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Observation of ultraviolet whispering gallery modes in ZnMgO microrods
No full textWe report on the fabrication of ZnO and Zn0.9Mg0.1O microrods using nanoparticle assisted pulsed laser deposition (NAPLD). Micro-photoluminescence studies reveal that Zn0.9Mg0.1O microrods exhibited a blue shift in the ultraviolet (UV) emission relative to unintentionally doped ZnO that was attributed to the increase in bandgap due to Mg doping. High-resolution micro-photoluminescence clearly indicated the presence of whispering gallery modes (WGMs) for both ZnO and Zn0.9Mg0.1O. Transverse electric (TE) and transverse magnetic (TM) optical WGMs were identified using the existing plane-wave model. The observation of lower order WGM modes in Zn0.9Mg0.1O microrods may be of great interest for future UV WGM lasing
Monitoring and assessment of heavy metal contamination in a constructed wetland in Shaoguan (Guangdong Province, China): bioaccumulation of Pb, Zn, Cu and Cd in aquatic and terrestrial components
Get PDFThe objective of this study is to evaluate the current
status of heavy metal concentrations in constructed wetland,
Shaoguan (Guangdong, China). Sediments, three wetland
plants (Typha latifolia, Phragmites australis, and Cyperus
malaccensis), and six freshwater fish species [Carassius
auratus (Goldfish), Cirrhinus molitorella (Mud carp),
Ctenopharyngodon idellus (Grass carp), Cyprinus carpio
(Wild common carp), Nicholsicypris normalis(Mandarin fish),
Sarcocheilichthys kiangsiensis (Minnows)] in a constructed
wetland in Shaoguan were collected and analyzed for their
heavy metal compositions. Levels of Pb, Zn, Cu, and Cd in
sediments exceeded approximately 532, 285, 11, and 66 times
of the Dutch Intervention value. From the current study, the
concentrations of Pb and Zn in three plants were generally
high, especially in root tissues. For fish, concentrations of all
studied metals in whole body of N. mormalis were the highest
among all the fishes investigated (Pb 113.4 mg/kg, dw; Zn
183.1 mg/kg, dw; Cu 19.41 mg/kg, dw; 0.846 mg/kg, dw).
Heavy metal accumulation in different ecological compartments was analyzed by principle component analysis (PCA), and there is one majority of grouped heavy metals concentration as similar in composition of ecological compartment, with
the Cd concentration quite dissimilar. In relation to future prospect, phytoremediation technology for enhanced heavy metal accumulation by constructed wetland is still in early stage and needs more attention in gene manipulation area
An elliptical model for lockstitch 301 seam to estimate thread consumption
Get PDFA geometrical model for lockstitch seam 301 has been proposed based on elliptical profile to estimate the thread consumption. The realistic elliptical shape of a lockstitch 301 seam has been confirmed by observing cut section along seam line. In order to validate a model across the different fabric types, varieties of fabrics from woven shirting, woven jeans, knitted single jersey to nonwoven interlining fabric have been considered. The different number of plies (2, 3 and 4) of given fabrics have been stitched at different levels of stitch densities (3, 4 and 5 stitches per cm) to observe effects in prediction of these parameters. It is found that the error % is increasing with increase in stitch density and number of ply. The proposed elliptical model have been compared with other recent rectangular profile based models, it is found that the propose model is more accurate and generalised with less error %, as compared to other models across the different fabric types. Also there is a strong correlation obtained between practical (actual) thread consumption and predicted from model
An experimental parametric analysis on performance characteristics in wire EDM of Inconel 718
No full textWire cut electrical discharge machining was identified as a good alternative to conventional machining for machining
super alloys that possess low machinability. In the present work, effect of wire tension along with current, pulse on time,
and pulse off time on the performance characteristics such as spark gap, surface roughness, amplitude of wire vibration,
and cutting rate were studied in wire cut electrical discharge machining of Inconel 718 metal. Experiments were con�ducted at five levels of the process parameters as per orthogonal array of L25 and their results were collected. These experimental results were analyzed and the interaction effect of wire tension along with current, pulse on time, and pulse off time on performance characteristics was studied using analysis of variance. Response models were developed for the four responses in terms of process parameters and the accuracy of such models was tested. In addition to the above studies, effect of the wire displacement on the kerf size, cutting rate was studied. Spark energy was also estimated for all the experiments and its effect on the performance characteristics was studied. The response models developed in this study were able to predict the experimental results i.e. amplitude of wire vibration, surface roughness, cutting rate, and spark gap with an accuracy of R2 values of 1.0, 0.96, 0.88, and 0.99, respectively. Interaction effect of current and wire tension was found to have the most significant effect on the amplitude of cutter vibration and surface roughness
Experimental and 3D FEM-ANN based analysis and prediction of cutting forces, tool vibration and tool wear in boring of TI-6AL-4V alloy
No full textIn this work, accurate 3D finite element models were developed to study and predict machining characteristics like tool vibration, tool wear, surface roughness, cutting force and thrust forces in the boring of Ti-6Al-4V alloy. Experiments were conducted on the proposed metal using carbide inserts at three levels of spindle speeds, depth of cuts and feed rates and experimental results were collected. Numerical simulation was carried out using Deform 3D software. Johnson-cook material model was also used in simulation to predict the machining characteristics. A Usui’s wear model was taken in simulation to
calculate tool wear at different working conditions. Experimental data of the five machining characteristics were analysed using analysis of variance to identify the most
significant parameters. Cutting speed, depth of cut and feed rate were found to be the most significant parameters. Simulated results of the machining characteristics were compared with the experimental data and found in a good agreement between them. An Artificial neural network (ANN) model was also developed and trained with the experimental data to validate the results. FEM simulation models provide relevant
