A zero-valent iron-zeolite permeable reactive barrier material proportioning optimization method and system considering the influence of fulvic acid concentration

Abstract

The application discloses a kind of zero-valent iron-zeolite permeable reaction barrier material proportioning optimization method and system considering the influence of fulvic acid concentration, and relates to the field of environmental geotechnical, including determining the FA equilibrium adsorption concentration under different proportioning conditions, calculating equilibrium adsorption amount;The relationship between influencing factors and response values is established by quadratic regression analysis;After standardization processing, the standardized quadratic regression model is obtained by conversion;Calculate the removal rate of adsorption material to FA.The application can accurately quantify the influence of multi-factor interaction on the repair effect, effectively overcome the model bias caused by nonlinear distribution of data, improve the prediction accuracy;Verify that it has good permeability and structural stability, so as to realize the synergistic optimization of repair performance and engineering applicability, and provide a scientific, feasible PRB material design method for complex and dynamic FA pollution control in actual site.

Description

Technical Field

[0001] This invention relates to the field of environmental geotechnical technology, and in particular to a method and system for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials, taking into account the influence of fulvic acid concentration. Background Technology

[0002] Currently, with the increasing prominence of groundwater pollution, permeable reactive barrier (PRB) technology is widely used for the treatment of organic and inorganic pollutants due to its advantages such as in-situ remediation, low operating costs, and minimal environmental disturbance. Among these technologies, zero-valent iron (ZFI) has shown significant effectiveness in degrading chlorinated hydrocarbons and heavy metals, serving as the mainstream PRB filling material. For pollution caused by natural organic pollutants such as fatty acids (FA), efforts are underway to combine adsorbent materials like zeolite with ZFI to enhance the synergistic removal of complex pollutants. However, FA concentrations fluctuate significantly in actual sites, potentially affecting not only the reactivity of PRB materials but also altering the quantitative relationship between material ratio and remediation efficiency. This makes traditional fixed-ratio PRB designs ill-suited to dynamic pollution conditions, necessitating the development of an intelligent ratio optimization method that responds to changes in FA concentration.

[0003] Existing PRB material formulation designs largely rely on experience or single-factor experiments, lacking a systematic consideration of multi-factor interactions. Even when some studies introduce experimental design methods, they often ignore the nonlinear distribution characteristics of response values ​​(such as FA equilibrium adsorption concentration) and fail to perform necessary data transformations, resulting in insufficient model prediction accuracy. Furthermore, current technologies generally focus on removal efficiency itself, neglecting the characterization of key physical structural parameters such as porosity and dry density of the optimized material combination, making it difficult to assess its permeability and stability in practical engineering. In addition, no technology has yet been found to couple the initial FA concentration, zero-valent iron, and zeolite addition amount to construct a standardized quadratic regression model using response surface methodology, and derive the optimal formulation relationship dynamically adjusted with pollution concentration, thereby achieving synergistic optimization of performance and engineering applicability. Summary of the Invention

[0004] In view of the problems existing in the current methods and systems for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials that take into account the influence of fulvic acid concentration, this invention is proposed.

[0005] Therefore, the problem to be solved by this invention is: how to scientifically optimize the ratio of zero-valent iron-zeolite PRB material based on the dynamic changes in fulvic acid (FA) pollution concentration, so as to simultaneously achieve high remediation efficiency and good engineering applicability.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for optimizing the formulation of zero-valent iron-zeolite permeable reactive barrier materials considering the influence of fulvic acid concentration. The method includes setting an influencing factor based on indoor batch adsorption experiments, dividing the influencing factor using Box-Behnken design, conducting equilibrium adsorption experiments of PRB material on FA, measuring the equilibrium adsorption concentration of FA under different formulation conditions, and calculating the equilibrium adsorption amount. Based on indoor batch adsorption experiments, response surface methodology (RSM) was introduced, and the relationship between influencing factors and response values ​​was established through quadratic regression analysis. Regression analysis was performed on the impact factors and response values ​​to obtain a quadratic regression model. The impact factors were then standardized and transformed to obtain a standardized quadratic regression model. Based on the experimental data from the indoor batch adsorption experiment, a standardized quadratic regression model was used for fitting analysis to calculate the removal rate of FA by the adsorption material.

