Computational Modeling by Case Study

All Models Are Uncertain

Zachary del Rosario, Gianluca Iaccarino (Autoren)

Buch | Hardcover

848 Seiten

2024 | Unabridged edition
Cambridge Scholars Publishing (Verlag)
978-1-0364-0291-4 (ISBN)

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Mathematical models power the modern world; they allow us to design safe buildings, investigate changes to the climate, and study the transmission of diseases through a population. However, all models are uncertain: building contractors deviate from the planned design, humans impact the climate unpredictably, and diseases mutate and change. Modern advances in mathematics and statistics provide us with techniques to understand and quantify these sources of uncertainty, allowing us to predict and design with confidence.This book presents a comprehensive treatment of uncertainty: its conceptual nature, techniques to quantify uncertainty, and numerous examples to illustrate sound approaches. Several case studies are discussed in detail to demonstrate an end-to-end treatment of scientific modeling under uncertainty, including framing the problem, building and assessing a model, and answering meaningful questions. The book illustrates a computational approach with the Python package Grama, presenting fully reproducible examples that students and practitioners can quickly adapt to their own problems.

Zachary del Rosario is an assistant professor of engineering and applied statistics at Olin College (USA), an engineering college focused on pedagogical innovation. He received his PhD from Stanford University (USA) in 2020. Professor del Rosario is the maintainer of the software package Grama, and has used this software to teach advanced uncertainty quantification (UQ) techniques to undergraduate students. He has published several technical articles on UQ and statistics. Gianluca Iaccarino is the Director of the Institute for Computational Mathematical Engineering (USA) and a professor in the Mechanical Engineering Department at Stanford University (USA). He received his PhD at the Politecnico di Bari (Italy) and worked for several years at the Center for Turbulence Research (NASA Ames & Stanford, USA). He is the Director of the Predictive Science Academic Alliance Program Center at Stanford, funded by the US Department of Energy, which focusses on multiphysics simulations, uncertainty quantification and exascale computing. In 2010, he received the Presidential Early Career Award for Scientists and Engineers (PECASE) award.

Erscheinungsdatum	10.05.2024
Verlagsort	Newcastle upon Tyne
Sprache	englisch
Maße	148 x 212 mm
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Themenwelt	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
ISBN-10	1-0364-0291-6 / 1036402916
ISBN-13	978-1-0364-0291-4 / 9781036402914
Zustand	Neuware