Jianjun Qin

Dr. Jianjun Qin


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

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

Representative Publications

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20 August 2023 in Reliability Engineering & System Safety
Verified
Journal Article
Closed access
YPYue Pan
Yue Pan
JQJianjun Qin
Jianjun Qin
YHYongmao Hou
Yongmao Hou
JCJin-jian Chen
Jin-jian Chen

24 June 2022 in Applied Energy
Verified
Journal Article
Open access
MLMin Liu
Min Liu
JQJianjun Qin
Jianjun Qin
Dagang LuDagang Lu
Dagang Lu
WZWei-Heng Zhang
Wei-Heng Zhang
JZJiang-Sheng Zhu
Jiang-Sheng Zhu
MFMichael Havbro Faber
Michael Havbro Faber

5 July 2022 in Structural Safety
Verified
Journal Article
Closed access
WZWei-Heng Zhang
Wei-Heng Zhang
JQJianjun Qin
Jianjun Qin
Dagang LuDagang Lu
Dagang Lu
MLMin Liu
Min Liu
MFMichael Havbro Faber
Michael Havbro Faber

8 November 2022 in Mechanical Systems and Signal Processing
Verified
Journal Article
Closed access
WZWei-Heng Zhang
Wei-Heng Zhang
JQJianjun Qin
Jianjun Qin
Dagang LuDagang Lu
Dagang Lu
MLMin Liu
Min Liu
MFMichael Havbro Faber
Michael Havbro Faber

22 November 2022 in Reliability Engineering & System Safety
Verified
Journal Article
Closed access
WZWei-Heng Zhang
Wei-Heng Zhang
JQJianjun Qin
Jianjun Qin
Dagang LuDagang Lu
Dagang Lu
MLMin Liu
Min Liu
MFMichael H. Faber
Michael H. Faber

17 July 2019 in Energies
Verified
Journal Article
Open access
PDF file
JQJianjun Qin
Jianjun Qin
MFMichael Havbro Faber
Michael Havbro Faber
A novel framework for resilience modeling of wind turbine parks is proposed in support of optimization of decisions on asset integrity management. The concept of resilience originating from natural and social sciences is adapted here to facilitate the joint optimization of decision alternatives related to design, with decision alternatives addressing organizational performance. The generic probabilistic systems representation framework by the Joint Committee on Structural Safety (JCSS) (2008) is utilized to establish a scenario-based modeling of how different types of disturbances may lead to damages and failures of systems and sub-systems of wind turbine parks, together with associated direct and indirect consequences. Special emphasis is directed on the consistent probabilistic representation of the uncertainties and the stochastic and causal dependencies within the wind turbine park system. The framework facilitates the identification of optimal asset integrity management decision alternatives that fulfill given requirements to resilience. The potentials associated with the use of the framework are highlighted by an example considering a wind turbine park with ten identical wind turbines, with each modelled as a system of mechanical, electrical, and structural sub-systems. The resilience performance characteristics of the wind turbine park, such as the expected value of generated service life benefits, the expected value of production down time, and the probability of resilience failure are modelled and quantified such as to support the ranking of decision alternatives relating to the design of the wind turbine sub-systems, the level of organizational preparedness, the percentage of the generated service life benefits to be kept to ensure sufficient economic capacity to deal with future disturbances, and the stock-keeping of essential spare parts.