Abstract
The parameters considered in structural dynamic reliability analysis have strong uncertainties during machinery operation, and affect analytical precision and efficiency. To improve structural dynamic fuzzy reliability analysis, we propose the weighted regression-based extremum response surface method (WR-ERSM) based on extremum response surface method (ERSM) and weighted regression (WR), by considering the randomness of design parameters and the fuzziness of the safety criterion. Therein, we utilize the ERSM to process the transient to improve computational efficiency, by transforming the random process of structural output response into a random variable. We employ the WR to find the efficient samples with larger weights to improve the calculative accuracy. The fuzziness of the safety criterion is regarded to improve computational precision in the WR-ERSM. The WR-ERSM is applied to perform the dynamic fuzzy reliability analysis of an aeroengine turbine blisk with the fluid-structure coupling technique, and is verified by the comparison of the Monte Carlo (MC) method, equivalent stochastic transformation method (ESTM) and ERSM, with the emphasis on model-fitting property and simulation performance. As revealed from this investigation, (1) the ERSM has the capacity of processing the transient of the structural dynamic reliability evaluation, and (2) the WR approach is able to improve modeling accuracy, and (3) regarding the fuzzy safety criterion is promising to improve the precision of structural dynamic fuzzy reliability evaluation, and (4) the change rule of turbine blisk structural stress from start to cruise for the aircraft is acquired with the maximum value of structural stress at t = 165 s and the reliability degree (Pr = 0.997) of turbine blisk. The proposed WR-ERSM can improve the efficiency and precision of structural dynamic reliability analysis. Therefore, the efforts of this study provide a promising method for structural dynamic reliability evaluation with respect to working processes.
Highlights
In mechanical systems, the structures always endure complex loads in the extreme environment.For instance, an aeroengine turbine blisk always suffers from high temperature, high pressure and high speed under operation [1]
(2) the weighted regression (WR) approach is able to improve modeling accuracy, and (3) regarding the fuzzy safety criterion is promising to improve the precision of structural dynamic fuzzy reliability evaluation, and (4) the change rule of turbine blisk structural stress from start to cruise for the aircraft is acquired with the maximum value of structural stress at t = 165 s and the reliability degree (Pr = 0.997) of turbine blisk
The result that the precision of the weighted regression-based extremum response surface method (WR-extremum response surface method (ERSM)) is superior to the ERSM indicates that considering the fuzziness of the safety criterion besides the WR is efficient for the improvement of structural dynamic reliability analysis
Summary
The structures always endure complex loads in the extreme environment. Flow chart of structural dynamic fuzzy reliability analysis with regression weighted extremum regression response surface method (WR-ERSM). The samples of random inputs are extracted by the full factorial design [29,30], and the extrema of response processes are gained as new output responses based on dynamic deterministic analysis in the time domain of interest, and their weights are confirmed by a series of deterministic analyses with the acquired input samples and FE model. The ERSM was developed to evaluate structural dynamic reliability by considering the extremum values instead of all the output responses within the time domain of interest, and was proved to be efficient in terms of the efficiency improvement [18,33]. Based on the above analysis, we can derive the WR-ERSM model
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