Defoaming agent distribution state evaluation method

Abstract

The invention discloses a defoaming agent distribution state evaluation method, and particularly relates to the field of defoaming agent evaluation.The defoaming agent distribution state evaluation method comprises the steps that structural data of a defoaming agent distribution circular area with the radius being r are obtained through an electronic scanning microscope, and the structural data are drawn up as structural imaging data; establishing a judgment condition I for the structure imaging data based on medium factors; the medium factors comprise a characteristic scale ratio and a diffusion-adsorption ratio; the first proposed judgment condition comprises the following steps: if the feature scale ratio is smaller than a preset feature scale ratio threshold value and the diffusion-adsorption ratio is smaller than a preset diffusion-adsorption ratio threshold value, judging that the structural imaging data is topological trap risk data; on the basis of medium factors, a topological trap first-stage model is constructed for topological trap risk data in combination with fluid shear force and surface energy gradient. By introducing a multi-factor model such as a characteristic scale ratio, a diffusion-adsorption ratio and a fluid shear force, the evaluation range is dynamically adjusted, so that the distribution state of the defoaming agent is comprehensively judged, and the evaluation accuracy of the distribution state is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of defoamer evaluation, and more particularly to a method for evaluating the distribution state of a defoamer. Background Art

[0002] Defoamers are a type of chemical additives that can inhibit or eliminate foam in liquid systems. They are widely used in the chemical, food, pharmaceutical, textile, papermaking and other industries. Their mechanism of action mainly includes three aspects: foam breaking, foam suppression and defoaming. Common types of defoamers include silicone oils, polyethers, silicones, mineral oils, etc. Defoamers accelerate the disappearance of foam by reducing the surface tension of the foam liquid film, destroying the stability of bubbles or promoting the merging of foams. They can be dispersed in the system in the form of emulsions, solutions or powders, and act on the foam interface. Different defoamers have different dispersibility, compatibility and persistence in different media, which affects their application effect.

[0003] Topological trapping refers to the phenomenon that certain particles, droplets or molecules are trapped in local areas and have difficulty in diffusing or migrating freely due to the geometric structure of the material surface or the microscopic morphology inside the medium. In the defoamer system, topological traps usually occur in porous media, rough surfaces or microscopic cracks, causing the defoamer to be locally trapped, reducing its effective diffusion rate, and thus affecting the overall defoaming efficiency. The existing technology does not fully consider the topological trap problem when evaluating the distribution state of the defoamer, which may cause the evaluation results to be inconsistent with actual usage. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for evaluating the distribution state of a defoaming agent. By introducing multi-factor models such as characteristic scale ratio, diffusion-adsorption ratio and fluid shear force, the evaluation range is dynamically adjusted to comprehensively determine the distribution state of the defoaming agent to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for evaluating the distribution state of a defoaming agent, comprising:

[0006] The structure data of the circular area of ​​the defoamer distribution with a radius of r is obtained by electron scanning microscopy, and it is formulated as the structure imaging data;

[0007] Establishing judgment condition 1 for structural imaging data based on medium factors; medium factors include characteristic scale ratio and diffusion-adsorption ratio;

[0008] The proposed judgment condition 1 includes: if the characteristic scale ratio is less than a preset characteristic scale ratio threshold, and the diffusion-adsorption ratio is less than a preset diffusion-adsorption ratio threshold, the structural imaging data is judged to be topological trap risk data;

[0009] Based on medium factors, a topological trap one-stage model is constructed by combining fluid shear force and surface energy gradient with topological trap risk data;

[0010] The topological trap stage one value is calculated based on the topological trap stage one model; if the topological trap stage one value deviates from the topological trap stage one threshold, the structural data of the defoamer distribution circular area with a radius of r+n is obtained, and it is proposed as the expanded evaluation area data;

[0011] A topological trap two-stage model is constructed based on the extended assessment area data, and a topological trap two-stage value is calculated based on the topological trap two-stage model. If the topological trap two-stage value deviates from the topological trap two-stage threshold, the value of n is adjusted;

[0012] Based on the adjusted n value, the topological trap two-stage model calculation is repeated until the topological trap two-stage value meets the preset convergence condition;

[0013] If the second-stage value of the topological trap meets the preset convergence condition, the overall distribution state of the defoamer is determined based on the distribution state model.

