Response surface method-based method for determining proportion of steel slag improved marine silt curing agent

Abstract

The invention discloses a steel slag improved marine facies sludge curing agent proportion determination method based on a response surface method, which comprises the following steps: carrying out a shear strength test on waste steel slag improved marine dredged sludge under a freezing and thawing cycle, and determining the optimal curing agent mixing amount of the marine dredged sludge; performing an unconfined compressive strength test based on the optimal mixing amount of the curing agent of the marine dredged sludge to obtain the optimal mixing amount range of each component of the curing agent; testing by taking the mixing amount of each component of the curing agent as a main variable and taking 7d compressive strength and 14d compressive strength as response amounts to obtain response value test results under different mixing ratios; performing nonlinear fitting on a response value test result, and establishing a response surface model; obtaining an expected value of each response quantity based on the response surface model; and obtaining the optimal mix proportion of the curing agent based on the expected value of each response amount. Under the condition of considering each index, the optimal mix proportion is found, and the overall performance and the construction effect are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of road engineering, and in particular relates to a method for determining the proportion of a steel slag-improved marine sludge solidifying agent based on a response surface methodology. Background Art

[0002] With the development of coastal port cities, the stockpile of marine dredged sludge has been increasing year by year, but the strength of marine dredged sludge is low and cannot be directly applied to engineering practice. At the same time, cities usually built on ports have developed steelmaking industries due to the import of iron ore. As solid waste discharged during the steelmaking process, the stockpile of steel slag occupies a large amount of land and affects the surrounding ecological environment. Steel slag has the characteristics of high strength and can be used as aggregate to improve marine dredged sludge, providing the possibility for large-scale resource comprehensive utilization of steel slag and marine dredged sludge.

[0003] At present, most of the research on the solidification technology of marine dredged mud is based on orthogonal experiments to seek the optimal ratio. However, the interaction between multiple factors makes the orthogonal experiment very labor-intensive. The systematic research on the physical parameters of steel slag, such as dosage and particle size, and the solidifying agent ratio of steel slag-modified marine dredged mud after the addition of steel slag is relatively weak.

[0004] In view of the large workload of multi-factor interactive solidification experiments on marine dredged sludge and the weak systematic research on physical parameters and the proportion of mixed soil sample solidifiers, there is an urgent need to provide a method for determining the proportion of steel slag-improved marine sludge solidifiers based on response surface methodology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes a method for determining the proportion of steel slag improved marine sludge solidifying agent based on response surface methodology to solve the problems existing in the above prior art.

[0006] To achieve the above object, the present invention provides a method for determining the proportion of a steel slag-improved marine sludge solidifying agent based on a response surface methodology, comprising the following steps:

[0007] Based on the optimal curing agent dosage of marine dredged sludge, an unconfined compressive strength test was conducted to obtain the optimal dosage range of each component of the curing agent;

[0008] In the optimal dosage range, the dosage of each component of the curing agent is taken as the main variable, and the 7d compressive strength and 14d compressive strength are taken as the response quantity, and the response value test results under different mix ratios are obtained;

[0009] Performing nonlinear fitting on the response value test results to establish a response surface model;

[0010] Based on the response surface model, the expected value of each response quantity is obtained in combination with the performance requirements of the mixed soil of marine dredged mud and waste steel slag;

[0011] Based on the expected values ​​of the various response quantities, the optimal mix ratio of the curing agent is obtained.

[0012] Optionally, the components of the curing agent include cement, lime and fly ash, wherein the optimal dosage range of cement is 4% to 8%, the optimal dosage range of lime is 6% to 10%, and the optimal dosage range of fly ash is 4% to 8%.

[0013] Optionally, the process of obtaining response value test results under different mix ratios includes: preparing a number of test specimens, sealing the test specimens and placing them in a standard curing box, and curing them to a predetermined age; within the variation range of the main variable, designing a number of groups of different main variable mix ratios, preparing the mixture according to the main variable mix ratios, and then testing and collecting the response quantity test results under different main variable mix ratios.

