Multimodel design strategies applied to sonic boom reduction

Abstract

The shape optimization of a supersonic aircraft need a composite model combining a 3D CFD high-fidelity model and a simplified boom propagation model. The management of this complexity is studied in an optimization loop, with exact discrete adjoints of 3D flow and mesh deformation system. The introduction of a mesh adaptation algorithm is also considered.

Algorithmic Differentiation for adjoint sensitivity calculation in plasma edge codes

“…The rst tangent AD applications date back to the 1960s [24,25], and the adjoint mode was developed by several scientists in the following decades [2628]. Hand-in-hand with scientic computing, AD developments continued and came within reach of several scientic domains, such as aerodynamic design [29], ice sheet modeling [30], and coil design for nuclear fusion stellarators [31]. We give next a general overview of AD and its main features, based on the thorough analysis available in [22].…”

Bayesian maximum a posteriori‐estimation of κ turbulence model parameters using algorithmic differentiation in SOLPS‐ITER

“…Therefore, we resort to algorithmic differentiation (AD), [ 11 ] allowing efficient and accurate semi‐automatic gradient computation either in tangent or adjoint mode. Applications of AD spans different domains, from aerodynamic shape optimization, [ 12 ] over ice sheet modelling, [ 13 ] to stellarator coils optimization. [ 14 ]…”

“…Therefore, we resort to algorithmic differentiation (AD), [11] allowing efficient and accurate semi-automatic gradient computation either in tangent or adjoint mode. Applications of AD spans different domains, from aerodynamic shape optimization, [12] over ice sheet modelling, [13] to stellarator coils optimization. [14] The second drawback of regression techniques, the absence of any uncertainty information, can effectively be overcome with Bayesian inference methods, [15] which in the past decades gained more and more popularity in several research fields, from fluid dynamics [16,17] to nuclear fusion.…”