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Measurement quality and uncertainty evaluation in civil engineering research

  • A. Silva Ribeiro (a1), J. Alves e Sousa (a2), C. Oliveira Costa (a1), J.F. Vieira de Sousa (a2), J. Almeida Garrett (a1) and L. Lages Martins (a1)...

Abstract

Civil engineering is a branch of science that covers a broad range of areas where experimental procedures often plays an important role. The research in this field is usually supported by experimental structures able to test physical and mathematical models and to provide measurement results with acceptable accuracy. To assure measurement quality, a metrology probabilistic approach can provide valuable mathematical and computational tools especially suited to the study, evaluation and improvement of measurement processes in its different components (modeling, instrumentation performance, data processing, data validation and traceability), emphasizing measurement uncertainty evaluation as a tool to the analysis of results and to promote the quality and capacity associated with decision-making. This paper presents some of the research held by the metrology division of the Portuguese civil engineering research institutes, focused on the contribution of measurement uncertainty studies to a variety of frameworks, such as testing for metrological characterization and physical and mathematical modeling. Experimental data will be used to illustrate practical cases.

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Corresponding author

Correspondence: asribeiro@lnec.pt

References

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[1] ISO/TS 17892-9:2004 Geotechnical investigation and testing – Laboratory testing of soil – Part 9: Consolidated triaxial compression tests on water saturated soil
[2] ISO/TS 28037:2010 The determination and use of straight-line calibration functions, Technical Specification, International Organization for Standardization, Geneva
[3] BS EN 12390-1: 2002 Testing hardened concrete - Part 1: Shape, dimensions and other requirements for specimens and moulds
[4] EN 196-1: 2005. Methods of testing cement – Part 1: Determination of strength
[5] JCGM. Evaluation of measurement data – Guide to the expression of uncertainty in measurement, JCGM 100:2008
[6] JCGM. Evaluation of measurement data – Supplement 1 to the “Guide to the expression of uncertainty in measurement” – Propagation of distributions using a Monte Carlo method, JCGM 101: 2008
[7] JCGM. Evaluation of measurement data – Supplement 2 to the “Guide to the expression of uncertainty in measurement” – Extension to any number of output quantities, JCGM 102: 2011

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