Production and Reliability Oriented SOFC Cell and Stack Design | Zendy

Martin Hauth | Zendy; V. Lawlor | Zendy; Peter Cartellieri | Zendy; Christopher Zechmeister | Zendy; Sebastian Wolff | Zendy; Christian Bucher | Zendy; Jürgen Malzbender | Zendy; Jianping Wei | Zendy; André Weber | Zendy; Georgios Tsotridis | Zendy; Henrik Lund Frandsen | Zendy; Kawai Kwok | Zendy; Tesfaye Tadesse Molla | Zendy; Zacharie Wuillemin | Zendy; Jan Van herle | Zendy; Fabio Greco | Zendy; Thierry Cornu | Zendy; Arata Nakajo | Zendy; A. Atkinson | Zendy; Luc Vandeperre | Zendy; Xin Wang | Zendy

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Production and Reliability Oriented SOFC Cell and Stack Design

Author(s) -

Martin Hauth,

V. Lawlor,

Peter Cartellieri,

Christopher Zechmeister,

Sebastian Wolff,

Christian Bucher,

Jürgen Malzbender,

Jianping Wei,

André Weber,

Georgios Tsotridis,

Henrik Lund Frandsen,

Kawai Kwok,

Tesfaye Tadesse Molla,

Zacharie Wuillemin,

Jan Van herle,

Fabio Greco,

Thierry Cornu,

Arata Nakajo,

A. Atkinson,

Luc Vandeperre,

Xin Wang

Publication year - 2017

Publication title -

ecs transactions

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.235

H-Index - 52

eISSN - 1938-6737

pISSN - 1938-5862

DOI - 10.1149/07801.2231ecst

Subject(s) - probabilistic logic , robustness (evolution) , design for manufacturability , stack (abstract data type) , reliability engineering , computer science , reliability (semiconductor) , statistical model , engineering , mechanical engineering , machine learning , biochemistry , chemistry , power (physics) , physics , quantum mechanics , artificial intelligence , gene , programming language

The paper presents an innovative development methodology for a production and reliability oriented SOFC cell and stack design aiming at improving the stacks robustness, manufacturability, efficiency and cost. Multi-physics models allowed a probabilistic approach to consider statistical variations in production, material and operating parameters for the optimization phase. A methodology for 3D description of spatial distribution of material properties based on a random field models was developed and validated by experiments. Homogenized material models on multiple levels of the SOFC stack were established. The probabilistic models were related to the experimentally obtained properties of base materials to establish a statistical relationship between the material properties and the most relevant load effects. Software algorithms for meta models that allow the detection of relationships between input and output parameters and to perform a sensitivity analysis were developed and implemented. The capabilities of the methodology is illustrated on two practical cases

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