Framework for definition of design formulations from empirical and semi‐empirical resistance models

Abstract

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.

Assessment of the Resistance Model Uncertainties in Plane Stress Nlfea of Cyclically Loaded Reinforced Concrete Systems

“…The numerical results in terms of global structural resistance of the simulations are listed in Tables 4-5. Figures 6-8 (a)-(f) show that models (3,6,9,12,15,18) related to elastic-plastic constitutive law for the concrete tensile behavior, always lead to an overestimation of the resistance and stiffness, while models elastic-brittle and with a linear tension softening in tension have more or less the same behavior, with a stiffness similar to the real one in the cyclic phase, but, in general, an underestimation of the resistance. It can be also noted that as the shear retention factor increases, the dissipated energy also increases.…”

Seismic Reliability-Based Design of Softening Structures Equipped With Double Sliding Devices

“…These response parameters are assumed as the engineering demand parameters (EDPs) and their peak values have been fitted with lognormal distribution [15], [16]- [21], [41], [60], [67], by estimating the sample , through the maximum likelihood estimation technique, to determine the 50 th , 84 th and 16 th percentile of each lognormal PDF [15]. Note that other uncertainties [73]- [78] as well as the influence of the infills [79]- [82] are not considered in this study. shown in Fig.s 2-3 is the maximum displacement recorded during the non-linear dynamic analysis, and generally is not concomitant with the maximum displacement recorded at each single surface.…”

Partial factor methods for existing structures according to fib Bulletin 80: Assessment of an existing prestressed concrete bridge

“…In particular, existing bridges and viaducts are extensively exposed to environmental actions, time dependent phenomena (e.g., creep, shrinkage, prestressing steel relaxation), degradation (e.g., corrosion due to carbonation and/or chloride penetration), and increasing magnitude of traffic loads. For these reasons, several investigations have been devoted to define methodologies to assess efficiently existing structures and infrastructures also including refined analysis methods . Moreover, national Authorities are strongly interested in the assessment of existing structures, with particular care for existing bridges and viaducts, due to the high costs for maintenance, interventions and upgrading.…”

“…For these reasons, several investigations have been devoted to define methodologies to assess efficiently existing structures and infrastructures also including refined analysis methods. [1][2][3][4][5][6] Moreover, national Authorities are strongly interested in the assessment of existing structures, with particular care for existing bridges and viaducts, due to the high costs for maintenance, interventions and upgrading.…”