A method for mix proportion design of alkali slag-containing multi-solid waste iron tailings powder clsm

Abstract

The application discloses a kind of containing alkali residue multi-solid waste iron tailings powder CLSM mix design method, according to preset CLSM performance target, water solid ratio W / S, glue bone ratio C / A and waste glue ratio SWC / C are obtained by adjusting, fitting model based on CLSM liquidity response and based on 28 days compressive strength response are established, according to the value range of water solid ratio W / S is determined according to CLSM liquidity target requirement;According to the minimum compressive strength and maximum compressive strength of the specific day compressive strength target requirement of CLSM, the value range of glue bone ratio C / A is determined;With SWC / C maximum value as optimization goal, the value of final W / S, C / A and SWC / C is obtained;The method solves the problem of low efficiency and high cost of traditional trial-and-error method, realizes the scientization and standardization of CLSM mix design.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of concrete engineering, in particular to a method for designing a mixture ratio of a CLSM containing alkali slag and multiple solid wastes and iron tailings powder. BACKGROUND

[0002] Cement costs account for 74%-80.8% of the cost of controllable low-strength material (CLSM) backfilling, so the cost optimization of CLSM filling technology needs to reduce the proportion of cement without affecting the performance; a solid waste cementitious material is used to replace part of the cement to prepare a multiple solid waste iron tailings powder CLSM.

[0003] The mixture ratio design of the multiple solid waste CLSM minimizes the cement dosage and maximizes the iron tailings powder dosage under the premise of meeting the performance requirements of the CLSM; however, due to the wide range of sources of raw materials for the CLSM and the large differences in performance, and the characteristics of the CLSM requiring large fluidity, low bleeding rate, and controllable strength, the working performance, mechanical properties, and economy of the CLSM need to be comprehensively balanced, so the mixture ratio design of the CLSM is a very complex process.

[0004] At present, the CLSM is still in the research stage and has not been widely applied, especially in China, the research is still in the initial stage, and there is no specification or standard for the mixture ratio of the CLSM, the mixture ratio of the CLSM is mainly completed through trial and error and repeated tests until a mixture ratio that meets the performance requirements is obtained, obviously the trial and error method has low test efficiency, therefore, an efficient CLSM mixture ratio design method is needed. SUMMARY

[0005] The present application establishes a response surface model of fluidity and compressive strength, takes the water-solid ratio (W / S), the cement-aggregate ratio (C / A), and the waste cement ratio (SWC / C) as the key variables, determines the parameter optimization range according to the preset performance target (such as fluidity ≥180mm, 28-day compressive strength 0.7-2.1MPa), and finally solves the optimal mixture ratio through nonlinear programming; solves the problems of low efficiency and high cost of the traditional trial and error method, and realizes the scientific and standardized purposes of the CLSM mixture ratio design.

[0006] To achieve the above purpose, the present application provides a method for designing a mixture ratio of a CLSM containing alkali slag and multiple solid wastes and iron tailings powder, adjusts the best water-solid ratio W / S, cement-aggregate ratio C / A, and waste cement ratio SWC / C according to a preset CLSM performance target, and the preset CLSM performance target includes a CLSM fluidity target requirement and a CLSM compressive strength target requirement.

[0007] The method comprises the following steps:

[0008] Step S1, according to historical multi-solid waste iron tailings powder CLSM mixing proportion data, a first fitting model based on CLSM liquidity response and a second fitting model based on 28-day compressive strength response are established, and the response factors of the fitting model are: water-solid ratio W / S, cement-aggregate ratio C / A and waste rubber-cement ratio SWC / C.

[0009] Step S2, according to the target requirement of CLSM liquidity, the value range of water-solid ratio W / S is determined through the first fitting model; when the target requirement of CLSM liquidity is greater than or equal to 180 mm (in order to obtain higher strength, less cement dosage is used), the cement-aggregate ratio is taken as the initial value C / A=0.13 and the waste rubber-cement ratio is taken as the initial value SWC / C=0.5, and the minimum value allowed for water-solid ratio W / S is obtained; when the target requirement of CLSM liquidity is greater than or equal to 200 mm (in order to expand the value range of W / S), the cement-aggregate ratio is taken as the maximum initial value C / A=0.2 and the waste rubber-cement ratio is taken as the minimum initial value SWC / C=0.2, and the minimum value allowed for W / S is calculated through the first fitting model.

