Adding Flight Mechanics to Flight Loads Surrogate Model using Multi-Output Gaussian Processes

Ankit Chiplunkar (1) , Michele Colombo (1) , Emmanuel Rachelson (2) , Joseph Morlier (3)

1 Airbus Defence and Space [Toulouse]
2 DISC - Département d'Ingénierie des Systèmes Complexes
3 ICA - Institut Clément Ader

In this paper analytical methods to formally incorporate knowledge of physics-based equations between multiple outputs in a Gaussian Process (GP) model are presented. In Gaussian Processes a multi-output kernel is a covariance function over correlated outputs. Using a general framework for constructing auto- and cross-covariance functions that are consistent with the physical laws, physics-based relationships among several outputs can be imposed. Results of the proposed methodology for simulated data and measurement from flight tests are presented. The main contribution of this paper is the application and validation of our methodology on a dataset of flight tests, while imposing knowledge of flight mechanics into the model.

Mots clés: Gaussian Process Regression; Flight Physics; Physical Consistency

Domaines: Autre

Ankit Chiplunkar, Michele Colombo, Emmanuel Rachelson, Joseph Morlier. Adding Flight Mechanics to Flight Loads Surrogate Model using Multi-Output Gaussian Processes. 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, AIAA AVIATION Forum, Jun 2016, Washington, United States. pp.1-11. ⟨hal-01828749⟩