Kinetic and mechanistic investigations of mesotrione degradation in aqueous medium by Fenton process

In this work, chemical oxidation of mesotrione herbicide by Fenton process in acidic medium (pH 3.5) was investigated. Total disappearance of mesotrione and up to 95% removal of total organic carbon (TOC) were achieved by Fenton's reagent under optimized initial concentrations of hydrogen peroxide (H(2)O(2)) and ferrous iron (Fe(2+)) at pH 3.5. The time-dependent degradation profiles of mesotrione were satisfactorily fitted by first-order kinetics. Competition kinetic model was used to evaluate a rate constant of 8.8(± 0.2) × 10(9)M(-1) s(-1) for the reaction of mesotrione with hydroxyl radicals. Aromatic and aliphatic intermediates of mesotrione oxidation were identified and quantified by high performance liquid chromatography (HPLC). It seems that the degradation of mesotrione by Fenton process begins with the rupture of mesotrione molecule into two moieties: cyclohexane-1,3-dione derivative and 2-nitro-4-methylsulfonylbenzoic acid. Hydroxylation and release of sulfonyl and/or nitro groups from 2-nitro-4-methylsulfonylbenzoic acid lead to the formation of polyhydroxylated benzoic acid derivatives which undergo an oxidative opening of benzene ring into carboxylic acids that end to be transformed into carbon dioxide.     

Confusion diagnosis and avoidance of discrete event systems using supervisory control

Nondeterministic firing of concurrent transitions in Petri nets (PNs) may lead to the disappearance of conflicts. The disappearance implies that the partial conflicting transitions in a conflict become disabled before the resolution of the conflict. The phenomenon is called confusions that are caused by the interlacement of conflicting and concurrent transitions in PNs, which generates incomplete and faulty system conflicting behavior such that conflicts cannot be correctly resolved. In this paper, conflict‐increasing confusions (CICs) and conflict‐decreasing confusions (CDCs) in a PN are investigated. The relation graph of conflicts and confusions (RGC²) in a PN is proposed to detect the structure of confusions. To avoid the occurrence of confusions in a PN, an algorithm based on generalized mutual exclusion constraints (GMECs) is proposed, which can generate confusion‐avoidance supervisors such that the occurrence of conflicts can be ensured in a PN. Finally, an example of confusion detection and avoidance in a flexible assembly system is presented. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Effect of Sprayed Solution Flow Rate on the Physical Properties of Anatase TiO2 Thin Films

Titanium dioxide (TiO₂) thin films were synthesized on glass substrates by spray pyrolysis. The effect of solution flow rate on the physical properties of the films was investigated by use of x-ray diffraction (XRD), scanning electron microscopy, atomic force microscopy (AFM), and spectrophotometry techniques. XRD analysis revealed the tetragonal anatase phase of TiO₂ with highly preferred (101) orientation. AFM images showed that grain size on top of TiO₂ thin films depended on solution flow rate. An indirect band gap energy of 3.46 eV was determined by means of transmission and reflection measurements. The envelope method, based on the optical transmission spectrum, was used to determine film thickness and optical constants, for example real and imaginary parts of the dielectric constant, refractive index, and extinction coefficient. Ultraviolet and visible photoluminescence emission peaks were observed at room temperature. These peaks were attributed to the intrinsic emission and to the surface defect states, respectively.     

End-to-end privacy preserving scheme for IoT-based healthcare systems

Preserving patients’ privacy is one of the most important challenges in IoT-based healthcare systems. Although patient privacy has been widely addressed in previous work, there is a lack of a comprehensive end-to-end approach that simultaneously preserves the location and data privacy of patients assuming that system entities are untrusted. Most of the past researches assume that parts of this end-to-end system are trustworthy while privacy may be threatened by insider attacks. In this paper, we propose an end-to-end privacy preserving scheme for the patients assuming that all main entities of the healthcare system (including sensors, gateways, and application providers) are untrusted. The proposed scheme preserves end-to-end privacy against insider threats as well as external attacks concerning the resource restrictions of the sensors. This scheme provides mutual authentication between main entities while preserves patients’ anonymity. Only the allowed users can access the real identity of patients alongside their locations and their healthcare information. Informal security analysis and formal security verification of the proposed protocol in AVISPA show that it is secure against impersonation, replay, modification, and man-in-the-middle attacks. Moreover, performance assessments show that the proposed protocol provides more security services without considerable growth in the computation overhead of the sensors. Also, it is shown that the proposed protocol diminishes the signaling overhead of the sensors and so their energy consumption compared to the literature at the expense of adding a little more signaling overhead to the gateways.

     

Developing GEP tree-based,neuro-swarm,and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

The type of materials used in designing and constructing structures significantly affects the way the structures behave. The performance of concrete and steel, which are used as a composite in columns, has a considerable effect upon the structure behavior under different loading conditions. In this paper, several advanced methods were applied and developed to predict the bearing capacity of the concrete-filled steel tube (CFST) columns in two phases of prediction and optimization. In the prediction phase, bearing capacity values of CFST columns were estimated through developing gene expression programming (GEP)-based tree equation; then, the results were compared with the results obtained from a hybrid model of artificial neural network (ANN) and particle swarm optimization (PSO). In the modeling process, the outer diameter, concrete compressive strength, tensile yield stress of the steel column, thickness of steel cover, and the length of the samples were considered as the model inputs. After a series of analyses, the best predictive models were selected based on the coefficient of determination (R²) results. R² values of 0.928 and 0.939 for training and testing datasets of the selected GEP-based tree equation, respectively, demonstrated that GEP was able to provide higher performance capacity compared to PSO–ANN model with R² values of 0.910 and 0.904 and ANN with R² values of 0.895 and 0.881. In the optimization phase, whale optimization algorithm (WOA), which has not yet been applied in structural engineering, was selected and developed to maximize the results of the bearing capacity. Based on the obtained results, WOA, by increasing bearing capacity to 23436.63 kN, was able to maximize significantly the bearing capacity of CFST columns.