[0014] Optionally, the process of establishing the response quantity model includes: establishing a response surface model based on a quadratic polynomial equation, substituting the response value test results into the quadratic polynomial equation to obtain model regression equation coefficients, and then using variance to evaluate the effectiveness of the response surface model.

[0015] Optionally, the response surface model is expressed as follows:

[0016]

[0017] Where Y is the vector of the response test value, β i and β ij is the coefficient of the regression equation, x i and x j are the dosages of the ith and jth materials respectively, and q is the number of test values ​​of the main variable.

[0018] Optionally, the variance calculation formula for evaluating the effectiveness of the response surface model is:

[0019]

[0020] In the formula, is the variance of the ith response, M i is the average test result of the ith response quantity, X i1 is the first data in the test result of the ith response quantity, X i2 …X in Similarly, n is the number of responses, N i is the number of test results for the ith response quantity.

[0021] Optionally, the expected values ​​of the various response quantities include minimizing the expected values ​​of 7d compressive strength, 14d compressive strength and cement dosage.

[0022] Optionally, the optimal mix ratio of the curing agent is:

[0023] Q j =Q j1 ×T1+Q j1 ×T2+...+Q jk ×T k

[0024] In the formula, Q j is the optimal mix ratio of the jth raw material, Q j1 is the optimal mix ratio of the jth raw material relative to the first response amount, Q j2 …Q jk Similarly, T1 is the weight factor of the first response, T2…T k Similarly, k is the amount of raw materials.

[0025] Compared with the prior art, the present invention has the following advantages and technical effects:

[0026] The method for determining the curing agent mix ratio provided by the present invention can obtain the optimal dosage and particle size of waste steel slag and the optimal mix ratio of each component of the marine dredged mud and waste steel slag mixed soil curing agent, meet the general needs of road subgrade engineering, have a wide range of applications, reduce the number of cumbersome cross-tests, provide a simple method for the optimized preparation of marine dredged mud and waste steel slag, and help to improve the engineering benefits and efficiency in practical applications.

[0027] Through the method of the present invention, the 7d compressive strength and 14d compressive strength of marine dredged mud and waste steel slag solidified soil are used as indicators for multi-objective optimization, and the influence of factors such as cement content, lime content and fly ash content in the solidifying agent component is fully considered. The 7d compressive strength and 14d compressive strength of the mixed soil are optimized by the response surface method to determine the optimal content of each solidifying agent component. The error between the optimized theoretical mix ratio and the actual performance is small, which meets the general engineering needs of road subgrade engineering.

[0028] By optimizing the mix ratio using the method of the present invention, the optimized mix ratio of the waste steel slag particle size, the dosage and the curing agent component can be obtained, so that the mixed soil of marine dredged mud and waste steel slag has better controllability and operability during the construction process, and through the multi-objective optimization method, the optimal mix ratio can be found while considering various indicators, so that the mixed soil of marine dredged mud and waste steel slag can reach the best state in multiple performance indicators, thereby improving the overall performance and construction effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0030] Figure 1 A schematic flow chart of a method for determining a curing agent mix ratio according to an embodiment of the present invention;

[0031] Figure 2 This is a curve diagram showing the effect of different slag dosages and particle sizes on the friction angle over time under the freeze-thaw cycle in Example 2;

[0032] Figure 3 This is a curve diagram showing the effect of different slag dosages and particle sizes on time cohesion under freeze-thaw cycles in Example 2;

[0033] Figure 4 The response surface diagram of the interaction between cement and lime on the 7-day unconfined compressive strength of steel slag improved marine dredged mud stabilized soil;

[0034] Figure 5 The response surface diagram of the interaction between lime and fly ash on the 7-day unconfined compressive strength of steel slag-improved marine dredged mud stabilized soil;

[0035] Figure 6 The response surface diagram of the interaction between cement and lime on the 14-day unconfined compressive strength of steel slag-improved marine dredged mud stabilized soil;

[0036] Figure 7 The scatter plot is a comparison of the measured values ​​of the unconfined compressive strength of the steel slag improved marine dredged silt solidified soil at 7d and 14d.