[0014] In a preferred embodiment, based on the structural imaging data, Represents the imaging area of ​​a circular structure with a radius of r;

[0015]

[0016] Where x and y are coordinates within the circular area; d is the local defoamer concentration, which is obtained by electron scanning microscopy imaging.

[0017] In a preferred embodiment, the characteristic scale ratio is calculated by characterizing the relative scale between the defoamer droplets and the medium pores; the characteristic scale ratio is proposed to be R t ;

[0018]

[0019] where Φ d is the characteristic diameter of the defoamer particles; Θ p is the local pore diameter of the medium;

[0020] The diffusion-adsorption ratio is described by the diffusion capacity of the defoamer in the fluid relative to its adsorption capacity on the medium; the diffusion-adsorption ratio is proposed to be Λ;

[0021]

[0022] Among them Ψ f is the diffusion coefficient of the defoamer; s is the adsorption rate of the defoamer on the surface of the medium;

[0023] Proposed and Λ thres Respectively represent the preset thresholds of characteristic scale ratio and diffusion-adsorption ratio; if And Λ<Λ thres The structural imaging data is then determined to be topological trap risk data.

[0024] In a preferred embodiment, a topological trap one-stage model is constructed; a topological trap one-stage value is calculated based on the topological trap one-stage model, and a topological trap one-stage value is proposed to be Ω1;

[0025]

[0026] Where Γ is the surface energy distribution function; are the gradients of surface energy along the x and y directions respectively; α1, α2, β1, β2 are weight parameters;

[0027] The proposed topology trap threshold for the first stage is When Ω1 deviates Adjust the assessment scope; the proposed adjusted assessment scope is r′;

[0028] r′=r+n

[0029] Where n is the step size for adjusting the radius.

[0030] In a preferred embodiment, a topological trap two-stage model is constructed; a topological trap two-stage value is calculated based on the topological trap two-stage model; and a topological trap two-stage value is proposed to be Ω2

[0031]

[0032] Where V is the fluid velocity distribution function; are the gradients of fluid velocity in the x and y directions respectively; δ1, δ2, δ3 are the weight parameters of the two-stage model;

[0033] The proposed topology trap second stage threshold is If Ω2 deviates from the threshold Then adjust n, and the adjusted n is proposed to be n′;

[0034]

[0035] Where σ is the step size adjustment parameter.

[0036] In a preferred embodiment, the distribution state of the defoaming agent in the medium is calculated by a distribution state model; the distribution state model is expressed as:

[0037]

[0038] Wherein Ξ is the overall distribution state index of the defoamer; S(r ′ ) indicates that the radius is r ′ The circular evaluation area R t is the characteristic scale ratio; Λ is the diffusion-adsorption ratio; is the surface energy gradient; Γ is the surface energy, which is used to describe the surface tension of the liquid medium; x, y are the spatial coordinates; is the fluid velocity gradient; V is the local fluid velocity; λ1, λ2, λ3, λ4 are weight coefficients.

[0039] In a preferred embodiment, in the distribution state model, the influence of topological traps on the evaluation is eliminated, and a mechanism for eliminating the influence of topological traps is established by introducing a topological trap correction factor;

[0040]

[0041] Where Θ is the topological trap impact metric; ω1, ω2, ω3, ω4 are the topological trap correction weights;

[0042] The effects of topology traps are corrected by:

[0043] Ξ ′ =Ξ-ηΘ

[0044] Among them ′ is the distribution state index of the defoamer after correction; η is the adjustment coefficient, which is used to control the strength of the topological trap correction;

[0045] Establish the final convergence judgment condition for distribution state evaluation:

[0046] |Ξ′-Ξ thres |<∈

[0047] Among them thres is the distribution state threshold; ∈ is the convergence accuracy; when the convergence condition is met, the overall distribution state of the defoamer is determined.

[0048] Technical effects and advantages of the present invention:

[0049] 1. By introducing the characteristic scale ratio and diffusion-adsorption ratio to establish the judgment conditions, the topological trap area can be effectively identified; based on the technical means of dynamic adjustment, it can not only analyze the initial local area, but also gradually correct it by expanding the evaluation range to ensure the accuracy of the distribution state evaluation; compared with the traditional method, this scheme overcomes the evaluation error problem caused by not considering the topological trap, which is conducive to the judgment of the defoamer distribution state;

[0050] 2. The model of topological trap risk data is constructed by combining fluid shear force and surface energy gradient, which not only fully considers the complex influencing factors in the medium environment, but also can quantitatively analyze the changes in fluid dynamics and surface energy. Through the progressive optimization of the first-stage and second-stage models, the adaptability of the overall assessment to complex medium environments is enhanced, avoiding the limitations of traditional single parameter assessment methods.

