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  • 1
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    Component testing for dynamic model verification (1984)
    In:  CASI
    Details
    Publication Date: 2006-02-14
    Description: Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, adjusted if necessary to bring it into agreement with the data, and then qualified for future use in predicting system response in a different dynamic environment. These are various ways to conduct model verification. The approach taken here employs Bayesian statistical parameter estimation. Unlike curve fitting, whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that funciton (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data; (2) will assist in the interpretation of test data; (3) can be used to help verify a design; (4) will reliably predict performance; and (5) in the case of space structures, will facilitate dynamic control.
    Keywords: AERODYNAMICS
    Type: NASA. Langley Research Center Recent Experiences in Multidisciplinary Analysis and Optimization, Part 2; 15 p
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  • 2
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    A computer program for model verification of dynamic systems (1987)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, and then qualified for future use in predicting system response in a different dynamic environment. There are various ways to conduct model verification. The approach adopted in MOVER II employs Bayesian statistical parameter estimation. Unlike curve fitting whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that function (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data, (2) will assist in the interpretation of test data, (3) can be used to help verify a design, (4) will reliably predict performance, and (5) in the case of space structures, facilitate dynamic control.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA. Marshall Space Flight Center Structural Dynamics and Control Interaction of Flexible Structures; p 199-214
    Format: application/pdf
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  • 3
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    Estimation of full modal damping matrices from complex test modes (1993)
    In:  Other Sources
    Details
    Publication Date: 2019-06-28
    Description: This paper describes the refinements of a previously published method for estimating a full modal damping matrix from complex test modes. It also documents application of the refined method to a structure where complex test modes were derived by the ERA method from multi-input random vibration test data. A numerical example based on simulated test data is presented to demonstrate the validity of the method. The application using real data was not successful, presumably because of noise in the small phase angles of the measured complex modes. Alternative test and data reduction procedures are suggested as possible remedies to the problem. A careful analysis of measurement and data processing errors should be made to examine basic feasibility before implementing the alternative procedures. The ability to estimate a full modal damping matrix is considered important for the preflight estimation of on-orbit damping, and for the synthesis of structural damping from substructure tests.
    Keywords: STRUCTURAL MECHANICS
    Type: AIAA PAPER 93-1668 , In: AIAA(ASME)ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 34th and AIAA/ASME Adaptive Structures Forum, La Jolla, CA, Apr. 19-22, 1993, Technical Papers. Pt. 6 (A93-33876 1; p. 3388-3398.
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  • 4
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    Model Verification of Mixed Dynamic Systems (1982)
    In:  Other Sources
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    Publication Date: 2019-06-28
    Description: MOVER uses experimental data to verify mathematical models of "mixed" dynamic systems. The term "mixed" refers to interactive mechanical, hydraulic, electrical, and other components. Program compares analytical transfer functions with experiment.
    Keywords: MECHANICS
    Type: MFS-23806 , NASA Tech Briefs (ISSN 0145-319X); 6; 2; P. 194
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  • 5
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    Improved dynamic modeling of a Space-Shuttle Turbo-Pump (1977)
    In:  Other Sources
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    Publication Date: 2019-07-13
    Description: The dynamic response of turbo-pumps has traditionally been modeled mathematically using electrical networks. A recently developed computer program is used herein to adjust the model parameters (L - inductance, R - resistance, C - capacitance, etc.) of the electrical network in an attempt to bring the analytical response of the network into closer agreement with newly-available experimental results. Results are presented for a fully-wetted (noncavitating) test of a Space-Shuttle Turbo-Pump and a significant improvement in the dynamic model is achieved.
    Keywords: SPACECRAFT PROPULSION AND POWER
    Type: SAE PAPER 770960 , Aerospace Meeting; Nov 14, 1977 - Nov 17, 1977; Los Angeles, CA
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  • 6
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    Model verification of mixed dynamic systems (1978)
    In:  Other Sources
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    Publication Date: 2019-06-27
    Description: A parameter-estimation method is described for verifying the mathematical model of mixed (combined interactive components from various engineering fields) dynamic systems against pertinent experimental data. The model verification problem is divided into two separate parts: defining a proper model and evaluating the parameters of that model. The main idea is to use differences between measured and predicted behavior (response) to adjust automatically the key parameters of a model so as to minimize response differences. To achieve the goal of modeling flexibility, the method combines the convenience of automated matrix generation with the generality of direct matrix input. The equations of motion are treated in first-order form, allowing for nonsymmetric matrices, modeling of general networks, and complex-mode analysis. The effectiveness of the method is demonstrated for an example problem involving a complex hydraulic-mechanical system.
    Keywords: SPACECRAFT DESIGN, TESTING AND PERFORMANCE
    Type: ASME PAPER 77-DET-85
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  • 7
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    A recent case study in system identification (1991)
    In:  Other Sources
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    Publication Date: 2019-07-13
    Description: Results of a recent study of a ten-bay truss structure at the NASA Langley Research Center are reported. First, the conditioning of complex eigenvectors derived by the ERA method is discussed. Results of parameter estimation using the SSID (Structural System Identification) code are then presented. Based on the results of the study, it is concluded that (1) parameter estimation based on modal data should include eigenvectors as well as eigenvalues; (2) the eigenvectors should be orthogonalized when orthogonality is poor due to closely spaced modes; and (3) the parameters used in the estimation should enable the model to match the data.
    Keywords: STRUCTURAL MECHANICS
    Type: AIAA PAPER 91-1190 , AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference; Apr 08, 1991 - Apr 10, 1991; Baltimore, MD; United States
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  • 8
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    Statistical analysis of modeling error in structural dynamic systems (1990)
    In:  Other Sources
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    Publication Date: 2019-07-13
    Description: The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.
    Keywords: SPACECRAFT DESIGN, TESTING AND PERFORMANCE
    Type: AIAA PAPER 90-1041 , AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference; Apr 02, 1990 - Apr 04, 1990; Long Beach, CA; United States
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