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基于单纯同调全局优化和三轴压缩试验的硬化土模型刚度和强度参数确定

Determination of stiffness and strength parameters for the hardening soil model based on the simplicial homology global optimization and triaxial compressive test.

作者信息

Li Bangxiang, Zhang Youliang, Liu Hao, Wang Zhiqing, Zhao Hongbo

机构信息

School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo, 255000, People's Republic of China.

College of Civil Engineering and Architecture, Hainan University, Haikou, 570228, People's Republic of China.

出版信息

Sci Rep. 2025 Mar 26;15(1):10413. doi: 10.1038/s41598-025-94955-6.

DOI:10.1038/s41598-025-94955-6
PMID:40140686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11947317/
Abstract

Constitute model calibration and their parameter determination are essential to scientifically and accurately characterize soil mechanical behavior. However, this is a challenging task due to the complexity of the geomaterials in geotechnical engineering. This study developed a novel model parameters determination framework combining simplicial homology global optimization (SHGO) and triaxial compressive test. The triaxial compressive test was utilized to generate and record test data, which characterize the constitutive law and cover the mechanical behavior. SHGO was employed to capture the mechanical and failure mechanism by minimizing the discrepancy between the test strain-deviatoric stress curve and that predicted by the hardening soil (HS) model using the unknown model parameters. The developed framework was verified and illustrated by a synthetic example based on the HS model. The results show that the determined strain-deviatoric stress curve is in excellent agreement with the test curve. SHGO performed excellently during the determination of model parameters. Then, the developed framework was applied to an actual triaxial compressive test. The results conclude that the developed framework provides an excellent way to calibrate the model and determine its parameters using optimal technology based on test data. The developed framework provides a scientific, reliable, and promising framework for geomaterials' parameter determination and model calibration.

摘要

本构模型校准及其参数确定对于科学准确地表征土力学行为至关重要。然而,由于岩土工程中岩土材料的复杂性,这是一项具有挑战性的任务。本研究开发了一种结合单纯形同调全局优化(SHGO)和三轴压缩试验的新型模型参数确定框架。利用三轴压缩试验来生成和记录测试数据,这些数据表征本构定律并涵盖力学行为。通过使用未知模型参数最小化测试应变 - 偏应力曲线与硬化土(HS)模型预测曲线之间的差异,采用SHGO来捕捉力学和破坏机制。基于HS模型的一个综合示例对所开发的框架进行了验证和说明。结果表明,所确定的应变 - 偏应力曲线与测试曲线非常吻合。在模型参数确定过程中,SHGO表现出色。然后,将所开发的框架应用于实际的三轴压缩试验。结果表明,所开发的框架提供了一种基于测试数据使用优化技术校准模型并确定其参数的极佳方法。所开发的框架为岩土材料的参数确定和模型校准提供了一个科学、可靠且有前景的框架。

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Cloud inversion analysis of surrounding rock parameters for underground powerhouse based on PSO-BP optimized neural network and web technology.基于粒子群优化-反向传播(PSO-BP)优化神经网络与网络技术的地下厂房围岩参数云图反演分析
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Brittle-ductile transition stress of different rock types and its relationship with uniaxial compressive strength and Hoek-Brown material constant (m).
不同岩性的脆-韧性转变应力及其与单轴抗压强度和霍克-布朗材料常数(m)的关系。
Sci Rep. 2023 Jan 21;13(1):1186. doi: 10.1038/s41598-023-28513-3.
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A novel method for identifying geomechanical parameters of rock masses based on a PSO and improved GPR hybrid algorithm.一种基于粒子群优化算法(PSO)和改进的探地雷达(GPR)混合算法识别岩体地质力学参数的新方法。
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