activity
20242026
collaborators

5 papers

physics.flu-dyn2026

Neural Differential Equations for Oscillatory Flows in Aeroelasticity Applied to Transonic Buffet

Michael Candon, Pier Marzocca, Earl Dowell

Self-excited aerodynamic flows arise across a broad range of systems and can drive nonlinear fluid-structure interactions and aeroelastic instabilities that are challenging and com…

physics.flu-dyn2026

Reduced-Order Hydrodynamic Modelling of a Sphere Near a Wall Using Sparse Regression and Neural Networks

Zev Hoffman, Sara Vahaji, Arpan Das +4

This work presents an interpretable parametric surrogate model motivated by the need to identify a hydrodynamic model for resolving the trajectory of an object in real-time. The su…

physics.flu-dyn2026

Aeroelastic Reduced-Order Model Differential Equations in Transonic Buffeting Flow

Michael Candon, Pier Marzocca, Earl H. Dowell

Numerical simulation of the transonic shock buffet phenomenon remains a formidable challenge due to its inherent nonlinear and unsteady characteristics. These difficulties are furt…

physics.flu-dyn2025

A Numerical Investigation of the Aeroelastic Interaction between Transonic Buffet and Structural Nonlinearity

Michael Candon, Vincenzo Muscarello, Pier Marzocca +1

Transonic shock buffet is a nonlinear, unsteady aerodynamic phenomenon characterized by self-sustained, periodic shock oscillations that can critically affect aircraft structural i…

stat.ME2024

Parsimonious Dynamic Mode Decomposition: A Robust and Automated Approach for Optimally Sparse Mode Selection in Complex Systems

Arpan Das, Pier Marzocca, Oleg Levinski

This paper introduces the Parsimonious Dynamic Mode Decomposition (parsDMD), a novel algorithm designed to automatically select an optimally sparse subset of dynamic modes for both…