Neural network model for rheology of rock and soil under step loading

SONG Fei; ZHAO Fa-suo

doi:10.16285/j.rsm.2006.07.034

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Neural network model for rheology of rock and soil under step loading

更新时间：2026-06-25

- Neural network model for rheology of rock and soil under step loading
- Issue 7, Pages: 1187-1190(2006)
- 作者机构：
  
  1. 长安大学地质工程系
  2. 长安大学地质工程系,西安,710054
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2006.07.034
  CLC： TU43
- Published：2006
- 稿件说明：
移动端阅览
[1]宋飞,赵法锁.分级加载下岩土流变的神经网络模型[J].岩土力学,2006(07):1187-1190.

SONG Fei, ZHAO Fa-suo. Neural network model for rheology of rock and soil under step loading[J]. 2006, (7): 1187-1190.
[1]宋飞,赵法锁.分级加载下岩土流变的神经网络模型[J].岩土力学,2006(07):1187-1190. DOI： 10.16285/j.rsm.2006.07.034.

SONG Fei, ZHAO Fa-suo. Neural network model for rheology of rock and soil under step loading[J]. 2006, (7): 1187-1190. DOI： 10.16285/j.rsm.2006.07.034.

摘要

针对分级加载下用线性叠加原理来描述岩土非线性流变存在的问题

采用人工神经网络方法代替传统数学力学方法

建立了分级加载下岩土流变的神经网络模型

并且对具体岩石的蠕变试验曲线进行了模拟。结果表明

该模型能较好地描述岩土的非线性流变

具有较强的泛化能力

为研究岩土的流变特性特别是分级加载下岩土的非线性流变特性提供了一条新途径。

Abstract

In light of the problem of describing nonlinear rheology of rock and soil with principle of linear superposition

a neural network model for rheology of rock and soil under step loading has been established with artificial neural network instead of traditional mathematical and mechanical methods.By simulating the experimental creep curves of gypsum breccias

it is shown that the model can effectively describe nonlinear rheology of rock and soil with better prediction.This approach provides a new way for studying rheological properties of rock and soil especially nonlinear rheological properties under step loading.

关键词

Keywords

references

Views

455

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Neural network model for rheology of rock and soil under step loading

Fractional nonlinear creep constitutive model of salt rock

CT triaxial rheological test on coarse-grained soils

Development of software for nonlinear analysis of single pile response based on load transfer method and its application

Mechanical behavior of sandstone and its neural network simulation of constitutive model considering cyclic drying-wetting effect

Related Author

SONG Fei

ZHAO Fa-suo

WU Fei

LIU Jian-feng

WU Zhi-de

BIAN Yu

ZHOU Zhi-wei

JIANG Jing-shan

Related Institution

Key Laboratory of Energy Engineering Safety and Disaster Mechanics of Ministry of Education, Sichuan University

College of Water Resources and Hydropower, Sichuan University

Langfang Branch, China Research Institute of Petroleum Exploration and Development

School of Civil Engineering, Nanjing Institute of Technology

Key Laboratory of Geotechnical Mechanics and Engineering of Ministry of Water Resources, Yangtze River Scientific Research Institute

AI问答

⁰