Probabilistic Analysis of Aircraft Using Multi-Fidelity Aerodynamics Databases
Jayant Mukhopadhaya

TL;DR
This paper introduces a probabilistic framework that uses multi-fidelity aerodynamics databases and uncertainty quantification to simulate aircraft certification tests, estimating success probabilities and guiding design improvements.
Contribution
It presents a novel multi-fidelity modeling approach combining CFD uncertainties with flight certification simulations for aircraft design validation.
Findings
Successfully generated stochastic aerodynamics databases for two aircraft models.
Quantified the probability of aircraft meeting certification requirements.
Provided insights for design adjustments to improve certification success rates.
Abstract
The rise in computational capability has increased reliance on simulations to inform aircraft design. However aircraft airworthiness testing for flight certification remains rooted in real-world experiments performed after manufacturing an aircraft prototype. Leveraging multi-fidelity modeling and uncertainty quantification, we present a framework creating a stochastic representation of the aircraft, uses it to simulate flight certification maneuvers, and determines the likelihood of successfully meeting the certification requirement. We focus on uncertainties associated with Computational Fluid Dynamics simulations solving the Reynolds-Averaged Navier-Stokes equations. The simulation predictions and associated uncertainties are combined with data from other analysis tools to create stochastic aerodynamics and controls databases. The databases describe the aircraft's behavior across its…
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Taxonomy
TopicsAir Traffic Management and Optimization · Aerospace and Aviation Technology · Probabilistic and Robust Engineering Design
