A stochastic approach for performance prediction of aircraft engine components under manufacturing uncertainty

AM McKeand… - … and Information in …, 2018 - asmedigitalcollection.asme.org
Efficient modeling of uncertainty introduced by the manufacturing process is critical in the
design of the components of the aircraft engines. In this study, a stochastic approach is …

Multiscale Modeling of Turbine Engine Component Under Manufacturing Uncertainty

AM McKeand… - Journal of …, 2019 - asmedigitalcollection.asme.org
Efficient modeling of uncertainty introduced by the manufacturing process is critical in the
design of turbine engine components. In this study, a stochastic multiscale modeling …

Gaussian Process Model-Based Performance Uncertainty Quantification of a Typical Turboshaft Engine

X Liu, H Tang, X Zhang, M Chen - Applied Sciences, 2021 - mdpi.com
The gas turbine engine is a widely used thermodynamic system for aircraft. The demand for
quantifying the uncertainty of engine performance is increasing due to the expectation of …

Polynomial chaos expansion with latin hypercube sampling for estimating response variability

SK Choi, RV Grandhi, RA Canfield, CL Pettit - AIAA journal, 2004 - arc.aiaa.org
A computationally efficient procedure for quantifying uncertainty and finding significant
parameters of uncertainty models is presented. To deal with the random nature of input …

Capture of manufacturing uncertainty in turbine blades through probabilistic techniques

N Thakur, A Keane, PB Nair - 2008 - eprints.soton.ac.uk
Efficient designing of the turbine blades is critical to the performance of an aircraft engine.
An area of significant research interest is the capture of manufacturing uncertainty in the …

Stochastic analysis and validation under aleatory and epistemic uncertainties

AM McKeand, RM Gorguluarslan, SK Choi - Reliability Engineering & …, 2021 - Elsevier
An uncertainty quantification and validation framework is presented to account for both
aleatory and epistemic uncertainties in stochastic simulations of turbine engine components …

Uncertainty quantification in helicopter performance using Monte Carlo simulations

C Siva, MS Murugan, R Ganguli - Journal of Aircraft, 2011 - arc.aiaa.org
UNDERSTANDING and management of uncertainties have become increasingly important
for aircraft industries to advance in the design process, make better field development …

Turbine blade probabilistic analysis using semi-analytical sensitivities

S Burton, R Kolonay, M Dindar - 19th AIAA Applied Aerodynamics …, 2001 - arc.aiaa.org
Over the years engineering design practices have matured to a point where significant
performance gains are not likely obtainable with further enhancement of existing …

Polynomial chaos expansion with latin hypercube sampling for predicting response variability

SK Choi, R Grandhi, R Canfield, C Pettit - 44th AIAA/ASME/ASCE/AHS …, 2003 - arc.aiaa.org
This paper presents a computationally efficient procedure for quantifying uncertainty and
finding significant parameters of uncertainty models. Deterministic measures cannot quantify …

An efficient approach to probabilistic uncertainty analysis in simulation-based multidisciplinary design

X Du, W Chen - 38th Aerospace Sciences Meeting and Exhibit, 2000 - arc.aiaa.org
In this paper, computationally efficient techniques for propagating the effect of uncertainty
are developed to accommodate generic probabilistic representations of uncertain …