Application of Finite Volume Method to Structural Stochastic Dynamics
Authors:
Open Access
- 1 January 2013
- journal article
- Published by SAGE Publications in Advances in Mechanical Engineering
- Vol. 5
Abstract
The stochastic dynamic problems were becoming more difficult after considering the influences of stochastic factors and the complexity of the dynamic problems. To this background, the finite volume method combined with Perturbation Method was proposed for the stochastic dynamic analysis. The equations of perturbation-finite volume method were derived; the explicit expressions between random response and basic random variables were given; the method of stochastic dynamic analysis was discussed; and the examples were presented to verify the perturbation-finite volume method. The results of perturbation-finite volume method were compared with the results of Monte Carlo Method, which proved that the proposed method was correct and accurate. Because the proposed method was simple and clear, the equations were easy to establish and the efficiency was improved. Meanwhile, the proposed method was successfully applied to the stochastic dynamic analysis of linear multibody system, which was verified through the example in this paper.Keywords
Funding Information
- The Science and Technology on Combustion and Explosion Laboratory Foundation (9140C350406150C35126)
This publication has 8 references indexed in Scilit:
- An unstructured finite volume approach for structural dynamics in response to fluid motionsComputers & Structures, 2008
- A matrix-free implicit unstructured multigrid finite volume method for simulating structural dynamics and fluid–structure interactionJournal of Computational Physics, 2007
- Dynamic response and reliability analysis of non-linear stochastic structuresProbabilistic Engineering Mechanics, 2005
- A cell vertex and cell centred finite volume method for plate bending analysisComputer Methods in Applied Mechanics and Engineering, 2004
- Time-Dependent Reliability Analysis of Steel Miter GatesInternational Journal of Modelling and Simulation, 2003
- Identification and Review of Sensitivity Analysis MethodsRisk Analysis, 2002
- Sensitivity Analysis for Importance AssessmentRisk Analysis, 2002
- Sensitivity Anaysis as an Ingredient of ModelingStatistical Science, 2000