The turbulent jet ignition concept using prechambers is a promising solution to achieve stable combustion at lean conditions in large gas engines, leading to high efficiency at low emission levels. Due to the wide range of design and operating parameters for large gas engine prechambers, the preferred method for evaluating different designs is computational fluid dynamics (CFD), as testing in test bed measurement campaigns is time-consuming and expensive. However, the significant computational time required for detailed CFD simulations due to the complexity of solving the underlying physics also limits its applicability. In optimization settings similar to the present case, i.e., where the evaluation of the objective function(s) is computationally costly, Bayesian optimization has largely replaced classical design-of-experiment. Thus, the present study deals with the computationally efficient Bayesian optimization of large gas engine prechambers design using CFD simulation. Reynolds-averaged-Navier-Stokes simulations are used to determine the target values as a function of the selected prechamber design parameters. The results indicate that the chosen strategy is effective to find a prechamber design that achieves the desired target values.

翻译：采用预燃室的湍流射流点火概念是实现大型燃气发动机稀薄燃烧稳定燃烧的有效方案，可确保高效率和低排放。由于大型燃气发动机预燃室的设计和运行参数范围广泛，评估不同设计的首选方法是计算流体动力学（CFD），因为测试平台测量耗时长且成本高。然而，由于求解底层物理问题的复杂性，详细CFD模拟所需的巨大计算时间也限制了其适用性。在与本研究类似的优化场景中（即目标函数评估计算成本高昂的情况下），贝叶斯优化已基本取代了经典实验设计。因此，本研究通过CFD模拟，对大型燃气发动机预燃室设计进行计算高效的贝叶斯优化。采用雷诺平均纳维-斯托克斯（RANS）模拟，以选定预燃室设计参数为变量确定目标值。结果表明，所选策略能够有效找到满足期望目标值的预燃室设计。