Advanced LS-OPT Deterministic & Probabilistic Optimization
This course is intended to help engineers with a basic knowledge of LS-DYNA and LS-OPT to become proficient in advanced optimization and probabilistic design methods. With this course we hope for you to become more productive at design and parameter identification of complex systems, such as multidisciplinary systems with competing objectives, advanced material testing and models, and systems with discontinuous responses. We will also provide insight into reliability and robustness to facilitate higher quality product design. Additionally, we will introduce classification-based adaptive sampling constraints as a tool for enhancing the efficiency.
In this course, we will discuss both the theoretical and practical aspects of design. We will cover advanced topics, such as multi-objective and collaborative optimization, digital image correlation, statistical classification, and probabilistic optimization. During workshop sessions, we will apply the discussed theoretical topics. We will use the LS-OPT graphical user interface to teach input preparation and post-processing. We will also emphasize interfacing with LS-DYNA.
Following the completion of this course, you will be able to:
- Calibrate unknown material model and system parameters using Digital Image Correlation (DIC).
- Perform multi-objective and collaborative optimization.
- Use classification-based constraint approximation to handle discontinuous and binary responses, and to perform adaptive sampling.
- Perform reliability analysis using Monte Carlo analysis.
- Perform probabilistic design and tolerance optimization to improve product reliability and robustness.
- Identify outliers and sources of uncertainty in design.
- Required: Basic knowledge about direct and metamodel-based optimization and result analysis using LS-OPT.
- Strongly recommended: Introduction to LS-OPT class since it provides a foundation for some of the advanced topics.
- Recommended but not required: An introductory class in LS-DYNA for familiarity with a few keywords.
Target Audience: CAE Engineers, Mechanical Engineers including Automotive Engineers, Aerospace Engineers, Biomechanical Engineers, and other subdisciplines, Students, and Academic Researchers.
Teaching Method: The teaching method is simple and practical to reduce the barrier to learn advanced topics. The class relies on simple class-room introduction of advanced topics in simple and incremental way to make it easier to understand all topics
Learning Options: Training materials for this course are available with an Ansys Learning Hub Subscription. If there is no active public schedule available, private training can be arranged. Please contact us.
Agenda SUBSCRIBE TODAY
|Date/Time||Duration||Event Type||Location||Language||Class Cost|
Sorry, no classes were found that matched your country selection. Subscribe today to take online courses.
Sorry, no classes were found that matched your country selection. Please try again or Subscribe today to take online courses.