CN-122021034-A - EPS top surface rebound modulus prediction method based on mechanical analysis software

Abstract

The invention belongs to the field of road, railway or bridge construction, and provides a EPS top surface resilience modulus prediction method based on mechanical analysis software, which comprises the steps of firstly determining the resilience modulus of a backfill layer, the thickness of the backfill layer, the resilience modulus of an EPS block, the thickness of the EPS layer and the elasticity modulus of original soft soil, and then calculating the vertical deformation value of the EPS light roadbed top surface under the influence of the factors by using mechanical analysis software; and then determining the rebound deformation value of the top surface of the EPS light roadbed according to the mechanical properties of the EPS blocks, and constructing an EPS light roadbed top surface rebound modulus estimation model based on multiple linear regression. The model can be directly used for predicting the rebound modulus of the top surface of the EPS light roadbed when the pavement structure is designed.

Inventors

• MA SHIBIN
• CHEN WEI
• SONG YANG
• LI ZIXUAN
• Du Weihan
• HAN SHUO
• LI GUIBIN
• LI YANHONG
• Chang Weichao
• NIU JINGLONG
• WANG WEIHAO
• LIU JIANHUAN

Assignees

• 河北工业大学
• 石家庄市公路桥梁建设集团有限公司
• 河北水利电力学院

Dates

Publication Date

20260512

Application Date

20260203

Claims (5)

1. 1. The EPS top surface rebound modulus prediction method based on the mechanical analysis software is characterized by comprising the following steps of: S1, determining influence factors of EPS light roadbed rebound modulus, and selecting the elastic modulus of a backfill layer, the thickness of the backfill layer, the elastic modulus of an EPS treatment layer, the thickness of the EPS treatment layer and the elastic modulus of a soft soil layer as independent variables; S2, drawing up the independent variable value range in the S1; s3, calculating mechanical response data of the EPS light roadbed top surface under the respective variable coupling; S4, removing the plastic residual deformation part, constructing a stress-strain relation curve in a rebound stage by using the residual rebound deformation part, and calculating to obtain the rebound modulus of the top surface of the EPS light roadbed; s5, determining respective variable weight coefficients based on multiple linear regression, and determining final weights based on contribution degree sequencing and weight coefficients of model error detection; s6, constructing an EPS light roadbed rebound modulus prediction model.
2. 2. The EPS top surface rebound modulus prediction method based on mechanical analysis software according to claim 1, wherein S3 comprises the steps of calculating and extracting stress and rebound strain data of the top surface of the roadbed under each working condition by adopting mechanical analysis software and setting different independent variable combinations, and further calculating corresponding mechanical response data, wherein the mechanical response data comprise first main stress, third main stress and vertical strain.
3. 3. The EPS top surface resilience modulus prediction method based on mechanical analysis software according to claim 1, wherein S4 comprises the steps of removing plastic residual deformation parts of the EPS light roadbed top surface based on mechanical response data of S3, and constructing a stress-strain relation curve of a resilience stage by the residual resilience deformation parts, wherein the plastic residual deformation parts of the EPS light roadbed top surface are 0.5% of the vertical total strain.
4. 4. The method for predicting the rebound modulus of the top surface of the EPS, based on mechanical analysis software, according to claim 1, wherein in S5, determining the weight coefficient of each variable, based on multiple linear regression, comprises: Based on multiple linear regression, constructing an estimated model with independent variables and EPS light roadbed rebound modulus as dependent variables, wherein the estimated model is expressed as: E 0 =β 0 + β 1 E f + β 2 H f + β 3 E EPS + β 4 H EPS + β 5 E S Wherein E 0 represents a predicted value of the rebound modulus of the EPS light roadbed, E f represents the rebound modulus of the backfill layer, H f represents the thickness of the backfill layer, E EPS represents the elastic modulus of the EPS treatment layer, H EPS represents the thickness of the EPS treatment layer, E S represents the elastic modulus of the soft soil layer, and beta 0 to beta 5 are estimated model coefficients determined by regression analysis.
5. 5. The method for predicting the rebound modulus of the top surface of the EPS, based on mechanical analysis software, according to claim 1, wherein in S5, determining the final weight based on the contribution degree ranking and the weight coefficient of the model error check, comprises: The larger the value of the independent variable contribution index I i ：I i = (MAPE i - MAPE 0 ) / MAPE 0 ;I i is calculated, the more the model error rises after the variable is removed, namely the higher the relative contribution of the variable is; The regression coefficient beta corresponding to all five independent variables is the weight coefficient finally confirmed, and MAPE 0 of the full-variable model is required to be lower than a preset engineering acceptable error threshold; And sorting all the independent variables from high to low in contribution degree according to the calculated I i value.

