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Dynamic reduced model and stochastic aspects for PFGM curved beams with variable curvature
(Pergamon-Elsevier Science Ltd, 2021-01)
In this paper a new 1D finite element model for dynamic calculations of PGFM curved beams with variable curvature is developed. The reduced high-speed calculation model allows stochastic aspects in the dynamic of the ...
High Performance Reduced Order Modeling Techniques Based on Optimal Energy Quadrature: Application to Geometrically Non-linear Multiscale Inelastic Material Modeling
(Springer, 2018-02)
A High-Performance Reduced-Order Model (HPROM) technique, previously presented by the authors in the context of hierarchical multiscale models for non linear-materials undergoing infinitesimal strains, is generalized to ...
Computational multiscale modeling of fracture problems and its model order reduction
(International Center for Numerical Methods in Engineering, 2017)
This work focuses on the numerical modeling of fracture and its propagationin heterogeneous materials by means of hierarchical multiscale models basedon the FE2 method, addressing at the same time, the problem of the ...
Reduced order modeling strategies for computational multiscale fracture
(Elsevier Science, 2016-10)
The paper proposes some new computational strategies for affordably solving multiscale fracture problems through a FE2 approach. To take into account the mechanical effects induced by fracture at the microstructure level ...
A reduced order state space model for aeroelastic analysis in time domain
(2017-02-01)
The objective of this paper is to describe a new method for modeling aeroelastic system in time domain based on a modification of the Laguerre Polynomials to represent complex quantities. These polynomials are used to ...
Covariance reducing models: An alternative to spectral modelling of covariance matrices
(Oxford University Press, 2008-12)
We introduce covariance reducing models for studying the sample covariance matrices of a random vector observed in different populations. The models are based on reducing the sample covariance matrices to an informational ...
Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2011-01-27)
We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We ...
Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2010-09-13)
We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We ...
Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2009-02-05)
We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We ...
Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2010-03-29)
We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We ...