A production-recycling-inventory model with learning effect

This paper develops an integrated production-recycling system over a finite time horizon. Here, the dynamic demand is satisfied by production and recycling. The used units are bought back and then either recycled or disposed of which are not repairable. The used units are collected continuously from the customers. Recycling products can be used as new products which are sold again. The rate of production and disposal are assumed to be function of time. The setup cost is reduced over time due to “Learning curve” effect. The optimum results are presented both in tabular form and graphically.     

Experimental and FE analysis of submerged arc weld induced residual stress and angular deformation of single and double sided fillet welded joint

Submerged arc welding is well-known for its very high deposition rate and thus the capability to join very high thickness metal pieces in large structural applications. Fillet joints are mostly used in structural applications which can be extensively seen in shipbuilding, bridge construction, house buildings, automobile or any other large structures. Thermal stresses generates in a fusion welded joint due to high temperature gradient, which is the cause of the residual stresses upon cooling followed by the angular deformation and failure of the welded structure. As an effect of the thermal gradient, the induced longitudinal, transverse residual stress & angular distortion can vary in single sided and double sided submerged arc welded fillet joints, during designing & manufacturing welded structures which should be taken into account. The main objective of this paper is to quantify the amount of residual stresses and angular deformation in a fillet welding joint. An elasto-plastic thermomechanical model has been developed for predicting residual stresses. A comparison of the residual stress and angular deformation between single and double sided fillet weld joint has been made. The simulation results reveal that the amount of residual stress present in the single sided fillet weld is more and unbalanced in both side of the center of weld line compared to the double sided fillet weld and the predicted results have been matched with the experiments as well as published literatures.     

Iron-Doped,Mullite-Impregnated PVDF Composite: An Alternative Separator for a High Charge Storage Ceramic Capacitor

In this communication, the formation mechanism of the electroactive β phase, morphology and the dielectric activities of increasing doping concentration (0–1.2 M.W % of mullite) of Fe²⁺ ion-doped, mullite-impregnated polyvinylidene fluoride (PVDF) nanocomposite have been investigated. Differential thermal analysis (DTA) confirms the formation of an electroactive β phase, and Fourier transform infrared spectroscopy (FTIR) showed that the β phase increases simultaneously and attains the maximum increment of 2.6 times compared to pristine PVDF. X-ray diffraction (XRD) spectra also agreed well with the β-phase increment behaviour and also confirmed the presence of required mullite phases. Field emission scanning electron microscopy (FESEM) images indicate the strong interaction between the polymer matrix and different concentrations of Fe²⁺ ion-doped mullite particles, resulting in enhanced electroactive β phase formation and large dielectric constant of the nanocomposite films followed by significant low dielectric loss with high ac conductivity compared to pristine PVDF films at room temperature. This doped polymer composite can be used as a high dielectric separator and, using this separator, we have successfully fabricated a high-charge-storage device. This paper also demonstrates that the loading of conductive Fe²⁺ ions within the highly insulating mullite matrix has a critical concentration for the enhancement and nucleation of the electroactive β phase of the PVDF polymer. In this critical concentration, the highest formation of a β network and maximum numbers of homogeneously distributed iron-doped mullite (FeM) particles in PVDF matrix improves the effective interfacial polarization by Maxwell–Wagner–Sillar (MWS) polarization effect which is responsible for the enhancement of dielectric constant and ac conductivity followed by significant tangent loss. So, it can be concluded that the incorporation of Fe²⁺-doped mullite into PVDF matrix is an effective way to fabricate a high dielectric separator of high-charge-storage electronic devices.     

