灰色自回归模型对钢纤维混凝土弯曲疲劳强度的预测

Prediction of Gray-autoregressive Model on Bending Fatigue Strength of Steel Fiber Reinforced Concrete(SFRC)

影响混凝土疲劳强度因素的不确定性使材料在最薄弱环节容易造成局部损伤破坏,最终导致整个材料的破坏。因此,随机预测具有一定的现实意义。通过灰色自回归模型和GM(1,1)模型预测钢纤维混凝土(SFRC)弯曲疲劳强度试验值,分析两种方法的预测精度的高低。结果表明,灰色自回归模型预测精度比GM(1,1)模型的精度较高。

Uncertainty of the factors that affect the fatigue strength of concrete is likely to cause local damage and failure in the weakest link of material, eventually leading to the destruction of the entire material. Therefore, the random prediction of fatigue strength of concrete has practical significance. The bending fatigue strength of SFRC is calculated by the gray autoregressive model and GM （1,1） model. Meanwhile, the forecast accuracy of the two models is analyzed by comparing with the calculated values. The results show that forecast precision of gray-autoregressive model is higher than that of GM （ 1,1 ） model.