Reduced-order model for microstructure evolution prediction in the electrodes of solid oxide fuel cell with dynamic discrepancy reduced modeling

JOURNAL OF POWER SOURCES

卷:416

Article

Lei, Yinkai^1,2  Chen, Tian-Le^1,3  Mebane, David S.⁴  Wen, You-Hai¹ 

[1] US DOE, Natl Energy Technol Lab, Albany, OR 97321 USA

[2] Oak Ridge Inst Sci & Educ, Oak Ridge, TN 37831 USA

[3] AECOM, POB 618, South Pk, PA 15129 USA

[4] West Virginia Univ, Dept Mech & Aerosp Engn, Morgantown, WV 26506 USA

关键词: SOFC degradation;    Microstructure evolution;    Reduced order model;    Dynamic discrepancy reduced modeling;    Bayesian calibration;    Phase-field simulation;   

DOI  :  10.1016/j.jpowsour.2019.01.046

来源: Elsevier

【 摘 要 】

Microstructure evolution in the electrodes of solid oxide fuel cell is an important degradation mechanism which reduces active sites for redox reaction and the electric conductivity. Phase field models for microstructure evolution simulation are usually expensive for large scale simulations. In this work, a reduced-order coarsening model is developed using dynamic discrepancy reduced modeling, which reduces the model order by inserting Gaussian process stochastic functions into the dynamic equations of Ostwald ripening. The reduced order model has been calibrated on a dataset generated by a phase field model that has been well validated to experiments. A validating dataset has also been generated with which the model prediction show good agreement. This model is further applied to predict long term microstructure evolution in different SOFC electrodes. This work is the first attempt of building a degradation model of SOFC using data science techniques.

【 授权许可】

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