A probabilistic framework for stability assessment of existing spatial structures. (May 2019) - Liu, Jun; Luo, Yongfeng; Wang, Li; Yang, Xu; Li, Yunsong; Guo, Xiaonong
Abstract: In the safety assessment of existing spatial structures, sampling measurements are widely used to investigate structural geometries. The information from sampling measurements is limited and leads to the positional uncertainty of unmeasured nodes. Uncertain nodal positions have a significant influence on the stability assessment of the spatial structures with high geometric-imperfection sensitivity. To deal with the uncertainty of nodal positions, a probabilistic framework based on the randomness of nodal positional deviations was proposed. In the framework, uncertain nodal positions are modeled by random field, whose relevant parameters were inferred with the data from sampling measurements; based on the random field model, a full-probability analysis is adopted to determine the load-bearing capacity and further perform the stability assessment. According to the analysis of the correlation between nodal positions, correlated and uncorrelated random fields were respectively introduced to model the correlated and uncorrelated nodal deviations. And the detailed modeling methods were discussed, including the inference of distribution types, parameters and correlations. Finally, an existing single-layer reticulated shell was used to validate the reliability of the proposed probabilistic framework. Highlights: A contribution to dealing with uncertain nodal positions for the stability assessment of existing spatial structures. The uncertainty of nodal positions is described by a random field that models the positional deviations. A probabilistic framework for the stability assessment is built on the random field model. The proposed framework is illustrated and validated with a single-layer reticulated shell.