Numerical and experimental investigation of melting of ice involving natural convection

Two‐dimensional transient melting of ice in a rectangular enclosure was numerically and experimentally investigated. Natural convection in the liquid phase due to the temperature dependency of water density was considered in the numerical model. The implicit finite difference method with fixed staggered grid approach was utilized. The SIMPLER algorithm was followed for the solution of pressure and velocity fields in the liquid phase. The prediction of the model was found to be satisfactory through preliminary experimentation. Copyright © 2002 John Wiley & Sons, Ltd.     

Determination of the Dill parameters of thick positive resist for use in modeling applications

The determination of Dill parameters of thick resist is very important to improve simulation models of resist exposure and real world processes. A new extraction technique of Dill parameters based on spectroscopic ellipsometry in combination with an advanced resist exposure model is proposed for thick resist analysis. The complex refractive index of the resist is related to the relative concentration of the photoactive compound in the resist in order to describe the vertical distribution of the refractive index and the extinction coefficient. Moreover, Dill parameters are extracted by directly fitting the bleaching curves to the measured ellipsometry data. The new approach was investigated experimentally by spectroscopic ellipsometry measurements on AZ5214E resist with two moderate layer thickness values in order to verify the accuracy of the new method. Dill parameters were extracted by using this new technique and by applying resist samples subjected to different exposure doses. Possible reasons for the variation of Dill parameters depending on resist thickness are explained. Furthermore, advantages, limitations and potential improvements of the model are discussed. Finally, the impact of Dill parameter variation on image formation in the resist is demonstrated by applying the spectroscopic ellipsometer analysis results as input parameters to the lithography simulator Dr.LiTHO.     

The Influence of Al2O3 and TiO2 Additives on the Electrical Resistivity of Epoxy Resin‐Based Composites at Low Temperature

Electrical insulation is a major security problem in aerospace applications where temperature can reach relatively low values. Epoxy resins are well known as easily formable dielectric materials and can be used to prepare complex insulator parts. In this study, the electrical performance of bisphenol A/epichlorohydrin epoxy resin matrix‐based nanocomposites containing 1, 3, or 6 wt% titanium oxide (TiO₂) or aluminium oxide (Al₂O₃) nanofillers are investigated. Composites are characterized with thermogravimetric analysis, scanning electron microscopy‐coupled electron dispersive spectroscopy, and confocal Raman spectroscopy. Furthermore, the role of additives and their ratio on the resistivity performance of the composites are evaluated from 77 to 500 K by applying a direct current voltage from 1 to 20 V. It is observed that the electrical properties of the matrix are directly influencing the insulation performance of the nanocomposite. For example, the abrupt decrease at 370 K of the positive temperature coefficient of the resin for all nanocomposites. It is found that the most resistive composite contains 3 wt% TiO₂ nanoparticles with a value above 3.7.10¹⁰ Ω from 77 to 370 K at 20 V. As a result, this work gives information on to the choice of appropriate insulator materials in extreme working conditions.     

New local binary pattern approaches based on color channels in texture classification

Multimedia Tools and Applications - In this paper, four novel, simple and robust approaches, which are left to right local binary patterns (LBPLL2R), top to down local binary patterns (LBPT2D),...     

The fabrication of exfoliated graphite sheet-based air cathodes and gel electrolyte for metal-air batteries

In this paper, we demonstrate that activated carbon (AC) and manganese dioxide (MnO₂) coated exfoliated graphite sheets are a promising cathode for metal-air batteries. A simple and effective method is developed to exfoliate the graphite sheets and to load a catalyst onto their surfaces. Several low-cost, environmentally friendly air cathodes are fabricated, and their performances are tested by constructing Al-air b`atteries whose electrolyte 6 M NaOH, including ZnO inhibitor, is gelled by adding a cost-effective water retainer. The experimental results show that this new Al-air battery has a good discharge performance. In particular one of the new cathodes containing 50 wt% AC and 50 wt% MnO₂ produces a capacity of 311 mAh/g at a constant current discharge of 1.56 mA. Finally, future research directions are discussed for the further usage of the fabricated cathodes.     

