Response Surface Method for Burgers Model Slope Soil Parameters
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Solution Overview
Problem
Current methods for identifying rheological parameters of creep soil slopes, such as the Burgers model, face challenges in accurately determining stratum stress states, leading to limited application of positive analysis methods and requiring extensive data collection for inverse analysis, which is resource-intensive.
Innovation Solution
A response surface method is employed to identify Burgers model parameters for slope soil, involving laboratory tests, numerical simulations, and displacement monitoring, using Box-Behnken design and polynomial regression to optimize parameter identification, reducing the need for extensive data collection and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If artificial intelligence methods (neural network, particle swarm optimization) are used for inverse displacement analysis, then the method can be applied without accurate stress state knowledge, but a lot of learning samples are needed consuming extensive manpower and material resources
Solution Approach 1:
The patent changes the approach from using artificial intelligence methods that require large datasets to using response surface methodology that requires a limited number of designed experiments. By transforming the parameter identification problem into a response surface optimization problem with a small number of calculated points, the method achieves accurate parameter identification without needing extensive learning samples, thus resolving the contradiction between adaptability and data quantity requirements.
2Measurement precision
If positive analysis method is used for parameter identification, then accurate stress state knowledge is required, but it is difficult to accurately obtain the actual stratum stress state limiting practical application
Solution Approach 1:
The patent applies inverse analysis instead of positive analysis to identify Burgers model parameters. By using displacement monitoring data and response surface methodology to invert the constitutive relationship, the method eliminates the need for accurate stress state measurement while maintaining parameter identification accuracy, thus resolving the contradiction between measurement precision and practical applicability.
3Measurement precision
If extensive laboratory tests and monitoring data are collected for inverse analysis, then parameter identification accuracy can be improved, but manpower and material resources are consumed
Solution Approach 1:
The patent performs preliminary action by designing a small number of calculated points (27 points in the Box-Behnken design) that cover the parameter space before actual field measurements are taken. This preliminary design allows the response surface to be constructed efficiently, and subsequent field monitoring only needs to provide a few displacement data points to complete the parameter identification, significantly reducing the time and resources needed compared to traditional extensive testing approaches.
Data Source
AI summary
The invention claims a response surface method for identifying the parameters of Burgers model for slope soil, comprising the following steps: determine the model parameters and the level thereof; determine the parameter combination and the test sequence of the numerical test; calculate the response equation; optimally identify the model parameters. Based on the combination of the laboratory test, the numerical simulation and the field monitoring, the response surface analysis method is adopted in the invention to determine the regression equation for the parameters of Burgers model and the slope surface displacement, and meanwhile the regression analysis is adopted to establish the optimal parameter combination.