PSI - Issue 59

Yaroslav Shved et al. / Procedia Structural Integrity 59 (2024) 664–671 Yaroslav Shved et al./ Structural Integrity Procedia 00 (2019) 000 – 000

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1. Introduction The general principles for ensuring the reliability and structural safety of buildings, structures, building constructions, and foundations, as outlined by Degertekin (2012) and Ahrari (2013), present specific requirements for core systems, particularly construction trusses. These stable building structures play a crucial role in maintaining the integrity of buildings and constructions but pose challenges in determining limit state parameters both during the design phase and in operation, as highlighted by Degertekin (2012), Khajeh (2023), and Rajput (2013). Currently, standardized methods ensuring high reliability of calculated values for limit state parameters are lacking. Typically, this issue is addressed by incorporating exaggerated safety margin coefficients, leading to increased material consumption and, consequently, higher construction costs. Existing application software packages employed for determining the bearing capacity and reliability of welded trusses through computer modeling experiments rely algorithmically on the finite element method, offering deterministic simulations. However, when studying trusses, most input parameters are stochastic (Shynhera, 2012; Brevus et al., 2013; Didych et al., 2018), resulting in a dispersion of values for input parameters such as mechanical properties of the base material, weld properties, and loading modes. Consequently, obtaining specific values for output parameters in the modeling process becomes challenging. The mechanical properties of materials, a crucial component of the input information base, exhibit significant dispersion when evaluated according to standards such as DSTU 4484:2005 or quality certificates for rolled metal products (Shynhera, 2011). Additionally, the utilization of physical modeling to explore the limit state parameters of a welded truss is noteworthy, contributing to the identification of fracture nature and process visualization (Kovalchuk, 2011). To comprehensively address the issue of modeling limit state parameters for a welded truss, a combination of full scale, small-scale, and computer simulation experiments is necessary. The relevance of this study stems from the need for existing methods to ensure a sufficient level of agreement between calculated and actual indicators of the stress-strain state (SSS) in truss structural elements. The study aims to determine the parameters of the limit state of a welded truss, considering the influence of structural, technological, and operational factors (Kryzhanivskyy et al, 2019). To achieve this goal, the following tasks must be addressed:  determine the mechanical properties of the main material and the weld of samples made of A570-36 steel;  analyze the SSS of a welded truss based on small-scale and computer simulation;  verify the results of the computer simulation experiment;  develop recommendations for strengthening the studied truss. The solution to these problems ensures maximum utilization of the structure’s bearing capacity without accidental destruction during operation. 2. Research Methods The following methodical approaches are known for assessing the strength and reliability of welded trusses:  classical analytical calculations;  computer simulation experiment. The research methods used in this paper are a complex combination of full-scale, small-scale, and computer simulation experiments. The full-scale experiment in the study of welded trusses is practically not used due to the significant material and energy consumption of the construction and the complexity of the test equipment. A small-scale experiment is rarely used and only for atypical and critical truss structures. Classical calculation methods involve many simplifications and generalizations and do not consider the complex effect of various factors on the studied structure. Computer simulation experiment has been used relatively recently and has several advantages over the abovementioned  full-scale experiment;  small-scale experiment;