Reliability-based Analysis for Two-phase Flow of Locomotive Side Wall Filtration Systems with Non-random Load Uncertainty

doi:10.3969/j.issn.1004-132X.2023.15.013

Abstract

Abstract: A two-phase flow reliability analysis method was proposed for locomotive side wall filtration systems with interval non-random load uncertainty， considering the difficulty of modeling the cognitive uncertainty of load parameters and combining the randomness of manufacturing and installation， aiming at the reliability problems of the locomotive side wall filtration systems with the changes of operating environments. Firstly， the CFD model of two-phase flow in the filter system of the locomotive side walls was established through experimental comparison. Secondly， the reliability analysis of the two-phase flow mechanics problem of the locomotive side wall filtration systems was carried out by using the probabilistic and interval mixed uncertainty model and the corresponding effective reliability analysis method. The structural parameters with sufficient samples and load parameters with insufficient samples were measured by probability and interval method respectively. The difficulty of modeling cognitive uncertainty caused by insufficient samples could be quickly solved， which extended the applicability of reliability analysis technique of interval mixed uncertainty in the study of two-phase flow mechanics problems. Through the study of load reliability problems such as resistance and filtration efficiency of two-phase flow problem of electric locomotive side wall filtration systems， reasonable improvement of the uncertainty level of key parameters may take into account the cost， and improve the reliability of the filtration systems， Which meets the requirements of high reliability applications in complex operating environments of electric locomotives， and provides reference for engineering applications.

Key words: two phase flow, reliability analysis, interval, hybrid model, locomotive side wall filtration system

摘要： 针对机车侧墙过滤系统制造安装和运行环境变化的可靠性问题，考虑到载荷参数认知不确定性建模困难，结合制造安装随机性，提出了一种含区间非随机载荷不确定的机车侧墙过滤系统两相流可靠性分析方法。首先，通过实验对比，建立了机车侧墙过滤系统两相流的CFD模型。其次，采用概率和区间混合不确定性模型及其相应的有效可靠性分析方法，对机车侧墙过滤系统的两相流动力学问题进行可靠性分析。对样本充足的结构参数和样本不足的载荷参数分别用概率和区间法进行度量，因样本不足而造成的认知不确定性建模困难可以快速得到解决，扩展了区间混合不确定性的可靠性分析技术在两相流动力学问题研究中的适用性。通过对电力机车侧墙过滤系统两相流问题的阻力和过滤效率等载荷可靠性问题的研究，合理提高了关键参数的不确定性水平，既可兼顾成本又可提高过滤系统的可靠性，满足电力机车运行复杂环境高可靠性应用的要求，为工程应用提供参考。

关键词: 两相流, 可靠性分析, 区间, 混合模型, 机车侧墙过滤系统

CLC Number:

TH122

QU Xiaozhang, ZHANG Jiabei, ZHAI Fangzhi. Reliability-based Analysis for Two-phase Flow of Locomotive Side Wall Filtration Systems with Non-random Load Uncertainty[J]. China Mechanical Engineering, 2023, 34(15): 1881-1889.

屈小章, 张加贝, 翟方志. 非随机载荷不确定的机车侧墙过滤系统两相流可靠性分析[J]. 中国机械工程, 2023, 34(15): 1881-1889.

