates to a long-channel building sound field modeling method and system based on acoustic microelements, belonging to the technical field of building acoustics. Background Art

[0002] With the rapid advancement of urbanization, more and more people will live in cities, where the architectural acoustic environment is a key factor influencing spatial perception, behavioral interactions, and information transmission. Long corridors, including corridors, tunnels, and passageways, are an integral component of various building designs, from residential and commercial buildings to transportation infrastructure and urban underground spaces. However, these long corridors have unique collective characteristics, including unusual proportions (one dimension is significantly larger than the other two), open ends (tunnels, subway stations, train stations, etc.), and different cross-sections (width-to-height ratios, sound-absorbing structures). These characteristics make the analysis and optimization of the acoustic environment of long corridors challenging compared to other building structures.

[0003] Existing research methods include manual measurement using specialized sound level meters, but these methods face significant uncertainty due to noise from the instrument's own functional modules. Classic acoustic simulation methods are divided into wave-based, statistical, and geometric acoustics methods. Wave-based methods require very large computational domains (~10 m³) for long-channel buildings, consuming significant computational resources. Statistical acoustics methods assume a diffuse field, but the extreme dimensions of long-channel buildings render the diffuse field ineffective. Geometric acoustics methods typically assume simple wall conditions and fail to fully account for the multidirectional scattering effects of sound waves. This simplification can affect the accuracy of the sound field distribution in highly reflective long-channel spaces. Complete architectural acoustics simulations require consideration of multiple dynamic sound sources, typically combining a combination of these methods, but this increases computational complexity and resources. Machine learning methods rely on black-box models, which can be limited in interpretability.

[0004] Therefore, the present invention aims to propose a long-channel building sound field modeling method based on acoustic microelements to solve the problems of high complexity, computational efficiency and poor interpretability. Summary of the Invention

[0005] Objective: To solve the problem that the current sound field modeling of long channel building spaces cannot be unified, comprehensive, accurate and efficient at the same time, this paper designs a long channel building sound field modeling method based on acoustic micro-elements. By introducing the concept of acoustic micro-elements, a unified modeling of complex and diverse sound sources in long channel spaces is achieved; a sound micro-element calculation framework based on a probability model is proposed, which can accurately and efficiently solve the complex nonlinear sound field of long channel building spaces from both microscopic and macroscopic levels; in order to further improve the computational efficiency, a parallel computing strategy based on multi-core and multi-threading is proposed, which greatly improves the model calculation efficiency.

[0006] Technical solution: To solve the above technical problems, the technical solution adopted by the present invention is:

[0007] In the first aspect, a long channel building sound field modeling method based on acoustic microelement specifically includes:

[0008] Step 1: According to the medium conditions in the long channel building space and the parameters of the target sound source and background noise, the parameters of the initialization acoustic microelement are obtained.

[0009] Step 2: According to the size and wall parameters of the long channel building space, the long channel space model is meshed and the absorption, reflection and transmission parameters of each grid are defined to obtain a meshed long channel space model.

[0010] Step 3: Based on the parameters of the initialized acoustic element, calculate the migration motion of the acoustic element in the gridded long channel space model and the collision between the acoustic element and the wall to obtain the transmission probability model of the acoustic element.

[0011] Step 4: Based on the gridded long channel space model, the parameters of the acoustic micro-element are initialized in all divided grids. A parallel computing strategy is used to track the migration motion of the initialized acoustic micro-element to obtain the redistribution probability model of the acoustic micro-element.

[0012] Step 5: Based on the transmission probability model and redistribution probability model of the acoustic microelement, the sound source pulse duration is used to iteratively solve the problem and output the flux distribution of the acoustic microelement in the spatial grid at each time step.

[0013] Step 6: Transform the flux distribution of the acoustic element in the spatial grid at each time step to obtain the sound pressure level distribution and dynamic change results in space.

[0014] Optionally, the parameters of the acoustic microelement include but are not limited to: the energy of the acoustic microelement, the velocity of the acoustic microelement, the emission angle distribution of the acoustic microelement, the velocity component of the acoustic microelement in the three-dimensional space coordinate system, the position of the acoustic microelement and the number of acoustic microelement.

[0015] Optionally, step 2 specifically includes:

[0016] Step 2.1: Divide the long corridor model into six sections based on their locations: top wall, bottom wall, left wall, right wall, front opening, and rear opening. Grid these six sections and number them i = 1, ... N, where N is the total number of grid cells.

[0017] Step 2.2: Initialize the absorption coefficient α, transmission coefficient β, and reflection coefficient γ of each mesh according to the material properties corresponding to each mesh.

[0018] Step 2.3: Construct a gridded long channel spatial model based on the divided grid and the grid's absorption coefficient, transmission coefficient, and reflection coefficient.

[0019] Optionally, step 3 specifically includes:

[0020] Step 3.1: Sample the sound source into M acoustic elements.

[0021] Step 3.2: Initialize the sampled velocities and positions of the M acoustic microelements.

[0022] Step 3.3: Update the M acoustic micro-elements through the trajectory formula to obtain the position after the small movement in each time step. Compare the coordinates of the acoustic micro-elements with the wall coordinates of the long channel space within the small movement range of the acoustic micro-elements, and initialize the counters for all grids divided by the long channel space model. If the micro-moving acoustic element passes through a certain grid i, the counter of the grid is updated , until all motion duration sampling is completed and the total number of acoustic micro-elements sampling is completed, the proportion of all grid counters relative to the total number of acoustic micro-elements M is counted and recorded to obtain the transmission probability model O of the acoustic micro-elements.

[0023] Step 3.4: Take the target sound source as the acoustic element and repeat steps 3.1 to 3.3 to obtain the target sound source transmission probability model.

[0024] Step 3.5: Using the background noise as an acoustic element, repeat steps 3.1 to 3.3 to obtain the background noise transmission probability model.

