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.
Authors
- Chaojiang Li (ORCID: https://orcid.org/0000-0002-5193-6779)
- Lingling Shi (ORCID: https://orcid.org/0000-0002-4821-6818)
- Xin Jin (ORCID: https://orcid.org/0000-0002-9375-4316)
- Yiqi Liu
- Xiao Chen
Institutions
- Beijing Institute of Technology (CN)
- Beijing Research Institute of Mechanical and Electrical Technology (CN)
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
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality