Non-linear finite element analyses have intrinsic model and user factors that influence the results of the analyses. However, non-linear finite element analysis can provide a tool to assess safety using realistic descriptions of material behaviour with actual material properties. A realistic estimation of the existing safety and capacity of slender column elements can be achieved by means of "true" material properties. Nevertheless, it seems that for some structural components, such as slender columns, non-linear finite element analyses can, due to its complexity and its various setting parameters, cause the risk of overestimating the real performance of analysed components or systems. Hence, an invited expert group has carried out an investigation into the experimental testing and the prediction of the bearing capacity of slender columns by performing independent non-linear finite element analyses in order to determine the practical applicability, and its inconsistencies, with respect to the stability failure of slender columns. This work aims the characterization of modelling uncertainties, concerning the prediction of slender columns stability when forecasted by non-linear finite element analysis.
Abstract. Application of current European standards (Eurocode) for the design of new bridges in assessment of existing ones proved non-efficient due to conservative assumptions regarding applied load and subsequent response of these bridges. That is why decisions regarding existing bridges should be based on probabilistic approach, combining advanced methods of analysis with real values and data gathered with on-site measurement and laboratory testing. These types of data are gathered trough Structural Health Monitoring tools as it allows us to observe and record various data over a period of time in order to estimate bridge current condition and to track eventual changes in its behavior. Bridge Weigh-in-Motion measurements, as a part of structural health monitoring of existing bridges, provide us with detailed information regarding volume and weight of traffic on the bridge, while also tracking its structural response. Site specific load models for examined bridges can be developed from collected traffic data, using various extrapolation methods. Simple and fast, and yet precise method of traffic data processing is presented in first part of this paper, while its application, along with bridge structural response data, in optimized bridge assessment is presented in the second part of the paper.
Bridge condition assessment in most European countries is based on visual inspection in combination with damage assessment of bridge components. For adequate bridge management, the assessment needs to be further developed to move from the bridge component level to the system functionality level and finally to the priority ranking level for repairs in the network. Although visual inspection provides only qualitative insights into bridge condition and cannot predict load-carrying capacity, it is still very often the only way to collect data on existing bridges and can provide very important information for evaluating structural safety, traffic safety, durability, and overall bridge condition. Therefore, this paper presents a unique procedure that establishes a relationship between a country-specific bridge condition assessment procedure based on visual inspection and the systematization of key bridge performance indicators developed within the European integrated management approach at three complementary and interrelated levels—component, system, and network levels. The assessment procedure for existing bridges initiates with damage assessment based on visual inspection of bridge components and runs through weighting at component, system, and network levels to the six most important key performance indicators (KPIs) for road bridges, which are organized as graphical and numerical inputs for ranking priority maintenance. These are bridge condition assessment, structural safety, traffic safety, durability indicator, availability, and the importance of the bridge in the network. The procedure is validated on a case study set of five real bridges, using the decision-making process as an example for the small sample size. The case study bridges differ in cross-section, type, and span (which vary from 9.5 to 72 m). The bridges were built between 1958 and 2001 and are located either on state or municipal roads in Croatia. The results, in terms of condition classification and priorities of future interventions within the representative group of bridges, justify the application of the described assessment procedure. Additional digitization efforts could easily implement the described assessment approach at the infrastructure network level.
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