From 6d928e813615cb17e35574a3386cff31f53d7e03 Mon Sep 17 00:00:00 2001 From: pancetta Date: Tue, 13 Jun 2023 07:03:11 +0000 Subject: [PATCH] updated pint.bib using bibbot --- _bibliography/pint.bib | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/_bibliography/pint.bib b/_bibliography/pint.bib index f43ccaaf..088df19c 100644 --- a/_bibliography/pint.bib +++ b/_bibliography/pint.bib @@ -6288,6 +6288,17 @@ @article{ZhangEtAl2022 year = {2022}, } +@inproceedings{BarmanEtAl2023, + author = {Abhishek Barman and Anupam Sharma}, + booktitle = {{AIAA} {AVIATION} 2023 Forum}, + doi = {10.2514/6.2023-3431}, + month = {jun}, + publisher = {American Institute of Aeronautics and Astronautics}, + title = {A Space-Time framework for compressible flow simulations using Finite Volume Method}, + url = {https://doi.org/10.2514/6.2023-3431}, + year = {2023}, +} + @unpublished{BouillonEtAl2023, abstract = {The ParaDiag family of algorithms solves differential equations by using preconditioners that can be inverted in parallel through diagonalization. In the context of optimal control of linear parabolic PDEs, the state-of-the-art ParaDiag method is limited to solving self-adjoint problems with a tracking objective. We propose three improvements to the ParaDiag method: the use of alpha-circulant matrices to construct an alternative preconditioner, a generalization of the algorithm for solving non-self-adjoint equations, and the formulation of an algorithm for terminal-cost objectives. We present novel analytic results about the eigenvalues of the preconditioned systems for all discussed ParaDiag algorithms in the case of self-adjoint equations, which proves the favorable properties the alpha-circulant preconditioner. We use these results to perform a theoretical parallel-scaling analysis of ParaDiag for self-adjoint problems. Numerical tests confirm our findings and suggest that the self-adjoint behavior, which is backed by theory, generalizes to the non-self-adjoint case. We provide a sequential, open-source reference solver in Matlab for all discussed algorithms.}, author = {Arne Bouillon and Giovanni Samaey and Karl Meerbergen},