[0051] 3. By introducing the topological trap correction factor into the distribution state model, a quantitative mechanism for the impact of topological traps was established. The design of the correction factor effectively eliminated the impact of the topological trap area, ensuring the scientificity and reliability of the final evaluation results.

[0052] 4. The nonlinear correction formula based on the hyperbolic tangent function is used to dynamically adjust the evaluation radius parameter, effectively ensuring the smoothness of the regional expansion and the convergence of the calculation results; through the flexible adjustment of the evaluation range, the evaluation model can be quickly adapted to different media;

[0053] 5. By constructing a distribution state model that includes characteristic scale ratio, diffusion-adsorption ratio, surface energy gradient and fluid velocity gradient, the distribution state optimization evaluation from local to global is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Refer to the instruction manual Figure 1 A method for evaluating the distribution state of a defoaming agent according to an embodiment of the present invention comprises:

[0057] The structure data of the circular area of ​​the defoamer distribution with a radius of r is obtained by electron scanning microscopy, and it is formulated as the structure imaging data;

[0058] Establishing judgment condition 1 for structural imaging data based on medium factors; medium factors include characteristic scale ratio and diffusion-adsorption ratio;

[0059] The proposed judgment condition 1 includes: if the characteristic scale ratio is less than a preset characteristic scale ratio threshold, and the diffusion-adsorption ratio is less than a preset diffusion-adsorption ratio threshold, the structural imaging data is judged to be topological trap risk data;

[0060] Based on medium factors, a topological trap one-stage model is constructed by combining fluid shear force and surface energy gradient with topological trap risk data;

[0061] The topological trap stage one value is calculated based on the topological trap stage one model; if the topological trap stage one value deviates from the topological trap stage one threshold, the structural data of the defoamer distribution circular area with a radius of r+n is obtained, and it is proposed as the expanded evaluation area data;

[0062] A topological trap two-stage model is constructed based on the extended assessment area data, and a topological trap two-stage value is calculated based on the topological trap two-stage model. If the topological trap two-stage value deviates from the topological trap two-stage threshold, the value of n is adjusted;

[0063] Based on the adjusted n value, the topological trap two-stage model calculation is repeated until the topological trap two-stage value meets the preset convergence condition;

[0064] If the second-stage value of the topological trap meets the preset convergence condition, the overall distribution state of the defoamer is determined based on the distribution state model;

[0065] What needs to be further explained about the above scheme is that the structural data of the defoamer distribution area is obtained by electron scanning microscopy and defined as basic imaging data, which provides an intuitive physical basis for subsequent evaluation. By introducing two medium factors, characteristic scale ratio and diffusion-adsorption ratio, judgment conditions are established to identify topological trap risk data, so as to scientifically quantify the local retention problem of defoamers in complex media; the judgment conditions judge the topological trap by comparing the actual data with the preset threshold, which reflects the operability of the method; based on the topological trap risk data, the fluid shear force and surface energy gradient are further combined to construct a first-stage model of topological traps, and the topological trap risk value is calculated to judge the local distribution state; when the model value deviates from the preset threshold, the evaluation area is expanded to obtain more comprehensive data, and the second-stage model is constructed and calculated. By repeatedly adjusting the regional parameters, the model value gradually meets the convergence condition, thereby ensuring the stability and accuracy of the evaluation; finally, the overall distribution of the defoamer is comprehensively evaluated through the distribution state model, and the interference of topological traps is effectively eliminated; the design logic of this scheme is based on the principles of layer-by-layer optimization and global analysis, and uses medium characteristics and fluid characteristics to provide rigorous and scientific technical support for solving the problem of uneven distribution of defoamers in complex media environments.

[0066] Based on structural imaging data, Represents the imaging area of ​​a circular structure with a radius of r;

[0067]

[0068] Where x and y are coordinates within the circular area; d is the local defoamer concentration, which is obtained by electron scanning microscopy imaging.

