10 citations · 11 across the 9 of their papers we have counts for
10 papers
Online Seakeeping Forecast Coupling System Identification With Nonlinear Pseudo Spectral Potential-Flow
Zev Hoffman, Sara Vahaji, Micheal Candon +2
This paper presents a grey-box framework for a robust deterministic, real-time prediction of coupled surge-heave-pitch motion in waves. The approach combines a physics-based online…
Geometry Parameterisation via a Structural Modal Basis for Aerodynamic Shape Optimisation
Alwin Wang, Robert Carrese, Luca Brown +2
Aircraft outer mould lines are often heavily constrained early by payload requirements, manufacturability limits, and low-observability considerations. The remaining aerodynamic de…
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…
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…
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…
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…
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…
Efficient Transonic Aeroelastic Model Reduction Using Optimized Sparse Multi-Input Polynomial Functionals
Michael Candon, Maciej Balajewicz, Arturo Delgado-Gutierrez +2
Nonlinear aeroelastic reduced-order models (ROMs) based on machine learning or artificial intelligence algorithms can be complex and computationally demanding to train, meaning tha…
Optimal Sparsity in Nonlinear Non-Parametric Reduced Order Models for Transonic Aeroelastic Systems
Michael Candon, Errol Hale, Maciej Balajewicz +2
Machine learning and artificial intelligence algorithms typically require large amount of data for training. This means that for nonlinear aeroelastic applications, where small tra…
A Data-driven Approach for Rapid Detection of Aeroelastic Modes from Flutter Flight Test Based on Limited Sensor Measurements
Arpan Das, Pier Marzocca, Giuliano Coppotelli +2
Flutter flight test involves the evaluation of the airframes aeroelastic stability by applying artificial excitation on the aircraft lifting surfaces. The subsequent responses are…