[0007] As a preferred embodiment of the zero-valent iron-zeolite permeable reactive barrier material ratio optimization method considering the influence of fulvic acid concentration described in this invention, wherein: the influencing factors include the initial concentration of FA, the amount of Fe and zeolite added in the PRB material; The FA refers to fulvic acid, the PRB refers to a permeable reactive barrier, and the Fe refers to an active repair material used in PRB, where Fe is zero-valent iron. The Box-Behnken design is used to arrange experimental combinations of the initial concentration of FA, the amount of Fe and zeolite added in PRB, construct a response surface mathematical model, and complete the optimization of PRB material ratio.

[0008] As a preferred embodiment of the zero-valent iron-zeolite permeable reactive barrier material ratio optimization method considering the influence of fulvic acid concentration described in this invention, the method of dividing the influencing factors includes setting the influencing factors, including the initial concentration of FA, the amount of Fe and zeolite added in the PRB material, to three levels using a Box-Behnken design. These three levels are low, medium, and high. The formula for calculating the equilibrium adsorption capacity is:

[0009] Among them, V s C0 represents the initial concentration of pollutant FA, and q represents the solution volume. e C represents the equilibrium adsorption capacity of FA. e denoted by , where m represents the equilibrium adsorption concentration of FA, and m represents the mass of the zeolite.

[0010] As a preferred embodiment of the method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier material considering the influence of fulvic acid concentration as described in this invention, the response value refers to the equilibrium adsorption concentration of FA. The establishment of the relationship between influencing factors and response values ​​through quadratic regression analysis includes establishing a mathematical model between the initial concentration of FA, the amount of Fe and zeolite added in the PRB material, and the equilibrium adsorption concentration of FA through quadratic regression analysis. The construction of the response surface mathematical model includes constructing a response surface mathematical model of the initial concentration of FA, the amount of Fe added, and the amount of zeolite added on the equilibrium adsorption concentration of FA through quadratic regression analysis, thereby completing the optimization of the PRB material ratio.

[0011] As a preferred embodiment of the zero-valent iron-zeolite permeable reactive barrier material formulation optimization method considering the influence of fulvic acid concentration described in this invention, the mathematical model establishing the relationship between the initial FA concentration, the amount of Fe and zeolite added to the PRB material, and the equilibrium adsorption concentration of FA includes: Using the mathematical method of Response Surface Methodology (RSM), a polynomial relationship between influencing factors and response values ​​is established through quadratic regression analysis. The specific formula is as follows:

[0012] Where F1 represents the initial concentration of FA, F2 represents the amount of zero-valent iron added, F3 represents the amount of zeolite added, k1 and k2 are the power function transformation parameters, and a0...a9 represent the individual terms of the power function transformation.

[0013] As a preferred embodiment of the zero-valent iron-zeolite permeable reactive barrier material ratio optimization method considering the influence of fulvic acid concentration described in this invention, the PRB material ratio optimization further includes characterizing the physical structural properties of the PRB material combination and evaluating its properties in engineering. The evaluation in engineering refers to characterizing the physical structure properties of the PRB material assembly by calculating the porosity and dry density of the adsorbent material in the PRB material assembly. The formula for calculating porosity is:

[0014] Where n represents porosity, m1 represents the combined mass of the adsorbent material before drying, m2 represents the combined mass of the adsorbent material after drying, and ρ w V represents the density of water, and V0 represents the volume of the combined sample of the dried adsorbent material. The formula for calculating the dry density is:

[0015] Where, ρ dThis indicates the dry density of the combined sample of adsorbent materials.

[0016] As a preferred embodiment of the zero-valent iron-zeolite permeable reactive barrier material ratio optimization method considering the influence of fulvic acid concentration described in this invention, wherein: the calculation formula for obtaining the quadratic regression model is:

[0017] The formula for obtaining the standardized quadratic regression model is as follows:

[0018] in, This indicates that the equilibrium adsorption concentration of FA is a dimensionless value. This represents the dimensionless value of the initial concentration of FA. The dimensionless value representing the amount of zero-valent iron added. Dimensionless value representing the amount of zeolite added; The process of standardizing and transforming the impact factors includes converting them into dimensionless variables after standardization. The specific transformation formula is as follows:

[0019] Where, x i This represents the measured value of the influencing factor in indoor batch adsorption experiments, x. imax x represents the maximum value of the measured value. imax This represents the minimum measured value; The fitting analysis includes calculating the optimal relationship between Fe and zeolite addition in the PRB material based on a quadratic regression model. The specific calculation formula is as follows: F2 = 2.09 - 3.59 × 10 -4 F1-0.049F3 The formula for calculating the removal rate of FA by the adsorbent material is as follows:

[0020] Where, η FA This indicates the removal rate of FA by the adsorbent material.