Novel ZA27/B4C/Graphite Hybrid Nanocomposite-Bearing Materials with Enhanced Wear and Corrosion Resistance

Metallurgical and Materials Transactions A - In this study, nanosized B4C and graphite-reinforced ZA27 matrix hybrid nanocomposites were produced with mechanical milling followed by hot pressing....     

Investigation of Ionospheric Electron Density Change During Two Partial Solar Eclipses and Its Comparison with Predictions of NeQuick 2 and IRI-2016 Models

Wireless Personal Communications - In the present study, the results obtained by incoherent scatter radar (ISR) and empirical models (NeQuick2 and IRI-2016) of the variations in mid-latitude...     

Lead(II) Adsorption from Aqueous Solution by Poly(ethylene terephthalate)-g-Acrylamide Fibers

In this study, a reactive fibrous adsorbent was prepared by graft copolymerization of Acrylamide (AAm) onto poly(ethylene terephthalate) (PET) fibers and the adsorption properties of Pb(II) ion from aqueous solution by the reactive fibers were examined by batch equilibration technique. The effects of graft yield, pH, adsorption time, initial ion concentration and adsorption temperature on the adsorption amount of Pb(II) ion was studied. The results show that the adsorption amounts of Pb(II) ion increased with grafting yield, shaking time, initial ion concentration and adsorption temperature. Adsorption of Pb(II) ion was strongly affected by pH. A Lagergren pseudo-second-order was the model that best described the adsorption mechanism. It was found that the adsorption isotherm of the Pb(II) ion fit Langmuir-type isotherms. From the Langmuir equation the adsorption capacity was found as 39.57 mg/g fiber for Pb(II) ion for the copolymer with a graft yield of 15.7%. Quantitative desorption of Pb(II) from reactive fibers were found to be 96% by 5 M HNO₃. Five adsorption–desorption cycles demonstrated that the reactive fibers were suitable for repeated use without considerable change in adsorption capacity. The results of the thermodynamic study indicated that the adsorption processes was endothermic and spontaneous.     

The effects of expanded perlite aggregate, silica fume and fly ash on the thermal conductivity of lightweight concrete

Thermal conductivity coefficients of concretes made up of mixtures of expanded perlite and pumice aggregates (PA) were measured. To determine the effect of silica fume (SF) and class C fly ash (FA) on the thermal conductivity of lightweight aggregate concrete (LWAC), SF and FA were added as replacement for cement by decreasing the cement weights in the ratios of 10%, 20% and 30% by weight.The highest thermal conductivity of 0.3178 W/mK was observed with the samples containing only PA and plain cement. It decreased with the increase of SF and FA as replacement for cement. The lowest value of thermal conductivity, which is 0.1472 W/mK, was obtained with the samples prepared with expanded perlite aggregate (EPA) replacement of PA and 70% cement+30% FA replacement of cement. Both SF and FA had a decreasing effect on thermal conductivity. EPA (used in place of PA) also induced a decrease of 43.5% in thermal conductivity of concrete.     

Primary User Emulation Detection Algorithm Based on Distributed Sensor Networks

In this paper, we propose a novel primary user emulation (PUE) detection approach which employs a distributed sensor network, where each sensor node operates as an independent PUE detector. Distributed nodes collaborate in order to obtain the final detection results for the whole network. A voting algorithm is used to improve the performance of energy detection, while the classification is conducted by the nearest node in order to improve the efficiency of the detector. As a result of voting, if a potential primary user exists, then the features of the unknown user is compared with entries from the database in order to obtain a solid detection match. An artificial neural network (ANN) is used for the classification of an unknown user. To assess the accuracy of the detection result, we implement a reliability check at the output of ANN. The proposed algorithm is validated via computer simulations as well as by experimental hardware implementations using the Universal Software Radio Peripheral (USRP) software-defined radio (SDR) platform. The experiment results show that the distributed network detector detects the PUE 180–200%, depending on the number of primary users, faster than single node detector.