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Structural reliability updating using experimental data
Lisha Zhu,Xianzhen Huang,Cong Yuan,Zunling Du 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.1
Conventional reliability analysis requires the information from an existing structure, such as a mechanical model and random distributed inputs. In many engineering problems, a state monitoring system commonly provides experimental or monitoring data, which can be used to update the initial estimation for structural reliability to reduce prediction uncertainty. A critical issue in this process is the manner in which the existing information and new data can be reasonably integrated into a reliability estimation. In this paper, Bayesian updating approach is applied to incorporate the additional data. Firstly, a theoretical model is established to predict the prior distribution of the limit state function (LSF) with the first-order reliability method. Then, the Bayesian inference theory is applied to update the probability distribution parameters of LSF using the acquired experimental or monitoring data. The analytical form of the LSF’s posterior distribution is derived under the assumption that the experimental test error follows a normal distribution. To improve accuracy, a second-order reliability method is proposed based on the theory of saddlepoint approximation. Markov chain Monte Carlo simulation is used to derive a general method for updating the LSF’s distribution using the experimental or monitoring data. Finally, three numerical examples are provided to illustrate the proposed framework’s validity.
Cong Yuan,Lisha Zhu,Shiqi Liu,Du Zunling,He Li 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.2
The flow dynamics of the cavitating jet through poppet valves inevitably suffers from the influence of varying openness, but the relevant mechanism remains unclear. Hence, the present study conducts a numerical study on the cavitating flow phenomenon inside poppet valves with two valve seat structures, in order to examine the flow mechanisms underlying varying cavitation phenomenon at different openness. According to the results, the overall cavitation distribution as well as the morphology feature follows a similar pattern due to the same inception mechanism irrelevant of the openness amount. However, examination of the dynamic behaviors confirms discernable variation in 2 coupling effects between flow instability and cavitation. The flow separation at the poppet trailing edge produces non-cavitation flow instability at 0.4 mm openness and attached cavitation at 0.8 mm, which amalgamate with upstream-shed vortex cavitation. The stably attached cavitation within the chamfered groove at 0.4 mm, as the source of non-cavitation flow instability, and the detached cavitation at 0.6 and 0.8 mm openness produce vortex cavitation at the free shearing side. The substantial variation in these two coupling effects contributes sensibly to the increase in the overall cavitation intensity. Meanwhile, the weakened coupling effect between the free shearing vortex and wall shearing vortex, as a consequence of increased potential core thickness at larger openness, leads to the attenuated vortex cavitation at the wall poppet side. Additionally, the vortex cavitation at free shearing side has a larger size in the chamfered valve seat case, due to the coupling of shed flow instability with the Kelvin-Helmholtz instability. As a conclusion, the inception mechanism for the cavitation remains unchanged with openness, while the difference in flow instabilities as well as the associated coupling effects with cavitation contributes to the variation in cavitation intensity.