[0069] The characteristic scale ratio is calculated by describing the relative scale between the defoamer droplets and the medium pores. The characteristic scale ratio is proposed to be R t ; When R t If it is smaller than the critical threshold preset by the system, it means that the defoamer may be trapped in the pores, forming a topological trap;

[0070]

[0071] where Φ d is the characteristic diameter of the defoamer particles; Θ p is the local pore diameter of the medium;

[0072] The diffusion-adsorption ratio is described by the diffusion ability of the defoamer in the fluid relative to its adsorption ability on the medium. The diffusion-adsorption ratio is proposed to be Λ. When Λ is less than the critical threshold preset by the system, it means that the defoamer is more inclined to adsorb than diffuse, which is likely to lead to the formation of topological traps.

[0073]

[0074] Among them Ψ f is the diffusion coefficient of the defoamer; s is the adsorption rate of the defoamer on the surface of the medium;

[0075] Proposed and Λ thres Respectively represent the preset thresholds of characteristic scale ratio and diffusion-adsorption ratio; if And Λ<Λ thres The structural imaging data is then determined to be topological trap risk data.

[0076] Construct a topological trap one-stage model; calculate the topological trap one-stage value based on the topological trap one-stage model, and propose a topological trap one-stage value of Ω1;

[0077]

[0078] Where Γ is the surface energy distribution function; are the gradients of surface energy along the x and y directions respectively; α1, α2, β1, β2 are weight parameters;

[0079] The proposed topology trap threshold for the first stage is When Ω1 deviates This indicates that the topological trap risk in the current area is high, and the assessment range is adjusted; the proposed adjusted assessment range is r′;

[0080] r′=r+n

[0081] Where n is the step size of adjusting the radius;

[0082] The above scheme clarifies the assessment method and adjustment basis of the topological trap risk in the current area by constructing a topological trap one-stage model; its core idea is to combine the characteristic scale ratio and the diffusion-adsorption ratio to describe the distribution characteristics of the defoamer in the medium, and further introduce the gradient of surface energy change along two spatial directions (i.e., surface energy gradient) to quantify the influence of the local environment on the distribution of the defoamer; the parameters in the formula are adjusted through experimental fitting and data weights to ensure the flexibility and accuracy of the model; once the calculated topological trap one-stage value exceeds the preset threshold, it means that the topological trap risk in the current area is high, and more comprehensive data needs to be obtained by expanding the assessment area (adjusting the radius); this design is based on the logic of step-by-step optimization to ensure the effective capture of local abnormalities or complex distribution areas, while preventing the limitations of the initial regional data from affecting the global assessment results; thus, the assessment range can be dynamically adjusted, which is conducive to reflecting the distribution status of the defoamer at different spatial scales and providing reliable input for the subsequent topological trap two-stage model.

[0083] Construct a two-stage model of topological trap; calculate the two-stage value of topological trap based on the two-stage model of topological trap; propose the two-stage value of topological trap as Ω2

[0084]

[0085] Where V is the fluid velocity distribution function; are the gradients of fluid velocity in the x and y directions respectively; δ1, δ2, δ3 are the weight parameters of the two-stage model;

[0086] The proposed topology trap second stage threshold is If Ω2 deviates from the threshold Then adjust n, and the adjusted n is proposed to be n′;

[0087]

[0088] Where σ is the step size adjustment parameter;

[0089] What needs to be explained about the above scheme is that, by constructing a two-stage model of topological trap, the evaluation logic of the defoamer distribution state is further optimized, and the problem of insufficient local range that may exist in the one-stage model is solved; on the basis of the calculated value of the one-stage model, the gradient of the fluid velocity distribution is introduced as the key variable to analyze the influence of fluid dynamics on the defoamer distribution; when the two-stage value of the topological trap deviates from the preset threshold, the extension parameter n is dynamically adjusted, and a nonlinear correction formula based on the hyperbolic tangent function is adopted to ensure the smoothness and convergence of the adjustment process; by iteratively adjusting the evaluation range and parameters, it gradually approaches the ideal state, thereby ensuring the comprehensiveness and accuracy of the evaluation results; this layer-by-layer modeling method not only enhances the model's adaptability to complex environments, but also provides a reliable data basis for the final overall distribution evaluation.

