Sentence examples for benchmark uncertainty from inspiring English sources

The topic of this paper is the development of sensitivity and uncertainty analysis capability to the CASMO-4/CASMO-4E – SIMULATE-3 code sequence in the context of the OECD/NEA benchmark 'Uncertainty Analysis in Best-Estimate Modelling for Design, Operation and Safety Analysis of LWRs' (UAM).

These methodologies are validated using a simplified pin-cell and a fuel assembly, and then applied to a full 3D core in the context of the OECD/NEA UAM benchmark (Uncertainty Analysis in Best-Estimate Modeling for Design, Operation and Safety Analysis of LWRs).

The sensors are then installed in a field location where laboratory benchmarked uncertainty is applied to field measurements.

A Nuclear Energy Agency NEA, Organization for Economic Co-operation Development OECDt (OECD) benchmark for Uncertainty Analysis in Modeling (UAM) is defined in order to facilitate the development and validation of available uncertainty analysis and sensitivity analysis methods for best-estimate Light water Reactor (LWR) design and safety calculations.

Hence, the outcome of this study may be useful for benchmarking estimation uncertainty for future events empirically.

This study benchmarks discharge uncertainty in several commonly used sensors by laboratory flume testing with and without a woody debris model.

This paper describes the new database, and applications of SFCOMPO-2.0 for computer code validation, integral nuclear data benchmarking, and uncertainty analysis in nuclear waste package analysis are briefly illustrated.

Such results are useful for benchmarking epistemic (model) uncertainty associated with tsunami predictions.Next, we examine the sensitivity of wave profile predictions at the four GPS buoys while considering strike, dip, and slip variations together with different original slip distributions.

The information on quantified variability is valuable for benchmarking the prediction uncertainty for future scenarios (for which no direct observations are available), thereby facilitating the rigorous validation of the tsunami simulation models and the quantification of uncertainty related to the predictions.

This work is undertaken under the framework of PREMIUM (Post-BEMUSE Reflood Model Input Uncertainty Methods) benchmark.

Of course, despite all of the uncertainties, our benchmark index, the Russell 3000, has risen in 13 of the past 17 months, with July returning 6.9%.