Determination of performance of non-ideal aluminized explosives

Non-ideal explosives can have Chapman-Jouguet (C-J) detonation pressure significantly different from those expected from existing thermodynamic computer codes, which usually allows finding the parameters of ideal detonation of individual high explosives with good accuracy. A simple method is introduced by which detonation pressure of non-ideal aluminized explosives with general formula C(a)H(b)N(c)O(d)Al(e) can be predicted only from a, b, c, d and e at any loading density without using any assumed detonation products and experimental data. Calculated detonation pressures show good agreement with experimental values with respect to computed results obtained by complicated computer code. It is shown here how loading density and atomic composition can be integrated into an empirical formula for predicting detonation pressure of proposed aluminized explosives.     

Reinforcing effects of aminosilane-functionalized graphene on the tribological and mechanical behaviors of epoxy nanocomposites

In this study, aminopropyl trimethoxysilane as an interfacial modifier was introduced on the surface of graphene (Gr) nanoplatelets. The effects of the silane-modified graphene (SGr) loading (0, 0.05, 0.1, 0.3, and 0.5 wt %) and silane modification on the tensile, compressive, interlaminar shear stress (ILSS), and tribological properties of the epoxy-based nanocomposites were investigated. Out of these specimens, the highest values of ILSS and compressive strength were related to the 0.3 wt % SGr–epoxy nanocomposite. The addition of SGr enhanced the tensile strength and strain to failure only at low contents (i.e., 0.05 wt %). Also, the tensile and compressive moduli were improved, and the highest values were observed at a 0.5 wt % SGr loading. In addition, decreases of approximately 40 and 68% in the coefficient of friction and wear rate, respectively, were observed at a 0.3 wt % SGr loading. Enhanced tensile, compressive, ILSS, and wear properties in the SGr–epoxy specimens were observed compared to those in the Gr–epoxy specimens. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47410.     

Screening of Food Samples for Zearalenone Toxin Using an Electrochemical Bioassay Based on DNA–Zearalenone Interaction

This study was conducted to design a biosensor as a new, rapid, and sensitive tool for investigation of binding of zearalenone with double-stranded DNA (dsDNA). Polydiallyldimethylammonium chloride (PDDA) as a polycation and multiwall carbon nanotubes (MWCNTs) provide a positively charged surface with a high surface area for the immobilization of dsDNA as a polyanion on the surface of pencil graphite electrode (PGE). Using the dsDNA/MWCNT–PDDA-modified PGE, it was possible to detect the interaction of zearalenone with dsDNA, which allowed us to apply the dsDNA-modified electrode for trace determination of zearalenone. The changes at the oxidation signal of adenine were evaluated before/after each modification/immobilization step. By using dsDNA/PDDA–MWCNT/PGE, zearalenone could be detected as low as 0.005 ng mL^?1. The relative standard deviation of five measurements of 0.5 ng mL^?1 zearalenone was found to be 4.2 %. Finally, the highly stable electrochemical biosensor was applied to analyze the zearalenone concentration in milk and wheat samples.

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Graphical Abstract xElectrochemical DNA Biosensor for Zearalenone detection

     

Piecewise affine modeling and control of a boiler–turbine unit

In this paper, a discrete-time piecewise affine (PWA) model has been proposed for a nonlinear model of boiler–turbine unit using plant operating points. PWA model is one of the main classes of hybrid systems being equivalent to some other hybrid modeling frameworks such as mixed logical dynamical (MLD) model. In order to control the system, a model predictive control (MPC) strategy in explicit form has been used which calculates the control law as an affine function of system states. In this method, the computation of MPC is moved off-line. The off-line control law is easier to implement reducing to a look-up table in comparison with the on-line approach. Finally, the explicit model predictive control performance has been compared with the linear controller obtained using H_∞ approach. The results are illustrated by simulations. They show that the explicit MPC method has suitably improved the system performance, especially the quantity of control efforts is smaller and without saturation compared with that of H_∞ control system.     