[0025] Optionally, the trajectory formula is expressed as follows:

[0026]

[0027] in, 、 、 Respectively represent the position after a small movement in the n+1th time step, 、 、 Respectively represent the position after a small movement in the nth time step, is the time step, 、 、 They represent the speed of the acoustic microelement in the x-axis, y-axis, and z-axis respectively.

[0028] Optionally, step 4 specifically includes:

[0029] Step 4.1: Based on the long channel-type building space divided into N grids i = 1, 2, 3, ..., N, V' acoustic micro-elements are randomly sampled from each grid. For the i-th grid, the V' acoustic micro-elements are dynamically updated and migrated according to the trajectory formula. The collisions between the coordinates of the acoustic micro-elements and the space walls are counted and recorded. The grid counter is updated to obtain the probability model of spatial grid i being transferred to grids i = 1, 2, 3, ..., N. The probability model of transferring all spatial grids to grids i = 1, 2, 3, ..., N is used as the probability model of the redistribution of acoustic micro-elements.

[0030] Optionally, step 5 specifically includes:

[0031] Step 5.1: Set the total duration of the sound source pulse According to the macro time step Divide and calculate the number of acoustic micro-elements emitted by the target sound source for each macro time step and the number of acoustic elements emitted by background noise .

[0032] Step 5.2: At each macroscopic time step, the number of acoustic microelements absorbed by spatial grid i is calculated based on the absorption coefficient of spatial grid i, the target sound source, and the transmission probability of background noise.

[0033] According to the transmission coefficient of grid i, the transmission probability of the target sound source and background noise, the number of acoustic microelements transmitted by spatial grid i is calculated.

[0034] The number of acoustic microelements reflected by spatial grid i is calculated based on the absorption coefficient, transmission coefficient or reflection coefficient of grid i, the transmission probability of the target sound source and the background noise.

[0035] According to the transmission probability of the target sound source and background noise, the acoustic element flux of grid i is calculated.

[0036] Step 5.3: At each macroscopic time step, the number of absorbing, transmitting, and reflecting acoustic micro-elements and the flux of the acoustic micro-elements of spatial grid i are iteratively updated according to the redistribution probability model of the acoustic micro-elements of spatial grid i. The sum of the updated number of reflected acoustic micro-elements is compared with the convergence condition. If the condition is met, the iteration of the macroscopic time step is completed, and the converged number of absorbing, transmitting, and reflecting acoustic micro-elements and the flux of the acoustic micro-elements of spatial grid i are output.

[0037] Step 5.4: Subtract the absorption part from the number of absorption, transmission, and reflection acoustic elements and the flux of the acoustic elements that converge in all networks in each macroscopic time step to obtain the final number of absorption, transmission, and reflection acoustic elements and the flux distribution in the spatial grid in each macroscopic time step.

[0038] Optionally, the expressions for the number of acoustic microelements absorbing, transmitting, and reflecting and the flux of the acoustic microelements of the spatial grid i are as follows:

[0039] ABS ( i ) = α ( i ) ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )]

[0040] in, represents the number of acoustic elements absorbed by spatial grid i, represents the absorption coefficient of spatial grid i, represents the transmission probability of the target sound source of spatial grid i, represents the transmission probability of the background noise of spatial grid i.

[0041] TRANS ( i ) = β ( i ) ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )]

[0042] in, represents the number of acoustic elements transmitted by spatial grid i, represents the transmission coefficient of spatial grid i.

[0043] REF ( i ) = [ 1 − α ( i ) − β ( i )] ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )] = γ ( i ) ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )]

[0044] in, represents the number of acoustic elements reflected by spatial grid i, represents the reflection coefficient of spatial grid i.

[0045] According to the transmission probability of the target sound source and background noise and , the acoustic element flux of grid i is calculated as:

[0046]

[0047] in, represents the acoustic element flux of grid i.

[0048] Optionally, the expressions for iterative update of the number of acoustic micro-elements of absorption, transmission, and reflection and the flux of the acoustic micro-elements of the spatial grid i are as follows:

[0049]

[0050]

[0051] REF new ( i ) = [ 1 − α ( i ) − β ( i )] ⋅ ∑ j G ( i , j ) ⋅ REF old ( j ) = γ ( i ) ⋅ ∑ j G ( i , j ) ⋅ REF old ( j )

[0052]

[0053] in, represents the number of acoustic elements absorbed by the updated spatial grid i, represents the number of acoustic elements absorbed by the spatial grid i in the previous iteration, represents the redistribution probability model of the acoustic element in the spatial grid i, represents the number of acoustic elements reflected by the spatial grid j in the previous iteration, represents the number of acoustic elements transmitted by the updated spatial grid i, represents the number of acoustic elements transmitted by the spatial grid i in the previous iteration, represents the number of acoustic elements reflected by the updated spatial grid i, represents the acoustic element flux of the updated spatial grid i, Represents the acoustic element flux of spatial grid i in the previous iteration.

[0054] The convergence condition expression is as follows:

[0055]

[0056] in: It is the total number of the minimum free acoustic elements in the long channel space.

[0057] Optionally, the final number of acoustic micro-elements absorbed, transmitted, and reflected in the spatial grid and the flux distribution in each macroscopic time step are expressed as follows:

[0058]

[0059]

[0060]

[0061]

[0062] in, Represents the final number of absorbing acoustic elements in all spatial grids, represents the number of converged absorbing acoustic elements of all spatial grids, Indicates the final number of transmitted acoustic elements of all spatial grids, Represents the number of acoustic elements that transmit and absorb in all spatial grids, The number of acoustic elements representing the final reflection of all spatial grids, The number of acoustic elements representing the converged reflections of all spatial grids, represents the final acoustic element flux of all spatial grids, represents the converged acoustic element flux of all spatial grids, and c represents the absorptivity.

[0063] Optionally, step 6 specifically includes:

[0064] Obtain the flux distribution of the acoustic microelement in the spatial grid at each macroscopic time step, initialize the parameters of the acoustic microelement, and obtain the sound pressure level distribution and dynamic change results in the long channel space model. The calculation formula is as follows:

[0065]

[0066] in, Represents the sound pressure level distribution and dynamic change results in the long channel space model, represents the energy parameter of the acoustic element, ρ represents the medium density inside the long channel space building, V represents the volume of the acoustic element, represents the velocity of the acoustic element, and p0 represents the reference sound pressure.

