Martina Šomodíková

Inverse Response Surface Method in Reliability-Based Design

Abstract The paper introduces an inverse response surface method utilized when performing reliability-based design optimization of time-consuming problems. Proposed procedure is based on a coupling of the adaptive response surface method and the artificial neural network-based inverse reliability method. The validity and accuracy of the method is tested using examples with explicit nonlinear limit state functions. Obtained results as well as important aspects of the method are discussed.

Reliability Analysis of Post-Tensioned Bridge Using Artificial Neural Network-Based Surrogate Model

The reliability analysis of complex structural systems requires utilization of approximation methods for calculation of reliability measures with the view of reduction of computational efforts to an acceptable level. The aim is to replace the original limit state function by an approximation, the so-called response surface, whose function values can be computed more easily. In the paper, an artificial neural network based response surface method in the combination with the small-sample simulation technique is introduced. An artificial neural network is used as a surrogate model for approximation of original limit state function. Efficiency is emphasized by utilization of the stratified simulation for the selection of neural network training set elements. The proposed method is employed for reliability assessment of post-tensioned composite bridge. Response surface obtained is independent of the type of distribution or correlations among the basic variables.

Input Value Correlation in Chloride Ion Ingress Modelling and Concrete Structures Reliability

The assessment of service life of a structure can be performed via mathematical modelling – either analytical or numerical and it can be viewed as a necessary pre-requisite for life-cycle engineering decisions. Many works concerning the modelling and testing of degradation effects for engineering systems are reported in the literature. The present paper discusses the degradation modelling of reinforced concrete structures and concentrates on the damage they sustain due to chloride ingress, namely a special aspect: the influence of statistical correlation among input variables on the reliability.

Assessment of Load Bearing Capacity of Concrete Bridges after Exceeding the Design Life

Advanced methods of reliability analysis based on simulation techniques of Monte Carlo type in combination with nonlinear finite element method analysis represent effective tools for reliability assessment of the existing bridges. Knowledge of current level of load bearing capacity of the bridge and its development in the coming years while meeting the required level of reliability may help to schedule the bridge maintenance systematically and efficiently and/or it can facilitate decision-making on the manner and extent of its reconstruction. The paper briefly introduces methodology of probabilistic determination of the load bearing capacity of bridges with respect to the ongoing deterioration processes in time. The methodology is applied to determine the current level of load bearing capacity of a reinforced concrete parapet beam bridge built and for its estimation in the coming years until the end of the theoretical service life of the structure.

Post-Tensioned Composite Bridge: Reliability-Based Optimization of Selected Design Parameters

In the paper small-sample double-loop optimization method is employed to find selected design parameters of a single-span post-tensioned composite bridge to ensure its reliability and load-bearing capacity. The selected approach consists in nesting the computation of the failure probability with respect to the current design within the optimization loop. The analyzed bridge is made of precast post-tensioned concrete girders, each composed of six segments that are connected by the transverse joints. Bridge spatial deterioration brings uncertainty into actual values of concrete strength in transversal joints and of actual loss of pre-stressing. Due to their significant effect on the bridge load-bearing capacity, both were considered as uncertain design parameters with the aim to find their critical values corresponding to desired reliability level and load-bearing capacity.