A comprehensive framework for model validation and reliability assessment of container crane structures

Abstract

A comprehensive framework for model validation and reliability assessment of container crane structures is pursued in this paper. The framework is composed of three phases. In phase I, a parameterized finite element model (FEM) of a typical type of container crane structure at Yangshan deep-water port, Shanghai, is developed for simulating the structure performance at controllable input/parameter settings. Full-scale experiments are conducted at multiple locations of the container crane for the validation assessment of the parameterized FEM. In phase II, high fidelity reliability model (HFRM) of the crane structure is constructed by incorporating the parameterized FEM, failure criteria, and uncertainty from multiple sources. To alleviate the computational burden for running finite element analysis at each function evaluation, surrogate modeling techniques, i.e., the polynomial response surface (PRS) and artificial neural networks (ANN) are applied to build lower fidelity reliability models (LFRM) using simulations generated from the high fidelity reliability model. Quantitative validation metrics, i.e., the area metric and u-pooling metric are applied to assess the degree to which the surrogates represent the high fidelity model in presence of uncertainty. Finally in phase III, the reliability of the container crane structure is assessed by estimating the probability of failure based on the surrogates of the high fidelity reliability model through structure reliability methods. The proposed framework provides a scientific and organized procedure for model validation activities, surrogate model building, and efficient reliability assessment to container cranes and other complex structures in engineering if necessary.