We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Find out more about the Kindle Personal Document Service.
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.
Email your librarian or administrator to recommend adding this to your organisation's collection.