Book Chapter10.1007/978-94-015-8508-8_7
Direct Methods using Modal Data
Michael I. Friswell,John E. Mottershead +1 more
- 01 Jan 1995
- pp 126-157
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TL;DR: This chapter discusses direct methods, which have the great advantage of not requiring iteration and thus the possibilities of divergence and excessive computation are eliminated.
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Abstract: To understand the strengths and weaknesses of the direct methods one must understand what the methods do, where errors may occur and how they are propagated into the updated model. Of course, as the title implies, these methods have the great advantage of not requiring iteration and thus the possibilities of divergence and excessive computation are eliminated.
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Citations
Model Update Using Modal Contribution to Static Flexibility Error
Keith K. Denoyer,Lee D. Peterson +1 more
TL;DR: In this paper, a new technique for the parametric correction of full-order analytical stiffness matrices from reduced-order modal measurements is presented, which corrects model parameters by minimizing a matrix residual formed at measurement degrees of freedom only.
13
Comparing Model Update Error Residuals and Effects on Model Predictive Accuracy
Keith K. Denoyer,Lee D. Peterson +1 more
TL;DR: In this article, the effect of error residual choice on the predictive capability of an updated structural model is examined, and the results show that the amount of uncertainty in predicted static displacements, static loads, and mode shapes and frequencies is directly related to the choice of the error residual and is different in each case.
6
A two-stage method to estimate the embedded length of foundation piles using FRF-based model updating
A. Ioakim,L.J. Prendergast +1 more
References
Improvement of a Large Analytical Model Using Test Data
Alex Berman,E. J. Nagy +1 more
TL;DR: In this paper, a method has been developed which uses measured normal modes and natural frequencies to improve an analytical mass and stiffness matrix model of a structure, which directly identifies, without iteration, a set of minimum changes in the analytical matrices which force the eigensolutions to agree with the test measurements.
616
Stiffness matrix adjustment using mode data
TL;DR: In this paper, a procedure that uses structural connectivity information to optimally adjust deficient stiffness matrices is presented. But the adjustment performed are such that the percentage change to each stiffness coefficient is minimized.
378
Optimization Procedure to Correct Stiffness and Flexibility Matrices Using Vibration Tests
TL;DR: The Lagrange function for the stiffness matrix weighted norm of the errors between the given and the optimal stiffness matrix unity matrix is defined in this paper, where the error is defined as the difference between the error between the desired stiffness matrix and the given stiffness matrix.
330
Eigenvalue/eigenvector assignment using output feedback
TL;DR: In this article, the problem of pole-assignment in a linear time-invariant multivariable system using output feedback is considered, and sufficient conditions are derived to assign an almost arbitrary set of min (n,m+r- 1) distinct eigenvalues, where n, m, and r are the number of states, inputs, and outputs, respectively.
204