Concrete compressive strength multi-factor presumption method based on coarse aggregate gradation

Abstract

The invention discloses a coarse aggregate gradation-based concrete compressive strength multi-factor presumption method, which comprises the following steps of: according to a plurality of parts of known continuous gradation coarse aggregate, calculating a concrete sample of screen residue, coarse aggregate void ratio, water-binder ratio, slurry-bone ratio, sand ratio, 28d compressive strength of a cementing material and 28d compressive strength of concrete; the presumption formula of the concrete compressive strength is established through multivariate nonlinear regression fitting analysis by taking coarse aggregate screening residues, coarse aggregate void ratio, water-binder ratio, slurry-to-bone ratio, sand ratio and cementing material 28d compressive strength as independent variables and concrete 28d compressive strength as dependent variables, and the presumption formula of the concrete compressive strength is calculated according to related parameters. And presuming the compressive strength of the concrete by using a presumption formula of the compressive strength of the concrete. According to the method, whether the strength of the concrete mixed according to different mixing ratios reaches the standard or not can be rapidly analyzed, employees can be guided to flexibly adjust the mixing ratio of the concrete, and the construction quality of the concrete is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of civil engineering materials, and particularly relates to a multi-factor estimation method for the compressive strength of concrete based on the grading of coarse aggregates. Background Art

[0002] The compressive strength of concrete, as an embodiment of the mechanical properties of concrete materials, reflects its ability to withstand external forces and is one of the most important indicators in the civil engineering industry. In the modern civil engineering field, for the test of the compressive strength of concrete, it is necessary to mix according to the material composition in the concrete mix ratio, and then pour the mixed concrete into a specified mold for forming. The formed concrete test blocks need to go through a specified curing period (usually a standard curing age of 28 days in the industry), and then the compressive strength test is carried out to evaluate the quality of the concrete. This method consumes materials and manpower, and the test time is long, and it cannot provide strength data reference for production technicians in the early stage of concrete production and construction.

[0003] Regarding the estimation of the compressive strength of concrete, the Pauli formula is commonly used in the industry. However, only two factors, namely the water-binder ratio and the strength of the binder material, are used as independent variables in this formula. Compared with the more extensive composition factors contained in modern concrete, the strength values obtained may have relatively large deviations. Summary of the Invention

[0004] Aiming at the deficiencies of the above-mentioned prior art, the technical problem to be solved by the present invention is: how to provide a simple, convenient, time-consuming short, and highly accurate multi-factor estimation method for the compressive strength of concrete based on the grading of coarse aggregates.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A multi-factor estimation method for the compressive strength of concrete based on the grading of coarse aggregates. According to concrete specimens with the cumulative sieve residue of several known continuously graded coarse aggregates, the void ratio of coarse aggregates, water-binder ratio, paste-aggregate ratio, sand ratio, 28-day compressive strength of binder material, and 28-day compressive strength of concrete, taking the cumulative sieve residue of coarse aggregates, the void ratio of coarse aggregates, water-binder ratio, paste-aggregate ratio, sand ratio, and 28-day compressive strength of binder material as independent variables, and the 28-day compressive strength of concrete as the dependent variable, through multiple non-linear regression fitting analysis, an estimation formula for the compressive strength of concrete is established. According to the cumulative sieve residue of coarse aggregates, the void ratio of coarse aggregates, water-binder ratio, paste-aggregate ratio, sand ratio, and 28-day compressive strength of binder material in the concrete mix ratio data, the compressive strength of concrete is estimated by using the estimation formula for the compressive strength of concrete.

[0007] As an optimization, Stata software is used for multiple non-linear regression fitting.

[0008] As an optimization, based on the cumulative sieve analysis of several known coarse aggregates with continuous gradations and the corresponding void ratios of the coarse aggregates, taking the cumulative sieve analysis of each portion of the coarse aggregate as the independent variable and the corresponding void ratio of the coarse aggregate as the dependent variable, the estimation formula for the void ratio of the coarse aggregate is obtained by fitting using the stepwise regression method. Then, based on the cumulative sieve analysis of the relevant coarse aggregates with continuous gradations, the void ratio of the coarse aggregate is estimated using the estimation formula for the void ratio of the coarse aggregate.

[0009] As an optimization, the number of independent variables is increased by raising the order of the cumulative sieve analysis of the coarse aggregate, and then the estimation formula for the void ratio of the coarse aggregate is obtained by fitting using the stepwise regression method. The specific steps are to raise the order of each cumulative sieve analysis to increase the number of independent variables, thereby increasing the sample size, and then using the stepwise regression method to eliminate the collinear variables in the mathematical model to make the mathematical model more concise.

[0010] As an optimization, the order of the cumulative sieve analysis of the coarse aggregate is set to 3 to 5 times.

