A method for evaluating the activity of tuffaceous volcanic ash materials

Abstract

The present invention provides a method for evaluating the strength activity of tuffaceous volcanic ash materials, that is, a quantitative method for evaluating the activity of tuffaceous volcanic ash materials using multiple influencing factors, and uses the response surface method to establish a response model of tuff powder specific surface area, dosage, specimen curing age and cement mortar strength, and further proposes a strength activity index model that integrates tuff powder specific surface area, dosage and specimen curing age, so as to provide a more accurate and comprehensive prediction of cement mortar strength performance and a method for evaluating the activity of tuffaceous volcanic ash materials. The model constructed in this application can comprehensively evaluate the activity of tuffaceous ash powder, with a relatively high prediction accuracy, guide engineering applications, and promote its widespread application in the field of building materials by more accurately evaluating the role of tuffaceous ash powder in cement mortar, thereby reducing the demand for traditional cement, reducing carbon emissions, and promoting the field of building materials to develop in the direction of sustainable development.

Description

Technical Field

[0001] The present invention relates to the technical field of building materials, and particularly relates to a method for evaluating the strength activity of the activity of a tuffaceous pozzolanic material. Background Art

[0002] With the continuous expansion of infrastructure construction in China, the demand for concrete is increasing. As one of the main raw materials of concrete, traditional cement releases a large amount of greenhouse gases such as CO2 during its production and transportation, causing serious harm to the atmospheric environment. Finding supplementary cementitious materials that can replace part of the cement has become the main method to reduce the environmental impact of concrete. However, in the southwestern region of China, the supply of common mineral admixtures such as fly ash and slag powder is short, so alternative solutions need to be explored.

[0003] Tuff powder has attracted much attention due to its rich resources, low carbon emissions, and potential improvement of concrete performance, and is regarded as an alternative material for cement. However, existing research mainly focuses on the single effect of tuff powder on the performance of cement mortar and concrete. At present, the complex effects of multiple factors on the mechanical properties of cement mortar have not been systematically studied, and no clear mathematical model has been established to quantify the influence degree of these factors, so the continuous influence trend of tuffaceous pozzolanic materials cannot be accurately reflected.

[0004] At present, in the evaluation method of the activity of tuffaceous pozzolanic materials, the commonly used method is the strength activity index method in the specification. This method is convenient to test and can relatively truly reflect the application situation of actual projects. However, the calculation method of this strength activity index has limitations, that is, it cannot accurately measure the independent contribution of tuffaceous pozzolanic materials to strength. In response to this problem, Professor Puxincheng of Chongqing University proposed an evaluation method for the strength contribution rate of the hydration activity effect of mineral admixtures, which can quantify the hydration activity effect of mineral admixtures more deeply. This method can calculate the specific strength, specific strength coefficient, and the contribution rate of the hydration activity strength effect of different admixtures with different dosages. Although this method can provide a reference for analyzing the contribution rate of each component of the cementitious material to the matrix strength, it only quantifies the influence of the admixture dosage and does not consider more possible variables. In addition, the new parameter introduced by Zaleska et al. is the pozzolan effectiveness coefficient (PEC). When 0 < PEC < 1, the higher the PEC value, the higher the pozzolanic activity. When PEC < 0, the pozzolan is inactive and can only be used as a filler. When PEC > 1, the effectiveness of limestone is higher than that of Portland cement, and there is a synergistic effect in the limestone-cement system. The strengthening effect of fly ash in cement was studied using this parameter, and the rationality and effectiveness of this method were verified. However, the above methods also only quantify the influence of the dosage of pozzolanic materials on the pozzolan effectiveness coefficient and even the activity of pozzolanic materials.

