A method and system for numerical simulation of atomizer atomization based on temperature change characteristics

Abstract

The present application relates to the technical field of atomization numerical simulation, and relates to an atomizer atomization numerical simulation method and system based on temperature variation characteristics, which comprises the following steps: confirming a test atomizer set and an ambient temperature set, obtaining a plurality of normal liquid viscosity sets and a plurality of normal liquid droplet surface tension sets, obtaining an optimized temperature interval, constructing a viscosity surface tension momentum equation, setting a solver parameter, sequentially extracting an optimized temperature value from the optimized temperature interval, simulating a pre-constructed simulation atomizer according to the solver parameter, the optimized temperature value and the viscosity surface tension momentum equation, obtaining a simulation atomization parameter, otherwise, taking the simulation atomization parameter as an optimized atomization parameter, summarizing the optimized atomization parameters, obtaining an optimized atomization parameter set, obtaining an optimal atomization parameter, and completing the atomizer atomization numerical simulation based on the temperature variation characteristics based on the optimal atomization parameter. The present application can improve the performance and atomization effect of the atomizer.

Description

Technical Field

[0001] This invention relates to the field of atomization numerical simulation technology, and in particular to a method and system for atomization numerical simulation of atomizers based on temperature change characteristics. Background Technology

[0002] Temperature change characteristics refer to the way temperature variations affect the fluid flow and phase change processes within an atomizer during the atomization process. An atomizer is a device that converts liquid into fine droplets. Atomization numerical simulation is a method that uses computer technology and numerical calculation methods to simulate and analyze the fluid flow, phase change, and atomization process within an atomizer.

[0003] Traditional numerical simulation methods for atomization often focus primarily on the flow characteristics of fluids, while failing to comprehensively consider the impact of temperature changes on the atomization process. In practical applications, atomizers often face complex operating conditions, and existing numerical simulation methods may suffer from insufficient simulation accuracy when handling these complex conditions. Therefore, improving the performance and atomization effect of atomizers is an urgent technical problem to be solved. Summary of the Invention

[0004] This invention provides a numerical simulation method for atomization based on temperature change characteristics and a computer-readable storage medium, the main purpose of which is to improve the performance and atomization effect of atomizers.

[0005] To achieve the above objectives, this invention provides a numerical simulation method for atomization of an atomizer based on temperature change characteristics, comprising:

[0006] The test atomizer set and the ambient temperature set were identified. The ambient temperature set includes multiple ambient temperatures, and each of the multiple ambient temperatures is different.

[0007] Multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are obtained based on the ambient temperature set and the test atomizer set. An optimized temperature range is obtained based on the multiple normal liquid viscosity sets, multiple normal droplet surface tension sets and the ambient temperature set. The optimized temperature range includes multiple optimized temperature values.

[0008] The viscosity-surface-tension-momentum equation is constructed based on pre-built numerical simulation software, optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets.

[0009] Set the solver parameters, extract the optimized temperature values ​​from the optimized temperature range in sequence, and simulate the pre-built simulated atomizer according to the solver parameters, optimized temperature values ​​and viscosity, surface tension and momentum equations to obtain simulated atomization parameters. The simulated atomization parameters include: simulated droplet size, simulated atomization rate and simulated atomization angle. The simulated atomization parameters correspond one-to-one with the optimized temperature values ​​in the optimized temperature range.

[0010] Calculate the relative error between the simulated atomization parameters and the preset atomization numerical parameters;

[0011] If the relative error is greater than the preset relative error threshold, the solver parameters are adjusted to obtain the tuned solver parameters. The tuned solver parameters are then used as the solver parameters. The process of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature value, and viscosity, surface tension, and momentum equations is repeated until the relative error is not greater than the preset relative error threshold, thus obtaining the optimized atomization parameters.

[0012] Otherwise, the simulated atomization parameters will be used as the optimized atomization parameters;

[0013] The optimized atomization parameters are summarized and optimized to obtain an optimized atomization parameter set. The optimal atomization parameters are then obtained based on the optimized atomization parameter set.

[0014] Optionally, the acquisition of multiple normal liquid viscosity sets and multiple normal droplet surface tension sets based on the ambient temperature set and the test atomizer set includes:

[0015] For each ambient temperature, perform the following operations:

[0016] Test atomizers are extracted from the test atomizer set, and the test atomizers are tested using a preset test time period and ambient temperature to obtain liquid viscosity set and droplet surface tension set. Among them, the test atomizer, liquid viscosity set and droplet surface tension set correspond one-to-one with the ambient temperature.

[0017] Normalize both the liquid viscosity set and the droplet surface tension set to obtain the normalized liquid viscosity set and the normalized droplet surface tension set.

[0018] The normalized liquid viscosity set is first removed for outliers to obtain the initial liquid viscosity set. A box plot is then drawn on the initial liquid viscosity set to obtain the initial liquid viscosity box plot.

[0019] Sort the initial liquid viscosity set in descending order to obtain the initial liquid viscosity sequence. Calculate the first quartile and the third quartile of the initial liquid viscosity sequence. Calculate the quartile difference based on the first quartile and the third quartile.

[0020] Calculate the upper and lower limits of liquid viscosity based on the quantile difference, the first quartile, and the third quartile; and determine the liquid viscosity range based on the upper and lower limits of liquid viscosity.

[0021] Within the liquid viscosity range, outliers are removed from the initial liquid viscosity set in the initial liquid viscosity box plot to obtain the normal liquid viscosity set, and the normal droplet surface tension set is obtained based on the normalized droplet surface tension set.

[0022] By summing up the normal liquid viscosity set and the normal droplet surface tension set, multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are obtained.

[0023] Optionally, the initial outlier removal from the normalized liquid viscosity set to obtain the initial liquid viscosity set includes:

[0024] The mean and standard deviation of liquid viscosity are calculated based on the normalized liquid viscosity set. The standard deviation of multiples is calculated based on the standard deviation of liquid viscosity and a preset multiple. The standard deviation of multiples is the product of the standard deviation of liquid viscosity and the multiple. The preset multiple is 3.

[0025] Extract the normalized liquid viscosity sequentially from the normalized liquid viscosity set, calculate the absolute difference between the normalized liquid viscosity and the mean liquid viscosity, and compare the absolute difference of liquid viscosity with the standard deviation of the multiple.

[0026] If the absolute difference in liquid viscosity is greater than a multiple of the standard deviation, the normalized liquid viscosity corresponding to the absolute difference in liquid viscosity is taken as the abnormal liquid viscosity. The abnormal liquid viscosity is removed from the normalized liquid viscosity set to obtain an updated liquid viscosity set. The updated liquid viscosity set is taken as the normalized liquid viscosity set. The process of extracting the normalized liquid viscosity from the normalized liquid viscosity set is repeated until the normalized liquid viscosity set is empty.

[0027] If the absolute difference in liquid viscosity is not greater than a multiple of the standard deviation, then the normalized liquid viscosity corresponding to the absolute difference in liquid viscosity is taken as the initial liquid viscosity.

[0028] The initial liquid viscosity is summarized to obtain the initial liquid viscosity set.

[0029] Optionally, obtaining the optimized temperature range based on multiple normal liquid viscosity sets, multiple normal droplet surface tension sets, and ambient temperature sets includes:

[0030] Normal liquid viscosity sets are extracted sequentially from multiple normal liquid viscosity sets, the mean normal liquid viscosity of each normal liquid viscosity set is calculated, and the mean normal liquid viscosity is summed to obtain multiple mean normal liquid viscosity values.

[0031] Multiple average surface tension values ​​of normal droplets are obtained based on multiple sets of surface tension of normal droplets. An experimental set is formed based on multiple average viscosity values ​​of normal liquids, multiple average surface tension values ​​of normal droplets and ambient temperature. The experimental set includes multiple experimental sets, and each experimental set includes: average viscosity value of normal liquid, average surface tension value of normal droplets and ambient temperature.

[0032] Construct an initial quadratic polynomial function, fit the initial quadratic polynomial function to the experimental combination set to obtain the quadratic polynomial coefficients, and obtain the quadratic polynomial function based on the quadratic polynomial coefficients and the initial quadratic polynomial function.

[0033] By taking the first derivative of the quadratic polynomial function, we obtain the critical temperature and the first derivative function. By taking the second derivative of the first derivative function, we obtain the second derivative value and the second derivative function.

[0034] The optimal temperature range is obtained based on the critical temperature, the value of the second derivative, and the second derivative function.

[0035] Optionally, obtaining the optimized temperature range based on the critical temperature, the second derivative value, and the second derivative function includes:

[0036] Compare the values ​​of the second derivative with zero;

[0037] If the second derivative value is greater than zero, the critical temperature is taken as the second abnormal temperature value.

[0038] If the second derivative value is less than zero, the critical temperature is used as the second optimal temperature value.

[0039] If the second derivative is equal to zero, then take the third derivative of the second derivative function to obtain the third derivative value, and compare the third derivative value with zero.

