Partial factors are commonly based on expert judgements and on calibration to previous design formats. This inevitably results in unbalanced structural reliability for different types of construction materials, loads and limit states. Probabilistic calibration makes it possible to account for plentiful requirements on structural performance, environmental conditions, production and execution quality etc. In the light of ongoing revisions of Eurocodes and the development of National Annexes, the study overviews the methodology of probabilistic calibration, provides input data for models of basic variables and illustrates the application by a case study. It appears that the partial factors recommended in the current standards provide for a lower reliability level than that indicated in EN 1990. Different values should be considered for the partial factors for imposed, wind and snow loads, appreciating the distinct nature of uncertainties in their load effects.
Resistance of steel structures is primarily dependent on material properties, geometry and uncertainties related to an applied model. While materials and geometry can be relatively well described, the uncertainties in resistance models are not yet well understood. In many cases significant efforts are spent to improve resistance models and reduce uncertainty associated with outcomes of the model. However, these achievements are then inadequately reflected in the values of partial factors. That is why the present paper clarifies a model uncertainty and its quantification. Initially a general concept of the model uncertainty is proposed. Influences affecting results obtained by tests and models and influences of actual structural conditions are overviewed. Statistical characteristics of the uncertainties in resistance of steel members are then provided. Simple engineering formulas, mostly based on the EN 1993-1-1 models, are taken into account. To facilitate practical applications, the partial factors for the model uncertainties are derived using a semiprobabilistic approach.
Many existing steel railway bridges, often recognized and protected for their heritage value, are exposed to degradation and increasing traffic loads and their reliability needs to be assessed. The key question is whether a particular bridge can be preserved, or needs to be strengthened or replaced. The main aspect in decision-making is specification of the target reliability. Development and wider use of the adjusted partial factor method seem to be reasonable to find the balance between demands on the input information, computational complexity, and improvements in reliability assessment. Adjusted partial factors are based on the relevant statistical parameters for basic variables and a selected target reliability index. In this contribution, the effect of the target reliability on updated partial factors are demonstrated. The case study illustrates that the target reliability levels recommended in various documents for new and existing structures are inconsistent in terms of the values and criteria according to which these values are to be selected. Consequently, the values of the partial factors for assessment may be significantly dissimilar.
Introduction. Using numerical models to analyze the behavior of complex or new structural solutions becomes increasingly popular. New software can be used by a beginner to easily create numerical models of structures, and this is, on the one hand, an undeniable advantage, which, on the other hand, raises concerns about the accuracy and reliability of the results to be obtained. It is noteworthy that the regulatory engineering framework ignores this area. Moreover, research and design communities lack any uniform approaches to modeling, and, more importantly, to interpreting results and ensuring the structural reliability of solutions. Materials and methods. The article proposes a method for analyzing design values of the bearing capacity designated for target reliability levels, taking into account the changeability of basic variables and the modeling error. This method was developed using the Bayesian approach to quantile prediction provided that the number of validation results was limited. Results. The article presents the implementation of the proposed method of analyzing the design value of the bearing capacity using the results of FEM (finite element method) modeling of the bearing capacity of corrugated steel beams. The influence of the assumption about the standard deviation of the modeling error is analyzed. Conclusions. The work presents a method for determining the design values of the bearing capacity for the target levels of reliability, taking into account the changeability of basic variables and the modeling error. The factors, having a great impact on evaluating the design value of the bearing capacity and deserving further research, are substantiated. First, it is necessary to draw attention to the justification and regulation of target levels of structural reliability in regulations. Second, it is necessary to draw attention to studying statistical parameters of the modeling error and developing recommendations about the designation of apriori statistical data and maximum evaluations in respect of the standard deviation of the modeling error. Thirdly, attention must be drawn to development of criteria and formats for checking limit states in the course of design based on numerical models of the bearing capacity.
Introduction. Steel beams with a corrugated web are increasingly frequently applied in industrial and civil engineering due to their cost effectiveness. There are numerous studies proving the advantages of corrugated beams. However, the issue of calculating such elements is insufficiently covered in the standards and engineering literature, which is one of the main factors restraining their widespread use. Materials and methods. Along with the use of analytical dependencies, which, as a rule, are focused on a specific type of web corrugation and have limitations in terms of the area of experimental susceptibility, numerical methods are widely used. The finite element (FE) method is applied in the article. Results. The article presents the principles of constructing a FE model for evaluating the load-bearing capacity and service ability of corrugated beams subjected to local loading (patch loading), verified by using the experimental data. The authors have analysed the influence of parameters of the FE model and input variables on the accuracy and uncertainty of modeling results. Conclusions. The article shows that the use of FE models allows for a highly accurate evaluation of the load-bearing capacity and the behaviour of a beam with a corrugated web subjected to local loading. The description of the behaviour of steel has one of dominant influences on the accuracy of FE models, while the value of yield strength has a dominant influence; values of ultimate strength and the type of deformation diagram have an auxiliary influence. The variability in the web thickness has a directly proportional effect on the value of the bearing capacity. The size of the finite element should be determined according to the condition of convergence of results against the criteria of critical and ultimate forces. The most optimal size of the finite element is about 3–5 web thicknesses. To reduce the total number of finite elements, it is recommended to use local condensation in areas of stresses. The shape of equivalent geometric imperfections is recommended to be assigned based on the forms of elastic buckling of the web.
Steel structures are second most numerous in the stock of existing buildings. In contrast to dominating concrete buildings, they are typically lightweight and are more sensitive to alterations in use or loads. While the sustainability principles require to maintain and keep using these structures, structural assessments often indicate insufficient reliability and need for replacements. The submitted contribution shows that the most important reliability considerations affecting the sustainability of existing steel structures consist of specifying (1) appropriate target reliability level, (2) verification methods, and (3) intervention procedures. The study focuses on the first two aspects. (1) Optimum target reliability can be specified by probabilistic optimisation considering sustainability aspects including structural costs, and expected consequences of replacement and of possible failure. It is shown that lower reliability levels might be considered for the assessment of existing structures than for the design of new structures, with benefits for sustainability in construction.Regarding (2), the most efficient verification methods are based on advanced probabilistic approaches. It is demonstrated that sustainability may be significantly affected by the selection of assessment methods. Advanced reliability approaches commonly reduce assessment requirements by 10–15 %. Sustainability indicators are mostly related to the key aspects (1) and (2). Using the advanced methods may bring a significantly positive contribution to sustainability, particularly when an upgrade of the existing structure is associated with high economic cost and significant environmental impact.
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