[0005] Therefore, more variables that may affect the results still need to be further considered to more accurately evaluate the activity of volcanic ash materials. Summary of the invention

[0006] Regarding the activity evaluation methods of volcanic ash materials in the prior art, although the strength activity index method in the current physical method is convenient to test and can more truly reflect the application of actual projects, the strength activity index calculation method has limitations. The activity of volcanic ash is affected by many factors such as its composition, structure, particle size, dosage, etc. The existing evaluation method may not be able to fully consider these factors, thus resulting in problems such as bias in the evaluation results, lack of comprehensiveness and accuracy. The present invention provides a strength activity evaluation method for the activity of tuffaceous volcanic ash materials, that is, a multi-factor quantitative method for evaluating the activity of tuffaceous volcanic ash materials, and uses the response surface method to establish a response model of tuff powder specific surface area, dosage and specimen curing age with cement mortar strength. A strength activity index model integrating tuff powder specific surface area, dosage and specimen curing age is further proposed to provide a more accurate and comprehensive cement mortar strength performance prediction and tuffaceous volcanic ash material activity evaluation method.

[0007] A method for evaluating the intensity activity of tuffaceous volcanic ash material comprises the following steps:

[0008] Determine the influencing factors and strength evaluation indexes of tuffaceous volcanic ash materials, wherein the above-mentioned strength influencing factors are the specific surface area, dosage and curing age of tuff powder, and the above-mentioned strength evaluation indexes are flexural strength, compressive strength and strength activity index;

[0009] Obtain experimental real data sample I of the specific surface area, dosage, curing age of a certain amount of tuff powder and the strength of tuff powder cement mortar;

[0010] Based on the response surface method, experimental design method, based on the experimental real data sample I and the relationship model R T Establish a fitting model for the relationship between the specific surface area, dosage, specimen curing age and cement mortar strength. T Predictive models;

[0011] Obtain experimental real data sample II of the curing age of a certain number of specimens without tuff powder and the strength of tuff powder cement mortar;

[0012] Based on experimental real data sample II and correlation model R c The fitting model of the strength of cement mortar without tuff powder and the curing age of specimens was obtained by nonlinear curve fitting. C Predictive models;

[0013] Based on R T Prediction Model, RC The prediction model constructs the strength activity index model K of tuffaceous volcanic ash materials;

[0014] The specific surface area, dosage and curing age of the tuff powder added to the test piece are input into the model K to obtain the predicted value of the strength activity index of the tuffaceous volcanic ash material.

[0015] The specific surface area of ​​the above tuff powder ranges from 400 to 500 m 2 / kg, the tuff powder dosage range is 30% to 55%, and the specimen curing age range is 3 to 28d.

[0016] The above relationship model R T The mathematical expression is:

[0017] R T =C+k1S w +k2D+k3A+k4DA+k5S w 2 +k6D 2 +k7A 2

[0018] In the formula, R T is the strength of cement mortar containing tuff powder, S w is the specific surface area of ​​tuff powder (m 2 / kg); D is the tuff powder dosage (%); A is the specimen curing age (d); C, k1, k2, k3, k4, k5, k6, k7 are fitting parameters.

[0019] The above R T The prediction model is expressed mathematically as follows:

[0020] Flexural strength: R Tf =16.3236+2.8617*S w +(-5.2103)*D+7.3266*A+(-1.3907)*DA+

[0021] (-1.6117)*S w 2 +0.0312*D 2 +(-2.1577)*A 2

[0022] Compressive strength: R Tc =-21.1006+0.1576*S w +(-0.2959)*D+1.3925*A+(-0.0089)*DA+

[0023] (-0.0002)*S w2 +(0.0002)*D 2 +(-0.0138)*A 2

[0024] In the formula, R Tf is the flexural strength of cement mortar containing tuff powder, R Tc S is the compressive strength of cement mortar containing tuff powder; w is the specific surface area of ​​tuff powder (m 2 / kg); D is the amount of tuff powder (%); A is the curing age of the specimen (d).

[0025] The above R T The prediction model building process specifically includes:

[0026] Obtain experimental real data samples of a certain amount of tuff powder specific surface area, dosage, specimen curing age and tuff powder cement mortar strength;

[0027] The real data samples of the experiment are adopted by the relational model R T Perform multiple regression fitting analysis to obtain the multiple regression fitting parameters of its coded values ​​and true values;

[0028] The above regression equation was subjected to variance analysis and significance test, as well as error statistical analysis;

[0029] Based on the influence of the above strength influencing factors on the above strength evaluation indicators, a quadratic linear regression fitting and significance analysis were performed to establish the R T Predictive models;

[0030] Compare the above predicted value with the above measured value to determine the above R T The accuracy of the prediction model.

