Dong Yi, Liu Jianmin, Liu Yanbin, Li Huaying, Zhang Shaoliang, Hu Xuesong, Zhang Xiaoming
Vehicle Engineering Department, Army Academy of Armored Forces, Beijing, China.
Department of Weapon and Control, Army Academy of Armored Forces, Beijing, China.
Sci Prog. 2021 Apr-Jun;104(2):368504211011347. doi: 10.1177/00368504211011347.
With the aim of enhancing both reliability and fatigue life of gasket, this study combines finite element analysis, orthogonal experimental design, dynamically-guided multi-objective optimization, and the non-dominated sorting genetic algorithm with elitist strategy to optimize the geometric parameters of the cylinder gasket. The finite element method was used to analyze the temperature field, thermal-mechanical coupling stress field, and deformation of cylinder gasket. The calculation results were experimentally validated by measured temperature data, and comparison results show that the maximum error between calculated value and experiment value is 7.1%, which is acceptable in engineering problems. Based on above results and orthogonal experiment design method, the effects of five factors, including diameter of combustion chamber circle, diameter of coolant flow hole, length of the insulation zone between third and fourth cylinders, thickness of gasket, and bolt preload, on three indexes: temperature, stress, and deformation of gasket, were examined in depth. Through the variance analysis of the results, three important factors were identified to proceed later calculation. The dynamically guided multi-objective optimization strategy and the non-dominated sorting genetic algorithm were effectively used and combined to determine the optimal geometric parameters of cylinder gasket. Furthermore, calculation results suggest that temperature, stress, and deformation of the optimized cylinder gasket have been improved by 27.88 K, 16.84 MPa, and 0.0542 mm, respectively when compared with the origin object, which shows the excellent performance of gasket optimization and effectiveness of the proposed optimization strategy.
为提高垫片的可靠性和疲劳寿命，本研究结合有限元分析、正交试验设计、动态引导多目标优化以及带精英策略的非支配排序遗传算法，对气缸垫片的几何参数进行优化。采用有限元方法分析气缸垫片的温度场、热-机械耦合应力场及变形情况。通过实测温度数据对计算结果进行实验验证，对比结果表明计算值与实验值之间的最大误差为7.1%，在工程问题中是可接受的。基于上述结果和正交试验设计方法，深入研究了燃烧室圆直径、冷却液流孔直径、第三和第四气缸之间隔热区长度、垫片厚度以及螺栓预紧力这五个因素对垫片温度、应力和变形这三个指标的影响。通过对结果的方差分析，确定了三个重要因素以便后续进行计算。有效运用并结合动态引导多目标优化策略和非支配排序遗传算法来确定气缸垫片的最优几何参数。此外，计算结果表明，与原始对象相比，优化后的气缸垫片的温度、应力和变形分别提高了27.88K、16.84MPa和0.0542mm，这表明垫片优化性能优异，所提出的优化策略有效。
