Lecture Notes in Computational Science and Engineering: QUIET selected contributions

D'Elia, Marta; Gunzburger, Max; Rozza, Gianluigi

This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book’s content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors.

Details

Published by: Springer

Publication Date: 2020-07-31

Format: Hardcover

ISBN-13: 9783030487201

DOI: 10.1007/978-3-030-48721-8

Dimensions: 235cm x155cm

Pages: 282