复合材料多排钉连接结构钉载分配规律
Load distribution law in multi-bolts connected composite structure
宋鑫 1李伟 2李桐 1王成波 2王博1
作者信息
- 1. 大连理工大学 工业装备结构分析优化与CAE软件全国重点实验室,大连 116024
- 2. 沈阳飞机设计研究所,沈阳 110035
- 折叠
摘要
针对复合材料多排钉连接结构实际强度破坏极限和破坏模式与传统工程算法不一致的问题,本文以光纤螺栓试验手段为基础,开展了复合材料连接结构钉载分配规律的研究.主要研究了钉载不对称、装配顺序、装配间隙等工艺特征对钉载分配的影响,同时建立了高精度有限元模型进行对比研究.研究结果表明:多排钉连接结构钉载不对称时会加剧钉载的不均匀分配;装配顺序对钉载分配存在影响,在装配螺栓时最后安装最外侧螺栓,可以有效降低钉载分布差异;连接结构存在一致装配间隙时的钉载分配与无间隙情况的载荷分配结果一致.同时,本文发现通过试验手段测得关键螺栓的钉载占比最大比有限元结果高出 10%,因此工程算法需要根据装配间隙等制造和工艺特征进行修正.
Abstract
To address the issue of inconsistencies between the actual strength and failure mode of composite multi-row nail connection structures and traditional engineering algorithms,this study investigated nail load distribution patterns in composite connection structures based on fibre optic bolt testing techniques.The study primarily examines the effect of process characteristics such as nail load asymmetry,assembly sequence and assembly clearance on nail load distribution,while also establishing a high-precision finite element model for comparative study.The results indicate that asymmetric nail loading in a multi-row nail connection structure exacerbates un-even nail load distribution.Assembly sequence affects nail load distribution,and installing the outermost bolt last during bolt assembly can effectively reduce differences in nail load distribution.Nail load distribution in structures with uniform assembly clearance is consistent with load distribution in structures with no clearance.Additionally,the study finds that the proportion of critical bolt nail loads measured through testing is over 10%higher than the finite element results,suggesting that engineering algorithms need to be modified based on manufacturing and process characteristics such as assembly clearance.
关键词
光纤螺栓/复合材料连接结构/钉载分配/有限元/多排钉Key words
optical fiber bolt/composite connection structure/nail load distribution/finite element/multi-row bolt引用本文复制引用
基金项目
国家自然科学基金(12172077)
国家自然科学基金(11825202)
大连市高层次人才创新支持计划(2019RD04)
大连市科技创新基金(2020JJ25CY011)
出版年
2024
NETL
NSTL
万方数据