[0037] Figure 8 This is the comparison error diagram of the predicted values ​​of the unconfined compressive strength of the steel slag improved marine dredged mud solidified soil at 7d and 14d;

[0038] Fig. 9 XRD pattern of steel slag improved marine dredged mud solidified soil. DETAILED DESCRIPTION

[0039] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0040] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0041] Embodiment 1

[0042] like Figure 1 As shown, in this embodiment, a method for determining the ratio of a steel slag modified marine sludge solidifying agent based on a response surface methodology is provided, comprising the following steps:

[0043] Step 1: Perform an unconfined compressive strength test under freeze-thaw cycles according to the optimal curing agent dosage of pure marine dredged mud to determine the optimal dosage and particle size of waste steel slag in marine dredged mud and steel slag mixed soil; Based on the response surface methodology, the test is conducted with the dosage of each component of the curing agent as the main variable, and the curing agent components include cement, lime and fly ash;

[0044] Furthermore, the solid components in the matrix of the mixed soil of marine dredged mud and waste steel slag include marine dredged mud, waste steel slag and water, wherein the marine dredged mud in this embodiment is marine dredged mud from the sludge dump of Qingdao Port in Shandong Province, with a particle size of less than 1.18 mm, and the waste steel slag comes from the steel slag dump of Qingdao Port.

[0045] Furthermore, the curing agent includes cement, lime and fly ash, wherein the cement is ordinary Portland cement, and the fly ash is waste fly ash piled up in Pingyin County, Jinan.

[0046] Furthermore, in step 1, the optimal dosage range of each main variable is obtained through a single factor gradient test. Through experiments, it can be determined that the dosage range of cement in the curing agent is 4% to 8%, the dosage of lime is 6% to 10%, and the dosage of fly ash is 4% to 8%.

[0047] Furthermore, in step 1, the optimal curing agent dosage of the marine dredged mud is obtained from existing experiments, and this experimental example will not be described in detail. The optimal curing agent dosage of the marine dredged mud is 6% cement, 8% lime, and 8% fly ash.

[0048] Step 2: Select the 7d compressive strength and 14d compressive strength of the mixed soil of marine dredged mud and waste steel slag as the response quantity, and collect the response value test results under different main variable mix ratios through experiments;

[0049] Furthermore, the specific process of the response volume test in step 2 is:

[0050] Prepare multiple specimens with a diameter of 39.1 mm, a height of 80 mm, and a compaction degree of 96%. After being sealed with sealing bags, place them in a standard curing box with a temperature of 14±1°C and a relative humidity of ≥90% and cure them to the predetermined age.

[0051] Furthermore, within the variation range of the main variable, 16 groups of different main variable mix ratios are designed, the mixtures are prepared according to the main variable mix ratios, and then the response quantity test data under different main variable mix ratios are tested and collected.

[0052] Step 3: Perform nonlinear fitting on the above test results, establish a regression equation, and use variance analysis to perform significance tests on each model of the established regression equation to evaluate its fitting accuracy and reliability;

[0053] Furthermore, the step of establishing a response surface model using the response quantity test data includes:

[0054] A quadratic polynomial equation is selected for mathematical modeling; the response quantity test data is substituted into the quadratic polynomial equation to obtain the model regression equation coefficient; variance analysis is used to evaluate the model validity and obtain a response surface model.

[0055] Furthermore, when the quadratic polynomial equation is used for mathematical modeling, the model form is as follows:

[0056]

[0057] Where Y is the vector of the response test value, β i and β ij is the coefficient of the regression equation, x i and x j are the dosages of the i-th and j-th materials, respectively, and q is the number of test values ​​of the main variable;

[0058] Create the following equation matrix:

[0059] Y'=Xβ+ε

[0060] Where Y' is an n×1 vector of the test values ​​of the response, n is the number of responses, β is an n×1 vector of parameters to be estimated, X is an n×p matrix of the main variables, p ≥ q, p is the number of terms in the model, and ε is an n×1 error vector with the following characteristics:

[0061] E(ε)=0,cov(εε')=σ 2 I n

[0062] Where E is the mathematical expectation of the vector, E(ε) is the mathematical expectation of the vector ε, cov is the covariance, ε' is the transposed vector of ε, cov(εε') is the covariance of the vector ε and the vector ε', σ 2 is the error variance, I n is the identity matrix.

