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CN-121999932-A - Asphalt mixture mix proportion design method based on response surface method

CN121999932ACN 121999932 ACN121999932 ACN 121999932ACN-121999932-A

Abstract

The invention discloses a method for designing an asphalt mixture mixing ratio based on a response surface method, and aims to solve the problems of strong subjectivity, insufficient optimization and low efficiency and precision of the traditional asphalt mixture mixing ratio design. The method comprises the steps of determining key design variables and response indexes, adopting a central composite design and arrangement experimental scheme in a response surface method, combining a three-control-point hyperbola theory to generate complete mineral aggregate grading, preparing a test piece, testing performance indexes, establishing a quadratic polynomial prediction model, solving an optimal design variable combination through multi-objective optimization, and finally determining an optimal mixing ratio through verification. According to the invention, by means of a mathematical statistics method, the artificial experience interference is reduced, the multi-factor interaction can be accurately quantized, the global optimal mixing ratio is obtained with fewer test times, the material performance potential is maximally exerted, and a scientific and efficient technical support is provided for asphalt mixture design.

Inventors

  • ZHANG HONG
  • WANG CHENG
  • ZHOU TAO
  • CHEN YIMING
  • LI NING

Assignees

  • 西北民族大学

Dates

Publication Date
20260508
Application Date
20260127

Claims (9)

  1. 1. The asphalt mixture mixing proportion design method based on the response surface method is characterized by comprising the following steps of: S1, determining design variables and response indexes, namely selecting 4 design variables with key influences on the volume index and the mechanical property of the asphalt mixture as input factors, wherein the design variables comprise the passing rate of sieve holes with nominal maximum particle size, the passing rate of sieve holes with coarse and fine aggregate demarcation, the passing rate of minimum sieve and the oil-stone ratio; S2, experimental design and grading generation, namely, adopting a central composite design in a response surface method, arranging experimental schemes for 4 design variables, and calculating a complete mineral aggregate grading curve corresponding to each group of experimental schemes based on a three-control-point hyperbola grading construction theory, a simultaneous coarse aggregate exponential function equation and a fine aggregate power function equation to generate a plurality of groups of different synthesized grading; S3, test piece preparation and performance test, namely preparing asphalt mixture test pieces according to the synthetic gradation and the corresponding oilstone ratio generated in the S2 and a standard method, and measuring and calculating 4 actual measurement values of key performance indexes of each group of test pieces; S4, model building and multi-objective optimization, namely, performing multi-element nonlinear regression analysis by using response surface analysis software and taking a design variable as an independent variable and a performance index actual measurement value as a dependent variable, and building a quadratic polynomial prediction model of each performance index; And S5, verifying and determining an optimal blending ratio, namely substituting the design variable optimization value obtained in the step S4 into a three-control point hyperbola model, calculating a final target grading curve, automatically giving out an whetstone ratio after multi-target optimization based on multiple groups of test data through response surface software, preparing a test piece according to the blending ratio, testing performance, comparing an actual measurement value with a model prediction value, and determining that the blending ratio is the optimal asphalt mixture blending ratio if the relative error of each index is in an acceptable range.
  2. 2. The asphalt mixture mix proportion design method based on the response surface method according to claim 1 is characterized in that the nominal maximum particle size sieve opening in S1 is 13.2mm, the coarse and fine aggregate demarcation sieve opening is 4.75mm, the minimum sieve opening is 0.075mm, the design variable has a value range of 95% -100% of sieve opening passing rate of 13.2mm, 27.5% -30.5% of sieve opening passing rate of 4.75mm, 8% -11% of sieve opening passing rate of 0.075mm and 5.8% -6.2% of whetstone.
  3. 3. The method for designing the mix proportion of asphalt mixture based on the response surface method according to claim 1, wherein the central composite design in S2 is 4 factors 5 horizontal design, 30 groups of experimental schemes are arranged in total, and the coarse aggregate exponential function equation is The fine aggregate power function equation is , wherein, The size of the sieve holes is the size of the sieve holes, In order for the pass rate to be high, 、 The obtained coefficient is solved according to the passing rate of the three control points.
  4. 4. The asphalt mixture mix proportion design method based on the response surface method according to claim 1, wherein the test piece prepared by the standard method in the step S3 is a Marshall test piece, and the performance test further comprises a supplementary road performance test, in particular a rutting test, a water immersion Marshall test and a freeze thawing splitting test.
  5. 5. The method for designing the mixing proportion of the asphalt mixture based on the response surface method, which is characterized by comprising the steps of firstly carrying out heat preservation treatment on aggregate for 2-3 hours at the temperature of about 170 ℃ for uniformly heating the aggregate, then placing the aggregate and fiber in a stirring pot for stirring for 90 seconds, adding modified asphalt for stirring for 90 seconds, adding mineral powder for stirring for 90 seconds, placing the mixture into a Marshall compacting die for compacting for 25 times, respectively compacting the front face and the back face for 75 times, naturally cooling the mixture for not less than 6 hours after demoulding, then placing the mixture in a water bath at 60 ℃ for soaking for 40 minutes, and carrying out Marshall stability test on the soaked Marshall test piece to obtain Marshall stability and flow value.
  6. 6. The method for designing asphalt mixture mix proportion based on response surface method according to claim 4, wherein the rutting test is in accordance with standard T0719 of Highway engineering asphalt and asphalt mixture test procedure, the prepared rutting board is cooled at room temperature under 60 ℃ under contact pressure of 0.7Mpa, wherein the matrix asphalt rutting board is not less than 12 hours, the modified asphalt rutting board is not less than 24 hours, after the condition is reached, the rutting board test piece is put into a 60 ℃ testing machine for heat preservation treatment for not less than 5 hours, the 300X 50mm test piece is rolled for 1 hour after the heat preservation treatment is finished, the dynamic stability index is tested, the soaking Marshall test is in accordance with standard T0709 of Highway engineering asphalt and asphalt mixture test procedure, the residual stability after 60 ℃ is tested for 48 hours, the freezing and thawing test is in accordance with standard T9 of Highway engineering asphalt and asphalt mixture test procedure, and the TSR 072 is tested at the loading rate of 50mm/min before and after the freezing and thawing cycle.
  7. 7. The asphalt mixture mix proportion design method based on the response surface method according to claim 1, wherein the response surface analysis software in S4 respectively builds a prediction model for four response indexes, wherein the response rules of porosity, mineral aggregate clearance rate and Marshall stability show obvious secondary nonlinear characteristics, a quadratic polynomial model is adopted for multiple regression fitting, the response relation of asphalt saturation is mainly based on factor interaction, curvature characteristics are not obvious, a two-factor interaction model is selected for description, the corresponding models of porosity, mineral aggregate clearance rate, marshall stability and asphalt saturation are subjected to significance test through variance analysis, and finally the model fitting goodness and prediction capability evaluation result are combined.
  8. 8. The asphalt mixture mix proportion design method based on the response surface method according to claim 1, wherein the constraint conditions in S4 are specifically that the porosity is 3% -4%, the mineral aggregate clearance is greater than 17%, the asphalt saturation is 75% -85%, and the Marshall stability is not less than 8.0kN.
  9. 9. The method for designing the blending ratio of the asphalt mixture based on the response surface method according to claim 1, wherein the acceptable range in the step S5 is that the relative errors of all indexes are less than 5%, and if the relative errors are out of the error range, the method returns to the step S2 to adjust the experimental scheme to carry out the subsequent steps again.

