switching criterion
Recently Published Documents


TOTAL DOCUMENTS

31
(FIVE YEARS 0)

H-INDEX

7
(FIVE YEARS 0)

2020 ◽  
Vol 36 (5) ◽  
pp. 675-689
Author(s):  
A. Salazar ◽  
F. Xiao

ABSTRACTExisting numerical schemes used to solve the governing equations for compressible flow suffer from dissipation errors which tend to smear out sharp discontinuities. Hybrid schemes show potential improvements in this challenging problem; however, the solution quality of a hybrid scheme heavily depends on the criterion to switch between the different candidate reconstruction functions. This work presents a new type of switching criterion (or selector) using machine learning techniques. The selector is trained with randomly generated samples of continuous and discontinuous data profiles, using the exact solution of the governing equation as a reference. Neural networks and random forests were used as the machine learning frameworks to train the selector, and it was later implemented as the indicator function in a hybrid scheme which includes THINC and WENO-Z as the candidate reconstruction functions. The trained selector has been verified to be effective as a reliable switching criterion in the hybrid scheme, which significantly improves the solution quality for both advection and Euler equations.


2013 ◽  
Vol 102 (9) ◽  
pp. 092905 ◽  
Author(s):  
Y. W. Li ◽  
X. B. Ren ◽  
F. X. Li ◽  
H. S. Luo ◽  
D. N. Fang

2012 ◽  
Vol 362 ◽  
pp. 012006 ◽  
Author(s):  
Jianping Meng ◽  
Nishanth Dongari ◽  
Jason M Reese ◽  
Yonghao Zhang

PAMM ◽  
2011 ◽  
Vol 11 (1) ◽  
pp. 475-476 ◽  
Author(s):  
Marc-André Keip ◽  
Jörg Schröder
Keyword(s):  

2009 ◽  
Vol 113 (12) ◽  
pp. 2689-2700 ◽  
Author(s):  
V.F. Banzon ◽  
H.R. Gordon ◽  
C.P. Kuchinke ◽  
D. Antoine ◽  
K.J. Voss ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document