[0067] In a second aspect, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements a long-channel building sound field modeling method based on acoustic microelements as described in any one of the first aspects.

[0068] According to a third aspect, a computer device includes:

[0069] Memory, used to store instructions.

[0070] The processor is configured to execute the instructions so that the computer device performs the operations of the long-channel building sound field modeling method based on acoustic microelements as described in any one of the first aspects.

[0071] Beneficial effects: The present invention provides a long-channel building sound field modeling method and system based on acoustic microelements, which are applied in the field of architectural acoustics. By abstracting the propagation of sound into the transport process of microelements with energy, unified modeling of different types of sound sources inside the building is achieved. By designing a corresponding calculation framework, not only can the transport process of acoustic microelements be described at the microscopic level, but also the dynamic changes of the overall sound field inside the building can be described at the macroscopic level. The framework includes a sound source model for describing the characteristics of the acoustic microelements corresponding to the sound source; a space model for describing the size and wall conditions of the building space; a probability model for accelerating the calculation of the transmission and redistribution probability of acoustic microelements by designing a parallel computing strategy; an acoustic dynamics algorithm for calculating the dynamic evolution of the sound field inside the building; and finally, the distribution and dynamic changes of the sound field inside the building are output. The present invention is concise and effective, has good robustness, and has broad application prospects.

[0072] Compared with the traditional combination method, the advantages of the present invention are as follows:

[0073] 1. It can not only effectively model the diverse and complex characteristics of sound sources in long channel building spaces, but also greatly reduce the computational complexity.

[0074] 2. Taking into account background noise and medium absorption makes the model richer and closer to real complex working conditions.

[0075] 3. The designed acoustic microelement calculation framework based on the probability model can greatly reduce the calculation time and storage space compared with traditional finite element calculation.

[0076] 4. A parallel computing strategy is designed for the redistribution probability model of acoustic microelements to avoid the problem of low computational efficiency caused by serial calculation of a large number of grids and microelements.

[0077] 5. Model the acoustic micro-element at the microscopic level, and then perform dynamic modeling in the macroscopic space, so that the results of the model can be traced back to the deep mechanism behind it for analysis. It has the characteristics of strong interpretability, accuracy and effectiveness, simplicity and efficiency, and broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a flow chart of the implementation process of the method of the present invention.

[0079] Figure 2 It is a schematic diagram of the emission of acoustic microelements on a grid according to the cosine distribution law during the implementation of the method of the present invention.

[0080] Figure 3 It is a schematic diagram of a model of a long channel building space and a sound source during the implementation of the method of the present invention.

[0081] Figure 4It is a schematic diagram of background noise being emitted from a grid divided by openings at both ends of a long channel-shaped space during implementation of the method of the present invention.

[0082] Figure 5 It is a schematic diagram of the collision, absorption, transmission and reflection between the acoustic microelement and the wall grid during the implementation of the method of the present invention.

[0083] Figure 6 It is a calculation flow chart of the acoustic microelement transmission probability model during the implementation of the method of the present invention.

[0084] Figure 7 It is a calculation flow chart of the acoustic microelement redistribution probability model during the implementation of the method of the present invention.

[0085] Figure 8 It is a grid transmission flow chart of the direct sound field and the reflected sound field in the long channel space during the implementation of the method of the present invention.

[0086] Figure 9 The method of the present invention is for the sound microelement flux and absorption distribution of the right wall of the long space under 85dB sound source, Figure 9 (a) is a schematic diagram of flux distribution. Figure 9 (b) is a schematic diagram of absorption distribution.

[0087] Figure 10 The method of the present invention compares the calculated sound pressure level attenuation value along the length direction of the long channel space with the experimental value under different sound source conditions.

[0088] Figure 11 The dynamic calculation value of the sound pressure level at the opening at the other end of the long channel under different dynamic sound source conditions is compared with the experimental value by the method of the present invention. DETAILED DESCRIPTION

[0089] The following is a clear and complete description of the technical solutions in the examples of the present invention, in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative work are within the scope of protection of the present invention.

[0090] The present invention will be further described below with reference to specific embodiments.

[0091] Example 1:

[0092] This embodiment introduces a method for modeling the sound field of a long channel building based on acoustic micro-elements. The specific steps are as follows:

[0093] Step 1: Initialize the acoustic element: According to the medium conditions in the long channel building space and the parameters of the target sound source and background noise, the parameters of the initialized acoustic element are obtained.

[0094] Step 2: Initialize the spatial model: According to the size and wall parameters in the long channel building space, the long channel spatial model is gridded and the absorption, reflection and transmission parameters of each grid are defined to obtain a gridded long channel spatial model.

[0095] Step 3: Solve the transmission probability model: Based on the parameters of the initialized acoustic element, calculate the migration motion of the acoustic element in the gridded long channel space model and the collision between the acoustic element and the wall to obtain the transmission probability model of the acoustic element.

[0096] Step 4: Solve the redistribution probability model: Based on the gridded long channel space model, initialize the parameters of the acoustic micro-element in all divided grids, use a parallel computing strategy to track the migration movement of the initialized acoustic micro-element, and obtain the redistribution probability model of the acoustic micro-element.

[0097] Step 5: Solve the dynamic sound field: According to the transmission probability model and redistribution probability model of the acoustic microelement, iteratively solve using the sound source pulse duration, and output the absorption, transmission, reflection and flux distribution of the acoustic microelement in the spatial grid at each time step.

[0098] Step 6: Conversion results: The flux distribution of the acoustic element in the spatial grid at each time step is converted to obtain the sound pressure level distribution and dynamic change results in the long channel space model.

