Numerical Simulation Calculation Method and System for Sonic Wave Affecting Particle Coalescence

Abstract

The present invention provides a numerical simulation calculation method and system for the influence of sound waves on particle coalescence. This method uses the particle size binning method, which can be applicable to various types of particles undergoing coalescence without limitation, and can greatly improve the calculation efficiency. Moreover, this method can simulate the evolution process of cloud or aerosol particles over time under the action of artificial strong sound waves with different frequencies and intensities under different initial particle size spectrum distribution conditions. The influence of artificial strong sound waves on particle coalescence can be increased by simple modification, expanding the scenarios involved in the numerical simulation calculation results, providing convenience for conducting field tests.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical simulation, and particularly relates to a numerical simulation calculation method and system for the influence of sound waves on particle coalescence. Background Art

[0002] Influencing the coalescence process of cloud or aerosol particles through artificial strong sound waves, and then achieving the effects of fog dissipation, influencing cloud precipitation, and removing atmospheric aerosols, is a new means of artificial weather modification with development potential at present. Since there are still few field experiments at present, and the effects obtained from a small number of experiments are not clear enough, it is necessary to simulate and calculate the effects of artificial strong sound waves with different intensities and frequencies on particle coalescence through a numerical simulation calculation system, so as to be able to carry out field experiments scientifically and targeted in the future, and ultimately promote the development of new means of artificial weather modification.

[0003] At present, the numerical simulation calculation method for the influence of artificial strong sound waves on aerosol particle coalescence is mainly discrete element simulation (DEM), that is, many independent particles are set as discrete elements in the three-dimensional space simulation space, and their respective movement trajectories and the coalescence that occurs between them under the action of sound waves are simulated. However, this numerical simulation calculation method is time-consuming and inefficient.

[0004] In the existing numerical simulation calculation methods for the influence of artificial strong sound waves on weather and cloud / fog particle coalescence, only the capture of cloud / fog particles by larger hydrometeors (such as raindrops, graupel, snow), and the changes of cloud / fog through condensation and evaporation are considered. After cloud particles grow to a certain extent, they are automatically converted into rain at a certain proportion, ignoring the coalescence process of cloud / fog itself under natural conditions. Although this numerical simulation calculation method is highly efficient, this microphysical calculation method does not separately consider the coalescence of cloud / fog particles themselves, and it is not easy to increase the influence of artificial strong sound waves on particle coalescence through simple modification, resulting in a single scenario of numerical simulation calculation results and restricting the development of field experiments. Summary of the Invention

[0005] The present invention provides a numerical simulation calculation method and system for the influence of sound waves on particle coalescence to solve the defects existing in the prior art.

[0006] The present invention provides a numerical simulation calculation method for the influence of sound waves on particle coalescence, including:

[0007] Obtaining input condition parameters for numerical simulation calculation, where the input condition parameters include operating parameters, particle spectrum binning parameters, and physical parameters;

[0008] Based on the operating parameters and the physical parameters, determine the target acoustic perturbation velocity, the target dynamic viscosity, and the base of the critical velocity for particle coalescence, and based on the particle spectrum binning parameters, determine the binning information for each particle size bin and the initial value of the particle spectrum;

[0009] Based on the target acoustic perturbation velocity, the target dynamic viscosity, and the base of the critical velocity for particle coalescence, construct a coalescence kernel function model for two particles;

[0010] Based on the initial value of the particle spectrum and the coalescence kernel function model, perform a forward-time calculation on the number density source term of particle coalescence for each particle size bin to determine the evolution of the particle spectrum for each particle size bin without considering particle sedimentation scavenging.

[0011] According to a numerical simulation calculation method for acoustic wave influencing particle coalescence provided by the present invention, the input condition parameters further include container parameters;

[0012] After performing the forward-time calculation on the number density source term of particle coalescence for each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum for each particle size bin without considering particle sedimentation scavenging, it includes:

[0013] Determine the terminal velocity of particle fall;

[0014] Based on the terminal velocity of particle fall and the container parameters, determine the evolution of the particle spectrum after particle sedimentation scavenging for each particle size bin.

[0015] According to a numerical simulation calculation method for acoustic wave influencing particle coalescence provided by the present invention, after performing the forward-time calculation on the number density source term of particle coalescence for each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum for each particle size bin without considering particle sedimentation scavenging, it includes:

[0016] Determine the particle spectrum density at each forward-time calculation moment for each particle size bin without considering particle sedimentation scavenging;

[0017] Based on the particle spectrum density at each forward-time calculation moment for each particle size bin without considering particle sedimentation scavenging and the binning information, calculate the time variation sequences of the total particle number concentration and the total particle mass content with the forward-time calculation moment.

[0018] According to a numerical simulation calculation method for acoustic wave influencing particle coalescence provided by the present invention, the construction of a coalescence kernel function model for two particles based on the target acoustic perturbation velocity, the target dynamic viscosity, and the base of the critical velocity for particle coalescence specifically includes:

[0019] Determine the particle relaxation time based on the target dynamic viscosity, and determine the equilibrium velocity of the particles without the influence of turbulence based on the target dynamic viscosity and the particle relaxation time;

[0020] Determine the base of the particle coalescence kernel function based on the target acoustic perturbation velocity, the equilibrium velocity, and the particle relaxation time, and determine the particle coalescence efficiency based on the particle flow-around velocity;

[0021] Determine the coalescence kernel function model based on the base of the particle coalescence kernel function and the particle coalescence efficiency.

[0022] According to a numerical simulation calculation method for acoustic wave influencing particle coalescence provided by the present invention, the base of the particle coalescence kernel function includes the base of the particle coalescence kernel function based on the gravitational coalescence mechanism, the base of the particle coalescence kernel function based on the acoustic wave co-directional coalescence mechanism, and the base of the particle coalescence kernel function based on the acoustic wake coalescence mechanism;

[0023] Correspondingly, the particle coalescence efficiency includes the particle coalescence efficiency based on the gravitational coalescence mechanism, the particle coalescence efficiency based on the acoustic wave co-directional coalescence mechanism, and the particle coalescence efficiency based on the acoustic wake coalescence mechanism.

[0024] According to a numerical simulation calculation method for acoustic wave influencing particle coalescence provided by the present invention, before performing a forward-in-time calculation on the number density source term of particle coalescence at each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum without considering particle sedimentation removal at each particle size bin, it includes:

[0025] Determine the equivalent spherical diameter of each new particle after particle merging;

[0026] For any new particle, if it is determined that the new particle belongs to a first particle size bin other than the above-mentioned particle size bins based on the equivalent spherical diameter, determine the second particle size bin and the third particle size bin that are close to the first particle size bin among the above-mentioned particle size bins, and the second particle size bin and the third particle size bin are adjacent;

[0027] Calculate the number density weights of the second particle size bin and the third particle size bin due to the new particle, and calculate the number density source increased by the second particle size bin due to the new particle and the number density source increased by the third particle size bin due to the new particle based on the number density weight corresponding to the second particle size bin and the number density weight corresponding to the third particle size bin;

[0028] Based on the number density sources increased by the respective new particles for each particle size bin, determine the first number density source and the second number density source, and determine the number density source term for particle coalescence at each particle size bin.

[0029] According to a numerical simulation calculation method for the influence of sound waves on particle coalescence provided by the present invention, the particles involved in the method include cloud particles or aerosol particles.

[0030] The present invention also provides a numerical simulation calculation system for the influence of sound waves on particle coalescence, including:

[0031] A parameter acquisition module, configured to acquire input condition parameters for numerical simulation calculation, where the input condition parameters include operating parameters, particle spectrum binning parameters, and physical parameters;

[0032] An initialization module, configured to determine a target sound wave perturbation velocity, a target dynamic viscosity, and a base particle coalescence critical velocity based on the operating parameters and the physical parameters, and determine the binning information and the initial particle spectrum value for each particle size bin based on the particle spectrum binning parameters;

[0033] A model construction module, configured to construct a coalescence kernel function model for two particles based on the target sound wave perturbation velocity, the target dynamic viscosity, and the base particle coalescence critical velocity;

[0034] A numerical simulation calculation module, configured to perform a forward-in-time calculation on the number density source term for particle coalescence at each particle size bin based on the initial particle spectrum value and the coalescence kernel function model, and determine the particle spectrum evolution without considering particle sedimentation scavenging at each particle size bin.

