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 …

Multidisciplinary design optimization is a field of research that studies the application of
numerical optimization techniques to the design of engineering systems involving multiple …

The surrogate modeling toolbox (SMT) is an open-source Python package that contains a
collection of surrogate modeling methods, sampling techniques, and benchmarking …

Computational fluid dynamics through the solution of the Navier–Stokes equations with
turbulence models has become commonplace. However, simply solving these equations is …

Mesh generation and deformation are critical elements in gradient-based aerodynamic
shape optimization (ASO). Improperly generated or deformed meshes may contain bad …

Multidisciplinary design optimization (MDO) is concerned with solving design problems
involving coupled numerical models of complex engineering systems. While various MDO …

Abstract The Surrogate Modeling Toolbox (SMT) is an open-source Python package that
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …

Aerodynamic optimisation has become an indispensable component for any aerodynamic
design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind …

Despite considerable research on aerodynamic shape optimization, there is no standard
benchmark problem allowing researchers to compare results. This work addresses this …

This paper presents a review of all existing discrete methods for computing the derivatives of
computational models within a unified mathematical framework. This framework hinges on a …