OpenFOAM is a powerful Open-Source (GPLv3) Computational Fluid Dynamics tool box
with a rising adoption in both academia and industry due to its continuously growing set of …

A computational fluid dynamics code is differentiated using algorithmic differentiation (AD) in
both tangent and adjoint modes. The two novelties of the present approach are (1) the …

The focus of this thesis lies on the efficient generation of sensitivity information for
computational fluid dynamics (CFD) applications, using the discrete adjoint approach …

In the context of numerical simulation a system of partial differential equations is typically
solved by discretizing it into a set of linear equations. The non-linear effects in the solution …

Abstract PETSc's [1] robustness, scalability and portability makes it the foundation of various
parallel implementations of numerical simulation codes. We formulate a least squares …

Algorithmic differentiation tools can automate the adjoint transformation of parallel message-
passing codes [J. Utke, L. Hascoët, P. Heimbach, C. Hill, P. Hovland, and U. Naumann …

A computational fluid dynamics code relying on a high-order spatial discretization is
differentiated using algorithmic differentiation (AD). Two unsteady test cases are considered …

This dissertation is concerned with algorithmic differentiation (AD), which is a method for
algorithmically computing the derivatives∇ F (x) of mathematical functions F: D⊂ Rn↦→ Rm …

We compute flow sensitivities by differentiating a high-order computational fluid dynamics
code. Our fully discrete approach relies on automatic differentiation (AD) of the original …