Why Uncertainty Quantification Matters

Understanding the impact of variability in design parameters and material properties is essential in engineering simulation. Uncertainty Quantification (UQ) enables engineers to evaluate robustness, reliability, and risk in their models. By integrating Abaqus with Isight, simulation-driven design exploration can be achieved through statistical techniques like Design of Experiments (DoE), response surface modeling, and Monte Carlo simulations.

Webtraining Focus

This webtraining introduces the fundamentals of UQ and how to implement it using Abaqus and Isight. Participants will gain insights into the workflow of parametric studies, probabilistic modeling, and data analysis using automated simulation frameworks.

Topics Covered

• Introduction to Uncertainty Quantification (UQ) principles

• Overview of Isight and its role in process automation

• Running Design of Experiments (DoE) and sensitivity studies

• Creating and validating meta-models (e.g., response surfaces, kriging)

• Setting up Monte Carlo simulations to assess variability and risk

• Coupling Isight with Abaqus for parametric loop simulations

• Visualizing results: scatter plots, correlation matrices, response histograms

What You Will Gain?

• Practical understanding of UQ tools in Isight and Abaqus

• Ability to automate large sets of simulations for design assessment

• Experience with metamodeling and Monte Carlo techniques

• Increased confidence in making data-driven design decisions

Who Should Attend?

• Simulation engineers using Abaqus looking to integrate statistical methods

• Analysts interested in design robustness and reliability assessment

• Engineers exploring advanced optimization and DoE workflows

• Researchers applying stochastic methods in material and structural modeling