[0010] Step S3, according to the minimum compressive strength and the maximum compressive strength of the specific number of days of CLSM compressive strength target requirement, the value range of cement-aggregate ratio C / A is determined; when the 28-day compressive strength target requirement is set as the minimum compressive strength, the value of W / S is taken as the minimum value allowed for W / S calculated through the first fitting model, and the value of SWC / C is taken as the maximum initial value SWC / C=0.8, and the minimum value allowed for cement-aggregate ratio C / A is obtained through the second fitting model; when the 28-day compressive strength target requirement is set as the maximum compressive strength, the value of W / S is taken as the maximum initial value W / S=0.37, and the value of SWC / C is taken as the minimum initial value SWC / C=0.2, and the maximum value allowed for cement-aggregate ratio C / A is obtained through the second fitting model.

[0011] Step S4, according to the first fitting model, the value range of W / S obtained in step S2, the value range of cement-aggregate ratio C / A obtained in step S3, and the constraint condition of 0.2≤SWC / C≤0.8, the maximum value of SWC / C is taken as the optimization target, and the values of W / S, C / A and SWC / C are obtained.

[0012] Further, the specific expression of the first fitting model based on the liquidity response of CLSM is:

[0013]

[0014] wherein, represents the liquidity value, i.e. the flow spread, and the unit is mm; 、 and respectively represent water-solid ratio W / S, cement-aggregate ratio C / A and solid waste cement ratio SWC / C.

[0015] Further, the initial value range of W / S is 0.30-0.37, the initial value range of C / A is 0.06-0.2, and the initial value range of SWC / C is 0.2-0.8.

[0016] Further, the expression of the second fitting model responding to the 28-day compressive strength is:

[0017]

[0018] wherein, is the 28-day compressive strength value, and the unit is MPa.

[0019] Further, the specific process of establishing the fitting model comprises:

[0020] Collecting no less than 20 groups of historical multiple solid waste iron tailings powder CLSM mix proportion test data, each group of data including water-solid ratio W / S, cement-aggregate ratio C / A, solid waste cement ratio SWC / C and corresponding fluidity test results and 28-day compressive strength test results; adopting response surface analysis method, taking W / S, C / A and SWC / C as independent variables, and taking fluidity and 28-day compressive strength as dependent variables, a quadratic polynomial regression model is established.

[0021] Significance test is performed on the established fitting model, and the correlation coefficients of the first fitting model and the second fitting model are required to be all greater than 0.85, and the value is less than 0.05.

[0022] Further, the nonlinear programming method is used to obtain the values of W / S, C / A and SWC / C corresponding to the maximum value of SWC / C under all constraint conditions, that is, the optimal water-solid ratio W / S, cement-aggregate ratio C / A and solid waste cement ratio SWC / C; and the proportions of water and solid, cementitious material and aggregate, and solid waste cementitious material and cementitious material are proportioned according to the optimal water-solid ratio W / S, cement-aggregate ratio C / A and solid waste cement ratio SWC / C.

[0023] Compared with the prior art, the beneficial effects of the present application are:

[0024] The present application replaces the traditional trial-and-error method with mathematical models and nonlinear programming, greatly shortens the mix proportion design cycle, maximizes the solid waste cementitious material (SWC) content, reduces the cement cost, and ensures the reliability of the fluidity and strength prediction based on the fitting model of the response surface analysis; promotes the resource utilization of iron tailings powder and other industrial solid wastes, and reduces the environmental burden. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A diagram of independent parameters for CLSM mix proportion design of the application;

[0026] Figure 2 A flowability disturbance analysis result diagram of the CLSM of the application;

[0027] Figure 3 A disturbance analysis diagram of the 28-day compressive strength of the CLSM of the application. DETAILED DESCRIPTION

[0028] To make the objectives, technical solutions and advantages of the application clearer, the technical solutions in the application are clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0029] As shown in Figure 1 A diagram of independent parameters for CLSM mix proportion design of the application, the performance of the CLSM is affected by factors such as the change of the amount of a single component, the type and amount of mineral admixtures and additives. When a single component changes or mineral admixtures are added, the mutual ratio between the corresponding components changes. In addition, the flowability of the CLSM is mainly affected by the proportion of solid admixture, and the compressive strength of the CLSM is mainly affected by the proportion of cementitious material. Therefore, the ratio of mixing water to solid (water-solid ratio, W / S), the ratio of cementitious material to aggregate (cement-aggregate ratio, C / A) and the ratio of solid waste cementitious material to cementitious material (waste cement ratio, SWC / C) are used as the mix proportion design factors, and these parameters can be adjusted independently.

