{"title":"利用纵向振动和视觉特性预测南方松2×8和2×10材的力学性能","authors":"F. França, T. França, R. D. Seale, R. Shmulsky","doi":"10.22382/wfs-2020-026","DOIUrl":null,"url":null,"abstract":"The objective of this study was to evaluate the accuracy of single MOE and MOR and combined mechanical properties with visual characteristics to improve the prediction of 2 x 8 and 2 x 10 No. @ southern pine lumber. This study evaluated the following variables: nondestructive tests, knots (knot diameter ratio [KDR] and knot area ratio), density, and mechanical properties (stiffness [MOE] and strength [MOR]). A total of 486 pieces were used, and linear regression models were constructed using stepwise selects to determine the best variables to estimate the MOE and MOR of southern pine lumber. The best single predictor for MOE and MOR was dynamic MOE (dMOE) followed by density. Among the two knot measurement methods used, the KDR best predicted stiffness and strength. For predicting the MOE, the variables dMOE, density, and KDR. The results showed that the addition of knot measurements to the models is able to improve the prediction of mechanical properties.","PeriodicalId":23620,"journal":{"name":"Wood and Fiber Science","volume":"52 1","pages":"280-291"},"PeriodicalIF":0.8000,"publicationDate":"2020-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Use of longitudinal vibration and visual characteristics to predict mechanical properties of No. S Southern pine 2x8 and 2x10 Lumber\",\"authors\":\"F. França, T. França, R. D. Seale, R. Shmulsky\",\"doi\":\"10.22382/wfs-2020-026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this study was to evaluate the accuracy of single MOE and MOR and combined mechanical properties with visual characteristics to improve the prediction of 2 x 8 and 2 x 10 No. @ southern pine lumber. This study evaluated the following variables: nondestructive tests, knots (knot diameter ratio [KDR] and knot area ratio), density, and mechanical properties (stiffness [MOE] and strength [MOR]). A total of 486 pieces were used, and linear regression models were constructed using stepwise selects to determine the best variables to estimate the MOE and MOR of southern pine lumber. The best single predictor for MOE and MOR was dynamic MOE (dMOE) followed by density. Among the two knot measurement methods used, the KDR best predicted stiffness and strength. For predicting the MOE, the variables dMOE, density, and KDR. The results showed that the addition of knot measurements to the models is able to improve the prediction of mechanical properties.\",\"PeriodicalId\":23620,\"journal\":{\"name\":\"Wood and Fiber Science\",\"volume\":\"52 1\",\"pages\":\"280-291\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2020-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wood and Fiber Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.22382/wfs-2020-026\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wood and Fiber Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.22382/wfs-2020-026","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 2
摘要
本研究的目的是评估单一MOE和MOR的准确性,并将机械性能与视觉特征相结合,以改进2 x 8和2 x 10号@南方松木材的预测。本研究评估了以下变量:无损检测、结(结直径比[KDR]和结面积比)、密度和机械性能(刚度[MOE]和强度[MOR])。共使用486块,并使用逐步选择构建线性回归模型,以确定估计南方松木材MOE和MOR的最佳变量。MOE和MOR的最佳单一预测因子是动态MOE(dMOE),其次是密度。在使用的两种结测量方法中,KDR最能预测刚度和强度。为了预测MOE,变量dMOE、密度和KDR。结果表明,在模型中添加结测量能够提高力学性能的预测。
Use of longitudinal vibration and visual characteristics to predict mechanical properties of No. S Southern pine 2x8 and 2x10 Lumber
The objective of this study was to evaluate the accuracy of single MOE and MOR and combined mechanical properties with visual characteristics to improve the prediction of 2 x 8 and 2 x 10 No. @ southern pine lumber. This study evaluated the following variables: nondestructive tests, knots (knot diameter ratio [KDR] and knot area ratio), density, and mechanical properties (stiffness [MOE] and strength [MOR]). A total of 486 pieces were used, and linear regression models were constructed using stepwise selects to determine the best variables to estimate the MOE and MOR of southern pine lumber. The best single predictor for MOE and MOR was dynamic MOE (dMOE) followed by density. Among the two knot measurement methods used, the KDR best predicted stiffness and strength. For predicting the MOE, the variables dMOE, density, and KDR. The results showed that the addition of knot measurements to the models is able to improve the prediction of mechanical properties.
期刊介绍:
W&FS SCIENTIFIC ARTICLES INCLUDE THESE TOPIC AREAS:
-Wood and Lignocellulosic Materials-
Biomaterials-
Timber Structures and Engineering-
Biology-
Nano-technology-
Natural Fiber Composites-
Timber Treatment and Harvesting-
Botany-
Mycology-
Adhesives and Bioresins-
Business Management and Marketing-
Operations Research.
SWST members have access to all full-text electronic versions of current and past Wood and Fiber Science issues.