Differentiable programming techniques are widely used in the community and are
responsible for the machine learning renaissance of the past several decades. While these …

Earth system models (ESMs) are the primary tools for investigating future Earth system
states at timescales from decades to centuries, especially in response to anthropogenic …

The prediction of the temporal dynamics of chaotic systems is challenging because
infinitesimal perturbations grow exponentially. The analysis of the dynamics of infinitesimal …

In this paper we demonstrate the ability to perform gradient-free aerodynamic shape
optimization using Large Eddy Simulation (LES) with the Mesh Adaptive Direct Search …

In an acoustic cavity with a heat source, such as a flame in a gas turbine, the thermal energy
of the heat source can be converted into acoustic energy, which may generate a loud …

This paper presents a discrete adjoint version of the recently developed non-intrusive least
squares shadowing (NILSS) algorithm, which circumvents the instability that conventional …

This paper uses compressible flow simulation to analyse the hyperbolicity, shadowing
directions and sensitivities of a weakly turbulent three-dimensional cylinder flow at Reynolds …

We develop the NILSAS algorithm, which performs adjoint sensitivity analysis of chaotic
systems via computing the adjoint shadowing direction. NILSAS constrains its minimization …

Abstract We present the Finite Difference Non-Intrusive Least Squares Shadowing (FD-
NILSS) algorithm for computing sensitivities of long-time averaged quantities in chaotic …

This paper presents an approach to mesh adaptation suitable for scale-resolving
simulations. The methodology is based on the entropy-adjoint approach, which corresponds …