Temperature dependent growth and optical properties of SnO<Subscript>2</Subscript> nanowires and nanobelts

SnO₂ nanowires and nanobelts have been grown by the thermal evaporation of Sn powders. The growth of nanowires and nanobelts has been investigated at different temperatures (750–1000°C). The field emission scanning electron microscopic and transmission electron microscopic studies revealed the growth of nanowires and nano-belts at different growth temperatures. The growth mechanisms of the formation of the nanostructures have also been discussed. X-ray diffraction patterns showed that the nanowires and nanobelts are highly crystalline with tetragonal rutile phase. UV-visible absorption spectrum showed the bulk bandgap value (∼ 3–6 eV) of SnO₂. Photoluminescence spectra demonstrated a Stokes-shifted emission in the wavelength range 558–588 nm. The Raman and Fourier transform infrared spectra revealed the formation of stoichiometric SnO₂ at different growth temperatures.     

A neural-network-based space-vector PWM controller for athree-level voltage-fed inverter induction motor drive

A neural-network-based implementation of space-vector modulation (SVM) of a three-level voltage-fed inverter is proposed in this paper that fully covers the linear undermodulation region. A neural network has the advantage of very fast implementation of an SVM algorithm, particularly when a dedicated application-specific IC chip is used instead of a digital signal processor (DSP). A three-level inverter has a large number of switching states compared to a two-level inverter and, therefore, the SVM algorithm to be implemented in a neural network is considerably more complex. In the proposed scheme, a three-layer feedforward neural network receives the command voltage and angle information at the input and generates symmetrical pulsewidth modulation waves for the three phases with the help of a single timer and simple logic circuits. The artificial-neural-network (ANN)-based modulator distributes switching states such that neutral-point voltage is balanced in an open-loop manner. The frequency and voltage can be varied from zero to full value in the whole undermodulation range. A simulated DSP-based modulator generates the data which are used to train the network by a backpropagation algorithm in the MATLAB Neural Network Toolbox. The performance of an open-loop volts/Hz speed-controlled induction motor drive has been evaluated with the ANN-based modulator and compared with that of a conventional DSP-based modulator, and shows excellent performance. The modulator can be easily applied to a vector-controlled drive, and its performance can be extended to the overmodulation region     

High stress abrasive wear behavior of sillimanite-reinforced Al-alloy matrix composite: A factorial design approach

An attempt has been made to explore the possibility of using a natural mineral, namely sillimanite, as dispersoid for synthesizing aluminum alloy composite by solidification technique. The abrasive wear behavior of this composite has been studied through factorial design of experiments. The wear behavior of the composite (Y _composite) and the alloy (Y _alloy) is expressed in terms of the coded values of different experimental parameters like applied load (x ₁), abrasive size (x ₂), and sliding distance (x ₃) by the following linear regression equations:

Offline/realtime traffic classification using semi-supervised learning

Identifying and categorizing network traffic by application type is challenging because of the continued evolution of applications, especially of those with a desire to be undetectable. The diminished effectiveness of port-based identification and the overheads of deep packet inspection approaches motivate us to classify traffic by exploiting distinctive flow characteristics of applications when they communicate on a network. In this paper, we explore this latter approach and propose a semi-supervised classification method that can accommodate both known and unknown applications. To the best of our knowledge, this is the first work to use semi-supervised learning techniques for the traffic classification problem. Our approach allows classifiers to be designed from training data that consists of only a few labeled and many unlabeled flows. We consider pragmatic classification issues such as longevity of classifiers and the need for retraining of classifiers. Our performance evaluation using empirical Internet traffic traces that span a 6-month period shows that: (1) high flow and byte classification accuracy (i.e., greater than 90%) can be achieved using training data that consists of a small number of labeled and a large number of unlabeled flows; (2) presence of “mice” and “elephant” flows in the Internet complicates the design of classifiers, especially of those with high byte accuracy, and necessitates the use of weighted sampling techniques to obtain training flows; and (3) retraining of classifiers is necessary only when there are non-transient changes in the network usage characteristics. As a proof of concept, we implement prototype offline and realtime classification systems to demonstrate the feasibility of our approach.     