[0099] Furthermore, the parameters of the acoustic microelement specifically include:

[0100] Step 1.1: Obtain the energy parameters of the acoustic element. Convert the sound pressure level spl (dB) of the target sound source into sound pressure p:

[0101] (1)

[0102] According to the calculated sound pressure, the energy parameter calculation formula of the initialized acoustic element is:

[0103] (2)

[0104] Where: p0 is the reference sound pressure. Since the minimum sound pressure perceptible to the human ear is 20 μPa, the reference sound pressure in air is generally 20 μPa. The sound pressure level of a sound with an effective sound pressure of 20 μPa is 0 dB; ρ is the density of the medium inside a long space building, for example, the density of air is approximately 1.2 kg / m³; v is the velocity of the sound element; and V is the volume of the sound element, in m³. spl represents the sound pressure level of the target sound source, and p represents the sound pressure of the target sound source.

[0105] In order to facilitate unified calculation, the energy parameters of the acoustic micro-element converted from background noise are consistent with those of the target sound source.

[0106] Step 1.2: Obtain the velocity parameters of the acoustic microelement. The velocity parameters of the acoustic microelement are closely related to the physical properties of the medium. Taking air as an example, the velocity calculation formula is:

[0107] (3)

[0108] Where: T is the air temperature in °C, the numerical part is used in the calculation, and 331.5 is the velocity base in meters per second.

[0109] Step 1.3: Obtain the emission angle distribution of the acoustic microelement. The emission state of the acoustic microelement is determined by the angle between the emission angle and the emission axis. According to Lambert's cosine law, the angle conforms to the cosine distribution, and the inverse method is used to generate a random number that meets the conditions. Specifically, calculate the cumulative distribution function:

[0110] (4)

[0111] According to the normalization condition F(π / 2)=1, C=1. Then through the inverse function Get pseudorandom numbers that follow a cosine distribution:

[0112] (5)

[0113] in: is a uniformly distributed random number, That is the polar angle of the emission direction of the acoustic microelement.

[0114] Step 1.4: Combine the velocity and angle distributions calculated in steps 1.2 and 1.3, as Figure 2 As shown in the figure, the velocity component of the acoustic microelement in the three-dimensional space coordinate system is calculated as follows:

[0115] (6)

[0116] in, 、 、 are the velocity components of the acoustic microelement on the x, y, and z axes in the three-dimensional space coordinate system, is pi, for A random number uniformly distributed on is the azimuth angle of the acoustic microelement emission direction, ranging from (0, 2π).

[0117] Step 1.5: Get the position of the acoustic element. The acoustic element position parameters are obtained based on the relative positions of the target sound source and background noise in the long channel space. Figure 3 As shown, the center of the long corridor's open end is the coordinate system's origin, with the height as the vertical axis (Y), the width as the horizontal axis (X), and the length as the Z axis. By establishing the coordinate system, assuming the target sound source is located in the middle of one end of the corridor, 30 cm from the center, the target sound source's position is (0, -0.3, 0). Background noise enters from both ends of the long corridor, so the positions of noise source 1 and noise source 2 are (x, y, 0) and (x, y, Lz), where Lz is the length of the long corridor. x and y are determined by the gridded center coordinates and must be determined in conjunction with step 2.1.

[0118] Step 1.6: Obtain the number of acoustic elements emitted by the target sound source. The number of acoustic elements is determined based on the parameters of the target sound source and is calculated using the following formula:

[0119] (7)

[0120] in: is the frequency of the target sound source, in Hz; The macro time step is divided according to the impulse response of the sound source, in seconds; is the volume of the target sound source.

[0121] Step 1.7: Obtain the number of acoustic elements corresponding to the background noise. The formula for calculating the number of acoustic elements of background noise is as follows:

[0122] (8)

[0123] Among them: spl b is the measured background noise sound pressure level.

[0124] Furthermore, the step 2 specifically includes:

[0125] Step 2.1: Divide the long channel space model into six parts according to location, namely top wall, bottom wall, left wall, right wall, front opening, and rear opening.

[0126] Divide the six parts into grids and number them i=1,...N. The size of the grid is Φ cm², as shown in Figure 3As shown. The total number of grids divided is N. For the initial position of the background noise at the open end in step 1.5, the center position of the divided grid can be calculated as the initial position of the background noise in the three-dimensional space coordinate system, as shown in Figure 4 shown.

[0127] like Figure 5 As shown, step 2.2: Initialize the absorption coefficient of the grid according to the material properties (door, window, floor, etc.) corresponding to each grid α = α1,…, α i , α i+1 , α i+2 ,…, α i+m ,…, α j , α j+1 , α j+2 ,…, α j+n ,…, α N and transmission coefficients β=β1,…, β i , β i+1 , β i+2 ,…, β i+m ,…, β j , β j+1 , β j+2 ,…, β j+n ,…, β N . Where α i , α i+1 ,α i+2 ,…, α i+m and β i , β i+1 , β i+2 ,…, β i+m Corresponding to the absorption coefficient and transmission coefficient of material 1, α j , α j+1 ,α j+2 ,…, α j+n and β j , β j+1 , β j+2 ,…, β j+n Corresponding to the transmission coefficient of material 2. The reflection coefficient γ is obtained according to the law of conservation of energy:

[0128] (9)

[0129] Step 2.3: Construct a gridded long channel spatial model based on the divided grid and the grid's absorption coefficient, transmission coefficient, and reflection coefficient.

[0130] Furthermore, the step 3 specifically includes:

[0131] Step 3.1: Sample the sound source into M acoustic elements. Note that the number of samples here is only related to the calculation of the transmission probability and is unrelated to the number of acoustic elements in step 1. Taking the target sound source in step 1 as an example, the position of the sound source at this time is (0, -0.3, 0). This means that M acoustic elements are transmitting from this position into the long channel space.

[0132] Step 3.2: Initialize the velocity and position of the M acoustic micro-element obtained by sampling. First, similar to step 1.4, initialize the velocity components of these micro-element. Then specify the maximum tracking times maxtime and time step , and the macroscopic time step The difference is that the time scale is very small, usually 10 -3 .

