基于机器学习的分形导数 Maxwell 混凝土徐变模型
|
|
梅生启,李旭峰,王兴举,刘晓东,吴黎明,李星艳,刘哲
|
Machine-learning based fractal derivative Maxwell concrete creep model
|
|
Shengqi MEI,Xufeng LI,Xingju WANG,Xiaodong LIU,Liming WU,Xingyan LI,Zhe LIU
|
|
| 表 1 分形导数黏弹性模型的示意图及应力-应变关系 |
| Tab.1 Schematic diagram and stress-strain relationship of fractal derivative viscoelastic model |
|
| 分形黏弹性模型 | 示意图 | 表达式 | | 分形黏性元件 |  | $\sigma = {\text{ }}\eta \dfrac{{{\text{d}}\varepsilon }}{{{\text{d}}{t^p}}}$ | | 分形Maxwell模型 |  | $\dfrac{{{\text{d}}\varepsilon }}{{{\text{d}}{t^p}}} = \dfrac{1}{E}\dfrac{{{\text{d}}\sigma }}{{{\text{d}}{t^p}}}+\dfrac{\sigma }{\eta }$ | | 分形Kelvin模型 |  | $\dfrac{{{\text{d}}\varepsilon }}{{{\text{d}}{t^p}}}+\dfrac{E}{\eta }\varepsilon = \dfrac{\sigma }{\eta }$ |
|
|
|