Validation problems in computational fluid mechanics
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2011, Vol 18, Issue 1
Abstract
Recent developments in Computational Fluid Dynamics (CFD) increased interest in quantifying quality of the numerical models. One of the necessary steps is the so-called code validation procedure, an assessment of a numerical simulation by comparisons between simulation results and laboratory measurements. The focus of the present review is application of modern full field experimental techniques, mostly based on the digital image analysis, in validating numerical solutions of complex flow configurations. Each validation procedure opens new issues of quantifying its outcome to find directions for model updating, limits of computer simulation quality, and to perform uncertainty quantification.
Authors and Affiliations
Tomasz A. Kowalewski
Application of artificial neural network in soil parameter identification for deep excavation numerical model
In this paper, an artificial neural network (ANN) is used to approximate response of deep excavation numerical model on input parameters. The approximated model is then used in minimization procedure of the inverse probl...
Scatter assessment of rotating system vibrations due to uncertain residual unbalances and bearing properties
The main objective of the presented study is an evaluation of the effectiveness of various methods for estimating statistics of rotor-shaft vibration responses. The computational effectiveness as well as the accuracy of...
Computational challenges in the simulation of nonlinear electroelasticity
Nonlinear electroelasticity is not a new problem, its theory involving nonlinear deformation and nonlinear material behavior has been well established. However, the numerical simulation of nonlinear electroelasticity is...
Identification problems of Recurrent Cascade Neural Network application in predicting an additional mass location
The paper is a development of research originated in [8]. The identification problem deals with searching the location of a small mass attached to a steel plate. The corresponding inverse problem is based on measurement...
Neural network prediction of load capacity for eccentrically loaded reinforced concrete columns
This paper presents neural networks prediction of load capacity for eccentrically loaded reinforced concrete (RC) columns. The direct modelling of the load capacity of RC columns by means of the finite element method pre...