[0031] The above correlation model R c The mathematical expression is:

[0032] R C =-R0·exp(-A / t0)+C0

[0033] In the formula, R C is the strength of cement mortar (MPa), A is the curing age of specimen (d); R0, t0, C0 are the parameters of experimental fitting.

[0034] The above R C The prediction model is expressed mathematically as follows:

[0035] Flexural strength: R Cf =-40.4exp(-A / 12.3)+47.8; R 2 =0.99;

[0036] Compressive strength: R Cc =-5.4exp(-A / 22.3)+9.6; R 2 =0.99;

[0037] In the formula, R Cf is the flexural strength of cement mortar (MPa), R Cc is the compressive strength of cement mortar (MPa), and A is the curing age of the specimen (d).

[0038] The above R C The prediction model building process includes:

[0039] Firstly, the flexural and compressive strengths of cement mortar without tuff powder at different ages and their curing age were analyzed according to the correlation model R C Perform nonlinear curve fitting;

[0040] Then, the fitting relationship between the strength of cement mortar without tuff powder and the curing age was obtained based on the test results.

[0041] The strength activity index model K of the tuffaceous volcanic ash material is expressed by the mathematical formula:

[0042]

[0043] Where, K is the intensity activity index (%); R T is the strength of tuff powder cement mortar (MPa), R C is the strength of cement mortar (MPa).

[0044] The process of constructing the above-mentioned tuffaceous volcanic ash material strength activity index K prediction model includes:

[0045] Based on R T Prediction Model, R C The prediction model constructs the strength activity index model K of tuffaceous volcanic ash materials;

[0046] The specific surface area, dosage and curing age of the tuff powder of the test piece are input into the model K to obtain the predicted value of the strength activity index of the tuff volcanic ash material for concrete.

[0047] Highly active tuffaceous volcanic ash is often used as an admixture for concrete, especially in structures that require high strength and durability, such as special concretes such as high-strength concrete and refractory concrete, roads and bridges, as well as buildings and water conservancy projects. Although low-activity tuffaceous volcanic ash has weaker reactivity, it also has unique application value. For example, it can be used as a filler for lightweight concrete to reduce the weight of concrete and improve construction efficiency. It can also be used to prepare flame-retardant and low-smoke materials with obvious effects, low cost, environmentally friendly materials, and non-toxicity. In addition, it can also be used to prepare flocculants for use in wastewater treatment and other fields.

[0048] Compared with the prior art, this application has the following advantages:

[0049] (1) Improve prediction accuracy: The traditional strength activity index calculation method has the problems of incomplete consideration of factors and insufficient continuity. The model combines multiple factors such as the specific surface area, dosage and specimen curing age of tuff powder, which can more accurately and comprehensively predict the strength properties of cement mortar, and the amount of data required for model construction is small.

[0050] (2) Comprehensive evaluation of tuff powder activity: The strength activity index model takes into account the comprehensive effects of tuff powder specific surface area, dosage and specimen curing age on the strength of cement mortar, making the evaluation of tuff powder activity more comprehensive and better reflecting its actual performance in concrete.

[0051] (3) Guiding engineering applications: The model can provide more scientific guidance for the field of building materials, especially in the design and construction process, and can more accurately determine the dosage of tuff powder, specific surface area, and specimen curing age to maximize the performance of cement mortar.

[0052] (4) Promote sustainable development: By more accurately evaluating the role of tuff powder in cement mortar, it can promote its widespread application in the field of building materials, thereby reducing the demand for traditional cement, reducing carbon emissions, and promoting the development of the building materials field towards sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a flowchart of the method for constructing an intensity activity index model for the activity of tuffaceous volcanic ash materials in this application. DETAILED DESCRIPTION

[0054] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solution of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Take the admixture of tuff powder as an example.

