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RISS 인기검색어
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- 저자 : Cunbao Zhao (검색결과 2 건)
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Mechanical behavior of coiled tubing over wellhead and analysis of its effect on downhole buckling
Le Zhao,Mingzhong Gao,Cunbao Li,Linyun Xian 국제구조공학회 2022 Steel and Composite Structures, An International J Vol.44 No.2
This study build finite element analysis (FEA) models describing the bending events of coiled tubing (CT) at the wellhead and trips into the hole, accurately provide the state of stress and strain while the CT is in service. The bending moment and axial force history curves are used as loads and boundary conditions in the diametrical growth models to ensure consistency with the actual working conditions in field operations. The simulation diametrical growth results in this study are more accurate and reasonable. Analysis the factors influencing fatigue and diametrical growth shows that the internal pressure has a first-order influence on fatigue, followed by the radius of the guide arch, reel and the CT diameter. As the number of trip cycles increase, fatigue damage, residual stress and strain cumulatively increase, until CT failure occurs. Significant residual stresses remain in the CT cross-section, and the CT exhibits a residual curvature, the initial residual bending configuration of CT under wellbore constraints, after running into the hole, is sinusoidal. The residual stresses and residual bending configuration significantly decrease the buckling load, making the buckling and buckling release of CT in the downhole an elastic-plastic process, exacerbating the helical lockup. The conclusions drawn in this study will improve CT models and contribute to the operational and economic success of CT services.
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Extreme Value Prediction of Traffic Loads Using the Average Conditional Exceedance Rate Method
Liping Zhang,Jianqing Bu,Liming Zhou,Wenlong Cao,Cunbao Zhao,Wei Chai 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.12
An efficient prediction of the extreme value of traffic loads is crucial for the structural design, reliability evaluation, maintenance planning, and further life-cycle cost analysis of bridges. In this work, a novel method is proposed for predicting the appropriate extreme traffic load distribution. Specifically, the average conditional exceedance rate (ACER) statistical model is estimated from the historical traffic loads which was collected through a weigh-in-motion system installed in toll stations. The basic idea of the ACER approach lies in the introduction of a cascade of conditioning approximations and the average exceedance rate to capture the dependence effects and obtain the data tail, the trend features of which are fitted with a similar Gumbel distribution function and extrapolated to the concerned level. An illustration case dealing with traffic loads using the ACER strategy is presented, the extreme value and confidence interval (CI) in any return period can be predicted by application of this approach. Furthermore, the peaks-over-threshold (POT) method based on the asymptotic extreme theory is also applied to illustrate the advantages of the ACER method. The ACER method has advantages in analyzing extreme traffic loads, with good robustness and the ability to handle extreme value prediction for different sampling strategies, it also can produce more accurate confidence intervals and predicts consistent extreme values. The study results are expected to help accurately determine traffic loads and ensure safety in bridge engineering.
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