[0035] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the program, it implements the numerical simulation calculation method for the influence of sound waves on particle coalescence as described in any one of the above.

[0036] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the numerical simulation calculation method for the influence of sound waves on particle coalescence as described in any one of the above.

[0037] The numerical simulation calculation method and system for the influence of sound waves on particle coalescence provided by the present invention adopt the method of particle size binning, which can be applicable to various types of particles undergoing coalescence without limitation, and can greatly improve the calculation efficiency. Moreover, this method can simulate the evolution process of cloud or aerosol particles over time under the action of artificial intense sound waves with different frequencies and intensities under different initial particle size spectrum distribution conditions. The influence of artificial intense sound waves on particle coalescence can be increased by simple modification, expanding the scenarios involved in the numerical simulation calculation results, providing convenience for carrying out field tests. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0039] Figure 1 It is a schematic diagram showing the movement trajectories of two particles under the action of sound waves in a discrete element simulation;

[0040] Figure 2 It is a schematic flow chart of the numerical simulation calculation method for the influence of sound waves on particle coalescence provided by the present invention;

[0041] Figure 3 It is a schematic diagram showing the simulation results of the numerical simulation calculation method for the influence of sound waves on particle coalescence provided by the present invention;

[0042] Figure 4 It is a schematic diagram showing the observed phenomena in the indoor fog dissipation test of artificial intense sound waves in Reference [1];

[0043] Figure 5 It is a schematic diagram showing the comparison results of the simulated aerosol dissipation effect of sound waves by the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention and the actual indoor test observations in Reference [2];

[0044] Figure 6 It is a schematic diagram showing the evolution results of the particle spectrum of the simulated aerosol dissipation by sound waves using the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention;

[0045] Figure 7 It is a schematic diagram showing the simulation results of the discrete element simulation scheme in Reference [2];

[0046] Figure 8 It is a schematic diagram showing the structure of the numerical simulation calculation system for the influence of sound waves on particle coalescence provided in the embodiments of the present invention;

[0047] Figure 9 It is a schematic diagram showing the structure of the electronic device provided by the present invention. Detailed implementation manners

[0048] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0049] Influencing the coalescence process of cloud or aerosol particles through artificial strong sound waves, and then achieving the effects of fog dissipation, influencing cloud precipitation, and removing atmospheric aerosols, is a new means of artificial weather modification with development potential at present. Some indoor experiments have proved that artificial strong sound waves can achieve fog dissipation and aerosol dissipation. Under the drive and influence of continuous strong sound waves, micron-scale particles can undergo additional relative motion, and thus form larger particles through coalescence (also known as aggregation and agglomeration) and accelerate their sinking. However, there are still few field experiments at present, and the effects obtained from a small number of experiments are not clear enough. This is because, on the one hand, the actual atmospheric conditions (such as the generation of natural fog) are not controllable like in the laboratory; on the other hand, the scale distribution spectra of cloud and aerosol particles in the actual atmosphere have large variability, which may be quite different from the particles with fixed size and single size distribution manufactured in the laboratory, and their responses to sound wave frequencies are also different. This requires a numerical simulation system to simulate and evaluate the effects of artificial strong sound waves with different intensities and frequencies on the coalescence of cloud or aerosol particles, so as to be able to carry out field experiments scientifically and targeted afterwards, and ultimately promote the development of new means of artificial weather modification.

[0050] At present, the numerical simulation calculation method for artificial strong sound waves to influence the coalescence of aerosol particles is mainly discrete element simulation (DEM), that is, many independent particles are set as discrete elements in the three-dimensional space simulation space, and their respective movement trajectories and the coalescence that occurs between them under the action of sound waves are simulated. Its main principle and key steps are as follows:

[0051] A. According to the initial conditions of the particle number concentration (such as N particles / m 3 ) and the particle size spectrum distribution, set V*N particles with specified sizes and random positions in the finite three-dimensional space V (m 3 );

[0052] B. According to the conditions of the artificial sound wave, such as the sound pressure level and frequency, calculate the sound disturbance velocity (periodically changing) at a certain time point;

[0053] C. According to the theoretical formula, calculate the airflow around each particle when affected by the sound disturbance velocity;

[0054] D. Calculate the airflow influence on each particle generated by other surrounding particles (for example, the airflow weakening caused by other particles blocking the windward side).

[0055] E. According to the sum of the original acoustic disturbance airflow and the airflow velocity under the influence of other particles received by each particle at the current time, calculate the force on the particle according to the aerodynamic drag principle of spherical particles. Combine with gravity to calculate the acceleration, velocity, and motion trajectory of the particle.

[0056] F. Perform forward calculation in time, determine coalescence according to the distance between two particles and the cut-off diameter. Finally, obtain the change of particle number concentration with time.

[0057] Figure 1 It is a schematic diagram of the movement trajectory of two particles in discrete element simulation under the action of sound waves. This technology is currently mainly aimed at the problem of removing particulate pollutants emitted in industry, that is, the problem of artificial strong sound waves affecting aerosol coalescence in a limited and extremely small space.

[0058] However, this discrete element simulation method is time-consuming and inefficient: hundreds or even thousands of particles need to be initially placed to make the simulation process with random initial positions representative and reliable. However, for each calculation time step, the relative positions of particles need to be calculated pairwise. Even with algorithm optimization, its time complexity is still close to the square of the number of particles participating in the simulation. On high-performance desktop computers and small workstations, the typical time consumption for simulating the evolution process of artificial strong sound wave aerosol removal in a few seconds is several hours to dozens of hours. This low computational efficiency cannot meet the research on simulating the influence of artificial strong sound waves on highly variable clouds and aerosols in the actual atmosphere.

[0059] Existing numerical simulation calculation methods for the influence of artificial strong sound waves on weather and cloud / fog particle coalescence also use weather and cloud / fog numerical models. Weather and cloud / fog numerical models generally do not specifically consider the coalescence effect between cloud / fog particles, only consider the capture of cloud / fog particles by larger hydrometeors (such as raindrops, graupel, snow), and the changes of cloud / fog through condensation and evaporation. After cloud particles grow to a certain extent, they are automatically converted into rain at a certain proportion, ignoring the natural coalescence process of cloud / fog itself. This is because the size of cloud / fog particles themselves is very small (the typical size order is 10μm or smaller), resulting in a very small probability of their mutual coalescence. In the actual atmosphere, the influence of condensation and evaporation processes on the change of the size distribution spectrum of cloud and fog particles is much greater than the influence brought by their own mutual coalescence.

[0060] In weather and cloud / fog numerical models, the variables characterizing clouds / fogs are usually differential variables, such as the number concentration of hydrometeor particles (number of particles per unit volume), water content, or specific content (particle mass per unit volume or per unit air parcel mass), etc., in order to study different atmospheric processes ranging from the meter scale to over a hundred kilometers scale, rather than taking a single particle as the research and calculation object.

[0061] When calculating the changes in variables such as the number concentration and specific content of cloud and fog particles in weather and cloud / fog numerical models, the calculation schemes are generally divided into two major categories: parameterization calculation schemes and binning calculation schemes.

[0062] Among them, the parameterization calculation scheme assumes that the particle size follows a certain distribution, such as a single-parameter, double-parameter, or triple-parameter Gamma distribution, and the Gamma distribution is a distribution characterizing an exponential or left-skewed unimodal type. Currently, there is no theoretical and experimental result indicating that cloud and fog or aerosol particles can still maintain an exponential or left-skewed unimodal type for evolution under the action of artificial strong sound waves. Therefore, simply modifying the correlation coefficients and parameters related to the changes of cloud particles in the existing cloud microphysical parameterization scheme empirically or simply cannot scientifically and accurately reflect the influence of artificial strong sound waves on the coalescence of cloud and fog particles.

[0063] The binning calculation scheme divides particles into bins according to their sizes, and then calculates the evolution of particles of different sizes separately. Since it does not fix the particle spectrum type, the binning calculation scheme is more scientific and accurate than the parameterization calculation scheme. Although the calculation efficiency of the binning calculation scheme is slightly lower than that of the parameterization calculation scheme, it is still much higher than that of the discrete element simulation. However, in the existing binning calculation schemes, the coalescence of cloud and fog particles themselves is not considered separately, and it is not easy to increase the influence of artificial strong sound waves on particle coalescence by simple modification, resulting in a single scenario of the numerical simulation calculation results and restricting the implementation of field tests. Therefore, in the embodiments of the present invention, a numerical simulation calculation method capable of reflecting the influence of artificial strong sound waves on the coalescence of cloud, fog, aerosol and other particles is provided.

