Next-Generation Parametric Reduced-Order Models
Abstract
Novel parametric reduced-order models are proposed for fast reanalysis to predict the dynamic response of complex structures, which suffered thickness variations caused by design changes or damage in one or more substructures. Parametric reduced-order models developed previously have two important challenges to overcome to improve accuracy and performance: (a) the transformation matrix is not mathematically stable, (b) the Taylor series parameterization techniques do not capture thickness variations of the structure modeled with solid-type elements due to the highly nonlinear dependence on thickness changes. Thus, herein, a new transformation matrix and novel parameterization techniques are proposed. Usual reduced-order models have an additional challenge, namely the difficulty in reducing the interface degrees of freedom. Thus a way of reducing the interface degrees of freedom is also proposed. The predicted vibration responses of complex structures are shown to agree very well with results obtained using a much more computationally expensive commercial tool.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 24, 2011
- Accession Number
- ADA551281
Entities
People
- Bogdan I Epureanu
- Matthew P. Castanier
- Sung-kwon Hong
Organizations
- United States Army Tank Automotive Research, Development and Engineering Center