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Composites FE Analysis - NAFEMS e-Learning Training Course

Special Note : If you have registered for this course and have not received your course registration information, please contact Matthew Ladzinski (matthew.ladzinski (at) nafems.org).


  

Simulation-Supported Engineering:

Addressing Variability with Stochastic Simulation

October 28th - November 18th, 2009 

Four-Week Training Course

Note: Once you register for the course using the "order" button (look right), you will receive the course attendee packet mentioned in the description below. Please click here to view the FAQ section, or if you need to contact NAFEMS about this course.

 

Course Overview

Today, compute capability is a commodity.  This compute commodity can readily be used by all engineers as a tool to get better information by addressing natural variation.  While using Monte Carlo methods to conduct stochastic simulation have been established and proven, the adoption of this method in mechanical engineering applications is just now starting to be broadly adopted.

This course provides the underlying principals supporting the process for addressing natural variability with Monte Carlo simulation.  The course demonstrates how information can be obtained through simulation – information that can only otherwise be gained through experience. 

The following unique aspects of this process are changing the way we do engineering.  The process:

  • Enables engineers to minimize the number of assumptions made in addressing a problem, as the process is independent of the number of variables.  This encourages incorporating as many variables into a problem as possible, vice making simplifying assumptions that can prevent getting accurate results. 
  • Can generate non-intuitive and unexpected results that provide insight into designs that can otherwise only be learned through test or operations.
  • Scales across engineers, as any engineer can use the process.  This enables transparency and reproducibility in engineering with the means to verify and validate results, providing credibility.

Course Process and Details 

In the current climate travel and training budgets are tight. To help you still meet your training needs the following e-learning course has been developed. The e-learning course runs over a four week period with a single two hour session per week.

This course is completely code independent. No software is required.

Each topic in the class is treated as a building block. The math is kept simple and the emphasis is on practical examples from real life to illustrate the topic. The tutor will be involving the students in the process via Q and A periods during each session, follow up emails and a Course Bulletin Board.   

Students are shown the process for incorporating variation into finite element models, and filtering through the results data generated to get information.  Information generated includes:

  • Identification of the most influential variables,
  • Combinations of variables that cause non-intuitive results, often referred to as outliers,
  • Potential instabilities from having different output states for the same inputs.

Interaction is encouraged throughout the course.  Full notes are provided for the students, together with personal passwords for e-learning backup material, bulletin board access etc.

Students will join the audio portion of the meetings by utilizing the VoIP (i.e. headset connected to the computer via headphone and microphone jacks) or by calling into a standard toll line. If you are interested in additional pricing to call-in using a toll-free line, please send an email to: e-learning @ nafems.org .

Who Should Attend?

This course is aimed at practicing engineers who wish to learn more about how to get valuable information from their analysis efforts.  Ideally a student should have some experience in engineering analysis of computer models, such as Finite Element Analysis or Computational Fluid Dynamics, but this is not essential. The material that is presented is independent of any particular software package, making it ideally suited to current and potential users of all commercial systems. This course is a must for all engineers aiming to use computers as a reliable predictive tool.

E-learning classes are ideal for companies with a group of engineers requiring training. E-learning classes can be provided to suit your needs and timescale. Contact us to discuss your requirements.

Course Program

Note: This is a four-week course. Each session represents one 2-hour session each week. Recordings of each session are made available to course attendees in the event they are unable to participate in one or more of the live meetings, or if they wish to review the material following each session. The times listed for each session are tentative; we try to schedule these sessions at times convenient for the majority of course attendees.

Session 1 – October 28th, 2009 @ 11am EDT (3pm GMT) (daylight savings change) 

Introduction, Overview and Intellectual Foundation

  • Engineering Objectives
  • Information to build knowledge
    • Learning what you do not know
    • Assumptions
  • Computer Models
  • Model Verification
  • Model Analysis Results
  • Model Validation
  • Representation of Reality
  • Monte Carlo Simulation
  • Demonstration

Session 2 – November 4th, 2009 @ 11am EST (4pm GMT)

Randomization and Sampling

  • Review previous session
  • Starting Point
  • Variability
    • Geometry
    • Material Properties
    • Loads, Boundary Conditions
  • Methods
    • Distributions
    • Random Fields
    • Real Data
  • What to randomize
  • Accuracy of Monte Carlo Simulation
  • Latin Hypercube Sampling
  • Parallel Processing
  • Examples

Session 3 – November 11th, 2009 @ 11am EST (4pm GMT)

Understanding Results

  • Review previous sessions
  • Meta-Models
  • Key Characteristics
  • Correlation
  • Advanced Methods
  • Traditional Views
  • Design Structure Matrix Format
  • Outliers
  • Examples

Session 4 – November 18th, 2009 @ 11am EST (4pm GMT)

Design Improvement and Summary

  • Review previous sessions
  • Design Space Exploration Methods
  • Optimization
  • Stochastic Design Improvement
  • Case Studies
  • Understanding and Managing Complexity
  • Change in Engineering Process

Special Note(s):

Telephony surcharges may apply for attendees who are located outside of North America, South America and Europe. These surcharges are related to individuals who join the audio portion of the web-meeting by calling in to the provided toll/toll-free teleconferencing lines. We have made a VoIP option available so anyone attending the class can join using a headset (headphones w/ microphone) connected to the computer. There is no associated surcharge to utilize the VoIP option, and is actually encouraged to ensure NAFEMS is able to keep the e-Learning course fees as low as possible. Please send an email to the e-Learning coordinator (e-learning @ nafems.org ) to determine if these surcharges may apply to your specific case. 

Just as with a live face-to-face training course, each registration only covers one person. If you plan to register a large group (5+), please send an email to e-learning @ nafems.org in advance for group discounts. 


For more information, please email e-learning @ nafems.org .

Details

Event Type: Course
Location: e-Learning Online
Date: October 28, 2009

Course Instructor

Gene Allen became a champion for using stochastic simulation after establishing and managing collaborative R&D programs focused on using computers to do better engineering.  His engineering foundation comes from the Nuclear Navy, where he trained the engineers on U.S.S. Arkansas, CGN-41, and was involved in testing all of the ship’s engineering systems during construction.  His focus on using computers to do better engineering originated in his time on Senator Byrd’s staff and has been pursued through work at the National Center for Manufacturing Sciences and MSC Software.  His collaborative R&D in concurrent engineering, robust design, and rapid response manufacturing involved working with a number of companies including General Electric, Texas Instruments, Ford, GM, Rocketdyne, United Technologies, Eastman Kodak, and numerous technology suppliers with government co-funding from NIST, DAPRA, and NASA.  While at MSC.Software, Mr. Allen trained application engineers and customers in conducting stochastic runs of NASTRAN models.  Mr. Allen returned to the Navy in June 2009 to use simulation to assist in ship design.  


Why an e-Learning Class?

In the current climate travel and training budgets are tight. To help you still meet your training needs the following e-learning course has been developed to complement the live class. The e-learning course runs over a six week period with a single two hour session per week.

E-learning classes are ideal for companies with a group of engineers requiring training. E-learning classes can be provided to suit your needs and timescale. Contact us to discuss your requirements.