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The purpose of this paper is the development of a multiscale model which simulates the effect of the dispersion, the waviness, the interphase geometry as well as the agglomerations of multi-walled carbon nanotubes (MWCNTs) on the Young’s modulus of a polymer filled with 0.4 Vol.% MWCNTs.

For the determination of the homogenized elastic properties of the hybrid material representative unit cells (RUCs) have been used. The predicted homogenized elastic properties were used for the prediction of the Young’s modulus of the filled material by simulating a finite element (FE) model of a tensile specimen. Moreover, the model has been validated by comparing the predicted values of the numerical analysis with experimental tensile results.

As the MWCNT agglomerates increase, the results showed a remarkable decrease of the Young’s modulus regarding the polymer filled with aligned MWCNTs while only slight differences on the Young’s modulus have been found in the case of randomly oriented MWCNTs. This might be attributed to the low concentration of the MWCNTs (0.4 Vol.%) into the polymer. For low MWCNTs concentrations, the interphase seems to have negligible effect on the Young’s modulus. Furthermore, as the MWCNTs waviness increases, a remarkable decrease of the Young’s modulus of the polymer filled with aligned MWCNTs is observed. In the case that MWCNTs are randomly dispersed into the polymer, both numerical and experimental results have been found to be consistent regarding the Young’s modulus.

The methodology used can be adopted by any system containing nanofillers.

Although several studies on the effect of the MWCNTs distribution on the Young’s modulus have been conducted, limited results exist by using a more realistic RUC including a periodic geometry of more than 20 MWCNTs with random orientation and a more realistic waviness of MWCNTs with aspect ratio exceeding 150.

In pure material design, the previous research has indicated that lots of optimization factors such as used algorithm and parameters have influence on the optimal solution. In other words, there are multiple local minima for the topological design of materials for extreme properties. Therefore, the purpose of this study is to attempt different or more concise algorithms to find much wider possible solutions to material design. As for the design of material microstructures for macro-structural performance, the previous studies test algorithms on 2D porous or composite materials only, it should be demonstrated for 3D problems to reveal numerical and computational performance of the used algorithm.

The presented paper is an attempt to use the strain energy method and the bi-directional evolutionary structural optimization (BESO) algorithm to tailor material microstructures so as to find the optimal topology with the selected objective functions. The adoption of the strain energy-based approach instead of the homogenization method significantly simplifies the numerical implementation. The BESO approach is well suited to the optimal design of porous materials, and the generated topology structures are described clearly which makes manufacturing easy.

As a result, the presented method shows high stability during the optimization process and requires little iterations for convergence. A number of interesting and valid material microstructures are obtained which verify the effectiveness of the proposed optimization algorithm. The numerical examples adequately consider effects of initial guesses of the representative unit cell (RUC) and of the volume constraints of solid materials on the final design. The presented paper also reveals that the optimized microstructure obtained from pure material design is not the optimal solution any more when considering the specific macro-structural performance. The optimal result depends on various effects such as the initial guess of RUC and the size dimension of the macrostructure itself.

This paper presents a new topology optimization method for the optimal design of 2D and 3D porous materials for extreme elastic properties and macro-structural performance. Unlike previous studies, the presented paper tests the proposed optimization algorithm for not only 2D porous material design but also 3D topology optimization to reveal numerical and computational performance of the used algorithm. In addition, some new and interesting material microstructural topologies have been obtained to provide wider possible solutions to the material design.

The purpose of this paper is to develop a multi-scale modeling approach for simulating the tensile behavior of corroded aluminum alloy 2024 T3.

The approach combines two FE models: a model of a three-dimensional representative unit cell representing a pit and a model of the tensile specimen. The models lie at the micro- and macro-scales, respectively. The local homogenized mechanical behavior of the corroded material is simulated for different pit configurations. Then, the behavior of the pits is introduced into different areas (elements) of the tensile specimen and final analyses are performed to simulate the mechanical behavior of the corroded material. The approach has been applied to six different exposure periods of the exfoliation corrosion test.

The numerical results show that the presence of pits and exfoliated areas reduces the yield strength of the material. The comparison of predicted elongation to fracture with the experimental of each exposure period value allows for the indirect assessment of the effect of hydrogen embrittlement.

Since the characteristics of corrosion damage evolution with exposure time are constant for the specific material, the model could be applied for the simulation of the mechanical behavior of any corroded structural part (e.g. a mechanically fastened panel) made from the aluminum 2024 T3 alloy.

The optimal material microstructures in pure material design are no longer efficient or optimal when accounting macroscopic structure performance with specific boundary conditions. Therefore, it is important to provide a novel multiscale topology optimization framework to tailor the topology of structure and the material to achieve specific applications. In comparison with porous materials, composites consisting of two or more phase materials are more attractive and advantageous from the perspective of engineering application. This paper aims to provide a novel concurrent topological design of structures and microscopic materials for thermal conductivity involving multi-material topology optimization (material distribution) at the lower scale.

In this work, the effective thermal conductivity properties of microscopic three or more phase materials are obtained via homogenization theory, which serves as a bridge of the macrostructure and the periodic material microstructures. The optimization problem, including the topological design of macrostructures and inverse homogenization of microscopic materials, are solved by bi-directional evolutionary structure optimization method.

As a result, the presented framework shows high stability during the optimization process and requires little iterations for convergence. A number of interesting and valid macrostructures and material microstructures are obtained in terms of optimal thermal conductive path, which verify the effectiveness of the proposed mutliscale topology optimization method. Numerical examples adequately consider effects of initial guesses of the representative unit cell and of the volume constraints of adopted base materials at the microscopic scale on the final design. The resultant structures at both the scales with clear and distinctive boundary between different phases, making the manufacturing straightforward.