[0064] Figure 2 It is a schematic flow chart of a numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention, as Figure 2 shown, the method includes:

[0065] S1, obtaining input condition parameters for numerical simulation calculation, where the input condition parameters include operation parameters, particle spectrum binning parameters, and physical parameters;

[0066] S2, determining the target sound wave perturbation velocity, target dynamic viscosity, and the base of the particle coalescence critical velocity based on the operation parameters and the physical parameters, and determining the binning information of each particle size bin and the initial value of the particle spectrum based on the particle spectrum binning parameters;

[0067] S3. Based on the target acoustic wave perturbation velocity, the target dynamic viscosity, and the base of the critical particle coalescence velocity, construct a coalescence kernel function model for two particles;

[0068] S4. Based on the initial particle spectrum and the coalescence kernel function model, perform a forward-in-time calculation on the number density source term of particle coalescence for each particle size bin to determine the evolution of the particle spectrum for each particle size bin without considering particle sedimentation scavenging.

[0069] Specifically, in the embodiment of the present invention, the numerical simulation calculation method for acoustic wave influencing particle coalescence has an execution subject which is a numerical simulation calculation system for acoustic wave influencing particle coalescence. This system can be configured in a server, and the server can be a local server or a cloud server. The local server can specifically be a computer, etc., and the embodiment of the present invention does not make specific limitations in this regard.

[0070] First, execute step S1 to obtain the input condition parameters for numerical simulation calculation. The input condition parameters refer to the condition parameters input by the user for numerical simulation calculation. Table 1 is a summary table of the input condition parameters involved in the embodiment of the present invention, and the input condition parameters can include operation parameters, particle spectrum binning parameters, and physical parameters. The operation parameters are the parameters required for the operation of the numerical simulation calculation method, and can include the forward calculation time step, the total simulation calculation time, the sound pressure level of the acoustic wave, the initial acoustic wave perturbation velocity amplitude, the acoustic wave frequency, and the coalescence mechanism switch. It can also include the gravity sedimentation mechanism switch.

[0071] Here, the initial acoustic wave perturbation velocity amplitude can be -1 or a value greater than 0. The involved coalescence mechanisms can include the acoustic wake coalescence mechanism. In addition, it can also include the gravity coalescence mechanism and the acoustic wave co-directional coalescence mechanism. Therefore, the coalescence mechanism switch can include the gravity coalescence mechanism switch, the acoustic wave co-directional coalescence mechanism switch, and the acoustic wake coalescence mechanism switch.

[0072] The particle spectrum binning parameters are the particle spectrum parameters of multiple particle size bins obtained by dividing all the particles involved in the numerical simulation calculation according to size, and can include the serial number of the initial particle spectrum distribution model, the first parameter of the initial particle spectrum, the second parameter of the initial particle spectrum, the initial total concentration, the lower limit of the particle spectrum binning, the upper limit of the particle spectrum binning, the particle spectrum binning interval, and the truncation diameter of the initial particle spectrum.

[0073] It can be understood that the initial particle spectrum distribution model can include the gamma distribution and the log-normal distribution. The model serial number of the gamma distribution is 1, and the model serial number of the log-normal distribution is 2. In model 1, the first parameter is the volume equivalent median diameter D0 (μm), and the second parameter is the spectral parameter μ. In model 2, the first parameter is the geometric mean diameter (μm), and the second parameter is the geometric standard deviation (μm).

[0074] The physical parameters are used to characterize the physical properties of each particle involved in the numerical simulation calculation and the physical properties of the air in the container where all particles are located. The physical properties of the particles may include particle density, initial dynamic viscosity, particle restitution coefficient, Hamaker constant, minimum interactive contact distance of the particles, and limiting contact pressure. The physical properties of the air may include air pressure, air temperature, and relative humidity. The initial dynamic viscosity may be -1 or a value greater than 0.

[0075] In addition, the input condition parameters further include container parameters, and the container parameters may be the height of the container where all particles are located. For the comparative simulation of indoor experiments, it is set according to the actual height of the container. For the simulation of defogging / aerosol experiments in the simulated outdoor open space, it is set to 1 per unit length.

[0076] Table 1 Summary table of input condition parameters

[0077]

[0078] It should be noted that d involved in the recommended value range in Table 1 represents double-precision scientific notation. Taking 1d8 as an example, it represents double-precision 10 8 .

[0079] Then, step S2 is executed, and according to the operating parameters and physical parameters, the target acoustic wave perturbation velocity, the target dynamic viscosity, and the base of the critical particle coalescence velocity are determined.

[0080] The target acoustic wave perturbation velocity refers to the acoustic wave perturbation velocity whose amplitude is determined based on the amplitude of the initial acoustic wave perturbation velocity and is used for numerical simulation calculation. If the amplitude of the initial acoustic wave perturbation velocity is -1, the amplitude of the target acoustic wave perturbation velocity can be determined by combining the sound pressure level of the acoustic wave with the physical parameters.

[0081] In the embodiments of the present invention, the sound pressure level (SPL) of the acoustic wave is usually used to quantitatively describe the intensity of the sound field. The relationship between SPL (dB) and the sound intensity I (W / m 2 ), and the amplitude U0 (m / s) of the target acoustic wave perturbation velocity can be converted through the following relationship:

[0082]

[0083]

[0084]

[0085]

[0086] Among them, P ref is the reference sound pressure, taking 2×10-5 Pa. P e (Pa) is the effective sound pressure, U e (m / s) is the effective perturbation velocity, ρ g (kg / m 3 ) is the air density, c s (m / s) is the estimated value of the adiabatic sound speed, R d is the air gas constant, T k is the Kelvin temperature of the air.

[0087] Through the input SPL and physical parameters, the amplitude U0 of the target acoustic wave perturbation velocity can be calculated using formulas (1)-(4).

[0088] In the embodiments of the present invention, the acoustic wave used can be an artificial intense acoustic wave. The acoustic wave intensity corresponding to this intense acoustic wave should be able to cause a meaningful movement change in the acting objects, namely clouds and aerosol particles, that is different from natural perturbations. The numerical values corresponding to the sound pressure level and each sound perturbation variable are shown in Table 2. When the sound pressure level reaches or exceeds the 130 dB level, a perturbation velocity greater than 0.1 m / s, which is of meteorological discussion significance, can be generated.

[0089] Table 2 Numerical table of SPL corresponding to sound perturbation variables

[0090]

[0091] If the amplitude of the initial acoustic wave perturbation velocity is greater than 0, then this amplitude of the initial acoustic wave perturbation velocity can be used as the amplitude of the target acoustic wave perturbation velocity.

[0092] Dynamic viscosity is a key parameter that determines the ability of the reciprocating oscillating airflow in the acoustic wave field to carry cloud and fog particles. The target dynamic viscosity refers to the dynamic viscosity determined based on the initial dynamic viscosity and used for numerical simulation calculations. If the initial dynamic viscosity is -1, then the target dynamic viscosity can be determined through physical parameters.

[0093] The target dynamic viscosity can include the target dynamic viscosity μ of dry air d (Pa·s) and the dynamic viscosity μ of moist air g (Pa·s). μ d can be calculated through formula (5), μ g can be calculated through formula (6).

[0094]

[0095]

[0096] μ v = (-8×10 -7 T c 2+4.01×10 -2 T c +8.022)×10 -6 (7)

[0097] Among them, μ v is the water vapor dynamic viscosity calculated by an empirical formula, q is the specific humidity (kg / kg), which is obtained by converting according to the input air temperature and relative humidity by a general meteorology formula; μ g is the dynamic viscosity of humid air, which is calculated by a binary component formula; T c is the air temperature in degrees Celsius (°C).

[0098] If the initial dynamic viscosity is greater than 0, the initial dynamic viscosity can be used as the target dynamic viscosity.