[0021] Secondly, embodiments of the present invention provide a zero-valent iron-zeolite permeable reactive barrier material ratio optimization system that considers the influence of fulvic acid concentration, comprising: The experimental design and data acquisition module is based on indoor batch adsorption experiments. It sets influencing factors, uses Box-Behnken design to divide the influencing factors, conducts equilibrium adsorption experiments of PRB material on FA, determines the equilibrium adsorption concentration of FA under different ratio conditions, and calculates the equilibrium adsorption amount. The response surface modeling module, based on indoor batch adsorption experiments, introduces the response surface methodology (RSM) and establishes the relationship between influencing factors and response values ​​through quadratic regression analysis. The model standardization and parameter optimization module performs regression analysis on the influencing factors and response values ​​to obtain a quadratic regression model. It also standardizes the influencing factors and transforms them to obtain a standardized quadratic regression model. The model validation and performance evaluation module uses experimental data based on indoor batch adsorption experiments to perform fitting analysis with a standardized quadratic regression model and calculate the removal rate of FA by the adsorption material.

[0022] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the above-described method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier material considering the influence of fulvic acid concentration.

[0023] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the above-described method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials considering the influence of fulvic acid concentration.

[0024] The beneficial effects of this invention are as follows: By introducing Box-Behnken experimental design and response surface methodology, this invention establishes a standardized quadratic regression model relating the initial concentration of fulvic acid, the amount of zero-valent iron added, and the amount of zeolite added to the equilibrium adsorption concentration of FA. This model can accurately quantify the impact of multi-factor interactions on the remediation effect and derive the optimal ratio of Fe to zeolite dynamically adjusted with pollution concentration, significantly improving the FA removal rate of PRB materials. Simultaneously, by processing the response values ​​using a power function transformation, the model bias caused by nonlinear data distribution is effectively overcome, improving prediction accuracy. Furthermore, this invention systematically characterizes the porosity and dry density of the PRB material combination under optimized ratios, verifying its good permeability and structural stability. This achieves synergistic optimization of remediation performance and engineering applicability, providing a scientific and feasible PRB material design method for the complex and dynamic FA pollution remediation in actual sites. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart illustrating a method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials, taking into account the influence of fulvic acid concentration, as provided in an embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram of a system for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials, taking into account the effect of fulvic acid concentration, as provided in an embodiment of the present invention.

[0027] Figure 3 This is a schematic diagram of the FA distribution on the Fe surface after equilibrium adsorption, based on an optimization method for the proportion of zero-valent iron-zeolite permeable reactive barrier material considering the influence of fulvic acid concentration, provided in an embodiment of the present invention.

[0028] Figure 4 This is a schematic diagram of the FA distribution on the zeolite surface after equilibrium adsorption, based on an optimization method for the proportion of zero-valent iron-zeolite permeable reactive barrier material considering the influence of fulvic acid concentration, provided in an embodiment of the present invention.

[0029] Figure 5 This is a schematic diagram of the structure of a medium for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier material, which takes into account the influence of fulvic acid concentration, as provided in an embodiment of the present invention.

[0030] Figure 6 This is a schematic diagram of a computing device for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials, taking into account the influence of fulvic acid concentration, as provided in an embodiment of the present invention. Detailed Implementation

[0031] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0032] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0033] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0034] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0035] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0036] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. Example

[0037] Reference Figures 1-4 This is the first embodiment of the present invention, which provides a method for optimizing the formulation of zero-valent iron-zeolite permeable reactive barrier materials considering the influence of fulvic acid concentration, including: S1: Based on indoor batch adsorption experiments, influencing factors were set, and Box-Behnken design was used to divide the influencing factors. Equilibrium adsorption experiments of PRB material on FA were carried out to determine the equilibrium adsorption concentration of FA under different ratio conditions and calculate the equilibrium adsorption amount.

