[1] BAUER J,HENGSBACH S,TESARI I,et al. High-Strength cellular ceramic composites with 3D microarchitecture[C]//Proceedings of the National Academy of Sciences,2014,111(7):2453-2458. [2] ELNASRI I,PATTOFATTO S,ZHAO H,et al. Shock enhancement of cellular structures under impact loading:Part i experiments[J]. Journal of the Mechanics and Physics of Solids,2007,55(12):2652-2671. [3] GOLOVIN I S,SINNING H R. Damping in some cellular metallic materials[J]. Journal of Alloys and Compounds,2003,355(1-2):2-9. [4] 王向明,苏亚东,吴斌,等. 微桁架点阵结构在飞机结构/功能一体化中的应用[J]. 航空制造技术,2018,61(10):16-25. WANG Xiangming,SU Yadong,WU Bin,et al. Application for additive manufacturing of lattice materials on integrated aircraft structures and functions[J]. Aeronautical Manufacturing Technology,2018,61(10):16-25. [5] DUMAS M,TERRIAULT P,BRAILOVSKI V. Modelling and characterization of a porosity graded lattice structure for additively manufactured biomaterials[J]. Materials & Design,2017,121:383-392. [6] RODRIGUES H,GUEDES J M,BENDSOE M P. Hierarchical optimization of material and structure[J]. Structural and Multidisciplinary Optimization,2002,24:1-10. [7] LIU Ling,YAN Jun,CHENG Gengdong. Optimum structure with homogeneous optimum truss-like material[J]. Computers & Structures,2008,86(13-14):1417-1425. [8] NIU Bin,YAN Jun,CHENG Gengdong. Optimum structure with homogeneous optimum cellular material for maximum fundamental frequency[J]. Structural and Multidisciplinary Optimization,2009,39:115-132. [9] WANG Chuang,GU Xiaojun,ZHU Jihong,et al. Concurrent design of hierarchical structures with three-dimensional parameterized lattice microstructures for additive manufacturing[J]. Structural and Multidisciplinary Optimization,2020,61:869-894. [10] HAN Yafeng,LU Wenfeng. A novel design method for nonuniform lattice structures based on topology optimization[J]. Journal of Mechanical Design,2018,140(9):091403. [11] HU Jingqiao,LI Ming,YANG Xingtong,et al. Cellular structure design based on free material optimization under connectivity control[J]. Computer-Aided Design,2020,127:102854. [12] 阎军,许琦,张起,等. 人工智能在结构拓扑优化领域的现状与未来趋势[J]. 计算力学学报,2021,38(4):412-422. YAN Jun,XU Qi,ZHANG Qi,et al. Current and future trends of artificial intelligence in the field of structure topology optimization[J]. Chinese Journal of Computational Mechanics,2021,38(4):412-422. [13] ZHANG Yan,GAO Liang,XIAO Mi. Maximizing natural frequencies of inhomogeneous cellular structures by kriging-assisted multiscale topology optimization[J]. Computers & Structures,2020,230:106197. [14] QIU Zheng,LI Quhao,LIU Shutian,et al. Clustering-based concurrent topology optimization with macrostructure,components,and materials[J]. Structural and Multidisciplinary Optimization,2021,63(3):1243-1263. [15] WANG Liwei,CHAN Yuchin,AHMED F,et al. Deep generative modeling for mechanistic-based learning and design of metamaterial systems[J]. Computer Methods in Applied Mechanics and Engineering,2020,372:113377. [16] ZHU B,SKOURAS M,CHEN D,et al. Two-scale topology optimization with microstructures[J]. ACM Transactions on Graphics,2017,36(5):1-16. [17] RADFORD A,METZ L,CHINTALA S. Unsupervised representation learning with deep convolutional generative adversarial networks[EB/OL]. (2015-11-19) arXiv preprint arXiv:1511. 06434,2015. https://arxiv.org/abs/1511.06434 [18] GOODFELLOW I,BENGIO Y,COURVILLE A. Deep learning[M]. Cambridge:MIT Press,2017. [19] SVANBERG K. The method of moving asymptotes-a new method for structural optimization[J]. International Journal for Numerical Methods in Engineering,1987,24(2):359-373. [20] LI Xiaolin,YANG Zijiang,BRINSON L C,et al. A deep adversarial learning methodology for designing microstructural material systems[C]//Proceedings of the ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2018,Quebec,Canada,2018. [21] TAN Renkai,ZHANG Nevin,YE Wenjing. A Deep learning-based method for the design of microstructural materials[J]. Structural and Multidisciplinary Optimization,2020,61(4):1417-1438. [22] GOODFELLOW I J,POUGET-ABADIE J,MIRZA M,et al. Generative adversarial nets[R]. 2014,27. [23] WANG Liwei,CHAN Yuchin,LIU Zhao,et al. Data-driven metamaterial design with laplace-beltrami spectrum as "Shape-DNA"[J]. Structural and Multidisciplinary Optimization,2020,61(6):2613-2628. [24] HEUSEL M,RAMSAUER H,UNTERTHINER T,et al. GANs trained by a two time-scale update rule converge to a local nash equilibrium[EB/OL].(2017-06-26) arXiv preprint arXiv:1706. 08500,2017. https://arxiv.org/abs/1706.08500. [25] MIYATO T,KATAOKA T,KOYAMA M,et al. Spectral normalization for generative adversarial networks[EB/OL]. (2018-02-16) arXiv preprint arXiv:1802. 05957,2018. https://arxiv.org/abs/1802.05957. [26] BERGSTRA J,YAMINS D,COX D D. Making a science of model search:hyperparameter optimization in hundreds of dimensions for vision architectures[C]//Proceedings of the 30th International Conference on Machine Learning (ICML 2013),Atlanta,USA,2013,28:115-123. [27] ANDREASSEN E,ANDREASEN C S. How to determine composite material properties using numerical homogenization[J]. Computational Materials Science,2014,83:488-495. [28] SETHIAN J A. A fast marching level set method for monotonically advancing fronts[J]. Proceedings of the National Academy of Sciences of the United States of America,1996,93(4):1591-1595. [29] MORITZ P,NISHIHARA R,WANG S,et al. Ray:A distributed framework for emerging AI applications[EB/OL]. (2017-12-16). arXiv preprint arXiv:1712. 05889,2017. https://arxiv.org/abs/1712.05889. |