[0099] The base of the critical velocity for particle coalescence refers to the constant in the calculation formula of the critical velocity for judging whether two particles will coalesce after collision. Since two particles do not necessarily coalesce after collision, they may also undergo elastic collision and bounce off in other directions. One of the indicators for judging whether two particles will coalesce is the critical velocity u cr , and its calculation formula is:

[0100] u cr = C ucr / d(8)

[0101] Among them, d is the particle diameter, and the smaller particle diameter of the two colliding particles can be taken. C ucr is the base of the critical velocity for particle coalescence, which is a constant independent of the particle scale and only related to the particle material, and it can be calculated based on physical parameters. The calculation formula is:

[0102]

[0103] Among them, e0 is the coefficient of restitution (usually the value can be taken as 0.4 - 0.6), H am is the Hamaker constant related to the molecular attraction of particles (usually 1×10 -19 ~5×10 -19 J), z0 is the minimum interaction contact distance of particles (usually taken as 0.4 nm), P p is the restricted contact pressure of particles (5×10 9 Pa), ρ w is the density of particles (kg / m 3 ).

[0104] In the embodiments of the present invention, the binning information of each particle size bin and the initial value of the particle spectrum can also be determined according to the particle spectrum binning parameters. The binning information may include the binning boundaries, binning center values, and binning widths of each particle size bin.

[0105] The bin boundaries D*(μm) for each particle size bin can be calculated from the lower limit lgmin of the particle spectrum bin, the upper limit lgmax of the particle spectrum bin, and the bin interval lgdif of the particle spectrum:

[0106] D * = 10 lgmin:lgdif:lgmax (10)

[0107] For example, if the lower limit lgmin of the particle spectrum bin is -0.1, the upper limit lgmax of the particle spectrum bin is 3.7, and the bin interval lgdif of the particle spectrum is 0.1, then there are 39 bin boundaries and 38 particle size bins in total, covering a size range from less than 1 μm to greater than 5 mm, in order to characterize the size ranges of common solid (aerosol) and liquid (cloud and raindrop) particles in the atmosphere.

[0108] The bin center value D of each particle size bin can be calculated by formula (11), and the bin width dD of each particle size bin can be calculated by formula (12).

[0109] D i = (D * i + D * i+1 ) / 2 (11)

[0110] dD i = (D * i+1 - D * i ) (12)

[0111] Where D i is the bin center value of the i-th particle size bin, D * i is the i-th bin boundary, D * i+1 is the (i + 1)-th bin boundary, and dD i is the bin width of the i-th particle size bin.

[0112] In the embodiments of the present invention, the initial value of the particle spectrum can either be the number density (per m -3 ·μm -1 ) set for each particle spectrum scale bin according to the observed data, or, for the convenience of input, the initial value of the particle spectrum can be set to follow a Gamma distribution or a normal distribution, so that only three particle spectrum bin parameters, namely the first parameter of the initial value of the particle spectrum, the second parameter of the initial value of the particle spectrum, and the initial value of the total concentration, are input for setting the initial value of the particle spectrum.

[0113] For the Gamma distribution, the initial value of the particle spectrum, i.e., the spectral density formula, is as follows:

[0114]

[0115] where N T is the initial value of the total number concentration (unit: m -3 ), D is the particle diameter, D0 is the median volume diameter of the particles (unit: μm), D0 is defined as the particle diameter corresponding to the integral median of the total particle volume, and the definition expression is shown in formula (14). μ is the spectral type parameter (should be greater than -1 according to the mathematical consistency of Gamma, dimensionless). When μ is larger, the particle spectrum is narrower and closer to the central unimodal distribution. When μ is 0 or less than 0, the particle spectrum is closer to the exponential distribution.

[0116]

[0117] For the normal distribution, the initial value of the particle spectrum, i.e., the spectral density formula, is as follows:

[0118]

[0119] where N T is the initial value of the total number concentration, D a is the average particle diameter, and σ is the standard deviation of the particle diameter.

[0120] In addition, under natural conditions, the maximum value of a particle distribution may not reach the maximum value of the measurement range. Therefore, when assigning the initial value of the particle spectrum, it is also necessary to consider that the assignment range may not reach the upper limit of the particle size bin at the initial moment. Therefore, the initial value truncation diameter of the particle spectrum is introduced. If the initial value truncation diameter of the particle spectrum is greater than 0, the initial value of the particle spectrum in the particle size bin with a particle diameter greater than the initial value truncation diameter of the particle spectrum can be set to 0.

[0121] After that, step S3 is executed to construct a collision kernel function model for two particles based on the target acoustic wave perturbation velocity, the target dynamic viscosity, and the critical velocity base of particle coalescence.

[0122] For two particles with diameters D1 and D2 (corresponding radii R1 and R2 respectively), the collision kernel function model K(m 3 / s) can be expressed by formula (16):

[0123] K(R1, R2) = E1·E2·π·(R1 + R1) 2 ·|U dif (R1, R2)| (16)

[0124] Among them, K refers to the instantaneous volume change rate when two particles merge into one particle, which is equivalent to the rate at which two particles merge into one particle within a fixed volume. By fixing the diameter of the i-th particle and performing spectral integration along the j-th particle, the rate of decrease in the number density of the i-th particle due to particle coalescence can be obtained. |U dif (R1, R2)| is the base of the particle collision kernel function and is the relative velocity U of two particles dif (R1, R2) of the absolute value. Both E1 and E2 are particle collision efficiencies or particle capture coefficients, representing the reduction effects of the collision success rate caused by the flow-around effect that causes the opposite movement to bypass and bounce off without merging after separation. Here, E1 is denoted as the first particle collision efficiency, and E2 is denoted as the second particle collision efficiency.

[0125] The relative velocity U of two particles dif (R1, R2) can include the relative velocity based on the gravitational collision mechanism, the relative velocity based on the acoustic wave co-directional coalescence mechanism, and the relative velocity based on the acoustic wake coalescence mechanism, which are respectively denoted as the first relative velocity, the second relative velocity, and the third relative velocity. The first relative velocity refers to the relative velocity U between particles of different sizes caused by natural gravity dif,g , the second relative velocity refers to the relative velocity U caused by the different abilities of acoustic waves to carry particles of different sizes dif,ac , and the third relative velocity refers to the relative velocity U caused by the acoustic wake effect (the two particles alternately block each other from the aerodynamic force of the acoustic perturbation) dif,tail .

[0126] In the embodiments of the present invention, U dif (R1, R2) and E1 and E2 can all be determined in combination with the target acoustic wave perturbation velocity, the target dynamic viscosity, and the base of the particle merging critical velocity, and then a collision kernel function model can be constructed.

[0127] Finally, step S4 is executed. Through the initial value of the particle spectrum and the collision kernel function model, the time-forward calculation of the number density source term of particle collisions at each particle size bin is performed to determine the evolution of the particle spectrum at each particle size bin without considering particle sedimentation removal. In this process, the sink term of the bin collision at the current moment can be calculated first according to the initial value of the particle spectrum and the collision kernel function model, then the source term of the bin collision at the current moment can be calculated according to the sink term of the bin collision at the current moment, and finally, the new particle spectrum at the current moment can be calculated according to the source term of the bin collision at the current moment and output the new particle spectrum at the current moment. After that, the time step is increased at the current moment, and the above calculation process is repeated until the specified simulation time is reached, and the time-forward calculation is ended.

[0128] It can be understood that during the forward time calculation process, the particle sedimentation removal situation can be not considered, that is, the value of the gravity sedimentation mechanism switch in the input condition parameters is 0.

[0129] The numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention adopts a particle size binning method, which can not limit the types of particles that undergo coalescence, and its calculation efficiency can be greatly improved. Moreover, this method can simulate the evolution process of cloud or aerosol particles over time under the action of artificial strong sound waves with different frequencies and intensities under different initial particle size spectrum distribution conditions, and can increase the influence of artificial strong sound waves on particle coalescence by simple modification, increasing the scenarios involved in the numerical simulation calculation results, providing convenience for carrying out field tests.

[0130] Based on the above embodiments, in the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention, the input condition parameters further include container parameters;

[0131] Based on the initial particle spectrum and the coalescence kernel function model, perform a forward time calculation on the number density source term of particle coalescence at each particle size bin, determine the particle spectrum evolution without considering particle sedimentation removal at each particle size bin, and then include:

[0132] Determine the terminal velocity of particle fall;

[0133] Based on the terminal velocity of particle fall and the container parameters, determine the particle spectrum evolution after particle sedimentation removal at each particle size bin.

