运营公路隧道的变形机理分析及危险性评价

Analysis of Deformation Mechanism and Risk Assessment of Tunnel in Operation

为合理评价运营隧道的安全现状及危险性发展趋势,提出利用BP神经网络和V/S分析构建运营隧道的危险性预测模型。首先,基于运营隧道所处的环境条件,分析其变形机理;其次,根据相关安全等级划分标准,评价运营隧道的安全现状;最后,利用优化BP神经网络构建运营隧道的变形预测模型,再利用V/S分析判断运营隧道的危险性发展趋势,以实现运营隧道的危险性预测。以嬉野隧道为实例进行验证,结果表明:运营隧道的变形影响因素较多,主要包括渗水因素、空洞因素、衬砌劣化因素及长期应力作用因素等;隧道的安全现状等级为Ⅴ级,危险性高,且沉降变形判断得到的危险性等级要高于水平收敛判断得到的危险性等级;变形预测结果和危险性趋势分析结果具有较好的一致性,均得出该隧道的危险性将会进一步增加,验证了BP预测和V/S分析2种模型在运营隧道危险性预测中的适用性和可靠性。研究成果为公路隧道的后期运营提供一定的指导。

Risk prediction models based on BP neural network and V/S analysis are proposed in this paper to evaluate the safety status and risk trend of tunnels under operation.First of all,the deformation mechanism is analyzed in line with the operating environment of the tunnel;secondly,the safety status of tunnel is assessed according to relevant safety classification standard;finally,the deformation prediction model of the tunnel is established using optimized BP neural network,and the risk development trend of tunnel is then examined based on V/S risk analysis.Case study shows that the deformation of tunnel is mainly affected by seepage,cavities,lining deterioration,and long-term stress.The safety status of the tunnel is at level V,high risk,and the risk level acquired based on settlement is higher than that of horizontal convergence.The deformation prediction result is well consistent with trend analysis result which indicates that the risk of the tunnel will further exacerbate.Both the deformation prediction model and the risk trend analysis model are verified applicable and reliable in predicting the risks of tunnel in operation.