[0040] If the third derivative value is greater than zero, the critical temperature is taken as the third abnormal temperature value.

[0041] If the third derivative value is less than zero, the critical temperature is used as the third optimal temperature value.

[0042] If the third derivative is equal to zero, then the fourth derivative of the third derivative function is taken until the derivative is less than zero, thus obtaining the fourth optimized temperature value.

[0043] The second, third, or fourth optimized temperature value is used as the optimized temperature value, and an initial optimized temperature range is constructed based on the optimized temperature value and the preset reference temperature span.

[0044] Determine whether the abnormal second or third temperature value is within the initial optimized temperature range;

[0045] If the abnormal second temperature value or the abnormal third temperature value is within the initial optimized temperature range, then the abnormal second temperature value and the abnormal third temperature value are removed from the initial optimized temperature range to obtain the optimized temperature range.

[0046] If neither the abnormal second temperature value nor the abnormal third temperature value is within the initial optimized temperature range, then the initial optimized temperature range will be used as the optimized temperature range.

[0047] Optionally, the construction of the viscosity-surface-tension-momentum equation based on pre-built numerical simulation software, optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets includes:

[0048] The simulated ambient temperature set is randomly extracted from the optimized temperature range. The simulated liquid viscosity set and the simulated liquid surface tension set are obtained based on the simulated optimized temperature value set, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets. The simulated optimized temperature value corresponds one-to-one with the simulated liquid viscosity and the simulated liquid surface tension.

[0049] The pre-constructed Arrhenius equation was fitted using a simulated liquid viscosity set and numerical simulation software to obtain the pre-exponential fitting factor and the fitting activation energy.

[0050] The viscosity-temperature term was determined based on the pre-exponential factor and the activation energy of the fit. The surface tension curve of the liquid was plotted based on the simulated liquid surface tension set. The horizontal axis of the surface tension curve represents the ambient temperature, and the vertical axis of the surface tension curve represents the surface tension value of the liquid.

[0051] The target ambient temperature is randomly extracted from the liquid surface tension curve. The target liquid surface tension value is determined based on the target ambient temperature. The derivative value of the liquid surface tension is calculated based on the target liquid surface tension value.

[0052] The viscosity-temperature term, the derivative of liquid surface tension, and the pre-constructed momentum equation are used to construct the viscosity-surface tension-momentum equation.

[0053] Optionally, the viscosity-surface-tension momentum equation is as follows:

[0054]

[0055] Where ρ represents the fluid density, The derivative of the fluid velocity with time. The negative pressure gradient term is represented by μ, and the viscosity-temperature term is represented by μ. Represents the velocity gradient tensor. This represents the transpose of the velocity gradient tensor. This represents the derivative of the surface tension of a liquid. Let represent the temperature gradient, δ represent the interface thickness, and n represent the interface normal vector. This represents the gradient operator.

[0056] Optionally, the relative error between the calculated simulated atomization parameters and the preset atomization numerical parameters includes:

[0057] Sensitivity coefficients for multiple parameters are calculated based on simulated atomization parameters and numerical atomization parameters. The numerical atomization parameters include: experimental droplet size, experimental atomization rate, and experimental atomization angle.

[0058] The relative error between the simulated atomization parameters and the numerical atomization parameters is calculated based on the sensitivity coefficients of multiple parameters. The formula for calculating the relative error is as follows:

[0059]

[0060] Where C represents the relative error, k represents the index of the simulated atomization parameter, N represents the effective data volume, and α k S represents the sensitivity coefficient of the parameter. k This represents the preset error sensitivity coefficient, ΔT1 represents the preset temperature deviation value, T0 represents the reference temperature range, and 1 / ∑α represents the normalization exponent. This represents the simulated atomization parameters of type k in the i-th simulation. This represents the numerical parameter of the k-th type of atomization corresponding to the i-th simulation.

[0061] Optionally, the step of calculating multiple parameter sensitivity coefficients based on simulated atomization parameters and atomization numerical parameters includes:

[0062] The simulated droplet size is extracted from the simulated atomization parameters. The droplet size difference is calculated based on the simulated droplet size and the experimental droplet size. The droplet size change is calculated based on the droplet size difference and the experimental droplet size.

[0063] The simulated temperature is determined based on the simulated droplet size. The temperature difference is calculated based on the simulated temperature and the preset reference temperature. The temperature change is calculated based on the temperature difference and the reference temperature.

[0064] The particle size sensitivity coefficient is obtained based on the particle size change value and the temperature change value; the atomization rate sensitivity coefficient is calculated based on the simulated atomization rate and the experimental atomization rate; and the atomization angle sensitivity coefficient is calculated based on the simulated atomization angle and the experimental atomization angle.

[0065] By summing the particle size sensitivity coefficient, atomization rate sensitivity coefficient, and atomization angle sensitivity coefficient, multiple parameter sensitivity coefficients are obtained, wherein the parameter sensitivity coefficients are the particle size sensitivity coefficient, atomization rate sensitivity coefficient, or atomization angle sensitivity coefficient.

[0066] To achieve the above objectives, the present invention also provides a numerical simulation system for atomization based on temperature change characteristics, comprising:

[0067] The optimization interval acquisition module is used to identify the test atomizer set and the ambient temperature set. The ambient temperature set includes multiple ambient temperatures, and each of the multiple ambient temperatures is different. Based on the ambient temperature set and the test atomizer set, multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are obtained. Based on the multiple normal liquid viscosity sets, multiple normal droplet surface tension sets and the ambient temperature set, the optimization temperature interval is obtained. The optimization temperature interval includes multiple optimization temperature values.

[0068] The momentum equation construction module is used to construct viscosity-surface-tension momentum equations based on pre-built numerical simulation software, optimized temperature ranges, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets.

[0069] The atomization numerical simulation module is used to set solver parameters, sequentially extract optimized temperature values ​​from the optimized temperature range, and simulate a pre-constructed simulated atomizer based on the solver parameters, optimized temperature values, and viscosity-surface-tension-momentum equations to obtain simulated atomization parameters. These simulated atomization parameters include simulated droplet size, simulated atomization rate, and simulated atomization angle. Each simulated atomization parameter corresponds one-to-one with the optimized temperature values ​​in the optimized temperature range. The module calculates the relative error between the simulated atomization parameters and preset atomization numerical parameters. If the relative error exceeds a preset relative error threshold, the solver parameters are adjusted to obtain adjusted solver parameters. These adjusted solver parameters are then used as the solver parameters. The process returns to the step of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature values, and viscosity-surface-tension-momentum equations until the relative error is no greater than the preset relative error threshold, thus obtaining optimized atomization parameters. Otherwise, the simulated atomization parameters are used as the optimized atomization parameters.

[0070] The optimal atomization parameter determination module is used to summarize and optimize atomization parameters to obtain an optimized atomization parameter set, and then obtain the optimal atomization parameters based on the optimized atomization parameter set.

[0071] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0072] Memory, storing at least one instruction;

[0073] The processor executes the instructions stored in the memory to implement the above-described numerical simulation method for atomization based on temperature change characteristics.

[0074] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the above-described numerical simulation method for atomizer atomization based on temperature change characteristics.

[0075] To address the problems described in the background art, this invention identifies a set of test atomizers and a set of ambient temperatures. The ambient temperature set includes multiple distinct ambient temperatures. By identifying the test atomizer set, this invention determines the specific atomizer type or model targeted in the numerical simulation, providing a clear objective and avoiding an overly broad research scope. Based on the ambient temperature set and the test atomizer set, multiple sets of normal liquid viscosity and multiple sets of normal droplet surface tension are obtained. Based on these sets of normal liquid viscosity, normal droplet surface tension, and the ambient temperature set, an optimized temperature range is obtained. This optimized temperature range includes multiple optimized temperature values. This invention, based on the ambient temperature set and the test atomizer set... The atomizer sets these parameters to accurately reflect the physical properties of liquids under different ambient temperatures, providing data support for building accurate physical models. Optimizing the temperature range focuses on the temperature range that significantly affects atomization, reducing unnecessary computation and improving simulation efficiency and relevance. Based on pre-built numerical simulation software, the optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets, a viscosity-surface tension-momentum equation is constructed. This invention's viscosity-surface tension-momentum equation combines the two key factors of liquid viscosity and droplet surface tension, more accurately describing the fluid motion and interaction during atomization. Solver parameters are set, and optimized temperature values ​​are extracted sequentially from the optimized temperature range. The pre-constructed simulated atomizer is simulated based on the solver parameters, optimized temperature values, and viscosity, surface tension, and momentum equations to obtain simulated atomization parameters. These simulated atomization parameters include: simulated droplet size, simulated atomization rate, and simulated atomization angle. Each simulated atomization parameter corresponds one-to-one with the optimized temperature value within the optimized temperature range. The solver parameter settings of this invention can control the accuracy and computational efficiency of the numerical simulation. Reasonable solver parameter settings can ensure the stability and accuracy of the simulation process, making the simulation results more reliable. The relative error between the simulated atomization parameters and the preset atomization numerical parameters is calculated. If the relative error exceeds a preset relative error threshold, the solver parameters are adjusted to obtain the tuned solver parameters. The parameters are used as solver parameters. The process returns to the step of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature value, and viscosity, surface tension, and momentum equations, until the relative error is no greater than a preset relative error threshold. This process yields optimized atomization parameters. The steps of this invention ensure that the simulation results are close to the preset ideal values, thus making the simulation results more reliable. In practical applications, reliable simulation results can provide a more accurate basis for the design and optimization of atomizers. If the relative error is no greater than the preset relative error threshold, the simulated atomization parameters are used as optimized atomization parameters. The optimized atomization parameters are then summarized to obtain an optimized atomization parameter set. Based on this optimized atomization parameter set, the optimal atomization parameters are obtained. This invention obtains the optimal atomization parameters based on the optimized atomization parameter set.This invention can filter out the optimal atomization parameters from numerous optimization results under different temperature conditions, maximizing the atomization effect. These optimal atomization parameters can be directly applied to the actual design and production of atomizers, helping engineers optimize the structure and operating parameters of atomizers, improving their performance and efficiency, and reducing production costs. Therefore, this invention can improve the performance and atomization effect of atomizers. Attached Figure Description

