Method for estimating void ratio of coarse aggregate

Abstract

The invention discloses a coarse aggregate void ratio presumption method, which comprises the following steps of: obtaining a plurality of continuously graded coarse aggregates with known void ratios, respectively extracting the grading screen residue of each coarse aggregate, and fitting by using a stepwise regression method by taking the grading screen residue of each coarse aggregate as an independent variable and the corresponding void ratio as a dependent variable to obtain a presumption formula of the void ratio of the coarse aggregates; and presuming the void ratio of the coarse aggregate by using a presumption formula of the void ratio of the coarse aggregate according to the counting screen residue of the continuous grading coarse aggregate to be detected. According to the invention, the test quantity can be reduced, and the test time of the coarse aggregate void ratio is shortened; the void ratio of the coarse aggregate can be presumed in real time according to the counting screen residue data of each grade in the grain composition test of the coarse aggregate on an engineering site, so that the mix proportion of the concrete is conveniently adjusted, and the construction quality of the concrete is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of civil engineering materials, and in particular to a method for estimating void ratio of coarse aggregate. Background Art

[0002] In concrete, coarse aggregate is an indispensable material and accounts for the largest volume share in concrete. It not only provides the necessary skeleton support for concrete, but also largely determines the mechanical properties, durability and economy of concrete. The void ratio of coarse aggregate refers to the percentage of voids in coarse aggregate, which is usually used to evaluate the density and quality of the material. The size of the void ratio directly affects the mechanical properties and durability of the material. The lower the void ratio, the tighter the filling between particles, the better the density of the material, and the correspondingly improved strength and durability; conversely, a higher void ratio may affect the engineering performance of the material, such as easy damage and easy penetration.

[0003] According to the traditional method, the void ratio of coarse aggregate needs to be tested by bulk density test and apparent density test first, and then the void ratio of coarse aggregate is calculated according to the relevant calculation formula. However, this process requires personnel to conduct two different tests separately, which is time-consuming and labor-intensive, and cannot meet the efficiency requirements of modern engineering. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the technical problem to be solved by the present invention is: how to provide a method for estimating the void ratio of coarse aggregate which is simple, convenient, time-saving, efficient and accurate.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A method for estimating the void ratio of coarse aggregate comprises the following steps: obtaining a plurality of continuously graded coarse aggregates with known void ratios, extracting the fractional sieve residues of each coarse aggregate respectively, taking the fractional sieve residue of each coarse aggregate as an independent variable and the corresponding void ratio as a dependent variable, fitting a formula for estimating the void ratio of coarse aggregate using a stepwise regression method, and estimating the void ratio of coarse aggregate using the formula for estimating the void ratio of coarse aggregate according to the fractional sieve residues of the continuously graded coarse aggregate to be tested.

[0007] As an optimization, after extracting the sieve residues of each coarse aggregate, the number of independent variables is increased by increasing the order of the sieve residues of the coarse aggregate, and then the stepwise regression method is used to fit the estimated formula for the void ratio of the coarse aggregate. Since the sum of the sieve residues of each coarse aggregate is 1, it has strong collinearity, so it is necessary to eliminate the influence of the collinearity of independent variables on the performance of the mathematical model. The specific steps are to increase the order of each sieve residue to increase the number of independent variables, thereby increasing the sample size, and then use the stepwise regression method to eliminate the variables with collinearity in the mathematical model to make the mathematical model more concise.

[0008] As an optimization, the gradation of the cumulative sieve residue of the coarse aggregate is set to 3 to 5 times.

[0009] Compared with the prior art, the present invention has the following advantages: the present invention can reduce the test amount and shorten the test time of the void ratio of the coarse aggregate; it can infer the void ratio of the coarse aggregate in real time according to the cumulative sieve residue data of each grade in the coarse aggregate particle gradation test at the construction site, so as to adjust the concrete mix ratio and ensure the construction quality of the concrete. Specific embodiments

[0010] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0011] In the method for inferring the void ratio of the coarse aggregate in this specific embodiment, a number of coarse aggregates with continuous gradation and known void ratios are obtained, and the cumulative sieve residue of each coarse aggregate is extracted respectively. Taking the cumulative sieve residue of each coarse aggregate as the independent variable and the corresponding void ratio as the dependent variable, the inference formula for the void ratio of the coarse aggregate is obtained by fitting using the stepwise regression method. According to the cumulative sieve residue of the coarse aggregate with continuous gradation to be detected, the void ratio of the coarse aggregate is inferred using the inference formula for the void ratio of the coarse aggregate.

[0012] In this specific embodiment, after the cumulative sieve residue of each coarse aggregate is extracted, the number of independent variables is increased by increasing the gradation of the cumulative sieve residue of the coarse aggregate, and then the inference formula for the void ratio of the coarse aggregate is obtained by fitting using the stepwise regression method.

[0013] In this specific embodiment, the gradation of the cumulative sieve residue of the coarse aggregate is set to 4 times.

