康春涛,贡力,王忠慧,等. 利用灰色残差GM(1,1)-Markov模型预测水工混凝土的劣化[J]. 水利水运工程学报,2021(1):95-103. doi: 10.12170/20200228002
引用本文: 康春涛,贡力,王忠慧,等. 利用灰色残差GM(1,1)-Markov模型预测水工混凝土的劣化[J]. 水利水运工程学报,2021(1):95-103. doi: 10.12170/20200228002
(KANG Chuntao, GONG Li, WANG Zhonghui, et al. Prediction of hydraulic concrete degradation based on gray residual GM (1,1)-Markov model[J]. Hydro-Science and Engineering, 2021(1): 95-103. (in Chinese)). doi: 10.12170/20200228002
Citation: (KANG Chuntao, GONG Li, WANG Zhonghui, et al. Prediction of hydraulic concrete degradation based on gray residual GM (1,1)-Markov model[J]. Hydro-Science and Engineering, 2021(1): 95-103. (in Chinese)). doi: 10.12170/20200228002

利用灰色残差GM(1,1)-Markov模型预测水工混凝土的劣化

Prediction of hydraulic concrete degradation based on gray residual GM (1,1)-Markov model

  • 摘要: 我国西北地区水工混凝土建筑物经常受到低温冻害和盐渍侵蚀作用,因此混凝土劣化预测的研究对水工建筑物的寿命预测具有十分重要的意义。为模拟水工混凝土建筑物所受到的破坏,以实验室方法进行混凝土试件的盐冻试验,得到4种工况下混凝土试件随着盐冻次数的增加,其质量和抗压强度的变化情况。研究抽取了其中两种工况的原始数据,首先利用灰色残差GM(1,1)模型对原始数据进行处理,并建立预测模型;然后通过预测模型进行计算,得到质量和抗压强度的修正值;最后通过灰色残差GM(1,1)-Markov模型,对150~200次盐冻试验的试件质量和抗压强度进行预测。结果表明:试件质量和抗压强度的预测值与原始值相比误差较小,说明该模型可较好预测混凝土劣化的质量和抗压强度损失。

     

    Abstract: The hydraulic concrete buildings in northwest China are often affected by low temperature frost and salt erosion, so the study of concrete deterioration prediction is of great significance to the life prediction of hydraulic buildings. In order to simulate the damage of hydraulic concrete buildings, the salt freezing test of the concrete test piece was carried out by laboratory method, and the quality and pressure strength with increase of the salt freezing times under 4 kinds of conditions were obtained. The two of these conditions were extracted from the study as the original data. Firstly, we processed these data by the gray residual GM (1,1) model, and established the prediction model. Then, we obtained the correction value of mass and pressure strength by the prediction model. Finally, we predicted the quality and pressure resistance of 150 to 200 salt freezing tests by the gray residual GM (1,1)-Markov model. The results show that the prediction values of quality and pressure strength have less errors than the original values, and in a certain range, the model can be proved to have good effect on the prediction of the deterioration of concrete and the loss of pressure strength.

     

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