     

A novel approach for forecasting of ground vibrations resulting from blasting: modified particle swarm optimization coupled extreme learning machine

Engineering with Computers - Ground vibration is one of the most important undesirable effects induced by blasting operations in the mining or tunneling projects. Hence, developing a precise model...     

The effect of the through-thickness yarn component on the in- and out-of-plane properties of composites from 3D orthogonal woven preforms

Development of three-dimensional (3D) weaving technology introduced new and enhanced features to the 2D weaving technology. 3D Orthogonal Woven (3DOW) preforms have a through-thickness yarn component that significantly enhances the out-of-plane properties and delamination resistance. In this study, a range of 3DOW E-glass preforms were woven using 3D weaving technology and then converted into composites, using vacuum assisted resin transfer molding technology. The composite samples had varying Z to Y-yarn/ layer ratio, the objective is to study the effect of changing the Z to Y-yarn/ layer ratio on the in-plane and out-of-plane mechanical properties. The study concludes that changing the amount of Z-yarn in the structure has negligible effect on the tensile (in-plane), yet, it has a significant effect on the drop weight impact properties (out-of-plane). Moreover, it had a strong effect on the failure mechanisms, and as the amount of Z-yarn is reduced, delamination became more significant.     

Uniaxial compressive strength prediction through a new technique based on gene expression programming

Proper estimation of rock strength is a critical task for evaluation and design of some geotechnical applications such as tunneling and excavation. Uniaxial compressive strength (UCS) test can be measured directly in the laboratory; nevertheless, the direct UCS determination is time-consuming and expensive. In this study, feasibility of gene expression programming (GEP) model in indirect determination of UCS values of sandstone rock samples is examined. In this regard, several laboratory tests including Brazilian test, density test, slake durability test and UCS test were conducted on 47 samples of sandstone which were collected from the Dengkil, Malaysia. Considering multiple inputs, several GEP models were constructed to estimate UCS of the rock and finally, the best GEP model was selected. In order to indicate capability of the proposed GEP model, linear multiple regression (LMR) was also performed. It was found that the GEP model is superior to LMR one in terms of applied performance indices. Based on coefficient of determination (R ²) of testing datasets, by proposing GEP model, it can be improved from 0.930 (which was obtained by LMR model) to 0.965. As a result, it is concluded that the proposed models in this study, could be utilized to estimate UCS of similar rock type in practice.

     

Detection of Impact Damage in Carbon Fiber Composites Using an Electromagnetic Sensor

This article presents a comprehensive experimental study of impact damage detection for carbon fiber-reinforced polymer (CFRP) composites using an electromagnetic (EM) sensor with coupled spiral inductors (CSI). Two representative types of damage are detected and evaluated, i.e., barely visible impact damage (BVID) and delamination. A multifrequency inspection is performed, where the resultant images indicate the potential of the CSI sensor in the characterization of damage extent. The accuracy and efficiency of the CSI sensor are compared with the open-ended waveguide imaging, near-field microwave microscopy, microwave time-domain reflectometry, the complementary split-ring resonator, and ultrasonic scanning. Applications and limitations of these nondestructive testing (NDT) methods for identifying impact damage are discussed. There is a free edge effect on the electromagnetic signal, which is illustrated for the first time with the proposed EM technique. Detection of the air gap produced by inserting a thin piece into a machined subsurface groove is carried out. It is found that the developed CSI sensor is able to accurately resolve the location and extent of the air gap. The experimental results demonstrate that the sensor could offer an alternative relatively low cost method that can be fully automated for structural monitoring of aircraft and other composite structures.     

A thermodynamic analysis of biogas partial oxidation to synthesis gas with emphasis on soot formation

A thermodynamic analysis of synthesis gas production via partial oxidation (POX) of biogas is performed in the present article. Chemical equilibrium calculations are conducted for partial oxidation of (CH₄+CO₂) mixtures based on Gibbs free energy minimization method emphasizing soot formation. Regarding precise evaluation of carbon dioxide effects on the reforming characteristics, the obtained results are compared with the experimental data. Furthermore, the effects of steam injection at the inlet of the reformer on the coking behavior and syngas production yield are studied. To investigate the effects of the equivalence ratio (?), temperature and pressure, a broad parametric study is performed. The results reveal that the process temperature plays a pivotal role in enhancing the syngas production and soot abatement. It is also found that the pressure has an impractical effect on the syngas production yield, leading to the soot formation and decrease in both hydrogen and carbon monoxide yields. Furthermore, increasing the inlet CO₂/CH₄ makes the thermal reforming efficiency to rise at an equivalence ratio lower than 3. Meanwhile, increasing the steam to methane (S/C) ratio reduces carbon formation and enhances hydrogen production. Nonetheless, when the S/C ratio is larger than 2 at ? = 2.5 and 1 at ? = 3, the enhancement of hydrogen generation is minimized and even tends to become impractical. Therefore, near adiabatic and atmospheric condition at ? = 2.5–3 with S/C < 1 are recommended as the optimum operating routes for partial oxidation of biogas.