Abstract: Nitriding of p-type Si samples by pulsed DC glow discharge is carried out for different Ar concentrations (30% to 90%) in nitrogen-argon plasma whereas the other parameters like pressure (2 mbar), treatment time (4 hr) and power (175 W) are kept constant. The phase identification, crystal structure, crystallinity, chemical composition, surface morphology and topography of the nitrided layer are studied using X-ray diffraction (XRD), Fourier transform infra-red spectroscopy (FTIR), optical microscopy (OM), scanning electron microscopy (SEM) and atomic force microscopy (AFM) respectively. The XRD patterns reveal the development of different diffraction planes of Si3N4 confirming the formation of polycrystalline layer. FTIR spectrum confirms the formation of bond between Si and N. Results reveal that addition of Ar into N2 plasma plays an important role to enhance the production of active species which facilitate the nitrogen diffusion.
Abstract: In the field of production, characterization of surface
roughness plays a vital role in assessing the quality of a manufactured
product. The defined parameters for this assessment, each, have their
own drawbacks in describing a profile surface. From the purview of
small-scale and medium-scale industries, an increase in time spent for
manual inspection of a product for various parameters adds to the
cost of the product. In order to reduce this, a uniform and established
standard is necessary for quantifying a profile of a manufactured
product. The inspection procedure in the small and medium-scale
manufacturing units at Jigani Industrial area, Bangalore, was
observed. The parameters currently in use in those industries are
described in the paper and a change in the inspection method is
proposed.
Abstract: The present work aims at contributing to the study of the complex phenomenon of wear of pin on disc contact in dry sliding friction between two material couples (bronze/steel and unsaturated polyester virgin and charged with graphite powder/steel). The work consists of the determination of the coefficient of friction, the study of the influence of the tribological parameters on this coefficient and the determination of the mass loss and the wear rate of the pin. This study is also widened to the highlighting of the influence of the addition of graphite powder on the tribological properties of the polymer constituting the pin. The experiments are carried out on a pin-disc type tribometer that we have designed and manufactured. Tests are conducted according to the standards DIN 50321 and DIN EN 50324. The discs are made of annealed XC48 steel and quenched and tempered XC48 steel. The main results are described here after. The increase of the normal load and the sliding speed causes the increase of the friction coefficient, whereas the increase of the percentage of graphite and the hardness of the disc surface contributes to its reduction. The mass loss also increases with the normal load. The influence of the normal load on the friction coefficient is more significant than that of the sliding speed. The effect of the sliding speed decreases for large speed values. The increase of the amount of graphite powder leads to a decrease of the coefficient of friction, the mass loss and the wear rate. The addition of graphite to the UP resin is beneficial; it plays the role of solid lubricant.
Abstract: In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability.
Abstract: This paper presents a technique for compact three
dimensional (3D) object model reconstruction using wavelet
networks. It consists to transform an input surface vertices
into signals,and uses wavelet network parameters for signal
approximations. To prove this, we use a wavelet network architecture
founded on several mother wavelet families. POLYnomials
WindOwed with Gaussians (POLYWOG) wavelet families are used
to maximize the probability to select the best wavelets which
ensure the good generalization of the network. To achieve a better
reconstruction, the network is trained several iterations to optimize the
wavelet network parameters until the error criterion is small enough.
Experimental results will shown that our proposed technique can
effectively reconstruct an irregular 3D object models when using
the optimized wavelet network parameters. We will prove that an
accurateness reconstruction depends on the best choice of the mother
wavelets.
Abstract: Superhydrophobic surfaces are abundant in nature. Several surfaces such as wings of butterfly, legs of water strider, feet of gecko and the lotus leaf show extreme water repellence behaviour. Self-cleaning, stain-free fabrics, spill-resistant protective wears, drag reduction in micro-fluidic devices etc. are few applications of superhydrophobic surfaces. In order to design robust superhydrophobic surface, it is important to understand the interaction of water with superhydrophobic surface textures. In this work, we report a simple coating method for creating large-scale flexible superhydrophobic paper surface. The surface consists of multiple layers of silanized zirconia microparticles decorated with zirconia nanoparticles. Water contact angle as high as 159±10 and contact angle hysteresis less than 80 was observed. Drop impact studies on superhydrophobic paper surface were carried out by impinging water droplet and capturing its dynamics through high speed imaging. During the drop impact, the Weber number was varied from 20 to 80 by altering the impact velocity of the drop and the parameters such as contact time, normalized spread diameter were obtained. In contrast to earlier literature reports, we observed contact time to be dependent on impact velocity on superhydrophobic surface. Total contact time was split into two components as spread time and recoil time. The recoil time was found to be dependent on the impact velocity while the spread time on the surface did not show much variation with the impact velocity. Further, normalized spreading parameter was found to increase with increase in impact velocity.
Abstract: The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe3O4/Al2O3 NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe3O4/Al2O3 NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL−1, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL-1 Fe2+ was 2.3%.
