## 7 Conclusions  
The paper studied the uncertainty of rainflow damage computed in stationary random loadings and in those non-stationary random loadings formed by a finite number of stationary states. Uncertainty refers to the statistical variability that characterizes the damage when it is computed from a limited number of stress-time histories, often from only one. Uncertainty was evaluated by a confidence interval on expected damage, constructed after a direct analysis of stress-time histories of finite length (which are subdivided into states and blocks). In the non-stationary switching case, the proposed confidence interval is based on an approximate solution derived for the confidence interval on the sum of normally distributed random variables. The correctness of the proposed confidence intervals on damage was first verified by numerical simulations (with three load types) and then by experiments with strain-time histories measured on a mountain bike. Tracks, road surfaces and riding conditions were designed to obtain stationary and non-stationary switching measured records. In a postprocessing phase after measurements, a statistical test (run test) was applied to check whether the records were in fact stationary or non-stationary. In experiments, a validation set with few strain-time histories was used for verification purposes. The obtained results allow the following conclusions to be drawn:  
* subdivision into states and blocks determines a negligible loss of fatigue cycles compared to the cycles counted in each state/block, which is especially valid when the stress-time history has negligible or no variation in its mean value among different stationary states;
* in numerical simulations, the estimated confidence level was almost coincident with the theoretical value of 95% for any number of block subdivisions, thus confirming the accuracy of the proposed method. A slightly larger confidence (98.1%) characterizes the limit case of two block subdivisions, which is indeed not recommended;
* in both simulations and experiments, the width of the confidence interval decreases as the number of blocks increases, until it approaches a sort of limit value characterizing the inherent randomness of the considered random loading. This trend then suggests the use of the largest possible number of block subdivisions, provided that a sufficient number of cycles remains within each block;
* the run test proved to be a powerful tool for classifying the measured records as stationary or non-stationary, regardless of the window length chosen in the analysis;
* the upper value of the confidence interval may be used as a reference damage value in a structural durability assessment. Figure 12: Confidence interval on expected damage for non-stationary switching loading measured in the mountain bike, as a function of the number of blocks. **Supplementary Materials:** A Matlab binary file is provided with the strain-time histories measured in the mountain bike (file: Measurements_mountain_bike_SuppMat.mat). The file has 63 columns in total. The first column is the vector of time (in seconds) common to all records; the other columns from 2 to 63 represent the stationary and non-stationary record values measured on the bike, normalized to zero mean and unit variance. Data comply with the acquisition described in Section 6.1. Columns from 2 to 11 group the records for Case M, column 12 is the single record for Case S and columns from 13 to 42 collect the validation set for the stationary case. The single non-stationary record is placed in column 43, and the remaining columns from 44 to 63 refer to the validation set for the non-stationary case. The data can be downloaded at [[https://www.pragtic.com/dataAppNci2023.php](https://www.pragtic.com/dataAppNci2023.php)]([https://www.pragtic.com/dataAppNci2023.php](https://www.pragtic.com/dataAppNci2023.php)). **Author Contributions:** Conceptualization, J.M.E.M. and D.B. ; experiments, J.M.E.M. ; data analysis, J.M.E.M. and D.B. ; writing--original draft preparation, J.M.E.M.