An ANSYS-based probabilistic finite element analysis has been created, expanding Haldar and Mahadevan’s canonical frame approach. The model is parameterized with eleven random variables, including applied loads, cross-section properties, member lengths, elastic modulus, and limit horizontal displacement. The sensitivity of these variables is analyzed, and the structure’s failure probability is evaluated using a limit state function for horizontal displacement. Monte Carlo (MC), Monte Carlo with Latin Hypercube sampling (MCLH), and Linear and Quadratic Response Surface (RSM-LIN and RSM-QUAX) methods analyze structural reliability; RSM methods achieved the lowest computational costs. The results are conclusive and future applications involving nonlinearity, dynamic loading, and other extreme scenarios are predicted.
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Rodríguez-Calderón et al. (2024) studied this question.
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