[0030] A method for mix proportion design of a CLSM containing alkali residue and multi-solid waste iron tailings powder, the best water-solid ratio W / S, cement-aggregate ratio C / A and waste cement ratio SWC / C are obtained by adjustment according to a preset CLSM performance target, and the preset CLSM performance target includes a CLSM flowability target requirement and a CLSM compressive strength target requirement.

[0031] The method comprises the following steps:

[0032] In step S1, a first fitting model based on the response of CLSM flowability and a second fitting model based on the response of 28-day compressive strength are established according to historical multi-solid waste iron tailings powder CLSM mix proportion data, and the response factors of the fitting models are the water-solid ratio W / S, the cement-aggregate ratio C / A and the waste cement ratio SWC / C.

[0033] The expected model of the test design and the suggested model of the data analysis are both Quadratic, so a square polynomial model is used for fitting, and the variance analysis result is shown in Table 1. In the table, X1, X2, X3 are the encoding values of the parameters W / S, C / A, SWC / C.

[0034] Table 1 Variance analysis and fitting statistical information table of flowability optimization model

[0035]

[0036] Determination coefficient =0.9898; Corrected determination coefficient =0.9824; Predictive determination coefficient =0.9533; Standard deviation = 7.99; Coefficient of variation C.V. = 4.91%; Signal-to-noise ratio = 40.879; The larger the F value is, the smaller the P value is, and the more significant the model term is. In the table, the model significance test F = 133.69, P < 0.0001, which indicates that the regression model is extremely significant, and the fitting precision is good, so the response surface approximation model can be used for subsequent optimization design. In the test of lack of fit, F = 1.36, P = 0.3752, and the P value is greater than 0.05, which is not significant, indicating that the simulation of the optimization model is consistent with the test results, and can reflect the relationship between flowability and each relative proportion parameter.

[0037] Error analysis is performed on the results of the 6 repeated center point tests, and the determination coefficient R 2 =0.9898 of the model is close to 1, which indicates that the test model is well fitted with the actual test, and about 98.98% of the results in the actual test can be explained by the fitted model. The corrected determination coefficient = 0.9824, and the predictive determination coefficient = 0.9533, and the difference between them is less than 0.2, which indicates that the model has sufficient accuracy and universality, and can fully reflect the change rule of flowability. The coefficient of variation = 4.91% is less than 10%, which indicates that the non-test factors have little effect on the results, the model has good test stability, and the test has high reliability and precision.

[0038] The signal-to-noise ratio refers to the ratio of the range of the design point prediction value to the average prediction error. The higher the signal-to-noise ratio, the stronger the signal relative to the noise, and the better the reliability and stability of the test results. When the signal-to-noise ratio is greater than 4, it indicates that the test results have high reliability and stability, and the model can be used to analyze and predict the test results reliably. The signal-to-noise ratio of the model is 37.8576, thus meeting the requirements. In summary, the model can be used to analyze and predict the influence of the relative ratio parameters on the flow performance of the multi-solid waste iron tailings powder CLSM slurry. The P value of the first-order term X1, X2, the interaction term X1X2 and the quadratic term 2X1 in the model term is less than 0.01, indicating that the influence on the flow performance of CLSM is extremely significant, and other factors are not significant. According to the F value, the order of factors affecting the flow performance of CLSM is: W / S > C / A > SWC / C; since the coefficient of X3 is negative, it indicates that the increase of SWC / C will adversely affect the flowability of CLSM, and the coefficients of the quadratic interaction terms X1X3 and X2X3 combined with X3 are both negative.

[0039] The specific expression of the first fitting model based on the flowability response of CLSM obtained finally is:

[0040]

[0041] wherein, represents the flowability value, i.e. the flow spread, with the unit of mm; , and respectively represent the water-solid ratio W / S, the cement-aggregate ratio C / A and the waste rubber ratio SWC / C.

[0042] The initial value range of W / S is 0.30-0.37, the initial value range of C / A is 0.06-0.2, and the initial value range of SWC / C is 0.2-0.8.