MWCNT reinforced Polyamide-6,6 films: preparation,characterization and properties

Composite films of Polyamide-6,6 (PA66) and multi-walled carbon nanotubes (MWCNTs) were prepared by a combination of solution casting followed by compression molding techniques. Both unfunctionalized (u-MWCNTs) and functionalized nanotubes (f-MWCNTs) were used in this study. The functionalization involved direct solvent-free amination of MWCNTs with hexamethylenediamine. Thermogravimetric analysis was used to observe the changes in the nanotubes upon functionalization and morphological features of the resulting composite films were studied using scanning electron microscopy, transmission electron microscopy, and atomic force microscopy. The crystallinity changes by incorporation of the u-MWCNTs and f-MWCNTs in the PA66 matrix were studied by wide angle X-ray scattering and differential scanning calorimetry. The f-MWCNT/PA66 film showed an improvement of ∼43% in maximum tensile stress (MTS) and ∼32% in Young’s modulus over pristine PA66 film, while at a similar loading of 0.5 wt%, the f-MWCNT/PA66 film showed ∼15% increase in MTS and ∼16% increase in modulus over the u-MWCNT/PA66 film. Dynamic mechanical analysis indicated significant difference in the small-strain mechanical properties between the MWCNT-filled and unfilled PA66 at the very low MWNT loadings that were tested and supported the tensile results. The water absorption trend of the composite films showed dramatic improvement over the neat film.     

Optimization study of adsorption parameters for removal of phenol on gastropod shell dust using response surface methodology

Phenolics have recently been of great concern because of the extreme toxicity and persistence in the environment. This study explores the possibility of using gastropod shell dust (GPSD) to remove phenol from aqueous solutions. The removal of phenol was investigated in batch mode. The influence of different experimental parameters—initial pH, adsorbent dose, initial concentration, contact time, stirring rate, temperature, and their interaction during phenol adsorption—were determined by response surface methodology based on three-level four-factorial Box–Behnken design. Optimized values of initial phenol concentration, pH, adsorbent dose, and contact time were found as 10.16 mg/L, 4.22, 0.50 g/L, and 33.47 min, respectively. The experimental equilibrium data were tested by four widely used isotherm models namely, Langmuir and Freundlich, D–R, and Temkin. It was found that adsorption of phenol on gastropod shell dust correlated with the Langmuir isotherm model, implying monolayer coverage of phenol onto the surface of the adsorbent. The maximum adsorption capacity was found to be 56.89 mg g^?1 at 333 K. Regeneration study revealed that about 92 % phenol can be regenerate within 90 min from the spent GPSD. Kinetics of the adsorption process was tested by pseudo-first-order, pseudo-second-order kinetics, and intra-particle diffusion mechanism. Pseudo-second-order kinetic model provided a better correlation for the experimental data studied in comparison to the pseudo-first-order model. Intra-particle diffusion was not the sole rate-controlling factor. The activation energy of the adsorption process (E _a) was found to be 2.68 kJ mol^?1, indicating physisorption nature of phenol adsorption onto gastropod shell dust. A thermodynamic study showed spontaneous nature and feasibility of the adsorption process. A negative enthalpy (ΔH°) value indicated that the adsorption process was exothermic. The results revealed that gastropod shell dust can be used as an effective and low-cost adsorbent to remove phenol from aqueous solutions.     

Technical note The effect of rate of decay of rain path profile on microwave communication

The attenuation of radio waves due to rain can be predicted with a good degree of accuracy, provided the rain rate characteristics over the entire path of propagation are known. The attenuation due to rain is usually deduced on the basis of point rain rate, which can lead to inaccuracy in the estimation of attenuation. We use the concept of rate of decay of rain path profile to estimate the attenuation due to rain. The attenuation has been deduced at 11GHz and 13.4 GHz for 56 elevation angle by using the theory of decay rate of rain path profile, its controlling factor, gamma, and rain rate distribution over Delhi, a tropical station in India. The theoretically-estimated attenuation is compared with observed values, as well as with values obtained using the International Radio Consultative Committee (CCIR) method. The CCIR model is found to overestimate the attenuation.