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MC133 – Verification and Validation in Scientific Computing (2 day course)
This course presents modern concepts and effective procedures for verification of numerical methods and software, validation of mathematical models, and an introduction to uncertainty quantification of nondeterministic simulations. The mathematical models considered are given in terms of partial differential or integral equations, and any type of numerical method or software package can be used. The techniques presented in this course are applicable to a wide range of engineering and science applications, including fluid dynamics, heat transfer, solid mechanics, structural dynamics, and computational chemistry.
Instructors: Christopher Roy & William Oberkampf
Book(s): Verification and Validation in Scientific Computing, Cambridge University Press (2010)
MC146 – Probabilistic and Uncertainty Quantification Methods for Model Verification & Validation (2 day course)
This course presents the concepts, methods, approaches, and strategies for characterizing and managing uncertainties within the context of model verification and validation (V&V). Uncertainty quantification methods are presented in-depth followed by simple exercises to reinforce the material. Attendees will learn to use the NESSUS probabilistic analysis software and will apply it throughout the course to gain experience in problem formulation, results interpretation and communication. V&V case studies are discussed to illustrate model development within a V&V framework.
Instructors: David Riha and Ben Thacker
ASME Learning & Development is accredited by the International Association for Continuing Education and Training (IACET). ASME Learning & Development complies with the ANSI/IACET Standard, which is recognized internationally as a standard of excellence in instructional practices. As a result of this accreditation, ASME Learning & Development is authorized to issue the IACET CEU.
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