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1. Discovery of Cellular Unit Cells With High Natural Frequency and Energy Absorption Capabilities by an Inverse Machine Learning Framework

   https://doi.org/10.3389/fmech.2021.779098  

   Challapalli, Adithya ; Konlan, John ; Patel, Dhrumil ; Li, Guoqiang ( November 2021 , Frontiers in Mechanical Engineering)

   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 enhancedmore »energy absorption capability.« less
2. 4D Printing of Recyclable Lightweight Architectures Using High Recovery Stress Shape Memory Polymer

   https://doi.org/10.1038/s41598-019-44110-9  

   Li, Ang ; Challapalli, Adithya ; Li, Guoqiang ( May 2019 , Scientific Reports)

   High-performance lightweight architectures, such as metallic microlattices with excellent mechanical properties have been 3D printed, but they do not possess shape memory effect (SME), limiting their usages for advanced engineering structures, such as serving as a core in multifunctional lightweight sandwich structures. 3D printable self-healing shape memory polymer (SMP) microlattices could be a solution. However, existing 3D printable thermoset SMPs are limited to either low strength, poor stress memory, or non-recyclability. To address this issue, a new thermoset polymer, integrated with high strength, high recovery stress, perfect shape recovery, good recyclability, and 3D printability using direct light printing, has been developed in this study. Lightweight microlattices with various unit cells and length scales were printed and tested. The results show that the cubic microlattice has mechanical strength comparable to or even greater than that of metallic microlattices, good SME, decent recovery stress, and recyclability, making it the first multifunctional lightweight architecture (MLA) for potential multifunctional lightweight load carrying structural applications.
3. 3D printable biomimetic rod with superior buckling resistance designed by machine learning

   https://doi.org/10.1038/s41598-020-77935-w  

   Challapalli, Adithya ; Li, Guoqiang ( November 2020 , Scientific Reports)

   Our mother nature has been providing human beings with numerous resources to inspire from, in building a finer life. Particularly in structural design, plenteous notions are being drawn from nature in enhancing the structural capacity as well as the appearance of the structures. Here plant stems, roots and various other structures available in nature that exhibit better buckling resistance are mimicked and modeled by finite element analysis to create a training database. The finite element analysis is validated by uniaxial compression to buckling of 3D printed biomimetic rods using a polymeric ink. After feature identification, forward design and data filtering are conducted by machine learning to optimize the biomimetic rods. The results show that the machine learning designed rods have 150% better buckling resistance than all the rods in the training database, i.e., better than the nature’s counterparts. It is expected that this study opens up a new opportunity to design engineering rods or columns with superior buckling resistance such as in bridges, buildings, and truss structures.
4. Performance Evaluation of Sandwich Structures Printed by Vat Photopolymerization

   https://doi.org/10.3390/polym14081513  

   Nath, Shukantu Dev ; Nilufar, Sabrina ( April 2022 , Polymers)

   Additive manufacturing such as vat photopolymerization allows to fabricate intricate geometric structures than conventional manufacturing techniques. However, the manufacturing of lightweight sandwich structures with integrated core and facesheet is rarely fabricated using this process. In this study, photoactivatable liquid resin was used to fabricate sandwich structures with various intricate core topologies including the honeycomb, re-entrant honeycomb, diamond, and square by a vat photopolymerization technique. Uniaxial compression tests were performed to investigate the compressive modulus and strength of these lightweight structures. Sandwich cores with the diamond structure exhibited superior compressive and weight-saving properties whereas the re-entrant structures showed high energy absorption capacity. The fractured regions of the cellular cores were visualized by scanning electron microscopy. Elastoplastic finite element analyses showed the stress distribution of the sandwich structures under compressive loading, which are found to be in good agreement with the experimental results. Dynamic mechanical analysis was performed to compare the behavior of these structures under varying temperatures. All the sandwich structures exhibited more stable thermomechanical properties than the solid materials at elevated temperatures. The findings of this study offer insights into the superior structural and thermal properties of sandwich structures printed by a vat photopolymerization technique, which can benefit a widemore »range of engineering applications.« less
5. Computational Synthesis of Large-Scale Three-dimensional Heterogeneous Lattice Structures

   https://doi.org/doi.org/10.1016/j.ast.2021.107258  

   Zhichao Wang Ali Y.Tamijani ( January 2022 , Aerospace science and technology)

   J.A. Ekaterinaris (Ed.)

   This paper describes a methodology for designing the material distribution and orientation of three-dimensional non-uniform (heterogeneous) lattice structures. Recent advances in additive manufacturing enable fabrication across multiple length scales. Homogenization-based design optimization and the subsequent projection of the optimized design facilitate the synthesis of large-scale microstructures that form lightweight bionic designs. The main aspects of this research are (a) the construction, homogenization-based optimization, and projection of two types of lattices with different degrees of anisotropy and (b) the parallelization of the analysis, optimization, and projection framework in order to handle large-scale meshes and obtain high-resolution, heterogeneous lattice structures. Cubic and octet-truss lattices were selected to demonstrate the ability of the framework to design different types of lattices. A quadcopter arm and an internal wing structure were designed using the optimization and projection framework, verifying its capability to synthesize heterogeneous lattice structures for complex design domains. The ability to change the complexity of optimized microlattices using the characteristic parameters of the lattice is discussed. The relationship between the lattice anisotropy and the optimized, smoothed orientation is investigated, and the optimized design for each lattice is compared with those obtained using conventional design optimization procedures.