[0056] Specific surface area determination method:

[0057] The LS-609 laser particle size analyzer was used to measure the particle size of tuff powder to obtain its specific surface area. The sample particle size analysis range of the instrument is 0.1-1000 μm, the sampling method is automatic wet sampling, and the sample material is mineral powder (refractive index 2.4, absorption rate 0.1, density 3.15 g / cm 3), the dispersion medium is distilled water (refractive index is 1.333). The light shielding rate is guaranteed to be between 10% and 15% during the test. Before each test, the injector should be cleaned 2 to 3 times with distilled water to ensure the accuracy of the test data.

[0058] The specimen curing conditions are:

[0059] According to the "Test Method for Cement Mortar Strength (ISO Method)" (GB / T 17671-2021), cement mortar is mixed with a planetary mixer according to the prescribed procedures. The freshly mixed mortar is poured into a test mold with a size of 40mm×40mm×160mm in two times and vibrated 60 times in sequence. The test mold containing mortar is removed and the surface of the test piece is smoothed. A glass cover is placed on the test mold. The cover does not contact the test piece and the distance between the cover and the test mold is controlled between 2mm and 3mm. The test mold is placed in a curing box with a temperature of 20℃±1℃ and a relative humidity of not less than 90%RH for 24 hours and then demolded. The demolded test piece is placed horizontally or vertically in 20℃±1℃ water for curing. When placed horizontally, the scraped surface should face up, and a certain distance should be maintained between the test pieces so that the water contacts the six surfaces of the test piece. During the curing period, the interval between the test pieces or the water depth on the upper surface of the test piece should not be less than 5mm.

[0060] The strength determination method is:

[0061] Specimen flexural strength (R f ), compressive strength (R c ) Performance test is carried out according to "Test method of cement mortar strength (ISO method)" (GB / T 17671-2021).

[0062] Place one side of the specimen on the supporting cylinder of the testing machine, with the long axis of the specimen perpendicular to the supporting cylinder. Use the loading cylinder to evenly apply load vertically to the opposite sides of the prism at a rate of 50N / s±10N / s until it breaks. Keep the two halves of the prism in a wet state until the compression test.

[0063] The flexural strength is calculated according to formula (1):

[0064] R f =1.5F f L / b 3 (1)

[0065] Where: R f —Flexural strength of test specimen, MPa; F f —Load applied to the middle of the prism when breaking, N; L—Distance between supporting cylinders, mm; b—Side length of the square section of the prism, mm.

[0066] Compressive strength R c The determination method is:

[0067] After the flexural strength test is completed, the two halves of the test specimens are taken out for compressive strength test. The difference between the center of the half prism and the center of pressure on the press plate should be within ±0.5mm, and the part of the prism exposed outside the press plate is about 10mm. During the entire loading process, the load is applied uniformly at a rate of 2400N / s±200N / s until failure.

[0068] The compressive strength is calculated according to formula (2):

[0069] R c =F c / A (2)

[0070] Where: R c —Compressive strength of test specimen, MPa; F c —Maximum load at failure, N; A—compressive area.

[0071] Strength activity index (K f , K c ) According to "Fly ash used in cement and concrete" (GB / T1596-2017), calculate according to formulas (3) and (4):

[0072] K f =R f / R f0 (3)

[0073] K c =R c / R c0 (4)

[0074] Where: K f , K c —Flexural and compressive strength activity index, %; R f0 , R c0 —Compare the flexural and compressive strength of the specimens, MPa.

[0075] The response surface methodology was used to design a three-factor three-level experiment. The influencing factors were the specific surface area of ​​tuff powder (S w ), dosage (D) and specimen curing age (A), the response values ​​are the flexural strength of cement mortar specimens (R f ), compressive strength (R c ), the experimental design and experimental results are shown in Table 1.

[0076] Table 1

[0077]

[0078] According to the Weierstrass polynomial best approximation theorem, most functions can be approximated by polynomials. The polynomial approximation model can handle a quite wide range of nonlinear problems. Therefore, in practical applications, regardless of the relationship between the independent variable and the dependent variable, the polynomial approximation model can be used for analysis.

[0079] The relationship model R T (R T quadratic polynomial model) is expressed mathematically as:

[0080] R T = C + k1S w + k2D + k3A + k4DA + k5S w 2 + k6D 2 + k7A 2

[0081] In the formula, R T is the strength of the cement mortar containing tuff powder, S w is the specific surface area of tuff powder (m 2 / kg); D is the dosage of tuff powder (%); A is the curing age of the specimen (d); C, k1, k2, k3, k4, k5, k6, k7 are fitting parameters.