Description

EPS top surface rebound modulus prediction method based on mechanical analysis software Technical Field The invention belongs to the field of road, railway or bridge construction, and particularly relates to an EPS top surface resilience modulus prediction method based on mechanical analysis software. Background Because the resilience modulus of the top surface of the roadbed directly determines the bearing capacity and long-term performance of the road surface structure, in the current EPS light roadbed design, the resilience modulus becomes a core index for evaluating the performance of the roadbed structure due to the key influence of the resilience modulus on the road surface thickness design. And the backfill modulus, EPS layer parameters and soft soil characteristics jointly form a composite system for influencing the rebound modulus of the top surface of the roadbed. However, the determination of the rebound modulus in the current EPS subgrade design mainly depends on empirical values or isolated experiments on backfill materials, and complex interactions formed by the stiffness differences of the EPS layer and the upper soil layer and the lower soil layer cannot be fully considered, so that the design parameters are difficult to accurately reflect the actual stiffness of the subgrade in the actual working state, and the design optimization cannot be scientifically guided. The following problems are presented in detail: (1) The conventional method of determining the modulus of resilience fails to adequately take into account the critical effects of the modulus of the underlying soft soil layer. In an EPS roadbed system, the modulus of a soft soil layer not only directly influences self settlement, but also changes the load transmission path and stress distribution of the whole system through interaction with the EPS layer and a backfill layer, thereby obviously influencing the rebound modulus of the roadbed top surface. Neglecting the systematic modulus coupling effect, only considering the backfill layer property in isolation will lead to significant deviation between the prediction result and the actual situation, and excessive conservation or misjudgment on the soft soil foundation bearing capacity may be caused in design. (2) Relying on empirical values leads to design conservation or risk. Because of the lack of a reliable prediction method, designers often adopt conservative experience values to ensure safety, resulting in material waste and reduced economy, or adopt adventure values for pursuing economy, and increase the early damage risk of the pavement. This "empirically driven" design mode lacks quantitative basis and is difficult to balance between safety and economy. (3) The influence of the multi-parameter cooperative change on the system rigidity cannot be responded. The modulus of resilience is simultaneously influenced by coupling of a plurality of factors such as the modulus of backfill, the thickness of each layer, the EPS modulus, the soft soil modulus and the like, and the interaction among the factors cannot be quantified by the traditional method. For example, increasing EPS thickness to reduce settlement may reduce subgrade top stiffness, and there is a lack of tools in the design to evaluate such trade-off. In view of this, there is a need to develop a method for predicting the rebound modulus of EPS light road beds based on mechanical mechanism and data regression. The prediction model established by the method can systematically reflect the coupling influence of each design variable, and provides accurate and convenient quantitative prediction of the rebound modulus for the design stage, thereby realizing scientific control and optimization design of EPS roadbed structural performance. Disclosure of Invention In order to solve the technical problems, the invention provides a EPS top surface rebound modulus prediction method based on mechanical analysis software, which solves the problems in the prior art, and adopts the following technical scheme: An EPS top surface rebound modulus prediction method based on mechanical analysis software comprises the following steps: S1, determining influence factors of EPS light roadbed rebound modulus, and selecting the elastic modulus of a backfill layer, the thickness of the backfill layer, the elastic modulus of an EPS treatment layer, the thickness of the EPS treatment layer and the elastic modulus of a soft soil layer as independent variables; S2, drawing up the independent variable value range in the S1; s3, calculating mechanical response data of the EPS light roadbed top surface under the respective variable coupling; S4, removing the plastic residual deformation part, constructing a stress-strain relation curve in a rebound stage by using the residual rebound deformation part, and calculating to obtain the rebound modulus of the top surface of the EPS light roadbed; s5, determining respective variable weight coefficients based on