Liu Dunwen, Chen Haofei, Tang Yu, Gong Chun, Jian Yinghua, Cao Kunpeng
School of Resources and Safety Engineering, Central South University, Changsha 410000, China.
Materials (Basel). 2021 Oct 8;14(19):5904. doi: 10.3390/ma14195904.
Sulfate erosion is a major cause of concrete durability deteriorations, especially for the service tunnels that suffer sulfate erosion for a long time. Accurately predicting the concrete damage failure under sulfate erosion has been a challenging problem in the evaluation and maintenance of concrete structures. Here we design the dry-wet cycle test of service tunnel concrete under sulfate erosion and analyze the Elastic relative dynamic modulus (Erd) and mass under 35 times cycle periods. Then we develop an autoregressive integrated moving average (ARIMA) prediction model linking damage failure to Erd and mass. The results show that the deterioration of concrete first increased and then decreased with an extension of the dry-wet cycle period. Moreover, based on a finite set of training data, the proposed prediction approach shows high accuracy for the changes of concrete damage failure parameters in or out of the training dataset. The ARIMA method is proven to be feasible and efficient for predicting the concrete damage failure of service tunnels under sulfate erosion for a long time.
硫酸盐侵蚀是导致混凝土耐久性劣化的主要原因，对于长期遭受硫酸盐侵蚀的运营隧道而言尤其如此。在混凝土结构的评估和维护中，准确预测硫酸盐侵蚀作用下混凝土的损伤破坏一直是一个具有挑战性的问题。在此，我们设计了运营隧道混凝土在硫酸盐侵蚀环境下的干湿循环试验，并分析了35个循环周期下的弹性相对动模量（Erd）和质量。然后，我们建立了一个自回归积分滑动平均（ARIMA）预测模型，将损伤破坏与Erd和质量联系起来。结果表明，随着干湿循环周期的延长，混凝土的劣化程度先增大后减小。此外，基于有限的训练数据，所提出的预测方法对于训练数据集内外混凝土损伤破坏参数的变化均显示出较高的准确性。事实证明，ARIMA方法对于长期预测硫酸盐侵蚀环境下运营隧道混凝土的损伤破坏是可行且高效的。
