Strength Analysis of Fasteners in Thick Sandwich Single Shear Connector Joints Guo Xiaoning Zhang Xu Shanghai Aircraft Design and Research Institute, Shanghai 201210 No. on the thickness of the connecting piece (mm) with 樯 according to 19.51 level 29.52 level 39.53 level 49.54 level 59.55 level G522 level 722.92830, The 52nd grade uses ABQUS finite element software to numerically simulate the structure of thick sandwich single-shear joints. The model is shown below.
The finite element analysis and experimental verification method were used to study the bending stress of the fastener caused by the bending strength of the fastener under the influence of different joint thickness, fastener fitting precision and tightening torque. influences. The results show that different joint thickness, fastener matching precision and tightening torque of the fastener have less influence on the fastener strength. The bending stress of the fastener can be ignored in the strength check of the fastener. .
Fasteners; joint thickness; mating accuracy; tightening torque Abstract In the design of aircraft system equipment brackets, in order to ensure the strength of the joint between the bracket and the fuselage structure, or because of the installation restrictions, thick sandwich single shear joints are often used The connection is made. In the connection of such a joint, the bending stress of the connecting fastener is compared with the shear stress due to the joint thickness, the fitting precision of the fastener and the connecting hole, and the tightening torque when the fastener is installed. May become the dominant stress. Therefore, it is necessary to consider not only the shearing and tensile stress of the fastener but also the bending of the fastener due to the influence of the joint thickness, the fitting precision and the tightening torque. stress. At present, the method for checking the bolt bending engineering method under such inert conditions is relatively conservative, and the strength of the bolt is often not satisfactory. In this paper, the effects of bolt bending on bolt strength under different thicknesses, different tightening torques and matching precision are studied by finite element analysis and experimental analysis. A typical connection form for a thick sandwich single shear joint is shown.
The finite element numerical simulation analysis of 1 thick sandwich single-shear joint is based on the precision of the fitting and the thickness of the joint. The finite element numerical simulation analysis of the bolt force is carried out, and the tightening torque has not found the setting method in the finite element calculation, so it is not considered. Numerical simulation analysis was carried out according to the combination of the matching precision and the thickness of the joint.
Table 1 Numerical Simulation Scheme 0 Stress Symptom of the 8th Combination Bolt From the stress deformation diagram of the bolt, it can be clearly seen that the bolt is bent and the maximum stress appears on the outside of the bend. Draw the maximum stress variation of the bolt as a graph, as shown in 1 and 12.
2 The maximum stress of the bolt can be seen as the thickness of the upper connecting piece changes. When the thickness of the upper connecting piece is equal, the smaller the matching clearance is, the higher the matching precision is. At this time, the maximum stress of the bolt is smaller; With the 2nd and 3rd stage matching accuracy, the maximum stress difference of the bolt is small. When the thickness of the upper connecting piece is changed from 9.5mm to 30.8mm, the maximum stress of the bolt is gradually reduced, but the difference between the minimum thickness and the maximum thickness is only 16 MPa, and the change is only 1.6 °%. Therefore, it can be seen from the analysis that the joint The thickness of the bolt and the matching accuracy of the connecting hole have little influence on the force of the bolt.
2 Thick sandwich single-shear joint test analysis test The test piece is designed according to the typical connection of the system equipment. The test piece form, the test piece is installed as shown in the following 3 and 4: 4 thick sandwich single shear joint test piece The installation form test is based on a total of 24 combinations of 4 different thickness joints, 2 different diameter bolts, 3 kinds of connecting bolt tightening torques and bolt hole fitting precision. The combination form is shown in Table 1.
Table 2 Test piece case combination 1. Vlmm) The following K buckle. 1 Note: 1 indicates bolt specifications. For example, in 04030, 04 represents the bolt diameter and 030 represents the bolt length.
2 indicates the accuracy of the fit between the bolt and the joint connection hole.
In the test, the bolt was destroyed and the time load curve of the bolt was obtained. The test results show that the damage load value is compared with the standard shear failure value of the bolt, so that it can be seen that the bending of the bolt affects the strength of the fastener under different joint thicknesses, different fitting precisions and tightening torques.
In order to facilitate the analysis of the thickness of the connecting piece, the matching accuracy and the influence of the tightening torque on the bolt breaking load, we have drawn a histogram.
a) The effect of different fitting precision on the shear load of the bolt under different interlayer thicknesses.
The science and technology education has innovated the examination of bookmark2, but the author did not explain whether this information should be included in the test of the test-retest reliability. In general, the reliability coefficients of multiple-choice questions, sorting questions, and open questions in the questionnaire cannot be calculated.
