Study of Sensitive Parameters on the Sensor Performance of a Compression-Type Piezoelectric Accelerometer Based on the Meta-Model
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- D. Huang & T. Allen & W. Notz & N. Zeng, 2006. "Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models," Journal of Global Optimization, Springer, vol. 34(3), pages 441-466, March.
- Aneesh Koka & Henry A. Sodano, 2013. "High-sensitivity accelerometer composed of ultra-long vertically aligned barium titanate nanowire arrays," Nature Communications, Nature, vol. 4(1), pages 1-10, December.
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Keywords
accelerometer; compression-type; finite element method; piezoelectric analysis; meta-model;All these keywords.
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