Aerodynamic design optimization: Challenges and perspectives
JRRA Martins - Computers & Fluids, 2022 - Elsevier
Antony Jameson pioneered CFD-based aerodynamic design optimization in the late 1980s.
In addition to develo** the fundamental theory, Jameson implemented that theory in …
In addition to develo** the fundamental theory, Jameson implemented that theory in …
Effective adjoint approaches for computational fluid dynamics
The adjoint method is used for high-fidelity aerodynamic shape optimization and is an
efficient approach for computing the derivatives of a function of interest with respect to a …
efficient approach for computing the derivatives of a function of interest with respect to a …
Combining differentiable PDE solvers and graph neural networks for fluid flow prediction
Solving large complex partial differential equations (PDEs), such as those that arise in
computational fluid dynamics (CFD), is a computationally expensive process. This has …
computational fluid dynamics (CFD), is a computationally expensive process. This has …
Toward the end-to-end optimization of particle physics instruments with differentiable programming
The full optimization of the design and operation of instruments whose functioning relies on
the interaction of radiation with matter is a super-human task, due to the large dimensionality …
the interaction of radiation with matter is a super-human task, due to the large dimensionality …
Dafoam: An open-source adjoint framework for multidisciplinary design optimization with openfoam
The adjoint method is an efficient approach for computing derivatives that allow gradient-
based optimization to handle systems parameterized with a large number of design …
based optimization to handle systems parameterized with a large number of design …
A discrete adjoint framework coupled with adaptive PCE for robust aerodynamic optimization of turbomachinery under flow uncertainty
J Zhang, L Li, X Dong, Z Zhang, Y Zhang… - Aerospace Science and …, 2023 - Elsevier
Flow uncertainty is commonly encountered in turbomachinery. To mitigate the negative
effects caused by the flow uncertainty, a framework coupled with adaptive polynomial chaos …
effects caused by the flow uncertainty, a framework coupled with adaptive polynomial chaos …
[HTML][HTML] Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations
Among the well-known methods to approximate derivatives of expectancies computed by
Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to …
Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to …
Scalable automatic differentiation of multiple parallel paradigms through compiler augmentation
Derivatives are key to numerous science, engineering, and machine learning applications.
While existing tools generate derivatives of programs in a single language, modern parallel …
While existing tools generate derivatives of programs in a single language, modern parallel …
A duality-preserving adjoint method for segregated Navier–Stokes solvers
Adjoint methods efficiently compute gradients for systems with many inputs and have been
widely used for large-scale gradient-based optimization in fluid mechanics. To ensure …
widely used for large-scale gradient-based optimization in fluid mechanics. To ensure …
Aerodynamic-driven topology optimization of compliant airfoils
A strategy for density-based topology optimization of fluid-structure interaction problems is
proposed that deals with some shortcomings associated to non stiffness-based design. The …
proposed that deals with some shortcomings associated to non stiffness-based design. The …