Prediction Interval Development for Wind-Tunnel Balance Check-Loading

Abstract

The current approach used to apply uncertainty intervals to balance estimated loads is based on the root mean square error from calibration. Using the root mean square error, a constant interval is applied around the estimated load and it is expected that a predetermined percentage of the check-loads applied fall within this constant uncertainty interval. However, this approach ignores additional sources of uncertainty and assumes constant uncertainty regardless of the load combination and magnitude applied to the balance. Rigorous prediction interval theory permits varying interval widths but fails to account for the additional error sources that are unrelated to the mathematical modeling. An engineered solution is proposed that combines prediction interval theory and the need to account for the additional sources of uncertainty from calibration and check loading. Results from a case study using the in-situ load system show improved probabilistic behavior in terms of uncertainty interval capture percentage when compared with the current root mean square error method.

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