[0076] Figure 1 This is a flowchart illustrating a numerical simulation method for atomization based on temperature change characteristics provided in an embodiment of the present invention.

[0077] Figure 2 A functional block diagram of a numerical simulation system for atomization based on temperature change characteristics provided in an embodiment of the present invention;

[0078] Figure 3 This is a schematic diagram of an electronic device for implementing the numerical simulation method for atomization based on temperature change characteristics, according to an embodiment of the present invention.

[0079] Explanation of reference numerals in the attached figures:

[0080] 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0081] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0082] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0083] This application provides a numerical simulation method for atomizer atomization based on temperature change characteristics. The execution entity of this numerical simulation method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the numerical simulation method for atomizer atomization based on temperature change characteristics can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0084] Reference Figure 1 The diagram shown is a flowchart illustrating a numerical simulation method for atomizer atomization based on temperature change characteristics according to an embodiment of the present invention. In this embodiment, the numerical simulation method for atomizer atomization based on temperature change characteristics includes:

[0085] S1. Identify the test atomizer set and the ambient temperature set. The ambient temperature set includes multiple ambient temperatures, and each of the multiple ambient temperatures is different.

[0086] It should be explained that the test atomizer set refers to the collection of all test atomizers. All test atomizers in the test atomizer set described in this embodiment of the invention are of the same type and function. A test atomizer is an atomizer used for experiments and numerical simulations.

[0087] S2. Based on the ambient temperature set and the test atomizer set, obtain multiple normal liquid viscosity sets and multiple normal droplet surface tension sets, and obtain the optimized temperature range based on the multiple normal liquid viscosity sets, multiple normal droplet surface tension sets and the ambient temperature set.

[0088] Specifically, the optimized temperature range includes multiple optimized temperature values.

[0089] Specifically, the acquisition of multiple normal liquid viscosity sets and multiple normal droplet surface tension sets based on the ambient temperature set and the test atomizer set includes:

[0090] For each ambient temperature, perform the following operations:

[0091] Test atomizers are extracted from the test atomizer set, and the test atomizers are tested using a preset test time period and ambient temperature to obtain liquid viscosity set and droplet surface tension set. Among them, the test atomizer, liquid viscosity set and droplet surface tension set correspond one-to-one with the ambient temperature.

[0092] Normalize both the liquid viscosity set and the droplet surface tension set to obtain the normalized liquid viscosity set and the normalized droplet surface tension set.

[0093] The normalized liquid viscosity set is first removed for outliers to obtain the initial liquid viscosity set. A box plot is then drawn on the initial liquid viscosity set to obtain the initial liquid viscosity box plot.

[0094] Sort the initial liquid viscosity set in descending order to obtain the initial liquid viscosity sequence. Calculate the first quartile and the third quartile of the initial liquid viscosity sequence. Calculate the quartile difference based on the first quartile and the third quartile.

[0095] Calculate the upper and lower limits of liquid viscosity based on the quantile difference, the first quartile, and the third quartile; and determine the liquid viscosity range based on the upper and lower limits of liquid viscosity.

[0096] Within the liquid viscosity range, outliers are removed from the initial liquid viscosity set in the initial liquid viscosity box plot to obtain the normal liquid viscosity set, and the normal droplet surface tension set is obtained based on the normalized droplet surface tension set.

[0097] By summing up the normal liquid viscosity set and the normal droplet surface tension set, multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are obtained.

[0098] It should be explained that the test time period refers to the time period during which the atomizer is tested at each ambient temperature. The liquid viscosity set refers to the set of liquid viscosity values ​​measured by a rheometer at a specific ambient temperature. The droplet surface tension set refers to the set of liquid surface tension values ​​measured by the pendant drop method at a specific ambient temperature. Normalizing both the liquid viscosity set and the droplet surface tension set means normalizing both sets using the maximum-minimum normalization formula. The normalized liquid viscosity set is the set obtained by normalizing each liquid viscosity value in the liquid viscosity set. The normalized droplet surface tension set is the set obtained by normalizing each droplet surface tension value in the droplet surface tension set. The initial liquid viscosity set is the set of initial liquid viscosities obtained after the first outlier removal from the normalized liquid viscosity set. Plotting a box plot on the initial liquid viscosity set means plotting a box plot on the initial liquid viscosity set using a plotting tool. For example, plotting tools include Matplotlib and Excel. The initial liquid viscosity box plot is a box plot drawn based on the initial liquid viscosity set. The initial liquid viscosity series refers to the sequence of initial liquid viscosities arranged in descending order from the initial liquid viscosity set.

[0099] Importantly, the first quartile refers to the initial liquid viscosity located in the first 25% of the initial liquid viscosity sequence. The third quartile refers to the initial liquid viscosity located in the first 75% of the initial liquid viscosity sequence. For example, if the initial liquid viscosity sequence is [10.5, 8.2, 6.8, 5.5, 4.2, 3.8, 3.2], and there are 7 initial liquid viscosities in the initial liquid viscosity sequence, then the digits of the first quartile are: The first quartile is 8.2, and the digits of the third quartile are: The third quartile is 3.8. If the initial liquid viscosity sequence is [12.0, 10.5, 9.0, 7.5, 6.0, 4.5, 3.0, 1.5], and there are 8 initial liquid viscosities in the initial liquid viscosity sequence, then the digits of the first quartile are: 2.25 is between the second and third digits. The initial liquid viscosity at the second digit is 10.5, and the initial liquid viscosity at the third digit is 9.0. Based on the initial liquid viscosity at the second and third digits, the first quartile is calculated as: 10.5 + 0.25 × (9.0 - 10.5) = 10.125. Therefore, the third quartile is: 6.75 is between the 6th and 7th digits. The initial liquid viscosity at the 6th digit is 4.5, and the initial liquid viscosity at the 7th digit is 3.0. Based on the initial liquid viscosity at the 6th and 7th digits, the third quartile is calculated as: 4.5 + 0.75 × (3.0 - 4.5) = 3.375.

[0100] It is understood that the quantile difference refers to the absolute difference between the third quartile and the first quartile. The steps for calculating the upper and lower limits of liquid viscosity based on the quantile difference, the first quartile, and the third quartile are as follows: Upper limit of liquid viscosity = Third quartile + 1.5 × quantile difference; Lower limit of liquid viscosity = First quartile - 1.5 × quantile difference. The liquid viscosity range refers to the interval composed of the upper and lower limits of liquid viscosity. The normal liquid viscosity set refers to the initial liquid viscosity set obtained by removing outliers from the initial liquid viscosity box plot within the liquid viscosity range. The method for obtaining the normal droplet surface tension set based on the normalized droplet surface tension set is the same as the method for obtaining the normal liquid viscosity set based on the normalized liquid viscosity set, and will not be repeated here.

[0101] Specifically, the initial outlier removal process for the normalized liquid viscosity set to obtain the initial liquid viscosity set includes:

[0102] The mean and standard deviation of liquid viscosity are calculated based on the normalized liquid viscosity set. The standard deviation of multiples is calculated based on the standard deviation of liquid viscosity and a preset multiple. The standard deviation of multiples is the product of the standard deviation of liquid viscosity and the multiple. The preset multiple is 3.

[0103] Extract the normalized liquid viscosity sequentially from the normalized liquid viscosity set, calculate the absolute difference between the normalized liquid viscosity and the mean liquid viscosity, and compare the absolute difference of liquid viscosity with the standard deviation of the multiple.

