A new UBC-constrained (ultimate-bearing-capacity-constrained) non-probabilistic reliability-based optimization method for structures with uncertain-but-bounded parameters is proposed. Different from the traditional stress-constrained optimization, the ultimate bearing capacity (UBC) is taken as the constraints in the non-probabilistic reliability-based optimization, which reflect the system safety of structures. Based on the interval mathematics, the UBC constraint is transformed into the format of non-probabilistic reliability, in which a novel measuring index, namely, the UBC, is defined by an interval interference model. Thus, structural optimization is converted by the lightweight design problem with UBC reliability constraints. Moreover, the gradient-based Taylor expansion method is employed to obtain the lower and upper bounds of the UBC, which transforms a double-layer optimization into an efficient single-layer one. Finally, 2D and 3D structural examples are given to illustrate the effectiveness of the proposed method.

针对具有不确定但有界参数的结构，提出了一种新的基于UBC约束（极限承载力约束）的非概率可靠性优化方法。与传统的应力约束优化不同，极限承载力（UBC）被作为基于非概率可靠性的优化的约束，反映了结构的系统安全性。基于区间数学，将UBC约束转换为非概率可靠性格式，其中通过区间干扰模型定义了一种新的测量指标，即UBC。因此，结构优化由具有UBC可靠性约束的轻型设计问题转换。而且，采用基于梯度的泰勒展开法来获取UBC的上下限，将双层优化转化为高效的单层优化。最后，给出了2D和3D结构示例，以说明该方法的有效性。