## 5 Conclusions  
The main contributions of the present study are summarized as follows:  
1. A reliability assessment method involving the fusion of simulation and test data, as well as a simulation evaluation method, was proposed. On the basis of the Bayesian method for zero-failure data, a reliability life prediction method based on data fusion theory was proposed that involves the fusion of test and simulation data. According to the principle of \"high probability\", we developed a method for stimulating the life and reliability testing through confidence limits. This method can solve problems of non-normal distributions such as the Weibull distribution, which is commonly used in engineering.
2. The proposed simulation and test data fusion method was validated by a numerical example. The results indicated that the error of the predicted life was reduced by 10.9% compared with that obtained using the original method under reasonable simulation conditions.
3. An LCF life reliability assessment was conducted for an aero-engine compressor disk, taking advantage of zero-failure data from the test and the simulation reliability assessment. Multiple sources of uncertainty were fully considered and quantified, such as the geometry, model parameters, and discrete errors. The uncertainties were quantified via geometric measurements of 13 actual compressor disks and fatigue test data of 42 specimens.
4. An LCF life reliability analysis of compressor disks was performed using the proposed reliability assessment method based on the fusion of test and simulation data. The results indicated that the lower confidence limit of the life predicted via the method using the fusion of test and simulation data was 6.02% higher than that of the evaluation method based on zero-failure test data at a reliability of 99.87% and a confidence level of \(\gamma\) = 0.95.  
In summary, this paper introduces the concept of exploiting zero-failure test data and high-precision simulation results for reliability assessment of events related to aero-engine disks with a low failure probability. The proposed method can also provide guidance for the development of validation test programs for disk components and the design of life extension programs.  
Methodology, R.C. and G.C.; validation, R.C. and G.C.; formal analysis, R.C. and X.L.; data curation, R.C. and X.L.; writing--original draft preparation, R.C., G.C. and X.L.;  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test Prediction Results** & **Simulation Prediction Results** & **Fusion Predicted Results** & **Percentage Increase of Lower Confidence Limit for Reliable Life** \\ \hline
16,340 & 16,251 & 17,324 & 6.02\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Reliable life prediction results obtained by fusing current test data with simulation data (Unit: cycles).  
writing--review and editing, R.C., G.C. and X.L.; supervision, X.L. and G.C.; project administration, X.L., G.C., X.A. and H.Z.; funding acquisition, X.L., G.C., X.A. and H.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (NSFC) (Grant No. 52105138); (Grant Nos. 51875023). Postdoctoral Science Foundation of China (CPSF) (Grant No. 2021M690289). National Science and Technology Major Project (Grant No. J2019-IV-0008-0076).  
The results reported in this study were obtained using our in-house code. The experimental data were obtained from measurements and fatigue experiments on real turbine disks. The data for producing the reported results will be made available upon request.  
The authors declare no conflict of interest.