Non-intrusive reduced order modelling of the Navier-Stokes equations

By Dunhui Xiao, Fangxin Fang, Andrew G. Buchan, Christopher C. Pain, Ionel M. Navon, A. Muggeridge. 2015

157 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Civil and Structural Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/0c0fa565e92a84d7cf3714ce4de8f923643d19d0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Karen E. Willcox
2. Benjamin Peherstorfer

In Civil and Structural Engineering

1. Benjamin Peherstorfer
2. Karen E. Willcox

In Statistical and Nonlinear Physics

1. Benjamin Peherstorfer
2. Karen E. Willcox
3. Steven L. Brunton
4. Charbel Farhat
5. Saifon Chaturantabut
6. Max D. Gunzburger
7. Danny C. Sorensen
8. J. Nathan Kutz

Citations in the corpus

• Data-driven operator inference for nonintrusive projection-based model reduction (2016, methodology): “In contrast to projection-based reduced models, data-fit surrogate models are constructed using interpolation and regression techniques to directly learn the map from inputs to outputs of the full model [19, 20, 21, 22].”