[0038] Among them, the influencing factors include the initial concentration of FA, the amount of Fe and zeolite added in the PRB material; FA refers to fulvic acid, PRB refers to permeable reactive barrier, and Fe refers to the active repair material used in PRB, where Fe is zero-valent iron. The Box-Behnken design is used to arrange experimental combinations of initial FA concentration, Fe and zeolite addition in PRB, construct response surface mathematical models, and complete the optimization of PRB material ratio.

[0039] The influencing factors were categorized into three levels: low, medium, and high. This included setting the initial concentration of FA, the amount of Fe added to the PRB material, and the amount of zeolite added. The formula for calculating the equilibrium adsorption capacity was:

[0040] Among them, V s C0 represents the initial concentration of pollutant FA, and q represents the solution volume. e C represents the equilibrium adsorption capacity of FA. e denoted by , where m represents the equilibrium adsorption concentration of FA, and m represents the mass of the zeolite.

[0041] Furthermore, the impact factor was set to three levels: low (-1), medium (0), and high (1). The environmental engineering batch experimental conditions optimized based on RSM are shown in Table 1 below: Table 1. Experimental conditions for environmental engineering batches based on RSM optimization.

[0042] Table 1 above describes the FA (BR, purity ≥95%) used in the experiment, with a density of 1.8 g / cm³. 3 Particle size ≤10 μm; zero-valent iron powder (AR, purity ≥99%), density 7.9 g / cm³ 3 Particle size ≤ 20 μm; synthetic zeolite (CP, calcium ion exchange capacity ≥ 20 mg / g), particle size ≤ 10 μm, density 1.9 g / cm³ 3 The water used in the experiment was ultrapure water, which was prepared by a French LILLPORE (Elix5) pure water equipment. The specific experimental steps are as follows: 1) Zero-valent iron powder and artificial zeolite were quantitatively combined and poured into a polyethylene bottle with a certain initial concentration of FA solution (50 mL); 2) At room temperature (25℃), the bottle was placed in a constant temperature shaker and shaken at a speed of 230 r / min for 24 hours; 3) The adsorption concentration was analyzed using a SHIMADZU three-dimensional fluorescence spectrophotometer (RF-6000).

[0043] S2: Based on indoor batch adsorption experiments, response surface methodology (RSM) is introduced, and the relationship between influencing factors and response values ​​is established through quadratic regression analysis.

[0044] The response value refers to the equilibrium adsorption concentration of FA. The relationship between influencing factors and response values ​​was established through quadratic regression analysis, including establishing a mathematical model between the initial concentration of FA, the amount of Fe and zeolite added in PRB material, and the equilibrium adsorption concentration of FA. The construction of the response surface mathematical model includes constructing a response surface mathematical model of the initial concentration of FA, the amount of Fe added and the amount of zeolite added on the equilibrium adsorption concentration of FA through quadratic regression analysis, thereby completing the optimization of PRB material ratio.

[0045] S2.1: Establishing a mathematical model relating the initial FA concentration, the amount of Fe and zeolite added to the PRB material, and the equilibrium adsorption concentration of FA includes: Using the mathematical method of Response Surface Methodology (RSM), a polynomial relationship between influencing factors and response values ​​is established through quadratic regression analysis. The specific formula is as follows:

[0046] Where F1 represents the initial concentration of FA, F2 represents the amount of zero-valent iron added, F3 represents the amount of zeolite added, k1 and k2 are the power function transformation parameters, and a0...a9 represent the individual terms of the power function transformation.

[0047] Furthermore, based on experimental data, the Response Surface Method (RSM) mathematical method was used to establish a polynomial between all factors and response values ​​through quadratic regression analysis, clarifying the precise relationship between factors and response values. According to the indoor experimental results, the equilibrium adsorption concentration range of fulvic acid was found to be 7.33 mg / L-95.29 mg / L, with a maximum to minimum ratio of 13, which is greater than 10. Power function transformation measures were then applied to the factors and response values.

