Status and Challenges in Homogenization Methods for Lattice Materials

Lattice structures have shown great potential in that mechanical properties are customizable without changing the material itself. Lattice materials could be light and highly stiff as well. With this flexibility of designing structures without raw material processing, lattice structures have been widely used in various applications such as smart and functional structures in aerospace and computational mechanics. Conventional methodologies for understanding behaviors of lattice materials take numerical approaches such as FEA (finite element analysis) and high-fidelity computational tools including ANSYS and ABAQUS. However, they demand a high computational load in each geometry run. Among many other methodologies, homogenization is another numerical approach but that enables to model behaviors of bulk lattice materials by analyzing either a small portion of them using numerical regression for rapid processing. In this paper, we provide a comprehensive survey of representative homogenization methodologies and their status and challenges in lattice materials with their fundamentals.

Non-zero Yarkovsky acceleration for near-Earth asteroid (99942) Apophis

The leading source of uncertainty to predict the orbital motion of asteroid (99942) Apophis is a non-gravitational acceleration arising from the anisotropic thermal re-emission of absorbed radiation, known as the Yarkovsky effect. Previous attempts to obtain this parameter from astrometry for this object have only yielded marginally small values, without ruling out a pure gravitational interaction. Here we present an independent estimation of the Yarkovsky effect based on optical and radar astrometry which includes observations obtained during 2021. Our numerical approach exploits automatic differentiation techniques. We find a non-zero Yarkovsky parameter, A2 = (−2.899 ± 0.025) × 10−14 au d−2, with induced semi-major axis drift of (−199.0 ± 1.5) m yr−1 for Apophis. Our results provide definite collision probability predictions for the close approaches in 2029, 2036, and 2068.

A Dual-Scale Numerical Model for the Diffusive Behaviour Prediction of Biocomposites Based on Randomly Oriented Fibres

This work aims to present a multi-scale numerical approach based on a 2D finite element model to simulate the diffusive behaviour of biocomposites based on randomly dispersed Diss fibres during ageing in water. So, first of all, the diffusive behaviour of each phase (fibres/matrix) as well as of the biocomposite was determined experimentally. Secondly, the microstructure of the biocomposite was observed by optical microscope and scanning electron microscope (SEM), and then regenerated in a Digimat finite element calculation software thanks to its own fibre generator: "Random fibre placement". Finally, the diffusion problem based on Fick's law was solved on the Abaqus finite element calculation software. The results showed an excellent agreement between the experiment and the numerical model. The numerical model has enabled a better understanding of the diffusive behaviour of water within the biocomposite, in particular the effect of the fibre/matrix interface. In terms of durability, the layered structure of this biocomposite has proven to be effective in protecting the plant fibres from hydrothermal transfer, which preserves the durability of the material.

Numerical Approach in Superconductivity: An Advanced Study

The dependence of the critical temperature $T_c$ of high-temperature superconductors of various families on their composition and structure is proposed. A clear dependence of the critical temperature of high-temperature superconductors (hydrides, Hg- and Y-based cuprates) on the serial number of the constituent elements, their valence and crystal lattice structure has been revealed. For cuprates, it is shown that it is possible to obtain even higher temperatures of superconducting transitions at normal pressure by implanting mercury atoms into the crystal lattice of cuprate.