[0063] Furthermore, the calculation formula for the variance of different responses as the main variable changes is:

[0064]

[0065] In the formula, is the variance of the ith response, M iis the average test result of the ith response quantity, X i1 is the first data in the test result of the ith response quantity, X i2 …X in Similarly, n is the number of responses, N i is the number of test results for the ith response quantity;

[0066] Then the weight factor T of the i-th response is i for:

[0067]

[0068] In the formula, is the variance of the first response, And so on.

[0069] Step 4: Determine the expected values ​​of the above-mentioned response quantities according to the performance requirements of the mixed soil of marine dredged mud and waste steel slag, and obtain the theoretical optimal mix ratio of the curing agent in combination with the expected values ​​of the response quantities.

[0070] Furthermore, the expected values ​​of the various response quantities in step 4 include 7d compressive strength, 14d compressive strength, and the expected value of cement dosage is minimized.

[0071] Furthermore, the final optimized mix ratio of the curing agent is:

[0072] Q j =Q j1 ×T1+Q j1 ×T2+...+Q jk ×T k

[0073] In the formula, Q j is the final optimized mix ratio of the jth raw material, Q j1 is the optimal mix ratio of the jth raw material relative to the first response amount, Q j2 …Q jk Similarly, T1 is the weight factor of the first response, T2…T k Similarly, k is the amount of raw materials.

[0074] Embodiment 2

[0075] This embodiment provides a method for determining the proportion of a steel slag modified marine sludge solidifying agent based on a response surface methodology, comprising the following steps:

[0076] Step 1: Through the unconfined compressive strength test under freeze-thaw cycles, the optimal curing agent ratio of marine dredged mud is added to determine the optimal particle size and dosage of waste steel slag in the mixture of marine dredged mud and waste steel slag. The number of freeze-thaw cycles is set to 0, 1, 3, and 6 times.

[0077] The solid components in the matrix of the mixed soil of marine dredged mud and waste steel slag include marine dredged mud, waste steel slag and water, wherein the marine dredged mud is marine dredged mud from the silt dump of Qingdao Port, Shandong Province, and the particle size is less than 1.18 mm. The proportions of each matrix are shown in Table 1 below:

[0078] Table 1

[0079]

[0080] The three selected curing agent components include cement, lime and fly ash, among which the cement is ordinary Portland cement and the fly ash comes from Pingyin County, Jinan City.

[0081] The single factor gradient test is used to obtain the optimal dosage range of each main variable. The single factor gradient test is an experimental method to determine the influence of a single factor in a model on the output. It is usually used to evaluate the sensitivity of the factor to the model gradient. This technology is a prior art and will not be described in detail in this embodiment. Through experiments, it can be determined that the dosage range of cement in the curing agent is 4% to 8%, the dosage of lime is 6% to 10%, and the dosage of fly ash is 4% to 8%.

[0082] The optimal curing agent dosage test for marine dredged mud is obtained from existing experiments, and this experimental example will not be described in detail. The optimal curing agent dosage for marine dredged mud is 6% cement, 8% lime, and 8% fly ash. The test results of the above test are shown in Table 2 below:

[0083] Table 2

[0084]

[0085] According to the test results, the unconfined compressive strength of the specimen under freeze-thaw cycles increases with the decrease of steel slag particle size and dosage, and the strength changes of steel slag with particle sizes of 0-1.18mm and 1.18-2.36mm are similar at the same dosage. Based on economic considerations, the largest possible steel slag is used, so the optimized steel slag dosage is 30% and the particle size is 1.18-2.36mm.

