Reverberation time control-based optimization method for microporous parameters of railway station building

Abstract

A reverberation time control-based optimization method for microporous parameters of a railway station building. The method comprises the following steps: S1, calculating an initial reverberation time and an initial average sound absorption coefficient in the space of a station building; S2, setting a target reverberation time and a microporous installation area, and calculating a target sound absorption coefficient of the station building; S3, setting value ranges of microporous parameters, and establishing a function for a sound absorption coefficient and the microporous parameters; S4, establishing a genetic algorithm optimization calculation model, and setting calculation parameters to obtain optimal microporous parameters and a corresponding microporous sound absorption coefficient; and S5, setting a determination condition, and determining the calculation effectiveness of the microporous parameters. Taking actual engineering situations into consideration, the method realizes the forward optimization of microporous parameters and overcomes multiple drawbacks of traditional microporous calculation methods, such as requiring extensive parameter calculations and having no obvious parameter optimization effects, thereby providing technical support for research and development of microporous products and reducing time costs.

Description

A method for optimizing micropore parameters in railway station buildings based on reverberation time control Technical Field

[0001] The present invention relates to the technical field of railway station noise control, and in particular to a railway station micropore parameter optimization method based on reverberation time control. Background Art

[0002] The "Railway Passenger Station Design Code" (TB10100-2018) stipulates that the reverberation time in public areas of railway stations must meet the following requirements: if the volume of the station public area is less than 1 million cubic meters, the reverberation time must not exceed 4 seconds; if the volume of the station public area is greater than 1 million cubic meters, the reverberation time must not exceed 5.5 seconds. To achieve the reverberation time requirements, sound-absorbing materials must be extensively installed throughout the station, and large-scale sound absorption treatment must be applied to areas such as the ceiling and side walls.

[0003] Currently, indoor sound absorption treatment in railway passenger stations generally involves filling decorative ceiling panels with sound-absorbing cotton or spraying inorganic fiber sound-absorbing materials on the roof. Both methods have significant limitations. Sound-absorbing cotton requires a perforated plate support and a waterproof, breathable membrane. The installation process is complex and time-consuming, and subsequent maintenance costs are high. It is not suitable for typical architectural designs such as curved decorative panels and grid ceilings. Inorganic fiber spraying cannot provide waterproofing and carries the potential risk of powdering, failure, and indoor air pollution, resulting in high maintenance costs.

[0004] To address the issues with these types of sound-absorbing materials, microporous sound absorption technology can be used to develop aluminum microporous sound-absorbing ceilings or wall panels. These panels offer excellent sound absorption, easy installation, maintenance-free operation, Class A fire protection, and zero pollution. The sound absorption performance of microporous products is primarily determined by four microporous parameters: pore diameter, porosity, panel thickness, and cavity depth. The feasibility of these parameters in engineering must be considered.

[0005] Conventional numerical analysis methods cannot meet the needs of micropore parameter optimization. Traditional micropore calculation methods use an exhaustive method to investigate the variation of micropore sound absorption coefficient under different parameters. The algorithm process is tedious and complex, and the operation is difficult. The calculation structure is greatly influenced by human selection, which makes it difficult to solve the parameter optimization problem of complex functions.

[0006] In addition, railway station noise has the characteristic of a long low-frequency reverberation time. When determining the micropore parameters, it is necessary to carry out parameter optimization analysis based on the need for reverberation time control in order to meet the requirements of the "Railway Passenger Station Design Code" (TB10100-2018).

[0007] Summary of the Invention

[0008] In order to solve the problem of using micropore parameters to control reverberation time in the prior art, the present invention provides a method for optimizing micropore parameters of railway station buildings based on reverberation time control.

[0009] To this end, the present invention adopts the following technical solutions:

[0010] A method for optimizing micropore parameters of railway station buildings based on reverberation time control comprises the following steps:

[0011] S1, calculate the initial reverberation time T0 and initial average sound absorption coefficient in the railway station space based on the space size and building material type of the railway station The following steps are involved:

[0012] S11, assuming that the spatial volume of the railway station building is V0, and the outline of the railway station building is composed of n planes with different material properties, then the initial reverberation time T0 is:

[0013] Where S i is the area of ​​the i-th plane, α i is the sound absorption coefficient of the i-th plane;

[0014] S12, the initial average sound absorption coefficient is calculated by the following formula

[0015] Wherein, S0 is the total area of ​​the n planes with different material properties,

[0016] S2, set the target reverberation time T and micropore installation area S c , calculate the target sound absorption coefficient α of the railway station building c :

[0017] in, is the target average sound absorption coefficient,

[0018] When the spatial volume V0 of the railway station building is ≤1 million cubic meters, the target reverberation time T is ≤4 seconds; when the spatial volume V0 of the railway station building is greater than 1 million cubic meters, the target reverberation time T is ≤5.5 seconds.

