The following videos were created by our SIMULIA Central's intern, Sara Jouzdani with the help of Swapan Sanjanwala. The intent is to provide an introduction to Isight. Hope you enjoy!

Part 1 Overview of Abaqus model:

This video provides a short summary of an Abaqus model that was created for an Adapter Duct and will be used in the “Abaqus Component” in other videos. The video explains the Abaqus model with pertinent analysis steps that take material properties, loads, and dimensions as inputs and calculate the maximum stress and mass of the duct.

Part 2.1 Setup of the DOE model and the Results interpretation

This video will guide you through the process of setting up, running, and evaluating the results of a Design of Experiments (DOE) using the Optimal Latin Hypercube technique to understand the design space of the adapter duct.

Part 2.2 Comparative studies of the DOE techniques

This video will provide some information about other DOE techniques such as Orthogonal Arrays. You could examine how the results of this technique are different from Optimal Latin Hypercube technique.

Part 3 Approximation

Approximations (RBF, RSM and Kriging) were created on the adapter duct Abaqus model.  The objective is to create a mathematical model for the specific outputs (Mass and Von Mises stress, in this example) as a function of design variables (thickness of Adapter Duct and material properties, in this example).

Part 4 Optimization

With the creation of approximations in the previous video, we can proceed to identify a better duct design – one that has lower mass and yet has a safety factor greater than 2. In this video we perform the optimization technique to obtain an optimum design point.

Part 5 Six Sigma

In the previous video, we have obtained an optimum design. Although this particular design is optimum, not all manufactured ducts will have identical dimensions due to variations in manufacturing. We need to verify that a substantial number of ducts manufactured will satisfy the safety factor requirement. In order to estimate the fraction of products that satisfy this constraint, we will set up and perform a Six Sigma reliability study. This video will guide you through the process of setting up a reliability analysis.

Part 6 Six Sigma Reliability

In the previous video, we estimated the probability of success to be around 50%. In this step, we will improve the quality level with Six Sigma optimization.

Part 7 I Beam MOOP

In this video, we perform multi-objective optimization on an I-Beam problem to explore the Engineering Data Mining (EDM) tab in Runtime Gateway especially to understand the Pareto family.