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al. [ 4 ] presents the concept and design of the calorimeter, the main measurements and the data evaluation. In all developments—calorimeter, measuring system, data acquisition and evaluation—the consideration of uncertainty sources has been an

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[1] Atanasova , S ., Pilipovi’c , S . and Saneva , K ., Directional time-frequency analysis and directional regularity , Bull. Malays. Math. Sci. Soc ., 42 ( 2019 ), 2075 – 2090 . [2] Beckner , W ., Pitt’s inequality and the uncertainty

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. Ortiz, J., C. Deutsch 2002: Calculation of uncertainty in the variogram. - Mathematical Geology, 34, pp. 169 - 183 . Calculation of uncertainty in the variogram. - Mathematical Geology

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Introduction Stochastic spatial simulation is a widely used method to quantify and display spatial uncertainty. Multiple, alternative, and equiprobable realizations are used to represent the spatial uncertainty of the given

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Journal of Radioanalytical and Nuclear Chemistry
Authors: P. Robouch, G. Arana, M. Eguskiza, S. Pommé, and N. Etxebarria

Abstract  

The concepts of the Guide to the expression of Uncertainties in Measurements for chemical measurements (GUM) and the recommendations of the Eurachem document "Quantifying Uncertainty in Analytical Methods" are applied to set up the uncertainty budget for k 0-NAA. The "universally applicable spreadsheet technique", described by Kragten, is applied to the k 0-NAA basic equations for the computation of uncertainties. The variance components — individual standard uncertainties — highlight the contribution and the importance of the different parameters to be taken into account.

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To properly interpret the quality of a gamma-spectroscopy measurement, an uncertainty estimate must be made. The uncertainty in the efficiency calibration is the dominant component to the total propagated measurement uncertainty for many types of measurements. Any deviations between the as-calibrated geometry and the as-measured geometry contribute to the total uncertainty. A mathematical technique has been developed to evaluate the variations between calibration and measurement conditions. A sensitivity analysis mode identifies those variables with the largest contribution to the uncertainty. The uncertainty mode uses probabilistic techniques for the combined variables to compute average efficiency and uncertainty, and then to propagate those values with the gamma-spectroscopic analysis into the final result for that sample.

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17 28 Chatfield, C. 1995. Model uncertainty, data mining and statistical-inference J. R. Statist. Soc. Series A , 158:419-466. Model uncertainty

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The apparent tendency to underestimate the uncertainty of experimentally determined half-life values of radionuclides is discussed. It is argued that the uncertainty derived from a least-squares analysis of a decay curve is prone to error. As it is quite common for a series of activity measurement results to be autocorrelated, the prerequisite of randomness of data for common statistical tests to apply is not fulfilled. In this work, an alternative data analysis method is applied that leads to a more realistic uncertainty budget. The uncertainty components are being subdivided in three categories according to the relative frequency at which they occur, an appropriate uncertainty propagation formula applied and then the total uncertainty obtained from an independent sum. An attempt is made to apply the protocol to problematic cases in literature, yet it is clear that the reporting is usually incomplete for a full uncertainty analysis. Suggestions are made for a concise but more complete reporting style, for the sake of traceability.

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by a comparably high standard deviation of up to 14%. The cause of this relatively high uncertainty has been investigated in detail and will be discussed and presented here. Hydrothermal carbonization of biomass is a reaction that takes place

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Low velocity surface layers can significantly increase ground accelerations during earthquakes. When saturated sandy sediments are present, because of pore pressure increase, decrease of soil strength or even liquefaction can occur. Some volume change follows the dissipation of excess pore pressure after the earthquake resulting surface settlements. To determine the liquefaction probability and post-liquefaction settlement is very important for critical facilities e.g. for the site of Paks Nuclear Power Plant, Hungary. Pore pressure increase and so the liquefaction and surface settlements depend on the characteristics of seismic loading and soil parameters. To quantify the extent of these phenomena is rather difficult. Uncertainties arise both from the probabilistic nature of the earthquake loading and from the simplifications of soil models as well. In the paper, the most important semi-empirical and dynamical effective stress methods for liquefaction and post-liquefaction settlement assessment are summarized. Most significant contributors to the uncertainties are highlighted, and particular examples through the investigation of Paks NPP site are given. Finally, a probabilistic procedure is proposed where the uncertainties will be taken into account by applying a logic tree methodology. At the same time, the uncertainties are reduced by the use of site-specific UHRS and stress reduction factors.

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