Zobrazeno 1 - 10
of 101
pro vyhledávání: '"GLAUBITZ, JAN"'
Autor:
Glaubitz, Jan, Ranocha, Hendrik, Winters, Andrew R., Schlottke-Lakemper, Michael, Öffner, Philipp, Gassner, Gregor
There is a pressing demand for robust, high-order baseline schemes for conservation laws that minimize reliance on supplementary stabilization. In this work, we respond to this demand by developing new baseline schemes within a nodal discontinuous Ga
Externí odkaz:
http://arxiv.org/abs/2406.14557
We introduce a novel construction procedure for one-dimensional summation-by-parts (SBP) operators. Existing construction procedures for FSBP operators of the form $D = P^{-1} Q$ proceed as follows: Given a boundary operator $B$, the norm matrix $P$
Externí odkaz:
http://arxiv.org/abs/2405.08770
Formulating dynamical models for physical phenomena is essential for understanding the interplay between the different mechanisms and predicting the evolution of physical states. However, a dynamical model alone is often insufficient to address these
Externí odkaz:
http://arxiv.org/abs/2404.14328
Bayesian hierarchical models can provide efficient algorithms for finding sparse solutions to ill-posed inverse problems. The models typically comprise a conditionally Gaussian prior model for the unknown which is augmented by a generalized gamma hyp
Externí odkaz:
http://arxiv.org/abs/2402.16623
Autor:
Ranocha, Hendrik, Winters, Andrew R., Schlottke-Lakemper, Michael, Öffner, Philipp, Glaubitz, Jan, Gassner, Gregor J.
Publikováno v:
Journal of Computational Physics, 2024
We use the framework of upwind summation-by-parts (SBP) operators developed by Mattsson (2017, doi:10.1016/j.jcp.2017.01.042) and study different flux vector splittings in this context. To do so, we introduce discontinuous-Galerkin-like interface ter
Externí odkaz:
http://arxiv.org/abs/2311.13888
Many applications rely on solving time-dependent partial differential equations (PDEs) that include second derivatives. Summation-by-parts (SBP) operators are crucial for developing stable, high-order accurate numerical methodologies for such problem
Externí odkaz:
http://arxiv.org/abs/2306.16314
Autor:
Glaubitz, Jan, Gelb, Anne
Publikováno v:
SIAM-ASA J Uncertain Quantif 12(2), 2024
We present a hierarchical Bayesian learning approach to infer jointly sparse parameter vectors from multiple measurement vectors. Our model uses separate conditionally Gaussian priors for each parameter vector and common gamma-distributed hyper-param
Externí odkaz:
http://arxiv.org/abs/2303.16954
Autor:
Glaubitz, Jan, Reeger, Jonah A.
Publikováno v:
Bit Numer Math 63, 6 (2023)
Quadrature formulas (QFs) based on radial basis functions (RBFs) have become an essential tool for multivariate numerical integration of scattered data. Although numerous works have been published on RBF-QFs, their stability theory can still be consi
Externí odkaz:
http://arxiv.org/abs/2301.12998
Summation-by-parts (SBP) operators allow us to systematically develop energy-stable and high-order accurate numerical methods for time-dependent differential equations. Until recently, the main idea behind existing SBP operators was that polynomials
Externí odkaz:
http://arxiv.org/abs/2301.12996
Autor:
Ranocha, Hendrik, Winters, Andrew R., Schlottke-Lakemper, Michael, Öffner, Philipp, Glaubitz, Jan, Gassner, Gregor J.
Publikováno v:
In Journal of Computational Physics 1 January 2025 520