[0133] Step 3.3: Update the M acoustic micro-elements using the trajectory formula to obtain the position after the small movement in each time step. The trajectory formula is expressed as follows:

[0134] (10)

[0135] in, 、 、 Respectively represent the position after a small movement in the n+1th time step, 、 、 Respectively represent the position after a small movement in the nth time step, is the time step, 、 、 They represent the speed of the acoustic microelement in the x-axis, y-axis, and z-axis respectively.

[0136] like Figure 6 As shown in the figure, by comparing the coordinates of the acoustic element with the coordinates of the wall of the long channel space within a small range of motion, it is determined whether the acoustic element collides with the wall of the long channel space. Specifically, the counters are initialized for all the grids divided by the long channel space model. If the micro-moving acoustic element passes through a certain grid i, the counter of the grid is updated The coordinates of the acoustic element that collides with the grid are recorded in the array located in the part of the grid to which it belongs. After all the motion duration sampling and the total number of acoustic elements are sampled, the proportion of all grid counters relative to the total number of acoustic elements M is counted and recorded to obtain the transmission probability model O of the acoustic element.

[0137] Step 3.4: Take the target sound source as the acoustic microelement and repeat steps 3.1 to 3.3 to obtain the target sound source transmission probability model .

[0138] Step 3.5: Using background noise as an acoustic element, repeat steps 3.1 to 3.3 to obtain the background noise transmission probability model. .

[0139] Furthermore, in one embodiment, step 4 specifically includes:

[0140] Step 4.1: Utilizing the multi-core, multi-threaded capabilities of modern computer processors, six cores of the processor are used to independently calculate the top, bottom, left, right, front, and rear openings of the long corridor. For each section, the migration motion of the acoustic micro-element corresponding to the mesh is calculated using hyperthreading.

[0141] like Figure 7 As shown, step 4.2: According to the long channel building space divided into N grids i=1, 2, 3, .., N, randomly sample V' acoustic micro-elements from each grid, the position distribution sampling is uniform, and the speed sampling is calculated using formula (6). The emission state conforms to Lambert's cosine law, and the emission direction is the normal vector direction of each grid center. The schematic diagram is shown as follows Figure 2 As shown in Figure 1, for the i-th grid, V′ acoustic micro-elements are dynamically updated according to the migration trajectory formula (10). The collisions between the coordinates of the acoustic micro-elements and the spatial wall are counted and recorded, and the grid counter is updated to obtain the probability model of spatial grid i being transferred to grids i=1, 2, 3, ..., N. The probability model of transferring all spatial grids to grids i=1, 2, 3, ..., N is used as the probability model of the redistribution of the acoustic micro-elements.

[0142] Step 4.3: Because different parts of the long channel space vary in size, different processor cores process the data at different speeds. After completing the mesh calculations for all parts, store them uniformly and efficiently. The results are stored in a two-dimensional array format, with rows and columns representing the sequentially stored meshes, and the values ​​representing the mesh-to-mesh redistribution probabilities. This storage format uses the .npz compressed format, which significantly improves model execution and storage efficiency.

[0143] Furthermore, the step 5 specifically includes:

[0144] Step 5.1: Set the total duration of the sound source pulse According to the macro time step For each macroscopic time step, the number of acoustic microelements emitted by the target sound source and background noise is calculated according to formulas (7) and (8): and .

[0145] Step 5.2: If Figure 8 As shown, at each macro time step, according to the absorption coefficient α of spatial grid i, the target sound source and the background noise transmission probability and , calculate the number of acoustic micro-elements absorbed by space grid i :

[0146] ABS ( i ) = α ( i ) ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )] (11)

[0147] in, represents the absorption coefficient of spatial grid i, represents the transmission probability of the target sound source of spatial grid i, represents the transmission probability of the background noise of spatial grid i.

[0148] According to the transmission coefficient β of grid i, the transmission probability of target sound source and background noise and , calculate the number of acoustic micro-elements transmitted by space grid i :

[0149] TRANS ( i ) = β ( i ) ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )] (12)

[0150] in, represents the transmission coefficient of spatial grid i.

[0151] According to the absorption coefficient α, transmission coefficient β or reflection coefficient γ of grid i, the transmission probability of target sound source and background noise and , calculate the number of acoustic micro-elements reflected by space grid i :

[0152] REF ( i ) = [ 1 − α ( i ) − β ( i )] ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )] = γ ( i ) ⋅ [ N s ⋅ O s ( i ) + N b ⋅ O b ( i )] (13)

[0153] in, represents the reflection coefficient of spatial grid i.

[0154] According to the transmission probability of the target sound source and background noise and , calculate the acoustic element flux of grid i :

[0155] (14)

[0156] Step 5.3: Since the acoustic elements emitted by grid j will reach grid i within the macroscopic time step, this redistribution process is updated through iteration. At each macroscopic time step, according to the redistribution probability model of the acoustic elements of spatial grid i, the number of absorbing, transmitting, and reflecting acoustic elements and the flux of the acoustic elements of spatial grid i are iteratively updated. The sum of the updated number of reflected acoustic elements is compared with the convergence condition. If it is met, the iteration of the macroscopic time step is completed, and the converged number of absorbing, transmitting, and reflecting acoustic elements and the flux of the acoustic elements of spatial grid i are output.

[0157] The updated expressions for the number of acoustic micro-elements absorbing, transmitting, and reflecting in the spatial grid i and the flux of the acoustic micro-elements are as follows:

[0158] (15)

[0159] (16)

[0160] REF new ( i ) = [ 1 − α ( i ) − β ( i )] ⋅ ∑ j G ( i , j ) ⋅ REF old ( j ) = γ ( i ) ⋅ ∑ j G ( i , j ) ⋅ REF old ( j ) (17)

[0161] (18)

[0162] in, represents the number of acoustic elements absorbed by the updated spatial grid i, represents the number of acoustic elements absorbed by the spatial grid i in the previous iteration, represents the redistribution probability model of the acoustic element in the spatial grid i, represents the number of acoustic elements reflected by the spatial grid j in the previous iteration, represents the number of acoustic elements transmitted by the updated spatial grid i, represents the number of acoustic elements transmitted by the spatial grid i in the previous iteration, represents the number of acoustic elements reflected by the updated spatial grid i, represents the acoustic element flux of the updated spatial grid i, Represents the acoustic element flux of spatial grid i in the previous iteration.