[0019] S3, set the value range of micropore parameters and establish the micropore sound absorption coefficient α′ c and the functional relationship between the micropore parameters and the reverberation frequency f, wherein the micropore parameters include: pore diameter d c , porosity σ c , plate thickness t c and cavity depth D c; The reverberation frequency f is the frequency of concern when designing micropores;

[0020] The functional relationship is shown in the following formula:

[0021] in, ω=2πf;ρ0 is the air density, c0 is the speed of sound, γ is the dynamic viscosity of air, is the kinematic viscosity, and ω is the angular frequency.

[0022] The value range of the micropore parameters is: 0.1mm≤d c ≤1mm, 0.1%≤σ c ≤3%, 0.01mm≤t c ≤3mm、10mm≤D c ≤500mm.

[0023] S4, establish a genetic algorithm optimization calculation model, set the operation parameters and fitness function of the genetic algorithm optimization calculation model, obtain the optimized micropore parameters through the model, and calculate the micropore sound absorption coefficient α corresponding to the optimized micropore parameters c The operation parameters include population size, maximum genetic generation, crossover rate and mutation rate.

[0024] The fitness function may be a maximum area function Max A or a maximum area ratio function Max A′, or other appropriate fitness functions.

[0025] The maximum area function is Max A = ∫g(d c ,σ c , t c , D c , f)δ(f)df;

[0026] The maximum area ratio function is:

[0027] Where, the reverberation frequency f is 20Hz-8000Hz; δ(f) is the weight factor that changes with frequency, and the value range is 0-1, f max is the maximum reverberation frequency, f min is the minimum reverberation frequency.

[0028] S5, the micropore target sound absorption coefficient α obtained in S2 c and the micropore sound absorption coefficient α′ obtained in S4 c Make comparisons;

[0029] When α c ′≥α cWhen the microporous parameters obtained in S4 are used as the optimal microporous parameters, the method ends; otherwise, return to step S2 and adjust the microporous material installation area S c S3 and S4 are recalculated until the optimal micropore parameters are obtained and the method ends.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. This paper aims to control the reverberation time of railway station buildings. It establishes the relationship between reverberation time, sound absorption coefficient, and micropore parameters. It uses reverberation time to perform forward optimization of micropore parameters. The optimized results are then used in actual construction. The actual on-site construction effect obtained is consistent with the calculated effect.

[0032] 2. This invention uses a genetic algorithm with reverberation frequency modulation to optimize micropore parameters, overcoming the drawbacks of traditional micropore calculation methods, which often require extensive parameter calculations and exhibit limited optimization results. This method allows for rapid preparation of micropore parameters tailored to project needs and feasibility, providing technical support for micropore product development and saving time and costs.

[0033] 3. The present invention can be used by engineering designers when designing railway station buildings, accurately considering the reverberation time control requirements, proposing procurement parameter requirements for microporous products, and providing technical support for the green and environmentally friendly construction of railway station buildings.

[0034] 4. The genetic algorithm used in the present invention is a randomized search method evolved from evolutionary inheritance and natural selection in the biological world, and can quickly process complex multi-parameter optimization problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] FIG1 is a flow chart of a micropore parameter optimization method of the present invention;

[0036] Figure 2 is a schematic diagram of the on-site test points. DETAILED DESCRIPTION

[0037] The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] A method for optimizing micropore parameters of railway station buildings based on reverberation time control comprises the following steps:

[0039] S1, calculate the initial reverberation time T0 and initial average sound absorption coefficient in the railway station space based on the volume of the railway station space and the type of its building materials The following steps are involved:

[0040] S11, obtain the spatial volume V0 of the railway station building; classify the various planes in the railway station building space to obtain n planes with different material properties; calculate the initial reverberation time T0 of the railway station building before decoration using formula (1):

[0041] Where S i is the area of ​​the i-th plane, α i is the sound absorption coefficient of the i-th plane. The sound absorption coefficient of the corresponding plane is obtained by the existing technology.

[0042] S12, calculate the initial average sound absorption coefficient by formula (2)

[0043] Where S0 is the total area of ​​n planes with different material properties,

[0044] S2, set the target reverberation time T and microporous material installation area S according to the actual situation of the railway station. c , calculate the target sound absorption coefficient α of the railway station building c :

[0045] According to national standards, the target reverberation time T includes two cases: when the railway station space volume V0 ≤ 1 million cubic meters, the target reverberation time T ≤ 4 seconds; when the railway station space volume V0 > 1 million cubic meters, the target reverberation time T ≤ 5.5 seconds;

[0046] The target sound absorption coefficient α of the micropores in railway station buildings is calculated by formula (3): c :

[0047] in, is the target average sound absorption coefficient,

[0048] S3, set the value range of micropore parameters and establish the function of sound absorption coefficient and micropore parameters:

[0049] The micropore parameters include pore diameter d c , porosity σ c , plate thickness t c and cavity depth D c , the value range of micropore parameters should be: 0.1mm≤d c ≤1mm, 0.1%≤σ c ≤3%, 0.01mm≤t c ≤3mm、10mm≤D c ≤500mm.

