防隔热一体化复合材料整体性能优化设计方法
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摘要
集非烧蚀、隔热和轻质可靠于一体的一类新型热防护材料是我国未来新型空天飞行器发展的核心技术,耐高温表层与内层隔热层的界面处是热失配最严重的区域,材料内部的梯度过渡设计是实现防隔热一体化复合材料的关键。为了提高材料的整体综合性能,首先利用单纯形法和邻域培植多目标遗传算法对材料梯度层组分过渡形式和材料尺寸参数进行了确定性优化,并以所获最优解作为初始值,进一步考虑了材料性能、载荷条件等的随机波动,采用6Sigma方法对材料整体性能进行了可靠性优化。结果表明:通过该优化策略,在获得满足可靠性要求的最优材料性能参数的同时,可以有效提高优化效率,对于计算模型复杂的优化问题尤为重要。
The development of a new kind of thermal protection material which combines non-ablation,thermal insulation,light-weight and reliability is the core technology for the development of new hypersonic vehicle.The interfaces between different materials are the most serious areas of thermal mismatch.The design of the gradient layers is the key to the realization of the composite material.To improve the performances of the composite material,deterministic optimization of transitional form of material components of the gradient layers and the material size parameters was made by using simplex method and neighborhood cultivation multi-objective genetic algorithm.Six Sigma method was further used to optimize the performances of the composite material considering uncertainty of material properties and load conditions and taking the above optimal solution as initial value.The optimization result shows that the optimization strategy can effectively improve the optimization efficiency while obtaining the optimal material performance parameters that meet the requirement of material reliability,which is especially important for calculating complex optimization problems.
The development of a new kind of thermal protection material which combines non-ablation,thermal insulation,light-weight and reliability is the core technology for the development of new hypersonic vehicle.The interfaces between different materials are the most serious areas of thermal mismatch.The design of the gradient layers is the key to the realization of the composite material.To improve the performances of the composite material,deterministic optimization of transitional form of material components of the gradient layers and the material size parameters was made by using simplex method and neighborhood cultivation multi-objective genetic algorithm.Six Sigma method was further used to optimize the performances of the composite material considering uncertainty of material properties and load conditions and taking the above optimal solution as initial value.The optimization result shows that the optimization strategy can effectively improve the optimization efficiency while obtaining the optimal material performance parameters that meet the requirement of material reliability,which is especially important for calculating complex optimization problems.
引文
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[2] STEWART D A,LEISER D B.Lightweight TUFROC TPS for hypersonic vehicles[C]//14th AIAA/AHI Space Planes and Hypersonic Systems and Technologies Conference.Canberra,2006.
[3]徐千军,余寿文.梯度功能涂层的剥落现象分析与梯度分布的优化[J].复合材料学报,1998,15(4):113-118.XU Qianjun,YU Shouwen.Spalling analyses of functional graded film/substrate structure and the optimization for the gradient distribution[J].Acta Materiae Compositae Sinica,1998,15(4):113-118(in Chinese).
[4] MESSE C,KLICHE D,WALLMERSPERGER T,et al.Modeling and simulation of heat transfer on functionally graded materials for hot structures in scramjet engines[C]//10th AIAA/ASME Joint Thermophysics and Heat Transfer Conference.Chicago,2010.
[5] JHA D K,KANT T,SINGH R K.A critical review of recent research on functionally graded plates[J].Composite Structures,2013,96:833-849.
[6] OOTAO Y,TANIGAWA Y,ISHIMARU O.Optimization of material composition of functionally graded plate for thermal stress relaxation using agenetic algorithm[J].Journal of Thermal Stresses,2000,23:257-271.
[7] CHO J R,HA D Y.Volume fraction optimization for minimizing thermal stress in Ni-Al2O3functionally graded materials[J].Materials Science and Engineering A,2002,334:147-155.
[8] JOSHI S C,NG H W.Optimizing functionally graded nickelzirconia coating profiles for thermal stress relaxation[J].Simulation Modelling Practice and Theory,2011,19(1):586-598.
[9] LIEU Q X,LEE J.Modeling and optimization of functionally graded plates under thermomechanical load using isogeometric analysis and adaptive hybrid evolutionary firefly algorithm[J].Composite Structures,2017,179:89-106.
[10] HUANG J,FADEL G M,BLOUIN V Y,et al.Bi-objective optimization design of functionally gradient materials[J].Materials&Design,2002,23(7):657-666.
[11] VEL S S,PELLETIER J L.Multi-objective optimization of functionally graded thick shells for thermal loading[J].Composite Structures,2007,81(3):386-400.
[12] CORREIA V M F,MADEIRA J F A,ARAúJO A L,et al.Multiobjective optimization of ceramic-metal functionally graded plates using a higher order model[J].Composite Structures,2018,183:146-160.
[13] YAO W,CHEN X,LUO W,et al.Review of uncertaintybased multidisciplinary design optimization methods for aerospace vehicles[J].Progress in Aerospace Sciences,2011,47(6):450-479.
[14] NOH Y J,KANG Y J,YOUN S J,et al.Reliability-based design optimization of volume fraction distribution in functionally graded composites[J].Computational Materials Science,2013,69:435-442.
[15] HAMZEHKOLAEI N S,MIRI M,RASHKI M.Reliabilitybased design optimization of rotating FGM cylindrical shells with temperature-dependent probabilistic frequency constraints[J].Aerospace Science and Technology,2017,68:223-239.
[16] REITER T,DVORAK G J.Micromechanical models for graded composite materials:II—Thermomechanical loading[J].Journal of the Mechanics and Physics of Solids,1998,46(9):1655-1673.
[17] SANTARE M H,LAMBROS J.Use of graded finite elements to model the behavior of nonhomogeneous materials[J].Journal of Applied Mechanics,2000,67(4):819-822.
[18] KIM J H,PAULINO G H.Isoparametric graded finite elements for nonhomogeneous isotropic and orthotropic materials[J].Journal of Applied Mechanics,2002,69(4):502-514.
[19] NELDER J A,MEAD R.The downhill simplex method[J].Computer Journal,1965,7:308-313.
[20] WATANABE S,HIROYASU T,MIKI M.NCGA:Neighborhood cultivation genetic algorithm for multi-objective optimization problems[C]//4th Asia-Pacific Conference on Simulated Evolution and Learning.2002.
[21] SALIBY E.Descriptive sampling:A better approach to monte carlo simulation[J].Journal of the Operational Research Society,1990,41(12):1133-1142.
[22]栾钰琨.基于电磁屏蔽的机器人驱动轮设计及优化研究[D].哈尔滨:哈尔滨工程大学,2012.LUAN Yukun.The research of design and optimization for propulsive wheel of mobile robot based on electromagnetic shielding[D].Harbin:Harbin Engineering University,2012(in Chinese).
[23] LASDON L S,WAREN A D,JAIN A,et al.Design and testing of a generalized reduced gradient code for nonlinear programming[J].Acm Transactions on Mathematical Software,1978,4(1):34-50.