Safety analysis and reliability assessment of engineering structures – The success story of SARA

Abstract

The concept for the safety assessment of concrete structures integrating nonlinear finite element analysis with stochastic and reliability technology into an advanced engineering tool is presented. The basic aim of the stochastic nonlinear analysis is to calculate the safety index (and failure probability) of an existing engineering structure, which characterizes its reliability. The nonlinear solution enables a realistic estimation of the structural response statistics to be obtained (failure load, deflections, cracks, stresses, etc.). The development of possibility of randomization for such computationally intensive problems was part of the project Safety Analysis and Reliability Assessment of Engineering Structures (SARA). Latin hypercube sampling has been used in SARA in order to keep the number of required simulations at an acceptable level. Statistical correlation, which is important for a realistic solution, was also imposed in SARA by using a stochastic optimization technique called simulated annealing. The sensitivity of results to random input parameters can be evaluated using nonparametric rank‐order correlation coefficients. The presented project SARA focusing on the safety assessment of engineering structures supersedes the usual methods based on simplified formulas. SARA supports a higher level of decision‐making process in bridge administration and maintenance of transport macrostructure. The object of this article is to present the diverse developments of the project SARA and to honor Professor Konrad Bergmeister, who was the frontrunner and chair of SARA and was mainly responsible for the SARA project initiation and its fruitful and amazing developments.

Probabilistic and Semi-Probabilistic Analysis of Slender Columns Frequently Used in Structural Engineering

“…In the course of the step-by-step axial loading process, the basic variables of the model input data were determined for each loading step with a step size increment of ∆N = 10 kN. The development of the sensitivity factors calculated using the Kendal Tau algorithm [36] were analyzed and are plotted as a function of the axial (normal) force N of the column in Figure 9a and the transverse deformation of the column at half the system length in Figure 9b. The Kendall rank correlation coefficient, commonly referred to as the Kendall's r coefficient, was used to measure the ordinal association between two measured quantities, e.g., model input variable i and model response k. The sensitivity analyses according to FORM were not applied here as the Kendal Tau algorithm allows a much simpler handling of the sensitivity considerations for finite element applications.…”

“…The probabilistic modeling based on the BOKU ATENA 3D NLFEM model and the stochastic information of the selected random variables according to Tables 4 and 5 were carried out with the Structural Analysis and Reliability Assessment (SARA) program package developed in the project "Safety and Reliability Assessment of Structure" [36,37] ] in which the Latin Hyper Cube Sampling (LHS) method with a sample number of n = 305 was used for the development of the input sampling sizes. The significantly increased number of samples compared to the previously described analytical probabilistic analysis results from the fracture processes that occur during the loading process and the clearly pronounced physical and material non-linearities that are also taken into account in the NLFEM analysis.…”

Nonlinear probabilistic structural assessment: Findings from Austrian and Czech bridges

“…Such trend can be observed since long time ago, e.g. [1][2][3][4][5][6][7][8]. Assessment of existing structures, like bridges, is quite different from the design of new structures due to significant differences in the uncertainties related to modelling of existing structures.…”

“…Different techniques for incorporating the deterioration effects in reinforced concrete structures were applied, such as random fields [11][12][13], Bayesian networks and updating [14][15][16]. Applications of probabilistic methods for existing structures/bridges can be found e.g., in [3,[6][7][17][18].…”

FReET: Software for Uncertainties Propagation

“…Methodology and software tool are prepared for a routine application. Software have been used in many practical applications mainly for concrete structures reliability analysis [4] and they are continuously improved by implementation of new state of art methods.…”