References

［1］GRIMSTAD B， FOSS B， HEDDLE R， et al. Global Optimization of Multiphase Flow Networks Using Spline Surrogate Models［J］. Computers & Chemical Engineering， 2016， 84：237-254.
［2］LIN Z， YANG W， ZHOU H， et al. Communication Optimization for Multiphase Flow Solver in the Library of OpenFOAM［J］. Water， 2018， 10（10）：1461.
［3］张健平，赵彦宾，邓尧. 基于气固两相流流动特性风帽式布风板结构参数优化［J］. 大学物理实验， 2022， 35（6）：1-11.
ZHANG Jianping， ZHAO Yanbin， DENG Yao. Structural Parameter Optimization of Cowl Distributor Based on Gas-solid Two-phase Flow Characteristics［J］. University Physical Experiment， 2022， 35（6）：1-11.
［4］FEI C W， TANG W Z， BAI G C. Novel Method and Model for Dynamic Reliability Optimal Design of Turbine Blade Deformation［J］. Aerospace Science and Technology， 2014， 39：588-595.
［5］HU Z， DU X， KOLEKAR N S， et al. Robust Design with Imprecise Random Variables and Its Application in Hydrokinetic Turbine Optimization［J］. Engineering Optimization， 2014， 46（3）：393-419.
［6］YANG H， ZHU Y， LU Q， et al. Dynamic Reliability Based Design Optimization of the Tripod Sub-structure of Offshore Wind Turbines［J］. Renewable Energy， 2015， 78：16-25.
［7］KIM D H， LEE S G. Reliability Analysis of Offshore Wind Turbine Support Structures under Extreme Ocean Environmental Loads［J］. Renewable Energy， 2015， 79：161-166.
［8］BALONI B D， PATHAK Y， CHANNIWALA S A. Centrifugal Blower Volute Optimization Based on Taguchi Method［J］. Computers & Fluids， 2015， 112：72-78.
［9］HU W， CHOI K K， CHO H. Reliability-based Design Optimization of Wind Turbine Blades for Fatigue Life under Dynamic Wind Load Uncertainty［J］. Structural and Multidisciplinary Optimization， 2016， 54（4）：953-970.
［10］GAO H， FEI C， BAI G， et al. Reliability-based Low-cycle Fatigue Damage Analysis for Turbine Blade with Thermo-structural Interaction［J］. Aerospace Science and Technology， 2016， 49：289-300.
［11］KAMENIK J， VOUTCHKOV I， TOAL D J， et al. Robust Turbine Blade Optimization in the Face of Real Geometric Variations［J］. Journal of Propulsion and Power， 2018， 34（6）：1479-1493.
［12］LI L， WAN H， GAO W， et al. Reliability Based Multi-disciplinary Design Optimization of Cooling Turbine Blade Considering Uncertainty Data Statistics［J］. Structural and Multidisciplinary Optimization， 2019， 59（2）：659-673.
［13］倪俊，虞跨海，岳珠峰. 基于可靠性的涡轮叶片双循环多学科设计优化［J］. 航空动力学报， 2009， 24（9）：2051-2056.
NI Jun， YU Kuahai， YUE Zhufeng. Multi-disciplinary Design Optimization of Turbine Blades with Double Cycle Based on Reliability［J］. Journal of Aerospace Power， 2009， 24（9）：2051-2056.
［14］贺谦，李元生，温志勋，等. 涡轮叶片多学科可靠性及稳健设计优化［J］. 推进技术， 2010， 31（2）：193-197.
HE Qian， LI Yuansheng， WEN Zhixun， et al. Multidisciplinary Reliability and Robust Design Optimization of Turbine Blades［J］. Journal of Propulsion Technology， 2010， 31（2）：193-197.
［15］屈小章，刘桂萍，韩旭，等. 基于区间的风机系统翼型气动性能不确定性优化［J］. 中国科学：技术科学， 2017， 47（9）：955-964.
QU Xiaozhang， LIU Guiping， HAN Xu， et al. Uncertainty Optimization of Aerodynamic Performance of Fan Airfoil Based on Interval［J］. Scientia Sinica Technol， 2017， 47（9）：955-964.
［16］屈小章，余江鸿，姚齐水，等. 基于随机-区间混合不确定性的风机性能可靠性分析［J］. 中国科学：技术科学， 2020， 50（3）：299-311.
QU Xiaozhang， YU Jianghong， YAO Qishui， et al. Reliability Analysis of Fan Performance Based on Random-interval Mixed Uncertainty［J］. Science China：Technology Sciences， 2020， 50（3）：299-311.
［17］QU Xiaozhang， YU Jianghong， YAO Qishui， et al. Reliability-based Analysis Method of Fluid Dynamics for Turbomachinery with Interval Distribution Parameters［J］. Engineering Optimization， 2021， 53（6）：919-940.
［18］JIANG C， LI W X， HAN X， et al. Structural Reliability Analysis Based on Random Distributions with Interval Parameters［J］. Computers & Structures， 2011， 89（23/24）：2292-2302.
［19］JIANG C， LU G Y， HAN X， et al. A New Reliability Analysis Method for Uncertain Structures with Random and Interval Variables［J］. International Journal of Mechanics and Materials in Design， 2012， 8（2）：169-182.
［20］HAN X， JIANG C， LIU L， et al. Response-surface-based Structural Reliability Analysis with Random and Interval Mixed Uncertainties［J］. Science China Technological Sciences， 2014， 57（7）：1322-1334.
［21］SHAHEED R， MOHAMMADIAN A， GILDEH K H. A Comparison of Standard k-ε and Realizable k-ε Turbulence Models in Curved and Confluent Channels［J］. Environmental Fluid Mechanics， 2019， 19（2）：543-568.
［22］LIN Z， SUN X， YU T， et al. Gas-solid Two-phase Flow and Erosion Calculation of Gate Valve Based on the CFD-DEM Model［J］. Powder Technology， 2020， 366：395-407.
［23］YAN G， LI Z， BORE T， et al. Discovery of Dynamic Two-phase Flow in Porous Media Using Two-dimensional Multiphase Lattice Boltzmann Simulation［J］. Energies， 2021， 14（13）：1-22.
［24］冯明坤. 电力机车用过滤器阻力特性及过滤特性的研究［D］. 长沙：中南大学， 2009.
FENG Mingkun. Research on Resistance Characteristics and Filtration Characteristics of Filters for Electric Locomotive［D］. Changsha：Central South University， 2009.
［25］李联波. 旋流喷动气固两相流场中颗粒运动行为研究［D］. 天津：天津大学， 2006.
LI Lianbo. Research on Particle Motion Behavior in Swirling Jet Gas-solid Two-phase Flow Field［D］. Tianjin：Tianjin University， 2006.

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