Inverse Design of Energy‐Absorbing Metamaterials by Topology Optimization

Compared with the forward design method through the control of geometric parameters and material types, the inverse design method based on the target stress‐strain curve is helpful for the discovery of new structures. This study proposes an optimization strategy for mechanical metamaterials based on a genetic algorithm and establishes a topology optimization method for energy‐absorbing structures with the desired stress‐strain curves. A series of structural mutation algorithms and design‐domain‐independent mesh generation method are developed to improve the efficiency of finite element analysis and optimization iteration. The algorithm realizes the design of ideal energy‐absorbing structures, which are verified by additive manufacturing and experimental characterization. The error between the stress‐strain curve of the designed structure and the target curve is less than 5%, and the densification strain reaches 0.6. Furthermore, special attention is paid to passive pedestrian protection and occupant protection, and a reasonable solution is given through the design of a multiplatform energy‐absorbing structure. The proposed topology optimization framework provides a new solution path for the elastic‐plastic large deformation problem that is unable to be resolved by using classical gradient algorithms or genetic algorithms, and simplifies the design process of energy‐absorbing mechanical metamaterials.

[1]  Zeang Zhao,et al.  A Deep Learning Approach for Reverse Design of Gradient Mechanical Metamaterials , 2022, International Journal of Mechanical Sciences.

[2]  Ke Liu,et al.  Growth rules for irregular architected materials with programmable properties , 2022, Science.

[3]  Bo Li,et al.  Solid Stress-Distribution-Oriented Design and Topology Optimization of 3D-Printed Heterogeneous Lattice Structures with Light Weight and High Specific Rigidity , 2022, Polymers.

[4]  F. V. Senhora,et al.  Optimally‐Tailored Spinodal Architected Materials for Multiscale Design and Manufacturing , 2022, Advanced materials.

[5]  Lihua Jin,et al.  Harnessing Friction in Intertwined Structures for High‐Capacity Reusable Energy‐Absorbing Architected Materials , 2022, Advanced science.

[6]  Yan Chen,et al.  Energy absorption of sandwich structures with a kirigami-inspired pyramid foldcore under quasi-static compression and shear , 2021 .

[7]  Bin Xu,et al.  Topology optimization of material nonlinear continuum structures under stress constraints , 2021 .

[8]  Yuesheng Wang,et al.  Customized broadband pentamode metamaterials by topology optimization , 2021, Journal of the Mechanics and Physics of Solids.

[9]  Haiyang Yang,et al.  Crashworthiness of circular fiber reinforced plastic tubes filled with composite skeletons/aluminum foam under drop-weight impact loading , 2021 .

[10]  Ole Sigmund,et al.  Design of composite structures with programmable elastic responses under finite deformations , 2021 .

[11]  Zhaocheng Liu,et al.  Tackling Photonic Inverse Design with Machine Learning , 2021, Advanced science.

[12]  Xi-Qiao Feng,et al.  Topology optimization method for the design of bioinspired self-similar hierarchical microstructures , 2020 .

[13]  Adeildo S. Ramos,et al.  Topology optimization considering the Drucker–Prager criterion with a surrogate nonlinear elastic constitutive model , 2020, Structural and Multidisciplinary Optimization.

[14]  P. Zavattieri,et al.  Publisher Correction: Toughening mechanisms of the elytra of the diabolical ironclad beetle , 2020, Nature.

[15]  O. Sigmund,et al.  Topology optimization and 3D printing of large deformation compliant mechanisms for straining biological tissues , 2020, Structural and Multidisciplinary Optimization.

[16]  G. Lu,et al.  A review of recent research on bio-inspired structures and materials for energy absorption applications , 2020 .

[17]  Stephen P. Lynch,et al.  Genetic algorithm based topology optimization of heat exchanger fins used in aerospace applications , 2019, International Journal of Heat and Mass Transfer.

[18]  O. Sigmund,et al.  De-homogenization of optimal multi-scale 3D topologies , 2019, Computer Methods in Applied Mechanics and Engineering.

[19]  Zhan Kang,et al.  Topology optimization for concurrent design of layer-wise graded lattice materials and structures , 2019, International Journal of Engineering Science.

[20]  Yang Yu,et al.  Biomimetic architected materials with improved dynamic performance , 2019, Journal of the Mechanics and Physics of Solids.

[21]  Wentao He,et al.  Effects of geometric configurations of corrugated cores on the local impact and planar compression of sandwich panels , 2018, Composites Part B: Engineering.

[22]  Anders Clausen,et al.  Minimum Compliance Topology Optimization of Shell-Infill Composites for Additive Manufacturing , 2017 .

[23]  Z. Luo,et al.  Level-set topology optimization for mechanical metamaterials under hybrid uncertainties , 2017 .

[24]  P. Breitkopf,et al.  Evolutionary topology optimization of elastoplastic structures , 2017 .

[25]  R. Boichot,et al.  A genetic algorithm for topology optimization of area-to-point heat conduction problem , 2016 .

[26]  Jakob S. Jensen,et al.  Topology Optimized Architectures with Programmable Poisson's Ratio over Large Deformations , 2015, Advanced materials.

[27]  Tomohiro Tachi,et al.  Origami tubes assembled into stiff, yet reconfigurable structures and metamaterials , 2015, Proceedings of the National Academy of Sciences.

[28]  J. Kato,et al.  Analytical sensitivity in topology optimization for elastoplastic composites , 2015 .

[29]  Jakob S. Jensen,et al.  Design of materials with prescribed nonlinear properties , 2014 .

[30]  Jakob S. Jensen,et al.  Interpolation scheme for fictitious domain techniques and topology optimization of finite strain elastic problems , 2014 .

[31]  Leon Wenliang Zhong,et al.  Topology optimization based on moving deformable components: A new computational framework , 2014, ArXiv.

[32]  Guoxing Lu,et al.  Quasi-static axial compression of thin-walled tubes with different cross-sectional shapes , 2013 .

[33]  Bin Xu,et al.  Integrated optimization of structural topology and control for piezoelectric smart plate based on genetic algorithm , 2013 .

[34]  Ugo Galvanetto,et al.  Shock absorption performance of a motorbike helmet with honeycomb reinforced liner , 2011 .

[35]  R. Singer,et al.  Design of Auxetic Structures via Mathematical Optimization , 2011, Advanced materials.

[36]  L. S. Ong,et al.  Dynamic indentation and penetration of aluminium foams , 2008 .

[37]  Jiesheng Jiang,et al.  Integrated optimization of structural topology and control for piezoelectric smart trusses using genetic algorithm , 2007 .

[38]  F. Barthelat,et al.  On the mechanics of mother-of-pearl: a key feature in the material hierarchical structure , 2007 .

[39]  Stelios Kyriakides,et al.  Plastic buckling of circular tubes under axial compression—part I: Experiments , 2006 .

[40]  K. Tai,et al.  Structural topology design optimization using Genetic Algorithms with a bit-array representation , 2005 .

[41]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[42]  Ole Sigmund,et al.  A 99 line topology optimization code written in Matlab , 2001 .

[43]  Anders Clausen,et al.  Efficient topology optimization in MATLAB using 88 lines of code , 2011 .

[44]  S. M. Sapuan,et al.  Conceptual design of a polymer composite automotive bumper energy absorber , 2008 .

[45]  S. Y. Wang,et al.  An extended level set method for shape and topology optimization , 2007, J. Comput. Phys..

[46]  M. Y. Wang,et al.  An enhanced genetic algorithm for structural topology optimization , 2006 .