Showing papers by "Mepco Schlenk Engineering College published in 2018"

Characterization of New Natural Cellulosic Fiber from Heteropogon Contortus Plant

Abstract: Natural fibers are one of effective substitute for switching artificial fiber and concentrating to reinforce polymer matrixes due to their decomposable character. This study was implied to ...

Physicochemical and Thermal Properties of Ceiba pentandra Bark Fiber

Abstract: Owing to their low weight-to-high strength ratio and recyclable features, the natural fibers are the most potential choice in place of synthetic fibers and been used as reinforcement materials in polymer matrix composites. Characterization of Ceiba pentandra bark fibers (CPFs) such chemical analysis, Fourier Transform-Infrared Analysis (FTIR), X-ray diffraction, thermogravimetric analysis, and Differential thermogravimetric analysis (DTG) analysis has analyzed. CPFs contain 60.9% (w/w) of cellulose, 17.5% (w/w) of hemicellulose, and 23.5% (w/w) of lignin. Besides, its density and crystallinity index are 682 kg m−3 and 57.94%, respectively. TG and DTG analysis discovered that CPFs are thermally stable up to 342.1°C. Further, all the resources of CPFs ensured that it can be an excellent alternative for synthetic fibers in polymer matrix composites.

Characterization of natural cellulosic fiber from Epipremnum aureum stem

Abstract: The natural fiber Epipremnum aureum was extracted from its plant. E. aureum fibers (EAFs) were investigated by chemical analysis, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction, ...

A numerical study on the effect of various combustion bowl parameters on the performance, combustion, and emission behavior on a single cylinder diesel engine

Abstract: A numerical study was carried out to study the effect of various combustion bowl parameters on the performance behavior, combustion characteristics, and emission magnitude on a single cylinder diesel engine. A base combustion bowl and 11 different combustion bowls were created by varying the aspect ratio, reentrancy ratio, and bore to bowl ratio. The study was carried out at engine rated speed and a full throttle performance condition, without altering the compression ratio. The results revealed that the combustion bowl parameters could have a huge impact on the performance behavior, combustion characteristics, and emission magnitude of the engine. The bowl parameters, namely throat diameter and toroidal radius, played a crucial role in determining the performance behavior of the combustion bowls. It was observed that the combustion bowl parameters, namely central pip distance, throat diameter, and bowl depth, also could have an impact on the combustion characteristics. And throat diameter and toroidal radius, central pip distance, and toroidal corner radius could have a consequent effect on the emission magnitude of the engine. Of the different combustion bowls tested, combustion bowl 4 was preferable to others owing to the superior performance of 3% of higher indicated mean effective pressure and lower fuel consumption. Interestingly, trade-off for NO x emission was higher only by 2.85% compared with the base bowl. The sensitivity analysis proved that bowl depth, bowl diameter, toroidal radius, and throat diameter played a vital role in the fuel consumption parameter and emission characteristics even at the manufacturing tolerance variations.

Nature inspired discrete firefly algorithm for optimal mobile data gathering in wireless sensor networks

Abstract: Nowadays wireless sensor networks enhance the life of human beings by helping them through several applications like precision agriculture, health monitoring, landslide detection, pollution control, etc. The built-in sensors on a sensor node are used to measure the various events like temperature, vibration, gas emission, etc., in the remotely deployed unmanned environment. The limited energy constraint of the sensor node causes a huge impact on the lifetime of the deployed network. The data transmitted by each sensor node cause significant energy consumption and it has to be efficiently used to improve the lifetime of the network. The energy consumption can be reduced significantly by incorporating mobility on a sink node. Thus the mobile data gathering can result in reduced energy consumption among all sensor nodes while transmitting their data. A special mobile sink node named as the mobile data transporter (MDT) is introduced in this paper to collect the information from the sensor nodes by visiting each of them and finally it sends them to the base station. The Data collection by the MDT is formulated as a discrete optimization problem which is termed as a data gathering tour problem. To reduce the distance traveled by the MDT during its tour, a nature-inspired heuristic discrete firefly algorithm is proposed in this paper to optimally collect the data from the sensor nodes. The proposed algorithm computes an optimal order to visit the sensor nodes by the MDT to collect their data with minimal travel distance. The proposed algorithm is compared with tree-based data collection approaches and ant colony optimization approach. The results demonstrate that the proposed algorithm outperform other approaches minimizing the tour length under different scenarios.