Abstract: The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.
Abstract: Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.
Abstract: The increasing demand of thermoplastic elastomers is related to the wide range of applications, such as automotive, footwear, wire and cable industries, adhesives and medical devices, cell phones, sporting goods, toys and others. These materials are susceptible to microbial attack. Moisture and organic matter present in some areas (such as shower area and sink), provide favorable conditions for microbial proliferation, which contributes to the spread of diseases and reduces the product life cycle. Compounds based on SEBS copolymers, poly(styrene-b-(ethylene-co-butylene)-b-styrene, are a class of thermoplastic elastomers (TPE), fully recyclable and largely used in domestic appliances like bath mats and tooth brushes (soft touch). Zinc oxide and zinc ions loaded in personal and home care products have become common in the last years due to its biocidal effect. In that sense, the aim of this study was to evaluate the effect of zinc as antimicrobial agent in compounds based on SEBS/polypropylene/oil/ calcite for use as refrigerator seals (gaskets), bath mats and sink squeegee. Two zinc oxides from different suppliers (ZnO-Pe and ZnO-WR) and one masterbatch of zinc ions (M-Zn-ion) were used in proportions of 0%, 1%, 3% and 5%. The compounds were prepared using a co-rotating double screw extruder (L/D ratio of 40/1 and 16 mm screw diameter). The extrusion parameters were kept constant for all materials. Tests specimens were prepared using the injection molding machine. A compound with no antimicrobial additive (standard) was also tested. Compounds were characterized by physical (density), mechanical (hardness and tensile properties) and rheological properties (melt flow rate - MFR). The Japan Industrial Standard (JIS) Z 2801:2010 was applied to evaluate antibacterial properties against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). The Brazilian Association of Technical Standards (ABNT) NBR 15275:2014 were used to evaluate antifungal properties against Aspergillus niger (A. niger), Aureobasidium pullulans (A. pullulans), Candida albicans (C. albicans), and Penicillium chrysogenum (P. chrysogenum). The microbiological assay showed a reduction over 42% in E. coli and over 49% in S. aureus population. The tests with fungi showed inconclusive results because the sample without zinc also demonstrated an inhibition of fungal development when tested against A. pullulans, C. albicans and P. chrysogenum. In addition, the zinc loaded samples showed worse results than the standard sample when tested against A. niger. The zinc addition did not show significant variation in mechanical properties. However, the density values increased with the rise in ZnO additives concentration, and had a little decrease in M-Zn-ion samples. Also, there were differences in the MFR results in all compounds compared to the standard.
Abstract: Three-dimensional incompressible turbulent fluid flow and heat transfer of pin fin heat sinks using air as a cooling fluid are numerically studied in this study. Two different kinds of pin fins are compared in the thermal performance, including circular and square cross sections, both are in-line and staggered arrangements. The turbulent governing equations are solved using a control-volume- based finite-difference method. Subsequently, numerical computations are performed with the realizable k - ԑ turbulence for the parameters studied, the fin height H, fin diameter D, and Reynolds number (Re) in the range of 7 ≤ H ≤ 10, 0.75 ≤ D ≤ 2, 2000 ≤ Re ≤ 126000 respectively. The numerical results are validated with available experimental data in the literature and good agreement has been found. It indicates that circular pin fins are streamlined in comparing with the square pin fins, the pressure drop is small than that of square pin fins, and heat transfer is not as good as the square pin fins. The thermal performance of the staggered pin fins is better than that of in-line pin fins because the staggered arrangements produce large disturbance. Both in-line and staggered arrangements show the same behavior for thermal resistance, pressure drop, and the entropy generation.
Abstract: Stochastic modeling concerns the use of probability
to model real-world situations in which uncertainty is present.
Therefore, the purpose of stochastic modeling is to estimate the
probability of outcomes within a forecast, i.e. to be able to predict
what conditions or decisions might happen under different situations.
In the present study, we present a model of a stochastic diffusion
process based on the bi-Weibull distribution function (its trend
is proportional to the bi-Weibull probability density function). In
general, the Weibull distribution has the ability to assume the
characteristics of many different types of distributions. This has
made it very popular among engineers and quality practitioners, who
have considered it the most commonly used distribution for studying
problems such as modeling reliability data, accelerated life testing,
and maintainability modeling and analysis. In this work, we start
by obtaining the probabilistic characteristics of this model, as the
explicit expression of the process, its trends, and its distribution by
transforming the diffusion process in a Wiener process as shown in
the Ricciaardi theorem. Then, we develop the statistical inference of
this model using the maximum likelihood methodology. Finally, we
analyse with simulated data the computational problems associated
with the parameters, an issue of great importance in its application to
real data with the use of the convergence analysis methods. Overall,
the use of a stochastic model reflects only a pragmatic decision on
the part of the modeler. According to the data that is available and
the universe of models known to the modeler, this model represents
the best currently available description of the phenomenon under
consideration.