[0043] The disturbance analysis result of the flowability of CLSM is shown in Figure 2 The horizontal coordinate axis in the figure represents the variation range of each factor in the test space, and the 0.000 point is the middle value of the three factors, i.e. W / S=0.335, C / A=0.13 and SWC / C=0.5.

[0044] The slope of the disturbance curve X1(W / S) is the largest, and it presents a weak quadratic relationship curve, indicating that as the W / S factor increases, the response value increases, especially when W / S>0.335, the degree of increase in flowability is significantly improved. A small change in W / S will result in a large change in the response variable, and the W / S factor is very sensitive to the flow performance. The slope of the disturbance curve X2(C / A) is the second, and as the C / A increases, the flow performance of CLSM increases.

[0045] The slope of the disturbance curve X3 (SWC / C) is the smallest, negative and close to a straight line, indicating that the flow performance of CLSM almost linearly decreases with the increase of SWC / C. The size order of the slope of the disturbance curve is consistent with the size order of the three main effect coefficients of the encoding value formula, and the slope of the disturbance curve X3 is negative, indicating that the increase of SWC / C has an adverse effect on the flowability.

[0046] W / S has a significant effect on the flowability and is positively correlated, the main reason is that water plays the role of lubricant in CLSM mixture, increasing the water-solid ratio can form more lubricating layers between solid particles, reduce the friction between particles, thereby improving the flowability of the mixture; the increase of water-solid ratio can enhance the capillary action, so that water can more effectively fill the gap between solid particles, thereby improving the overall flowability of the mixture; the increase of water-solid ratio will lead to the increase of the distance between solid particles, the interaction force between particles is weakened, which helps to improve the flowability of the slurry; in addition, the addition of water will reduce the viscosity of CLSM mixture, the lower the viscosity, the easier the slurry flows.

[0047] It should be noted that the disturbance curve X1 is the response change in the range of 0.3≤W / S≤0.37, when W / S exceeds this range, the flowability of CLSM is not infinitely increased or decreased, when W / S is less than a certain value, the CLSM mixture cannot flow due to lack of water lubrication and transportation, when W / S is greater than a certain value, the CLSM causes serious water excretion due to excessive water, and the solid in the mixture cannot flow with water. Therefore, in practical application, it is necessary to reasonably control the water-solid ratio according to the specific engineering requirements and material properties.

[0048] C / A is positively correlated with flowability, but its effect on flowability is less significant than W / S. The mechanism of C / A affecting flowability is that cementitious materials are mixed with water to form cementitious slurry, which has a certain flowability, and the increase of the proportion of cementitious materials increases the amount of cementitious slurry, which helps to improve the flowability of the whole CLSM mixture. The cementitious slurry has adhesion and can wrap and lubricate the iron ore tailings powder particles, increasing the distance between the iron ore tailings powder particles and reducing the frictional resistance between the particles, thereby improving the flowability.

[0049] SWC / C is negatively correlated with flowability, and with the increase of the proportion of full-solid waste cementitious materials, the flowability of CLSM shows a weak downward trend. The main reasons are as follows: the particle size distribution and particle size of full-solid waste cementitious materials are different from cement, the specific surface area of full-solid waste cementitious materials is 333.5m 2 / kg, and the specific surface area of cement is 372.6m 2 / kg, the particles of the all-solid waste cementitious material are relatively coarse, which reduces the lubrication between particles and thus reduces the fluidity of the mortar; the hydration activity of cement is higher than that of the all-solid waste cementitious material, and cement can hydrate rapidly in the early stage, forming more hydration products. These products can effectively coat and lubricate the iron tailings powder particles, which helps to improve the fluidity and workability of CLSM; the all-solid waste cementitious material contains 5% alkali residue, which increases the alkali content in the mixture and may accelerate the hydration reaction of cement, especially the reaction with tricalcium silicate C3A, thereby causing false setting and adversely affecting the fluidity of CLSM.

[0050] As shown by disturbance curve X3, the change in the SWC / C factor has a very small impact on the fluidity of CLSM. This is because both solid waste cementitious materials and cement are cementitious materials, and their physical properties, such as density and specific surface area, are relatively similar. Therefore, the fluidity of CLSM is less affected by changes in the SWC / C factor. The slopes of the three curves indicate that the significance of the W / S main effect is greater than that of the C / A main effect, which is greater than that of the SWC / C main effect. Therefore, W / S is the main factor affecting the fluidity of CLSM.