[0134] Specifically, in the embodiments of the present invention, when the value of the gravity sedimentation mechanism switch in the input condition parameters is 1, the particle sedimentation removal situation needs to be considered. At this time, after performing a forward time calculation on the number density source term of particle coalescence at each particle size bin through the initial particle spectrum and the coalescence kernel function model, and determining the particle spectrum evolution without considering particle sedimentation removal at each particle size bin, the terminal velocity of particle fall can also be determined first.

[0135] For the equilibrium velocity v without the influence of turbulence T , it should be the velocity when the aerodynamic drag during particle fall is balanced with the gravitational acceleration g, and is obtained by solving the following quadratic equation:

[0136]

[0137] where τ is the particle relaxation time. That is:

[0138] τ = 2ρ w R 2 / 9μ g (18)

[0139] Equation (17) will be used as the basis for calculating the relative motion velocity based on the gravitational coalescence mechanism.

[0140] For the problem of particle sedimentation removal, considering that when comparing with indoor experiments, there will be particles continuously falling to the bottom of the container, forming a particle removal effect in the observation space. Using Equation (17) as the calculation of the final falling velocity of the removed particles will result in an overestimated removal effect. Therefore, when calculating sedimentation removal, the commonly used final falling velocity v of particles under turbulent background is used. turb Calculation method:

[0141] v turb = 1.74(Dρ g g / ρ w ) 0.5 (19)

[0142] where D is the particle diameter, and ρ w is the particle density.

[0143] Since the input condition parameters include container parameters, that is, the height of the container. Therefore, by combining the final falling velocity of particles and the container parameters, the particle spectrum evolution without considering particle sedimentation removal for each particle size bin is updated, and then the particle spectrum evolution after particle sedimentation removal for each particle size bin can be determined. There is:

[0144] n(D) t＝0.5 = n(D) t＝0 ·exp(C vtg ) (20)

[0145] C vtg = -dt·v turb ·exp(-T pass ·g / v turb ) / L cont (21)

[0146] where T pass is the time (in s) that has passed in the numerical simulation calculation, and L cont is the height of the container (in m). n(D) t＝0.5 is the particle number density after particle sedimentation removal for each particle size bin.

[0147] Based on the above embodiments, in the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention, based on the particle spectrum initial value and the coalescence kernel function model, the time-forward calculation of the number density source term of particle coalescence for each particle size bin is performed to determine the particle spectrum evolution without considering particle sedimentation removal for each particle size bin. Then, it includes:

[0148] Determine the particle spectral density at each forward calculation time without considering particle sedimentation scavenging for each particle size bin;

[0149] Based on the particle spectral density at each forward calculation time without considering particle sedimentation scavenging for each particle size bin and the bin information, calculate the time variation sequences of the total particle number concentration and the total particle mass content with respect to the forward calculation time.

[0150] Specifically, in the embodiments of the present invention, the particle spectrum evolution without considering particle sedimentation scavenging for each particle size bin, that is, the time variation sequence of the particle spectral density without considering particle sedimentation scavenging for each particle size bin. Therefore, after determining the particle spectrum evolution without considering particle sedimentation scavenging for each particle size bin, the particle spectral density at each forward calculation time without considering particle sedimentation scavenging for each particle size bin can be determined. Thereafter, the time variation sequences of the total particle number concentration and the total particle mass content with respect to the forward calculation time can be calculated by combining the particle spectral density at each forward calculation time without considering particle sedimentation scavenging for each particle size bin and the bin information.

[0151] For a certain forward calculation time, according to the particle spectral density N(D i ) at this forward calculation time without considering particle sedimentation scavenging in the i-th particle size bin, the particle diameter D i and the bin width dD i , the calculation formula for the total particle number concentration N T is as follows:

[0152]

[0153] The calculation formula for the total particle mass W is as follows:

[0154]

[0155] Thereafter, the time variation sequence of the total particle number concentration N T and the total particle mass content W without considering particle sedimentation scavenging with respect to the forward calculation time can be obtained.

[0156] It can be understood that the total particle number concentration N T and the total particle mass content W can also be calculated according to formula (22) and formula (23) by combining the particle spectral density at each forward calculation time after particle sedimentation scavenging for each particle size bin and the bin information, and then the time variation sequences of the two after particle sedimentation scavenging with respect to the forward calculation time can be obtained.

[0157] Based on the above embodiments, in the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention, the coalescence kernel function model of two particles is constructed based on the target sound wave perturbation velocity, the target dynamic viscosity, and the critical velocity base for particle coalescence, specifically including:

[0158] Based on the target dynamic viscosity, determine the particle relaxation time, and based on the target dynamic viscosity and the particle relaxation time, determine the equilibrium velocity of the particle without the influence of turbulence;

[0159] Based on the target sound wave perturbation velocity, the equilibrium velocity, and the particle relaxation time, determine the base of the particle coalescence kernel function, and based on the particle flow-around velocity, determine the particle coalescence efficiency;

[0160] Based on the base of the particle coalescence kernel function and the particle coalescence efficiency, determine the coalescence kernel function model.

[0161] Specifically, in the embodiments of the present invention, when constructing the coalescence kernel function model of two particles, the particle relaxation time can be first determined according to the target dynamic viscosity through formula (18).

[0162] Then, through the target dynamic viscosity and the particle relaxation time, the equilibrium velocity of the particle without the influence of turbulence is determined through formula (17).

[0163] After that, in combination with the target sound wave perturbation velocity, the equilibrium velocity, and the particle relaxation time, the base of the particle coalescence kernel function is determined.

[0164] The base of the particle coalescence kernel function may include the base of the particle coalescence kernel function based on the gravity coalescence mechanism, the base of the particle coalescence kernel function based on the sound wave co-directional coalescence mechanism, and the base of the particle coalescence kernel function based on the acoustic wake coalescence mechanism, which are respectively the absolute value of the first relative motion velocity |U dif,g |, the absolute value of the second relative motion velocity |U dif,ac |, and the absolute value of the third relative motion velocity |U dif,tail |.

[0165] For the gravity coalescence mechanism, the calculation scheme of the relative motion velocity of two particles i and j is:

[0166] U dif,g = v T (R2) - v T (R1) (24)

[0167] Wherein, R1 is the radius of particle i, and R2 is the radius of particle j. v T (R2) is the equilibrium velocity of particle j, and v T (R1) is the equilibrium velocity of particle i.

[0168] For the acoustic wave co - flow coalescence mechanism, the calculation scheme of the relative motion velocity of particles i and j under the target acoustic wave perturbation velocity amplitude U0 and the acoustic wave angular velocity ω is as follows:

[0169]

[0170] For the acoustic wake coalescence mechanism, the calculation scheme of the relative motion velocity of particles i and j under the target acoustic wave perturbation velocity amplitude U0 and the acoustic wave angular velocity ω is as follows:

[0171] U dif,tail = 2×B(R1,R2) / L (26)

[0172]

[0173]

[0174] Among them, formula (26) consists of two parts, B and L. B is only related to the dynamic parameters and acoustic wave conditions and can be pre - calculated. L is the average particle spacing and is continuously updated during the simulation.

[0175] After that, combined with the particle flow - around velocity, the particle collision efficiency is determined. The particle collision efficiency can include the particle collision efficiency based on the gravitational collision mechanism, the particle collision efficiency based on the acoustic wave co - flow coalescence mechanism, and the particle collision efficiency based on the acoustic wake coalescence mechanism. Also, since the particle collision efficiency includes the first particle collision efficiency E1 and the second particle collision efficiency E2, it is necessary to calculate E1 and E2 for the three coalescence mechanisms.

[0176] E1 under the gravitational collision mechanism is obtained from the flow - around simulation. What needs to be simulated is whether the flow - around around the small and large particles will cause the small particles to finally bypass the large particles without collision during the process of the relatively small particles gradually moving towards the relatively large particles. The relevant calculation scheme is as follows:

[0177] r * =(x 2 +y 2 ) 0.5 / R 1(2) (29)

[0178]

[0179]

[0180] V y =V r,Oseen sin(θ)+V θ,Oseen sin(θ - π / 2) (32)

[0181] θ sh =1 + Vr,Oseen cos(θ) + V θ,Oseen cos(θ - π / 2) (33)

[0182] where r * is a dimensionless distance, which is obtained by dividing the distance between two particles ((x 2 + y 2 ) 0.5 , where x is the direction in which the small particle initially moves towards the large particle, y is the direction perpendicular to x) by the radius (R1 or R2) of the particle around which the flow is calculated. V r,oseen and V θ,oseen are the radial and tangential flow velocities around the particles (both the small particle and the large particle need to be calculated) respectively. V y is the resultant velocity in the direction perpendicular to the sound wave propagation direction, i.e., the direction in which the flow pushes the small particle outwards. θ is the angle between the line connecting the small particle and the large particle and the sound wave propagation direction. α sh is the shielding ratio. First, set α sh to 1 initially, and calculate the flow velocities V r,oseen and V θ,oseen around the small particle using equations (29) - (31). Then, obtain α sh , i.e., the shielding effect of the rear part of the small particle on the large particle, according to equation (33). Then, calculate the corresponding V y around the large particle using equations (29) - (32), i.e., the air flow velocity that can push the small particle in the y direction.