[0048] Further refinement of the PRB material ratio optimization in step S2 is provided. The PRB material ratio optimization also includes characterizing the physical structural properties of the PRB material combination and evaluating its properties in engineering. Assessing the properties of PRB materials in engineering involves calculating the porosity and dry density of the adsorbent material in the PRB material assemblies, thereby characterizing the physical structural properties of the PRB material assemblies. The formula for calculating porosity is:

[0049] Where n represents porosity, m1 represents the combined mass of the adsorbent material before drying, m2 represents the combined mass of the adsorbent material after drying, and ρ w V represents the density of water, and V0 represents the volume of the combined sample of the dried adsorbent material. The formula for calculating dry density is:

[0050] Where, ρ d This indicates the dry density of the combined sample of adsorbent materials.

[0051] Preferably, after the adsorption experiment is completed, the adsorbent material is placed in an oven at 105 °C and dried for 8 hours to determine the porosity and dry density of the adsorbent material.

[0052] The environmental engineering batch test results of the RSM-optimized PRB material for FA remediation are shown in Table 2 below: Table 2. Environmental engineering batch test results of RSM-optimized PRB materials for FA remediation.

[0053] Table 2 above lists the conditions and results of 17 batch adsorption experiments, including the initial concentration of fulvic acid, the amount of zero-valent iron added, the amount of zeolite added, and the corresponding equilibrium adsorption concentration.

[0054] S3: Perform regression analysis on the impact factors and response values ​​to obtain a quadratic regression model. Standardize the impact factors and then transform them to obtain a standardized quadratic regression model.

[0055] The formula for calculating the quadratic regression model is as follows:

[0056] The formula for obtaining the standardized quadratic regression model is:

[0057] in, This indicates that the equilibrium adsorption concentration of FA is a dimensionless value. This represents the dimensionless value of the initial concentration of FA. The dimensionless value representing the amount of zero-valent iron added. Dimensionless value representing the amount of zeolite added; The transformation process after standardizing the impact factors includes converting them into dimensionless variables. The specific transformation formula is as follows:

[0058] Where, x i This represents the measured value of the influencing factor in indoor batch adsorption experiments, x. imax x represents the maximum value of the measured value. imax This represents the minimum measured value.

[0059] S4: Based on the experimental data from the indoor batch adsorption experiment, a standardized quadratic regression model was used for fitting analysis to calculate the removal rate of FA by the adsorption material.

[0060] The fitting analysis included calculating the optimal relationship between Fe and zeolite addition in the PRB material using a quadratic regression model. The specific calculation formula is as follows: F2 = 2.09 - 3.59 × 10 -4 F1-0.049F3 The formula for calculating the removal rate of FA by the adsorbent material is as follows:

[0061] Where, η FA This indicates the removal rate of FA by the adsorbent material.

[0062] Preferably, the results of the fitting analysis are shown in Table 3: the standard deviation is 1.38, with an error of less than 2; the predicted R² value is 0.984, which is consistent with the adjusted R² value of 0.998, with a difference of less than 0.02; the signal-to-noise ratio of 82.306 is much greater than 4, indicating that the experimental data intensity is significantly higher than the interference factors, and the prediction results are good; the coefficient of variation is 2.390%, which is much less than 5%, indicating that the data is highly stable and reliable. Table 3 Results of Fit Analysis

[0063] Table 3 shows the experimental data based on the indoor batch adsorption experiment. The fitting analysis with the standardized quadratic regression model shows that the model has a high coefficient of determination, low standard deviation and coefficient of variation, as well as a high signal-to-noise ratio, good prediction accuracy and stable and reliable data.

[0064] Based on the material usage in the experiment, the porosity of the materials in this scheme ranges from 0.29 to 0.40, and the dry density ranges from 1.67 to 2.03 g / cm³. 3 .

[0065] If 0.2 g of zeolite is used as the adsorbent to adsorb 200 mg / L of fecal organic matter (FA), when the amount of Fe added is 2.00 g, the Ce removal rate of the adsorbent material combination reaches 54.54 mg / L for FA, with a removal rate of 72.73%. In contrast, the removal rate of the material without optimized ratio (1 g each of zeolite and iron) does not exceed 58%. The removal rate of the optimized material is more than 25% higher than that before optimization, which significantly improves the remediation effect of the adsorbent material on FA.

