Results 241 to 250 of about 15,207 (302)

Data-driven, ML-assisted approaches to problem well-posedness. [PDF]

PNAS Nexus
Bertalan T, Kevrekidis GA, Koronaki ED, Mishra S, Rebrova E, Kevrekidis IG.   +5 more
europepmc   +1 more source

Accelerated inference for stochastic compartmental models with over-dispersed partial observations. [PDF]

Stat Comput
Whitehouse M.
europepmc   +1 more source

Stochastic finite elements: a B-spline approach

, 2014
Carbone, Vincenzo Ilario, Mancini, Giuseppe, Allaix, Diego Lorenzo   +2 more
core  

Reliability for composite structures by using stochastic finite elements methods

, 2005
Richard, Fabrice, Boubakar, Lamine, Guicheret-Retel, Violaine   +2 more
core  

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Stochastic elastic–plastic finite elements

Computer Methods in Applied Mechanics and Engineering, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kallol Sett, Boris Jeremic
exaly   +2 more sources

Stochastic finite elements for crash problems

Structural Safety, 1990
Abstract A stochastic finite element technique, based on the association of a response surface scheme with the “impact” finite-element code PAMCRASH , is implemented. The actual response is modelled by a piecewise idealization which combines several response surface interpolations.
FARAVELLI, LUCIA, Bigi D.
openaire   +3 more sources

On stochastic finite elements for structural analysis

Computers & Structures, 1994
Summary: This paper considers the stochastic finite element analysis of structures resulting from random spatial variability of material properties, when they are subjected to loads of deterministic nature. Direct Monte Carlo simulation, Monte Carlo simulations with Neumann expansion of the stiffness matrix, and Taylor series expansion combined with ...
Araújo, J. M., Awruch, A. M.
openaire   +2 more sources

A Spectral Formulation of Stochastic Finite Elements

, 1997
Until recently, stochastic structural mechanics has addressed the issue of deterministic structures subjected to random loading. With the availability of more accurate analysis and design tools, however, quantifying the sensitivity of model predictions to uncertainty in the mechanical properties of structures has become possible.
R. G. Ghanem, P. D. Spanos
openaire   +2 more sources