[0014] Taking the coarse aggregate with a continuous particle size of 5 - 25 mm as an example, the cumulative sieve residues of the particle size groups of 4.75 - 9.5 mm (4.75 mm sieve), 9.5 - 16 mm (9.5 mm sieve), 16 - 19 mm (16 mm sieve), and 19 - 26.5 mm (19 mm sieve) in the continuous particle size of 5 - 25 mm are extracted. The inference formula for the void ratio of the coarse aggregate obtained by analyzing and fitting using the stepwise regression method is as follows:

[0015]

[0016] In the formula, X 1 、X 2 、X 3 、X 4They respectively represent the cumulative sieve residues of particle size groups 4.75 - 9.5 mm, 9.5 - 16 mm, 16 - 19 mm, and 19 - 26.5 mm. The parameter y represents the estimated value of the void ratio of coarse aggregates, b1 is the constant term of the fitting formula, and in addition, b2 to b17 are the fitting coefficients in the mathematical formula. Through statistical analysis and data fitting, the fitting results of the following mathematical model are obtained, as shown in

[0017] Table 1:

[0018]

[0019] Table 1

[0020] After statistical analysis, the mathematical model of the above-mentioned void ratio of coarse aggregates shows good overall significance, all coefficients in the mathematical model have statistical significance, and the goodness of fit of the mathematical model shows a high fitting effect. Specifically, the value ranges of the coefficients in the model are as follows:

[0021] b1: [42.87647 - 43.55138] b2: [3.24×10 -8 ~4.87×10 -8

[0022] b3: [3.18×10 -8 ~4.80×10 -8 b4: [3.17×10 -8 ~4.77×10 -8

[0023] b5: [3.25×10 -8 ~4.93×10 -8 b6: [3.63×10 -7 ~9.00×10 -7

[0024] b7: [1.25×10 -7 ~3.16×10 -7 b8: [2.03×10 -7 ~7.33×10 -7

[0025] b9: [1.94×10 -7 ~4.36×10 -7 b10: [-2.30×10 -6 ~-6.00×10 -7

[0026] b11: [3.43×10 -8 ~1.79×10 -7 b12: [3.95×10​​​​​-8 ~1.54*10 -7

[0027] b13: [1.59*10 -7 ~2.71*10 -7 b14: [-2.12*10 -7 ~ -1.01*10 -7

[0028] b15: [1.14*10 -7 ~3.57*10 -7 b16: [-1.86*10 -7 ~ -6.45*10 -8

[0029] b17: [2.90*10 -8 ~1.76*10 -7

[0030] Next, conduct an actual test on the void ratio of coarse aggregates to specifically verify the actual effect of the above-mentioned estimation method. Use the special crushed stones for admixture testing, design different gradations of coarse aggregates, and according to the provisions of the current standard "Pebbles and Crushed Stones for Construction" (GBT / 14685), test the bulk density and apparent density of the coarse aggregates, and finally calculate the void ratio of the coarse aggregates based on these data. The obtained coarse aggregate data is sorted out as shown in Table 2:

[0031]

[0032]

[0033] Table 2

[0034] Substitute the cumulative sieve residue of each grade in the above table of coarse aggregate data into the estimation formula for the void ratio of coarse aggregates for estimation. The values of each coefficient in the estimation formula are as follows:

[0035] b1: 43.21392 b2: 4.06*10 -8 b3: 3.99*10 -8

[0036] b4: 3.97*10 -8 b5: 4.09*10 -8 b6: 6.31*10 -7

[0037] b7: 2.21*10 -7 b8: 2.21*10 -7 b9: 3.15*10 -7

[0038] ​​​​b10: -1.45 * 10 -6 b11: 1.07 * 10 -7 b12: 9.65 * 10 -8

[0039] b13: 2.15 * 10 -7 b14: -1.56 * 10 -7 b15: 2.36 * 10 -7

[0040] b16: -1.25 * 10 -7 b17: 1.03 * 10 -7

[0041] The following estimated formula for the void ratio of coarse aggregate is obtained:

[0042]

[0043] The estimated void ratio is calculated and compared with the actual void ratio as shown in Table 3:

[0044]

[0045]

[0046] Table 3

[0047] Analysis of the content in Table 3 shows that for coarse aggregate with a continuous particle size range of 5 - 25 mm, the absolute error between the estimated void ratio and the actual void ratio is within 3.6%, the minimum absolute error reaches 0.2%, and the average absolute error is 2.53%. In terms of relative error, the maximum value is 7.3%, the minimum value is 0.5%, and the average value is 5.68%. In addition, the value of Y estimated / Y actual is between 0.925 and 1.005, indicating that the estimated value has high accuracy. These numerical results fully confirm that the void ratio of coarse aggregate estimated by the present invention has good stability and reliability, and the estimated value has a high correlation coefficient with the true value, and the estimation method has high accuracy.

[0048] Based on the above analysis, the present invention can relatively accurately estimate the void ratio of coarse aggregate only by testing the cumulative sieve residue of each grade in the coarse aggregate particle size distribution test. This method not only significantly reduces the input of manpower and time, but also meets the requirements of the modern civil engineering field for rapid acquisition of relevant indicators of coarse aggregate.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described with reference to the preferred embodiments of the present invention, it should be understood by those skilled in the art that various changes may be made in form and details without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A method for estimating the void ratio of coarse aggregate, characterized in that: Several portions of continuously graded coarse aggregate with known void ratio are obtained, and the fractional sieve residue of each coarse aggregate is extracted respectively. The fractional sieve residue of each portion of coarse aggregate is taken as the independent variable, and the corresponding void ratio is taken as the dependent variable. The stepwise regression method is used to fit the formula for estimating the void ratio of the coarse aggregate. The void ratio of the coarse aggregate is estimated based on the fractional sieve residue of the continuously graded coarse aggregate to be tested using the estimating formula for the void ratio of the coarse aggregate.

2. The method for estimating the void ratio of coarse aggregate according to claim 1, characterized in that: After extracting the fractional sieve residues of each coarse aggregate, the number of independent variables is increased by increasing the order of the fractional sieve residues of the coarse aggregate, and then the stepwise regression method is used to fit the estimation formula for the void ratio of the coarse aggregate.

3. The method for estimating the void ratio of coarse aggregate according to claim 2, characterized in that: The order of the screening residue of coarse aggregate is set to 3 to 5 times.

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