Sensitivity Analysis — Lesson 4

In this lesson, we will learn how to set up the sensitivity analysis for our example problem using the Adaptive Metamodel of Optimal Prognosis (AMOP) approach and post-processing of the results. This lesson explains the three-step process of the Sensitivity Analysis process using Ansys optiSLang® process integration and design optimization software. This includes the generation of a Design of Experiments (DoE), creating Metamodels and then finalizing the Metamodel of Optimal Prognosis (MOP) characterised by the highest Coefficient of Prognosis (CoP). Following the discussion of the three-step process, we will learn about the AMOP approach which refines the DoE based on the quality of the metamodel, automatically running new simulations where necessary to improve the metamodel’s quality.

Alternate video link.

Video Highlights

00:07 – Introduction

01:05 – Understanding sensitivity analysis and AMOP

04:05 – Setting up sensitivity analysis using Sensitivity Wizard

06:41 – Postprocessing

11:37 – Summary