[0183] Select different initial y - positions of the small particle. The x - position is taken as a distance of 10 times the radius of the large particle. The x - direction velocity is taken as the difference between the V T of the two particles. The y - direction velocity is calculated forward based on formula (34) along small time steps. The calculation ends when the small particle crosses x = 0 or the small particle touches the large particle, and record the intercept y c . Through simulations with multiple different initial y - positions, the initial release position y c at which the small particle just critically touches the large particle is obtained by linear interpolation. Take y c 2 / (R1 + R2) 2 as E1 under the gravity - coalescence mechanism.

[0184] The formula for calculating the acceleration of a spherical particle due to aerodynamic drag is as follows:

[0185]

[0186] where V p is the velocity of the affected particle, V g is the air velocity that varies periodically under the action of the sound field, V k is the relative velocity of the air flow with respect to the particle, τ is the particle relaxation time, ρw is the particle density.

[0187] Under the acoustic wave co - agglomeration mechanism and the acoustic wake mechanism, considering that the acoustic wave action can frequently generate wake vortices with alternating directions, which can pull the small particles that have bypassed the large particles back for agglomeration, the corresponding E1 is set to 1.

[0188] When calculating E2 for different mechanisms, it is calculated according to the following formula (35), and according to different U dif Calculate respectively:

[0189]

[0190] So far, the collision kernel function model K and related parameters corresponding to different agglomeration mechanisms can be calculated, and thus the collision kernel function model can be constructed.

[0191] In the embodiment of the present invention, since the acoustic wake agglomeration mechanism is considered in the construction of the collision kernel function model, this collision kernel function model is related to the acoustic field characteristics, the atmospheric background characteristics, and the cloud / fog particle size distribution. Therefore, it can realize the simulation of variables such as the particle size spectrum and study the influence of the artificial strong acoustic field on the collision of cloud and fog particles including the acoustic wake effect, increasing the accuracy of the numerical simulation calculation results.

[0192] On the basis of the above - mentioned embodiment, in the numerical simulation calculation method for the influence of acoustic waves on particle collision provided in the embodiment of the present invention, during the numerical simulation calculation process, it also involves the calculation of the acoustic - carrying coefficient q and the slip coefficient l.

[0193] The calculation schemes for the acoustic - carrying coefficient q and the slip coefficient l are as follows:

[0194]

[0195]

[0196] Among them, the acoustic - carrying coefficient q s and the slip coefficient l s , when the angular velocity of the acoustic wave is ω, are respectively:

[0197]

[0198]

[0199] The intermediate calculation quantity h is:

[0200] h = 9ρ g U0 / 2πρ P ωR (40) The phase difference between the particle and the atmosphere (gas) is:

[0201]

[0202] Based on the above embodiments, in the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention, based on the initial value of the particle spectrum and the coalescence kernel function model, the time-forward calculation of the number density source term of particle coalescence for each particle size bin is performed to determine the evolution of the particle spectrum without considering particle sedimentation scavenging. It includes:

[0203] Determine the equivalent spherical diameter of each new particle after particle coalescence;

[0204] For any new particle, if it is determined that the new particle belongs to a first particle size bin other than the above particle size bins based on the equivalent spherical diameter, determine the second particle size bin and the third particle size bin that are close to the first particle size bin among the above particle size bins, and the second particle size bin and the third particle size bin are adjacent;

[0205] Calculate the number density weights of the second particle size bin and the third particle size bin due to the new particle, and based on the number density weight corresponding to the second particle size bin and the number density weight corresponding to the third particle size bin, calculate the number density source increased by the second particle size bin due to the new particle and the number density source increased by the third particle size bin due to the new particle;

[0206] Based on the number density sources increased by each new particle for each particle size bin, determine the first number density source and the second number density source, and determine the number density source term of particle coalescence for each particle size bin.

[0207] Specifically, in the embodiments of the present invention, before performing the time-forward calculation of the number density source term of particle coalescence for each particle size bin through the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum without considering particle sedimentation scavenging, the equivalent spherical diameter of each new particle after particle coalescence can be determined first. For example, for the equivalent spherical diameter D of the new particle after the coalescence of the i-th and j-th bin particles com It can be calculated by formula (42):

[0208]

[0209] where D i is the diameter of the i-th bin particle, and D j is the diameter of the j-th bin particle.

[0210] Since the new particle formed after the collision of two particles in the same particle size bin is usually in the same particle size bin, no specific elaboration is made here, and only the new particles formed after the collision of particles from two particle size bins are considered. The number of such new particles can be one or more, depending on the specific situation, and no specific limitation is made here.

[0211] For any one of all the new particles, that is, any new particle, compare the equivalent spherical diameter of the any new particle with each particle size bin to determine which particle size bin the any new particle belongs to.

[0212] If the any new particle belongs to the first particle size bin other than each particle size bin, that is, the any new particle does not belong to any of the original particle size bins, then determine the second particle size bin and the third particle size bin that are close to the first particle size bin among the particle size bins. The second particle size bin and the third particle size bin are adjacent. Here, the second particle size bin can be denoted as the left bin, and its bin index can be expressed as S left (i, j), and the third particle size bin is denoted as the right bin, and its bin index can be expressed as S right (i, j), and there is S right (i, j) = S left (i, j) + 1.

[0213] After the particle number density of the first particle size bin changes due to the generation of the any new particle, the number density weights W left that should be divided among the second particle size bin D(S left ) and the third particle size bin D(S left (i, j)) and W right (i, j) can be determined by the following formulas (41) and (42):

[0214] w p2 = (D com - D(s left )) / (D(s left + 1) - D(s left )) (39)

[0215] w p1 = (D(s left + 1) - D com ) / (D(s left + 1) - D(s left )) (40)

[0216]

[0217]

[0218] After that, through the number density weight W left (i, j) corresponding to the second particle size bin and the number density weight W right (i, j) corresponding to the third particle size bin, the number density source n left increased in the second particle size bin D(S com (S left (i, j)) due to this new particle and the number density source n com (S right (i, j)) increased in the third particle size bin due to this new particle are calculated.

[0219] Here, the concepts of the coalescence sink term and the coalescence source term are introduced. The coalescence sink term refers to the reduction rate of the number density in a certain particle size bin due to the coalescence effect (the change rate of the number density per unit time), and the coalescence source term refers to the rate of increasing the number density of each bin when particles coalesce to form larger particles. The coalescence sink term n sink (D i ) of particles in a certain particle size bin i due to the coalescence with all particle size bins j can be directly obtained from the total coalescence kernel function model and the particle spectral density, that is:

[0220]

[0221] When calculating the coalescence sink term of particle size bin i, there should be an equal amount of particles appearing in other particle size bins as the corresponding coalescence source term. Taking the summation component of formula (43), iteratively accumulate and calculate the number density sources n com (S left (i, j)) and n com (S right (i, j)) of the second and third particle size bins on the left and right of the first particle size bin corresponding to the coalescence sink term of particle size bin i at the current forward calculation time, that is:

[0222]

[0223]

[0224] After calculating the coalescence sink terms of all particle size bins, accumulate the coalescence source terms belonging to the same particle size bin, and the number concentration source term n source (D i ) of a certain particle size bin i is obtained, that is:

[0225]

[0226] The net change rate of the number density for each particle size bin should be the difference between 0.5 times the above-mentioned coalescence source term and the coalescence sink term, i.e.,

[0227]

[0228] By performing a forward-time calculation on Equation (47) with a small time step, the evolution of the particle spectrum can be obtained without considering particle sedimentation scavenging (constant total particle mass).

[0229] Based on the above embodiments, the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention involves particles including cloud particles or aerosol particles.

