Finite Element Model Developed and Modal Analysis of Large Scale Steam Turbine Rotor: Quantification of Uncertainties and Model Updating

Giagopoulos, Dimitrios; Αραϊλόπουλος, Αλέξανδρος; Zacharakis, Ilias; Pipili, Eleni

doi:10.7712/120217.5349.16898

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…The Bayesian inference method is applied in rotor dynamic systems mainly for inverse uncertainty analysis, including fault diagnosis [164][165][166], model updating [167,168] and parameter identification [169,170], such as bearing parameters. In the Bayes scheme, expert knowledge is used in the process of model calibrations.…”

Section: Bayesian Inferencementioning

confidence: 99%

“…Estimation of unknown parameters under uncertainty such as measurement error is meaningful for robust system identification [247], accurate modeling and damage assessment [248]. Although model updating of rotor systems is closely related to parameter estimation and calibration, it is a dedicated topic in general dynamic systems and has its own principles [167,168,249]. This paper, which concentrates on uncertainty treatment, will not cover much of that area.…”

Section: Parameter Identificationmentioning

confidence: 99%

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A state-of-the-art review on uncertainty analysis of rotor systems

Sinou

Zhu

et al. 2023

Mechanical Systems and Signal Processing

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Section: Bayesian Inferencementioning

confidence: 99%

Section: Parameter Identificationmentioning

confidence: 99%

A state-of-the-art review on uncertainty analysis of rotor systems

Sinou

Zhu

et al. 2023

Mechanical Systems and Signal Processing

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“…This kind of test is not straightforward for an IBR/blisk, and the literature reflects different options. [6][7][8][9] Although model updating techniques have been applied to represent the global behaviour of rotor systems, 10,11 this article takes a step forward and applies these techniques to represent the mistuning phenomena in rotor components. The idea is to perform a standard modal test that characterizes dynamically the whole structure.…”

Section: Introductionmentioning

confidence: 99%

Application of model updating techniques to turbomachinery rotor components

Alonso

Albizuri

Esparza³

2019

Advances in Mechanical Engineering

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Model updating techniques are commonly used to improve simulation accuracy. Experimental data of component testing under laboratory conditions are normally used to improve analytical predictions of that component under operational conditions. In this study, we have applied these techniques to the dynamics of turbomachinery components. Dynamics of turbomachinery rotor components are normally analysed assuming perfect cyclic symmetry of the basis sector (one blade and its corresponding part of the disc) and this sector is mechanically the same in every angular position. However, the manufacturing process introduces small differences among sectors (mistuning) and changes the global dynamic behaviour. There are several analytical approaches in the literature to model these differences with reduced order models of the whole rotor that include the frequency differences among sectors, which can be obtained experimentally in a component test. Several approaches in the literature use experimental results from a test with a particular set-up in order to obtain the inputs for the models. The approach proposed in this article is just to perform a standard modal test that generates the input for model updating and to extract from the updated model the required input for representing the mistuning phenomena in turbomachinery rotor components.

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“…Standard optimization techniques are then used to find the optimal values of the structural parameters that minimize a singleobjective function. [9][10][11][12][13] It is worthy to mention that using a full-scale FE model for conducting model updating has been investigated by previous researchers. Both gradient-based updating methods using deterministic objective function 14,15 and stochastic algorithms applying probabilistic objective functions 16 have been previously examined.…”

Section: Introductionmentioning

confidence: 99%

A model-based fatigue damage estimation framework of large-scale structural systems

Giagopoulos

Αραϊλόπουλος

Natsiavas

2019

Structural Health Monitoring

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A model-based fatigue damage estimation framework is proposed for online estimation of fatigue damage, for structural systems by integrating operational vibration measurements in a high-fidelity, large-scale, finite element (FE) model and applying a fatigue damage accumulation methodology. To proceed with fatigue predictions, one has to infer the stress response time histories characteristics based on the monitoring information contained in vibration measurements collected from a limited number of sensors attached to a structure. Predictions, like the existence, the location, the time, and the extent of the damage, are possible if one combines the information in the measurements with information obtained from a high-fidelity FE model of the structure. Such a model may be optimized with respect to the data, using state-of-the-art FE model updating techniques. These methods provide much more comprehensive information about the condition of the monitored system than the analysis of raw data. The diagnosed degradation state, along with its identified uncertainties, can be incorporated into robust reliability tools for updating predictions of the residual useful lifetime of structural components and safety against various failure modes taking into account stochastic models of future loading characteristics. Fatigue is estimated using the Palmgren–Miner damage rule, S-N curves, and rainflow cycle counting of the variable amplitude time histories of the stress components. Incorporating a numerical model of the structure in the response estimation procedure, permits stress estimation at unmeasured spots. The proposed method is applied in a steel frame of a real city bus.

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Finite Element Model Developed and Modal Analysis of Large Scale Steam Turbine Rotor: Quantification of Uncertainties and Model Updating

Abstract: Abstract. In this work, the effectiveness of a computational framework to handle large scale linear and nonlinear models is presented by calibrating a high-fidelity

Cited by 5 publications

References 14 publications

A state-of-the-art review on uncertainty analysis of rotor systems

A state-of-the-art review on uncertainty analysis of rotor systems

Application of model updating techniques to turbomachinery rotor components

A model-based fatigue damage estimation framework of large-scale structural systems

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