2.3 Descriptive analysis of survey results For descriptive analysis, statistical graphs and statistical tables can be used. Because different types of variables are used in different descriptions, it is necessary to first distinguish the types of variables. Generally speaking, the original data is mostly used with stem and leaf maps. Box line graph, group data multi-use histogram, time series data with line graph, multi-variable data with scatter plot, bubble map, radar map.
In the actual application, the statistical table appears the most frequently, which also indicates that everyone agrees with the role of the statistical table. However, some of the articles are too single to be averaged, proportioned, etc., or just a type of descriptive analysis. For example, there are 21 forms in the analysis of the factors affecting the development of secondary vocational sports in a certain area, but there are 19 forms in the following form: Table 1 The percentage of surveys and statistics of physical education teachers on students' ideological and moral education is more frequent. C does not often D occasionally E does not make selections and then draws a conclusion. In fact, the inferiority of physical education teachers' ideological and moral education can be divided into five categories and the teacher factors that restrict sports development. Multi-factor analysis is also needed. Of course, for the application of factor analysis, it is very important to master its thoughts. If you can't grasp the essence of factor analysis, you will not be able to make choices about the number of factors and solutions in combination with actual problems, and even if the calculation results are reasonable or not.
2.4 Inferred Analysis of Survey Results Parameter Estimation: Two Requirements for Parameter Estimation: Accuracy: The maximum range of estimated error is reflected by the limit error. Obviously, the smaller A is, the higher the accuracy requirement is estimated. The larger A is, the lower the accuracy requirement is. The determination of the limit error is based on actual needs. Reliability: A probabilistic guarantee of the correctness of the estimate, often referred to as the confidence of the estimate.
Hypothesis testing: A statistical analysis method that demonstrates the authenticity of a hypothesis by proposing hypotheses and using the "small probability principle" and "probability counter-evidence method". As long as the fact (parameter assumption) is established, under the premise that the fact is established, To prove that the probability of the statistic from the fact (parameter assumption) and sample construction is small to prove whether the assumption is true.
Some authors have a lot of scientific factors in the hypothesis test based on the calculation of the statistical results, which is not the only one that can be determined by calculation. In fact, the statistical calculation itself has certain limitations, because its conclusion is a certain probability, rather than absolute affirmation and negation, so the calculation results must be combined with relevant professional knowledge to make a clear analysis. The other extreme is to apply all the statistical methods, namely, correlation analysis, hypothesis testing, regression analysis, etc., and think that it is better to do more than to do less analysis.
Example: A comparative analysis of two groups of 100m breaststroke before and after the experiment, the score of group A increased by 0.94〃, P<0.05, the difference was not significant, the score did not improve; group B increased by 0.9〃, P<0.05, the difference has Significant meaning, improved scores. This kind of contradictory conclusion should consider whether the calculation is wrong or the experimental design method is improper. If there is no problem above, the sample capacity should be increased for re-experiment.
According to the student's actual inertia, you can follow the analysis of the other party's difference, factor analysis, and related analysis. You can also combine this part of the content with the specific operations of the last lesson and statistical software.
2.5 Using statistical software to analyze and summarize the results for analysis, you can first conduct some social surveys, and then provide guidance on specific issues (to be combined with professional teachers to extract the main data).
Before this class, teachers need to consult relevant information at home and abroad, analyze the misuse and misunderstanding of scientific research papers, and raise the issues that should be paid attention to in practice. I hope to minimize the misuse of statistical methods used by students. Misunderstood. For example: strict control error, the idea of ​​optimization is reflected as much as possible, that is, using economic manpower, material resources and time to obtain more satisfactory results, answering the questions of research hypothesis. The experimental design should be appropriate. If the experimental design is not appropriate, it will increase the number of experiments, prolong the experimental period, cause waste of manpower and material resources, and it is difficult to achieve the expected results, and even lead to the failure of the entire research work. In short, it is necessary to summarize the statistical analysis process, for example, practical application.
3 The problem that should be paid attention to in teaching is a complex system engineering waiting for us to study and explore a lot of problems. Teachers need to be able to learn to observe, design, and compare the teaching practice experience to the teaching theory while emphasizing the "foundation" while also focusing on cultivating students' innovative "thought" and "classification" ability to solve problems, in line with the current Ministry of Education. Cultivate the requirements of applied talents. The role of the "short-time" course: The micro-curriculum will help teachers strengthen and improve their teaching skills and methods, reduce mistakes, and enable students to build confidence as quickly as possible.
For different professional teachers, firstly communicate with the professional teachers to focus on the design of the primary school curriculum. Although the methods or methods are the same, but the professional differences cause different teaching contents, the statistical theory need not be said, the key point is Application, what content to apply, and considerations for the application process. Finally, it is pointed out that although the statistical methods used by the sports major are diverse, different types of articles are selected according to the purpose of the researcher. Such as the comparison of various training methods and teaching methods, the measurement of students' health status, etc. For different research questions, there is no uniform statistical method that can be used.
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