A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks

Morelli, Myles; Hauth, Jeremiah; Guardone, Alberto; Huan, Xun; Zhou, Beckett Y.

doi:10.1007/s00158-023-03610-z

Title: A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks

Journal Article · 21 August 2023 · Structural and Multidisciplinary Optimization

DOI: https://doi.org/10.1007/s00158-023-03610-z · OSTI ID:1996076

Morelli, Myles; Hauth, Jeremiah; Guardone, Alberto; Huan, Xun;

Abstract This work develops a novel ice detection framework specifically suitable for rotorcraft using computational aeroacoustics and Bayesian neural networks. In an offline phase of the work, the acoustic signature of glaze and rime ice shapes on an oscillating wing are computed. In addition, the aerodynamic performance indicators corresponding to the ice shapes are also monitored. These performance indicators include the lift, drag, and moment coefficients. A Bayesian neural network is subsequently trained using projected Stein variational gradient descent to create a mapping from the acoustic signature generated by the iced wings to predict their performance indicators along with quantified uncertainty that is highly important for time- and safety-critical decision-making scenarios. While the training is carried out fully offline, usage of the Bayesian neural network to make predictions can be conducted rapidly online allowing for an ice detection system that can be used in real time and in-flight.

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Research Organization:: University of Michigan, Ann Arbor, MI (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC) Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: SC0021397

OSTI ID:: 1996076

Journal Information:: Structural and Multidisciplinary Optimization, Journal Name: Structural and Multidisciplinary Optimization Journal Issue: 9 Vol. 66; ISSN 1615-147X

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: Germany

Language:: English

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