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形状记忆效应与超弹性耦合作用下镍钛合金波形垫片力学与密封性能计算模型:两种密封性能

Calculation Model of Mechanical and Sealing Properties of NiTi Alloy Corrugated Gaskets under Shape Memory Effect and Hyperelastic Coupling: Two Sealing Properties.

作者信息

Zhu Lingxue, Liu Yang, Li Mingxuan, Lu Xiaofeng, Zhu Xiaolei

机构信息

Department of Mathematics, Jinling Institute of Technology, Nanjing 211169, China.

School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China.

出版信息

Materials (Basel). 2022 Jul 2;15(13):4659. doi: 10.3390/ma15134659.

DOI:10.3390/ma15134659
PMID:35806783
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9267744/
Abstract

Bolted flange connections are commonly used in process industries. Their sealing performance is greatly affected by the gasket. In this paper, a NiTi alloy corrugated gasket was simulated to reveal its sealing performance, considering the gasket surface roughness, shape memory effect and superelastic effect. A fluid-structure coupling analysis method that takes the real surface morphology of the gasket contact zone was proposed, and a leakage rate prediction model was established. The results showed that NiTi shape memory effect could enhance the sealing reliability in service and lower the leakage rate. The leakage rate of the NiTi alloy corrugated gasket is positively correlated with the internal pressure of the medium and the roughness of the sealing surface. The prediction model of the NiTi alloy corrugated gasket leakage rate has good reliability with an average error of about 16.81% compared with the simulation.

摘要

螺栓法兰连接在过程工业中广泛应用。其密封性能受垫片影响很大。本文对镍钛合金波纹垫片进行模拟以揭示其密封性能,考虑了垫片表面粗糙度、形状记忆效应和超弹性效应。提出了一种考虑垫片接触区真实表面形貌的流固耦合分析方法,并建立了泄漏率预测模型。结果表明,镍钛形状记忆效应可提高服役中的密封可靠性并降低泄漏率。镍钛合金波纹垫片的泄漏率与介质内部压力和密封面粗糙度呈正相关。镍钛合金波纹垫片泄漏率预测模型具有良好的可靠性,与模拟结果相比平均误差约为16.81%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/8396b54a4cd0/materials-15-04659-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/fbcbb5dd4b6a/materials-15-04659-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/647625fb0a4d/materials-15-04659-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/4fb67769642d/materials-15-04659-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/6b1bb4676bfd/materials-15-04659-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/699313aed274/materials-15-04659-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/857449968419/materials-15-04659-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/4689b251c2f5/materials-15-04659-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/b68eb60cfbe0/materials-15-04659-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/8396b54a4cd0/materials-15-04659-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/fbcbb5dd4b6a/materials-15-04659-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/d3609902ecac/materials-15-04659-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/ebfc113ff5c3/materials-15-04659-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/64ab0f0a05fa/materials-15-04659-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/31c352763c69/materials-15-04659-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/b947f89048c5/materials-15-04659-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/647625fb0a4d/materials-15-04659-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/4fb67769642d/materials-15-04659-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/6b1bb4676bfd/materials-15-04659-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/699313aed274/materials-15-04659-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/857449968419/materials-15-04659-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/4689b251c2f5/materials-15-04659-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/b68eb60cfbe0/materials-15-04659-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0207/9267744/8396b54a4cd0/materials-15-04659-g014.jpg

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