[0066] According to the results of FE-ESEM scanning electron microscopy, Fe has a stronger adsorption capacity for FA than zeolite, and flocculent and spherical FA particles were observed on the surfaces of both Fe and zeolite. Figure 3 and Figure 4 FA contains negatively charged functional groups, which can form complexes with positively charged Fe ions or zero-valent iron, thereby alleviating the aggregation of Fe; zeolite has the ability to adsorb HA / FA due to its ion exchange properties.

[0067] Fe and zeolite exhibit good adsorption performance for FA under non-alkaline conditions. This is mainly because both Fe and zeolite are positively charged at pH < 7, which repel each other and inhibits adsorption or cation exchange. Therefore, the competitive adsorption between Fe and zeolite has no significant effect on FA.

[0068] In a preferred embodiment, a zero-valent iron-zeolite permeable reactive barrier material formulation optimization system considering the influence of fulvic acid concentration is provided. This system includes an experimental design and data acquisition module, which, based on indoor batch adsorption experiments, sets influencing factors, uses Box-Behnken design to divide these factors, conducts equilibrium adsorption experiments of PRB material on FA, determines the equilibrium adsorption concentration of FA under different formulation conditions, and calculates the equilibrium adsorption amount; a response surface modeling module, which, based on indoor batch adsorption experiments, introduces the response surface methodology (RSM) and establishes the relationship between influencing factors and response values ​​through quadratic regression analysis; a model standardization and parameter optimization module, which performs regression analysis on influencing factors and response values ​​to obtain a quadratic regression model, standardizes the influencing factors, and transforms them to obtain a standardized quadratic regression model; and a model validation and performance evaluation module, which performs fitting analysis between experimental data based on the indoor batch adsorption process and the standardized quadratic regression model to calculate the removal rate of FA by the adsorption material.

[0069] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or independent of it, or they can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0070] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface of the computer device is used for wired or wireless communication with external terminals. Wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be an LCD screen or an e-ink display screen. The input device of the computer device may be a touch layer covering the display screen, or buttons, a trackball, or a touchpad located on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0071] In summary, this invention, by introducing Box-Behnken experimental design and response surface methodology, established a standardized quadratic regression model relating the initial concentration of fulvic acid, the amount of zero-valent iron added, and the amount of zeolite added to the equilibrium adsorption concentration of FA. This model can accurately quantify the impact of multi-factor interactions on the remediation effect and derive the optimal ratio of Fe to zeolite dynamically adjusted with pollution concentration, significantly improving the FA removal rate of PRB materials. Simultaneously, by processing the response values ​​using a power function transformation, the model bias caused by nonlinear data distribution is effectively overcome, improving prediction accuracy. Furthermore, this invention systematically characterizes the porosity and dry density of the PRB material combination under optimized ratios, verifying its good permeability and structural stability. This achieves synergistic optimization of remediation performance and engineering applicability, providing a scientific and feasible PRB material design method for the complex and dynamic FA pollution remediation in real-world sites.

[0072] Reference Figures 5-6 After introducing the method and system of exemplary embodiments of the present invention, the following references are made. Figure 5 A computer-readable storage medium according to exemplary embodiments of the present invention will be described, please refer to... Figure 5 The computer-readable storage medium shown is an optical disc 30, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it implements the steps described in the above-described method implementation. For example, based on indoor batch adsorption experiments, influencing factors are set, and Box-Behnken design is used to divide the influencing factors. Equilibrium adsorption experiments of PRB material on FA are carried out to determine the equilibrium adsorption concentration of FA under different ratios and to calculate the equilibrium adsorption amount. Based on indoor batch adsorption experiments, Response Surface Methodology (RSM) is introduced, and the relationship between influencing factors and response values ​​is established through quadratic regression analysis. Regression analysis is performed on the influencing factors and response values ​​to obtain a quadratic regression model. The influencing factors are standardized and then transformed to obtain a standardized quadratic regression model. The experimental data based on the indoor batch adsorption process are fitted with the standardized quadratic regression model to calculate the removal rate of FA by the adsorption material. The specific implementation methods of each step will not be repeated here.

[0073] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media, which will not be elaborated here.

[0074] After introducing the methods and media of exemplary embodiments of the present invention, the following references are made. Figure 6 A computational device for adaptive recovery of low-voltage power grid self-healing control according to an exemplary embodiment of the present invention.

