A discrete model for simulating shear strength and deformation behaviour of rockfill material, considering the particle breakage phenomenon

This study focuses on numerical modelling of rockfill material with the discrete element method (DEM). This method was used due to the special features of rockfill material, such as intense particle breakage and high contracting behaviour, which are inherently due to large particle size. Because the DEM models the interaction of separate elements, it is capable of modelling discrete structures of granular materials and particle breakage. The model used in this study uses PFC^2D and considers breakable clumps. To validate the presented model for rockfill material, numerical single crushing tests and triaxial tests on the Purulia dam’s material were simulated. Due to the size-dependant crushing strength being involved in the breakage criterion, and also considering particle confinement, size-dependant and stress level-dependant behaviour was successfully simulated on modelled rockfill material. The variation of the sample’s particle grading from before the biaxial tests and after shear failure occurred was reported. The obtained results demonstrate the accuracy of the adopted model and the model’s capability for considering a rockfill material’s strength, deformation and crushing behaviour.     

Dithiocarbamate as an efficient intermediate for the synthesis of 2-(alkylthio)thiazol-4(5H)-ones

An effective approach for the synthesis of 2-(alkylthio)thiazol-4(5H)-ones from alkyl dithiocarbamates and chloroacetyl chloride in the presence of NaHCO₃ has been developed. Good to excellent yields of products, simple reaction conditions and general applicability are the most important advantages of this protocol.     

Facile method for the preparation of the WS2 nanoparticles

A facile and simple synthetic route was proposed for the synthesis of WS2 nanoparticles. The as-prepared WS2 nanoparticles can be characterized with X-ray diffraction spectrum (XRD), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The average particle size of the product is about 85 nm that was calculated from XRD pattern by the Debye-Scherrer formula.     

Effect of particle size on thermomechanical properties of particulate polymer composite

Particulate composite materials (PCM) consisting of a matrix reinforced by micro to nano-sized dispersed phase are receiving the attention of designers as a promising futuristic materials. This study unearths the thermal and mechanical behavior of maleic anhydride grafted polypropylene/silica (MA-g-PP/silica) composites for reinforcement ranging from micro- to nano-size. The monodisperse silica spherical particles were used in all the formulations of composites. Further the volume fraction was kept the same in all the compounded thermoplastic composites ranging from 100 nm to 130 μm in a co-rotating conical twin-screw micro-compounder. The micrographs were obtained from transmission electron microscopy (TEM) and the scanning electron microscopy (SEM). The SEM and TEM results revealed a good dispersion of the silica spheres within the MA-g-PP matrix. The compounded composite materials were injection molded to fabricate tensile test specimens (ASTM D638 type V) and tested for tensile properties. In order to investigate the effect of particle size on crystallite structure of the matrix, the composites were tested on differential scanning calorimeter and X-ray diffraction (WAXD). The thermal stability and degradation kinetics were studied via thermogravimetric analysis. The results show increase in crystallization rate, crystallinity percentage, Young’s modulus, strength and thermal stability of MA-g-PP by addition of the silica particles. Further it was observed that the small-sized dispersed phase had better overall thermal and mechanical behavior than its larger sized counterpart.     

Estimation of Petroleum Reservoir Parameters Using an Integrated Approach Neural Network,Principal Component Analysis and Fisher Discriminant Analysis

A new predictive methodology is introduced, based on a combined principal component analysis (PCA), Fisher discriminant analysis (FDA), and artificial neural network (ANN) methodologies for parameters estimation of a petroleum reservoir. Prediction of continuous petrophysical parameters is often time consuming and complicated because of geological variability such as facies changes due to sedimentary and structural changes. The petrophysical parameters, however, are usually difficult to measure due to reliability considerations, limitations insights on cost, inappropriate instrument maintenance, and sensor failures, evaluated by crude diagrams of reservoir parameters valuably. PCA and FDA provides an optimal lower dimensional representation in terms of discriminating among classes of data and are developed utilizing the reservoir historical data to incorporate reliability and prediction capabilities of ANN. The developed soft sensors are applied to predict the parameters of Marun reservoir located in Ahwaz, Iran, by utilizing the available geophysical well log data. The resulting outcomes demonstrate the promising capabilities of the proposed hybrid PCA-FDA-NN methodology than the conventional back-propagation NN, FDA, and PCA algorithms.     

JuNoLo - Jülich nonlocal code for parallel post-processing evaluation of vdW-DF correlation energy

Nowadays the state of the art Density Functional Theory (DFT) codes are based on local (LDA) or semilocal (GGA) energy functionals. Recently the theory of a truly nonlocal energy functional has been developed. It has been used mostly as a post-DFT calculation approach, i.e. by applying the functional to the charge density calculated using any standard DFT code, thus obtaining a new improved value for the total energy of the system. Nonlocal calculation is computationally quite expensive and scales as N² where N is the number of points in which the density is defined, and a massively parallel calculation is welcome for a wider applicability of the new approach. In this article we present a code which accomplishes this goal.

Program summary

Program title: JuNoLoCatalogue identifier: AEFM_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFM_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 176 980No. of bytes in distributed program, including test data, etc.: 2 126 072Distribution format: tar.gzProgramming language: Fortran 90Computer: any architecture with a Fortran 90 compilerOperating system: Linux, AIXHas the code been vectorised or parallelized?: Yes, from 1 to 65536 processors may be used.RAM: depends strongly on the problem's size.Classification: 7.3External routines:• FFTW (http://www.tw.org/)• MPI (http://www.mcs.anl.gov/research/projects/mpich2/ or http://www.lam-mpi.org/)Nature of problem: Obtaining the value of the nonlocal vdW-DF energy based on the charge density distribution obtained from some Density Functional Theory code.Solution method: Numerical calculation of the double sum is implemented in a parallel F90 code. Calculation of this sum yields the required nonlocal vdW-DF energy.Unusual features: Binds to virtually any DFT program.Additional comments: Excellent parallelization features.Running time: Depends strongly on the size of the problem and the number of CPUs used.