2021/10/22 by Yunfeng Yang, Martin Lysy, Yang, Yunfeng +3
Decision Sciences · Environmental Science · #Applications (stat.AP) #Environmental Impact and Sustainability #FOS: Computer and information sciences #Forest ecology and management #Probabilistic and Robust Engineering Design
paper · pdf · doi:10.48550/arxiv.2110.11896
openalex publication_date 2021/10/22 · openalex created_date 2021/11/08 · openalex updated_date 2026/07/28
This paper evaluates the reliability of lumber, accounting for the duration-of-load (DOL) effect under different load profiles based on a multimodel Bayesian approach. Three individual DOL models previously used for reliability assessment are considered: the US model, the Canadian model, and the Gamma process model. Procedures for stochastic generation of residential, snow, and wind loads are also described. We propose Bayesian model-averaging (BMA) as a method for combining the reliability estimates of individual models under a given load profile that coherently accounts for statistical uncertainty in the choice of model and parameter values. The method is applied to the analysis of a Hemlock experimental dataset, where the BMA results are illustrated via estimated reliability indices together with 95% interval bands.