内压
失效模式及影响分析
失效机理
机制(生物学)
结构工程
模式(计算机接口)
比例(比率)
材料科学
工程类
计算机科学
复合材料
物理
量子力学
操作系统
摘要
Abstract Prestressed concrete cylinder pipes (PCCP) have been widely used in water conveyance projects, particularly for transregional projects with large diameters and long distances. Ensuring structural safety under complex service conditions is highly important. Internal pressure overload due to water hammering is one of the reasons for structural damage and failure. Current research is primarily focused on vertical internal pressure tests. However, there is insufficient research pertaining to the structural analysis of PCCPs in service that are subjected to internal pressure overload. In this paper, a nonlinear finite element model of PCCP was established and verified by experimental data, and then the model was utilized to investigate the damage to and deterioration of in‐service PCCPs due to internal pressure overload. The results demonstrate that the damage characteristics are different for various components. The more vulnerable positions of the outer materials (outer concrete core, prestressing wires and mortar) are beside the springlines, whereas the inner materials (inner concrete core and cylinder) are over the crown and invert, and the damage to each material extends from the spigot end to the pipe barrel. With increasing internal pressure, each material successively reaches its critical damage value (cracking or yielding), indicating that the PCCP reaches its limit states in turn. The failure mode of a PCCP under pressure overload can be summarized as follows: cracks form over the invert of the inner concrete core, cracks form at the crown of the inner concrete, cracks form beside the springlines of the outer concrete, cracks form at the springlines of the mortar coating, the steel cylinder yields, and finally, the wires yield. The findings provide deep and comprehensive insights into the effects of internal pressure overload and contribute to the structural safety assessment of in‐service PCCPs.
科研通智能强力驱动
Strongly Powered by AbleSci AI