[0090] The distribution state of the defoamer in the medium is calculated by the distribution state model; the distribution state model is expressed as:

[0091]

[0092]

[0093] Where Ξ is the overall distribution state index of the defoamer, and Ξ is used to characterize the overall distribution uniformity; S(r ′ ) indicates that the radius is r ′ The circular evaluation area R t is the characteristic scale ratio, R t It is used to indicate the relative relationship between the size of the defoamer and the pore size of the medium; Λ is the diffusion-adsorption ratio, which characterizes the diffusion capacity of the defoamer in the fluid relative to its adsorption capacity on the medium; is the surface energy gradient, which is used to measure the effect of surface energy changes on the distribution of defoamers; Γ is the surface energy, which is used to describe the surface tension of the liquid medium; x, y are spatial coordinates; is the fluid velocity gradient, which is used to measure the effect of fluid shear force on the distribution of defoaming agent; V is the local fluid velocity; λ1, λ2, λ3, λ4 are weight coefficients.

[0094] In the distribution state model, the influence of topological traps on the evaluation is eliminated, and a mechanism for eliminating the influence of topological traps is established by introducing topological trap correction factors.

[0095]

[0096] Where Θ is the topological trap impact metric; ω1, ω2, ω3, ω4 are the topological trap correction weights;

[0097] The effects of topology traps are corrected by:

[0098] Ξ′ =Ξ-ηΘ

[0099] Among them ′ is the distribution state index of the defoamer after correction, which removes the influence of topological traps; η is the adjustment coefficient, which is used to control the strength of topological trap correction;

[0100] Establish the final convergence judgment condition for distribution state evaluation:

[0101] |Ξ′-Ξthres|<∈

[0102] Among them thres is the distribution state threshold; ∈ is the convergence accuracy; when the convergence condition is met, the overall distribution state of the defoamer is determined.

[0103] The complete distribution state model is expressed as:

[0104]

[0105] Used for overall distribution evaluation of defoamers, ensuring the removal of topological trap effects and accurately calculating the distribution state of defoamers in the medium;

[0106] Firstly, a distribution state model is established to quantify the overall distribution uniformity of the defoamer. Physical parameters such as characteristic scale ratio, diffusion-adsorption ratio, surface energy gradient and fluid velocity gradient are introduced into the integral expression to comprehensively evaluate the distribution characteristics of the defoamer in the medium. In order to eliminate the interference of topological traps on the distribution evaluation, a topological trap correction mechanism is designed to quantify the influence of topological traps on the distribution state through correction factors.

[0107] Based on the progressive approach from local to global: firstly, the behavior of the defoamer in the local area is described by basic physical parameters (such as characteristic scale ratio and diffusion-adsorption ratio), and then the dynamic characteristics of the defoamer in complex media are reflected by combining surface energy gradient and fluid dynamics parameters; the correction factor is calculated by an independent integral formula to ensure that the interference of local abnormal data on the overall evaluation is eliminated; finally, the whole model verifies the reliability and consistency of the results through the convergence condition to ensure the comprehensiveness and stability of the evaluation;

[0108] Traditional mean or simple statistical methods are difficult to accurately capture the topological trap effect in complex media. However, this scheme can effectively eliminate abnormal interference and enhance the applicability and scientificity of the model by introducing multi-physical parameters and dynamic correction mechanisms. This design logic is closely connected, gradually advancing from mathematical models to physical meanings, providing a reliable technical path for solving the distribution evaluation problem of defoaming agents in complex environments.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the distribution state of a defoaming agent, characterized in that: include: The structure data of the circular area of ​​the defoamer distribution with a radius of r is obtained by electron scanning microscopy, and it is formulated as the structure imaging data; Establishing judgment condition one for structural imaging data based on medium factors; Medium factors include characteristic scale ratio and diffusion-adsorption ratio; The proposed judgment condition 1 includes: if the characteristic scale ratio is less than a preset characteristic scale ratio threshold, and the diffusion-adsorption ratio is less than a preset diffusion-adsorption ratio threshold, the structural imaging data is judged to be topological trap risk data; Based on medium factors, a topological trap one-stage model is constructed by combining fluid shear force and surface energy gradient with topological trap risk data; The topological trap stage one value is calculated based on the topological trap stage one model; if the topological trap stage one value deviates from the topological trap stage one threshold, the structural data of the defoamer distribution circular area with a radius of r+n is obtained, and it is proposed as the expanded evaluation area data; A topological trap two-stage model is constructed based on the extended assessment area data, and a topological trap two-stage value is calculated based on the topological trap two-stage model. If the topological trap two-stage value deviates from the topological trap two-stage threshold, the value of n is adjusted; Based on the adjusted n value, the topological trap two-stage model calculation is repeated until the topological trap two-stage value meets the preset convergence condition; If the second-stage value of the topological trap meets the preset convergence condition, the overall distribution state of the defoamer is determined based on the distribution state model.

