Gerhards模型在针叶木材长期寿命预测中的适用性分析

Applicability Analysis of Gerhards Model in Long-Term Life Prediction of Coniferous Wood

【目的】分析木材长期寿命预测中常用Gerhards模型的适用性,探讨参数选取对不同加载工况下模型预测结果的影响,同时针对木材寿命预测中预测值大于真实值的问题,提出一种基于Gerhards模型的区间预测模型分析方法,为进一步提高木材长期寿命预测精度提供理论依据。【方法】首先对Gerhards模型进行理论推导,明确木材破坏时间与线性加载速度或恒定应力水平的关系;然后对比文献中针叶木材受荷试验数据真实值与8组Gerhards模型预测值,分析各模型对不同受荷形式下木材寿命预测结果的优劣;最后针对木材寿命预测中预测值大于真实值的问题,提出一种基于Gerhards模型的区间预测模型分析方法。【结果】基于Gerhards模型预测线性加载工况下木材寿命时,各模型预测值较为接近,且与试验值偏差较小;预测恒定加载工况下木材寿命时,各模型预测值间差别较大,且个别模型预测值与试验值差异极大。当木材试样为承受恒定应力水平介于60%~95%的北美花旗松时,建议采用Gerhards模型6进行寿命预测;当木材试样为承受恒定应力水平介于55%~105%的欧洲云杉时,建议采用Gerhards模型7进行寿命预测;当木材试样承受恒定应力水平小于50%时,建议采用Gerhards模型1进行寿命预测。预测模型所用数据加载工况与被预测对象受荷工况之间的差异对模型预测精度影响极大。相比传统预测模型,区间预测模型能够更完整地反映试验数据分布特征,且基于试验数据分位数拟合的预测模型较基于T分布假设拟合的预测模型涵盖更多试验数据点。【结论】分析Gerhards模型在木材长期寿命预测中的适用性十分必要,当预测模型所用数据加载工况与被预测对象受荷工况相似时,模型具有较好预测效果。本研究提出的分位数模型分析方法能够使绝大多数试验数据点落在区间模型内,可为提高木材长期寿命预测精度提供理论依据。

【Objective】In order to provide a theoretical basis for further improving the accuracy of wood long-term life prediction,the applicability of the commonly used Gerhards model in wood life prediction research was analyzed,the influences of the selection of model parameters on the life prediction results were discussed,and an interval model that can better reflect the distribution characteristics of test data based on the Gerhards model also proposed.【Method】Firstly,the Gerhards model was theoretically deduced to clarify the relationships between the failure time of the wood specimen and the ramp loading speed or constant stress level.Then,by comparing the real values of coniferous wood loading test data in the literature with the predicted values of 8 groups of Gerhards models,the pros and cons of each model for wood life predictions of different loading conditions were analyzed.Finally,aiming at the problem that the predicted value is higher than the true value in wood life prediction,an interval prediction model analysis method based on Gerhards model was proposed.【Result】When the Gerhards model is used to predict the life of wood specimens under linear loading conditions,the predicted values are relatively close,and the deviation from the experimental values is small;when predicting the life of wood specimens under constant loading conditions,the difference between each predicted values is large,and some of the predicted value are very different from the experimental values.When the constant stress level on the Northern Douglas fir sample is between 60%and 95%,it is recommended to use the Gerhards model 6 for life prediction.When the stress level on the Norway spruce sample is between 55%and 105%,it is recommended to use the Gerhards model 7 for life prediction.When the stress level on the wood sample is lower than 50%,it is recommended to use the Gerhards model 1 for life prediction.The difference between the loading condition of the data used in the fitting model and the loading condition of the predicted object has a great influence on the model prediction accuracy.Compared with the traditional prediction models,the interval model can reflect the distribution characteristics of the test data more completely,and the interval prediction model fitted by percentiles can cover more test data than that fitted by the data based on T distribution hypothesis.【Conclusion】It is necessary to discuss the applicability of the Gerhards model in the study of wood life prediction.The model could have a better prediction effect when the loading condition of the data used in the fitting model is similar to the loading condition of the predicted object.The quantile model proposed in this paper can make most of the test data points fall within the interval,which can provide a reference for improving the long-term life prediction accuracy of wood.