Fundamentals of Uncertainty Quantification for Engineers: Methods and Models

Author:   Yan Wang, Ph.D (Professor of Mechanical Engineering, Georgia Institute of Technology, USA.) ,  Anh.V. Tran, Ph.D. (Research Staff Member, Department of Scientific Machine Learning, Sandia National Laboratories, USA.) ,  David L. Mcdowell, Ph.D. (Georgia Institute of Technology,)
Publisher:   Elsevier - Health Sciences Division
ISBN:  

9780443136610


Pages:   434
Publication Date:   27 June 2025
Format:   Paperback
Availability:   In Print   Availability explained
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Fundamentals of Uncertainty Quantification for  Engineers: Methods and Models


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Author:   Yan Wang, Ph.D (Professor of Mechanical Engineering, Georgia Institute of Technology, USA.) ,  Anh.V. Tran, Ph.D. (Research Staff Member, Department of Scientific Machine Learning, Sandia National Laboratories, USA.) ,  David L. Mcdowell, Ph.D. (Georgia Institute of Technology,)
Publisher:   Elsevier - Health Sciences Division
Imprint:   Elsevier - Health Sciences Division
Weight:   0.450kg
ISBN:  

9780443136610


ISBN 10:   0443136610
Pages:   434
Publication Date:   27 June 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Dr. Yan Wang is a Professor of Mechanical Engineering at the Georgia Institute of Technology. He leads the Multiscale Systems Engineering Research Group at Georgia Tech. His research interests include probabilistic and non‐probabilistic approaches to quantify uncertainty in both physics‐based and data‐driven models for multiscale systems engineering for materials design. He has over 200 publications, including the first book on uncertainty quantification in multiscale materials modelling co‐edited with David McDowell. Dr. Anh V. Tran is a research staff member at the Department of Scientific Machine Learning, Sandia National Laboratories. His research areas include uncertainty quantification, optimization, machine learning for multiscale computational materials science. David L. McDowell Ph.D. is Regents’ Professor Emeritus at the Georgia Institute of Technology, having joined Georgia Tech as a faculty member in 1983. His research focuses on multiscale modelling of materials with emphasis on multiscale modeling of the inelastic behavior of metals, microstructure-sensitive computational fatigue analysis of microstructures, methods for materials design that are robust against uncertainty, and coarse-grained atomistic modelling methods.

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