Uncertainty Quantification and Predictive Computational Science
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Uncertainty Quantification and Predictive Computational Science
Ryan G. McClarren
90.94 €
Computer Simulations in Science and Engineering
Juan Manuel Durán
35.30 €
Automatic trend estimation
Calin Vamos, Maria Craciun
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Strukturbildung und Simulation technischer Systeme
Axel Rossmann
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The Uncertainty Analysis of Model Results
Eduard Hofer
96.29 €
246.09 €
Methodologies for Service Life Prediction of Buildings
Ana Silva, Jorge de Brito, Pedro Lima Gaspar
160.49 €
Basic Concepts in Computational Physics
Benjamin A. Stickler, Ewald Schachinger
48.14 €
Statistics and Analysis of Scientific Data
Massimiliano Bonamente
79.99 €
Analyse empirischer und experimenteller Daten
Siegmund Brandt
14.99 €
Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems
Han-Xiong Li, Chenkun Qi
106.99 €
Engineering Analysis
Merle C. Potter
85.59 €
Multivariate Statistical Modelling Based On Generalized Linear Models
Ludwig Fahrmeir, Gerhard Tutz
192.59 €
Computational Methods in Physics
Simon Sirca, Martin Horvat
128.39 €
Uncertainty Quantification and Predictive Computational Science
Ryan G. McClarren
90.94 €
Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment.
The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems.
Uncertainty Quantification and Predictive Computational Scienc e fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by
Ryan McClarren has been teaching uncertainty quantification and predictive computational science to students from various engineering and physical science departments at since 2009. He is currently Associate Professor of Aerospace and Mechanical Engineering at the University of Notre Dame. Prior to joining Notre Dame in 2017, he was Assistant Professor of Nuclear Engineering at Texas A&M University, an institution well-known in the nuclear engineering community for its computational research and education. He has authored numerous publications in refereed journals, is the author of a book that teaches python and numerical methods to undergraduates, Computational Nuclear Engineering and Radiological Science Using Python, and was the editor of a special issue of the journal Transport Theory and Statistical Physics. A well-known member of the computational nuclear engineering community, he has won research awards from NSF, DOE, and three national labs. While an undergraduate at theUniversity of Michigan he won three awards for creative writing. Before joining the faculty of Texas A&M, Dr. McClarren was a research scientist at Los Alamos National Laboratory in the Computational Physics and Methods group.
- Autor: Ryan G. McClarren
- 1st ed. 2018, 364 Seiten, Maße: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3319995243
- ISBN-13: 9783319995243
- Erscheinungsdatum: 05.12.2018
Computer Simulations in Science and Engineering
Juan Manuel Durán
35.30 €
Automatic trend estimation
Calin Vamos, Maria Craciun
53.45 €
Strukturbildung und Simulation technischer Systeme
Axel Rossmann
79.99 €
The Uncertainty Analysis of Model Results
Eduard Hofer
96.29 €
246.09 €
Methodologies for Service Life Prediction of Buildings
Ana Silva, Jorge de Brito, Pedro Lima Gaspar
160.49 €
Basic Concepts in Computational Physics
Benjamin A. Stickler, Ewald Schachinger
48.14 €
Statistics and Analysis of Scientific Data
Massimiliano Bonamente
79.99 €
Analyse empirischer und experimenteller Daten
Siegmund Brandt
14.99 €
Strukturbildung und Simulation technischer Systeme
Axel Rossmann
Statt 79.99 € 19
62.99 €
Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems
Han-Xiong Li, Chenkun Qi
106.99 €
Engineering Analysis
Merle C. Potter
85.59 €
Multivariate Statistical Modelling Based On Generalized Linear Models
Ludwig Fahrmeir, Gerhard Tutz
192.59 €
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