Continuum and Molecular Dynamics Studies of the Hydrodynamics of Colloids Straddling a Fluid Interface

Colloid-sized particles (10 nm–10 μm in characteristic size) adsorb onto fluid interfaces, where they minimize their interfacial energy by straddling the surface, immersing themselves partly in each phase bounding the interface. The energy minimum achieved by relocation to the surface can be orders of magnitude greater than the thermal energy, effectively trapping the particles into monolayers, allowing them freedom only to translate and rotate along the surface. Particles adsorbed at interfaces are models for the understanding of the dynamics and assembly of particles in two dimensions and have broad technological applications, importantly in foam and emulsion science and in the bottom-up fabrication of new materials based on their monolayer assemblies. In this review, the hydrodynamics of the colloid motion along the surface is examined from both continuum and molecular dynamics frameworks. The interfacial energies of adsorbed particles is discussed first, followed by the hydrodynamics, starting with isolated particles followed by pairwise and multiple particle interactions. The effect of particle shape is emphasized, and the role played by the immersion depth and the surface rheology is discussed; experiments illustrating the applicability of the hydrodynamic studies are also examined. Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 54 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A Cylindrical Crash Absorber with Discontinuous Protrusions and Its Manufacture Using a Successive Partial Rubber-Bulging Method

In an effort to improve impact energy-absorption characteristics, this study introduces a cylindrical crash absorber (CAP) with discontinuous protrusions and a continuous local-expansion plastic-forming method for its manufacture. The mechanical properties of the cylindrical energy-absorption structure were modified by installing multiple particle protrusions on the cylinder sidewall to reduce the initial pickup load and improve the impact energy-absorption performance. To facilitate manufacture of the proposed CAP, a cylindrical rubber piece was placed into a cylindrical tube and pressure was applied to the rubber from both ends of the tube. The CAP was formed by the bulging force of the rubber. The formability was verified by developing a successive local bulge-forming experimental device and comparing the manufactured CAP with the results of numerical simulations. Testing of quasi-static collapse conducted on a CAP manufactured using this device verified the effectiveness of the proposed CAP design and its plastic-forming method. It was determined that this design reduced the initial peak load, and the crash absorber could maintain stability over a long, continuous distance during crushing deformation.

A Damage Detection Method Using Neural Network Optimized by Multiple Particle Collision Algorithm

A critical task of structural health monitoring is damage detection and localization. Lamb wave propagation methods have been successfully applied for damage identification in plate-like structures. However, Lamb wave processing is still a challenging task due to its multimodal and dispersive characteristics. To address this issue, data-driven machine learning approaches as artificial neural network (ANN) have been proposed. However, the effectiveness of ANN can be improved based on its architecture and the learning strategy employed to train it. The present paper proposes a Multiple Particle Collision Algorithm (MPCA) to design an optimum ANN architecture to detect and locate damages in plate-like structures. For the first time in the literature, the MPCA is applied to find damages in plate-like structures. The present work uses one piezoelectric transducer to generate Lamb wave signals on an aluminum plate structure and a linear array of four transducers to capture the scattered signals. The continuous wavelet transform (CWT) processes the captured signals to estimate the time-of-flight (ToF) that is the ANN inputs. The ANN output is the damage spatial coordinates. In addition to MPCA optimization, this paper uses a quantitative entropy-based criterion to find the best mother wavelet and the scale values. The presented experimental results show that MPCA is capable of finding a simple ANN architecture with good generalization performance in the proposed damage localization application. The proposed method is compared with the 1-dimensional convolutional neural network (1D-CNN). A discussion about the advantages and limitations of the proposed method is presented.

How to Modify LAMMPS: From the Prospective of a Particle Method Researcher

LAMMPS is a powerful simulator originally developed for molecular dynamics that, today, also accounts for other particle-based algorithms such as DEM, SPH, or Peridynamics. The versatility of this software is further enhanced by the fact that it is open-source and modifiable by users. This property suits particularly well Discrete Multiphysics and hybrid models that combine multiple particle methods in the same simulation. Modifying LAMMPS can be challenging for researchers with little coding experience. The available material explaining how to modify LAMMPS is either too basic or too advanced for the average researcher. In this work, we provide several examples, with increasing level of complexity, suitable for researchers and practitioners in physics and engineering, who are familiar with coding without been experts. For each feature, step by step instructions for implementing them in LAMMPS are shown to allow researchers to easily follow the procedure and compile a new version of the code. The aim is to fill a gap in the literature with particular reference to the scientific community that uses particle methods for (discrete) multiphysics.