摘要
荷载条件、环境条件以及沥青混合料本身性质都会影响沥青混合料的疲劳性能。而疲劳试验所得出的疲劳方程不能反映众多因素对沥青混合料疲劳性能的影响。将荷载间歇时间、加载频率、试验温度、沥青混合料空隙率、沥青软化点、沥青用量等6个影响因素适当组合,在MTS材料试验系统上进行了不同条件下的应力控制的疲劳试验;然后,运用遗传算法和神经网络理论来考虑各因素对沥青混合料疲劳性能的影响,得出一种较为完善的沥青混合料疲劳性能的预测模型。
Factors that influence of load term, environment term and the material of asphalt mixtures oneself on the fatigue properties of asphalt mixture. Six factors consist of load intermission, load frequency,Temperature, voids of mixture asphalt softening index and dosage of asphalt were assembled properly by means of fatigue test under different conditions of control stress on the MTS810, and based on the theory of Artificial neural network and genetic arithmetic, the prediction model of asphalt mixtures＇fatigue properties was put forward.The result shown that this approach is scientific and feasible completely, its prediction is accurate.
出处
《市政技术》
2006年第1期31-33,62,共4页
Journal of Municipal Technology
关键词
沥青混合料
疲劳性能
影响因素
神经网络
遗传算法
预测模型
Asphalt mixtures
Fatigue properties
Effect factors
Neural net work
Genetic arithmetic
Prediction model
