摘要
惯性级滤清器性能是影响船舶燃气轮机进气系统出口流场品质的重要因素,也在一定程度上决定了船舶的动力水平。本文采用气-液两相流数值模拟方法,以低总压损失和高过滤效率为共同目标,结合试验设计方法,分别构建了总压损失、过滤效率与叶片几何参数间的响应面方程,并采用多目标遗传优化算法对惯性级滤清器叶片参数进行优化设计。结果表明:优化后的惯性级滤清器在所研究速度条件下均以更小的总压损失实现了更高的过滤效率。2 m/s的速度方案下,优化后的总压损失减少了16.98%,过滤效率提升37.61%;7 m/s的速度方案下,优化后的总压损失减少16.7%,而过滤效率提升20.83%;流速高时应选用叶片间距更小、坡度更低、叶片越长的滤清器;而低流速应该改用间距更大、长度更短、坡度更高的惯性级滤清器叶片。优化后的滤清器叶片结构既减小了叶片背风区的分离,使总压损失减小,也增加了液体颗粒与叶片的接触而提升了过滤效率,从而提高了滤清器的整体性能。
The performance of inertia stage filter is an important factor affecting the quality of the flow field at the outlet of marine gas turbine air intake system,and also determines the power level of the ship to a certain extent.With low total pressure loss and high filtration efficiency as the common goal,the numerical simulation method of gas-liquid two phase flow combined with experimental design method are adopted to construct the response surface equations among total pressure loss,filtration efficiency and blade geometric parameters respectively in this paper,and a multi-objective non-dominated sorting genetic algorithmis used to optimize and design the parameters of inertia stage filter blades.The results show that the optimized inertia stage filter achieves higher filtration efficiency with less total pressure loss in the full speed range.At the speed of 2 m/s,the optimized total pressure loss is reduced by 16.98%and the filtration efficiency is increased by 37.61%.At the speed of 7 m/s,the optimized total pressure loss is reduced by 16.7%,and the filtration efficiency is increased by 20.83%;in inertia stage filters,for high flow speed,longer blade with smaller spacing and lower slope should be selected;for low flow speed,shorter blade with larger spacing and higher slope should be used;the optimized filter blade structure not only reduces the separation in the leeward area of the blade to reduce the total pressure loss,but also increases the contact between liquid particles and the blade to improve the filtration efficiency,so as to improve the whole performance of filter.
作者
付宇
阳仕柏
刘艳明
王建华
FU Yu;YANG Shi-bo;LIU Yan-ming;WANG Jian-hua(Systems Engineering Research Institute of CSSC,Beijing,China,Post Code:100094;School of Aerospace Engineering,Beijing Institute of Technology,Beijing,China,Post Code:100081)
出处
《热能动力工程》
CAS
CSCD
北大核心
2023年第4期33-38,共6页
Journal of Engineering for Thermal Energy and Power
关键词
惯性级滤清器
多目标遗传算法
优化设计
总压损失
过滤效率
inertia stage filters
multi-objective genetic algorithm
optimized design
total pressure loss
filtration efficiency
