Fat Tails Aircraft Engine Simulations.pdf (1.5 MB)
Uncertainty quantification for fat-tailed probability distributions in aircraft engine simulations
journal contribution
posted on 2023-06-09, 05:29 authored by R Ahlfeld, F Montomoli, Enrico ScalasEnrico Scalas, S ShahparRare event simulation is vital for industrial design because some events, so-called black swans, can have fatal consequences despite their low probability of occurrence. Finding low-probability events far off the mean design is a challenging task for realistic engineering models because they are characterized by high computational demands, many input variables, and often insufficient statistical information to build parametric probability distributions. Therefore, an adaptive and arbitrary polynomial chaos method, called sparse approximation of moment-based arbitrary polynomial chaos, is suggested in this work. Sparse approximation of moment-based arbitrary polynomial chaos creates custom polynomial basis functions and grids based on statistical moments to avoid incorrect statistical assumptions. The contribution of this work is that it is derived how rare event simulation can conveniently be integrated into adaptive sparse grid methods by calculating polynomial chaos expansions based on the statistical moments of truncated fat-tailed distributions. Moreover, the use of tempered alpha-stable distributions is suggested to avoid discontinuous tail cutoffs. Sparse approximation of moment-based arbitrary polynomial chaos is compared to other statistical methods in two industrial aircraft engine simulations: a simulation of transient cycle temperature in a turbine cavity and hot-gas ingestion in the interwheel region. In both cases, sparse approximation of moment-based arbitrary polynomial chaos agrees with previous results but obtains them with lower computational effort.
History
Publication status
- Published
File Version
- Accepted version
Journal
Journal of Propulsion and PowerISSN
0748-4658Publisher
American Institute of Aeronautics and AstronauticsExternal DOI
Issue
4Volume
33Page range
881-890Department affiliated with
- Mathematics Publications
Full text available
- Yes
Peer reviewed?
- Yes