About this Webinar

Engineers always make trade-offs between size, performance, and reliability in engineering product development. Simulation helps make informed decisions early in the design cycle.

This episode starts with a structural finite element model in Ansys LS-DYNA, involving multiple design parameters and focusing on a multi-objective optimization problem. Instead of manually tuning parameters and running tedious iterations in a trial-and-error approach, we'll show how optiSLang parametric workflow directly from Ansys LS-DYNA helps to automate and streamline the optimization process. Optimization and sensitivity studies utilize the latest AI and Machine Learning methods in optiSLang and include linear, nonlinear, and thermal FEA problems. We’ll demonstrate the workflow on a representative issue aligned with typical industrial problems.

What You Will Learn

• Explore the design space with advanced sensitivity analysis
• Make the most use of the simulation Design of the Experiment and use it as the building block for:
  • Optimization with a minimal learning curve
  • Creating a metamodel of optimal prognosis (surrogate model) and finding optimal design faster
  • Accelerating innovation by minimizing non-value-added and repetitive tasks and fully automating the simulation workflows

Who Should Attend

Mechanical (Simulation) Engineers & Analysts in all industries + Academia

Speakers

• Ravi Teja Katragadda