[0050] With reference to the impedance analog equivalent circuit, the environmental parameters in the railway station space and existing technologies are used to establish the microporous sound absorption coefficient α′ c The functional relationship between the micropore parameters and the reverberation frequency f is shown in formula (4), where the reverberation frequency f is the frequency of interest in micropore design:

[0051] in:

[0052] ω=2πf;

[0053] Where ρ0 is the air density, c0 is the speed of sound, γ is the dynamic viscosity of air, is the kinematic viscosity, ω is the angular frequency k m , r, k r , m is an intermediate quantity in calculation and has no specific meaning.

[0054] S4, establish a genetic algorithm optimization calculation model, set four operation parameters: population size, maximum genetic generation, crossover rate and mutation rate. Use the model to calculate, and finally optimize iteratively to obtain the optimal aperture d c , porosity σ c , plate thickness t c , cavity depth D c Take the value and calculate the micropore sound absorption coefficient α′ c .

[0055] The genetic algorithm is calculated using the Matlab program, and the maximum area method or the maximum area ratio method is used as the fitness function of the optimization calculation model to reflect the size of the sound absorption coefficient. Among them, formula (5) is the fitness function Max A of the maximum area method, and formula (6) is the fitness function Max A′ of the maximum area ratio method:

[0056] Max A=∫g(d c ,σ c , t c , D c ,f)δ(f)df (5)

[0057] Where, the reverberation frequency f is within 20Hz-8000Hz; δ(f) is the weight factor that changes with the reverberation frequency, and its value range is 0-1, f max is the maximum reverberation frequency, f min is the minimum reverberation frequency.

[0058] S5, according to the micropore target sound absorption coefficient α in S2 c and the micropore sound absorption coefficient α′ calculated by the genetic algorithm in S4 cSize relationship determines the effectiveness of micropore parameter optimization calculation:

[0059] When α′ c ≥α c When , the requirements are met, the micropore parameters obtained in S4 are taken as the optimal micropore parameters, and the method ends;

[0060] Otherwise, return to S2 and adjust (increase) the microporous material installation area S c S3 and S4 are recalculated until the optimal micropore parameters are obtained and the method ends.

[0061] Example

[0062] Taking a railway station as an example, the elevated waiting hall is a rectangle with a plane of 214.5m×192.0m, and the projected area is 41184m 2 The waiting hall's ceiling is a concave arch, with its highest point approximately 39 meters above the ground. The surrounding walls are glass or curtain walls with a sound absorption coefficient of 0.23; the floor is granite with a sound absorption coefficient of 0.1. The space contains leather seats, sound-absorbing flaps, and sound-absorbing side panels, with sound absorption coefficients of 0.25, 0.66, and 0.66, respectively. The ceiling is not equipped with microporous sound absorption holes, and the initial reverberation time T0 is 7.2s, which does not meet the 5.5s specified in the "Code for Design of Railway Passenger Stations" (TB10100-2018).

[0063] Considering the lighting effect of the ceiling, half of the area is made of microporous materials. In order to make the target reverberation time of the station room 5.5s, the target sound absorption coefficient α of the microporous material is calculated. c It should be at least 0.56.

[0064] Using the maximum area method, the fitness function is established as:

[0065] Max A=∫g(d c ,σ c , t c , D c ,f)δ(f)df

[0066] According to the engineering installation conditions, the back cavity is only within 300mm. Set the aperture d c , porosity σ c 、plate thickness t c , cavity depth D c The value range is: 0.1mm≤d c ≤1mm, 0.1%≤σ c ≤3%, 0.01mm≤t c ≤1mm、10mm≤D c≤300mm, reverberation frequency f is 200Hz-5000Hz. In the Matlab genetic algorithm toolbox, the population size is set to 200, the number of genetic iterations is 800, the crossover rate is 0.9, and the mutation rate is 0.1. The iteration step of aperture and plate thickness is 0.1, the iteration step of perforation rate is 0.1%, and the iteration step of empty wall depth is 1. The micropore parameters obtained by calculation are aperture d c is 0.11mm, porosity σ c 2.4%, plate thickness t c The cavity depth D is 0.11 mm. c The micropore sound absorption coefficient α′ is calculated accordingly. c is 0.68. c >α c , meeting the optimization calculation requirements.

