Short Course

Short course on Model Order reduction for Complex Multi-scale problems @ AFRL Dayton 

Aug 29/30/31 2023

AFRL POC: Dr. Ramakanth Munipalli

The goal of this workshop is two-fold:

a) Introduce data-driven and reduced order modeling, and

b) Present leading-edge research performed under the Air Force Center of Excellence project to AFRL and various DoD stakeholders.

• The first day is on foundational concepts in Linear algebra

• The second day introduces basics of data-driven & reduced order modeling.

• The third day covers advanced topics.

Slides are below (click on the underlined links)

-----Day 1-----

1. Introduction (K. Duraisamy, U. Michigan)

2. Basics of Linear Algebra (K. Duraisamy, U. Michigan)

-----Day 2-----

3. Intro to Projection-based ROMs (B. Peherstorfer, NYU)

4. Linear Model Order Reduction (E. Rezaian, U. Michigan)

5. Learning dynamical systems from data (I. Farcas, UT Austin)

6. Introduction to adaptive basis and sampling (B. Peherstorfer, NYU)

7. ROM code demo   (E. Rezaian, U. Michigan)

-----Day 3-----

8. Robust ROMs for Complex Multi-scale problems (K. Duraisamy, U. Michigan)

9. Non-intrusive ROMs for large scale applications  (I. Farcas, UT Austin)

10. Adaptive ROMs for complex problems (C. Huang, U. Kansas)

11. Multi-component ROMs (C. Huang, U. Kansas)

Appendix

2D RDE startup  : Movie that shows a 2D rotating detonation engine simulation in which the ROM is initialized (trained)  from (almost) quiescent conditions, and develops a system of shocks in predictive model