Abstract: Biogas can be currently considered as an alternative option for electricity production, mainly due to its high energy content (hydrocarbon-rich source), its renewable status and its relatively low utilization cost. Solid Oxide Fuel Cell (SOFC) stacks convert fuel’s chemical energy to electricity with high efficiencies and reveal significant advantages on fuel flexibility combined with lower emissions rate, especially when utilize biogas. Electricity production by biogas constitutes a composite problem which incorporates an extensive parametric analysis on numerous dynamic variables. The main scope of the presented study is to propose a detailed thermodynamic model on the optimization of SOFC-based power plants’ operation based on fundamental thermodynamics, energy and exergy balances. This model named THERMAS (THERmodynamic MAthematical Simulation model) incorporates each individual process, during electricity production, mathematically simulated for different case studies that represent real life operational conditions. Also, THERMAS offers the opportunity to choose a great variety of different values for each operational parameter individually, thus allowing for studies within unexplored and experimentally impossible operational ranges. Finally, THERMAS innovatively incorporates a specific criterion concluded by the extensive energy analysis to identify the most optimal scenario per simulated system in exergy terms. Therefore, several dynamical parameters as well as several biogas mixture compositions have been taken into account, to cover all the possible incidents. Towards the optimization process in terms of an innovative OPF (OPtimization Factor), presented here, this research study reveals that systems supplied by low methane fuels can be comparable to these supplied by pure methane. To conclude, such an innovative simulation model indicates a perspective on the optimal design of a SOFC stack based system, in the direction of the commercialization of systems utilizing biogas.
Abstract: Conical sections and shells of metal plates manufactured by 3-roller conical bending process are widely used in the industries. The process is completed by first bending the metal plates statically and then dynamic roller bending sequentially. It is required to have an analytical model to get maximum bending force, for optimum design of the machine, for static bending stage. Analytical models assuming various stress conditions are considered and these analytical models are compared considering various parameters and reported in this paper. It is concluded from the study that for higher bottom roller inclination, the shear stress affects greatly to the static bending force whereas for lower bottom roller inclination it can be neglected.
Abstract: Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.
Abstract: Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.
Abstract: The present work numerically analyzes the transient heat transfer in the absorber plates of a flat-plate solar collector based on the dual-phase-lag (DPL) heat conduction model. An efficient numerical scheme involving the hybrid application of the Laplace transform and control volume methods is used to solve the linear hyperbolic heat conduction equation. This work also examines the effect of different medium parameters on the behavior of heat transfer. Results show that, while the heat-flux phase lag induces thermal waves in the medium, the temperature-gradient phase lag smoothens the thermal waves by promoting non-Fourier diffusion-like conduction into the medium.
Abstract: The numerical simulation based on the Finite Element Method (FEM) is widely used in academic institutes and in the industry. It is a useful tool to predict many phenomena present in the classical manufacturing forming processes such as fracture. But, the results of such numerical model depend strongly on the parameters of the constitutive behavior model. The influences of thermal and mechanical loads cause damage. The temperature and strain rate dependent materials’ properties and their modelling are discussed. A Johnson-Cook Model of damage has been selected for the numerical simulations. Virtual software called the ABAQUS 6.11 is used for finite element analysis. This model was introduced in order to give information concerning crack initiation during thermal and mechanical loads.
Abstract: Power law approximation was used in this study to evaluate the reaction orders of calcium oxide, CaO catalyzed transesterification of refined cottonseed oil and methanol. The kinetics study was carried out at temperatures of 45, 55 and 65 oC. The kinetic parameters such as reaction order 2.02 and rate constant 2.8 hr-1g-1cat, obtained at the temperature of 65 oC best fitted the kinetic model. The activation energy, Ea obtained was 127.744 KJ/mol. The results indicate that the transesterification reaction of the refined cottonseed oil using calcium oxide catalyst is approximately second order reaction.
Abstract: High population and irregular urban development in Kabul city, Afghanistan's capital, are among factors that increase its vulnerability to earthquake disasters (on top of its location in a high seismic region); this can lead to widespread economic loss and casualties. This study aims to evaluate earthquake risks in Kabul's 13th district based on scientific data. The research data, which include hazard curves of Kabul, vulnerability curves, and a questionnaire survey through sampling in district 13, have been incorporated to develop risk curves. To estimate potential casualties, we used a set of M parameters in a model developed by Coburn and Spence. The results indicate that in the worst case scenario, more than 90% of district 13, which comprises mostly residential buildings, is exposed to high risk; this may lead to nearly 1000 million USD economic loss and 120 thousand casualties (equal to 25.88% of the 13th district's population) for a nighttime earthquake. To reduce risks, we present the reconstruction of the most vulnerable buildings, which are primarily adobe and masonry buildings. A comparison of risk reduction between reconstructing adobe and masonry buildings indicates that rebuilding adobe buildings would be more effective.