The duration of load effect in lumber as stochastic degradation

TL;DR

This paper introduces a gamma process model for damage accumulation in lumber under load, offering a novel approach compared to traditional accumulated damage models, and highlights challenges in using accelerated testing data for long-term reliability assessment.

Contribution

The paper applies a gamma process model to lumber degradation, separating internal and external damage factors, and demonstrates its advantages over traditional models in reliability analysis.

Findings

Gamma process effectively models damage accumulation in lumber.

Bayesian analysis reveals limitations of accelerated testing data.

Need for more comprehensive testing or expert-informed priors.

Abstract

This paper proposes a gamma process for modelling the damage that accumulates over time in the lumber used in structural engineering applications when stress is applied. The model separates the stochastic processes representing features internal to the piece of lumber on the one hand, from those representing external forces due to applied dead and live loads. The model applies those external forces through a time-varying population level function designed for time-varying loads. The application of this type of model, which is standard in reliability analysis, is novel in this context, which has been dominated by accumulated damage models (ADMs) over more than half a century. The proposed model is compared with one of the traditional ADMs. Our statistical results based on a Bayesian analysis of experimental data highlight the limitations of using accelerated testing data to assess long-term reliability, as seen in the wide posterior intervals. This suggests the need for more comprehensive testing in future applications, or to encode appropriate expert knowledge in the priors used for Bayesian analysis.