[0082] Multiple regression fitting analysis was carried out on the flexural and compressive strengths of the cement mortar containing tuff powder respectively, and the multiple regression fitting parameters of their coded values and true values were obtained, as shown in Table 2.

[0083] Table 2

[0084]

[0085] The equation expressed by coded factors can be used to predict the response to a given level of each factor. By comparing the coefficients of each factor, the relative influence of each factor can be determined. Since the absolute values of the coefficients of the coded value equation are k1 < k2 < k3, the sensitivity of the three influencing factors to the strength is ranked from high to low as curing age, dosage, and specific surface area.

[0086] Analysis of variance and significance test were carried out on the above regression equation, as shown in Table 3.

[0087] Table 3

[0088]

[0089] The p-values of the above models are all less than 0.05, so the models are significant and can be used for subsequent optimization design; the lack-of-fit term is the degree of fitting between the model and the experiment, that is, the degree of difference between the two. The p-values of the lack-of-fit terms of the models are all greater than 0.05, indicating that the difference between the model and the experiment is not significant, that is, the degree of irrelevance between the experimental data and the model is not significant, and the model is credible.

[0090] The statistical analysis results of the flexural and compressive strength regression equation errors are shown in Table 4.

[0091] Table 4

[0092] Statistical items Flexural strength / compressive strength Statistical items Flexural strength / compressive strength Standard Deviation 0.1376 / 0.5507 Model determination coefficient 0.9937 / 0.9959 Mean 3.38 / 12.50 Model-adjusted coefficient of determination 0.9887 / 0.9928 Model coefficient of variation % 4.07 / 4.41 Model prediction coefficient of determination 0.9534 / 0.9718 The sum of squared prediction errors 1.25 / 19.00 Precision 50.4719 / 66.3775

[0093] The model determination coefficients were 0.9937 and 0.9959, respectively, indicating that the predicted values ​​of the model were in high agreement with the measured values; the model correction determination coefficients were 0.9887 and 0.9928, respectively, that is, the model regression equations could simulate 98.87% and 99.28% of the response value changes, respectively, and the absolute values ​​of the differences between the model correction determination coefficient and the model prediction determination coefficient were 0.0353 and 0.0210, respectively, both less than 0.2, indicating that the regression model can fully explain the process problems; the precisions were 50.4719 and 66.3775, respectively, and those greater than 4 were reasonable. In addition, the model variation coefficients were 4.07% and 4.41%, respectively, less than 10%, indicating that the test had high accuracy and reliability.

[0094] Therefore, R T The regression equation of the quadratic polynomial model can replace the true value of the test and analyze the test results.

[0095] The comparison between the predicted results of the tuff powder specific surface area, dosage and curing age of cement mortar specimens and the measured results of the tuff powder cement mortar strength response model is shown in Table 5. The absolute error ranges between the predicted results of the flexural and compressive strength model and the measured results are 0-0.3MPa and 0-0.9MPa, respectively, both within 1MP.

[0096] Table 5

[0097]

[0098] The above results show that R T Predictive models can achieve efficient and accurate predictions.

[0099] The test results of cement mortar strength of the control group (without tuff powder) at different ages are shown in Table 6;

[0100] Table 6

[0101] Curing age (d) 3 7 28 Measured flexural strength (MPa) 4.8 5.6 8 Measured compressive strength (MPa) 16.2 25.7 43.7

[0102] The flexural and compressive strengths and curing age are based on the measured data in Table 6 according to the correlation model R C (Exponential function model) for nonlinear curve fitting;

[0103] Correlation Model R C The mathematical expression is:

[0104] R C =-R0·exp(-A / t0)+C0

[0105] In the formula, R C is the cement mortar strength at age A (MPa); R0, t0, C0 are the experimental fitting parameters.

