Measurement uncertainty of quantities that are functions of more than one measured variable are usually determined using propagation methods; either the Taylor Series Method or the Monte Carlo Method. Each of these requires critical assumptions that are more sweeping and potentially dangerous than commonly realized. The implications of these assumptions is explained along with some examples of how violation of these assumptions invalidates the uncertainty estimate. A new perspective based on consideration of potential error sources is presented ranging from the physical system being measured, the measurement system, the data reduction system, to the final experimental measurement result. An alternative approach that relies on sampling of error sources, whether known or unknown, is demonstrated through several examples. These examples demonstrate that the alternative approach can provide a more realistic estimate of total experimental uncertainty; one which is commonly much larger than that provided by traditional propagation methods.
- Fluids Engineering Division
Limitations of and Alternatives to Traditional Uncertainty Quantification for Measurements
Smith, BL, & Oberkampf, WL. "Limitations of and Alternatives to Traditional Uncertainty Quantification for Measurements." Proceedings of the ASME 2014 4th Joint US-European Fluids Engineering Division Summer Meeting collocated with the ASME 2014 12th International Conference on Nanochannels, Microchannels, and Minichannels. Volume 1D, Symposia: Transport Phenomena in Mixing; Turbulent Flows; Urban Fluid Mechanics; Fluid Dynamic Behavior of Complex Particles; Analysis of Elementary Processes in Dispersed Multiphase Flows; Multiphase Flow With Heat/Mass Transfer in Process Technology; Fluid Mechanics of Aircraft and Rocket Emissions and Their Environmental Impacts; High Performance CFD Computation; Performance of Multiphase Flow Systems; Wind Energy; Uncertainty Quantification in Flow Measurements and Simulations. Chicago, Illinois, USA. August 3–7, 2014. V01DT40A005. ASME. https://doi.org/10.1115/FEDSM2014-22068
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