System Identification of Structural Dynamic Parameters From Modal Data
Comparisons between observed behavior and predicted response from a mathematical representation are often not consistent. Through Bayesian inference, use can be made of the data and parameters of the model to arrive at a better correlation. The correspond
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Springer-Verlag Berlin Heidelberg GmbH 1982
G. A. Keramidas C.A. Brebbia Computational Mechanics Centre, Ashurst Lodge, Ashurst, Southampton, Hampshire, S04 2AA
UK
ISBN 978-3-662-11355-4 ISBN 978-3-662-11353-0 (eBook) DOI 10.1007/978-3-662-11353-0
This work is subject
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is concerned, specifically those of translation, reprinting, re-use of illustrations, broadcasting, reproduction by photocopying machine or similar means, and storage in data banks. Under § 54 of the Gennan Copyright Law where copies are made fOr other than private use a tee is payable to
'Verwertungsgesellschafi Wort', Munich.
©Springer-Verlag Berlin Heidelberg 1982 Originally published by Springer-Verlag Berlin Heidelberg New York in 1982 Soticover reprint of the hardcover lst edition 1982 The use of registered names, trademarks, etc. in this publication does nm imply, even in the absence of a specific statement, that such names are exempt from the relevam protective laws and regulations and therefOre free fOr general use.
CONTENTS SESSION 1
KEYNOTE ADDRESS
SESSION 2A
SYSTEM IDENTIFICATION
Damage Identification of Existing Structures
3
Survey on Parameter Estllnation Within System Identification Using a Priori Knowledge of System Analysis
17
Modal and Damage Analysis of Elastic Structures Frequency Separation by Non-Linear Filter
28
System Identification of Structural Dynamic Parameters from Modal Data
40
James T.P. Yao, Purdue University, W. Lafayette, U.S.A
Natke, H.G., Curt-Risch-Institut, Universitat Hannover, Germany
Walter Wedig, University Karlsruhe
Jean-Guy Beliveau, University de Sherbrooke, Canada Samir Chater, Lavalin Inc., Quebec, Canada SESSION 2B
WATER RESOURCES
Solution of an Inverse Problem in Groundwater Flow Using Uncertain DataD. H
53
Pressure Field Data Acquisition on a Physical Well Model Using a Minicomputer
64
A Two Dimensional Numerical Model for Mising in Natural Rivers
76
D.H. Tang, Princeton University, U.S.A. G.F. Pinder, Princeton University, U.S.A
Jerry S. Martin, Bureau of Reclamation
Y.S. Halabi, H.T. Shen, T.S. Papatheodorou and W.L. Briggs, Clarkson College of Technology, U.S.A.
SESSION 3A
DATA IDENTIFICATION
Acquisition and Processing of Experimental Data by a Mini Conputer in a Hydraulic Laboratory Cedo Maksimovic, Institute of Hydraulic Engineering, Yugoslavia
91
Computer-Based Measurements of Incipient Wave Breaking S.E. Ramberg and C.L. Bartholomew Naval Research Laboratory, Washington D.C., U.S.A
102
Acquisition and Display of Data From Large Arrays of Sensors Johannes Buhler, Institut fur Hydromechanik und Wasserwirtschaft, Switzerland
116
SESSION 3B
ATMOSPHERIC FLUID DYNAMICS
Designing Experiments for Investigating Collmnar Vortices John T. Snow, Purdue University, U.S.A.
129
Comparative Studies of Tornado-Like Vortices David R. Smith, Purdue University, U.S.A.
141
N'Ll!IErical calculation of the Regime Diagram for the Atmospheric General Circulation Experiment T. Miller and R
