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24 September 2013 Photovoltaic lifetime and degradation science statistical pathway development: acrylic degradation
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Abstract
In order to optimize and extend the life of photovoltaics (PV) modules, scienti c and mechanistic statistical analytics must be performed on a large sample of materials, components and systems. Statistically signi - cant relationships were investigated between di erent mechanistically based variables to develop a statistical pathway diagram for the degradation of acrylic that is important in concentrating photovoltaics. The statisti- cally signi cant relationships were investigated using lifetime and degradation science using a domain knowledge semi-supervised generalized structural equation modeling (semi-gSEM. Predictive analytics and prognostics are informed from the statistical pathway diagram in order to predictively understand the lifetime of PV modules in di erent stress conditions and help with these critical lifetime technologies.
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Laura S. Bruckman, Nicholas R. Wheeler, Ian V. Kidd, Jiayang Sun, and Roger H. French "Photovoltaic lifetime and degradation science statistical pathway development: acrylic degradation", Proc. SPIE 8825, Reliability of Photovoltaic Cells, Modules, Components, and Systems VI, 88250D (24 September 2013); https://doi.org/10.1117/12.2024717
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