The structural safety assessment of large liquid tanks (LLT) has attracted an extensive attention. As a typical gray box model, the belief rule base (BRB) model can handle qualitative information and quantitative data simultaneously, which is a suitable modeling tool for structural safety assessment. However, it is difficult to establish and train the BRB model when there is a lack of expert experience and fault samples of LLT. Therefore, a novel safety assessment model for LLT based on BRB and finite element method (FEM-BRB) is proposed in this paper. The FEM is introduced to construct the BRB model by combining expert knowledge and industry standards for the first time, which can effectively compensate for the lack of expert experience. The fault samples are generated in the mechanism simulation model under different working conditions. Based on the fault samples generated by the FEM and historical samples, the projection covariance matrix adaption evolution strategy (P-CMA-ES) optimization algorithm is then used to train the model, which further improves the structural safety assessment accuracy when lacking fault samples. A case study of three actual oil tanks in a coastal port is conducted to illustrate the effectiveness and advantage of the developed structural safety assessment method.

大型液体储罐（LLT）的结构安全评估引起了广泛关注。作为典型的灰盒模型，信念规则库（BRB）模型可以同时处理定性信息和定量数据，是一种适合结构安全评估的建模工具。但是，在缺乏专家经验和 LLT 故障样本的情况下，很难建立和训练 BRB 模型。因此，本文提出了一种基于 BRB 和有限元法的新型 LLT 安全评估模型（FEM-BRB）。首次引入FEM，结合专家知识和行业标准构建BRB模型，有效弥补了专家经验的不足。故障样本是在不同工况下的机理仿真模型中生成的。然后基于有限元法生成的故障样本和历史样本，采用投影协方差矩阵自适应演化策略（P-CMA-ES）优化算法训练模型，进一步提高了在缺乏故障样本时结构安全评估的准确性。对沿海港口的三个实际油罐进行案例研究，以说明所开发的结构安全评估方法的有效性和优势。