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Multi-extremum-modified response basis model for nonlinear response prediction of dynamic turbine blisk

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Abstract

For the nonlinear dynamic analyses of complex mechanical components, it is necessary to apply efficient modeling framework to reduce computational burden. The accurate surrogate model for approximating the nonlinear responses of several failures is a vital issue to provide robust and safe design conditions in complex engineering applications. In this paper, two different Modified multi-extremum Response Surface basis Models (MRSM) are proposed for dynamic nonlinear responses of failure capacities for turbine blisk responses. The proposed MRSM is established using two regression processes including regressed the input variables by linear or exponential basis functions in first calibrating phase and regressed the second-order polynomial basis function using inputs data provided by first stage in second calibrating procedure. A sensitivity analysis using MRSM is proposed to consider the variation of input variables on the nonlinear responses. In the sensitivity analysis procedure, the effects of input variables are evaluated using the calibrating results given from the first regressed process. To evaluate the performance of the proposed MRSM, three multi-extremum failure modes including radial deformation of compressor blisk, maximum strain, and stress of compressor blade and disk are considered. the prediction of MRSM of nonlinear responses for Thermal-fluid–structure system with dynamical nonlinear finite-element analyses is compared with response surface method (RSM) and artificial neural network (ANN). The predicted results of modeling approaches showed that the sensitivity analysis based on MRSM accurately provided the effective degree for input variables. The gas temperature has the highest effects on nonlinear responses of turbine blisk which is followed by angular speed and material density. The MRSM combined with basic exponential function performs better than other models, while the MRSM coupled with linear function is more accurate than ANN and RSM. The proposed MRSM models have illustrated the accurate and efficient framework for approximating dynamic structural analysis of complex components.

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Acknowledgements

This paper is co-supported by the National Natural Science Foundation of China (Grant nos. 51975124), Shanghai Belt and Road International Cooperation Project of China (Grant No. 20110741700) and University of Zabol (Grant no. UOZ-GR-9618-1). The authors would like to thank them. The Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, Saudi Arabia has funded this project under grant no. (FP-214-42).

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Authors and Affiliations

  1. Department of Aeronautics and Astronautics, Fudan University, Shanghai, 200433, People’s Republic of China

    Behrooz Keshtegar, Cheng-Wei Fei & Cheng Lu

  2. Department of Civil Engineering, Faculty of Engineering, University of Zabol, P.B. 9861335856, Zabol, Iran

    Behrooz Keshtegar

  3. Institute of Research and Development, The Faculty of Civil Engineering, Duy Tan University, Da Nang, 550000, Vietnam

    Behrooz Keshtegar

  4. Department of Civil Engineering, Birjand University of Technology, Birjand, Iran

    Mansour Bagheri

  5. Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, P. O. Box 80204, Jeddah, Saudi Arabia

    Osman Taylan

  6. Department of Civil and Environmental Engineering, Sejong University, 98 Gunja-dong, Gwangjin-gu, Seoul, 143-747, South Korea

    Duc-Kien Thai

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  1. Behrooz Keshtegar
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Correspondence to Cheng-Wei Fei.

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Keshtegar, B., Bagheri, M., Fei, CW. et al. Multi-extremum-modified response basis model for nonlinear response prediction of dynamic turbine blisk. Engineering with Computers 38 (Suppl 2), 1243–1254 (2022). https://doi.org/10.1007/s00366-020-01273-8

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