In the Performance-Based Engineering (PBE) framework, uncertainties in system parameters, or modelling uncertainties, have been shown to have significant effects on capacity fragilities and annual collapse rates of buildings. Yet, since modelling uncertainties are non-ergodic variables, their consideration in failure rate calculations offends the Poisson assumption of independent crossings. This problem has been addressed in the literature, and errors found negligible for small annual collapse failure rates. However, the errors could be significant for serviceability limit states, and when failure rates are integrated in time, to provide lifetime failure probabilities. Herein, we present a novel formulation to fully avoid the error in integration of non-ergodic variables. The proposed product-of-lognormals formulation is fully compatible with popular fragility modelling approaches in PBE context. Moreover, we address collapse limit states of realistic reinforced concrete buildings, and find errors of the order of 5 to 8% for 50-year lifetimes, up to 14% for 100 years. Computation of accurate lifetime failure probabilities in a PBE context is clearly important, as it allows comparison with lifetime target reliability values for other structural analysis formulations.
翻译:在基于绩效的工程(PBE)框架内,系统参数或建模不确定性的不确定性被证明对能力脆弱性和建筑物年崩溃率有重大影响。然而,由于建模不确定性是非遗传变量,因此在计算故障率时的考虑与Poisson独立过境点的假设不相符。这个问题在文献中已经解决,小年崩溃率中发现的差错微不足道。然而,这些差错对于可使用性限值国家来说可能很重要,当故障率在时间上得到整合时,可以提供终生故障概率。这里我们提出了一个新颖的配方,以充分避免非遗传变量的整合出错。拟议的异常产品配方与PBE背景下流行的脆弱性建模方法完全兼容。此外,我们还解决了现实强化混凝土建筑的崩溃限度,并发现50年期5-8%的悬浮值有误,100年达14 %。计算PBE背景下准确的终身故障概率显然很重要,因为它可以与其他结构分析的配置的终身目标可靠性值进行比较。