[0086] Figure 2 and Figure 3 The internal friction angle and cohesion change curves obtained by direct shear test of the above steel slag improved marine dredged mud are as follows: Figure 2 It can be seen that the internal friction angle of the specimen is the largest when the steel slag content is 30% and the particle size is 1.18mm-2.36mm, indicating that the addition of steel slag with this particle size content can better change the particle size distribution of marine dredged mud, making the dredged mud particles in closer contact, and the bite, friction and rolling effects between steel slag and dredged mud particles, between dredged mud particles and between steel slag are stronger. Figure 3It can be seen that the cohesion of the specimens mixed with steel slag with a dosage of 30% and a particle size of 1.18mm to 2.36mm is slightly higher than that of the specimens mixed with other steel slags.

[0087] Based on this, it can be determined that the optimal dosage and particle size of steel slag for improved marine dredged mud are 30%, 1.18mm~2.36mm.

[0088] Step 2: Select the 7d compressive strength and 14d compressive strength of the mixture of marine dredged mud and waste steel slag as the response quantity, and collect the response value test results under different main variable mix ratios through experiments. Specifically:

[0089] The Box-Behnken Design (BBD) experimental design scheme in the response surface methodology was adopted, as shown in Table 3 below, including the BBD experimental influencing factors and levels coded as A, B, and C:

[0090] Table 3

[0091]

[0092] By changing the dosage of each curing agent component, multiple actual tests were carried out, and the response value test results under different main variable mix ratios were collected, as shown in Table 4:

[0093] Table 4

[0094]

[0095]

[0096] The 7d compressive strength and 14d compressive strength of the mixed soil of the above-mentioned marine dredged mud and waste steel slag are used as response quantities to carry out different test tests respectively. The test process includes:

[0097] (1) The specific process of 7d compressive strength is:

[0098] According to the requirements of unconfined compressive strength test pieces, specimens with a diameter of 39.1 mm and a height of 80 mm were prepared. The specimens were divided into 7 groups, with 3 parallel samples in each group. After curing for 7 days, the specimens that reached the age were taken out for testing.

[0099] (2) The specific process of 14d compressive strength is:

[0100] According to the requirements of unconfined compressive strength test pieces, specimens with a diameter of 39.1 mm and a height of 80 mm were prepared. The specimens were divided into 7 groups, with 3 parallel samples in each group. After curing for 14 days, the specimens that reached the age were taken out for testing.

[0101] Through the above experiments, the response surface test results collected under different main variable combinations are shown in Table 5 below:

[0102] Table 5

[0103]

[0104]

[0105] The experimental results of step 2 above are subjected to nonlinear fitting, and a quadratic polynomial regression equation is established by selecting different quadratic polynomial regression models in order to better fit the data and solve the problem.

[0106] The experimental data were fitted with a quadratic polynomial regression, and the significance test and variance results of each coefficient were obtained as shown in Table 6.

[0107] Table 6

[0108]

[0109] A second-order empirical model between the distribution ratio of each curing agent group and the unconfined compressive strength is established. The model can be described as:

[0110]

[0111] In the formula, Y is the predicted response value, β0 is the intercept, and β i is the linear coefficient, β ij is the interaction coefficient, β ii is the square coefficient; k is the number of factors, and in this experiment k=3.

[0112] The regression equations obtained according to the coding factors are shown as follows:

[0113]

[0114] The regression equations obtained according to the actual coefficients are shown as follows:

[0115] Y 7d =-7.235+0.871×cement+1.033×lime+0.671×fly ash+0.106×cement×lime

[0116] +0.013×cement×fly ash+0.106×lime×fly ash-0.151×cement 2 -0.133 × lime 2 -0.126×Fly ash 2 ,

[0117] Y 14d =-10.728+1.523×cement+1.311×lime+0.804×fly ash+0.131×cement×lime-0.019×cement×fly ash+0.050×lime×fly ash-0.199×cement2 -0.130 × Lime 2 -0.093×Fly ash 2 .

