Research on Simulation System of Rubber Particle Mat Based on Web Technology

The current design of rubber granular floor mats is limited to a single fixed plane sample drawing, and it consumes a lot of time, manpower and material resources in obtaining customer design requirements. In response to this situation, the use of Web development technology to realize the free combination of particles in proportion, generate simulation application scenarios, provide interface operations, and finally complete the order process. By constructing a particle probability distribution model, establishing a particle position coordinate matrix, and developing a particle mat simulation system, based on the sample quality of the sampled data, it is compared with the real artificial mechanical product. Finally, by mixing and matching 9 different color values according to the industrial production ratio, randomly combining 10 groups and comparing with the real products of the same color ratio, quantifying the color difference, contrast, and particle position offset to obtain the production simulation floor mat sample and the actual product. The finished product is quite close. The system generates simulated particle mat maps and real sample maps with a high degree of simulation, and provides an interface that allows users to directly match the particle combination program that suits their needs, saving labor cycles and improving work efficiency.

USING DATA SCIENCE TO EVALUATE NANO-REINFORCED EPOXY SURFACES

Toughened composites reinforced with nanofillers show improved mechanical performance such as increased abrasion resistance, fracture toughness, and fracture energy. The degree of these improvements is influenced by the degree of dispersion of the nanofillers which can be analyzed using force microscopy (AFM), a technique that allows for mapping the local height and elastic modulus of a surface. However, current AFM apparatuses can only measure a narrow range of moduli according to the type of tip, which complicates the full-field measurement of moduli in nanocomposites with nanosilica (~72 GPa) embedded in epoxy (0.1 – 5 GPa). Moreover, height mapping can only visualize filler particles exposed at the surface. These limitations make it challenging to determine the 3D location of nanoparticles near the surface of a composite. To overcome these limitations of conventional AFM, we used a combination of data science, micromechanics, and experimental data from AFM to locate the centroidal position of nanosilica (NS) particles relative to the surrounding epoxy surface. Using finite element simulations, a theoretical dataset of modulus values as a function of particle position relative to the epoxy surface was created as a training set. Bayesian optimization determines the “best” particle position that results in minimum error between simulated and experimental modulus contours. The algorithm returns the 3D position of the fully or partially embedded NS particle relative to the epoxy surface. The algorithm has shown the ability to partially produce simulated modulus contours that resemble the experimental modulus contours.

Distribution of random motion at renewal instants in three-dimensional space

In physics, chemistry, and mathematics, the process of Brownian motion is often identified with the Wiener process that has infinitesimal increments. Recently, many models of Brownian motion with finite velocity have been intensively studied. We consider one of such models, namely, a generalization of the Goldstein--Kac process to the three-dimensional case with the Erlang-2 and Maxwell--Boltzmann distributions of velocities alternations. Despite the importance of having a three-dimensional isotropic random model for the motion of Brownian particles, numerous research efforts did not lead to an expression for the probability of the distribution of the particle position, the motion of which is described by the three-dimensional telegraph process. The case where a particle carries out its movement along the directions determined by the vertices of a regular $n+1$-hedron in the $n$-dimensional space was studied in \cite{Samoilenko}, and closed-form results for the distribution of the particle position were obtained. Here, we obtain expressions for the distribution function of the norm of the vector that defines particle's position at renewal instants in semi-Markov cases of the Erlang-2 and Maxwell--Boltzmann distributions and study its properties. By knowing this distribution, we can determine the distribution of particle positions, since the motion of a particle is isotropic, i.e., the direction of its movement is uniformly distributed on the unit sphere in ${\mathbb R}^3$. Our results may be useful in studying the properties of an ideal gas.

Drag on Janus Sphere in a Channel: Effect of Particle Position

Potential use of Janus spheres in novel engineering applications is being explored actively in recent years. Hydrodynamics around Janus spheres is different from that around homogeneous sticky or slippery spheres. Instantaneous motion of a sphere in channel flow is governed by hydrodynamic force experienced by the sphere, which in turn depends on the particle to channel size ratio, its instantaneous position, hydrophobicity of its surface and the particle Reynolds number. We investigate numerically the drag experienced by a Janus sphere located at different off-centre positions in a square channel. Two orientations of Janus sphere consisting of a sticky and a slippery hemisphere with the boundary between them parallel to the channel mid-plane are studied: (1) slippery hemisphere facing the channel centreline and (2) sticky hemisphere facing the channel centreline. The flow field around Janus sphere is found to be steady (for Re ≤ 50 investigated in this work) and asymmetric. Based on the data obtained, a correlation for drag coefficient as a function of particle Reynolds number and dimensionless particle position is also proposed.