In practice, a truss consists of a large number of members which makes it a complex system. This leads to difficulties to estimate the system reliability due to computational costs. An adaptive method is thereby proposed to deal with this issue. It constructs a global metamodel to quickly estimate the rough reliability index of a truss. According to the estimated reliability index, the differential evolution algorithm is performed to generate more samples located in an expanded domain so that more representative failure modes can be identified. Combined with AK-SYSi, local metamodels of representative failure mods are built, and updated through active learning. When the convergence criterion is satisfied, the results of system reliability analysis can be obtained. Eventually, two examples of truss structures are studied to illustrate the superiority of the proposed method in balancing accuracy and efficiency. The results indicate that the proposed method makes a good balance between accuracy and efficiency when it is applied to analyze the system reliability of the truss.
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Considerations presented in this paper focus on the assessment of steel truss fire safety with the use of the system reliability analysis. In calculations of capacity and the effect of actions, random variation in the Young's modulus, yield strength and the cross-sectional areas of rods are taken into account. The aim of the analysis is to monitor the reliability index in the consecutive minutes of the fire. That allows estimation of the failure probability, and also taking decisions on whether the required safety level is ensured. The new method described in the paper makes it possible to take into account changes in the structure static scheme under fire conditions.
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