Production of Garcinia gummi-gutta Methyl Ester (GGME) as a Potential Alternative Feedstock for Existing Unmodified DI Diesel Engine: Combustion, Performance, and Emission Characteristics

Abstract: In the current scenario, the use of fossil fuel is increasing sharply in the global energy store and playing a highly hazardous role in the ecological system, besides contributing to global warming. Biodiesel is one of the most credible keys for addressing this issue. The present experimental study has been done on Kirloskar make TAF-1 model compression ignition (CI) engine, powered by Garcinia gummi-gutta methyl ester (GGME) biodiesel and its blends. Experimental results were correlated with those of mineral diesel. To start with, biodiesel was synthesized from Garcinia gummi-gutta seed oil, assisted by novel Thermomyces lanuginosus lipase (TL) enzyme linked biocatalyst transesterification. Using nanotechnology, ferric oxide (Fe3O4) nanoparticles were prepared using the coprecipitation method. The TL enzymes were covalently linked with magnetic Fe3O4 nanomaterial, powered using the immobilization method and characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier-transform infrared spectroscopy (FTIR) analyses. A large quantity of TL functional groups attached with Fe3O4 magnetic nanoparticle in reaction with an active functional group in oils leads to improved efficiency and effective recycling via an external magnetic field. At the end of 74 h of reaction time with confined optimization conditions, the transesterification process yielded 93.08 % GGME. All the physiochemical properties of GGME blends were investigated as per ASTM standards. Raw GGME was blended with mineral diesel in various proportions, namely B10, B20, B30, B40, and B100. The fuel blends were analyzed in terms of combustion, performance, and emission characteristics. Test results revealed B20 (20 % GGME + 80 % diesel) blend as on par with mineral diesel in terms of brake thermal efficiency (BTE), unburned hydrocarbon (UBHC), and carbon dioxide (CO2), followed by nitrogen oxides (NOx) and smoke emissions. At 100 % load, cylinder pressure, the heat release rate (HRR), brake specific energy consumption (BSEC), and carbon monoxide (CO) emissions of B20 were significantly lower than mineral diesel. Overall, B20 was showcased as a reliable alternative fuel for the CI engine.

Rice husk as nanoadditive in diesel–biodiesel fuel blends used in diesel engine

Abstract: The fossil fuels are gradually reducing due to the increase in energy users and prices. In India the biodiesel is one of the best available renewable energy sources to satisfy the energy demand and environmentally friendly nature. In the present work, non-edible feedstock of pongamia pinnata seed oil is used for biodiesel production. The biodiesel was prepared by transesterification method with methanol in the existence of KOH as catalyst, and in addition of rice husk (RH) nano-organic additive is used in biodiesel production. The RH nanoparticles are characterized by using scanning electron microscopy, transmission electron microscopy (TEM), X-ray diffraction and the CHNS elemental analysis. TEM results confirm that the RH nanoparticle has size of around 20 nm. The pure diesel, 20% biodiesel 80% diesel and 20% biodiesel 80% diesel with 0.1% RH nanoparticles are used as fuels in the diesel engine. The performance and emission characteristics of the IC engine are studied. The results showed that the RH nanoparticles added with pongamia seed oil methyl ester improve the brake thermal efficiency, reduced CO, HC emissions and lowered the NOx emissions.

Improved Cluster Based Data Gathering Using Ant Lion Optimization in Wireless Sensor Networks

Abstract: Wireless sensor networks play a vital role in this digital world through various applications in several domains. The sensor networks are heavily energy constrained due to limited battery power. Therefore, the energy has to be optimally exploited to improve the lifetime and throughput of the network. Among the various existing approaches, cluster based routing algorithms are more popular for its balanced and less energy consumption throughout the communication network. Improper clustering often results in numerous individual nodes (sensor nodes which are not a part of any clusters). The individual nodes will send their information to the base station with high transmission power which heavily impacts the lifetime of the sensor network. Hence, a heuristic Ant Lion Optimization clustering algorithm for wireless sensor network is proposed in this paper. In the proposed work, the cluster head selection is modeled as a fitness function of the Antlion optimization algorithm, which improves the network performance. Also, a Discrete Ant Lion Optimization algorithm is applied to find the optimal data gathering tour for a mobile sink with minimal data collection tour length. The Discrete Ant Lion optimization algorithm computes the optimal order for the mobile sink to visit the selected cluster head nodes and collects their data. The simulation results show that the proposed clustering scheme improves the network lifetime, network throughput and it also reduces the number of individual nodes when compared to existing algorithms. Also, the proposed cluster-based mobile data gathering using the Ant Lion Optimization algorithm produces an optimal tour for the mobile sink to collect data from the cluster head node with minimum data collection tour distance.