[0118] Figure 4 , Figure 5 and Figure 6 They are the response surface diagram of the interaction between cement and lime on the 7-day unconfined compressive strength of steel slag improved marine dredged mud stabilized soil, the response surface diagram of the interaction between lime and fly ash on the 7-day unconfined compressive strength of steel slag improved marine dredged mud stabilized soil, and the response surface diagram of the interaction between cement and lime on the 14-day unconfined compressive strength of steel slag improved marine dredged mud stabilized soil.

[0119] according to Figure 4 and Figure 6 The unconfined compressive strength of the steel slag improved marine dredged mud solidified soil at 7d and 14d increased first and then decreased with the increase of cement and lime content, while the highest peak compressive strength of the solidified soil at 14d increased by about 26.8% compared with that at 7d. This is because with the increase in age, the hydration reaction of the components in the solidified soil is more complete, generating more CAH hydration products, and the filling effect on the gaps in the solidified soil is more significant, thereby improving the compressive strength. At the same time, the highest point of the 14d compressive strength model of the 14d specimen with a lime content of 10% appeared in the range of 7% to 8% cement, which was about 1% higher than the position where the highest point of the 7d compressive strength model appeared (in the range of 6% to 7%), and the position where the highest point of the 7d model and the highest point of the 14d model appeared when the lime content was 6% also had a similar effect (increasing from about 5% cement content to the range of 5% to 6%). It can be inferred that with the increase of curing age, hydration reaction, carbonation reaction and volcanic ash reaction continue, and the later strength growth of steel slag improved marine dredged mud will consume more curing agent components, thereby increasing the curing agent content at the highest point of the compressive strength model.

[0120] according to Figure 5 The 7d unconfined compressive strength of steel slag improved marine dredged mud stabilized soil increases first and then decreases with the increase of lime and fly ash content. The reason is similar to the interaction between lime and cement, both of which increase the alkalinity and calcium content of the reaction system to increase the generation rate and amount of CAH.

[0121] Figure 7 It is the predicted value and true value diagram of the 7d and 14d specimens of steel slag improved marine dredged mud. The predicted value of the unconfined compressive strength is the inclined straight line in the diagram, while the actual value of the unconfined compressive strength is always distributed around the inclined straight line.

[0122] Figure 8is the external studentized residual diagram of the 7d and 14d specimens of steel slag modified marine dredged mud. Figure 8 It can be seen that the maximum error between the measured and predicted values ​​of the 7d and 14d compressive strength of steel slag improved marine dredged mud solidified soil is 3.795%, indicating that the optimized response surface model has a high accuracy.

[0123] pass Figure 7 and Figure 8 It can be seen that the mix ratio determination model provided in this embodiment has high accuracy.

[0124] Fig. 9 The XRD analysis comparison diagram of the steel slag improved marine dredged mud sample and the steel slag improved marine dredged mud solidified soil sample shows that at 2θ=23.21°, 26.67°, and 27.95°, the XRD spectrum of the solidified soil shows the newly added diffraction peaks of hydrated silicate (CSH) and hydrated aluminosilicate (C-(A)-SH). At 2θ=40.23° and 44.23°, the XRD spectrum of the solidified soil shows the newly added diffraction peaks of hydrated aluminate (CAH). These observations confirm the generation of hydration products such as CAH, CSH, and C-(A)-SH during the solidification process.

[0125] Step 4: According to the performance requirements of the mixed soil of marine dredged mud and waste steel slag, the expected values ​​of each response quantity, including the 7d compressive strength and 14d compressive strength, are expected to be maximized, while the cement content is expected to be minimized. Based on the above expected values ​​of the response quantities, the theoretical optimal mix ratio is obtained by the response surface method, where the predicted optimal mix ratio is: cement 5.604%; lime 10.000%; fly ash 7.962%. This ratio is the optimal mix ratio of the curing agent in this application.

[0126] Example 3

[0127] Different from Example 2, the mass proportion of cement in this example is 6.530%, the mass proportion of lime is 9.375%, and the mass proportion of fly ash is 6.672%. This ratio is the optimal ratio of the curing agent in this application.

