A Method for Estimating the Resultant Expanded Uncertainty Value Based on Interval Arithmetic

The article describes a method for determining the resultant expanded uncertainty value in the case of analyzing an uncertainty budget with many components. It employs interval arithmetic, known for its low calculation complexity compared to other methods in the literature. The article includes a detailed explanation of the proposed method and showcases its applications. Results are compared with those from the Monte Carlo method and assumptions based on the central limit theorem. The relative error in estimating the resulting expanded uncertainty value typically stays within ±5% of the Monte Carlo method’s result.

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Publication Details

Journal
Applied Sciences
Published
2024-08-20
DOI
https://doi.org/10.3390/app14167334
Citations
3
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
1.38
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article

A Method for Estimating the Resultant Expanded Uncertainty Value Based on Interval Arithmetic

Łukasz Dróżdż, Marian Kampik, Jerzy Roj
3 citations
Applied Sciences
Probabilistic and Robust Engineering Design
1.38
article

A Method for Estimating the Resultant Expanded Uncertainty Value Based on Interval Arithmetic

Łukasz Dróżdż, Marian Kampik, Jerzy Roj
article en
3 citations

Abstract

The article describes a method for determining the resultant expanded uncertainty value in the case of analyzing an uncertainty budget with many components. It employs interval arithmetic, known for its low calculation complexity compared to other methods in the literature. The article includes a detailed explanation of the proposed method and showcases its applications. Results are compared with those from the Monte Carlo method and assumptions based on the central limit theorem. The relative error in estimating the resulting expanded uncertainty value typically stays within ±5% of the Monte Carlo method’s result.

Applied SciencesVol. 14(16)
Silesian University of Technology (PL)
Openalex Percentile: Top 17%
Probabilistic and Robust Engineering Design
1.38
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