An Introduction to the Adjoint Approach to Design

By M. Giles, Niles A. Pierce. 2000

1,128 citations recorded by the source corpus.

Subfields: Applied Mathematics, Computational Mechanics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/df3fd274d792ed99f1f136927ffbd52d9d1392aa

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In Applied Mathematics

In Computational Mechanics

In Statistics and Probability

Citations in the corpus

Optimizing parameterized CAD geometries using sensitivities based on adjoint functions (2012, methodology): “An efficient approach to optimization when there are a large number of design variables is to use adjoint analysis [12] which computes the sensitivity of an objective function to a small movement of the model boundary, e.”
Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils (2016, background): “One such assumption implies a balance between the production and dissipation of turbulent kinetic energy.”
Effective adjoint approaches for computational fluid dynamics (2019, background): “However, analytically differentiating the adjoint partial derivative terms requires significant expertise in the particular flow-solver implementation and is prone to human error [7].”
Neural Controlled Differential Equations for Irregular Time Series (2020, background): “An attractive part of Neural ODEs is the ability to train via adjoint backpropagation, see [15, 26, 27, 28], which uses only O ( H ) memory in the time horizon L = t n − t 0 and the memory footprint H of the vector ﬁeld.”
Review and Unification of Methods for Computing Derivatives of Multidisciplinary Computational Models (2013, background): “will not discuss the continuous approach in this paper, but ample literature can be found on the subject [72–77], including discussions comparing the two approaches [27,78,79].”
Recent advances in surrogate-based optimization (2009, background): “Most likely to be of use is gradient information found via algorithmic differentiation (AD) [29] (also known as automatic differentiation, though the term ‘automatic’ can instill false hope, since manual intervention is required in most cases), which requires access to the function source code, and ”
Fluid control using the adjoint method (2004, background): “This sub-stitution can be viewed in terms of linear duality [Giles and Pierce 2000].”
Optimization of wind plant layouts using an adjoint approach (2017, background): “Reviews of adjoint techniques in various flow control and optimization applications have been published by Jameson (2003), Giles and Pierce (2000), Giannakoglou and Papadimitriou (2008), and Luchini and Bottaro (2014).”