提前终止累加误差函数粒子群算法应用研究
Application of a Modified Particle Swarm Optimization Algorithm with Early-Stopping Error Function Summation Mechanism
康恒一1
作者信息
- 1. 中国电建集团华东勘测设计研究院有限公司交通市政工程院,浙江杭州 311122
- 折叠
摘要
岩土材料本构模型参数的直接标定要求模型参数具有明确的物理意义且试验数据中有与之对应的几何特征.而针对复杂本构模型中可能存在的超参数,仅能通过参数调节与优化的方式进行标定.优化方式将粒子群算法应用到本构模型参数的标定中,讨论了基于应力-应变曲线进行粒子群标定的技术细节,重点分析了粒子群数量的需求、von Wolfersdorff亚塑性模型和Drucker-Prager弹塑性模型对数据完备性的需求以及算法在用以分析实际试验数据时的行为.针对本问题中误差函数计算过程为累加的特点,对在计算过程中误差函数已经超过其历史最优或函数值溢出的粒子,改进了提前终止应力积分和误差函数累加计算.研究结果显示,提前终止累加误差函数机制对计算效率有显著提升.
Abstract
The direct calibration of constitutive models requires that the model parameters have clear physical significance,which corresponds to the geometric interpretation of the testing data.However,for the complex constitutive models with multiple hy-perparameters,the optimization technique shall be applied to calibrate those parameters.The particle swarm optimization(PSO)was utilized,which can calibrate the model parameters based on raw data of the stress-strain curves.Technical details of properly imple-menting the algorithm were illustrated,which focuses on the quantity of particles,and the data requirements for the von Wolfersdorff hypoplastic model and the Drucker-Prager elastoplastic model.Also,the behavior of the PSO algorithm in analyzing the real experi-mental data was discussed.Since the calculation of the error function is a summation,the stress integration can be terminated for those particles,whose error function has exceeded its historical optimum or reached an overflow state.The early-stopping mechanism was proved to significantly improve computation efficiency.
关键词
粒子群/本构模型/参数标定/启发式算法/岩土材料Key words
particle swarm optimization/constitutive model/parameter calibration/heuristic algorithm/geomaterials引用本文复制引用
出版年
2024
NETL
NSTL
万方数据