[0106] According to the test results, the fitting relationship between the cement mortar strength and the curing age of the control group (without tuff powder) is as follows:

[0107] Flexural strength ~ curing age: R Cf =-40.4exp(-A / 12.3)+47.8; R 2 =0.99;

[0108] Compressive strength ~ curing age: R Cc =-5.4exp(-A / 22.3)+9.6; R 2 =0.99.

[0109] R C Model R 2 It reaches 0.99, and the fitting effect is excellent, which can achieve efficient and accurate prediction.

[0110] Based on the currently commonly used method for determining the activity of volcanic ash, and considering that the strength activity index is affected by various factors, the present invention proposes a method for quantitatively evaluating the activity of tuffaceous volcanic ash materials using multiple influencing factors, namely, a strength activity index model that integrates the specific surface area, dosage, and curing age of tuff powder, to comprehensively evaluate the influence of the activity of tuffaceous volcanic ash materials on the strength of cement mortar. This model can more comprehensively reflect the contribution of tuff powder to the strength of cement mortar, and quantify the influence of the specific surface area, dosage, and curing age of tuff powder on its strength activity index. The model is expressed in the mathematical formula:

[0111] K=R T / R C

[0112] Where, K is the intensity activity index, %; R T , R C They are tuff powder cement mortar strength and cement mortar strength, MPa respectively.

[0113] Comprehensive R T , R C The strength activity index model proposed by the present invention, which integrates the specific surface area, dosage and curing age of the tuff powder, is obtained by using the K model as follows:

[0114]

[0115] A total of 27 groups of flexural and compressive strength activity index standard calculation results of all levels were compared with the prediction results of the strength activity index model proposed in the present invention, including the specific surface area, dosage and curing age of the tuff powder, as shown in Table 7. The absolute error range between the prediction results of the strength activity index model proposed in the present invention, including the specific surface area, dosage and curing age of the tuff powder, and the results calculated according to the standard for the measured data is 0-5%, so it can provide a reference for more accurate and comprehensive cement mortar performance prediction, influence quantification and mix ratio optimization, and volcanic ash activity evaluation method of tuff volcanic ash materials.

[0116] Table 7

[0117]

[0118] In summary, the beneficial effects of the present invention are: improving prediction accuracy: the traditional strength activity index calculation method has the problems of incomplete consideration of factors and insufficient continuity, while the model combines multiple factors such as the specific surface area, dosage and specimen curing age of tuff powder, which can more accurately and comprehensively predict the strength performance of cement mortar, and the amount of data required for model construction is small.

[0119] Comprehensive evaluation of tuff powder activity: The strength activity index model takes into account the comprehensive effects of tuff powder specific surface area, dosage and specimen curing age on the strength of cement mortar, making the evaluation of tuff powder activity more comprehensive and better reflecting its actual performance in concrete.

[0120] Guiding engineering applications: This model can provide more scientific guidance for the field of building materials, especially in the design and construction process, and can more accurately determine the dosage of tuff powder, specific surface area and specimen curing age to maximize the performance of cement mortar.

[0121] Promoting sustainable development: By more accurately evaluating the role of tuff powder in cement mortar, its widespread application in the field of building materials can be promoted, thereby reducing the demand for traditional cement, reducing carbon emissions, and promoting the development of the building materials field towards sustainable development.

[0122] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the intensity activity of tuffaceous volcanic ash materials, characterized in that: The following steps are involved: Determine the strength influencing factors and strength evaluation indexes of tuffaceous volcanic ash materials, wherein the strength influencing factors are the specific surface area, dosage and curing age of tuff powder, and the strength evaluation indexes are flexural strength, compressive strength and strength activity index; Obtain the experimental real data sample I of the specific surface area, dosage and curing age of tuff powder and the strength of tuff powder cement mortar; Based on the response surface method, experimental design method, based on the experimental real data sample I and the relationship model R T Establish a fitting model for the relationship between the specific surface area, dosage, specimen curing age and cement mortar strength. T Predictive models; Obtaining experimental real data sample II of the curing age of specimens without tuff powder and the strength of tuff powder cement mortar; Based on experimental real data sample II and correlation model R c The fitting model of the strength of cement mortar without tuff powder and the curing age of specimens was obtained by nonlinear curve fitting. C Predictive models; Based on R T Prediction Model, R C The prediction model constructs the strength activity index model K of the tuffaceous volcanic ash material; the specific surface area, dosage and curing age parameters of the tuffaceous ash powder added to the test piece are input into the model K to obtain the predicted value of the strength activity index of the tuffaceous volcanic ash material; The relational model R T The mathematical expression is: R T =C+k1S w +k2D+k3A+k4DA+k5S w 2 +k6D 2 +k7A 2 In the formula, R T is the strength of cement mortar containing tuff powder, S w is the specific surface area of ​​tuff powder (m 2 / kg); D is the amount of tuff powder (%); A is the curing age of the specimen (d); C, k1, k2, k3, k4, k5, k6, k7 are fitting parameters; The association model R c The mathematical expression is: R C =-R0·exp(-A / t0)+C0 In the formula, R C is the strength of cement mortar (MPa), A is the curing age of specimen (d); R0, t0, C0 are the parameters of experimental fitting.

