Improved extra group network: a new fault-tolerant multistage interconnection network

Supersystems are shown to provide enough computational power to solve complex problems on a real-time basis. In all these systems, the computational parallelism is obtained from multiple processors. Multistage interconnection networks (MINs) play a vital role on the performance of these multiprocessor systems. This paper introduces a new fault-tolerant MIN named as improved extra group network (IEGN). IEGN is designed by existing extra group (EGN) network, which is a regular multipath network with limited fault tolerance. IEGN provides four times more paths between any source–destination pairs compared with EGN. The performance of IEGN has been evaluated in terms of permutation capability, fault tolerance, reliability, path length, and cost. It has also been proved that the IEGN can achieve better results in terms of fault tolerance, reliability, path length and cost-effectiveness, in comparison to known networks, namely, EGN, augmented baseline network, augmented shuffle-exchange network, fault-tolerant double tree, Benes network, and Replicated MIN.     

F-LEACH: a fuzzy-based data aggregation scheme for healthcare IoT systems

The Journal of Supercomputing - Internet of Things (IoT) is an emerging paradigm that consists of numerous connected and interrelated devices with embedded sensors, exchanging data with each other...     

A new synthetic metamodel methodology for liquid‐propellant engine's cooling system optimization

The present paper strives for optimization of the cooling system of a liquid‐propellant engine (LPE). To this end, the new synthetic metamodel methodology utilizing the design of experiment method and the response surface method was developed and implemented as two effective means of designing, analyzing, and optimizing. The input variables, constraints, objective functions, and their surfaces were identified. Hence, the design and development strategy of combustion chamber and nozzle was clarified, and 64 different experiments were carried out on the RD‐161 propulsion system, of which 47 experiments were approved and compatible with the problem constraints. This engine used all three modes of cooling: the radiation cooling, the regenerative cooling, and the film cooling. The response surface curves were drawn and the related objective function equations were obtained. The analysis of variance results indicate that the developed synthetic model is capable to predict the responses adequately within the limits of input parameters. The three‐dimensional response surface curves and contour plots have been developed to find out the combined effects of input parameters on responses. In addition, the precision of the models was assessed and the output was interpreted and analyzed, which showed high accuracy. Therefore, the desirability function analysis has been applied to LPE's cooling system for multiobjective optimization to maximize the total heat transfer and minimize the cooling system pressure loss simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, this methodology optimizes the LPE's cooling system, a 2% increase in the total heat transfer, and a 38% decrease in the pressure loss of the cooling system. These values are considerably large for the LPE design.     

Development of an electrochemical sulfite biosensor by immobilization of sulfite oxidase on conducting polyaniline film

In this work, a biosensor was developed for the determination of sulfite. The bioelectrochemical response of the enzyme-modified electrode based on electrochemical incorporation of sulfite oxidase into polyaniline aluminum modified electrode was investigated. Electropolymerization of polyaniline and simultaneous immobilization of sulfite oxidase on the aluminum were performed in an aqueous solution containing sulfite oxidase. The sulfite biosensor constructed by cycling the potential scan between +1.2 and ?0.5 V vs. saturated calomel electrode (SCE) that showed a sensitive response to sulfite with a linear calibration graph in the concentration ranges of 0.006–5 mM sulfite and detection limit 0.002 mM sulfite (S/N = 3). The obtained results from the stability tests of the biosensor show that the sulfite biosensor can be used for two different applications, for immediate usage and long term usage. Also, the bioelectrochemical response of the enzyme-modified electrode as a sulfite biosensor was evaluated at different experimental conditions. The optimum pH when using phosphate buffer and temperature were 8.5 and 35 °C, respectively. Finally, the apparent Michaelis–Menten constant was determined which has value of 0.365 mM which is really close to the magnitude of the Michaelis–Menten constant of free sulfite oxidase that shows the enzyme was not chemically modified and has its usual kinetic reaction.     

Effects of thermal and mechanical activation methods on compressive strength of ordinary Portland cement–slag mortar

Activation methods and curing regimes have crucial effects on the strength of mortars and concretes. The objective of this investigation is to examine the early and later compressive strength of activated ordinary Portland cement (OPC)–ground granulated blast-furnace slag (GGBFS) mortars and identify the most effective activation technique. The methods of activation used were thermal, mechanical and thermal–mechanical combined. Two curing regimes were adopted and five groups of mortars were prepared. It was observed that OPC–GGBFS mortars have greater sensitivity to OPC mortars against the curing regimes. However, the study revealed that there was no particular activation method which when used gave the best results for both early and later strengths and did not cause strength loss. It also proved that the most effective activation method for early strength is a combination of both the thermal and mechanical, while for later strengths, none of the activation methods was recommended.     