Finite-element simulation and validation of material flow in thermal drilling process

Abstract: Galvanized steel is broadly employed in metal roofing, air conditioning duct, support beams, construction materials, and domestic appliances, etc. In conventional drilling method has limitations such as asymmetrical holes, as well as formation of crack inside the hole made in sheet metal. This problem was entirely exterminated in thermal drilling (TD) process. In the course of TD process, the high temperature was developed due to rotational and feed rate of thermal drill into the workpiece. Owing to this reason, the thermal drill pierces workpiece effortlessly. However, in this process, workpiece deformation is very high; therefore, finite-element simulation is used to study the material flow which is challenging in experimental method. According to finite-element method (FEM), the finite-element analysis of TD process was conducted by the DEFORM-3D simulation software. The aim of this study is to conduct an experimental investigation of TD process on galvanized steel (GS), and then, it is compared to numerical results obtained from the FEM. Between experimental and FEM simulation of TD process, a good relationship was found.

Friction push plug welding in airframe structures using Ti-6Al-4V plug

Abstract: Friction push plug welding, a recent variation of friction welding process has tremendous applications in joining and repairing operations in aerospace and automotive engineering. The main objective of the present work demonstrates joining feasibility of high performance Ti-6Al-4V to low density AA2024 employed in passenger seat track, vertical stabilizers and wing spars of aircraft structures of aerospace applications. Mechanical testing is carried out to analyse the joint integrity and strength of Ti-6Al-4V/AA2024 joints. The microstructural aspects are investigated to study the bonding mechanism to obtain defect-free welds. SEM micrograph reveals the formation of different zones with significant reduction in grain size. EDX analysis confirms the formation of Ti3Al intermetallic compound which is less brittle. Appreciable impact strength of about 286.354 kJ/m2 indicates friction push plug welding as a promising candidate for joining of Ti-6Al-4V and AA2024 in airframe structures.

Electrochemical Machining of Aluminium Metal Matrix Composites

Abstract: High performance aluminium based metal matrix composites possess low machinability characteristic. Electrochemical machining (ECM) is one of the advanced machining processes, used for machining of these newly developed exotic materials. This article critically reviews the research work on experimental investigations on ECM of aluminium matrix composites. Besides, recently developed techniques such as abrasive assisted electrochemical machining, electrochemical grinding, electrochemical micromachining, and electrochemical drilling are explored in the processing of aluminium metal matrix composites.

Mechanical Properties of SiC, Al 2 O 3 Reinforced Aluminium 6061-T6 Hybrid Matrix Composite

Abstract: This paper contains the investigation of tensile, compression and impact characterization of SiC, Al2O3 reinforced Aluminium 6061-T6 matrix hybrid composite. Hybrid matrix composite fabrication was done by stir casting method. An attempt has been made by keeping Al2O3 percentage (7%) constant and increasing SiC percentage (10, 15, and 20%). After fabricating, the samples were prepared and tested to find out the various mechanical properties like tensile, compressive, and impact strength of the developed composites of different weight % of silicon carbide and Alumina in Aluminium alloy. The main objective of the study is to compare the values obtained and choose the best composition of the hybrid matrix composite from the mechanical properties point of view.

Deep Learning Techniques for Breast Cancer Detection Using Medical Image Analysis

Abstract: Breast cancer has the second highest mortality rate in women next to lung cancer. As per clinical statistics, 1 in every 8 women is diagnosed with breast cancer in their lifetime. However, periodic clinical checkups and self-tests help in early detection and thereby significantly increase the chances of survival. Invasive detection techniques cause rupture of the tumor, accelerating the spread of cancer to adjoining areas. Hence, there arises the need for a more robust, fast, accurate, and efficient noninvasive cancer detection system. In this work, an automated system is proposed for achieving error-free detection of breast cancer using mammogram. In this system, the deep learning techniques such as convolutional neural network, sparse autoencoder, and stacked sparse autoencoder are used. The performance of these techniques is analyzed and compared with the existing methods. From the analysis, it is observed that the stacked sparse autoencoder performs better compared to other methods.

Comparative analyses of biodiesel produced from jatropha and neem seed oil using a gas chromatography–mass spectroscopy technique

Abstract: Biodiesel from jatropha, neem and cottonseed were produced and their compositions were analyzed using gas chromatography–mass spectroscopy. The results revealed that the jatropha, neem and cottonse...

Optimal design of repetitive group sampling plans for Weibull and gamma distributions with applications and comparison to the Birnbaum–Saunders distribution

Abstract: In this paper, we propose a multiple deferred state repetitive group sampling plan which is a new sampling plan developed by incorporating the features of both multiple deferred state sampling plan...