Stochastic Inverse Problem with Noisy Simulator. Application to aeronautical model
Author(s) -
Nabil Rachdi,
JeanClaude Fort,
Thierry Klein
Publication year - 2012
Publication title -
annales de la faculté des sciences de toulouse mathématiques
Language(s) - English
Resource type - Journals
eISSN - 2258-7519
pISSN - 0240-2963
DOI - 10.5802/afst.1346
Subject(s) - representation (politics) , cruise , inference , computer science , inverse problem , inverse , phenomenon , simulation , operations research , industrial engineering , engineering , aerospace engineering , mathematics , artificial intelligence , physics , mathematical analysis , geometry , quantum mechanics , politics , political science , law
Inverse problem is a current practice in engineering where the goal is to identify parameters from observed data through numerical models. These numerical models, also called Simulators, are built to represent the phenomenon making possible the inference. However, such representation can include some part of variability or commonly called uncertainty (see [4]), arising from some variables of the model. The phenomenon we study is the fuel mass needed to link two given countries with a commercial aircraft, where we only consider the Cruise phase . From a data base of fuel mass consumptions during the cruise phase, we aim at identifying the Speci c Fuel Consumption (SFC) in a robust way, given the uncertainty of the cruise speed V and the lift-to-drag ratio F. In this paper, we present an estimation procedure based on Maximum-Likelihood estimation, taking into account this uncertainty.
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