Investigating infill density and pattern effects in additive manufacturing by characterizing metamaterials along the strain-gradient theory

Aydin, Gokhan; Sarar, B Cagri; Yildizdag, M. Erden; Abali, Bilen Emek

doi:10.1177/10812865221100978

Cited by 26 publications

(5 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The design methods of microstructure may generally be classified as experimental exploration [8][9][10], heuristic design [11,12] and topology optimization [13][14][15][16][17]. The first two methods succeed in design of microstructure under certain conditions, but failed in complex metamaterials with extreme mechanical properties due to large number of uncertain factors leading to a long design cycle.…”

Section: Introductionmentioning

confidence: 99%

ResUNet involved generative adversarial network-based topology optimization for design of 2D microstructure with extreme material properties

Li,

Ye,

Wei

et al. 2024

Mathematics and Mechanics of Solids

View full text Add to dashboard Cite

Topology optimization is one of the most common methods for design of material distribution in mechanical metamaterials, but resulting in expensive computational cost due to iterative simulation of finite element method. In this work, a novel deep learning-based topology optimization method is proposed to design mechanical microstructure efficiently for metamaterials with extreme material properties, such as maximum bulk modulus, maximum shear modulus, or negative Poisson’s ratio. Large numbers of microstructures with various configurations are first simulated by modified solid isotropic material with penalization (SIMP), to construct the microstructure data set. Subsequently, the ResUNet involved generative and adversarial network (ResUNet-GAN) is developed for high-dimensional mapping between optimization parameters and corresponding microstructures to improve the design accuracy of ResUNet. By given optimization parameters, the well-trained ResUNet-GAN is successfully applied to the microstructure design of metamaterials with different optimization objectives under proper configurations. According to the simulation results, the proposed ResUNet-GAN-based topology optimization not only significantly reduces the computational duration for the optimization process, but also improves the structure precise and mechanical performance.

show abstract

Section: Introductionmentioning

confidence: 99%

ResUNet involved generative adversarial network-based topology optimization for design of 2D microstructure with extreme material properties

Li,

Ye,

Wei

et al. 2024

Mathematics and Mechanics of Solids

View full text Add to dashboard Cite

show abstract

“…[68] The prominent advantages of additive manufacturing are the capability to customize periodic microstructural units with programmability for mechanical metamaterials, [50,69] and to improve their plasticity or fatigue response by optimizing local microstructures. [47,70,71] In addition, artificial intelligence (AI)enabled design has been reported for inverse design [72][73][74][75][76][77] and structural optimization [77][78][79][80][81][82] of mechanical metamaterials, which leads to more accurate and effective fabrication, especially at the micro/nanoscale. AI can automate the exploration and design of mechanical metamaterials via machine learning (ML) and data mining, which has dramatically sped up the evolutionary process of traditional materials.…”

Section: Introductionmentioning

confidence: 99%

Advanced Fabrication of Mechanical Metamaterials Based on Micro/Nanoscale Technology

Chen,

Lin,

Salehi

et al. 2023

Adv Eng Mater

View full text Add to dashboard Cite

In recent years, mechanical metamaterials have shown good mechanical properties such as ultra‐lightness, programmable stiffness, and tunable Poisson’s ratio through clever structural design of microstructures. Micro/nanotechnology has been used to ensure mechanical metamaterials’ fabrication quality and performance for use as structural substrates in multifunctional applications. Mechanical metamaterials are intentionally engineered with periodic microstructures in diverse shapes, allowing for the creation of complex structural substrates. However, this sophisticated design poses significant challenges in the fabrication process, particularly at the micro/nanoscale level, where current technology hinders mechanical metamaterials’ performance improvement and function realization. This review explores the fabrication processes of mechanical metamaterials using micro/nanotechnology and showcase recent progress and future trends. Particular attention is given to recent development, challenges, and future trends in advanced fabrication technologies for mechanical metamaterials. This survey aims to explain why mechanical metamaterials have significant benefits and are well‐suited as structural substrates for multifunctional applications, what advanced fabrication technologies at the micro/nanoscale have been introduced to prepare mechanical metamaterials and how to overcome manufacturing technology bottlenecks of mechanical metamaterials in terms of synthesis, materials and design method.This article is protected by copyright. All rights reserved.

show abstract

“…In fact, microrotation in microstructure is usually associated with displacement. Hence, some researchers utilized strain gradient theory to study the metamaterial [39][40][41]. However, the strain gradient theory usually introduces too many material length scale parameters, which makes it difficult to apply in structural analysis.…”

Section: Introductionmentioning

confidence: 99%

A one-dimensional model for mechanical coupling metamaterials using couple stress theory

Guo

et al. 2023

Mathematics and Mechanics of Solids

View full text Add to dashboard Cite

A new model for a one-dimensional (1D) metamaterial model is formulated based on the couple stress theory. Different point groups of crystal will affect the mechanical couplings in the 1D metamaterial model. We find that when the material belongs to D2 point group, an unusual set of equations is decoupled from governing equations: axial force–torsion–warping (FTW) metamaterial model, which describes an unusual mechanical coupling that cannot occur in traditional materials. The deformation behaviors of the current model under a different axial force are analyzed by using the FTW metamaterial model. The numerical results show that the middle part of the current model has maximum torsional deformation when subjected to sine-type axial force. Since the end of the current model is fixed, the current model does not have compressional deformation globally. Moreover, when the current model is subjected to cosine-type axial force, the FTW coupling is successfully achieved. Then, we study a rod-like metamaterial model under an axial end force. The results show that the compressional deformation occurs at the free end, with a counterclockwise torsion. The current work provides guidance for the structural design and theoretical analysis of the rod-like metamaterial when using the couple stress theory.

show abstract

Investigating infill density and pattern effects in additive manufacturing by characterizing metamaterials along the strain-gradient theory

Cited by 26 publications

References 71 publications

ResUNet involved generative adversarial network-based topology optimization for design of 2D microstructure with extreme material properties

ResUNet involved generative adversarial network-based topology optimization for design of 2D microstructure with extreme material properties

Advanced Fabrication of Mechanical Metamaterials Based on Micro/Nanoscale Technology

A one-dimensional model for mechanical coupling metamaterials using couple stress theory

Contact Info

Product

Resources

About