Yan Li

Dr. Yan Li


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 May 2023 in Energies
Verified
Journal Article
Open access
PDF file
JZJiqi Zhu
Jiqi Zhu
YLYan Li
Yan Li
WCWenhong Cao
Wenhong Cao
YLYuebing LI
Yuebing LI
ZGZengliang Gao
Zengliang Gao
This study focuses on the critical connection area between type IV hydrogen storage vessels and external valves, which is commonly referred to as the BOSS structure. The novel BOSS structures were proposed to further ensure the safety of pressure vessels. In order to identify optimal structure that meet industrial requirements, finite element models were performed to analyze and compare the effectiveness of the proposed models in terms of strength, fatigue, and sealing performance. Some influences were discussed, including the angle of inclination of the stop-rotation platform and the number of sealing grooves in the BOSS structures. The results showed that the fatigue life of the proposed BOSS structures can exceed the design life of 30,000 cycles using austenitic stainless steel S31603. The maximum contact stresses were higher than the operating pressure of 58 MPa. Additionally, The BOSS structure model designed with a stop-rotation platform featuring a 65° tilt angle and two sealing grooves had the lowest mean square deviation of contact stress, which was 13.47 MPa, indicating reliable sealing performance.

15 May 2024 in Metals
Verified
Journal Article
Open access
PDF file
KTKaikai Tang
Kaikai Tang
YLYan Li
Yan Li
YLYuebing LI
Yuebing LI
WJWeiya Jin
Weiya Jin
JLJiameng Liu
Jiameng Liu
Reactor pressure vessel (RPV) steels are highly susceptible to irradiation embrittlement due to prolonged exposure to high temperature, high pressure, and intense neutron irradiation. This leads to the shift in nil-ductility transition reference temperature—∆RTNDT. The change in ∆RTNDT follows a certain distribution pattern and is impacted by factors including chemical composition, neutron fluence, and irradiation temperature. Existing empirical procedures can estimate ∆RTNDT based on fitting extensive irradiation embrittlement data, but their reliability has not been thoroughly investigated. Probability statistical distributions and the Gamma stochastic process were performed to model material property degradation in RPV steels from a pressurized water reactor due to irradiation embrittlement, with the probability models considered being normal, Weibull, and lognormal distributions. Comparisons with existing empirical procedures showed that the Weibull distribution model and the Gamma stochastic model demonstrate good reliability in predicting ∆RTNDT for RPV steels. This provides a valuable reference for studying irradiation embrittlement in RPV materials.