Super-model automatic modeling method

Through an automatic hypermodel modeling method, including geometric model cleaning, initial modeling calculation, step-by-step refinement calculation, model convergence analysis and determination of hypermodel, the problems of many iterations, labor-consuming and high calculation costs in the establishment of supermodels in the existing technology are solved, and the efficient and reliable establishment of the model is achieved, meeting the dual indicators of accuracy and efficiency.

CN119720681AInactive Publication Date: 2025-03-28NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Patent Information

Application Number
CN202411904323.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-23
Publication Date
2025-03-28
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The prior art requires multiple iterations when establishing a hypermodel, which consumes a lot of manpower and computing costs, and it is difficult to ensure the convergence and accuracy of the model.

Method used

A hypermodel automatic modeling method is proposed, including geometric model cleaning, initial modeling calculation, step-by-step refinement calculation, model convergence analysis and the steps of determining the hypermodel. Modal pairing is performed through modal confidence criterion (MAC), clear convergence judgment criteria are set, and convergence model is quickly determined.

Benefits of technology

It significantly reduces the number of iterations in the model establishment process, saves manpower and computing resources, ensures the convergence and accuracy of the model, improves the reliability and work efficiency of the model, and provides a super model that meets the dual indicators of accuracy and efficiency.

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Abstract

The invention relates to the technical field of dynamic design and predictive design, and discloses a super-model automatic modeling method, which specifically comprises the following steps of: 1, geometric model cleaning: performing geometric cleaning on an original structure model, eliminating geometric errors in a modeling process, and obtaining a geometric model; according to the automatic super-model modeling method, the number of iterations in the model building process can be remarkably reduced, manpower and computing resources are saved, the convergence and precision of the model are ensured through step-by-step refinement and correlation analysis, the reliability of the model is improved, modal matching is carried out through the modal confidence criterion (MAC), modal analysis of the model is more accurate, and the modeling efficiency is improved. According to the method, the dynamic characteristics of the structure can be accurately predicted, the convergence model can be rapidly determined by setting a clear convergence judgment standard, meaningless calculation is avoided, the working efficiency is improved, the finally determined super model can meet the double indexes of precision and efficiency, and a powerful tool is provided for dynamic design and prediction.
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