[0104] If the absolute difference in liquid viscosity is greater than a multiple of the standard deviation, the normalized liquid viscosity corresponding to the absolute difference in liquid viscosity is taken as the abnormal liquid viscosity. The abnormal liquid viscosity is removed from the normalized liquid viscosity set to obtain an updated liquid viscosity set. The updated liquid viscosity set is taken as the normalized liquid viscosity set. The process of extracting the normalized liquid viscosity from the normalized liquid viscosity set is repeated until the normalized liquid viscosity set is empty.

[0105] If the absolute difference in liquid viscosity is not greater than a multiple of the standard deviation, then the normalized liquid viscosity corresponding to the absolute difference in liquid viscosity is taken as the initial liquid viscosity.

[0106] The initial liquid viscosity is summarized to obtain the initial liquid viscosity set.

[0107] It should be explained that the mean liquid viscosity refers to the average of all normalized liquid viscosities in the normalized liquid viscosity set. The standard deviation of liquid viscosity is the value obtained by calculating the standard deviation of the normalized liquid viscosities in the normalized liquid viscosity set. The multiple standard deviation is the product of the standard deviation and a multiple. The absolute difference in liquid viscosity is the absolute difference between the normalized liquid viscosity and the mean liquid viscosity. Anomaly liquid viscosity refers to a normalized liquid viscosity whose absolute difference is greater than a multiple standard deviation. An updated liquid viscosity set is a new liquid viscosity set obtained by removing anomaly liquid viscosities from the normalized liquid viscosity set. The initial liquid viscosity refers to a normalized liquid viscosity whose absolute difference is not greater than a multiple standard deviation.

[0108] Specifically, the process of obtaining the optimized temperature range based on multiple normal liquid viscosity sets, multiple normal droplet surface tension sets, and ambient temperature sets includes:

[0109] Normal liquid viscosity sets are extracted sequentially from multiple normal liquid viscosity sets, the mean normal liquid viscosity of each normal liquid viscosity set is calculated, and the mean normal liquid viscosity is summed to obtain multiple mean normal liquid viscosity values.

[0110] Multiple average surface tension values ​​of normal droplets are obtained based on multiple sets of surface tension of normal droplets. An experimental set is formed based on multiple average viscosity values ​​of normal liquids, multiple average surface tension values ​​of normal droplets and ambient temperature. The experimental set includes multiple experimental sets, and each experimental set includes: average viscosity value of normal liquid, average surface tension value of normal droplets and ambient temperature.

[0111] Construct an initial quadratic polynomial function, fit the initial quadratic polynomial function to the experimental combination set to obtain the quadratic polynomial coefficients, and obtain the quadratic polynomial function based on the quadratic polynomial coefficients and the initial quadratic polynomial function.

[0112] By taking the first derivative of the quadratic polynomial function, we obtain the critical temperature and the first derivative function. By taking the second derivative of the first derivative function, we obtain the second derivative value and the second derivative function.

[0113] The optimal temperature range is obtained based on the critical temperature, the value of the second derivative, and the second derivative function.

[0114] It should be explained that the mean normal liquid viscosity refers to the average normal liquid viscosity in each normal liquid viscosity set. The mean normal droplet surface tension refers to the average normal droplet surface tension in each normal droplet surface tension set. The method for obtaining multiple mean normal droplet surface tension values ​​based on multiple normal droplet surface tension sets is the same as the method for obtaining multiple mean normal liquid viscosity values ​​based on multiple normal liquid viscosity sets, and will not be repeated here. The step of forming an experimental combination set based on multiple mean normal liquid viscosity values, multiple mean normal droplet surface tension values, and ambient temperature sets refers to forming an experimental combination by combining the mean normal liquid viscosity values ​​and mean normal droplet surface tension values ​​corresponding to each ambient temperature in the ambient temperature set, and summing the experimental combinations to obtain the experimental combination set. The initial quadratic polynomial function in the step of constructing the initial quadratic polynomial function is shown below:

[0115] y = a0 + a1 × x1 + a2 × x2 + a3 × x1 2 +a4×x2 2 +a5×x1×x2

[0116] Where y represents ambient temperature, x1 represents the average viscosity of the normal liquid, x2 represents the average surface tension of the normal droplet, and a0, a1, a2, a3, a4, and a5 represent the unknown coefficients of the initial quadratic polynomial function. The phrase "fitting the initial quadratic polynomial function to obtain the quadratic polynomial coefficients based on the experimental set" refers to fitting the initial quadratic polynomial function using the least squares method and the experimental set to obtain the quadratic polynomial coefficients. The phrase "obtaining the quadratic polynomial function based on the quadratic polynomial coefficients and the initial quadratic polynomial function" refers to substituting the quadratic polynomial coefficients into the initial quadratic polynomial function to obtain the quadratic polynomial function. The critical temperature is the value obtained by taking the first derivative of the quadratic polynomial function, setting the first derivative to zero, and solving for the value. The first derivative is the first derivative of the quadratic polynomial function with respect to the independent variable (ambient temperature). The second derivative value is the value obtained by substituting the critical temperature into the second derivative function. The second derivative function is the function obtained by taking the derivative of the first derivative function again.

[0117] Specifically, the process of obtaining the optimized temperature range based on the critical temperature, the second derivative value, and the second derivative function includes:

[0118] Compare the values ​​of the second derivative with zero;

[0119] If the second derivative value is greater than zero, the critical temperature is taken as the second abnormal temperature value.

[0120] If the second derivative value is less than zero, the critical temperature is used as the second optimal temperature value.

[0121] If the second derivative is equal to zero, then take the third derivative of the second derivative function to obtain the third derivative value, and compare the third derivative value with zero.

[0122] If the third derivative value is greater than zero, the critical temperature is taken as the third abnormal temperature value.

[0123] If the third derivative value is less than zero, the critical temperature is used as the third optimal temperature value.

[0124] If the third derivative is equal to zero, then the fourth derivative of the third derivative function is taken until the derivative is less than zero, thus obtaining the fourth optimized temperature value.

[0125] The second, third, or fourth optimized temperature value is used as the optimized temperature value, and an initial optimized temperature range is constructed based on the optimized temperature value and the preset reference temperature span.

[0126] Determine whether the abnormal second or third temperature value is within the initial optimized temperature range;

[0127] If the abnormal second temperature value or the abnormal third temperature value is within the initial optimized temperature range, then the abnormal second temperature value and the abnormal third temperature value are removed from the initial optimized temperature range to obtain the optimized temperature range.

[0128] If neither the abnormal second temperature value nor the abnormal third temperature value is within the initial optimized temperature range, then the initial optimized temperature range will be used as the optimized temperature range.

[0129] It should be explained that the abnormal second temperature value refers to the critical temperature when the second derivative is greater than zero. The second optimized temperature value refers to the critical temperature when the second derivative is less than zero. The third derivative value refers to the value obtained by taking the third derivative of the second derivative function. The abnormal third temperature value refers to the critical temperature when the second derivative is equal to zero and the third derivative is greater than zero. The third optimized temperature value refers to the critical temperature when the second derivative is equal to zero and the third derivative is less than zero. The fourth optimized temperature value refers to the critical temperature obtained by taking the fourth derivative of the third derivative function when both the second and third derivatives are equal to zero, until the derivative is less than zero. The optimized temperature value refers to the finally determined critical temperature, which can be the second, third, or fourth optimized temperature value. The reference temperature span is the temperature interval used to construct the initial optimized temperature range. For example, the reference temperature span is ±5℃. The initial optimized temperature range refers to the temperature range constructed based on the optimized temperature values ​​and the reference temperature span. For example, if the optimized temperature value is 40℃ and the reference temperature range is ±5℃, then the initial optimized temperature range is [40℃-5℃, 40℃+5℃], which is [35℃, 45℃]. The optimized temperature range refers to the temperature range after removing abnormal temperature values ​​from the initial optimized temperature range.

[0130] S3. Based on pre-built numerical simulation software, optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets, a viscosity-surface tension-momentum equation is constructed.

[0131] It should be explained that numerical simulation software refers to software used to construct and solve the governing equations that describe fluid flow and heat transfer.

[0132] In detail, the construction of the viscosity-surface-tension-momentum equation based on pre-built numerical simulation software, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets includes:

[0133] Randomly extract the set of simulated optimized temperature values ​​from the optimized temperature range. Obtain the set of simulated liquid viscosity and the set of simulated liquid surface tension based on the set of simulated optimized temperature values, multiple sets of normal liquid viscosity, and multiple sets of normal droplet surface tension. The simulated optimized temperature values ​​correspond one-to-one with the simulated liquid viscosity and the simulated liquid surface tension.

[0134] The pre-constructed Arrhenius equation was fitted using a simulated liquid viscosity set and numerical simulation software to obtain the pre-exponential fitting factor and the fitting activation energy.

[0135] The viscosity-temperature term was determined based on the pre-exponential factor and the activation energy of the fit. The surface tension curve of the liquid was plotted based on the simulated liquid surface tension set. The horizontal axis of the surface tension curve represents the ambient temperature, and the vertical axis of the surface tension curve represents the surface tension value of the liquid.

