The evaluation of the diffuse interface method for phase change simulations using OpenFOAM

In the present study, a new solver named phaseChangeHeatFoam is implemented on the OpenFOAM cfd package to simulate boiling and condensation. The solver is capturing the interface between two immiscible phases with a color function volume of fluid (CF‐VOF) method. The two fluids (vapor and liquid) are assumed Newtonian and incompressible. The surface tension is modeled with continuous surface force (CSF) which is improved with a Lafaurie filter to suppress the spurious current. The mass flux across the interface in the phase change process is determined by either Lee or Tanasawa mass transfer models. Additionally, the slight variation of saturation temperature with local pressure is considered with the simplified Clausius–Clapeyron relation. The coupled velocity pressure equation is solved using the PIMPLE algorithm. The new solver is validated and examined with (i) Stefan problem, (ii) two‐dimensional film boiling, (iii) the film condensation on a horizontal plate, (iv) the laminar film condensation over a vertical plate, and (v) bubble condensation in subcooled boiling. The present study shows the capability of a diffuse interface method in accurate simulation of the phase change process and it is expected to be instructive for further numerical studies in this area.     

Resistance Spot Welding of Quenching and Partitioning (Q&P) Third-Generation Advanced High-Strength Steel: Process–Microstructure–Performance

Metallurgical and Materials Transactions A - This paper investigates process–microstructure–performance relationships in Q&P980 third-generation advanced high-strength steel...     

Electricity market price spike analysis by a hybrid data model and feature selection technique

In a competitive electricity market, energy price forecasting is an important activity for both suppliers and consumers. For this reason, many techniques have been proposed to predict electricity market prices in the recent years. However, electricity price is a complex volatile signal owning many spikes. Most of electricity price forecast techniques focus on the normal price prediction, while price spike forecast is a different and more complex prediction process. Price spike forecasting has two main aspects: prediction of price spike occurrence and value. In this paper, a novel technique for price spike occurrence prediction is presented composed of a new hybrid data model, a novel feature selection technique and an efficient forecast engine. The hybrid data model includes both wavelet and time domain variables as well as calendar indicators, comprising a large candidate input set. The set is refined by the proposed feature selection technique evaluating both relevancy and redundancy of the candidate inputs. The forecast engine is a probabilistic neural network, which are fed by the selected candidate inputs of the feature selection technique and predict price spike occurrence. The efficiency of the whole proposed method for price spike occurrence forecasting is evaluated by means of real data from the Queensland and PJM electricity markets.     

Reactive power market development considering power system security

In the new open access environment, in pursuit of profit, power producers tend to operate closer to the security boundaries and consequently, the voltage instability, which is caused by insufficient reactive power support, threats system security and reliability. This paper presents a day-ahead reactive power market based on uniform auction price scheme considering voltage security. First, expected payment function (EPF), identified earlier in the literature to construct a bidding framework for synchronous generators, is modified. Then, the modified EPF is used as the objective function of optimal power flow problem to clear reactive power market. Finally, the OPF, including overload, voltage drop and voltage stability margin in its constraints, is solved by binary coded genetic algorithm. The validity of the proposed reactive power market is studied based on the IEEE 24-bus reliability test system.     

Probabilistic safety assessment of self-centering steel braced frame

The main drawback of conventional braced frames is implicitly accepting structural damage under the design earthquake load, which leads to considerable economic losses. Controlled rocking self-centering system as a modern low-damage system is capable of minimizing the drawbacks of conventional braced frames. This paper quantifies main limit states and investigates the seismic performance of self-centering braced frame using a Probabilistic Safety Assessment procedure. Margin of safety, confidence level, and mean annual frequency of the self-centering archetypes for their main limit states, including PT yield, fuse fracture, and global collapse, are established and are compared with their acceptance criteria. Considering incorporating aleatory and epistemic uncertainties, the efficiency of the system is examined. Results of the investigation indicate that the design of low- and mid-rise self-centering archetypes could provide the adequate margin of safety against exceeding the undesirable limit-states.     

Kinetics of zinc sulfide concentrate direct leaching in pilot plant scale and development of semi-empirical model

The direct leaching kinetics of an iron-poor zinc sulfide concentrate in the tubular reactor was examined. All tests were carried out in the pilot plant. To allow the execution of hydrostatic pressure condition, the slurry with ferrous sulfate and sulfuric acid solution was filled into a vertical tube (9 m in height) and air was blown from the bottom of the reactor. The effects of initial acid concentration, temperature, particle size, initial zinc sulfate concentration, pulp density and the concentration of Fe on the leaching kinetics were investigated. Results of the kinetic analysis indicate that direct leaching of zinc sulfide concentrate follows shrinking core model (SCM). This process was controlled by a chemical reaction with the apparent activation energy of 49.7 kJ/mol. Furthermore, a semi-empirical equation is obtained, showing that the order of the iron, sulfuric acid and zinc sulfate concentrations and particle radius are 0.982, 0.189, ?0.097 and ?0.992, respectively. Analysis of the unreacted and reacted sulfide particles by SEM–EDS shows that insensitive agitation in the reactor causes detachment of the sulfur layer from the particles surface in lower than 60% Zn conversion and lixiviant in the face with sphalerite particles.     

