Treffer: 基于主动学习代理模型的采气井口O 形密封圈可靠性分析.

In practical engineering applications, O-ring design parameters such as manufacturing tolerances, load fluctuations, and material properties often deviate from deterministic values and exhibit stochastic variations within specific ranges. To account for the impact of these uncertainty factors on O-ring sealing performance, a reliability analysis method based on an active learning Kriging model was proposed for evaluating the sealing reliability of O - ring rubber seals in high-pressure gas wellheads. Taking a eertain O_ring rubber seal at a high-pressure gas wellhead as the analysis objeet, a sealing reliability funetion was established. Python was used for seeondary development simulation of Abaqus, by ineorporating uneertainties eaused by manufaeturing toleranees and load fluetuations into the sealing performanee ealeulation proeess, the sealing reliability of the O - ring rubber seal was analyzed utilizing an adaptive Kriging eombined with the Monte Carlo method(AK-MCS). The analysis results show that eonsidering manufaeturing toleranees and load fluetuations, the failure probability of the O-ring rubber seal due to maximum Mises stress is 0. 013%. Groove depth, groove edge fillet radius, and internal pressure signifieantly influenee the maximum Mises stress in sealing rings. Speeifieally, internal pressure and groove edge fillet radius exhibit a positive eorrelation with the maximum Mises stress, while groove depth shows a negative eorrelation. The failure probability due to maximum eontaet stress is 0, and groove depth has a signifieant influenee on the maximum eontaet stress of the seal. The use of a reliability analysis method based on aetive learning Kriging models for high-pressure gas wellhead O-ring rubber seal ean evaluate the dangerous struetures of eomponents matehing with the O -ring rubber seal and the sealing failure probability, providing eorresponding guidanee for praetieal engineering. [ABSTRACT FROM AUTHOR]

由于制造公差、载荷波动、材料特性等,在实际工程中形圈的相关设计参数往往不再是一个确定值,可能在一定的范围内波动。考虑不确定性因素对O形圈密封性能的影响,提出基于主动学习 Kriging 模型的可靠性分析方法,用于高压采气井口形橡胶密封圈密封性能的可靠性分析。以高压采气井口某0形橡胶密封圈为分析对象,建立密封可靠性功能函数;使用Python 进行 Abaqus的二次开发仿真,将制造公差、载荷波动带来的不确定性纳入密封性能计算过程,并基于自适应性 Kriging 与Monte Carlo 法相结合的方法(AK-MCS),对该形橡胶密封圈的密封可靠性进行分析。结果表明:在考虑制造公差与载荷波动的情况下,该形橡胶密封圈由于最大 Mises 应力导致的失效概率为0.013%;凹槽深度、槽校圆角半径、内压对密封圈的最大 Mises 应力有着较大影响,其中内压,槽枝圆角半径与最大 Mises 应力呈正相关关系,凹槽深度与最大 Mises 应力呈负相关关系;最大接触应力导致的失效概率为0。凹槽深度对密封圈的最大接触应力有较大影响。使用基于主动学习 Kriging 模型的高压采气井口形橡胶密封圈密封可靠性分析方法,可评估与形橡胶密封圈相配合部件的危险结构与密封圈密封失效概率,为实际工程. [ABSTRACT FROM AUTHOR]

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