Finite element model updating has emerged in the s as a subject of immense and maintenance of mechanical systems and civil engineering structures. PDF · Finite Element Modelling. M. I. Friswell, J. E. Mottershead. Pages Finite element model updating has emerged in the s as a subject of immense and maintenance of mechanical systems and civil engineering structures. DRM-free; Included format: PDF; ebooks can be used on all reading devices. The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for. Germany, the.
|Language:||English, Spanish, Portuguese|
|Distribution:||Free* [*Registration needed]|
Jun 19, Article (PDF Available) in Journal of Sound and Vibration The text "Finite element model updating in structural dynamics" by Friswell and. Apr 20, PDF | This paper is a review of information and related studies Model updating techniques are about updating a finite element model of a. Finite Element Model Updating in Structural Dynamics. M I Friswell and J E Mottershead. Kluwer Academic Publishers, , pp., ISBN
Pages Finite Element Modelling. Vibration Testing. Comparing Numerical Data with Test Results. Estimation Techniques. Parameters for Model Updating.
Direct Methods using Modal Data. Iterative Methods using Modal Data. Methods using Frequency Domain Data. Case Study: An Automobile Body. Discussion and Recommendations. Back Matter Pages About this book Introduction Finite element model updating has emerged in the s as a subject of immense importance to the design, construction and maintenance of mechanical systems and civil engineering structures.
This book, the first on the subject, sets out to explain the principles of model updating, not only as a research text, but also as a guide for the practising engineer who wants to get acquainted with, or use, updating techniques. The process begins with the formulation of an initial FE model using initial values for the update parameters. The FEA results that will be used to check correlation with test are computed using the FE model with the current update parameter values.
The model updating method uses the discrepancy between FEA results and test, and sensitivities to determine a change in the update parameters that will reduce the discrepancy. The FE model is then reformed using the new values of the update parameters, and the process repeats until some convergence criteria, analyzed by means of correlation functions, is met. Key Features Automated, iterative, sensitivity-based updating procedure. Built-in parameter estimators weighted, least squares, multi-objective or custom.
Predefined and customizable target functions. Selection of all element material properties, geometrical properties, boundary conditions, lumped masses, damping factors and excitation forces as updating parameters.
Generic parameters and responses. Weighting of updating parameters and targets expressing user-confidence Bayesian parameter estimation.
Constraints on updating parameters max per iteration, abs max, abs min. Possibility to combine different parameter types and response types in a single run.
Support of parameter relations linear and non-linear equality constraints. Option to re-analyze updated models using FEMtools modal solver for fast, approximate iterations. Superelement-based model updating.
Simultaneous updating of multiple models MMU. Using internally or externally computed sensitivities.
Automated scaling of sensitivity matrix for optimal performance. Automated support of internal and external solvers for static or dynamic re-analysis of updated models. Tracking of updating parameters and system responses during updating. Dedicated tables and graphics to examine results e.
Undo functions and database restoration. Regrouping of local model updating results. Export of updated FE models.. Superelement-Based Model Updating When working with large FE models, a bottom-up modeling, testing and assembly approach should be considered. This is most efficient if superelements are used to model the parts that do not change.
For each configuration there is a modal test. For example, solar panels for satellites can be tested during different stages of deployment and for each stage there is a FE model.
This provides a richer set of test data to serve as reference for updating element properties that are common in all configurations. Such properties can be, for example, the joint stiffness or material properties.
Other examples are a launcher tested with different levels of fuel, or differently shaped test specimens made of a composite material that needs to be identified. Harmonic Force Identification From measured harmonic operational shapes, and an updated finite element model, a system of equations can be solved to obtain the excitation forces.
Key Features Force identification from dynamic response measurements. Definition of masks for location of forces. Identification of harmonic nodal loads or element pressure loads.
Export of identified forces Probabilistic Analysis All physical properties are subject to scatter and uncertainty. It is important to assess how this variability of properties propagates in a structure and results in also variability on the output responses. This has applications in robust design for example Design for Six Sigma - DfSS but is also used for statistical correlation and probabilistic model updating in case multiple tests have been performed.
Key Features Apply a statistical probability distribution to physical properties and randomly sample thousands of physical properties using only a few commands Monte Carlo simulation.
Re-analysis for each sample using FEMtools or external solvers. For dynamic responses, a fast approximate modal solver can be used to significantly reduce the time required to run hundreds of simulations. Use all parameter and response choices available for Sensitivity Analysis and Model Updating see above.
Postprocess simulations to obtain histogram, mean and standard deviation of output responses.