Influence of particle contact models on soil response of poorly graded sand during cavity expansion in discrete element simulation

The discrete element method (DEM) has been extensively adopted to investigate many complex geotechnical related problems due to its capability to incorporate the discontinuous nature of granular materials. In particular, when simulating large deformations or distortion of soil (e.g. cavity expansion), DEM can be very effective as other numerical solutions may experience convergence problems. Cavity expansion theory has widespread applications in geotechnical engineering, particularly to the problems concerning in situ testing, pile installation and so forth. In addition, the behaviour of geomaterials in a macro-level is utterly determined by microscopic properties, highlighting the importance of contact models. Despite the fact that there are numerous contact models proposed to mimic the realistic behaviour of granular materials, there are lack of studies on the effects of these contact models on the soil response. Hence, in this study, a series of three-dimensional numerical simulations with different contact constitutive models was conducted to simulate the response of sandy soils during cylindrical cavity expansion. In this numerical investigation, three contact models, i.e. linear contact model, rolling resistance contact model, and Hertz contact model, are considered. It should be noted that the former two models are linear based models, providing linearly elastic and frictional plasticity behaviours, whereas the latter one consists of nonlinear formulation based on an approximation of the theory of Mindlin and Deresiewicz. To examine the effects of these contact models, several cylindrical cavities were created and expanded gradually from an initial radius of 0.055 m to a final radius of 0.1 m. The numerical predictions confirm that the calibrated contact models produced similar results regarding the variations of cavity pressure, radial stress, deviatoric stress, volumetric strain, as well as the soil radial displacement. However, the linear contact model may result in inaccurate predictions when highly angular soil particles are involved. In addition, considering the excessive soil displacement induced by the pile installation (i.e. cavity expansion), a minimum distance of 11a (a is the cavity radius) is recommend for practicing engineers to avoid the potential damages to the existing piles and adjacent structures.     

Novel electrospun polymer electrolytes incorporated with Keggin‐type hetero polyoxometalate fillers as solvent‐free electrolytes for lithium ion batteries

In this study, solvent‐free nanofibrous electrolytes were fabricated through an electrospinning method. Polyethylene oxide (PEO), lithium perchlorate and ethylene carbonate were used as polymer matrix, salt and plasticizer respectively in the electrolyte structures. Keggin‐type hetero polyoxometalate (Cu‐POM@Ru‐rGO, Ni‐POM@Ru‐rGO and Co‐POM@Ru‐rGO (POM, polyoxometalate; rGO, reduced graphene oxide)) nanoparticles were synthesized and inserted into the PEO‐based nanofibrous electrolytes. TEM and SEM analyses were carried out for further evaluation of the synthesized filler structures and the electrospun nanofibre morphologies. The fractions of free ions and crystalline phases of the as‐spun electrolytes were estimated by obtaining Fourier transform infrared and XRD spectra, respectively. The results showed a significant improvement in the ionic conductivity of the nanofibrous electrolytes by increasing filler concentrations. The highest ionic conductivity of 0.28 mS cm^?1 was obtained by the introduction of 0.49 wt% Co‐POM@Ru‐rGO into the electrospun electrolyte at ambient temperature. Compared with solution‐cast polymeric electrolytes, the electrospun electrolytes present superior ionic conductivity. Moreover, the cycle stability of the as‐spun electrolytes was clearly improved by the addition of fillers. Furthermore, the mechanical strength was enhanced with the insertion of 0.07 wt% fillers to the electrospun electrolytes. The results implied that the prepared nanofibres are good candidates as solvent‐free electrolytes for lithium ion batteries. © 2020 Society of Chemical Industry     

Densification improvement of spark plasma sintered TiB2-based composites with micron-, submicron- and nano-sized SiC particulates

Taguchi design of experiments methodology was used to determine the most influential spark plasma sintering (SPS) parameters on densification of TiB₂–SiC ceramic composites. In this case, four processing factors (SPS temperature, soaking time, applied external pressure and SiC particle size) at three levels were examined in order to acquire the optimum conditions. The statistical analysis identified the sintering temperature as the most effective factor influencing the relative density of TiB₂–SiC ceramics. A relative density of 99.5% was achieved at the optimal SPS conditions; i.e. temperature of 1800?°C, soaking time of 15?min and pressure of 30?MPa by adding 200-nm SiC particulates to the TiB₂ matrix. The experimental measurements and predicted values for the relative density of composite fabricated at the optimum SPS conditions and reinforced with the proper SiC particle size were almost similar. The mechanisms of sintering and densification of spark plasma sintered TiB₂–SiC composites were discussed in details.     