[0128] Example 4

[0129] Different from Example 2, the mass proportion of cement in this example is 7.547%, the mass proportion of lime is 10.000%, and the mass proportion of fly ash is 7.998%. This ratio is the optimal ratio of the curing agent in this application.

[0130] Example 5

[0131] Different from Example 2, the mass proportion of cement in this example is 5.493%, the mass proportion of lime is 9.448%, and the mass proportion of fly ash is 5.259%. This ratio is the optimal ratio of the curing agent in this application.

[0132] Example 6

[0133] Different from Example 2, the mass proportion of cement in this example is 5.089%, the mass proportion of lime is 7.580%, and the mass proportion of fly ash is 7.197%. This ratio is the optimal ratio of the curing agent in this application.

[0134] Example 7

[0135] Different from Example 2, the mass proportion of cement in this example is 5.021%, the mass proportion of lime is 7.109%, and the mass proportion of fly ash is 4.770%. This ratio is the optimal ratio of the curing agent in this application.

[0136] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for determining the proportion of steel slag-improved marine sludge solidifying agent based on response surface methodology, characterized in that: The following steps are involved: Based on the shear strength test of waste steel slag improved marine dredged mud under freeze-thaw cycles, the optimal solidifying agent dosage of marine dredged mud was determined; Based on the optimal curing agent dosage of marine dredged sludge, an unconfined compressive strength test was conducted to obtain the optimal dosage range of each component of the curing agent; In the optimal dosage range, the dosage of each component of the curing agent is taken as the main variable, and the 7d compressive strength and 14d compressive strength are taken as the response quantity, and the response value test results under different mix ratios are obtained; Performing nonlinear fitting on the response value test results to establish a response surface model; Based on the response surface model, the expected value of each response quantity is obtained in combination with the performance requirements of the mixed soil of marine dredged mud and waste steel slag; Based on the expected values ​​of the various response quantities, the optimal mix ratio of the curing agent is obtained.

2. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 1, characterized in that: The components of the curing agent include cement, lime and fly ash, wherein the optimal mixing amount of cement is 4% to 8%, the optimal mixing amount of lime is 6% to 10%, and the optimal mixing amount of fly ash is 4% to 8%.

3. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 1, characterized in that: The process of obtaining the response value test results under different mix ratios includes: preparing a number of test pieces, sealing the test pieces and placing them in a standard curing box, and curing them to a predetermined age; within the variation range of the main variable, designing a number of groups of different main variable mix ratios, preparing the mixture according to the main variable mix ratios, and then testing and collecting the response quantity test results under different main variable mix ratios.

4. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 1, characterized in that: The process of establishing the response quantity model includes: establishing a response surface model based on a quadratic polynomial equation, substituting the response value test results into the quadratic polynomial equation, obtaining the model regression equation coefficients, and then using variance to evaluate the effectiveness of the response surface model.

5. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 4, characterized in that: The response surface model is formulated as follows: Where Y is the vector of the response test value, β i and β ij is the coefficient of the regression equation, x i and x j are the dosages of the ith and jth materials respectively, and q is the number of test values ​​of the main variable.

6. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 1, characterized in that: . The variance calculation formula for evaluating the effectiveness of the response surface model is: In the formula, is the variance of the ith response, M i is the average test result of the ith response quantity, X i1 is the first data in the test result of the ith response quantity, X i2 …X in Similarly, n is the number of responses, N i is the number of test results for the ith response quantity.

7. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 1, characterized in that: The expected values ​​of various response quantities include minimization of the expected values ​​of 7d compressive strength, 14d compressive strength and cement dosage.

8. The method for determining the ratio of steel slag-improved marine sludge solidifying agent based on response surface methodology according to claim 1, characterized in that: The optimal mix ratio of curing agent is: Q j =Q j1 ×T1+Q j1 ×T2+...+Q jk ×T k In the formula, Q j is the optimal mix ratio of the jth raw material, Q j1 is the optimal mix ratio of the jth raw material relative to the first response amount, Q j2 …Q jk Similarly, T1 is the weight factor of the first response, T2…T k By analogy, k is the quantity of raw materials.

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