53 research outputs found
Using parametric model order reduction for inverse analysis of large nonlinear cardiac simulations
Predictive high-fidelity finite element simulations of human cardiac mechanics commonly require a large number of structural degrees of freedom. Additionally, these models are often coupled with lumped-parameter models of hemodynamics. High computational demands, however, slow down model calibration and therefore limit the use of cardiac simulations in clinical practice. As cardiac models rely on several patient-specific parameters, just one solution corresponding to one specific parameter set does not at all meet clinical demands. Moreover, while solving the nonlinear problem, 90% of the computation time is spent solving linear systems of equations. We propose to reduce the structural dimension of a monolithically coupled structure-Windkessel system by projection onto a lower-dimensional subspace. We obtain a good approximation of the displacement field as well as of key scalar cardiac outputs even with very few reduced degrees of freedom, while achieving considerable speedups. For subspace generation, we use proper orthogonal decomposition of displacement snapshots. Following a brief comparison of subspace interpolation methods, we demonstrate how projection-based model order reduction can be easily integrated into a gradient-based optimization. We demonstrate the performance of our method in a real-world multivariate inverse analysis scenario. Using the presented projection-based model order reduction approach can significantly speed up model personalization and could be used for many-query tasks in a clinical setting
A new damping modelling approach and its application in thin wall machining
In this paper, a new approach to modelling the
damping parameters and its application in thin wall
machining is presented. The approach to predicting the
damping parameters proposed in this paper eliminates the
need for experiments otherwise used to acquire these
parameters. The damping model proposed was compared
with available damping models and experimental results. A
finite element analysis and Fourier transform approach has
been used to obtain frequency response function (FRF)
needed for stability lobes prediction. Several predicted
stable regions using both experimental and numerical
FRFâs for various examples gave a good comparison.Engineering and Physical Sciences Research Counci
Using parametric model order reduction for inverse analysis of large nonlinear cardiac simulations
Cluster computingâaided model updating for a highâfidelity finite element model of a longâspan cableâstayed bridge
Model-based identification of damage from sparse sensor measurements using Neumann series expansion
A field experiment on a steel Gerber-truss bridge for damage detection utilizing vehicle-induced vibrations
A field experiment was conducted on a real continuous steel Gerber-truss bridge with artificial damage applied. This article summarizes the results of the experiment for bridge damage detection utilizing traffic-induced vibrations. It investigates the sensitivities of a number of quantities to bridge damage including the identified modal parameters and their statistical patterns, Nairâs damage indicator and its statistical pattern and different sets of measurement points. The modal parameters are identified by autoregressive time-series models. The decision on bridge health condition is made and the sensitivity of variables is evaluated with the aid of the MahalanobisâTaguchi system, a multivariate pattern recognition tool. Several observations are made as follows. For the modal parameters, although bridge damage detection can be achieved by performing MahalanobisâTaguchi system on certain modal parameters of certain sets of measurement points, difficulties were faced in subjective selection of meaningful bridge modes and low sensitivity of the statistical pattern of the modal parameters to damage. For Nairâs damage indicator, bridge damage detection could be achieved by performing MahalanobisâTaguchi system on Nairâs damage indicators of most sets of measurement points. As a damage indicator, Nairâs damage indicator was superior to the modal parameters. Three main advantages were observed: it does not require any subjective decision in calculating Nairâs damage indicator, thus potential human errors can be prevented and an automatic detection task can be achieved; its statistical pattern has high sensitivity to damage and, finally, it is flexible regarding the choice of sets of measurement points.</p
Vibration-based damage detection in beam structures with multiple cracks: modal curvature vs. modal flexibility methods
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