Speaker independent feature selection for speech emotion recognition: A multi-task approach

Nowadays, automatic speech emotion recognition has numerous applications. One of the important steps of these systems is the feature selection step. Because it is not known which acoustic features of person’s speech are related to speech emotion, much effort has been made to introduce several acoustic features. However, since employing all of these features will lower the learning efficiency of classifiers, it is necessary to select some features. Moreover, when there are several speakers, choosing speaker-independent features is required. For this reason, the present paper attempts to select features which are not only related to the emotion of speech, but are also speaker-independent. For this purpose, the current study proposes a multi-task approach which selects the proper speaker-independent features for each pair of classes. The selected features are then given to the classifier. Finally, the outputs of the classifiers are appropriately combined to achieve an output of a multi-class problem. Simulation results reveal that the proposed approach outperforms other methods and offers higher efficiency in terms of detection accuracy and runtime.

     

NOMA performance enhancement-based imperfect SIC minimization using a novel user pairing scenario involving three users in each pair

Wireless Networks - Due to the non-uniform distribution of users in a cellular area, there are users with similar channel conditions. In non-orthogonal multiple access (NOMA) systems, a small...     

Context-driven mean residual life estimation of mining machinery

Maintenance is crucial to ensure production/output and customer satisfaction in the mining sector. The cost of maintenance of mechanised and automated mining systems is very high, necessitating efforts to enhance the effectiveness of maintenance systems and organisation. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. Determining the Mean Residual Life (MRL) of systems allows organisations to more effectively plan maintenance tasks. In this paper, we use a statistical approach to estimate MRL and consider a Weibull proportional hazard model (PHM) with time-independent covariates to model the hazard function so that the operating environment could be integrated into the reliability analysis. The paper explains our methods for calculating the conditional reliability function and computing the MRL as a function of the current conditions. The model is verified and validated using data from the hydraulic system of LHD equipment in a Swedish mine. The results are useful to estimate the remaining useful life of such systems; the method can be used for maintenance planning, helping to control unplanned stoppages of highly mechanised and automated systems.     

Selective molecularly imprinted polymer nanofiber sorbent for the extraction of bisphenol A in a water sample

Novel molecularly imprinted polymer nanofibers (MIP‐NFs) were prepared for the adsorption of bisphenol A (BPA) in a water sample using the sol–gel process and the electrospinning technique. The effects of a number of synthesis parameters on the adsorption efficiency were investigated. The successful removal of BPA from MIP‐NFs was studied using UV–visible spectroscopy. The prepared MIP‐NFs were characterized by Fourier transform infrared, field emission SEM, TEM and energy dispersive X‐ray analysis. The results showed that the required molar ratio of 3‐aminopropyltriethoxysilane (APTES) to BPA was 15:1, which indicates a good performance in the rebinding test. Likewise, the molar ratio of APTES:acid:water was 1:2:9. The nylon 6 polymer solution, with a concentration of 12 wt%, showed a maximum adsorption capacity for BPA due to a decrease in the nanofiber diameter and an increase in the accessible sites. Furthermore, the maximum adsorption capacity of BPA was achieved at pH 7. Concerning the binding of BPA on MIP‐NFs, the experimental data matched well with the pseudo‐second‐order kinetics data and the Sips isotherm model. The saturated binding capacity for MIP‐NFs was predicted to be 115.1 mg g^?1, which was more than twice as high as that for non‐imprinted polymer nanofibers (46.82 mg g^?1). The results obtained in this study confirmed that the prepared MIP‐NFs showed considerable binding specificity for BPA in comparison with similar structural compounds such as phenol, naphthol and Naphthol AS, in aqueous solution. The binding capacity of MIP‐NFs remained almost constant after five cycles of reuse. The real sample analysis indicated that MIP‐NFs could be utilized as a useful sorbent material for the extraction of BPA from a water sample.     

Nanostructured Carbide-Free Bainite Formation in Low Carbon Steel

It is an important challenge to reduce the carbon content in nanostructured bainitic steels for commercialization purposes while still being able to gain the desired microstructural characteristics in nanoscale and not to deteriorate the strength-ductility combinations. That is the point at which an appropriate heat treatment procedure design would be an important parameter. This article aims to investigate how to obtain nanostructured bainite in steel with 0.26 wt% carbon content by applying multi-step austempering procedures. One-, two- and three-step austempering processes have been implemented, and proper heat treatment temperatures and approaches were selected based on dilatometry tests. Results indicated that it has become possible to achieve bainitic ferrites and austenite films with overall thicknesses of 164, 145 and 132 nm and 134, 105 and 90 nm at the end of one-, two- and three-step austempering heat treatments, respectively. Meanwhile, microstructural characteristics resulted in enhanced mechanical properties with ultimate tensile strength (UTS) of 1435, 1455 and 1428 MPa in combination with elongation levels of 15.4, 13.6 and 11.4% after implementing those heat treatments. Finally, it has been shown that applying the multi-step austempering heat treatments resulted in enhanced yield strength and impact toughness values due to the microstructural characteristics and proper heat treatment procedure design.