2. The method for evaluating the activity intensity of tuffaceous volcanic ash materials according to claim 1, characterized in that: The specific surface area of ​​the tuff powder is in the range of 400 to 500 m 2 / kg, the tuff powder dosage range is 30% to 55%, and the specimen curing age range is 3 to 28d.

3. The method for evaluating the activity intensity of tuffaceous volcanic ash materials according to claim 1, characterized in that: The R T The prediction model is expressed mathematically as follows: Flexural strength: R Tf =16.3236+2.8617*S w +(-5.2103)*D+7.3266*A+(-1.3907)*DA+(-1.6117)*S w 2 +0.0312*D 2 +(-2.1577)*A 2 Compressive strength: R Tc =-21.1006+0.1576*S w +(-0.2959)*D+1.3925*A+(-0.0089)*DA+(-0.0002)*S w 2 +(0.0002)*D 2 +(-0.0138)*A 2 In the formula, R Tf is the flexural strength of cement mortar containing tuff powder, R Tc is the compressive strength of cement mortar containing tuff powder; S w is the specific surface area of ​​tuff powder (m 2 / kg); D is the amount of tuff powder added (%); A is the curing age of the specimen (d).

4. The method for evaluating the activity intensity of tuffaceous volcanic ash materials according to claim 1, characterized in that: The R C The prediction model is expressed mathematically as follows: Flexural strength: R Cf =-40.4exp(-A / 12.3)+47.8; R 2 =0.99; Compressive strength: R Cc =-5.4exp(-A / 22.3)+9.6; R 2 =0.99; In the formula, R Cf is the flexural strength of cement mortar (MPa), R Cc is the compressive strength of cement mortar (MPa), and A is the curing age of the specimen (d).

5. The method for evaluating the activity intensity of tuffaceous volcanic ash materials according to claim 1, characterized in that: The strength activity index model K of the tuffaceous volcanic ash material is expressed by the mathematical formula: Where, K is the intensity activity index (%); R T is the strength of tuff powder cement mortar (MPa), R C is the strength of cement mortar (MPa).

6. The method for evaluating the activity intensity of tuffaceous volcanic ash materials according to claim 1, characterized in that: The R T The prediction model building process specifically includes: Obtain experimental real data samples of a certain amount of tuff powder specific surface area, dosage, specimen curing age and tuff powder cement mortar strength; The real data samples of the experiment are adopted by the relational model R T Perform multiple regression fitting analysis to obtain the multiple regression fitting parameters of its coded values ​​and true values; Perform variance analysis and significance test on the regression equation, as well as error statistical analysis; Based on the influence of the strength influencing factors on the strength evaluation index, a quadratic linear regression fitting and significance analysis were performed to establish the R T Predictive models; Compare the predicted value with the measured value to determine the R T The accuracy of the prediction model.

7. The method for evaluating the activity intensity of tuffaceous volcanic ash materials according to claim 1, characterized in that: The R C The prediction model building process includes: Firstly, the flexural and compressive strengths of cement mortar without tuff powder at different ages and their curing age were analyzed according to the correlation model R C Perform nonlinear curve fitting; Then, the fitting relationship between the strength of cement mortar without tuff powder and the curing age was obtained based on the test results.

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