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Framework for definition of design formulations from empirical and semi‐empirical resistance models
Author(s) -
Castaldo Paolo,
Gino Diego,
Carbone Vincenzo Ilario,
Mancini Giuseppe
Publication year - 2018
Publication title -
structural concrete
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 34
eISSN - 1751-7648
pISSN - 1464-4177
DOI - 10.1002/suco.201800083
Subject(s) - empirical research , probabilistic logic , reliability (semiconductor) , empirical modelling , calibration , computer science , reliability engineering , monte carlo method , empirical likelihood , econometrics , engineering , mathematics , statistics , simulation , artificial intelligence , power (physics) , physics , quantum mechanics , inference
The study proposes a framework based on the Monte Carlo method for the probabilistic calibration of empirical and semi‐empirical resisting models. The resisting models adopted in engineering practice may be based both on physical laws, such as equilibrium of forces, and on semi‐empirical or empirical formulations. Precisely, empirical or semi‐empirical resisting models are calibrated in order to fit experimental data and the direct application of partial safety factors to material properties does not allow a proper estimation of the structural reliability. For this reason, a probabilistic definition of design expressions from empirical or semi‐empirical resisting models should be preferred to define a final formulation in agreement with a specific level of reliability. After a detailed description of the framework, its application to the probabilistic calibration of the semi‐empirical model proposed by fib Model Code 2010 for the estimation of tensile strength of laps and anchorages in reinforced concrete structures is proposed.