Abstract
Cellular materials have been widely used in load carrying lightweight structures. Although lightweight increases natural frequency, low stiffness of cellular structures reduces natural frequency. Designing structures with higher natural frequency can usually avoid resonance. In addition, because of the less amount of materials used in cellular structures, the energy absorption capability usually decreases such as under impact loading. Therefore, designing cellular structures with higher natural frequency and higher energy absorption capability is highly desired. In this study, machine learning and novel inverse design techniques enable to search a huge space of unexplored structural designs. In this study, machine learning regression and Generative Neural Networks (GANs) were used to form an inverse design framework. Optimal cellular unit cells that surpass the performance of biomimetic structures inspired from honeycomb, plant stems and trabecular bone in terms of natural frequency and impact resistance were discovered using machine learning. The discovered optimal cellular unit cells exhibited 30–100% higher natural frequency and 300% higher energy absorption than those of the biomimetic counterparts. The discovered optimal unit cells were validated through experimental and simulation comparisons. The machine learning framework in this study would help in designing load carrying engineering structures with increased natural frequency and enhanced energy absorption capability.
Highlights
Lightweight structures such as lattice cored sandwich have been widely used in load bearing engineering structures such as fuselage and wing of aircraft, wind turbine blade, ship hull, bridge deck, offshore oil platform, etc
We demonstrated inverse structural design techniques by using machine learning regression and Generative Neural Networks (GANs) to optimize several lightweight lattice unit cell structures with superior load carrying capacity compared to octet lattice unit cell (Challapalli et al, 2021)
The higher natural frequency makes Models 1 to 5 better choice as cellular unit cells. These structures are considered for further experimental and simulation validations to observe their behavior under uniaxial compression, Dynamic Mechanical Analysis (DMA), and impact tests
Summary
Lightweight structures such as lattice cored sandwich have been widely used in load bearing engineering structures such as fuselage and wing of aircraft, wind turbine blade, ship hull, bridge deck, offshore oil platform, etc. One concern with these lightweight structures persists in their resonance to dynamic load and vulnerability to impact load. Increasing the natural frequency to avoid resonance and enhancing energy absorption are viable ways to improve the performance of these lightweight structures To this end, biomimetic design has been a driving force for discovering optimal lattice structures. Natural frequency is optimized by 40% to aid structures subjected to dynamic loading (Huang et al, 2010)
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