Geometry and topology optimization of switched reluctance machines: A review
Switched reluctance machines (SRMs) have recently attracted more interest in many
applications due to the volatile prices of rare-earth permanent magnets (PMs) used in …
applications due to the volatile prices of rare-earth permanent magnets (PMs) used in …
A taxonomy of automatic differentiation pitfalls
Automatic differentiation is a popular technique for computing derivatives of computer
programs. While automatic differentiation has been successfully used in countless …
programs. While automatic differentiation has been successfully used in countless …
Pitfalls of discrete adjoint fixed-points based on algorithmic differentiation
P Gomes, R Palacios - AIAA Journal, 2022 - arc.aiaa.org
ADJOINT methods are widely used to compute gradients for numerical optimization
problems that involve the simulation of complex physical phenomena, such as fluid flow [1 …
problems that involve the simulation of complex physical phenomena, such as fluid flow [1 …
Understanding Automatic Differentiation Pitfalls
Automatic differentiation, also known as backpropagation, AD, autodiff, or algorithmic
differentiation, is a popular technique for computing derivatives of computer programs …
differentiation, is a popular technique for computing derivatives of computer programs …
[PDF][PDF] Discrete adjoint optimization with OpenFOAM
M Towara - 2018 - scholar.archive.org
The focus of this thesis lies on the efficient generation of sensitivity information for
computational fluid dynamics (CFD) applications, using the discrete adjoint approach …
computational fluid dynamics (CFD) applications, using the discrete adjoint approach …
Simple adjoint message passing
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 …
solved by discretizing it into a set of linear equations. The non-linear effects in the solution …
[PDF][PDF] A high-performance open-source framework for multiphysics simulation and adjoint-based shape and topology optimization
PC Gomes - 2021 - core.ac.uk
The first part of this thesis presents the advances made in the Open-Source software SU2,
towards transforming it into a high-performance framework for design and optimization of …
towards transforming it into a high-performance framework for design and optimization of …
Discrete adjoints on many cores Algorithmic differentiation of accelerated fluid simulations
JC Hückelheim - 2017 - qmro.qmul.ac.uk
Simulations are used in science and industry to predict the performance of technical
systems. Adjoint derivatives of these simulations can reveal the sensitivity of the system …
systems. Adjoint derivatives of these simulations can reveal the sensitivity of the system …
[HTML][HTML] Compiler support for operator overloading and algorithmic differentiation in c++
A Hück - 2020 - tuprints.ulb.tu-darmstadt.de
Multiphysics software needs derivatives for, eg, solving a system of non-linear equations,
conducting model verification, or sensitivity studies. In C++, algorithmic differentiation (AD) …
conducting model verification, or sensitivity studies. In C++, algorithmic differentiation (AD) …
Approximate linearization of fixed-point iterations: Error analysis of tangent and adjoint problems linearized about non-stationary points
E Padway, D Mavriplis - Numerical Algorithms, 2022 - Springer
Previous papers have shown the impact of partial convergence of discretized PDEs on the
accuracy of tangent and adjoint linearizations. A series of papers suggested linearization of …
accuracy of tangent and adjoint linearizations. A series of papers suggested linearization of …