详细信息
基于蒙特卡洛模拟预测正交胶合木(CLT)顺纹抗压强度 被引量:3
Prediction of the Compressive Strength of Cross-laminated Timber Based on Monte Carlo Simulation
文献类型:期刊文献
中文题名:基于蒙特卡洛模拟预测正交胶合木(CLT)顺纹抗压强度
英文题名:Prediction of the Compressive Strength of Cross-laminated Timber Based on Monte Carlo Simulation
作者:龚迎春[1] 叶琦[2] 武国芳[3] 任海青[1] 管成[2]
机构:[1]中国林科院林业新技术研究所,北京100091;[2]北京林业大学,北京100083;[3]中国林科院木材工业研究所,北京100091
年份:2020
卷号:35
期号:6
起止页码:234-237
中文期刊名:西北林学院学报
外文期刊名:Journal of Northwest Forestry University
收录:CSTPCD;;北大核心:【北大核心2017】;CSCD:【CSCD_E2019_2020】;
基金:中央级公益性科研院所基本科研业务费专项资金“正交胶合木墙体稳定性能研”(CAFYBB2018SY032);国家自然科学基金“正交胶合木构件受压失稳机理及计算方法研究”(51808546)。
语种:中文
中文关键词:正交胶合木;顺纹抗压强度;概率分布;蒙特卡洛模拟
外文关键词:cross-laminated timber;compressive strength parallel to grain;probability distribution;Monte Carlo simulation
分类号:S781.21
摘要:基于《木结构试验方法标准》测试锯材和正交胶合木(CLT)顺纹抗压强度,采用正态分布、对数正态分布、威布尔分布函数进行数据拟合,利用K-S检验判断拟合优度,基于复合层板理论利用蒙特卡洛模拟预测CLT顺纹抗压强度。结果表明,CLT和锯材的顺纹抗压强度平均测试值分别为39.96 MPa和30.41 MPa;采用威布尔分布的拟合优度最高;CLT抗压强度的预测值与实测值相对误差在8%以下,采用蒙特卡洛模拟数据预测CLT顺纹抗压强度平均值和5%分位值的相对误差分别为5.8%和-0.8%,具有更高预测准确性。
Based on the national standard of China,GB/T 50329-2012“Standard for Test Methods of Timber Structures”,the ultimate compressive strength parallel to grain of lumber and cross-laminated timber(CLT)was tested.The normal distribution,lognormal distribution and Weibull distribution functions were adopted to fit the test results.K-S test was used to determine the most consistent probability distribution.The compressive strength of CLT was predicted by using Monte Carlo simulation method(MCS)based on the composite laminate theory.The study results showed that the values of average compressive strength of CLT and timber were 39.9 MPa and 30.41 MPa,respectively.Weibull distribution had the highest goodness of fit.The relative error between the prediction value and measured value of compressive strength of CLT was under 8.0%.There was higher predictive accuracy of CLT's compressive strength by using MCS method,whose relative error of average value and 5%percentile value were 5.8%and-0.8%,respectively.
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