Integrating the Capsule-like Smart Aggregate-Based EMI Technique with Deep Learning for Stress Assessment in Concrete.

This study presents a concrete stress monitoring method utilizing 1D CNN deep learning of raw electromechanical impedance (EMI) signals measured with a capsule-like smart aggregate (CSA) sensor. Firstly, the CSA-based EMI measurement technique is presented by depicting a prototype of the CSA sensor and a 2 degrees of freedom (2 DOFs) EMI model for the CSA sensor embedded in a concrete cylinder. Secondly, the 1D CNN deep regression model is designed to adapt raw EMI responses from the CSA sensor for estimating concrete stresses.

Collapse dynamics and deposition morphology of low-viscocohesive granular columns on a rough horizontal surface.

Using the three-dimensional discrete element method, we numerically investigate the collapse dynamics and deposition morphology of low-viscocohesive granular columns on a rough-horizontal plane by systematically varying a broad range of values of the initial column aspect ratio, cohesive stress, and liquid viscosity. The results show that the kinetic energy, half runout time, and runout distance increase with increasing the initial column aspect ratio but decrease with increasing the cohesive and viscous effects of the binding liquid, while the toe angle and deposit height decrease with increasing the aspect ratio and increase with increasing cohesive stress and liquid viscosity. Remarkably, by defining a dimensionless scaling number that incorporates the Bond number and initial column aspect ratio, this allows us to nicely describe the kinetic energy, half runout time, deposition height, runout distance, and toe angle.

Online learning experiences of secondary school students during COVID-19 - Dataset from Vietnam.

This dataset provides an insight into the reality and experiences of online learning as perceived by secondary school students in Vietnam during COVID-related school closures. The dataset addresses four main aspects of online learning, namely (a) students' access to learning devices, (b) their digital skill readiness, (c) their experience with online learning and assessment activities, and (d) their overall evaluation of the effectiveness of online learning. The survey was administered online via Google Form from September to December 2021 with responses received from 5,327 secondary school students in 5 provinces of Vietnam.

Unified penetration depth of low-velocity intruders into granular packings.

Penetration of intruders into granular packings is well described by separately considering the dry or wet case of granular environments in previous experiments and simulations; however, the unified description of such penetration depth in these two granular media remains elusive due to lacking clear explanations about its origins. Based on three-dimensional discrete element method simulations, we introduce a power-law fitting form of the final penetration depth of a spherical intruder with low velocity vertically penetrating into dry and wet granular packings, excellently expressed on a master curve as a power-law function of a dimensionless impact number that is defined as the square root of the ratio between the inertial stress of the intruder and the linear combination of the mean gravitational stress and the cohesive stress exerted on each grain in the packings, as a remarkable extension of the inertial number in dry granular flows. This scaling robustly provides physical insights inherent in the unified description of the material properties of granular packings and the impactor penetration conditions on the final penetration depth in the impact tests, providing evidence of impact properties in different disciplines and applications in science and engineering.

Effects of size polydispersity on segregation of spherical particles in rotating drum.

To get insight into the segregation process of a polydisperse granular materials flow, we numerically investigated the migration process of particles in a rotating drum operating in the rolling regime by means of the discrete element method. Particle migration is analyzed through the variation of the proportion of particles in different zones where the flow property is characterized. The proportion of particles in different zones of the drum shows to increase in the center of the flow radially and axially where a higher concentration of small particles is observed, while its decreases in other zones with a higher concentration of larger particles.

Scaling behavior of the tensile strength of viscocohesive granular aggregates.

We numerically analyze the tensile strength of a single wet agglomerate modeled as a viscocohesive aggregate impacting a flat surface by using the discrete-element simulations. The viscocohesive agglomerate composed of primary spherical particles with the inclusion of the interstitial liquid in the form of the capillary bridges characterized by the cohesive and viscous forces between particles is extracted from a cuboidal sample of granular materials by applying a spherical probe. The tensile strength is measured from the impact test of a wet agglomerate by systematically varying different values of the surface tension of the interstitial liquid, the liquid viscosity, and the impact speed.

Evolution of wet agglomerates inside inertial shear flow of dry granular materials.

We use particle dynamics simulations to investigate the evolution of a wet agglomerate inside homogeneous shear flows of dry particles. The agglomerate is modeled by introducing approximate analytical expressions of capillary and viscous forces between particles in addition to frictional contacts. During shear flow, the agglomerate may elongate, break, or be eroded by loss of its capillary bonds and primary particles.

Additive rheology of complex granular flows.

Granular flows are omnipresent in nature and industrial processes, but their rheological properties such as apparent friction and packing fraction are still elusive when inertial, cohesive and viscous interactions occur between particles in addition to frictional and elastic forces. Here we report on extensive particle dynamics simulations of such complex flows for a model granular system composed of perfectly rigid particles. We show that, when the apparent friction and packing fraction are normalized by their cohesion-dependent quasistatic values, they are governed by a single dimensionless number that, by virtue of stress additivity, accounts for all interactions.

Agglomeration of wet particles in dense granular flows.

In order to get insight into the wet agglomeration process, we numerically investigate the growth of a single granule inside a dense flow of an initially homogeneous distribution of wet and dry particles. The simulations are performed by means of the discrete element method and the binding liquid is assumed to be transported by the wet particles, which interact via capillary and viscous force laws. The granule size is found to be an exponential function of time, reflecting the conservation of the amount of liquid and the decrease of the number of available wet particles inside the flow during agglomeration.