[0067] Based on the obtained microporous parameters, the microporous materials used in the construction were selected. After the construction was completed, on-site testing was carried out, and the reverberation time of the site was measured using the interrupted sound source method. As shown in Figure 2, a total of 6 points were tested, including M1-M6, with two sound sources S1 and S2 emitting sound. B1 represents the entrance to the station, and KZ represents the pillars in the railway station. The test obtained 12 sets of reverberation time data. For the S1 sound source, the reverberation time of each point is T1 M1 =5s; T1 M2 =4.8s; T1 M3 =4.7s; T1 M4 =4.9s; T1 M5 =4.5s; T1 M6 =4.1s; for the S2 sound source, the reverberation time at each point is T2 M1 =5.5s; T2 M2 =3.8s; T2 M3 =4.7s; T2 M4 =4.7s; T2 M5 =5.1s; T2 M6 =6.6s. The average reverberation time of the S1 sound source is 4.7s, and the average reverberation time of the S2 sound source is 4.9s, both meeting the specification requirements. The calculated effect of reverberation time control is consistent with the engineering application effect.

Claims

1. A method for optimizing the micropore parameters of a railway station building based on reverberation time control, characterized in that, It includes the following steps: S1. Calculate the initial reverberation time T0 and the initial average sound absorption coefficient in the space of the railway station building according to the spatial dimensions and building material types of the railway station building. It includes the following steps: S11. Assume that the spatial volume of the railway station building is V0, and the outline of the railway station building consists of n planes with different material properties. Then the initial reverberation time T0 is as follows: where S i is the area of the i-th plane, and α i is the sound absorption coefficient of the i-th plane; S12. Calculate the initial average sound absorption coefficient using the following formula where S0 is the total area of the n planes with different material properties, S2. Set the target reverberation time T and the microporous installation area S c , calculate the target sound absorption coefficient α of the railway station building c : Among them, is the target average sound absorption coefficient, S3. Set the value range of the micro-hole parameters and establish the micro-hole sound absorption coefficient α′ c and the functional relationship between the micro-hole parameters and the reverberation frequency f, where the micro-hole parameters include: pore diameter d c , porosity σ c , plate thickness t c and cavity depth D c ; The functional relationship is shown as follows: Among them, ω = 2πf; Wherein, ρ0 is the air density, c0 is the speed of sound, γ is the dynamic viscosity of air, η is the kinematic viscosity, and ω is the angular frequency; S4. Establish an optimization calculation model of the genetic algorithm, set the operation parameters and fitness function of the optimization calculation model of the genetic algorithm, obtain the optimized microporous parameters through the model, and calculate the corresponding microporous sound absorption coefficient α′ of the optimized microporous parameters c ; S5. Compare the microporous target sound absorption coefficient α c obtained in S2 c with the microporous sound absorption coefficient α' obtained in S4; When α′ c ≥ α c , the micropore parameters obtained in S4 are taken as the optimal micropore parameters; otherwise, return to step S2, adjust the installation area S of the microporous material c and recalculate the target sound absorption coefficient α c , and execute S3 and S4 until the optimal micropore parameters are obtained.

2. The method for optimizing the micropore parameters of a railway station building based on reverberation time control according to claim 1, wherein: In S2, when the space volume V0 of the railway station building ≤ 1 million cubic meters, the target reverberation time T ≤ 4 seconds; when the space volume V0 of the railway station building > 1 million cubic meters, the target reverberation time T ≤ 5.5 seconds.

3. The method for optimizing the micropore parameters of a railway station building based on reverberation time control according to claim 1, wherein: The value range of the micropore parameters described in S3 is: 0.1 mm ≤ d c ≤ 1 mm, 0.1% ≤ σ c ≤ 3%, 0.01 mm ≤ t c ≤ 3 mm, 10 mm ≤ D c ≤ 500 mm.

4. The method for optimizing the micropore parameters of a railway station building based on reverberation time control according to claim 1, wherein: In S4, the operation parameters include the population number, the maximum number of genetic generations, the crossover rate, and the mutation rate.

5. The method for optimizing the micropore parameters of a railway station building based on reverberation time control according to claim 1, wherein: In S4, the fitness function is the maximum area function Max A or the maximum area ratio function Max A', where: The maximum area function is Max A = ∫g(d c , σ c , t c , D c , f)δ(f)df; The maximum area ratio function is Wherein, the value range of f is 20 Hz - 8000 Hz; δ(f) is a weight factor varying with frequency, and its value range is 0 - 1, f max is the maximum reverberation frequency, f min is the minimum reverberation frequency.

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