[0075] Figure 6 A block diagram is shown of an exemplary computing device 40 suitable for implementing embodiments of the present invention. The computing device 40 may be a computer system or a server. Figure 6 The computing device 40 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0076] like Figure 6 As shown, the components of computing device 40 may include, but are not limited to: one or more processors or processing units 401, system memory 402, and bus 403 connecting different system components (including system memory 402 and processing unit 401).

[0077] The computing device 40 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computing device 40, including volatile and non-volatile media, and removable and non-removable media.

[0078] System memory 402 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 4021 and / or cache memory 4022. Computing device 40 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, ROM 4023 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 6 (Not shown in the image, usually referred to as "hard drive"). Although not shown in... Figure 6 The diagram illustrates that disk drives for reading and writing to removable non-volatile disks (e.g., "floppy disks") and optical disc drives for reading and writing to removable non-volatile optical discs (e.g., CD-ROMs, DVD-ROMs, or other optical media) can be provided. In these cases, each drive can be connected to bus 403 via one or more data media interfaces. System memory 402 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0079] A program / utility 4025 having a set (at least one) of program modules 4024 may be stored, for example, in system memory 402, and such program modules 4024 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment. Program modules 4024 typically perform the functions and / or methods described in the embodiments of the present invention.

[0080] The computing device 40 can also communicate with one or more external devices 404 (such as a keyboard, pointing device, display, etc.). This communication can be performed via the input / output (I / O) interface 405. Furthermore, the computing device 40 can also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 406. Figure 6 As shown, network adapter 406 communicates with other modules of computing device 40 (such as processing unit 401) via bus 403. It should be understood that, although... Figure 6 As not shown, it can be used in conjunction with computing device 40 with other hardware and / or software modules.

[0081] The processing unit 401 executes various functional applications and data processing by running programs stored in the system memory 402. For example, based on indoor batch adsorption experiments, it sets influencing factors, uses Box-Behnken design to divide the influencing factors, conducts equilibrium adsorption experiments of PRB material on FA, measures the equilibrium adsorption concentration of FA under different ratios, and calculates the equilibrium adsorption amount. Based on indoor batch adsorption experiments, it introduces the response surface methodology (RSM) and establishes the relationship between influencing factors and response values ​​through quadratic regression analysis. It performs regression analysis on the influencing factors and response values ​​to obtain a quadratic regression model, standardizes the influencing factors, and transforms them to obtain a standardized quadratic regression model. It then performs fitting analysis on the experimental data based on the indoor batch adsorption process with the standardized quadratic regression model to calculate the removal rate of FA by the adsorbent material.

[0082] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0083] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0084] The units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0085] In addition, the functional units 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.

[0086] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0088] Furthermore, although the operations of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0089] 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, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing the formulation of zero-valent iron-zeolite permeable reactive barrier materials considering the effect of fulvic acid concentration, characterized in that: include, Based on indoor batch adsorption experiments, influencing factors were defined and Box-Behnken design was used to divide the influencing factors. Equilibrium adsorption experiments of PRB material on FA were carried out, the equilibrium adsorption concentration of FA under different ratio conditions was determined, and the equilibrium adsorption amount was calculated. Based on indoor batch adsorption experiments, response surface methodology (RSM) was introduced, and the relationship between influencing factors and response values ​​was established through quadratic regression analysis. Regression analysis was performed on the impact factors and response values ​​to obtain a quadratic regression model. The impact factors were then standardized and transformed to obtain a standardized quadratic regression model. Based on experimental data from indoor batch adsorption experiments, a standardized quadratic regression model was used for fitting analysis to calculate the removal rate of fatty acids (FA) by the adsorption material. The influencing factors include the initial concentration of FA, the amount of Fe and zeolite added to the PRB material; The FA refers to fulvic acid, the PRB refers to a permeable reactive barrier, and the Fe refers to an active repair material used for PRB. The Box-Behnken design was used to arrange experimental combinations of initial FA concentration, Fe and zeolite addition in PRB, construct a response surface mathematical model, and optimize the PRB material ratio. The response value refers to the equilibrium adsorption concentration of FA; The establishment of the relationship between influencing factors and response values ​​through quadratic regression analysis includes establishing a mathematical model between the initial concentration of FA, the amount of Fe and zeolite added in the PRB material, and the equilibrium adsorption concentration of FA through quadratic regression analysis. The construction of the response surface mathematical model includes constructing a response surface mathematical model of the initial concentration of FA, the amount of Fe added and the amount of zeolite added on the equilibrium adsorption concentration of FA through quadratic regression analysis, thereby completing the optimization of PRB material ratio; The mathematical model establishing the relationship between the initial FA concentration, the amount of Fe and zeolite added to the PRB material, and the equilibrium adsorption concentration of FA includes: Using the mathematical method of Response Surface Methodology (RSM), a polynomial relationship between influencing factors and response values ​​is established through quadratic regression analysis. The specific formula is as follows: in, This indicates the initial concentration of FA. Indicates the amount of zero-valent iron added. This indicates the amount of zeolite added. and These are the parameters for the power function transformation. These represent the individual terms of the power function transformation.

