Search

The paper portrays a comprehensive computational procedure for determining the global structural resistances of two existing bridges made of I‐73 and KA‐61 precast post‐tensioned concrete girders using advanced statistical assessment methods in combination with nonlinear fracture mechanics‐based finite element method analysis. Although this combination is a powerful tool for realistic modeling of structures, its practical application is still very time consuming. Therefore, a statistical sampling approach for the determination of the structural design resistance is compared to selected efficient semi‐probabilistic methods based on the estimation of coefficient of variation—estimation of coefficient of variation (ECoV) method according to fib Model Code 2010 and improved approach called Eigen ECoV method. Load‐bearing capacity is determined for the ultimate as well as several serviceability limit states. The sensitivity of the input parameters burdened with uncertainties on the response of the structure is quantified using a sensitivity analysis supported by a surrogate model based on polynomial chaos expansion. The paper shows that the applicability of nonlinear modeling with respect to uncertainties is possible when using these ECoV methods and a surrogate model and can be applied in a routine manner. The shortcomings and advantages of all the used safety design/assessment methods are discussed. [ABSTRACT FROM AUTHOR]

Advanced experimental evaluation of the mechanical fracture properties of quasi‐brittle materials is an important part of the design, assessment, and computational modeling of structures made of these materials. The aim is to determine parameters independent of the test configuration or the size of the test specimens. This paper presents the results of an extensive experimental program which is part of the development of a comprehensive multilevel approach for experimental–computational determination of the mechanical fracture parameters of concrete. Three‐point bending and wedge‐splitting tests were performed simultaneously using three different geometrically similar specimen sizes and two well‐separated depths of initial notches. Before the start of the main testing program, the pilot tests that were performed were aimed at the design of the most appropriate concrete mixture. Special attention was paid to the selection of a maximum aggregate grain size. In order to study the process of concrete aging and the development of its mechanical properties, the accompanying destructive and non‐destructive tests were carried out at different ages of hardening. Fracture parameters were evaluated using the effective crack‐length formulation and work‐of‐fracture method. Finally, the size‐independent specific fracture energy was back‐calculated from the measured specific fracture energy. [ABSTRACT FROM AUTHOR]

Three sensitivity analysis methods are employed to achieve the optimum selection of the dominant random variables of selected concrete structures. The first of these methods uses the nonparametric rank‐order statistical correlation between the basic random input variables and the structural response output variable. The second is neural network ensemble‐based sensitivity analysis and the last of them is sensitivity analysis in terms of coefficient of variation. All of the methods were utilized and compared for two selected concrete structures: a prestressed concrete bridge made of MPD girders, and T‐shaped prestressed concrete roof girder. The obtained information was used to set up a stochastic model and response surfaces in an optimum manner and was employed in the subsequent determination of selected uncertain design parameters followed by load‐bearing capacity and reliability assessment. [ABSTRACT FROM AUTHOR]