Bayesian assessments of aeroengine performance with transfer learning

Bayesian assessments of aeroengine performance with transfer learning

Aeroengine performance is determined by temperature and pressure profiles along various axial stations within an engine. Given limited sensor measurements, we require a statistically principled approach for inferring these profiles. In this paper we detail a Bayesian methodology for interpolating th...

Full description

Bibliographic Details
Main Authors: Pranay Seshadri, Andrew B. Duncan, George Thorne, Geoffrey Parks, Raul Vazquez Diaz, Mark Girolami
Format: Article
Language:English
Published: Cambridge University Press 2022-01-01
Series:Data-Centric Engineering
Subjects:
Gaussian processes
jet-engines
Bayesian inference
measurements
thermofluids
Online Access:https://www.cambridge.org/core/product/identifier/S2632673622000296/type/journal_article

Internet

https://www.cambridge.org/core/product/identifier/S2632673622000296/type/journal_article

Similar Items