2. A method for evaluating the distribution state of a defoaming agent according to claim 1, characterized in that: Based on structural imaging data, Represents the imaging area of ​​a circular structure with a radius of r; Where x and y are coordinates within the circular area; d is the local defoamer concentration, which is obtained by electron scanning microscopy imaging.

3. A defoamer distribution state evaluation method according to claim 2, characterized in that: The characteristic scale ratio is calculated by characterizing the relative scale between the defoamer droplets and the medium pores; The proposed characteristic scale ratio is R t ; where Φ d is the characteristic diameter of the defoamer particles; Θ p is the local pore diameter of the medium; The diffusion-adsorption ratio is described by the diffusion capacity of the defoamer in the fluid relative to its adsorption capacity on the medium; the diffusion-adsorption ratio is proposed to be Λ; Among them Ψ f is the diffusion coefficient of the defoamer; s is the adsorption rate of the defoamer on the surface of the medium; Proposed and Λ thres Respectively represent the preset thresholds of characteristic scale ratio and diffusion-adsorption ratio; if And Λ<Λ thres The structural imaging data is then determined to be topological trap risk data.

4. A method for evaluating the distribution state of a defoaming agent according to claim 3, characterized in that: Construct a topological trap one-stage model; calculate the topological trap one-stage value based on the topological trap one-stage model, and propose a topological trap one-stage value of Ω1; Where Γ is the surface energy distribution function; are the gradients of surface energy along the x and y directions respectively; α1, α2, β1, β2 are weight parameters; The proposed topology trap threshold for the first stage is When Ω1 deviates Adjust the assessment scope; the proposed adjusted assessment scope is r′; r′＝r+n Where n is the step size for adjusting the radius.

5. A method for evaluating the distribution state of a defoaming agent according to claim 4, characterized in that: Construct a two-stage model of topological trap; calculate the two-stage value of topological trap based on the two-stage model of topological trap; propose the two-stage value of topological trap as Ω2 Where V is the fluid velocity distribution function; are the gradients of fluid velocity in the x and y directions respectively; δ1, δ2, δ3 are the weight parameters of the two-stage model; The proposed topology trap second stage threshold is If Ω2 deviates from the threshold Then adjust n, and the adjusted n is proposed to be n′; Where σ is the step size adjustment parameter.

6. A method for evaluating the distribution state of a defoaming agent according to claim 5, characterized in that: The distribution state of the defoamer in the medium is calculated by the distribution state model; the distribution state model is expressed as: Wherein Ξ is the overall distribution state index of the defoamer; S(r ′ ) indicates that the radius is r ′ The circular evaluation area R t is the characteristic scale ratio; Λ is the diffusion-adsorption ratio; is the surface energy gradient; Γ is the surface energy, which is used to describe the surface tension of the liquid medium; x, y are the spatial coordinates; is the fluid velocity gradient; V is the local fluid velocity; λ1, λ2, λ3, λ4 are weight coefficients.

7. A method for evaluating the distribution state of a defoaming agent according to claim 6, characterized in that: In the distribution state model, the influence of topological traps on the evaluation is eliminated, and a mechanism for eliminating the influence of topological traps is established by introducing topological trap correction factors. Where Θ is the topological trap impact metric; ω1, ω2, ω3, ω4 are the topological trap correction weights; The effects of topology traps are corrected by: X ′ =Ξ-ηΘ Among them ′ is the distribution state index of the defoamer after correction; η is the adjustment coefficient, which is used to control the strength of the topological trap correction; Establish the final convergence judgment condition for distribution state evaluation: X′-X thres |<∈ Among them thres is the distribution state threshold; ∈ is the convergence accuracy; when the convergence condition is met, the overall distribution state of the defoamer is determined.

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