***THE UPDATED SHORT COURSE***
Experimentation, Validation and Uncertainty Analysis
This cutting-edge, comprehensive, two-day course has been updated to include revisions made in preparing the new 4th edition (2018) of their award-wining book, and it emphasizes the Monte Carlo Method of propagation which has become the method of choice in recent years. The course presents experimental uncertainty analysis and verification and validation concepts and techniques based on current standards such as:
The course covers the planning, design, debugging, and execution of experiments used to validate a model or simulation, solve a particular problem, or experimentally characterize the behavior of a system. Cases in which the experimental result is determined only once and in which the result is determined multiple times in a test are addressed and illustrated with examples from the authors’ experience. The important practical cases in which multiple measured variables share correlated errors are discussed in detail, and strategies to take advantage of such effects in calibrations and comparative testing situations are presented. The latest V&V standards are discussed and incorporated throughout the course.
WHO SHOULD ATTEND
Knowledge of the materials in this course is a must for those involved in managing or executing experimental programs or involved in the validation of models, codes, and simulations. Past course participants have ranged from those with fresh B.S. degrees in engineering and the sciences to those with advanced degrees in fields from engineering, physics, and medicine to geography and applied mathematics.
contact: info@uncertainty-analysis.com
Experimentation, Validation and Uncertainty Analysis
This cutting-edge, comprehensive, two-day course has been updated to include revisions made in preparing the new 4th edition (2018) of their award-wining book, and it emphasizes the Monte Carlo Method of propagation which has become the method of choice in recent years. The course presents experimental uncertainty analysis and verification and validation concepts and techniques based on current standards such as:
- the 1995 ISO Guide to the Expression of Uncertainty in Measurement (GUM),
- the 2008 JCGM Supplement 1 to the GUM: Evaluation of Measurement Data – Propagation of Distributions Using a Monte Carlo Method, and
- the 2009 ASME Standard V&V-2009: Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer.
- the ASME Standard PTC19.1-2018 Test Uncertainty
The course covers the planning, design, debugging, and execution of experiments used to validate a model or simulation, solve a particular problem, or experimentally characterize the behavior of a system. Cases in which the experimental result is determined only once and in which the result is determined multiple times in a test are addressed and illustrated with examples from the authors’ experience. The important practical cases in which multiple measured variables share correlated errors are discussed in detail, and strategies to take advantage of such effects in calibrations and comparative testing situations are presented. The latest V&V standards are discussed and incorporated throughout the course.
WHO SHOULD ATTEND
Knowledge of the materials in this course is a must for those involved in managing or executing experimental programs or involved in the validation of models, codes, and simulations. Past course participants have ranged from those with fresh B.S. degrees in engineering and the sciences to those with advanced degrees in fields from engineering, physics, and medicine to geography and applied mathematics.
contact: info@uncertainty-analysis.com