The impact responses and failure mechanism of composite gradient reentrant honeycomb structure

Liu, Zhikang; Liu, Jingxi; Liu, Jiayi; Zeng, Wei; Huang, Wei

doi:10.1016/j.tws.2022.110228

Cited by 20 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Exemplary unit cell designs include hexagonal/re-entrant (figure 5(A)) [410,411]), square/cubic (figure 5(B)) [412]), or chiral/antichiral (figure 5(C)) [413][414][415][416][417]. Unit cell design degrees of freedom include; varying rib orientation (figures 5(A) and (B)), length, or thickness-slender ribs are often less stiff, varying rib form (figure 5(B))-Eigenmode example); varying the number of ribs (figures 5(A) and (B)), or adding and combining shapes and features (figure 5(C)).…”

Section: Periodic Structuresmentioning

confidence: 99%

Mechanical metamaterials for sports helmets: structural mechanics, design optimisation, and performance

Haid,

Foster,

Hart

et al. 2023

Smart Mater. Struct.

View full text Add to dashboard Cite

Sports concussions are a public health concern. Improving helmet performance to reduce concussion risk is a key part of the research and development community response. Head impacts with compliant surfaces that cause long duration moderate or high linear and rotational accelerations are associated with a high rate of clinical diagnoses of concussion. As engineered structures with unusual combinations of properties, mechanical metamaterials are being applied to sports helmets, with the goal of improving impact performance and reducing brain injury risk. Replacing established helmet material (i.e., foam) selection with a metamaterials design approach (structuring material to obtain desired properties) allows development of near optimal properties. Objective functions based on up to date understanding of concussion could be applied to topology optimisation regimes, when designing mechanical metamaterials for helmets. Such regimes balance computational efficiency with predictive accuracy, both of which could be improved under high strains and strain rates to allow helmet modifications as knowledge of concussion develops. Researchers could also share mechanical metamaterial data, topologies and computational models in open, homogenised repositories, to improve the efficiency of their development.

show abstract

Section: Periodic Structuresmentioning

confidence: 99%

Mechanical metamaterials for sports helmets: structural mechanics, design optimisation, and performance

Haid,

Foster,

Hart

et al. 2023

Smart Mater. Struct.

View full text Add to dashboard Cite

show abstract

“…They investigated five different types of AH structures including Sshaped, chiral, star-shaped, double arrowhead, and re-entrant types. Yu et al 30 examined the failure analysis of an AH structure under compressive loading. They reported some useful results via the ABAQUS software and compared their results with the experimental ones to confirm the precision of their model.…”

Section: Introductionmentioning

confidence: 99%

Vibration characteristics of a cylindrical sandwich shell with an FG auxetic honeycomb core and nanocomposite face layers subjected to supersonic fluid flow

Amirabadi,

Darakhsh,

Sarafraz

et al. 2024

Noise & Vibration Worldwide

View full text Add to dashboard Cite

In this paper, the flutter analysis is studied for a cylindrical sandwich shell subjected to external supersonic fluid flow. The sandwich shell consists of a re-entrant auxetic honeycomb (AH) core made of functionally graded materials (FGMs) which is covered with two polymeric face layers enriched with either carbon nanotubes (CNTs), graphene nanoplatelets (GNPs), or graphene oxide powders (GOPs). The volume fraction (percentage) of the ceramic phase in the functionally graded auxetic honeycomb (FGAH) core varies from zero at the inner surface to one at the outer one based on either power-law function (P-FGM), exponential function (E-FGM), or sigmoid function (S-FGM). It is assumed that the nanofillers are distributed uniformly inside the face layers. The first-order shear deformation theory (FSDT) and the piston theory are employed to provide the mathematical models of the shell and the aerodynamic pressure, respectively. The governing equations and boundary conditions are derived via Hamilton’s principle. An exact solution is performed in the circumferential direction via harmonic trigonometric functions (sine and cosine) and an approximate solution is performed in the axial direction utilizing the differential quadrature method (DQM). The natural frequencies and corresponding damping ratios are attained through the presented semi-analytical solution and the impacts of several factors on the natural frequencies and the critical aerodynamic pressure of the shell are examined. These factors the type of the FGM, the material index, and inclined angle of the cells in the FGAH core, the thickness of the FGAH core, the type and mass fraction of the nanofillers in the nanocomposite face layers, and boundary conditions.

show abstract

“…The failure behavior of auxetic reentrants is widely studied in the literature. Yu et al (2023) studied the compressive responses and failure behaviors of composite graded auxetic reentrant honeycomb structure, and Liu et al (2023) studied the impact responses and failure mechanisms of composite gradient reentrant honeycomb structure. The dynamic behavior of these structures is also widely studied.…”

Section: Introductionmentioning

confidence: 99%

“…Yu et al. (2023) studied the compressive responses and failure behaviors of composite graded auxetic reentrant honeycomb structure, and Liu et al. (2023) studied the impact responses and failure mechanisms of composite gradient reentrant honeycomb structure.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective design optimization of reentrant auxetic model using Lichtenberg algorithm based on metamodel

Francisco,

Pereira,

Oliveira

et al. 2023

View full text Add to dashboard Cite

PurposeThe present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how each of the design factors impact each of the responses.Design/methodology/approachThe multi-objective optimization of five different responses of an auxetic model was considered: mass, critical buckling load under compression effort, natural frequency, Poisson's ratio and failure load. The response surface methodology was applied, and a new meta-heuristic of optimization called the multi-objective Lichtenberg algorithm was applied to find the optimized configuration of the model. It was possible to increase the failure load by 26.75% in compression performance optimization. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. This paper addresses something new in the scientific world to date when evaluating in a multi-objective optimization problem, the compression and modal performance of an auxetic reentrant model.FindingsIt was possible to find multi-objective optimized structures. It was possible to increase the critical buckling load by 42.82%, and the failure load in compression performance by 26.75%. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%, and decrease the mass by 15.97%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, increase the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively.Originality/valueThere is no work in the literature to date that performed the optimization of 5 responses simultaneously of a reentrant hexagonal cell auxetic structure. This paper also presents an unprecedented statistical analysis in the literature that verifies how the design factors impact each of the responses.

show abstract

The impact responses and failure mechanism of composite gradient reentrant honeycomb structure

Cited by 20 publications

References 30 publications

Mechanical metamaterials for sports helmets: structural mechanics, design optimisation, and performance

Mechanical metamaterials for sports helmets: structural mechanics, design optimisation, and performance

Vibration characteristics of a cylindrical sandwich shell with an FG auxetic honeycomb core and nanocomposite face layers subjected to supersonic fluid flow

Multi-objective design optimization of reentrant auxetic model using Lichtenberg algorithm based on metamodel

Contact Info

Product

Resources

About