Finite Element Model Calibration Approach for Ares I-X

Horta, Lucas G.; Reaves, Mercedes C.; Buehrle, Ralph D.; Templeton, Justin D.; Lazor, Daniel R.; Gaspar, James L.; Parks, Russel A.; Bartolotta, Paul A.

doi:10.1007/978-1-4419-9834-7_92

Cited by 8 publications

(5 citation statements)

References 18 publications

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“…The comparison shows that the majority of the measured frequencies were within 5% of predictions, with one exception at 6.4% for the 3 rd bending mode in the Y-direction. More information about the use of the measured data in the post-test analysis is included in a companion paper 9 . …”

Section: Resultsmentioning

confidence: 99%

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

Templeton

Buehrle

Gaspar

et al. 2011

Structural Dynamics, Volume 3

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Section: Resultsmentioning

confidence: 99%

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

Templeton

Buehrle

Gaspar

et al. 2011

Structural Dynamics, Volume 3

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“…The second axial frequency is approximately 29.0-29. 4 Hz. The range of modal damping value is rather low (see Table 1) and is believed to be a very conservative estimate.…”

Section: In-flight Modal Identificationmentioning

confidence: 99%

Ares I-X In-Flight Modal Identification

Bartkowicz

James

2011

52nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

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Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction. Nomenclature C= damping matrix K = stiffness matrix M = mass matrix x = vector of x f = force vector ф A = mode shape A T = period

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“…If the probability is not zero, a reconciling solution is obtained by minimizing a quadratic function of the prediction error using the nonlinear optimization approach described by Lewis [17]. Although some of the Ares I-X initial results are reported in Buehrle [18] and Horta [19], this document includes additional full vehicle calibration results.…”

Section: Introductionmentioning

confidence: 99%

Finite Element Model Calibration for Ares I-X Flight Vehicle

et al. 2011

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Ares I-X is a flight test vehicle developed by NASA to demonstrate a new class of crew launch vehicle. For this first flight test, the first stage was a four segment solid rocket booster with mass simulators used to represent the other sections of the Ares I vehicle. Although this vehicle is significantly simpler than the Ares I, model calibration was required for the finite element model used in loads analysis and flight control evaluations before its maiden flight. The process of calibrating models involves updating parameters and reconciling predictions with test data. This work presents a probabilistic approach to the calibration process. The approach uses Analysis of Variance (ANOVA) for parameter sensitivity, nonlinear optimization to minimize the error between test and analysis, and multiple FEM models to bound the system response and to assess the probability of finding a reconciling solution. To reduce the computational burden associated with ANOVA, response surface models are used in lieu of computationally intensive finite element solutions. Uncertainty in the parameters and their effect on the frequency response function is studied in terms of Principal Values of the frequency response functions. Uncertainty bounds of the principal values are established across multiple models to allow one to determine the probability of finding a solution that reconciles analysis with test results. Results from applying this model calibration process to the Ares I-X project are described. Findings presented in the paper confirmed that the baseline model used for pre-flight assessments was within the acceptable range established for guidance and control.

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Finite Element Model Calibration Approach for Ares I-X

Cited by 8 publications

References 18 publications

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

Ares I-X In-Flight Modal Identification

Finite Element Model Calibration for Ares I-X Flight Vehicle

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