[0051] Collect no fewer than 20 sets of historical CLSM mix proportion test data of multi-solid waste iron tailings powder. Each set of data includes water-to-solid ratio (W / S), binder-to-aggregate ratio (C / A), waste binder-to-aggregate ratio (SWC / C), and corresponding flowability test results and 28-day compressive strength test results. Use response surface methodology to establish a quadratic polynomial regression model with W / S, C / A, and SWC / C as independent variables and flowability and 28-day compressive strength as dependent variables, respectively.

[0052] A significance test is performed on the established fitting model, requiring the correlation coefficient between the first fitting model and the second fitting model to be considered. All are not less than 0.85, and The value is less than 0.05.

[0053] Multivariate fitting and variance analysis were performed on the measured values ​​of 28-day compressive strength. The expression of the second fitting model for the 28-day compressive strength response was finally obtained as follows:

[0054]

[0055] in, This is the compressive strength value at 28 days, in MPa.

[0056] The perturbation analysis diagram of the 28-day compressive strength of CLSM is shown below. Figure 3As shown, the influence of W / S on 28-day compressive strength is similar to that on 3-day and 7-day compressive strength, and has a weak negative correlation effect. When W / S increases from 0.3 to 0.37, the predicted value of compressive strength of CLSM decreases from 3.44 MPa to 2.55 MPa, decreasing by 25.83%. The influence of C / A on 28-day compressive strength is similar to that on 7-day strength. When W / S = 0.335, SWC / C = 0.5, and C / A increases from 0.06 to 0.2, the predicted value of 28-day compressive strength increases from 1.11 MPa to 5.07 MPa, increasing by 356.75%. The increase rate is smaller than that of 3-day and 7-day strength, because the hydration reaction of cementitious materials occurs faster in the early stage, and the hydration rate of cementitious materials slows down with the increase of age. With the increase of SWC / C, the 28-day compressive strength of CLSM shows a trend of first slowly decreasing and then increasing. When SWC / C increases from 0.2 to 0.8, the predicted value of compressive strength of CLSM increases from 3.11 MPa to 3.66 MPa, increasing by 17.74%. The growth rate is larger than that of 7-day strength, indicating that the hydration rate of solid waste cementitious materials is slower, which can significantly improve the late strength of CLSM. For CLSM with excavation requirements, attention should be paid to the contribution of solid waste cementitious materials to the late strength. By comparing the above three main effects, it can be seen that factors C / A and SWC / C are positively correlated with 28-day compressive strength, and factor W / S is negatively correlated with 28-day compressive strength. The significance of the three factors is C / A > W / S > SWC / C in turn.

[0057] In step S2, the value range of water-solid ratio W / S is determined according to the target requirement of flowability of CLSM. When the target requirement of flowability of CLSM is greater than or equal to 180 mm (a smaller amount of cement is used to obtain higher strength), the cement-bone ratio is taken as the initial value C / A = 0.13, the waste cement ratio is taken as the initial value SWC / C = 0.5, and the minimum value of water-solid ratio W / S allowed is obtained. When the target requirement of flowability of CLSM is greater than or equal to 200 mm (to expand the value range of W / S), the cement-bone ratio is taken as the maximum initial value C / A = 0.2, the waste cement ratio is taken as the minimum initial value SWC / C = 0.2, and the minimum value of W / S allowed is calculated by the first fitting model.

[0058] Generally, the flowability of CLSM should be greater than 200 mm, and the 28-day compressive strength of CLSM should be less than 2.1 MPa after hardening for excavation. Therefore, the lower limit of the optimization target of flowability is set to 200 mm, the upper limit of the optimization target of 28-day strength is set to 2.1 MPa, and the optimization target of 3-day and 7-day strength is set to be empty, i.e., not as an optimization target.

[0059] According to the CLSM flowability test results, W / S has a significant effect on flowability, therefore, according to the CLSM flowability target setting requirements, the value range of W / S is preliminarily determined. In order to obtain higher strength, when a smaller amount of cement is used, the flowability requirement is greater than or equal to 180 mm, the C / A and SWC / C value settings are the middle values, that is, C / A = 0.13 and SWC / C = 0.5, so that the value range of W / S is determined:

[0060] .