Description

Asphalt mixture mix proportion design method based on response surface method Technical Field The invention relates to the technical field of asphalt mixture design, in particular to an asphalt mixture mixing proportion design method based on a response surface method. Background The scientificity of the mix proportion design of the asphalt mixture serving as a core road construction material of the highway pavement directly determines the bearing capacity, rut resistance, crack resistance and durability of the pavement, thereby influencing the service life and operation safety of highway engineering. Currently, the highway construction of China is developing towards the directions of high grade, long service life and low maintenance, the performance requirements on asphalt mixtures are increasingly severe, the limitations of the traditional mix proportion design method are more remarkable, and the modern engineering requirements are difficult to meet. The traditional asphalt mixture mix proportion design mostly adopts a Marshall design method, the method takes experience as a core, an engineer is relied on to adjust the mineral aggregate grade mix proportion and the asphalt dosage through visual inspection, hand feeling and past construction experience, and the design result has extremely strong subjectivity. The experience difference of different engineers can lead to the fact that the mixing proportion of the same type of mixture has obvious deviation, the unified and quantized design standard is lacking, and then the road construction quality is fluctuated, and the early damage problem easily occurs to partial road sections. Meanwhile, the traditional method can only carry out isolated adjustment on single factors, cannot scientifically analyze complex interaction among a plurality of key factors such as mineral aggregate gradation, asphalt consumption, fiber addition and the like, and can only find qualified proportion in a range limited by specifications instead of global optimal proportion, so that the physical and mechanical properties of raw materials cannot be fully exerted, and the engineering construction and later maintenance cost is indirectly increased. In terms of optimization objectives and experimental efficiency, the conventional design method has a significantly short plate. The optimization target is only focused on meeting the qualification threshold values of basic indexes such as Marshall stability and porosity, a multi-performance index cooperative optimization system is not established, and the designed mixture has a lifting space on the comprehensive performances such as high-temperature stability, water stability and freeze thawing resistance, and is easy to cause pavement diseases such as rutting in summer, water damage in rainy season and freeze thawing cracking in alpine region. In addition, the traditional trial-and-error method or the single-factor rotation method needs to develop a large number of renaturation tests, has long test period and large workload, is difficult to accurately position an optimal region under the combined action of multiple factors, has low design efficiency and is difficult to guarantee precision. The existing partial optimization method is tried to introduce a mathematical statistics tool, but is limited to single-factor or double-factor optimization, and cannot effectively fuse the mineral aggregate grading construction theory and a multi-objective optimization algorithm, so that the coupling influence of each factor on the performance of the mixture cannot be accurately quantified. The response surface method is used as an efficient multi-factor optimization tool, and a nonlinear relation between factors and performance indexes can be constructed in fewer test times through scientific experimental design and mathematical modeling, so that a technical path is provided for solving the defects of the traditional design method. Therefore, a design method for blending ratio of asphalt mixture by combining a response curved surface method and a mineral aggregate grading structure theory is needed, the subjective limitation of the traditional method is broken through, multi-factor collaborative optimization is realized, the design efficiency and the design accuracy are improved, and the high-performance requirement of modern highway engineering on the asphalt mixture is met. Disclosure of Invention The invention aims to overcome the defects of strong subjectivity, insufficient optimization and low efficiency and precision of asphalt mixture mix proportion design in the prior art, and provides an asphalt mixture mix proportion design method based on a response surface method, which realizes multi-factor collaborative optimization by combining mathematical statistics and grading construction theory and improves scientificity, precision and efficiency of mix proportion design. In order to achieve the above purpose, the invention adopts the following techni