Algorithmic differentiation of numerical methods: Tangent and adjoint solvers for parameterized systems of nonlinear equations

U Naumann, J Lotz, K Leppkes, M Towara - ACM Transactions on …, 2015 - dl.acm.org
We discuss software tool support for the algorithmic differentiation (AD), also known as
automatic differentiation, of numerical simulation programs that contain calls to solvers for …

Preparation and assembly of discrete adjoint CFD codes

D Jones, JD Müller, F Christakopoulos - Computers & Fluids, 2011 - Elsevier
A methodology for constructing the sensitivity of the incompressible Navier–Stokes
equations is presented as the context for differentiating high-level Fortran source code using …

Discontinuous Galerkin unsteady discrete adjoint method for real-time efficient tsunami simulations

S Blaise, A St-Cyr, D Mavriplis, B Lockwood - Journal of Computational …, 2013 - Elsevier
An unsteady discrete adjoint implementation for a discontinuous Galerkin model solving the
shallow water wave equations on the sphere is presented. Its use for tsunami simulations is …

[PDF][PDF] Semantics driven adjoints of the message passing interface

M Schanen - 2016 - publications.rwth-aachen.de
1.1 Background This dissertation was created at the Software and Tools for Computational
Engineering (STCE) institute of RWTH University in Aachen. At the time of this writing the …

Ensemble-type numerical uncertainty information from single model integrations

F Rauser, J Marotzke, P Korn - Journal of Computational Physics, 2015 - Elsevier
We suggest an algorithm that quantifies the discretization error of time-dependent physical
quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal …

Performance evaluation and case study of a coupling software ppOpen-MATH/MP

T Arakawa, T Inoue, M Sato - Procedia Computer Science, 2014 - Elsevier
We are developing a coupling software ppOpen-MATH/MP. ppOpen-MATH/MP is
characterized by its wide applicability. This feature comes from the design that grid point …

Predicting goal error evolution from near-initial-information: A learning algorithm

F Rauser, P Korn, J Marotzke - Journal of computational physics, 2011 - Elsevier
We estimate the discretization error of time-dependent goals that are calculated from a
numerical model of the spherical shallow-water equations. The goal errors are described as …

[PDF][PDF] Toward goal-oriented R-adaptive models in geophysical fluid dynamics using a generalized discretization approach

W Bauer - 2013 - pure.mpg.de
We propose a generalized discretization procedure for meshes on general polytopes for our
new set of invariant equations of geophysical fluid dynamics (GFD) and develop a goal …

[HTML][HTML] Estimation of data assimilation error: A shallow-water model study

A Vlasenko, P Korn, J Riehme… - Monthly Weather …, 2014 - journals.ametsoc.org
Four-dimensional variational data assimilation (4D-Var) produces unavoidable inaccuracies
in the models initial state vector. In this paper the authors investigate a novel variational …

Algorithmic differentiation for cloud schemes (IFS cy43r3) using CoDiPack (v1. 8.1)

M Baumgartner, M Sagebaum… - Geoscientific Model …, 2019 - gmd.copernicus.org
Numerical models in atmospheric sciences not only need to approximate the flow equations
on a suitable computational grid, they also need to include subgrid effects of many non …