Description Qty Item Price  
your basket is empty

sub total£0.00  
£ $
proceed to checkout

Course Instructors

Dr. François Hemez

Dr. François Hemez has over 10 years of experience in the discipline of Verification and Validation (V&V) and its application to structural dynamics and computational physics. His experience includes finite element model updating for both linear and nonlinear structural dynamics models, code and solution verification, sensitivity analysis, uncertainty quantification, and decision-making. Dr. Hemez has taught the first-ever graduate course on V&V offered in a U.S. University at the University of California San Diego during the spring of 2006. Dr. Hemez is currently a Technical Staff Member of the Verification Team at the Los Alamos National Laboratory.

Dr. Charles "Chuck" Farrar

Dr. Charles “Chuck” Farrar is a world leader in the disciplines of Structural Health Monitoring (SHM) and damage prognosis, where he has pioneered the role of statistical pattern recognition and validated simulations. Dr. Farrar has developed SHM solutions for a variety of engineering applications, many of which are integrated to the course he teaches on SHM at the University of California San Diego. Dr. Farrar has been working at Los Alamos National Laboratory since 1983 where he is the director of the Engineering Institute that develops a multi-disciplinary research and educational program in damage detection, model validation, and life-cycle engineering.

Finite Element Model Validation, Updating, and Uncertainty Quantification for Linear and Non-linear Models

A 2-Day Short Course for Aerospace, Civil and Mechanical Engineers from Oct. 27-28, 2008

Offered in conjunction with the NAFEMS 2008 Regional Summit

 

“Do You Know Everything That You Should About Your Finite Element Model?”

How closely do predictions match the real-world response of the structure?

Is the discretization sufficient to asymptotically converge the numerical solution?

How much do errors in model input parameters impact the accuracy of predictions?

Which of the input parameters have the greatest influence on prediction quantities of interest?

  • Learn the latest techniques for evaluating the accuracy of your models over a range of parameter values.
  • Learn how to design validation experiments that will help determine the model’s true range of validity.
  • Learn how to calibrate your model parameters to reflect the measured response from the experiment — even for non-linear models!

Course Synopsis

When an engineer or analyst builds a finite element model, the results should be trustworthy. But how does one know (and prove quantitatively) that the predictions can be believed with a given level of confidence? Recent research in the areas of solution verification, finite element model validation, sensitivity analysis, uncertainty analysis, and test-analysis correlation has led to the development of a methodology to answer these questions and more, enabling one to use his/her finite element model predictions with confidence. This course will provide an overview of the latest technology for evaluating and improving the accuracy and validity of linear and non-linear finite element models. The course provides a blend of research and real-world applications in the fields of aerospace, automotive, and civil engineering.


Course Goals

Upon completion of this course, attendees will be able to:

  • Describe the model validation paradigm of input-output effect analysis, test/analysis correlation, and uncertainty analysis;
  • Summarize the history of finite element model test/analysis correlation and updating;
  • Conduct code verification, solution verification, and solution self-convergence studies;
  • Describe the process for selecting and computing appropriate response features from the model outputs;
  • Discuss current techniques for global sensitivity analysis and parameter screening;
  • Explain the role of designs of experiments (DOE) and analysis of variance (ANOVA) in model validation;
  • Define appropriate test/analysis correlation metrics for model calibration and revision.

Upon completion of this course, attendees will have learned:

  • The latest techniques for evaluating the accuracy of computational models over a range of parameter values;
  • How to design validation experiments that will help determine the simulation range of validity;
  • How to calibrate model parameters to reflect the measured response from experiments — even for non-linear models!


Course Outline

  • Introduction
  • Historical overview
  • Feature extraction
  • Code verification and solution convergence
  • Uncertainty propagation and quantification
  • Local and global sensitivity analysis
  • Meta-modeling, surrogate modeling
  • Design of validation experiment
  • Test-analysis correlation and validation metrics
  • Model revision and updating
  • Applications for linear and non-linear structural dynamics


 

Sample course notes at www.la-dynamics.com .

Please direct questions to hemez@la-dynamics.com .

The instructors will assume a basic knowledge of structural mechanics, dynamics, and mathematics, such as that obtained in a bachelor’s level aerospace, civil, or mechanical engineering program. To ensure top-quality content, the instructors reserve the right to alter the course schedule. Los Alamos Dynamics is an independent company, not affiliated with the Los Alamos National Laboratory.



Venue, Location and Accomodation

Click for more information on the venue, location and accomodation .


NAFEMS Travel Policy : NAFEMS is not responsible for the purchase of non-refundable airline tickets or the cancellation/change fees associated with canceling a flight. Please call to confirm that the course is running before purchasing airline tickets. NAFEMS retains the right to cancel a course up to 3 weeks before scheduled presentation date.



Your comments


Add your comments

Anonymous on 24th October 2014 - 6:44 pm
Your rating:

Purchasing Details

Members Price
£624 | $1000 | €790


Non-Members Price
£936 | $1500 | €1184
Order Ref: VandV_NAFEMS_NA_2008
Event Type: Course
Location: Hampton, Virginia USA
Date: October 27, 2008

Detailed Course Outline

1. Introduction

  • Description of the model validation process
  • Definition of key terminology
  • Sources of modeling errors, examples of validation studies

2. Historical Overview

  • Discipline specific applications (aerospace, civil, automotive)
  • Linear test/analysis correlation methods
  • Examples in linear and non-linear structural dynamics

3. Code and Calculation Verification

  • Code and solution verification
  • Asymptotic convergence, estimators of convergence
  • Extrapolation, solution error Ansatz, and self-convergence

4. Extraction of Response Features

  • Desirable properties of response features
  • Classification and selection of features
  • Calculation of features, examples in linear and non-linear dynamics

5. Overview of Probability and Statistics

  • Descriptive statistics and their properties
  • Statistical sampling, design of experiments (DOE)
  • Statistical testing, confidence intervals

6. Local and Global Sensitivity Analysis

  • Local sensitivity analysis, derivatives and finite differences
  • Global sensitivity analysis
  • Analysis of variance (ANOVA) and effect screening

7. Meta-modeling

  • Overview of surrogate modeling, meta-model forms
  • Model regression and error estimation
  • Calibration, optimization, and sensitivity studies using meta-models

8. Quantification of Uncertainty

  • Classification of measurement, simulation uncertainty
  • Forward propagation of uncertainty, sampling, DOE
  • Inverse propagation of uncertainty, optimization under uncertainty

9. Design of Validation Experiments

  • What makes validation experiments different from other tests?
  • Experiment design, instrumentation selection and placement
  • Replication, effect blocking, variable screening, experiment uncertainty

10. Test/Analysis Correlation

  • Comparisons between predictions and measurements
  • Definitions of fidelity metrics, correlation metrics
  • How good is good enough?

11. Model Updating and Revision

  • Revising conceptual model forms and assumptions
  • Model parameter calibration, finite element model updating
  • Independent parameter assessment

12. Examples of Model Validation Studies

  • Explosively driven impulse on a threaded interface
  • Modal response, delamination damage of composite plates
  • Simulation of polymer foam impacts, shell buckling, Taylor anvil impacts