[0136] The target ambient temperature is randomly extracted from the liquid surface tension curve. The target liquid surface tension value is determined based on the target ambient temperature. The derivative value of the liquid surface tension is calculated based on the target liquid surface tension value.

[0137] The viscosity-temperature term, the derivative of liquid surface tension, and the pre-constructed momentum equation are used to construct the viscosity-surface tension-momentum equation.

[0138] Importantly, the simulated optimized temperature value set refers to a set randomly extracted from the optimized temperature range, and the extracted simulated optimized temperature values ​​can be found in the ambient temperature set. In this embodiment of the invention, the optimized temperature range is not a continuous range, but rather an range containing only multiple optimized temperature values. The steps for obtaining the simulated liquid viscosity set and simulated liquid surface tension set based on the simulated optimized temperature value set, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets are as follows: Simulated optimized temperature values ​​are extracted sequentially from the simulated optimized temperature value set; normal liquid viscosity sets and normal droplet surface tension sets corresponding to the simulated optimized temperature values ​​are extracted from the multiple normal liquid viscosity sets and multiple normal droplet surface tension sets, respectively; the average liquid viscosity and average droplet surface tension of the normal liquid viscosity sets and normal droplet surface tension sets are calculated, respectively; the average liquid viscosity is used as the simulated liquid viscosity, and the average droplet surface tension is used as the simulated liquid surface tension; the simulated liquid viscosity and simulated liquid surface tension are summarized, respectively, to obtain the simulated liquid viscosity set and simulated liquid surface tension set.

[0139] It should be explained that the simulated ambient temperature set refers to a set of temperature values ​​randomly extracted from the optimized temperature range, used to simulate the atomization process. The simulated liquid viscosity set refers to the viscosity values ​​extracted from multiple normal liquid viscosity sets at each simulated ambient temperature. The simulated liquid surface tension set refers to the surface tension values ​​extracted from multiple normal droplet surface tension sets at each simulated ambient temperature. The Arrhenius equation is a formula describing the change of viscosity with temperature. The fitting pre-exponential factor and fitting activation energy are parameters obtained by fitting the Arrhenius equation. The viscosity-temperature term refers to the term in the momentum equation that considers the change of viscosity with temperature. The liquid surface tension curve refers to the curve plotted to show the change of surface tension with temperature. The target ambient temperature refers to the temperature value randomly extracted from the liquid surface tension curve, used to calculate the target liquid surface tension value. Calculating the derivative value of the liquid surface tension based on the target liquid surface tension value means taking the derivative of the liquid surface tension curve at the point corresponding to the target liquid surface tension value to obtain the derivative value of the liquid surface tension. The momentum equation described in this embodiment is as follows:

[0140]

[0141] Here, F represents other external forces. For example, other external forces are forces caused by surface tension gradients.

[0142] In detail, the viscosity-surface-tension momentum equation is as follows:

[0143]

[0144] Where ρ represents the fluid density, The derivative of the fluid velocity with time. The negative pressure gradient term is represented by μ, and the viscosity-temperature term is represented by μ. Represents the velocity gradient tensor. This represents the transpose of the velocity gradient tensor. This represents the derivative of the surface tension of a liquid. Let represent the temperature gradient, δ represent the interface thickness, and n represent the interface normal vector. This represents the gradient operator.

[0145] It needs to be explained that fluid density refers to the mass of fluid per unit volume. The negative pressure gradient term refers to the rate of change of pressure in space. For example, in a pipe, the pressure gradually decreases from the inlet to the outlet, forming a negative pressure gradient. Fluids always flow from areas of high pressure to areas of low pressure, and the negative pressure gradient term reflects this driving force caused by the pressure difference. In the momentum equation, it represents the force exerted by the pressure difference on a unit volume of fluid, causing the fluid to flow and deform. The velocity gradient tensor is a tensor that describes the change of fluid velocity in space. The temperature gradient refers to the gradient of the simulated ambient temperature set. Interface thickness refers to the physical phenomenon at the interface used in the momentum equation. Because the fluid properties (such as viscosity, surface tension, etc.) at the interface differ from the bulk fluid, the presence of interface thickness affects the stress distribution and flow characteristics at the interface. The interface normal vector is used to determine the direction information at the interface. In the momentum equation, it is combined with the product of the temperature gradient and the derivative of the surface tension to describe the direction of the force generated at the interface due to the change of surface tension with temperature. This force affects the motion and deformation of the fluid at the interface.

[0146] S4. Set the solver parameters, extract the optimized temperature values ​​from the optimized temperature range in sequence, and simulate the pre-built simulated atomizer according to the solver parameters, optimized temperature values ​​and viscosity, surface tension and momentum equations to obtain the simulated atomization parameters.

[0147] Specifically, the simulated atomization parameters include: simulated droplet size, simulated atomization rate, and simulated atomization angle. The simulated atomization parameters correspond one-to-one with the optimized temperature values ​​in the optimized temperature range.

[0148] It should be explained that solver parameters refer to the parameters used in numerical simulation software to control the numerical solution process. For example, solver parameters include the time step and the number of iterations. The simulation based on solver parameters, the optimized temperature range, and the viscosity-surface-tension-momentum equation refers to sequentially extracting a temperature from the optimized temperature range and simulating it using numerical simulation software under the standard conditions of the viscosity-surface-tension-momentum equation. The simulated atomizer refers to the atomizer model used in the numerical simulation. This model is based on actual atomizer design parameters (such as nozzle diameter, gas flow rate, liquid flow rate, etc.) and is set and configured in the numerical simulation software.

[0149] S5. Calculate the relative error between the simulated atomization parameters and the preset atomization numerical parameters.

[0150] Specifically, the relative error between the calculated simulated atomization parameters and the preset atomization numerical parameters includes:

[0151] Sensitivity coefficients for multiple parameters are calculated based on simulated atomization parameters and numerical atomization parameters. The numerical atomization parameters include: experimental droplet size, experimental atomization rate, and experimental atomization angle.

[0152] The relative error between the simulated atomization parameters and the numerical atomization parameters is calculated based on the sensitivity coefficients of multiple parameters. The formula for calculating the relative error is as follows:

[0153]

[0154] Where C represents the relative error, k represents the index of the simulated atomization parameter, N represents the effective data volume, and α k S represents the sensitivity coefficient of the parameter. k This represents the preset error sensitivity coefficient, ΔT1 represents the preset temperature deviation value, T0 represents the reference temperature range, and 1 / ∑α represents the normalization exponent. This represents the simulated atomization parameters of type k in the i-th simulation. This represents the numerical parameter of the k-th type of atomization corresponding to the i-th simulation.

[0155] It should be explained that relative error refers to the degree of difference between simulated atomization parameters and preset atomization numerical parameters. Effective data volume refers to the number of data points actually involved in the calculation of relative error. Error sensitivity coefficient is a pre-set coefficient used to adjust the contribution of each parameter type to the total error when calculating relative error. Temperature deviation value is a pre-set value that considers the impact of temperature changes on the error when calculating relative error. Normalization index is an index used to normalize the total error when calculating relative error.

[0156] In detail, the calculation of multiple parameter sensitivity coefficients based on simulated atomization parameters and atomization numerical parameters includes:

[0157] The simulated droplet size is extracted from the simulated atomization parameters. The droplet size difference is calculated based on the simulated droplet size and the experimental droplet size. The droplet size change is calculated based on the droplet size difference and the experimental droplet size.

[0158] The simulated temperature is determined based on the simulated droplet size. The temperature difference is calculated based on the simulated temperature and the preset reference temperature. The temperature change is calculated based on the temperature difference and the reference temperature.

[0159] The particle size sensitivity coefficient is obtained based on the particle size change value and the temperature change value; the atomization rate sensitivity coefficient is calculated based on the simulated atomization rate and the experimental atomization rate; and the atomization angle sensitivity coefficient is calculated based on the simulated atomization angle and the experimental atomization angle.

[0160] By summing the particle size sensitivity coefficient, atomization rate sensitivity coefficient, and atomization angle sensitivity coefficient, multiple parameter sensitivity coefficients are obtained, wherein the parameter sensitivity coefficients are the particle size sensitivity coefficient, atomization rate sensitivity coefficient, or atomization angle sensitivity coefficient.

[0161] It should be explained that the simulated droplet size refers to the droplet size value obtained through numerical simulation software. The experimental droplet size refers to the pre-set droplet size. The droplet size difference = simulated droplet size - experimental droplet size. In the step of calculating the droplet size change value based on the droplet size difference and the experimental droplet size, the formula for calculating the droplet size change value is: Droplet size change value = Droplet size difference / Experimental droplet size. The simulated temperature refers to the temperature corresponding to the simulated droplet size in the numerical simulation. The reference temperature refers to the pre-set reference temperature value used when calculating temperature changes. The temperature difference = simulated temperature - reference temperature. In the step of calculating the temperature change value based on the temperature difference and the reference temperature, the formula for calculating the temperature change value is: Temperature change value = Temperature difference / Reference temperature. In the step of obtaining the droplet size sensitivity coefficient based on the droplet size change value and the temperature change value, the droplet size sensitivity coefficient = Droplet size change value / Temperature change value. The method for calculating the atomization rate sensitivity coefficient based on the simulated atomization rate and the experimental atomization rate is the same as the method for calculating the droplet size sensitivity coefficient based on the simulated droplet size and the experimental droplet size, and the method for calculating the atomization angle sensitivity coefficient based on the simulated atomization angle and the experimental atomization angle, and will not be described again here.

