NX Nastran
Design Sensitivity and Optimization with Simcenter Pre/Post (G2H)

Course Code
NXNAS331
Software
NX Nastran 11.0
User Level
Advanced
Pricing ID
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List Price
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Training Center Duration
2 Days

(G2H) Guaranteed to Hold. Select Here for more information about G2H courses.

The Design Sensitivity and Optimization with Simcenter Pre/Post course offers the theoretical and practical aspects of using the NX Nastran sensitivity and optimization capabilities. Sensitivity and design optimization can be used to automate the improvement of a proposed design. The NX Nastran design sensitivity and optimization solution is extremely flexible and allows the user to vary the model parameters to minimize an objective function, such as overall weight, given constraints on both the static and dynamic response. The class will cover the definition of design variables, constraints and objectives in NX Nastran, as well as the interpretation of results. The student will learn to use NX Nastran sensitivity and optimization through the presentation of lecture materials and the completion of example problems. The class is focused on NX Nastran and most of the material applies independently of pre- or postprocessor. However, additional material is available for demonstration of use with Simcenter Pre/Post.

WHO SHOULD ATTEND

This course is intended for finite element analysts who need to optimize the performance of their components or systems, or understand what parameters in the system most strongly affect performance.

PREREQUISITES
PROVIDED COURSE MATERIALS
  • Student Guide
  • Activity Material

This course is no longer offered. Contact us if you would like to schedule a training event at your facility.

For more information
Learning Services, USA

PRIMARY COURSE TOPICS

  • Understanding structural optimization
  • Defining design variables in NX Nastran
  • Defining design constraints in NX Nastran
  • Defining objective functions in NX Nastran
  • Optimization for combinations of static and dynamic loads
  • Interpreting design sensitivity and optimization results