High-fidelity standard model reconstruction and verification of an airliner based on point clouds

Abstract

Computational fluid dynamics (CFD) numerical simulation as the primary research tool is particularly essential for its credibility during the aerodynamic design of aircraft. To further promote CFD verification and validation on the airliner, a high-fidelity model reconstruction of the airliner is fundamental. Based on this, we put forward a novel framework, to our best knowledge, to reconstruct a high-fidelity standard model for an airliner efficiently, and the feasibility and accuracy of these reconstructed models are accessed by the CFD simulation-based validation method. First and foremost, a laser scanner was placed at each station around the airliner to scan and acquire multiview point clouds. Afterwards, the truncated least-squares-based algorithm was adopted to register these point clouds entirely. Additionally, we fitted the nonuniform rational basis spline surface based on the least-squares progressive and iterative approximation algorithm. Finally, CFD simulation results were compared and analyzed with the aerodynamic data obtained by the aircraft manufacturer under the same Mach number of the uniform model. It turns out that the coincidence between them is high, and the changing trend is basically consistent. Hence, this method is highly feasible and can establish a high-fidelity standard model of an airliner with unified high and low speeds so that its appearance, test data, and research results can be adopted as the standard data for CFD verification and validation.