[0230] Specifically, the method provided in the embodiments of the present invention can be applied to the numerical simulation calculation of the influence of sound waves on the coalescence of cloud particles or aerosol particles, with high calculation efficiency and more accurate calculation results.

[0231] In summary, the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention is derived and improved based on the existing theoretical formulas or approximate formulas for the influence of acoustic vibrations on the motion of cloud particles in previous studies, and a calculation scheme is created. Combining with the coalescence equation in cloud physics, a numerical simulation system including microphysical mechanisms such as natural gravitational coalescence, co-moving coalescence under strong sound fields, and acoustic wake coalescence is established. It can obtain the changes of parameters such as the cloud particle size spectrum, particle number concentration, and water content over time under different frequencies and intensities of sound waves in different water vapor and hydrometeor conditions. Its calculation efficiency is much higher than the "discrete element" simulation scheme in the background technology, and it can complete the numerical simulation tasks that take several hours to dozens of hours in the background technology within seconds to minutes.

[0232] The numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention can obtain results that are basically consistent with existing indoor experiments and numerical experiments, providing a scientific basis for guiding and evaluating future field experiments.

[0233] (1) Numerical simulation results that are basically consistent with previous indoor fog dissipation experiments can be obtained

[0234] Figure 3 The simulation results of the numerical simulation calculation method for the influence of sound waves on particle coalescence provided in the embodiments of the present invention are shown, Figure 4 The observed phenomena of the artificial strong sound wave indoor fog dissipation experiment in Reference [1] (Hou Shuangquan, Wu Jia, Xi Baoshu, 2002, Experimental study on the effect of low-frequency sound waves on the dissipation of water mist [J], Experiments and Measurements in Fluid Mechanics, 16(4):52 - 56, 63) are shown. Figure 3 and Figure 4 By comparison, it can be seen that Figure 3Under the action of sound waves with a sound pressure level SPL of 136 dB and a frequency f of 30 Hz, the number concentration of fog droplets drops to less than 20% in about 100 s, while under the action of sound waves with an SPL of 131 dB and an f of 30 Hz, the time for the fog droplets to drop to 20% is between 150 and 200 s, which is Figure 4 basically consistent with the observed phenomena in the reference [1] shown in. Without sound waves, the total number concentration of fog droplets only drops to about 60% within 300 s, which conforms to the observed phenomena described in the text of reference [1] ("If there is no sound wave action, the natural dissipation time of fog is generally more than 300 s").

[0235] (2) Numerical simulation results that can be basically consistent with previous indoor aerosol removal experiments

[0236] Figure 5 shows the comparison results of the simulated acoustic aerosol removal effect of the present invention with the actual indoor test observations of reference [2] (Zhang, G., Zhang, L., Wang, J., Chi, Z., 2018, A new model for the acoustic wake effect in aerosol - acoustic agglomeration processes, Appl. Math. Model., 61: 124 - 140). The simulated situations of aerosol removal by 3 sound pressure level sound waves in 8 s are basically close to the measured values. The greater the sound pressure level, the more the corresponding reduction in aerosol number concentration. It can be reduced to less than 20% at 8 s under 145 dB. Since the experiment in reference [2] was carried out in a tank - type device, the actual observed results may be affected by factors such as tank wall reflection and initial concentration fluctuations, so there are differences from the simulation results of the present invention, but the difference range is basically reasonable.

[0237] (3) The calculation time is much lower than the discrete element simulation scheme of reference [2]

[0238] Figure 6 shows the particle spectrum evolution results of the simulated acoustic aerosol removal of the present invention, Figure 7 shows the simulation results of the discrete element simulation scheme in reference [2]. The number concentration of the single - peak type in the simulated particle spectrum gradually decreases within 6 s, which is basically consistent with the phenomena shown in the pictures in reference [2]. Since the statistics of the bin numbers in reference [2] are discretized at unequal intervals, there are slight differences from the initial values input in the calculation of the present invention and the spectrum type and number concentration bin values during the simulation process, but the degree of difference is within a reasonable range.

[0239] In addition, the discrete element simulation used in reference [2] was obtained on a high - performance PC or a small workstation Figure 6Typical simulations required for the results take several hours to dozens of hours, while the present invention only takes several seconds to run on a desktop personal computer, featuring high efficiency.

[0240] As Figure 8 shown, based on the above embodiments, an acoustic wave-influenced particle coalescence numerical simulation calculation system is provided in an embodiment of the present invention, including:

[0241] A parameter acquisition module 81, configured to acquire input condition parameters for numerical simulation calculation, where the input condition parameters include operating parameters, particle spectrum binning parameters, and physical parameters;

[0242] An initialization module 82, configured to determine a target acoustic wave perturbation velocity, a target dynamic viscosity, and a base of the particle coalescence critical velocity based on the operating parameters and the physical parameters, and determine binning information for each particle size bin and an initial value of the particle spectrum based on the particle spectrum binning parameters;

[0243] A model construction module 83, configured to construct a coalescence kernel function model for two particles based on the target acoustic wave perturbation velocity, the target dynamic viscosity, and the base of the particle coalescence critical velocity;

[0244] A numerical simulation calculation module 84, configured to perform a forward-in-time calculation on the number density source term of particle coalescence for each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model, and determine the evolution of the particle spectrum for each particle size bin without considering particle sedimentation removal.

[0245] Based on the above embodiments, in the acoustic wave-influenced particle coalescence numerical simulation calculation system provided in an embodiment of the present invention, the input condition parameters further include container parameters;

[0246] The numerical simulation calculation module is further configured to:

[0247] Determine the terminal velocity of particle fall;

[0248] Based on the terminal velocity of particle fall and the container parameters, determine the evolution of the particle spectrum for each particle size bin after particle sedimentation removal.

[0249] Based on the above embodiments, in the acoustic wave-influenced particle coalescence numerical simulation calculation system provided in an embodiment of the present invention, the numerical simulation calculation module is further configured to:

[0250] Determine the particle spectrum density at each forward calculation moment for each particle size bin without considering particle sedimentation removal;

[0251] Based on the particle spectral density at each forward calculation time without considering particle sedimentation removal under each particle size bin and the bin information, calculate the time-varying sequences of the total particle number concentration and the total particle mass content with respect to the forward calculation time.

[0252] Based on the above embodiments, in the numerical simulation calculation system for acoustic wave influencing particle coalescence provided by the embodiments of the present invention, the model construction module is specifically configured to:

[0253] Determine the particle relaxation time based on the target dynamic viscosity, and determine the equilibrium velocity of the particle without turbulent influence based on the target dynamic viscosity and the particle relaxation time;

[0254] Determine the base of the particle coalescence kernel function based on the target acoustic perturbation velocity, the equilibrium velocity, and the particle relaxation time, and determine the particle coalescence efficiency based on the particle flow-around velocity;

[0255] Determine the coalescence kernel function model based on the base of the particle coalescence kernel function and the particle coalescence efficiency.

[0256] Based on the above embodiments, in the numerical simulation calculation system for acoustic wave influencing particle coalescence provided by the embodiments of the present invention, the base of the particle coalescence kernel function includes the base of the particle coalescence kernel function based on the gravity coalescence mechanism, the base of the particle coalescence kernel function based on the acoustic wave co-directional coalescence mechanism, and the base of the particle coalescence kernel function based on the acoustic wake coalescence mechanism;

[0257] Correspondingly, the particle coalescence efficiency includes the particle coalescence efficiency based on the gravity coalescence mechanism, the particle coalescence efficiency based on the acoustic wave co-directional coalescence mechanism, and the particle coalescence efficiency based on the acoustic wake coalescence mechanism.

[0258] Based on the above embodiments, the numerical simulation calculation system for acoustic wave influencing particle coalescence provided by the embodiments of the present invention further includes a number density source term determination module for:

[0259] Determine the equivalent spherical diameter of each new particle after particle merging;

[0260] For any new particle, if it is determined that the new particle belongs to a first particle size bin other than the above particle size bins based on the equivalent spherical diameter, determine the second particle size bin and the third particle size bin that are close to the first particle size bin among the above particle size bins, and the second particle size bin and the third particle size bin are adjacent;

[0261] Calculate the number density weights of the second particle size bin and the third particle size bin due to any new particle, and calculate the number density source increased by the second particle size bin due to any new particle and the number density source increased by the third particle size bin due to any new particle based on the number density weight corresponding to the second particle size bin and the number density weight corresponding to the third particle size bin;

[0262] Based on the number density sources increased by each particle size bin due to each new particle, determine the first number density source and the second number density source, and determine the number density source term of particle coalescence under each particle size bin.