[0163] The convergence condition expression is as follows:

[0164] (19)

[0165] in: It is the total number of the minimum free acoustic elements in the long channel space.

[0166] Step 5.4: Considering the absorption of sound by the medium in the long channel building model, subtract the absorption portion from the number of absorbing, transmitting, and reflecting acoustic elements and the flux of the acoustic elements converged in each macroscopic time step for all networks. The final number of absorbing, transmitting, and reflecting acoustic elements and the flux distribution of the acoustic elements in the spatial grid in that macroscopic time step are obtained. Assuming the absorption rate is c, the final number of absorbing, transmitting, and reflecting acoustic elements and the flux distribution of the acoustic elements in the spatial grid in each macroscopic time step are expressed as follows:

[0167] (20)

[0168] (twenty one)

[0169] (twenty three)

[0170] (twenty four)

[0171] in, Represents the final number of absorbing acoustic elements in all spatial grids, represents the number of converged absorbing acoustic elements of all spatial grids, Indicates the final number of transmitted acoustic elements of all spatial grids, Represents the number of acoustic elements that transmit and absorb in all spatial grids, The number of acoustic elements representing the final reflection of all spatial grids, The number of acoustic elements representing the converged reflections of all spatial grids, represents the final acoustic element flux of all spatial grids, Represents the converged acoustic element flux for all spatial grids.

[0172] Furthermore, the step 6 specifically includes:

[0173] Obtain the flux distribution of the acoustic element in the spatial grid at each time step, initialize the parameters of the acoustic element, and obtain the sound pressure level distribution and dynamic change results in the long channel space model. The calculation formula is as follows:

[0174] (25)

[0175] in, Represents the sound pressure level distribution and dynamic change results in the long channel space model, represents the energy parameter of the acoustic element, ρ represents the medium density inside the long channel space building, V represents the volume of the acoustic element, represents the velocity of the acoustic element, and p0 represents the reference sound pressure.

[0176] Example 2:

[0177] This embodiment introduces a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for modeling a long-channel building sound field based on acoustic microelements as described in any one of the embodiments 1 is implemented.

[0178] Example 3:

[0179] This embodiment introduces a computer device, including:

[0180] Memory, used to store instructions.

[0181] The processor is configured to execute the instructions so that the computer device performs the operations of the long-channel building sound field modeling method based on acoustic microelements as described in any one of the embodiments 1.

[0182] Example 4:

[0183] This embodiment introduces the specific implementation process of the method of the present invention as follows: Figure 1 As shown:

[0184] Convert the target sound source and background noise into sound elements.

[0185] First, the energy and velocity of the acoustic element are calculated based on the sound pressure level parameters of the sound source.

[0186] Second, the emission state is sampled according to Lambert's cosine law, as Figure 2 shown.

[0187] Secondly, the emission position is obtained based on the relative positions of the target sound source and the background noise in the long channel space. Figure 3 As shown in , the three-dimensional space coordinate far point is located at the center of the long channel space open end, and the position coordinates of the target sound source and background noise can be obtained. Among them, the target sound source is usually a point sound source, and the background noise is calculated as a multi-point sound source, such as Figure 4 shown.

[0188] Secondly, the emission quantity of the acoustic microelement is calculated according to the frequency of the sound source, the time step of the impulse response and the volume.

[0189] Mesh division and parameter setting for the long channel building space model.

[0190] First, the long channel space is divided into six parts: top wall, bottom wall, left wall, right wall, front opening, and rear opening. They are gridded and numbered in order and finally merged.

[0191] Secondly, initialize the absorption coefficient, transmission coefficient and reflection coefficient of all grids and modify them according to different materials, as shown in the schematic diagram Figure 5 shown.

[0192] Calculate the transmission probability model of the acoustic microelement, the flow chart is as follows Figure 6 shown.

[0193] First, a large number of acoustic microelements of sound sources are sampled, and their migration motion rules, time steps and maximum movement times at the microscopic level are set.

[0194] Next, the migration of the acoustic element reflected from the initial position is tracked. At each time step, it is determined whether it collides with the six walls of the long channel space. If a collision occurs, the coordinates of the acoustic element are recorded and the grid counter at the collision location is updated. This process continues until all time steps and sampled elements are completed, resulting in the transmission probability corresponding to all grids.

[0195] Calculate the redistribution probability model of acoustic microelement and use parallel processing to accelerate the calculation. The flow chart is as follows Figure 7 shown.

[0196] First, the six parts of the long channel space division are processed separately by using the multi-core of the computer processor.

[0197] Next, for each individual segment, hyperthreading is used to process the acoustic elements of the grid. Specifically, multiple threads simultaneously initialize acoustic elements for multiple grids, tracking their migration and collisions. This process continues until all acoustic elements in all grids within the segment are calculated, yielding the transmission probability between that segment and other grids.

[0198] Secondly, wait for all parts to be calculated and merge them into a two-dimensional array in order to obtain the redistribution probability model of the acoustic microelement, and finally store it in the compressed format of .npz.

[0199] The dynamic distribution of the sound field in the long channel space is solved based on the acoustic dynamics algorithm.

[0200] First, the total duration of the sound source pulse According to the macro time step Divide.

[0201] Secondly, for each time step, according to the number of acoustic micro-elements emitted by the target sound source and background noise, the transmission probability model, and the absorption, reflection, and transmission coefficients, the absorption, reflection, and transmission number of acoustic micro-elements of all grids and the corresponding flux are preliminarily calculated, corresponding to Figure 8 Direct sound field in.