[0162] S6. If the relative error is greater than the preset relative error threshold, the solver parameters are adjusted to obtain the tuned solver parameters. The tuned solver parameters are used as the solver parameters, and the process of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature value, and viscosity, surface tension, and momentum equations is repeated until the relative error is not greater than the preset relative error threshold, thus obtaining the optimized atomization parameters.

[0163] It should be explained that the relative error threshold is a pre-set value used to determine whether the difference between the simulation results and the experimental data falls within this range. Adjusting the solver parameters refers to adjusting the time step or the number of iterations in the solver parameters. For example, if the time step in the solver parameters is 0.01 seconds and the number of iterations is 100, and during the numerical simulation, it was found that the residual fluctuated significantly during the iterations and had not converged after 100 iterations, the time step was reduced from 0.01 seconds to 0.005 seconds to improve the stability and convergence speed of the simulation, and the maximum number of iterations was increased from 100 to 200 to ensure that the simulation has sufficient time to converge.

[0164] S7. Otherwise, use the simulated atomization parameters as the optimized atomization parameters, summarize the optimized atomization parameters to obtain the optimized atomization parameter set, and obtain the optimal atomization parameters based on the optimized atomization parameter set.

[0165] It should be explained that optimized atomization parameters refer to simulated atomization parameters with a relative error not exceeding a preset relative error threshold. The optimized atomization parameter set refers to the collection of all optimized atomization parameters. The optimal atomization parameter refers to the optimized atomization parameter corresponding to the smallest relative error in the optimized atomization parameter set. The optimal atomization parameters described in this embodiment can be directly applied to the actual design and production of atomizers, helping engineers optimize the structure and operating parameters of atomizers, improve atomizer performance and efficiency, and reduce production costs.

[0166] To address the problems described in the background art, this invention identifies a set of test atomizers and a set of ambient temperatures. The ambient temperature set includes multiple distinct ambient temperatures. By identifying the test atomizer set, this invention determines the specific atomizer type or model targeted in the numerical simulation, providing a clear objective and avoiding an overly broad research scope. Based on the ambient temperature set and the test atomizer set, multiple sets of normal liquid viscosity and multiple sets of normal droplet surface tension are obtained. Based on these sets of normal liquid viscosity, normal droplet surface tension, and the ambient temperature set, an optimized temperature range is obtained. This optimized temperature range includes multiple optimized temperature values. This invention, based on the ambient temperature set and the test atomizer set... The atomizer sets these parameters to accurately reflect the physical properties of liquids under different ambient temperatures, providing data support for building accurate physical models. Optimizing the temperature range focuses on the temperature range that significantly affects atomization, reducing unnecessary computation and improving simulation efficiency and relevance. Based on pre-built numerical simulation software, the optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets, a viscosity-surface tension-momentum equation is constructed. This invention's viscosity-surface tension-momentum equation combines the two key factors of liquid viscosity and droplet surface tension, more accurately describing the fluid motion and interaction during atomization. Solver parameters are set, and optimized temperature values ​​are extracted sequentially from the optimized temperature range. The pre-constructed simulated atomizer is simulated based on the solver parameters, optimized temperature values, and viscosity, surface tension, and momentum equations to obtain simulated atomization parameters. These simulated atomization parameters include: simulated droplet size, simulated atomization rate, and simulated atomization angle. Each simulated atomization parameter corresponds one-to-one with the optimized temperature value within the optimized temperature range. The solver parameter settings of this invention can control the accuracy and computational efficiency of the numerical simulation. Reasonable solver parameter settings can ensure the stability and accuracy of the simulation process, making the simulation results more reliable. The relative error between the simulated atomization parameters and the preset atomization numerical parameters is calculated. If the relative error exceeds a preset relative error threshold, the solver parameters are adjusted to obtain the tuned solver parameters. The parameters are used as solver parameters. The process returns to the step of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature value, and viscosity, surface tension, and momentum equations, until the relative error is no greater than a preset relative error threshold. This process yields optimized atomization parameters. The steps of this invention ensure that the simulation results are close to the preset ideal values, thus making the simulation results more reliable. In practical applications, reliable simulation results can provide a more accurate basis for the design and optimization of atomizers. If the relative error is no greater than the preset relative error threshold, the simulated atomization parameters are used as optimized atomization parameters. The optimized atomization parameters are then summarized to obtain an optimized atomization parameter set. Based on this optimized atomization parameter set, the optimal atomization parameters are obtained. This invention obtains the optimal atomization parameters based on the optimized atomization parameter set.This invention can filter out the optimal atomization parameters from numerous optimization results under different temperature conditions, maximizing the atomization effect. These optimal atomization parameters can be directly applied to the actual design and production of atomizers, helping engineers optimize the structure and operating parameters of atomizers, improving their performance and efficiency, and reducing production costs. Therefore, this invention can improve the performance and atomization effect of atomizers.

[0167] like Figure 2 The diagram shown is a functional block diagram of a numerical simulation system for atomization based on temperature change characteristics provided in an embodiment of the present invention.

[0168] The atomizer atomization numerical simulation system 100 based on temperature change characteristics described in this invention can be installed in an electronic device. Depending on the functions implemented, the atomizer atomization numerical simulation system 100 may include an optimization interval acquisition module 101, a momentum equation construction module 102, an atomization numerical simulation module 103, and an optimal atomization parameter determination module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0169] The optimization range acquisition module 101 is used to identify the test atomizer set and the ambient temperature set, wherein the ambient temperature set includes multiple ambient temperatures, and each of the multiple ambient temperatures is different; based on the ambient temperature set and the test atomizer set, multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are acquired; based on the multiple normal liquid viscosity sets, multiple normal droplet surface tension sets and the ambient temperature set, an optimization temperature range is acquired, wherein the optimization temperature range includes multiple optimization temperature values;

[0170] The momentum equation construction module 102 is used to construct a viscosity-surface-tension momentum equation based on pre-built numerical simulation software, optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets.

[0171] The atomization numerical simulation module 103 is used to set solver parameters, sequentially extract optimized temperature values ​​from the optimized temperature range, and simulate the pre-constructed simulated atomizer according to the solver parameters, optimized temperature values, and viscosity-surface-tension-momentum equations to obtain simulated atomization parameters. The simulated atomization parameters include: simulated droplet size, simulated atomization rate, and simulated atomization angle. The simulated atomization parameters correspond one-to-one with the optimized temperature values ​​in the optimized temperature range. The relative error between the simulated atomization parameters and the preset atomization numerical parameters is calculated. If the relative error is greater than the preset relative error threshold, the solver parameters are adjusted to obtain the adjusted solver parameters. The adjusted solver parameters are used as the solver parameters, and the process returns to the step of simulating the pre-constructed simulated atomizer according to the solver parameters, optimized temperature values, and viscosity-surface-tension-momentum equations until the relative error is not greater than the preset relative error threshold, thus obtaining the optimized atomization parameters. Otherwise, the simulated atomization parameters are used as the optimized atomization parameters.

[0172] The optimal atomization parameter determination module 104 is used to summarize the optimized atomization parameters to obtain an optimized atomization parameter set, and obtain the optimal atomization parameters based on the optimized atomization parameter set.

[0173] In detail, the modules in the atomizer atomization numerical simulation system 100 based on temperature change characteristics described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method used is the same as the numerical simulation method for atomizer atomization based on temperature change characteristics described above, and can produce the same technical effect, so it will not be repeated here.

[0174] like Figure 3 The diagram shown is a schematic representation of an electronic device that implements a numerical simulation method for atomization based on temperature change characteristics, according to an embodiment of the present invention.

[0175] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a numerical simulation method program for atomizer atomization based on temperature change characteristics.

[0176] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a numerical simulation method program for atomizer atomization based on temperature change characteristics, but also to temporarily store data that has been output or will be output.

[0177] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a numerical simulation method program for atomizer atomization based on temperature change characteristics) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0178] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0179] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0180] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0181] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0182] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0183] The atomizer atomization numerical simulation method program based on temperature change characteristics stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0184] The test atomizer set and the ambient temperature set were identified. The ambient temperature set includes multiple ambient temperatures, and each of the multiple ambient temperatures is different.

[0185] Multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are obtained based on the ambient temperature set and the test atomizer set. An optimized temperature range is obtained based on the multiple normal liquid viscosity sets, multiple normal droplet surface tension sets and the ambient temperature set. The optimized temperature range includes multiple optimized temperature values.

