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Title: Structural system identification of a composite shell

Abstract

Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.

Authors:
; ; ;
Publication Date:
Research Org.:
Sandia National Labs., Albuquerque, NM (United States)
Sponsoring Org.:
USDOE; USDOE, Washington, DC (United States)
OSTI Identifier:
5752783
Report Number(s):
SAND-91-1904C; CONF-920499-1
ON: DE92009060
DOE Contract Number:
AC04-76DP00789
Resource Type:
Conference
Resource Relation:
Conference: 33. Structural dynamics and materials conference, Dallas, TX (United States), 13-15 Apr 1992
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; COMPOSITE MATERIALS; FREQUENCY ANALYSIS; FINITE ELEMENT METHOD; ALGORITHMS; DATA ANALYSIS; EIGENVALUES; EPOXIDES; GRAPHITE; IMPACT SHOCK; MATHEMATICAL MODELS; MECHANICAL VIBRATIONS; RESPONSE FUNCTIONS; STATISTICS; STRUCTURAL MODELS; CARBON; ELEMENTAL MINERALS; ELEMENTS; FUNCTIONS; MATERIALS; MATHEMATICAL LOGIC; MATHEMATICS; MINERALS; NONMETALS; NUMERICAL SOLUTION; ORGANIC COMPOUNDS; ORGANIC OXYGEN COMPOUNDS; 420500* - Engineering- Materials Testing

Citation Formats

Red-Horse, J.R., Carne, T.G., James, G.H., and Witkowski, W.R. Structural system identification of a composite shell. United States: N. p., 1991. Web.
Red-Horse, J.R., Carne, T.G., James, G.H., & Witkowski, W.R. Structural system identification of a composite shell. United States.
Red-Horse, J.R., Carne, T.G., James, G.H., and Witkowski, W.R. 1991. "Structural system identification of a composite shell". United States. doi:.
@article{osti_5752783,
title = {Structural system identification of a composite shell},
author = {Red-Horse, J.R. and Carne, T.G. and James, G.H. and Witkowski, W.R.},
abstractNote = {Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 1991,
month = 1
}

Conference:
Other availability
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  • Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.
  • One of the basic requirements in engineering analysis is the development of a mathematical model describing the system. Frequently, comparisons with test data are used as a measurement of the adequacy of the model. An attempt is typically made to update or improve the model to provide a test-verified analysis tool. System identification provides a systematic procedure for accomplishing this task. The terms system identification, parameter estimation, and model correlation all refer to techniques that use test information to update or verify mathematical models. The goal of system identification is to improve the correlation of model predictions with measured testmore » data, and produce accurate, predictive models. For nonmetallic structures the modeling task is often difficult due to uncertainties in the elastic constants. In this work a parameter identification procedure was used to determine the elastic constants of a cylindrical, graphite epoxy composite shell. A finite element model of the shell was created, which included uncertain orthotropic elastic constants. A modal survey test was then performed on the shell. The resulting modal data, along with the finite element model of the shell, were used in a Bayes estimation algorithm. This permitted the use of covariance matrices to weight the confidence in the initial parameter values as well as confidence in the measured test data. The estimation procedure also employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem. 17 refs., 7 figs.« less
  • A finite element model of a composite shell was created. The model includes uncertain orthotropic elastic constants. To identify these constants, a modal survey was performed on an actual shell. The resulting modal data along with the finite element model of the shell were used in a Bayes estimation algorithm. Values of the elastic constants were estimated which minimized the differences between the test results and the finite element predictions. The estimation procedure employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem.
  • Nonlinear forces acting on offshore structures are examined from a system identification perspective. The nonlinearities are induced by ocean waves and may become significant in many situations. They are not necessarily in the form of Morison`s equation. Various wave force models are examined. The force function is either decomposed into a set of base functions or it is expanded in terms of the wave and structural kinematics. The resulting nonlinear system is decomposed into a number of parallel no-memory nonlinear systems, each followed by a finite memory linear system. A conditioning procedure is applied to decouple these linear sub-systems; amore » frequency domain technique involving autospectra and cross-spectra is employed to identify the linear transfer functions. The structural properties and the force transfer parameters are determined with the aid of the coherence functions. The method is verified using simulated data. It provides a versatile and non-iterative approach for dealing with nonlinear interaction problems encountered in offshore structural analysis and design.« less
  • Mitigating the effects of damaging wind turbine loads and responses extends the lifetime of the turbine and, consequently, reduces the associated Cost of Energy (COE). Active control of aerodynamic devices is one option for achieving wind turbine load mitigation. Generally speaking, control system design and analysis requires a reasonable dynamic model of {open_quotes}plant,{close_quotes} (i.e., the system being controlled). This paper extends the wind turbine aileron control research, previously conducted at the National Wind Technology Center (NWTC), by presenting a more detailed development of the wind turbine dynamic model. In prior research, active aileron control designs were implemented in an existingmore » wind turbine structural dynamics code, FAST (Fatigue, Aerodynamics, Structures, and Turbulence). In this paper, the FAST code is used, in conjunction with system identification, to generate a wind turbine dynamic model for use in active aileron control system design. The FAST code is described and an overview of the system identification technique is presented. An aileron control case study is used to demonstrate this modeling technique. The results of the case study are then used to propose ideas for generalizing this technique for creating dynamic models for other wind turbine control applications.« less