1st Edition

Uncertainty Quantification of Stochastic Defects in Materials

By Liu Chu Copyright 2022
210 Pages 158 B/W Illustrations
by CRC Press

210 Pages 158 B/W Illustrations
by CRC Press

210 Pages 158 B/W Illustrations
by CRC Press

Uncertainty Quantification of Stochastic Defects in Materials investigates the uncertainty quantification methods for stochastic defects in material microstructures. It provides effective supplementary approaches for conventional experimental observation with the consideration of stochastic factors and uncertainty propagation. Pursuing a comprehensive numerical analytical system, this book... Read more
1. Overview. 2. Stochastic Defects. Part I: Methods and Theories. 3. Monte Carlo Methods. 4. Polynomial Chaos Expansion. 5. Stochastic Finite Element Method. 6. Machine Learning Methods. Part II: Examples. 7. Numerical Examples. 8. Monte Carlo-based Finite Element Method. 9. Impacts of Vacancy Defects in Resonant Vibration. 10. Uncertainty Quantification in Nanomaterial. 11. Equivalent Young’s Modulus Prediction. 12. Strengthen Possibility by Random Vacancy Defects.

Biography

Dr. Liu Chu received her B.E. degree in Materials Science and Engineering, and M.E. degree in Mechanics from Dalian Maritime University, China, and the Ph.D. in Mechanics from the Institut national des sciences appliquées de Rouen (INSA Rouen), France. Dr. Chu focuses on research in computational material mechanics and structural reliability. Her recent research interests include low-dimensional nanomaterial vacancy defects quantification, artificial material microstructure optimization, and mechanical structure reliability analysis. Since 2018, Dr. Chu has published 18 peer-reviewed science and technical papers in international journals and conferences. She is a member of IEEE and has served as a reviewer of several international journals.