An Investigation of Mechanical Properties of Polyurethane Nanocomposites with Various Silicas: Experimental Study and Modeling of Finite Deformation Response

It is well-known that polymer nanocomposites can bring about superior mechanical, thermal, optical, physical, and chemical properties in comparison with pure polymers. In this study, different contents of unmodified silica nanoparticles (Si-Un), surface modified nano-silica by octylsilane (Si-OS), and surface modified nano-silica by polydimethylsiloxane (Si-PDMS) are added to the polyurethane (PU) matrix and their effects on the physical properties of the polymer examined. The experimental results indicate that most of the nanocomposites have a higher tensile strength and elongation. In addition, hyperelastic energy function models have been used to model the stress-strain relation of the nanocomposites. In this study, Mooney-Rivlin, neo-Hookean, Rivlin general polynomial, and Davies-De Thomas (DDT) models have been investigated, possessing respectively, two, one, eight, and three constants to be determined. The differential evolution (DE) optimization method, a strong heuristic optimization algorithm, has been used to find the constants; in which the absolute summation of the differences between the models’ predictions and experimental data is taken into account as the objective function and the models’ constants are considered as the decision variables. Moreover, equation constants are found by using regression, an indicator of DE optimization superiority. The results show that even though the Rivlin general polynomial model provides the most accurate prediction, the DDT model, consisting of three constants, can be considered as the most acceptable one.     

On the dispersion of CNTs in polyamide 6 matrix via solution methods: assessment through electrical, rheological, thermal and morphological analyses

In this study, polyamide 6 (PA 6)/multi-walled carbon nanotube (MWCNT) nanocomposites were prepared by different solution methods based on phase inversion, drop-casting and simple evaporation processes. Optical microscopy and field emission scanning electron microscopy techniques were used to investigate the dispersion states of the nanotubes in PA 6 matrix. The results indicated that the dispersion state of MWCNTs in the nanocomposites prepared by the phase inversion-based method was better than those in the nanocomposites prepared by the other two methods. Electrical, rheological, differential scanning calorimetry and thermo-gravimetric analysis measurements showed that the PA 6/MWCNTs nanocomposites prepared by the phase inversion-based method had higher electrical conductivity, storage modulus, crystallization temperature and thermal stability in comparison with those prepared by the other two methods, attributed to the better dispersion state of MWCNTs. These results confirmed achievement of a good dispersion state of MWCNTs within PA 6 matrix by the phase inversion-based efficient approach.     

Temperature Rise Inside Shear Bands in a Simple Model Glass

One of the key factors, which hampers the application of metallic glasses as structural components, is the localization of deformation in narrow bands of a few tens up to one hundred nanometers thickness, the so-called shear bands. Processes, which occur inside shear bands are of central importance for the question whether a catastrophic failure of the material is unavoidable or can be circumvented or, at least, delayed. Via molecular dynamics simulations, this study addresses one of these processes, namely the local temperature rise due to viscous heat generation. The major contribution to energy dissipation is traced back to the plastic work performed by shear stress during steady deformation. Zones of largest strain contribute the most to this process and coincide with high-temperature domains (hottest spots) inside the sample. Magnitude of temperature rise can reach a few percent of the sample’s glass transition temperature. Consequences of these observations are discussed in the context of the current research in the field.     

Renewable energy harvesting with the application of nanotechnology: A review

It is believed that fossil fuel sources are exhaustible and also the major cause of greenhouse gas emission. Therefore, it is required to increase the portion of renewable energy sources in supplying the primary energy of the world. In this study, it is focused on application of nanotechnology in exploitation of renewable energy sources and the related technologies such as hydrogen production, solar cell, geothermal, and biofuel. Here, nanotechnologies influence on providing an alternative energy sources, which are environmentally benign, are comprehensively discussed and reviewed. Based on the literature, employing nanotechnology enhances the heat transfer rate in photovoltaic/thermal (PV/T) systems and modifies PV structures, which can improve its performance, making fuel cells much cost‐effective and improving the performance of biofuel industry through utilization of nanocatalysts, manufacturing materials with high durability and lower weight for wind energy industry.     

Effect of Foliar-Applied Silicon on Flower Yield and Essential Oil Composition of Damask Rose (Rosa damascena Miller) under Water Deficit Stress

Silicon - A field experiment was conducted to investigate the effect of silicon on the flower yield and essential oil composition of damask rose under water deficit stress. Silicon was applied as...