[0202] Secondly, according to the convergence criterion of the total amount of reflection of the acoustic micro-element in space, the absorption, reflection, transmission and corresponding flux of the acoustic micro-element of all grids in each time step are dynamically updated, corresponding to Figure 8 Until the total number of acoustic element reflections within this time step is less than the sum of the minimum number of free acoustic elements in the long channel space.

[0203] Secondly, the absorption effect of the medium in the long space on sound is considered, and the absorption part is subtracted from the parameter results that converge within a short period of time.

[0204] Convert the flux results of the acoustodynamics algorithm into sound pressure level parameters.

[0205] The dimensions of the long channel space selected in this example are Lx, Ly, and Lz, respectively, 2.2m, 3m, and 19m, and the grid size is 225cm. 2 The target sound source is an Aiwa AWA5510A dodecahedron sound source. The sound source signal is white noise with sound pressure level parameters of 75, 85, and 90 dB respectively. The location is at the open end of the long channel space. The background noise enters the space at both ends and is measured by a sound level meter to be 25 dB. The acoustic microelement transmission probability model is calculated by sampling 5000 acoustic microelements. The time step is is 10 -3 An 8-core 16-thread processor is used to parallelly calculate the redistribution probability model of acoustic micro-elements in six parts of the long channel space, and the grid sampling number of each part is 50 acoustic micro-elements.

[0206] By total pulse duration The time step is 5 seconds The dynamic distribution of absorption, reflection, transmission and flux in space is calculated using the acoustic dynamics algorithm for 0.5 seconds. Figure 9 (a) shows the flux distribution on the right wall of the long channel space under an 85dB sound source. Figure 9 (b) is the absorption distribution of the acoustic element on the right wall of the long channel space under an 85dB sound source. By converting the flux into sound pressure level parameters, Figure 10 The figure shows the stable sound pressure level at different distances from the sound source along the length of a long channel space. For comparison, the actual value measured by a sound level meter is also given. The method of the present invention can accurately describe the acoustic nonlinear attenuation characteristics along the length of a long channel space.

[0207] By total pulse duration The time step is 20 seconds, the sound source is turned on for the first 10 seconds and turned off for the last 10 seconds. The acoustic dynamics algorithm is used to calculate the dynamic changes of the sound pressure level parameters at the other end of the space for 0.5 seconds, such as Figure 11As shown. For comparison, the real value measured by the sound level meter is also given. The present invention can accurately describe the dynamic evolution process when the sound source is turned on and the reverberation process after the sound source is turned off.

[0208] Table 1 compares the results of serial and parallel computations using the proposed method, as well as the results of computations using the acoustic ray tracing module in the commercial simulation software COMSOL Multiphysics 6.0. The proposed computational framework and parallel computing strategy are lightweight and highly efficient.

[0209] Table 1 shows the calculation results of the acoustic redistribution probability model under different grid sizes and the number of sampled acoustic elements.

[0210] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0211] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0212] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0213] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0214] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for modeling the sound field of a long-channel building based on acoustic microelements, characterized by: Specifically include: Step 1: According to the medium conditions in the long channel building space and the parameters of the target sound source and background noise, the parameters of the initialization acoustic micro-element are obtained; Step 2: According to the dimensions and wall parameters of the long channel building space, the long channel space model is meshed and the absorption, reflection, and transmission parameters of each grid are defined to obtain a meshed long channel space model; Step 3: Based on the parameters of the initialized acoustic element, the migration motion of the acoustic element in the gridded long channel space model and the collision between the acoustic element and the wall are calculated to obtain the transmission probability model of the acoustic element; Step 4: Based on the gridded long channel space model, the parameters of the acoustic micro-element are initialized in all the divided grids. The migration motion of the initialized acoustic micro-element is tracked using a parallel computing strategy to obtain the redistribution probability model of the acoustic micro-element. Step 5: Based on the transmission probability model and redistribution probability model of the acoustic microelement, it is iteratively solved using the sound source pulse duration, and the flux distribution of the acoustic microelement in the spatial grid at each time step is output; Step 6: Transform the flux distribution of the acoustic element in the spatial grid at each time step to obtain the sound pressure level distribution and dynamic change results in space.

2. The long channel building sound field modeling method based on acoustic microelement according to claim 1, characterized in that: The parameters of the acoustic microelement include but are not limited to: the energy of the acoustic microelement, the velocity of the acoustic microelement, the emission angle distribution of the acoustic microelement, the velocity component of the acoustic microelement in the three-dimensional space coordinate system, the position of the acoustic microelement and the number of acoustic microelement.

3. The long channel building sound field modeling method based on acoustic microelement according to claim 1 is characterized in that: The step 2 specifically includes: Step 2.1: Divide the long channel spatial model into six parts according to their locations: top wall, bottom wall, left wall, right wall, front opening, and rear opening; mesh the six parts and number them i=1,...N, where N is the total number of meshes. Step 2.2: Initialize the absorption coefficient, transmission coefficient, and reflection coefficient of each mesh according to the material properties corresponding to each mesh; Step 2.3: Construct a gridded long channel spatial model based on the divided grid and the grid's absorption coefficient, transmission coefficient, and reflection coefficient.

4. The long channel building sound field modeling method based on acoustic microelement according to claim 1 is characterized in that: The step 3 specifically includes: Step 3.1: Sample the sound source into M acoustic elements; Step 3.2: Initialize the sampled velocities and positions of the M acoustic microelements; Step 3.3: Update the M acoustic micro-elements through the trajectory formula to obtain the position after the small movement in each time step. Compare the coordinates of the acoustic micro-elements with the wall coordinates of the long channel space within the small movement range of the acoustic micro-elements, and initialize the counters for all grids divided by the long channel space model. If the micro-moving acoustic element passes through a certain grid i, the counter of the grid is updated , until all motion duration sampling and total acoustic element number sampling are completed, count and record the proportion of all grid counters relative to the total acoustic element number M, and obtain the transmission probability model of the acoustic element; Step 3.4: Using the target sound source as the acoustic microelement, repeat steps 3.1 to 3.3 to obtain the target sound source transmission probability model; Step 3.5: Using the background noise as an acoustic element, repeat steps 3.1 to 3.3 to obtain the background noise transmission probability model.