[0061] In order to expand the value range of W / S, the C / A value setting is set to a high level, that is, 0.2, and the SWC / C value setting is set to a low level, that is, 0.2, and the CLSM flowability requirement is greater than or equal to 200 mm as the design target, and the minimum ratio of W / S allowed is 0.3402.

[0062] Step S3, according to the minimum compressive strength and the maximum compressive strength of the specific number of days of CLSM compressive strength target requirements, the value range of cement-aggregate ratio C / A is determined; when the 28-day compressive strength target requirement is set as the minimum compressive strength, the value of W / S is the minimum value allowed by W / S calculated by the first fitting model, and the value of SWC / C is the maximum initial value SWC / C = 0.8, and the minimum value of cement-aggregate ratio C / A allowed is obtained by the second fitting model; when the 28-day compressive strength target requirement is set as the maximum compressive strength, the value of W / S is the maximum initial value W / S = 0.37, and the value of SWC / C is the minimum initial value SWC / C = 0.2, and the maximum value of cement-aggregate ratio C / A allowed is obtained by the second fitting model.

[0063] According to the CLSM compressive strength target setting requirements, the value range of C / A is preliminarily determined, and the content of cementitious materials is reduced as much as possible to reduce the cost. It is assumed that the 28-day compressive strength requirement of CLSM in step S2 is greater than or equal to 0.7 MPa and less than or equal to 2.1 MPa. According to the analysis results of the influence of the main effect of each parameter on the 28-day compressive strength of CLSM, the value range of C / A is expanded, and when the 28-day compressive strength requirement of CLSM is greater than or equal to 0.7 MPa, the value of W / S is set to a low level, that is, the result obtained in the first step is 0.3402. The value of SWC / C is set to a high level, that is, 0.8.

[0064] The minimum value of cement-aggregate ratio C / A allowed is obtained by the second fitting model:

[0065] .

[0066] When the 28-day compressive strength requirement of the CLSM is less than or equal to 2.1 MPa, the W / S value is set to a high level, i.e. 0.37. The SWC / C value is set to a low level, i.e. 0.2. The maximum allowed ratio of C / A is 0.11, .

[0067] If the 28-day compressive strength of the CLSM without the need for re-excavation after hardening is not greater than 8.3 MPa, the maximum allowed ratio of C / A is 0.318

[0068] Step S4, according to the first fitting model, the value range of W / S obtained in step S2, the value range of the cement-bone ratio C / A obtained in step S3, and 0.2≤SWC / C≤0.8 as constraint conditions, the maximum value of SWC / C as the optimization target, to obtain the final values of W / S, C / A and SWC / C.

[0069] The nonlinear programming method is used to solve the maximum value of SWC / C under all constraint conditions, i.e. the optimal water-solid ratio W / S, cement-bone ratio C / A and solid waste cement ratio SWC / C; according to the optimal water-solid ratio W / S, cement-bone ratio C / A and solid waste cement ratio SWC / C, the proportions of water and solid, cementitious materials and aggregates, and solid waste cementitious materials and cementitious materials are matched.

[0070] The relative proportion parameters used in the mix proportion design method are independent of each other, and the CLSM mix proportion is defined by modifying the relative proportion parameters between components, so as to control the performance of the CLSM without affecting the ratio of other parameters. This method can effectively reduce the trial and error times of the mix proportion design of the multi-solid waste iron tailings powder CLSM, improve the design efficiency, and provide theoretical guidance for the resource utilization of the iron tailings powder in the region.

[0071] Further, the method can further include: step S5, adjusting the mix proportion according to the regression model. According to the preliminary mix proportion determined in steps S2 to S4, the preliminary mix proportion is adjusted as necessary by using the fluidity and 28d strength regression model to achieve a specific CLSM performance target. In the case of meeting the target performance, the W / S and C / A ratios are reduced as much as possible, and the SWC / C ratio is increased, so as to reduce the raw material cost.

[0072] Step S6, adjusting the mix proportion according to the test. The mix proportion adjusted in the fourth step is tested in the unit weight of cementitious materials, and the W / S is adjusted to reach the required fluidity. When adjusting W / S, attention should be paid to the adverse effects of the increase of W / S on strength, segregation and bleeding.

[0073] Step S7, adjusting C / A according to the target strength

[0074] Step S8, obtaining final W / S, C / A and SWC / C.