[0011] Compared with the prior art, the present invention has the following advantages: the present invention reduces labor costs and time costs and improves work efficiency; it can estimate the compressive strength of concrete when the composition materials of the concrete change, thereby guiding practitioners to adjust the concrete mix ratio in a timely manner and improving the construction quality of the concrete; it can also be used as a traceability means when the concrete strength grade does not meet the expectation. When significant quality fluctuations occur under the condition of consistent concrete construction technology, it can be verified according to the present invention to determine whether there is unreasonableness in the concrete mix design, and further adjust and correct the unreasonable part. Specific Embodiments

[0012] 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.

[0013] In the present specific implementation manner, for the multi-factor deduction method of concrete compressive strength based on the grading of coarse aggregates, according to a number of concrete specimens with known cumulative sieve residues of coarse aggregates with continuous gradings, void ratios of coarse aggregates, water-binder ratios, paste-aggregate ratios, sand ratios, 28-day compressive strengths of cementitious materials, and 28-day compressive strengths of concrete, taking the cumulative sieve residues of coarse aggregates, void ratios of coarse aggregates, water-binder ratios, paste-aggregate ratios, sand ratios, and 28-day compressive strengths of cementitious materials as independent variables and the 28-day compressive strength of concrete as the dependent variable, through multiple non-linear regression fitting analysis, a deduction formula for concrete compressive strength is established. According to the cumulative sieve residues of coarse aggregates, void ratios of coarse aggregates, water-binder ratios, paste-aggregate ratios, sand ratios, and 28-day compressive strengths of cementitious materials in the concrete mix proportion data, the compressive strength of concrete is deduced by using the deduction formula for concrete compressive strength.

[0014] In the present specific implementation manner, Stata software is used for multiple non-linear regression fitting.

[0015] In the present specific implementation manner, through a number of known cumulative sieve residues of coarse aggregates with continuous gradings and corresponding void ratio data of coarse aggregates, taking the cumulative sieve residue of each coarse aggregate as the independent variable and the corresponding void ratio of coarse aggregate as the dependent variable, the deduction formula for the void ratio of coarse aggregate is obtained by using the stepwise regression method for fitting, and then according to the cumulative sieve residues of relevant coarse aggregates with continuous gradings, the void ratio of coarse aggregate is deduced by using the deduction formula for the void ratio of coarse aggregate.

[0016] In the present specific implementation manner, the number of independent variables is increased by raising the order of the cumulative sieve residues of coarse aggregates, and then the deduction formula for the void ratio of coarse aggregate is obtained by using the stepwise regression method for fitting.

[0017] In the present specific implementation manner, the order of the cumulative sieve residues of coarse aggregates is set to 4.

[0018] Taking the concrete prepared with 5 - 25mm continuously graded coarse aggregates as an example, the deduction formula model for the 28-day compressive strength of concrete obtained by fitting with the mathematical analysis software Stata is as follows:

[0019] y = b1*X 4 *(X 1 -1 +b2)+b3*lnX 2 +b4*X 3 b5 +b6*X 5 2 +b7*X 6 2 +b8*X 7 2 +b9*X 8 2 +b10*X 9 2 +b11*X 102

[0020] In the formula, the water-binder ratio (x 1 ), the sand ratio (x 2 ), the paste-aggregate ratio (x 3 ), the 28-day compressive strength of the binder (x 4 ), the cumulative sieve residue on the 2.36 mm sieve opening (x 5 ), the cumulative sieve residue on the 4.75 mm sieve opening (x 6 ), the cumulative sieve residue on the 9.5 mm sieve opening (x 7 ), the cumulative sieve residue on the 16 mm sieve opening (x 8 ), the cumulative sieve residue on the 19 mm sieve opening (x 9 ), the void ratio of the coarse aggregate (x 10 ), and the 28-day compressive strength of the concrete (y). b1 to b11 represent the fitting coefficients in the mathematical formula. By fitting these parameters with mathematical software, the fitting results are obtained as shown in Table 1:

[0021]

[0022] Table 1

[0023] After strict fitting analysis, the coefficients of the mathematical model are obtained, and all coefficients show significant statistical significance. At the same time, the goodness of fit R 2 of this formula reaches 0.9899, showing high fitting accuracy and reliability. The selection ranges of the coefficients are as follows:

[0024] b1: [0.3882459~0.4171199] b2: [-1.120701~-0.9285437]

[0025] b3: [-19.88577~-12.21054] b4: [85.42403~116.309]

[0026] b5: [0.1577352~0.2680478] b6: [-0.0069911~-0.004457]

[0027] b7: [-0.000419~-0.0001801] b8: [-0.0007971~-0.0003551]

[0028] b9: [-0.0004783~-0.0001903] b10: [-0.007587~-0.0000503]

[0029] b11: [0.0021239~0.0057581]

[0030] Design different coarse aggregate gradations and conduct 12 groups of concrete experiments to test and verify the concrete strength. The mix proportions of the concrete raw materials are shown in Table 2 as follows:

[0031]

[0032] Table 2

[0033] Among them: the cement grade is P.O42.5; the fly ash is of Class F; the water used is tap water; the fine aggregate is medium sand manufactured sand in Zone II with a fineness modulus of 2.8; the coarse aggregate is crushed stone with a continuous particle size of 5 - 25mm.