machining information without conducting experimentation for any metal
The best suitable alternative to diesel in a compression ignition engine between waste plastic oil and waste tire oil blends with diesel
No full textDepletion of conventional fossil fuels due to their increased consumption and the stringent emission norms, urge us to search alternative fuels for automotive engines. Alongside, serious challenge posed to the environment by the waste plastic in terms of its nondegradability is threatening the human sustainability. Both these issues can be addressed by converting the waste plastic into useful energy. In the present article, blends of diesel and oils derived from waste plastic and waste tire were used in a diesel engine, without any engine modifications to study the effect of blending waste plastic oil and waste tire oil to diesel up to 10% on the performance and
combustion characteristics of the engine. Blending the pyrolysis oils to 10% with diesel could not improve the thermal efficiency but the change in the brake specific fuel consumption was to significant level. However, plastic oil-diesel blend yielded almost same brake specific fuel consumption which conveys that it is better to blend plastic oil rather than tire oil. But, the
engine operation in case of P10 would not be as smooth as that in case of T10 and diesel owing to the higher rate of pressure rise of P10
A study on effect of dead metal zone on tool vibration, cutting and thrust forces in micro milling of Inconel 718
No full textInconel 718 is a nickel-based super alloy, its characteristics pose more complex in micro machining. Aim of the present study is to investigate effect of process parameters and tool parameters on the dead metal zone (DMZ) geometry and length of shear plane and further on cutting force, thrust force and amplitude
of cutter vibration. In the present study, mechanistic models were integrated with finite element method (FEM) simulation to predict cutting force and thrust force in micro milling of Inconel 718. Numerical simulation was carried out to estimate size of DMZ and its angles for all the experiments. Simulation
results were used in the mechanistic models to estimated cutting force and thrust force. Series of ex�periments were carried out on the Inconel 718 at different levels of process and tool parameters and cutting forces were measured. Comparison between the predicted values of cutting forces and thrust
forces with experimental results shown a good agreement. Effect of process and tool parameters on size of DMZ and length of shear plane was studied. Further, effect of DMZ and length of shear plane on cutting force, thrust force and amplitude cutter vibration was studied. Feed per tooth and cutter nose radius have significant effect on length of shear plane and length of DMZ side respectively. The parameters were optimized as 4500 rpm of cutting speed, 10 mm per tooth of feed, 0.12 mm of cutter nose radius and 6.8485� of rake angle for minimum side length of DMZ and length of shear plane in order to reduce
cutting force, thrust force and amplitude of cutter vibration
Deep CNN: A machine learning approach for driver drowsiness detection based on eye state
No full textDriver drowsiness is one of the reasons for large number of road accidents these days. With the advancement in Computer Vision technologies, smart/intelligent cameras are developed to
identify drowsiness in drivers, thereby alerting drivers which in turn reduce accidents when they are in fatigue. In this work, a new framework is proposed using deep learning to detect
driver drowsiness based on Eye state while driving the vehicle. To detect the face and extract the eye region from the face images, Viola-Jones face detection algorithm is used in this work. Stacked deep convolution neural network is developed to extract features from dynamically identified key frames from camera sequences and used for learning phase. A SoftMax layer in CNN classifier is used to classify the driver as sleep or non-sleep. This system alerts driver with an alarm when the driver is in sleepy mood. The proposed work is evaluated on a collected dataset and shows better accuracy with 96.42% when compared with traditional CNN. The limitation of traditional CNN such as pose accuracy in regression is overcome with the proposed Staked Deep CN
Investigating the Properties of Wet-Laid Nonwoven Made from Mechanically Fibrillated Jute Fiber
Get PDFThe jute fibers have been mechanically fibrillated, and the wet-laid nonwoven fabrics have been manufactured using these fibers at two different concentrations of binder. The mechanically fibrillated states from non-fibrillated and partially fibrillated to highly fibrillated are considered at different lengths of fibers such as 5 and 10 mm to 15 mm. The tensile strength, air permeability, and the acoustic property of formed web are analyzed. There is no significant effect of fiber fibrillation found on the tensile properties of the manufactured wet-laid web, while there is an effect of fiber fibrillation observed on air permeability
Cyclotriphosphazene nanofber‑reinforced polybenzoxazine/epoxy nanocomposites for low dielectric and fame‑retardant applications
No full textAbstract
In the present work, a halogen-free fame-retardant cyclotriphosphazene nanofber�reinforced polybenzoxazine/epoxy (PBZ/EP/PZT) hybrid nanocomposites have been developed and characterized. Initially, equimolar quantities of benzoxazine and the
epoxy matrix is blended and varying weight percentages (0, 0.5, 1.0 and 1.5 wt%) of PZT nanofber are reinforced to obtain hybrid nanocomposites. It was observed that PBZ/EP/PZT nanocomposites possess higher values of glass transition temperatures
(Tg—208 °C) and displayed enhanced thermal stability with high char yields than those of neat matrix. The fammability characteristics of the nanocomposites were studied on the basis of the LOI, UL-94 burning experiments as well as the analy�sis of residual chars of the tested bars after burning. The V-0 classifcation for the
nanocomposites indicates that the incorporation of PZT nanofber (1.5 wt%) imparts enhanced fame retardancy to the PBZ/EP matrix. The dielectric properties of these nanocomposites have been studied at 1 MHz over the temperature range between
30 and 200 °C. Data resulted from thermal, fame-retardant and dielectric studies indicate that the composite materials can be considered as the potential candidate for thermally stable fre and heat resistant, dielectric sealants, and encapsulants in electronic application