[0075] The above detailed description of the specific embodiments of the present application has further explained the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for mix proportion design of alkali slag-containing multi-solid waste iron tailings powder CLSM, for adjusting to obtain optimal water-solid ratio W / S, cement-aggregate ratio C / A and waste rubber ratio SWC / C according to a preset CLSM performance target, the preset CLSM performance target comprising: The CLSM fluidity target requirement and the CLSM compressive strength target requirement; and the method comprises the following steps: In step S1, a first fitting model based on the CLSM fluidity response and a second fitting model based on the 28-day compressive strength response are established according to historical multi-solid waste iron tailings powder CLSM mixing ratio data, and the response factors of the fitting models are: water-solid ratio W / S, cement-aggregate ratio C / A and waste cement ratio SWC / C. The specific expression of the first fitting model based on the CLSM fluidity response is: wherein, represents the flow value, i.e. the flow spread, in mm; , and respectively represent the water-solid ratio W / S, the glue-bone ratio C / A and the waste glue ratio SWC / C; The initial value range of W / S is 0.30-0.37, the initial value range of C / A is 0.06-0.2, and the initial value range of SWC / C is 0.2-0.

8. The expression of the second fitting model of the 28-day compressive strength response is: wherein, is the compressive strength value at 28 days, in MPa; In step S2, the value range of W / S is determined by the first fitting model according to the CLSM fluidity target requirement; when the CLSM fluidity target requirement is greater than or equal to 180 mm, the cement-aggregate ratio is taken as the initial value middle value C / A=0.13 and the waste cement ratio is taken as the initial value middle value SWC / C=0.5 to obtain the minimum value allowed for W / S; when the CLSM fluidity requirement is greater than or equal to 200 mm, the cement-aggregate ratio is taken as the maximum initial value C / A=0.2 and the waste cement ratio is taken as the minimum initial value SWC / C=0.2, and the minimum value allowed for W / S is calculated by the first fitting model; In step S3, the value range of C / A is determined according to the minimum compressive strength and the maximum compressive strength of the specific number of days compressive strength target requirement of the CLSM; when the 28-day compressive strength target requirement is set as the minimum compressive strength, the value of W / S is taken as the minimum value allowed for W / S calculated by the first fitting model, the value of SWC / C is taken as the maximum initial value SWC / C=0.8, and the minimum value allowed for C / A is obtained by the second fitting model; when the 28-day compressive strength target requirement is set as the maximum compressive strength, the value of W / S is taken as the maximum initial value W / S=0.37, the value of SWC / C is taken as the minimum initial value SWC / C=0.2, and the maximum value allowed for C / A is obtained by the second fitting model; In step S4, according to the first fitting model, the value range of W / S obtained in step S2, the value range of C / A obtained in step S3, and the constraint condition of 0.2≤SWC / C≤0.8, the maximum value of SWC / C is taken as the optimization target to obtain the values of W / S, C / A and SWC / C.

2. The method according to claim 1, characterized in that, The specific process of establishing the fitting model comprises: At least 20 groups of historical multi-solid waste iron tailings powder CLSM mixing ratio test data are collected, each group of data including water-solid ratio W / S, cement-aggregate ratio C / A, waste cement ratio SWC / C, and corresponding fluidity test results and 28-day compressive strength test results; a quadratic polynomial regression model is established by using response surface analysis method, taking W / S, C / A and SWC / C as independent variables and taking fluidity and 28-day compressive strength as dependent variables; A significance test is performed on the established fitting models, requiring the correlation coefficients of the first fitting model and the second fitting model to be both not less than 0.85, and the values of the first fitting model and the second fitting model to be less than 0.

05. the values of the first fitting model and the second fitting model to be less than 0.

05.

3. The method according to claim 2, characterized in that, The nonlinear programming method is used to obtain the W / S, C / A and SWC / C values corresponding to the maximum SWC / C value under the condition of meeting all constraints, that is, the optimal water-solid ratio W / S, cement-aggregate ratio C / A and waste rubber-cement ratio SWC / C.

4. The method according to claim 3, characterized in that, According to the optimal water-solid ratio W / S, cement-aggregate ratio C / A and waste rubber-cement ratio SWC / C, the water-solid ratio, the cement-aggregate ratio and the waste rubber-cement ratio are represented, and the three ratio parameters are independent multi-level ratios, and the three parameters do not affect each other.

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