[0034] Carry out concrete experiments in combination with the designed test concrete mix proportions, and at the same time conduct mortar experiments on the corresponding cementitious materials' 28 - day compressive strength according to the specifications. After normal curing for 28 days, record the corresponding 28 - day mortar compressive strength and the corresponding concrete 28 - day compressive strength. In addition, according to the designed different coarse aggregate gradations, test their coarse aggregate void ratios. Table 3 shows the experimental verification data:

[0035]

[0036]

[0037] Table 3

[0038] Substitute the respective parameter values of the above - mentioned concrete into the concrete compressive strength deduction formula. The selection of each coefficient value of the deduction formula is as follows:

[0039]

[0040]

[0041] The comparison between the calculated deduction values (unit: MPa) and the measured values (unit: MPa) is shown in Table 4:

[0042]

[0043] Table 4

[0044] Analyzing the content in Table 4 shows that: the absolute error between the deduction value and the measured value of the concrete compressive strength is controlled within ±6MPa, the minimum absolute error is 0.8MPa, and the average absolute error is 2.8MPa. In terms of the relative error, the maximum value is 13.8%, the minimum value is 0.5%, and the average value is 8.2%. In addition, the value of Y deduction / Y measured is between 0.872 and 1.053, indicating that the deduction value has a high degree of accuracy. These numerical results fully confirm that the 28 - day concrete compressive strength deduced by the present invention has a high degree of stability and reliability.

[0045] The above data results show that the estimated value of the compressive strength of concrete calculated by the multi-factor estimation method of the compressive strength of concrete containing coarse aggregate gradation in the present invention has a high correlation coefficient with the measured value of the compressive strength of concrete, and the prediction accuracy and accuracy are high.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described by referring to the preferred embodiments of the present invention, those of ordinary skill in the art should understand that various changes can be made in form and details without departing from the spirit and scope of the present invention defined by the appended claims.

Claims

1. A multi-factor estimation method for concrete compressive strength based on coarse aggregate gradation, characterized by: According to several concrete specimens with known continuous gradation, coarse aggregate fraction, coarse aggregate void ratio, water-binder ratio, mortar-aggregate ratio, sand ratio, 28d compressive strength of cementitious materials and 28d compressive strength of concrete, the estimating formula for the compressive strength of concrete was established through multivariate nonlinear regression fitting analysis, with coarse aggregate fraction, coarse aggregate void ratio, water-binder ratio, mortar-aggregate ratio, sand ratio and 28d compressive strength of cementitious materials as independent variables and 28d compressive strength of concrete as dependent variable. According to the coarse aggregate fraction, coarse aggregate void ratio, water-binder ratio, mortar-aggregate ratio, sand ratio and 28d compressive strength of cementitious materials in the concrete mix proportion data, the compressive strength of concrete was estimated using the estimating formula for the compressive strength of concrete.

2. The multi-factor estimation method for concrete compressive strength based on coarse aggregate gradation according to claim 1 is characterized in that: Stata software was used for multivariate nonlinear regression fitting.

3. The multi-factor estimation method for concrete compressive strength based on coarse aggregate gradation according to claim 1 is characterized in that: Through several known continuous grading coarse aggregate fraction sieve residues and corresponding coarse aggregate void ratio data, with each coarse aggregate fraction sieve residue as the independent variable and the corresponding coarse aggregate void ratio as the dependent variable, the stepwise regression method is used to fit the estimation formula for coarse aggregate void ratio. Then, based on the relevant continuous grading coarse aggregate fraction sieve residues, the void ratio of coarse aggregate is estimated using the estimation formula for coarse aggregate void ratio.

4. The multi-factor estimation method for concrete compressive strength based on coarse aggregate gradation according to claim 3 is characterized in that: The number of independent variables was increased by increasing the order of the coarse aggregate fraction, and then the stepwise regression method was used to fit the estimation formula for the void ratio of coarse aggregate.

5. The multi-factor estimation method for concrete compressive strength based on coarse aggregate gradation according to claim 4 is characterized in that: The order of the coarse aggregate residue is set to 3 to 5 times.

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