2. The method for optimizing the formulation of zero-valent iron-zeolite permeable reactive barrier material considering the effect of fulvic acid concentration as described in claim 1, characterized in that: The influencing factors are divided into three levels using a Box-Behnken design, including the initial concentration of FA, the amount of Fe and zeolite added to the PRB material, and low, medium, and high levels. The formula for calculating the equilibrium adsorption capacity is: in, Indicates the volume of the solution. This indicates the initial concentration of pollutant FA. This represents the equilibrium adsorption capacity of FA. This represents the equilibrium adsorption concentration of FA. This indicates the mass of the zeolite.

3. The method for optimizing the formulation of zero-valent iron-zeolite permeable reactive barrier materials considering the effect of fulvic acid concentration as described in claim 1, characterized in that: The optimization of PRB material proportions also includes characterizing the physical structural properties of the PRB material combination and evaluating its properties in engineering. The evaluation in engineering refers to characterizing the physical structure properties of the PRB material assembly by calculating the porosity and dry density of the adsorbent material in the PRB material assembly. The formula for calculating porosity is: in, This indicates the dry density of the combined sample of adsorbent materials.

4. The method for optimizing the formulation of zero-valent iron-zeolite permeable reactive barrier materials considering the effect of fulvic acid concentration as described in claim 3, characterized in that: The formula for calculating the quadratic regression model is as follows: The formula for obtaining the standardized quadratic regression model is: in, This indicates that the equilibrium adsorption concentration of FA is a dimensionless value. This represents the dimensionless value of the initial concentration of FA. The dimensionless value representing the amount of zero-valent iron added. The dimensionless value representing the amount of zeolite added; the standardization and transformation of the influencing factors includes converting the influencing factors into dimensionless variables after standardization, and the specific transformation formula is as follows: in, This represents the measured value of the influencing factor in indoor batch adsorption experiments. This represents the maximum value of the measured value. This represents the minimum measured value; the fitting analysis includes calculating the optimal relationship between Fe and zeolite addition in the PRB material based on a quadratic regression model, with the specific calculation formula as follows: The formula for calculating the removal rate of FA by the adsorbent material is as follows: in, This indicates the removal rate of FA by the adsorbent material.

5. A system for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials considering the influence of fulvic acid concentration, based on the method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier materials considering the influence of fulvic acid concentration as described in any one of claims 1 to 4, characterized in that: This includes an experimental design and data acquisition module, which is based on indoor batch adsorption experiments, sets influencing factors, uses Box-Behnken design to divide the influencing factors, conducts equilibrium adsorption experiments of PRB material on FA, determines the equilibrium adsorption concentration of FA under different ratio conditions, and calculates the equilibrium adsorption amount; and a response surface modeling module, which is based on indoor batch adsorption experiments, introduces the response surface method RSM, and establishes the relationship between influencing factors and response values ​​through quadratic regression analysis. The model standardization and parameter optimization module performs regression analysis on the influencing factors and response values ​​to obtain a quadratic regression model. It also standardizes the influencing factors and transforms them to obtain a standardized quadratic regression model. The model validation and performance evaluation module uses experimental data based on indoor batch adsorption experiments to perform fitting analysis with a standardized quadratic regression model and calculate the removal rate of FA by the adsorption material.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier material considering the effect of fulvic acid concentration as described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for optimizing the proportion of zero-valent iron-zeolite permeable reactive barrier material considering the effect of fulvic acid concentration as described in any one of claims 1 to 4.

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