Integrally Bladed Rotor Mistuning Identification and Model Updating Using Geometric Mistuning Models

2021 ◽  
Author(s):  
Joseph Beck ◽  
Jeffrey Brown ◽  
Daniel Gillaugh ◽  
Emily Carper ◽  
Alex Kaszynski
Keyword(s):  
Author(s):  
Joseph A. Beck ◽  
Jeffrey M. Brown ◽  
Daniel L. Gillaugh ◽  
Emily B. Carper ◽  
Alex A. Kaszynski

Abstract Non-uniform manufacturing variations and uneven usage wear and damage, referred to as mistuning, can drastically alter the dynamic response of Integrally Blade Rotors (IBR)s. Optical scanners, combined with Finite Element Model (FEM) mesh metamorphosis algorithms, have provided capabilities to create analytical models that reduce the effect of geometrical uncertainties in numerical predictions. However, deviations in material properties cannot be obtained via optical scanning, so additional approaches are needed. A geometric mistuning Reduced-Order Model (ROM) is developed and modified to solve for unknown IBR sector eigenvalues that are linearly proportional to Elastic modulus. The developed approach accounts for both proportional and non-proportional mistuning and allows updating of the Elastic modulus for each sector in the ROM. Different tuned and mistuned modal reduction procedures are employed to understand the implications of each for identifying mistuning. Simulated test data with known inputs indicate the efficiency and accuracy of the method and improvements over using a traditional, tuned mode approach. The developed methods are then extended to bench-level traveling wave excitation data to discern how sector frequencies vary due to geometry and modulus mistuning.


Author(s):  
Joseph Beck ◽  
Jeffrey Brown ◽  
Daniel Gillaugh ◽  
Emily Carper ◽  
Alex Kaszynski

Abstract Non-uniform manufacturing variations and uneven usage wear and damage, referred to as mistuning, can drastically alter the dynamic response of Integrally Bladed Rotors (IBRs). Optical scanners, combined with Finite Element Model mesh metamorphosis algorithms, have provided capabilities to create analytical models that reduce the effect of geometrical uncertainties in numerical predictions. However, deviations in material properties cannot be obtained via optical scanning, so additional approaches are needed. A geometric mistuning Reduced-Order Model (ROM) is developed and modified to solve for unknown IBR sector eigenvalues that are linearly proportional to Elastic modulus. The developed approach accounts for both proportional and non-proportional mistuning and allows updating of the Elastic modulus for each sector in the ROM. Different tuned and mistuned modal reduction procedures are employed to understand the implications of each for identifying mistuning. Simulated test data with known inputs indicate the efficiency and accuracy of the method and improvements over using a traditional, tuned mode approach. The developed methods are then extended to bench-level traveling wave excitation data to discern how sector frequencies vary due to geometry and modulus mistuning.


2008 ◽  
Author(s):  
W. Matthew Collins ◽  
Keith Rayner

2020 ◽  
Vol 14 (3) ◽  
pp. 7141-7151 ◽  
Author(s):  
R. Omar ◽  
M. N. Abdul Rani ◽  
M. A. Yunus

Efficient and accurate finite element (FE) modelling of bolted joints is essential for increasing confidence in the investigation of structural vibrations. However, modelling of bolted joints for the investigation is often found to be very challenging. This paper proposes an appropriate FE representation of bolted joints for the prediction of the dynamic behaviour of a bolted joint structure. Two different FE models of the bolted joint structure with two different FE element connectors, which are CBEAM and CBUSH, representing the bolted joints are developed. Modal updating is used to correlate the two FE models with the experimental model. The dynamic behaviour of the two FE models is compared with experimental modal analysis to evaluate and determine the most appropriate FE model of the bolted joint structure. The comparison reveals that the CBUSH element connectors based FE model has a greater capability in representing the bolted joints with 86 percent accuracy and greater efficiency in updating the model parameters. The proposed modelling technique will be useful in the modelling of a complex structure with a large number of bolted joints.


2016 ◽  
Vol 106 (8) ◽  
pp. 490-497
Author(s):  
Dong-Uk PARK ◽  
Jae-Bong KIM ◽  
Nam-Sik KIM ◽  
Sung-Il KIM

2016 ◽  
Vol 106 (8) ◽  
pp. 538-545 ◽  
Author(s):  
Guanzhe Fa ◽  
Enrico Mazzarolo ◽  
Leqia He ◽  
Bruno Briseghella ◽  
Luigi Fenu ◽  
...  

2011 ◽  
Vol 71-78 ◽  
pp. 4501-4505
Author(s):  
Ming Chen ◽  
Wan Zhou

Although modern bridge are carefully designed and well constructed, damage may occur in them due to unexpected causes. Currently, many different techniques have been proposed and investigated in bridge condition assessment. However, evaluation efficiency of condition assessment has not been paid much attention by the researchers. A fast evaluation of the urban railway bridge condition based on the cloud computing is presented. In this paper dynamic FE model and Artificial neural networks technique is applied to model updating. The cloud computing model provides the basis for fast analyses. It was found that when applied to the actually railway bridges, the proposed method provided results similar to those obtained by experts, but can improve efficiency of bridge


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