The quantitative risk assessment of a hydrogen generation unit

The safety of hydrogen generation process is a major concern. This paper discusses the quantitative analyzes of the risk imposed on neighborhood from the operation of a hydrogen generator using natural gas reforming process. For this purpose, after hazard identification, the frequency of scenarios was estimated using generic data. Quantitative risk assessment was applied for consequence modeling and risk estimation. The results revealed that, jet fire caused by a full bore rupture in Desulphurization reactor has the highest fatality (26person) and affects the largest area of 5102 m². The lethality radius, maximum radiation and safe distance of this incident were 140 m, 370 kW/m² and 225 m respectively. A full bore rupture in Reformer can lead to the most dangerous flash fire. In this incident the concentration of released material in LFL zone (area of 1483.17 m²) and ½ LEL zone (area of 1970.74 m²) were 61,125 ppm and 40,000 ppm respectively. QRA is a credible method to assess the risks of hydrogen generation process.     

Effect of storage options on price-based scheduling for a hybrid trigeneration system

Trigeneration is efficient to supply cooling, heat, and power demands. Also, hydro (pumped) storage with zero fuel costs can increase profit when price-based scheduling problem is solved. The goal of this study is to investigate the effects of electric boiler, hydro storage, and heat storage tank on price-based scheduling problem for hybrid trigeneration (trigeneration-conventional-gas boiler) system. A heuristic algorithm is applied to a power system where in validation case, total cost reduction of 0.63% to 0.91% is reached as compared with reported in literature. The results show that the utilization of electric boiler, hydro storage, and heat storage tank leads to profit improvement by 4.58%. Also, a critical sensitivity analysis is conducted and the results show the significant effects of several factors on scheduling results.     

Investigation the impact of additives on the displacement of the onset point of asphaltene precipitation using interfacial tension measurement

The purpose of this study is to explore the impact of additives on the displacement of the onset point of asphaltene precipitation in crude oil using the interfacial tension measurement method, based on the examined oil has been taken from Iran reservoirs. The experimental results suggest that the addition of surfactants of dodecyl benzene sulfonic acid (DBSA) and coconut diethanolamide (CDEA) to the oil has triggered the onset of asphaltene precipitation. These findings imply that CDEA has a more effective role in preventing asphaltene precipitation. Also, it was observed that increasing the concentration of the surfactants has led to obtaining greater results. Finally, critical micelle concentration was calculated to be 5000 and 4700 ppm in the cases of CDEA and DBSA, respectively.     

Free convection of water–Fe3O4 nanofluid in an inclined cavity subjected to a magnetic field: CFD modeling,sensitivity analysis

Modeling of natural convection heat transfer in an inclined C-shape cavity is studied in this paper. The enclosure is filled with H₂O-Fe₃O₄ nanofluid under the effect of magnetic field. The operating range of parameters used in this study were Hartmann number (Ha) from 0 to 80, Rayleigh number (Ra) from 1E2 to 1E6, nanoparticles volume fraction (φ) from 0 to 0.1, inclination angle (α) from 0 to 90 deg, and aspect ratio (AR) from 0.2 to 0.8. The employed model is solved using CFD tools based on the finite element method. The comparison with reference experimental data indicated the accuracy and generalization capability of the model. In addition, a novel correlation and an artificial neural network (ANN) model were productively developed for predicting Nu number as a function of aforementioned independent variables. The influence of the model parameters on the Nu number is precisely presented and discussed. It is shown that Ra number and aspect ratio have more impact on Nu than the other variables.     

Cognitive radio networks for green wireless communications: an overview

As power consumption results in greenhouse gas emissions and energy costs for operators, analyzing power consumption in wireless networks and portable devices is of crutial importance. Due to environmental effects resulted from energy generation and exploitation as well as the cost of surging energy, energy-aware wireless systems attract unprecedented attention. Cognitive Radio (CR) is one of the optimal solutions that allows for energy savings on both the networks and devices. Thus, cognitive radio contributes to increase spectral and energy efficiency as well as reduction in power consumption. In addition, energy consumption of the CR technologies as intelligent technology should be considered to realize the green networks objective. In this article, we look into energy efficiency of the cognitive wireless network paradigms. Moreover, energy efficiency analysis and modelling in these systems are specifically focused on achieving green communications objectives. However, CRs by altering all elements of wireless data communications are considered in this paper, and the energy-efficient operation and energy efficiency enabler perspectives of CRs are also analyzed.