[0186] The viscosity-surface-tension-momentum equation is constructed based on pre-built numerical simulation software, optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets.

[0187] Set the solver parameters, extract the optimized temperature values ​​from the optimized temperature range in sequence, and simulate the pre-built simulated atomizer according to the solver parameters, optimized temperature values ​​and viscosity, surface tension and momentum equations to obtain simulated atomization parameters. The simulated atomization parameters include: simulated droplet size, simulated atomization rate and simulated atomization angle. The simulated atomization parameters correspond one-to-one with the optimized temperature values ​​in the optimized temperature range.

[0188] Calculate the relative error between the simulated atomization parameters and the preset atomization numerical parameters;

[0189] If the relative error is greater than the preset relative error threshold, the solver parameters are adjusted to obtain the tuned solver parameters. The tuned solver parameters are then used as the solver parameters. The process of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature value, and viscosity, surface tension, and momentum equations is repeated until the relative error is not greater than the preset relative error threshold, thus obtaining the optimized atomization parameters.

[0190] Otherwise, the simulated atomization parameters will be used as the optimized atomization parameters;

[0191] The optimized atomization parameters are summarized and optimized to obtain an optimized atomization parameter set. The optimal atomization parameters are then obtained based on the optimized atomization parameter set.

[0192] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0193] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0194] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0195] The test atomizer set and the ambient temperature set were identified. The ambient temperature set includes multiple ambient temperatures, and each of the multiple ambient temperatures is different.

[0196] Multiple normal liquid viscosity sets and multiple normal droplet surface tension sets are obtained based on the ambient temperature set and the test atomizer set. An optimized temperature range is obtained based on the multiple normal liquid viscosity sets, multiple normal droplet surface tension sets and the ambient temperature set. The optimized temperature range includes multiple optimized temperature values.

[0197] The viscosity-surface-tension-momentum equation is constructed based on pre-built numerical simulation software, optimized temperature range, multiple normal liquid viscosity sets, and multiple normal droplet surface tension sets.

[0198] Set the solver parameters, extract the optimized temperature values ​​from the optimized temperature range in sequence, and simulate the pre-built simulated atomizer according to the solver parameters, optimized temperature values ​​and viscosity, surface tension and momentum equations to obtain simulated atomization parameters. The simulated atomization parameters include: simulated droplet size, simulated atomization rate and simulated atomization angle. The simulated atomization parameters correspond one-to-one with the optimized temperature values ​​in the optimized temperature range.

[0199] Calculate the relative error between the simulated atomization parameters and the preset atomization numerical parameters;

[0200] If the relative error is greater than the preset relative error threshold, the solver parameters are adjusted to obtain the tuned solver parameters. The tuned solver parameters are then used as the solver parameters. The process of simulating the pre-constructed simulated atomizer based on the solver parameters, optimized temperature value, and viscosity, surface tension, and momentum equations is repeated until the relative error is not greater than the preset relative error threshold, thus obtaining the optimized atomization parameters.

[0201] Otherwise, the simulated atomization parameters will be used as the optimized atomization parameters;

[0202] The optimized atomization parameters are summarized and optimized to obtain an optimized atomization parameter set. The optimal atomization parameters are then obtained based on the optimized atomization parameter set.

[0203] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0204] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0205] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0206] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0207] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method of numerical simulation of atomization of an atomizer based on temperature change characteristics, characterized by, The method comprises: confirming a test atomizer set and an environment temperature set, wherein the environment temperature set comprises a plurality of environment temperatures, and each of the plurality of environment temperatures is different; obtaining a plurality of normal liquid viscosity sets and a plurality of normal droplet surface tension sets based on the environment temperature set and the test atomizer set, and obtaining an optimized temperature interval based on the plurality of normal liquid viscosity sets, the plurality of normal droplet surface tension sets, and the environment temperature set, wherein the optimized temperature interval comprises a plurality of optimized temperature values; constructing a viscosity surface tension momentum equation based on a pre-constructed numerical simulation software, the optimized temperature interval, the plurality of normal liquid viscosity sets, and the plurality of normal droplet surface tension sets; setting a solver parameter, sequentially extracting an optimized temperature value from the optimized temperature interval, simulating a pre-constructed simulation atomizer according to the solver parameter, the optimized temperature value, and the viscosity surface tension momentum equation, and obtaining a simulation atomization parameter, wherein the simulation atomization parameter comprises a simulation droplet particle size, a simulation atomization rate, and a simulation atomization angle, and the simulation atomization parameter corresponds to the optimized temperature value in the optimized temperature interval in a one-to-one manner; calculating a relative error between the simulation atomization parameter and a preset atomization numerical parameter; if the relative error is greater than a preset relative error threshold, adjusting the solver parameter to obtain an adjusted solver parameter, taking the adjusted solver parameter as the solver parameter, returning to the step of simulating the pre-constructed simulation atomizer according to the solver parameter, the optimized temperature value, and the viscosity surface tension momentum equation, until the relative error is not greater than the preset relative error threshold, and obtaining an optimized atomization parameter; otherwise, taking the simulation atomization parameter as the optimized atomization parameter; summarizing the optimized atomization parameter to obtain an optimized atomization parameter set, and obtaining an optimal atomization parameter based on the optimized atomization parameter set.

2. The temperature change characteristic-based atomizer atomization numerical simulation method according to claim 1, characterized by, The method comprises: performing the following operations on each environment temperature in the environment temperature set: extracting a test atomizer from the test atomizer set, testing the test atomizer using a preset test time period and the environment temperature, obtaining a liquid viscosity set and a droplet surface tension set, wherein the test atomizer, the liquid viscosity set, and the droplet surface tension set correspond to the environment temperature in a one-to-one manner; normalizing the liquid viscosity set and the droplet surface tension set to obtain a normalized liquid viscosity set and a normalized droplet surface tension set; performing first outlier rejection on the normalized liquid viscosity set to obtain an initial liquid viscosity set, and performing box plot drawing on the initial liquid viscosity set to obtain an initial liquid viscosity box plot; performing descending order sorting on the initial liquid viscosity set to obtain an initial liquid viscosity sequence, calculating a first quartile and a third quartile of the initial liquid viscosity sequence, and calculating a quartile difference value based on the first quartile and the third quartile; calculating a liquid viscosity upper limit and a liquid viscosity lower limit based on the quartile difference value, the first quartile, and the third quartile, and confirming a liquid viscosity interval based on the liquid viscosity upper limit and the liquid viscosity lower limit; In the liquid viscosity interval, the initial liquid viscosity set in the initial liquid viscosity box plot is subjected to outlier elimination to obtain a normal liquid viscosity set, and the normal liquid droplet surface tension set is obtained based on the normalized liquid droplet surface tension set; The normal liquid viscosity set and the normal liquid droplet surface tension set are respectively summarized to obtain a plurality of normal liquid viscosity sets and a plurality of normal liquid droplet surface tension sets.

3. The method of claim 2, wherein the temperature change characteristics are based on a temperature change of the atomizer. The first outlier elimination on the normalized liquid viscosity set is performed to obtain the initial liquid viscosity set, including: The liquid viscosity mean and the liquid viscosity standard deviation are calculated based on the normalized liquid viscosity set, and the multiple standard deviation is calculated based on the liquid viscosity standard deviation and a preset multiple, wherein the multiple standard deviation is the product of the liquid viscosity standard deviation and the multiple, and the preset multiple is 3; The normalized liquid viscosity is sequentially extracted from the normalized liquid viscosity set, the liquid viscosity absolute difference value between the normalized liquid viscosity and the liquid viscosity mean is calculated, and the liquid viscosity absolute difference value is compared with the multiple standard deviation; If the liquid viscosity absolute difference value is greater than the multiple standard deviation, the normalized liquid viscosity corresponding to the liquid viscosity absolute difference value is taken as an abnormal liquid viscosity, the abnormal liquid viscosity is eliminated from the normalized liquid viscosity set to obtain an updated liquid viscosity set, the updated liquid viscosity set is taken as the normalized liquid viscosity set, and the step of sequentially extracting the normalized liquid viscosity from the normalized liquid viscosity set is returned until the normalized liquid viscosity set is empty; If the liquid viscosity absolute difference value is not greater than the multiple standard deviation, the normalized liquid viscosity corresponding to the liquid viscosity absolute difference value is taken as the initial liquid viscosity. The initial liquid viscosities are summarized to obtain the initial liquid viscosity set.

