27th Conference of the International Linear Algebra Society (ILAS 2026)

Improving prediction for a low rank tensor ROM via continuous data assimilation

May 20, 2026, 11:25 AM

25m

Torgersen Hall 1060

Minisymposium Talk Recent Advances in Tensor Decompositions for Model and Data Reduction Recent Advances in Tensor Decompositions for Model and Data Reduction

Speaker

Prof. Leo Rebholz (Clemson University)

Description

We extend a low rank tensor ROM recently developed by Olshanskii et al by enhancing it with continuous data assimilation (CDA). We show how CDA is easily incorporated into the ROM, and analytically show that it provides for theoretical long time error estimates. Numerical tests illustrate the theory and show it is an effective tool for simulating incompressible flow over a wide range of Reynolds numbers.