5. The long channel building sound field modeling method based on acoustic microelement according to claim 4 is characterized in that: The trajectory formula expression is as follows: ； in, 、 、 Respectively represent the position after a small movement in the n+1th time step, 、 、 Respectively represent the position after a small movement in the nth time step, is the time step, 、 、 They represent the speed of the acoustic microelement in the x-axis, y-axis, and z-axis respectively.

6. The long channel building sound field modeling method based on acoustic microelement according to claim 1, characterized in that: The step 4 specifically includes: Step 4.1: Based on the long channel-type building space divided into N grids i = 1, 2, 3, ..., N, V' acoustic micro-elements are randomly sampled from each grid. For the i-th grid, the V' acoustic micro-elements are dynamically updated and migrated according to the trajectory formula. The collisions between the coordinates of the acoustic micro-elements and the space walls are counted and recorded. The grid counter is updated to obtain the probability model of spatial grid i being transferred to grids i = 1, 2, 3, ..., N. The probability model of transferring all spatial grids to grids i = 1, 2, 3, ..., N is used as the probability model of the redistribution of acoustic micro-elements.

7. The long channel building sound field modeling method based on acoustic microelement according to claim 1 is characterized by: The step 5 specifically includes: Step 5.1: Set the total duration of the sound source pulse According to the macro time step Divide and calculate the number of acoustic micro-elements emitted by the target sound source for each macro time step and the number of acoustic elements emitted by background noise ; Step 5.2: At each macroscopic time step, the number of acoustic microelements absorbed by spatial grid i is calculated based on the absorption coefficient of spatial grid i, the target sound source, and the transmission probability of background noise; According to the transmission coefficient of grid i, the transmission probability of the target sound source and background noise, the number of acoustic micro-elements transmitted by spatial grid i is calculated; The number of acoustic microelements reflected by spatial grid i is calculated based on the absorption coefficient, transmission coefficient or reflection coefficient of grid i, the transmission probability of the target sound source and background noise; According to the transmission probability of the target sound source and background noise, the acoustic microelement flux of grid i is calculated; Step 5.3: At each macroscopic time step, the number of absorbing, transmitting, and reflecting acoustic elements and the flux of the acoustic elements of spatial grid i are iteratively updated according to the redistribution probability model of the acoustic elements of spatial grid i. The updated sum of the number of reflected acoustic elements is compared with the convergence condition. If the conditions are met, the iteration of the macroscopic time step is completed, and the converged number of absorbing, transmitting, and reflecting acoustic elements and the flux of the acoustic elements of spatial grid i are output. Step 5.4: Subtract the absorption part from the number of absorption, transmission, and reflection acoustic elements and the flux of the acoustic elements that converge in all networks in each macroscopic time step to obtain the final number of absorption, transmission, and reflection acoustic elements and the flux distribution in the spatial grid in each macroscopic time step.

8. The long channel building sound field modeling method based on acoustic microelement according to claim 7 is characterized in that: The expressions for the number of absorption, transmission, and reflection acoustic microelements and the flux of the acoustic microelements of the spatial grid i are as follows: ； in, represents the number of acoustic elements absorbed by spatial grid i, represents the absorption coefficient of spatial grid i, represents the transmission probability of the target sound source of spatial grid i, represents the transmission probability of the background noise of spatial grid i; ； in, represents the number of acoustic elements transmitted by spatial grid i, represents the transmission coefficient of spatial grid i; ； in, represents the number of acoustic elements reflected by spatial grid i, represents the reflection coefficient of spatial grid i; According to the transmission probability of the target sound source and background noise and , the acoustic element flux of grid i is calculated as: ； in, represents the acoustic element flux of grid i; The expressions for iterative update of the number of acoustic micro-elements that absorb, transmit, and reflect in spatial grid i and the flux of the acoustic micro-elements are as follows: ； ； ； ； in, represents the number of acoustic elements absorbed by the updated spatial grid i, represents the number of acoustic elements absorbed by the spatial grid i in the previous iteration, represents the redistribution probability model of the acoustic element in the spatial grid i, represents the number of acoustic elements reflected by the spatial grid j in the previous iteration, represents the number of acoustic elements transmitted by the updated spatial grid i, represents the number of acoustic elements transmitted by the spatial grid i in the previous iteration, represents the number of acoustic elements reflected by the updated spatial grid i, represents the acoustic element flux of the updated spatial grid i, represents the acoustic element flux of spatial grid i in the previous iteration; The convergence condition expression is as follows: ； in: It is the total number of the minimum free acoustic elements in the long channel space.

9. The long channel building sound field modeling method based on acoustic microelement according to claim 8, characterized in that: The final number of acoustic micro-elements absorbed, transmitted, and reflected in the spatial grid in each macroscopic time step, as well as the expression of the flux distribution, are as follows: ； ； ； ； in, Represents the final number of absorbing acoustic elements in all spatial grids, represents the number of converged absorbing acoustic elements of all spatial grids, Indicates the final number of transmitted acoustic elements of all spatial grids, Represents the number of acoustic elements that transmit and absorb in all spatial grids, The number of acoustic elements representing the final reflection of all spatial grids, The number of acoustic elements representing the converged reflections of all spatial grids, represents the final acoustic element flux of all spatial grids, represents the converged acoustic element flux of all spatial grids, and c represents the absorptivity.

10. The long channel building sound field modeling method based on acoustic microelement according to claim 9, characterized in that: The step 6 specifically includes: Obtain the flux distribution of the acoustic microelement in the spatial grid at each macroscopic time step, initialize the parameters of the acoustic microelement, and obtain the sound pressure level distribution and dynamic change results in the long channel space model. The calculation formula is as follows: ； in, Represents the sound pressure level distribution and dynamic change results in the long channel space model, represents the energy parameter of the acoustic element, ρ represents the medium density inside the long channel space building, V represents the volume of the acoustic element, represents the velocity of the acoustic element, and p0 represents the reference sound pressure.

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