4. The method of claim 3, wherein the temperature change characteristics are based on a temperature change of the atomizer. The optimized temperature interval is obtained based on the plurality of normal liquid viscosity sets, the plurality of normal liquid droplet surface tension sets, and the ambient temperature set, including: The normal liquid viscosity set is sequentially extracted from the plurality of normal liquid viscosity sets, the normal liquid viscosity mean of the normal liquid viscosity set is calculated, and the normal liquid viscosity means are summarized to obtain a plurality of normal liquid viscosity means; The plurality of normal liquid droplet surface tension means is obtained based on the plurality of normal liquid droplet surface tension sets, and the experimental combination set is composed of the plurality of normal liquid viscosity means, the plurality of normal liquid droplet surface tension means, and the ambient temperature set, wherein the experimental combination set includes a plurality of experimental combinations, and each experimental combination in the plurality of experimental combinations includes: the normal liquid viscosity mean, the normal liquid droplet surface tension mean, and the ambient temperature; The initial quadratic polynomial function is constructed, the initial quadratic polynomial function is fitted based on the experimental combination set to obtain the quadratic polynomial coefficient, and the quadratic polynomial function is obtained based on the quadratic polynomial coefficient and the initial quadratic polynomial function; The first derivative of the quadratic polynomial function is obtained to obtain the critical temperature and the first derivative function, and the second derivative of the first derivative function is obtained to obtain the second derivative value and the second derivative function; The optimized temperature interval is obtained based on the critical temperature, the second derivative value, and the second derivative function.

5. The method of claim 4, wherein the temperature change characteristics are based on a temperature change of the atomizer. The optimized temperature interval is obtained based on the critical temperature, the second derivative value, and the second derivative function, including: The second derivative value is compared with zero; If the second derivative value is greater than zero, the critical temperature is taken as an abnormal second temperature value; If the second derivative value is less than zero, the critical temperature is taken as a second optimized temperature value; If the second derivative value is equal to zero, a third derivative of the second derivative function is taken to obtain a third derivative value, and the third derivative value is compared with zero; If the third derivative value is greater than zero, the critical temperature is taken as an abnormal third temperature value; If the third derivative value is less than zero, the critical temperature is taken as a third optimized temperature value; If the third derivative value is equal to zero, a fourth derivative of the third derivative function is taken until a derivative value is less than zero to obtain a fourth optimized temperature value; The second optimized temperature value, the third optimized temperature value, or the fourth optimized temperature value is taken as an optimized temperature value, and an initial optimized temperature interval is constructed based on the optimized temperature value and a preset reference temperature span; It is determined whether the abnormal second temperature value or the abnormal third temperature value is in the initial optimized temperature interval; If the abnormal second temperature value or the abnormal third temperature value is in the initial optimized temperature interval, the abnormal second temperature value and the abnormal third temperature value are excluded from the initial optimized temperature interval to obtain an optimized temperature interval; If the abnormal second temperature value and the abnormal third temperature value are not in the initial optimized temperature interval, the initial optimized temperature interval is taken as an optimized temperature interval.

6. The temperature change characteristic-based atomizer atomization numerical simulation method according to claim 5, wherein The viscosity-surface tension momentum equation is constructed based on the pre-constructed numerical simulation software, the optimized temperature interval, the plurality of normal liquid viscosity sets, and the plurality of normal liquid droplet surface tension sets, and includes: A set of simulation optimized temperature values is randomly extracted from the optimized temperature interval, a set of simulation liquid viscosities and a set of simulation liquid surface tensions are obtained according to the set of simulation optimized temperature values, the plurality of normal liquid viscosity sets, and the plurality of normal liquid droplet surface tension sets, wherein the simulation optimized temperature values correspond one-to-one to the simulation liquid viscosities and the simulation liquid surface tensions; The pre-constructed Arrhenius equation is fitted using the set of simulation liquid viscosities and the numerical simulation software to obtain a fitted pre-exponential factor and a fitted activation energy; The viscosity-temperature term is determined according to the fitted pre-exponential factor and the fitted activation energy, and a liquid surface tension curve is drawn according to the set of simulation liquid surface tensions, wherein the horizontal axis of the liquid surface tension curve is the environmental temperature, and the vertical axis of the liquid surface tension curve is the liquid surface tension value; A target environmental temperature is randomly extracted from the liquid surface tension curve, a target liquid surface tension value is determined according to the target environmental temperature, and a liquid surface tension derivative value is calculated according to the target liquid surface tension value; The viscosity-surface tension momentum equation is constructed based on the viscosity-temperature term, the liquid surface tension derivative value, and the pre-constructed momentum equation.

7. The temperature change characteristic-based atomizer atomization numerical simulation method according to claim 6, characterized by, The viscosity-surface tension momentum equation is as follows: where p denotes the fluid density, denotes the derivative of the fluid velocity with respect to time, denotes the negative pressure gradient term, p denotes the viscosity temperature term, denotes the velocity gradient tensor, denotes the transpose of the velocity gradient tensor, denotes the liquid surface tension derivative value, denotes the temperature gradient, d denotes the interface thickness, n denotes the interface normal vector, denotes the gradient operator.

8. The method of claim 7, wherein the temperature change characteristics are based on a temperature change of the atomizer. The relative error between the simulation atomization parameter and the preset atomization numerical parameter includes: A plurality of parameter sensitivity coefficients are calculated according to the simulation atomization parameter and the atomization numerical parameter, wherein the atomization numerical parameter includes: an experimental droplet particle size, an experimental atomization rate, and an experimental atomization angle; The relative error between the simulation atomization parameter and the atomization numerical parameter is calculated according to the plurality of parameter sensitivity coefficients, wherein the calculation formula of the relative error is as follows: wherein C represents a relative error, k represents an index of the simulated atomization parameter, N represents an effective data amount, a k represents a parameter sensitivity coefficient, S k represents a preset error sensitivity coefficient, ΔT1 represents a preset temperature deviation value, T0 represents a reference temperature span, 1 / ∑α represents a normalization index, represents the kth simulated atomization parameter of the i-th simulation, represents the kth atomization numerical parameter corresponding to the i-th simulation.

9. The method of claim 8, wherein the temperature change characteristics are based on a temperature change of the atomizer. The plurality of parameter sensitivity coefficients are calculated according to the simulation atomization parameter and the atomization numerical parameter, and include: A simulation droplet particle size is extracted from the simulation atomization parameter, a particle size difference value is calculated according to the simulation droplet particle size and the experimental droplet particle size, and a particle size change value is calculated based on the particle size difference value and the experimental droplet particle size; The simulation temperature is determined according to the simulated droplet particle size, a temperature difference value is calculated based on the simulation temperature and a preset reference temperature, and a temperature change value is calculated based on the temperature difference value and the reference temperature; The particle size sensitive coefficient is obtained based on the particle size change value and the temperature change value, the atomization rate sensitive coefficient is calculated based on the simulated atomization rate and the experimental atomization rate, and the atomization angle sensitive coefficient is calculated based on the simulated atomization angle and the experimental atomization angle; The particle size sensitive coefficient, the atomization rate sensitive coefficient and the atomization angle sensitive coefficient are summarized to obtain a plurality of parameter sensitive coefficients, wherein the parameter sensitive coefficient is the particle size sensitive coefficient, the atomization rate sensitive coefficient or the atomization angle sensitive coefficient.

10. A system for simulating the atomization of an atomizer based on temperature change characteristics, comprising: The system comprises: The optimization interval obtaining module is configured to determine a test atomizer set and an environmental temperature set, wherein the environmental temperature set comprises a plurality of environmental temperatures, each of which is different, a plurality of normal liquid viscosity sets and a plurality of normal droplet surface tension sets are obtained based on the environmental temperature set and the test atomizer set, and an optimization temperature interval is obtained based on the plurality of normal liquid viscosity sets, the plurality of normal droplet surface tension sets and the environmental temperature set, wherein the optimization temperature interval comprises a plurality of optimization temperature values; The momentum equation constructing module is configured to construct a viscosity surface tension momentum equation based on a pre-constructed numerical simulation software, the optimization temperature interval, the plurality of normal liquid viscosity sets and the plurality of normal droplet surface tension sets; The atomization numerical simulation module is configured to set a solver parameter, extract an optimization temperature value from the optimization temperature interval in sequence, simulate the pre-constructed simulation atomizer according to the solver parameter, the optimization temperature value and the viscosity surface tension momentum equation to obtain a simulation atomization parameter, wherein the simulation atomization parameter comprises a simulated droplet particle size, a simulated atomization rate and a simulated atomization angle, the simulation atomization parameter corresponds to the optimization temperature value in the optimization temperature interval in a one-to-one manner, a relative error between the simulation atomization parameter and a preset atomization numerical parameter is calculated, if the relative error is greater than a preset relative error threshold, the solver parameter is adjusted to obtain an adjusted solver parameter, the adjusted solver parameter is taken as the solver parameter, and the step of simulating the pre-constructed simulation atomizer according to the solver parameter, the optimization temperature value and the viscosity surface tension momentum equation is returned until the relative error is not greater than the preset relative error threshold to obtain an optimization atomization parameter, otherwise, the simulation atomization parameter is taken as the optimization atomization parameter; The optimal atomization parameter determining module is configured to summarize the optimization atomization parameters to obtain an optimization atomization parameter set, and obtain an optimal atomization parameter based on the optimization atomization parameter set.

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