Synthesis and Characterization of the Antibacterial Activity of Zinc Oxide Nanoparticles against Salmonella typhi

Metal oxides can be used as a series of new and effective anti-bacterial agents.In this study,four concentrations of ZnO nanoparticles(0.2,0.5,0.7 and 1.0 mol/L) were synthesized using a low-temperature sol-gel method annealed at400 and 550 °C.The products were characterized by X-ray diffraction(XRD),transmission electron microscopy(TEM)and Fourier transform infrared spectroscopy(FTER).XRD results show the hexagonal wurtzite structure of the nanoparticles with the grain size in the range of 38-43 nm.TEM micrographs exhibit a polyhedral form of the synthesized nanoparticles.The antimicrobial activity of different concentrations of nanoparticles against Salmonella typhi PTCC 1609 was determined by disk diffusion and agar dilution method at five concentrations of 10,5,2.5,1.25 and 0.625 mg/mL.Analysis shows that the prepared ZnO nanoparticles have a very effective antimicrobial activity against Salmonella typhi.This activity increases by reducing the size of nanoparticles and increasing their content in the bacterial growth medium.     

A new F(ast)-CMS NEGF algorithm for efficient 3D simulations of switching characteristics enhancement in constricted tunnel barrier silicon nanowire MuGFETs

In this paper, we present 3D quantum simulations based on Non-Equilibrium Green’s Function (NEGF) formalism using the Comsol Multiphysics^? software and on the implementation of a new Fast Coupled Mode-Space (FCMS) approach. The FCMS algorithm allows one to simulate transport in nanostructures presenting discontinuities, as the normal Coupled Mode-Space (CMS) algorithm does, but with the speed of a Fast Uncoupled-Mode Space (FUMS) algorithm (a faster algorithm that cannot handle discontinuities). We then use this new algorithm to explore the effect of local constrictions on the performance of nanowire MultiGate Field-Effect Transistors (MuGFETs). We show that cross-section variations in a nanowire result in the formation of energy barriers that can be used to improve the on/off current ratio and switching characteristics of transistors: (1) A small constriction resulting in a barrier of the order of a 0.1 eV can be used as an effective means to improve the subthreshold slope and minimize the on/off current ratio degradation resulting from SD tunneling in ultra scaled transistor, and (2) We also report a new variable barrier transistor (VBT) device concept that is able to achieve sub-kT/q subthreshold slope without using impact ionization or band-to-band tunneling. Intra-band tunneling through constriction barriers is used instead. The device is, therefore, fully symmetrical and can operate at very low supply voltages. A subthreshold slope as low as 56.5 mV/decade is reported at T=300 K. The VBT reported here breaks the 60 mV/dec barrier over more than five decades of subthreshold current, which is the widest current range reported so far.     

Improving the interfacial adhesion in a new renewable resource-based biocomposites from biofuel coproduct and biodegradable plastic

Biocomposites of a biopolymer and the coproduct of corn bioethanol industry, dried distillers’ grains with solubles (DDGS), were produced by reactive melt extrusion and injection molding. The biopolymer matrix was a blend of polyhydroxy(butyrate-co-valrerate), PHBV, and poly(butylene adipate-co-terphthalate), PBAT. The effect of compatibilizer, polymeric methylene diphenyl diisocyanate (PMDI), and corn oil lubricant was studied. The change in melt processing force suggested the occurrence of chemical reactions during the processing. This hypothesis was further investigated by infrared spectroscopy by which the formation of urethane and urea bonds between DDGS and polymeric matrix was approved. Dynamic mechanical analysis confirmed the occurrence of crosslinks at PBAT–PHBV interface showing that the tan δ curves for PBAT and PHBV of the matrix shifted slightly towards each other. Moreover, the calculated parameter of interaction, A, from tan δ curves admitted the stronger bond at the DDGS–matrix interface as a result of addition of PMDI compatibilizer. Also, scanning electron microscopy images revealed improved interfacial adhesion at the DDGS–matrix interface as well as PBAT–PHBV interface within the matrix itself. The obtained crosslinked interfaces resulted in improvement in the strength, modulus, and elongation-at-break of biocomposites. Moreover, a synergism of PMDI and corn oil effects led to a dramatic improvement in impact strength of this biocomposite system so that the respective value for the prepared DDGS biocomposite increased from 75 to 212 J/m with addition of 1 % of PMDI and 3 % of corn oil.     

Supply chain network optimization considering assembly line balancing and demand uncertainty

In supply chain optimisation problems, determining the location, number and capacity of facilities is concerned as strategic decisions, while mid-term and short-term decisions such as assembly policy, inventory levels and scheduling are considered as the tactical and operational decision levels. This paper addresses the optimisation of strategic and tactical decisions in the supply chain network design (SCND) under demand uncertainty. In this respect, a two-stage stochastic programming model is developed in which strategic location decisions are made in the first-stage, while the second-stage contains SCND problem and the assembly line balancing as a tactical decision. In the solution scheme, the combination of sample average approximation and Latin hypercube sampling methods is utilised to solve the developed two-stage mixed-integer stochastic programming model. Finally, computational experiments on randomly generated problem instances are presented to demonstrate the performance and power of developed model in handling uncertainty. Computational experiments showed that stochastic model yields better results compared with deterministic model in terms of objective function value, i.e. the sum of the first-stage costs and the expected second-stage costs. This issue proved that uncertainty would be a significant and fundamental element of developed model and improve the quality of solutions.