Fatigue performance analysis of precast segmental assembled concrete beams
Autor(en): |
Yan Liang
Shun-En Ren Ming-Na Tong Jiang-Nan Zhu Li Yan |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Advances in Structural Engineering, 18 März 2024, n. 6, v. 27 |
Seite(n): | 895-911 |
DOI: | 10.1177/13694332241237573 |
Abstrakt: |
In recent years, assembled bridges have become widely utilized in bridge construction, raising concerns about durability-related bridge diseases over time. These issues significantly impact the fatigue life of assembled bridges, necessitating an in-depth exploration of their fatigue performance. While existing research primarily concentrates on the transverse connection of multiple longitudinal beams, there is a notable dearth of studies on longitudinal precast segmental assembled bridges. This paper addresses this gap by establishing a fatigue benchmark finite element model for segmental assembled concrete beams, building upon existing experiments. The study employs numerical simulation to analyze the entire fatigue process, examining stress distribution, damage development, and considering the influence of reinforcement corrosion. Furthermore, a fatigue life prediction method, based on fatigue residual strength (R), is proposed for predicting the fatigue life (N) of concrete in precast segmental assembled beams. Results reveal that prestressed and ordinary reinforcements experience increasing stress with loading cycles, peaking around 100,000 cycles. Throughout fatigue loading, compressive stress in concrete remains low, preventing fatigue compression failure. However, tensile stress near joints gradually rises, initiating cracks at the mid-span beam’s bottom. With continued cyclic loading, these cracks propagate towards the loading point. The upper and lower limits of fatigue life predicted by the fatigue life prediction method closely align with the compressive fatigue test values of concrete, proposed fatigue life prediction method is efficient and accurate. |
- Über diese
Datenseite - Reference-ID
10770276 - Veröffentlicht am:
29.04.2024 - Geändert am:
29.04.2024