This paper presents a novel multiscale concurrent topology optimization method for structures and the underlying multi-phase materials for thermal conductivity. The authors have carried out the concurrent multi-phase topology optimization for both 2D and 3D cases, which makes this work distinguished from existing references. In addition, some interesting and efficient multi-phase material microstructures and macrostructures have been obtained in terms of optimal thermal conductive path.

Blast‐induced traumatic brain injury (TBI) is a signature injury of the current military conflicts. Among the different types of TBI, diffuse axonal injury (DAI) plays an important role since it can lead to devastating effects in the inflicted military personnel. To better understand the potential causes associated with DAI, this paper aims to investigate a transient non‐linear dynamics finite element simulation of the response of the brain white matter to shock loading.

Brain white matter is considered to be a heterogeneous material consisting of fiber‐like axons and a structure‐less extracellular matrix (ECM). The brain white matter microstructure in the investigated corpus callosum region of the brain is idealized using a regular hexagonal arrangement of aligned equal‐size axons. Deviatoric stress response of the axon and the ECM is modeled using a linear isotropic viscoelastic formulation while the hydrostatic stress response is modeled using a shock‐type equation of state. To account for the stochastic character of the brain white matter microstructure and shock loading, a parametric study is carried out involving a factorial variation of the key microstructural and waveform parameters.

The results obtained show that the extent of axon undulations and the strength of axon/ECM bonding profoundly affect the spatial distribution and magnitude of the axonal axial normal and shear stresses (the stresses which can cause diffuse axonal injury).

The present approach enables a more accurate determination of the mechanical behavior of brain white matter when subjected to a shock.

The purpose of this study is the investigation of self-healing materials containing encapsulated healing agents embedded in a polymer matrix with dispersed catalysts. In recent years, the high performance and design flexibility of composite materials have led to their widespread use in the aeronautics, space, automotive and marine fields. Simultaneously, as the need for advanced material properties has increased, many studies have been conducted on multifunctional materials, focusing on different fields of their desired capabilities.

A multiscale model was developed to simulate the effect of microcapsules on the mechanical behavior of the polymer matrix. Furthermore, the effects of microcapsule diameter and microcapsule concentration on the mechanical behavior of the composite were studied. Digimat and Ansys software were used to simulate the self-healing composites.

There is a trade-off between the efficiency of the microcapsules and the degradation of the properties of the composite material.

The generated model simulated an encapsulated healing agent in a polymeric matrix.

Within the context of 2D square lattices, searching for the existence of band gaps assumes a great interest owing to many possible fields of application: from energy absorption devices to noise and vibration controllers, as well as advanced strategies for the seismic isolation.

The underlying microstructure may influence the mechanical response of 2D square lattices according to a complex interplay between different factors. A first one is related to the so-called “size-effect”. A second one relates, instead, to the mass density distribution.

It has been observed that lumped masses may induce additional band gaps to appear and may magnify their width. Finally, an additional factor deals with the inner damping characteristics of the constituent materials, which usually are polymer-based.

This study focuses on the first factor from a specific perspective: to investigate the influence of the size effect on the existence and properties of frequency band gaps.

Regularities imposed by an external wall on the random distribution of particles in a packed bed lead to anisotropic wall effects of the bed. The resulting deviations of near—wall porosity from the average bed—porosity markedly affect the average velocity profile, not only near the wall but also some distance into the bed itself. The effect of wall channelling due to such variations in porosity near external boundaries is predicted by means of two different numerical solution methods for a unified model for granular porous media. The results are shown to compare favourably to experimental and numerical results reported in the literature.

The “chiralisation” of Euclidean polygonal tessellations is a novel, recent method which has been used to design new auxetic metamaterials with complex topologies and improved geometric versatility over traditional chiral honeycombs. This paper aims to design and manufacture chiral honeycombs representative of four distinct classes of 2D Euclidean tessellations with hexagonal rotational symmetry using fused-deposition additive manufacturing and experimentally analysed the mechanical properties and failure modes of these metamaterials.

Finite Element simulations were also used to study the high-strain compressive performance of these systems under both periodic boundary conditions and realistic, finite conditions. Experimental uniaxial compressive loading tests were applied to additively manufactured prototypes and digital image correlation was used to measure the Poisson’s ratio and analyse the deformation behaviour of these systems.

The results obtained demonstrate that these systems have the ability to exhibit a wide range of Poisson’s ratios (positive, quasi-zero and negative values) and stiffnesses as well as unusual failure modes characterised by a sequential layer-by-layer collapse of specific, non-adjacent ligaments. These findings provide useful insights on the mechanical properties and deformation behaviours of this new class of metamaterials and indicate that these chiral honeycombs could potentially possess anomalous characteristics which are not commonly found in traditional chiral metamaterials based on regular monohedral tilings.

To the best of the authors’ knowledge, the authors have analysed for the first time the high strain behaviour and failure modes of chiral metamaterials based on Euclidean multi-polygonal tessellations.

Bureaucratic theory, systems theory and a review of research on innovation, provide a conceptual framework on which seven predictions are posited. The predictions relate to the innovative behaviour of a bureaucratic education system throughout a period of twenty years. An innovation is defined as a new structure or process that appeared for the first time in the education system. One hundred and sixty‐four innovations are identified and classified as task‐oriented, personnel‐oriented and organization‐oriented. When tested the predictions reveal inter alia, (1) an upward trend in the annual frequencies of innovation through the period 1946 to 1965, (2) educational policies of state governments appear to be distinguished by different rates of innovation, (3) the frequency of innovation tends to increase following the succession to office of a new Director‐General and (4) innovation tends to occur least in the central office system.