Uncertainty Quantification and Predictive Computational Science A Foundation for Physical Scientists and Engineers /

• Main Author: McClarren, Ryan G. (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Subjects: Physics.; Computer mathematics.; Statistics .; Applied mathematics.; Engineering mathematics.; Mathematical physics.; Computer simulation.; Numerical and Computational Physics, Simulation.; Computational Science and Engineering.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Mathematical and Computational Engineering.; Mathematical Applications in the Physical Sciences.; Simulation and Modeling.

This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-conse...