Rapid generation method of element model with geometric distribution errors for high-fidelity aero-engine simulation

• Novel method generates error-embedded meshes directly without CAD reconstruction. • Modeling efficiency is improved 62-fold, requiring only 20.8s for generation. • Automated generation module is integrated into commercial CAE software. • Method improves high-fidelity prediction accuracy of aero-engine casing assembly. The performance and service life of aero-engines strongly depend on assembly quality. High-fidelity assembly simulation is therefore essential, yet its accuracy relies on precise representation of non-uniform geometric errors on assembly interfaces. However, existing approaches cannot adequately capture their spatial distribution or meet modern industrial requirements in accuracy and efficiency. This study proposes a rapid method for generating element models with geometric distribution errors (EM-GDE). The method reconstructs the geometric error surface from point-cloud measurements. It then embeds the error field directly into the finite element mesh using a node-wise vector-height re-placement algorithm, eliminating CAD reconstruction. An EM-GDE generation module was integrated into commercial CAE software to support engineering deployment. Experimental tests show that the method reduces modeling time to 20.8 s, achieving a 62-fold improvement while maintaining high accuracy. A case study on aero-engine casing assembly shows that EM-GDE-based simulation improves coaxiality prediction accuracy compared with ideal and tolerance-based models, reaching an average precision of 88.59% with experimental measurements. The results further reveal how non-uniform geometric errors induce asymmetric deformation and coaxiality degradation. This study establishes an effective framework for online high-precision simulation of aero-engines performance and offers significant engineering value for digital assembly and assembly process optimization.

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Publication Details

Journal
Results in Engineering
Published
2026-04-21
DOI
https://doi.org/10.1016/j.rineng.2026.110649
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Rapid generation method of element model with geometric distribution errors for high-fidelity aero-engine simulation

Chaojiang Li, Lingling Shi, Xin Jin, Yiqi Liu et al.
Results in Engineering
Computational Fluid Dynamics and Aerodynamics
article

Rapid generation method of element model with geometric distribution errors for high-fidelity aero-engine simulation

Chaojiang Li, Lingling Shi, Xin Jin, Yiqi Liu, Xiao Chen
article en

Abstract

• Novel method generates error-embedded meshes directly without CAD reconstruction. • Modeling efficiency is improved 62-fold, requiring only 20.8s for generation. • Automated generation module is integrated into commercial CAE software. • Method improves high-fidelity prediction accuracy of aero-engine casing assembly. The performance and service life of aero-engines strongly depend on assembly quality. High-fidelity assembly simulation is therefore essential, yet its accuracy relies on precise representation of non-uniform geometric errors on assembly interfaces. However, existing approaches cannot adequately capture their spatial distribution or meet modern industrial requirements in accuracy and efficiency. This study proposes a rapid method for generating element models with geometric distribution errors (EM-GDE). The method reconstructs the geometric error surface from point-cloud measurements. It then embeds the error field directly into the finite element mesh using a node-wise vector-height re-placement algorithm, eliminating CAD reconstruction. An EM-GDE generation module was integrated into commercial CAE software to support engineering deployment. Experimental tests show that the method reduces modeling time to 20.8 s, achieving a 62-fold improvement while maintaining high accuracy. A case study on aero-engine casing assembly shows that EM-GDE-based simulation improves coaxiality prediction accuracy compared with ideal and tolerance-based models, reaching an average precision of 88.59% with experimental measurements. The results further reveal how non-uniform geometric errors induce asymmetric deformation and coaxiality degradation. This study establishes an effective framework for online high-precision simulation of aero-engines performance and offers significant engineering value for digital assembly and assembly process optimization.

Results in EngineeringVol. 30
Beijing Institute of Technology (CN), Beijing Research Institute of Mechanical and Electrical Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality
Affordable and clean energy
Openalex Percentile: Top 16%
Computational Fluid Dynamics and Aerodynamics
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