[0263] On the basis of the above embodiments, in the numerical simulation calculation system for acoustic wave affecting particle coalescence provided in the embodiments of the present invention, the particles involved in the method include cloud particles or aerosol particles.

[0264] Specifically, the functions of the modules in the numerical simulation calculation system for acoustic wave affecting particle coalescence provided in the embodiments of the present invention correspond one-to-one to the operation processes of the steps in the above method-like embodiments, and the achieved effects are also the same. For details, please refer to the above embodiments, and the embodiments of the present invention will not be elaborated herein.

[0265] Figure 9 An example of a schematic physical structure diagram of an electronic device is shown as Figure 9 shown. The electronic device may include: a processor (Processor) 910, a communication interface (Communications Interface) 920, a memory (Memory) 930, and a communication bus 940. Among them, the processor 910, the communication interface 920, and the memory 930 communicate with each other through the communication bus 940. The processor 910 can call the logical instructions in the memory 930 to execute the numerical simulation calculation method for acoustic wave affecting particle coalescence provided in each of the above embodiments.

[0266] In addition, when the logical instructions in the above-mentioned memory 930 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0267] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the numerical simulation calculation method for the influence of sound waves on particle collision provided by the above-mentioned various methods.

[0268] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the numerical simulation calculation method for the influence of sound waves on particle collision provided by the above-mentioned various methods.

[0269] The device embodiments described above are merely illustrative. 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 distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0270] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium such as ROM / RAM, magnetic disks, optical discs, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0271] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention 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 perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A numerical simulation calculation method for the influence of sound waves on particle coalescence, characterized in that, Including: Obtain input condition parameters for numerical simulation calculation, where the input condition parameters include operating parameters, particle spectrum binning parameters, and physical parameters; Based on the operating parameters and the physical parameters, determine the target acoustic wave perturbation velocity, the target dynamic viscosity, and the base of the particle coalescence critical velocity, and based on the particle spectrum binning parameters, determine the binning information for each particle size bin and the initial value of the particle spectrum; Based on the target acoustic wave perturbation velocity, the target dynamic viscosity, and the base of the particle coalescence critical velocity, construct a coalescence kernel function model for two particles; Based on the initial value of the particle spectrum and the coalescence kernel function model, perform a forward-time calculation of the number density source term for particle coalescence in each particle size bin to determine the evolution of the particle spectrum without considering particle sedimentation removal in each particle size bin; Before the step of performing a forward-time calculation of the number density source term for particle coalescence in each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum without considering particle sedimentation removal in each particle size bin, it includes: Determine the equivalent spherical diameter of each new particle after particle coalescence; For any new particle, if it is determined that the new particle belongs to a first particle size bin other than the above-mentioned particle size bins based on the equivalent spherical diameter, then determine a second particle size bin and a third particle size bin that are close to the first particle size bin among the above-mentioned particle size bins, and the second particle size bin and the third particle size bin are adjacent; Calculate the number density weights of the second particle size bin and the third particle size bin due to the new particle, and based on the number density weight corresponding to the second particle size bin and the number density weight corresponding to the third particle size bin, calculate the number density source increased by the second particle size bin due to the new particle and the number density source increased by the third particle size bin due to the new particle; Based on the number density sources increased by each new particle in each particle size bin, determine the first number density source and the second number density source, and determine the number density source term for particle coalescence in each particle size bin.

2. The numerical simulation calculation method for the influence of sound waves on particle coalescence according to claim 1, characterized in that, The input condition parameters further include container parameters; After the step of performing a forward-time calculation of the number density source term for particle coalescence in each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum without considering particle sedimentation removal in each particle size bin, it includes: Determine the terminal velocity of particle fall; Based on the terminal velocity of particle fall and the container parameters, determine the evolution of the particle spectrum after particle sedimentation removal in each particle size bin.

3. The numerical simulation calculation method for the influence of sound waves on particle coalescence according to claim 1, characterized in that, After the step of performing a forward-time calculation of the number density source term for particle coalescence in each particle size bin based on the initial value of the particle spectrum and the coalescence kernel function model to determine the evolution of the particle spectrum without considering particle sedimentation removal in each particle size bin, it includes: Determine the particle spectrum density at each forward-time calculation moment without considering particle sedimentation removal in each particle size bin; Based on the particle spectral density at each forward calculation time without considering particle sedimentation scavenging under each particle size bin and the bin information, calculate the time variation sequences of the total particle number concentration and the total particle mass content with the forward calculation time.

4. The numerical simulation calculation method for the influence of sound waves on particle coalescence according to any one of claims 1-3, characterized in that, Constructing a coalescence kernel function model for two particles based on the target acoustic perturbation velocity, the target dynamic viscosity, and the base of the particle coalescence critical velocity, specifically including: Based on the target dynamic viscosity, determine the particle relaxation time, and based on the target dynamic viscosity and the particle relaxation time, determine the equilibrium velocity of the particle without the influence of turbulence; Based on the target acoustic perturbation velocity, the equilibrium velocity, and the particle relaxation time, determine the base of the particle coalescence kernel function, and based on the particle flow-around velocity, determine the particle coalescence efficiency; Based on the base of the particle coalescence kernel function and the particle coalescence efficiency, determine the coalescence kernel function model.

5. The numerical simulation calculation method for the influence of sound waves on particle coalescence according to claim 4, characterized in that, The base of the particle coalescence kernel function includes the base of the particle coalescence kernel function based on the gravitational coalescence mechanism, the base of the particle coalescence kernel function based on the acoustic wave co-aggregation mechanism, and the base of the particle coalescence kernel function based on the acoustic wake aggregation mechanism; Correspondingly, the particle coalescence efficiency includes the particle coalescence efficiency based on the gravitational coalescence mechanism, the particle coalescence efficiency based on the acoustic wave co-aggregation mechanism, and the particle coalescence efficiency based on the acoustic wake aggregation mechanism.

6. The numerical simulation calculation method for the influence of sound waves on particle coalescence according to any one of claims 1-3, characterized in that, The particles involved in the method include cloud particles or aerosol particles.

7. A numerical simulation calculation system for the influence of sound waves on particle coalescence, characterized in that, Including: A parameter acquisition module for acquiring input condition parameters for numerical simulation calculations, where the input condition parameters include operating parameters, particle spectrum binning parameters, and physical parameters; An initialization module for determining the target acoustic perturbation velocity, the target dynamic viscosity, and the base of the particle coalescence critical velocity based on the operating parameters and the physical parameters, and determining the bin information and the initial particle spectrum value of each particle size bin based on the particle spectrum binning parameters; A model construction module for constructing a coalescence kernel function model for two particles based on the target acoustic perturbation velocity, the target dynamic viscosity, and the base of the particle coalescence critical velocity; A numerical simulation calculation module for performing a forward time calculation on the number density source term of particle coalescence under each particle size bin based on the initial particle spectrum and the coalescence kernel function model, and determining the particle spectrum evolution without considering particle sedimentation scavenging under each particle size bin; Before performing the forward time calculation on the number density source term of particle coalescence under each particle size bin based on the initial particle spectrum and the coalescence kernel function model, and determining the particle spectrum evolution without considering particle sedimentation scavenging under each particle size bin, it includes: Determine the equivalent spherical diameter of each new particle after particle coalescence; For any new particle, if it is determined that the new particle belongs to a first particle size bin other than the each particle size bin based on the equivalent spherical diameter, then determine the second particle size bin and the third particle size bin that are close to the first particle size bin among the each particle size bins, and the second particle size bin and the third particle size bin are adjacent; Calculate the number density weights obtained for the second particle size bin and the third particle size bin due to the any new particle, and calculate the number density source increased for the second particle size bin due to the any new particle and the number density source increased for the third particle size bin due to the any new particle based on the number density weight corresponding to the second particle size bin and the number density weight corresponding to the third particle size bin; Based on the number density sources increased for each particle size bin due to the respective new particles, determine the first number density source and the second number density source, and determine the number density source term of particle coalescence under each particle size bin.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the numerical simulation calculation method for acoustic wave affecting particle coalescence according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the numerical simulation calculation method for acoustic wave affecting particle coalescence according to any one of claims 1 to 6.

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