Saltar al contenido
República del Perú · Observatorio de la producción científica universitaria
OApol.org Observatorio de Inteligencia Científica Universitaria del Perú
OApol.org
Inicio Universidades Publicaciones Investigadores
Repositorios
Tesis y trabajos académicosRevistas
Indicadores
Ranking trimestralRanking por carreraObjetivos de Desarrollo SostenibleReporte OCDERed neuronal 3D
Acerca
MetodologíaPrivacidad

Nonlinear model reduction for large-scale structures via dual substructuring

Flores P.A. · Scientific Reports (2026) · DOI: 10.1038/s41598-026-38015-7

Resumen

This work presents a nonlinear model reduction strategy for large-scale structural systems with localized nonlinearities based on a dual substructuring approach. The method combines the computational benefits of the dual Craig-Bampton formulation with the accuracy of nonlinear normal modes (NNMs) embedded within each substructure dynamic reduction. Internal nonlinearities are treated locally via invariant manifold-based approximations, while interface compatibility is enforced through interface forces, maintaining the modularity and flexibility of the dual formulation. The performance of the proposed method is assessed on a steel frame with localized nonlinearities subjected to harmonic loading. The results obtained with the proposed formulation were compared with those of the full finite element model. In both analyses, the Hilber–Hughes–Taylor (HHT) algorithm was employed as the time integration strategy. The reduced models achieve significant reductions in computational cost while preserving high accuracy in the predicted transient response. The approach demonstrates strong potential for efficient nonlinear dynamic simulation of complex engineering structures with localized nonlinearities. © The Author(s) 2026.

Instituciones: Pontificia Universidad Católica del Perú