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ANALYSIS AND OPTIMIZATION of INJECTION TIMING for AN ADVANCED COMPRESSED AIR ENGINE KIT
Kumar, Akshay,Kumar, Vasu,Gupta, Dhruv,Kumar, Naveen The Institute of Internet 2015 International journal of advanced smart convergenc Vol.4 No.1
Increasing air pollution levels and the global oil crisis has become a major hindrance in the growth of our automobile sector. Traditional Internal Combustion engines running on non-renewable fuels are proving to be the major culprit for the harmful effects on environment. With few modifications and also with assistance of few additional components current small SI engines can be modified into a pneumatic engine (commonly known as Compressed Air Engines) without much technical complications where the working fluid is compressed air. The working principle is very basic as adiabatic expansion of the compressed air takes place inside the cylinder pushing the piston downwards creating enough MEP to run the crank shaft at decent RPM. With the assistance of new research and development on pneumatic engines can explore the potential of pneumatic engines as a viable option over IC engines. The paper deals with analysis on RPM variation with corresponding compressed air injection at different crank angles from TDC keeping constant injection time period. Similarly RPM variation can also be observed at different injection pressures with similar injection angle variation. A setup employing a combination of magnetic switch (reed switch), magnets and solenoid valve is used in order to injection timing control. A conclusive data is obtained after detailed analysis of RPM variation that can be employed in newly modified pneumatic engines in order to enhance the running performance. With a number of benefits offered by pneumatic engine over IC engines such as no emissions, better efficiency, low running cost, light weight accompanied by optimized injection conditions can cause a significant development in pneumatic engines without any major alteration.
Development of Empirical Relations to Predict Ground Vibrations due to Underground Metro Trains
Naveen Kumar Kedia,Anil Kumar,Yogendra Singh 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.1
The vibration caused due to underground metro trains in densely populated urban areas and its adverse effect on the nearby structures and occupants is a growing concern for the policymakers and government bodies, demanding its rapid and correct assessment. Metro bodies in India use Research Designs and Standards Organisation guidelines similar to Federal Transit Administration guidelines for vibration assessment. However, in the guidelines, there is limited discussion on soil geotechnical properties, tunnel depth and axle load, which considerably affect the magnitude of train-induced ground vibration. This study focuses on developing easily comprehendible empirical relations to predict metro train-induced ground vibrations considering the effect of these parameters. Multiple non-linear regression is used to establish the empirical relations utilising the datasets generated from a two-dimensional train-track-tunnel-soil dynamic interaction (TTTSDI) finite element model. The TTTSDI model is based on the two-step methodology available in the literature and is validated with field measurement results of the Delhi metro sites. The developed empirical relations predicted the ground vibrations with maximum and minimum errors of 2.66% and 0.84%, respectively.
Kumar, Naveen,Borm, Jin-Hwan,Panwar, Vikas,Chai, Jangbom 한국정밀공학회 2012 International Journal of Precision Engineering and Vol.13 No.8
In this paper, a hybrid trajectory tracking controller is designed for redundant robot manipulators, consisting of RBF neural network and an adaptive bound on disturbances. The controller is composed of computed torque type part, RBF neural network and an adaptive controller. The controller achieves end-effector trajectory tracking as well as subtask tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the robot dynamics with no requirement of the offline training. The adaptive controller is used to estimate the unknown bounds on unstructured uncertainties and neural network reconstruction error. The overall system is proved to be asymptotically stable in the sense of Lyapunov. Finally, numerical simulation studies are performed on a 3R planar robot manipulator to show the effectiveness of the control scheme.
Naveen Kumar,김준동 한국진공학회 2021 한국진공학회 학술발표회초록집 Vol.2021 No.2
A unique RF superimposed DC sputtering technique was used to tailor the plasma during the sputtering process and to control the kinetics for the growth of a-IZO. The growth dynamics were controlled to achieve high optoelectronic properties, low surface roughness and low residual stress for flexible devices using statistical design of experiment approach. A common growth space was found to achieve a smooth surface in a stress-free and high optoelectronic merit a-IZO thin film. The grown a-IZO thin film was also used as a transparent electrode in a flexible Ga<sub>2</<sub>O<sub>3</sub> solar-blind photodetector.
Face and Eye Recognition on Gray Image using DWT with RBFSVM Method
Naveen Kumar Ahirwar,Manish Dixit 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6
Facial part detection or extraction shows the most important role in face and eye recognition. In this article proposed a new algorithm for Face and Eye Recognition (FER) using radial basis function support vector machine (RBFSVM) classifier. The discrete wavelet transform (DWT) is used for feature extraction and selection. For the experimental results, used JAFFE and ORL database. In this algorithm, extract face component like left eye, right eye, mouth and nose. In the preprocessing stage, apply median filtering for removing noise from an image. This stage improves the feature extraction process. Finding an image from the image components is a typical task in pattern recognition. The detection rate has reached up to100% for eye recognition and for face recognition is 90-96%. The proposed system estimates the value of precision and recall. This algorithm is compared with SVM and our proposed proved better than previous algorithms.
Molecular Characterization of Hallikar Breed of Cattle Using Microsatellite Markers
Kumar, S. Naveen,Jayashankar, M.R.,Nagaraja, C.S.,Govindaiah, M.G.,Saravanan, R.,Karthickeyan, S.M.K. Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.5
Molecular characterization of Hallikar, the native cattle breed of Karnataka, was undertaken using 19 cattle specific, highly polymorphic microsatellite markers recommended by FAO. The genomic DNA was subjected to PCR amplification and alleles were resolved through six per cent denaturing PAGE with a 10 bp DNA ladder followed by silver staining. Genotyping of animals was done based on allele size. The number of alleles ranged from three to nine with allele sizes ranging from 102 bp to 294 bp. These alleles were distributed in the frequency range between 0.0306 and 0.8673 in the population. The mean observed number of alleles was $6.368{\pm}1.4225$. The mean observed and expected heterozygosities were $0.7515{\pm}0.1734$ and $0.7850{\pm}0.1381$, respectively. The high heterozygosity observed implies presence of higher genetic variability within Hallikar breed. The PIC (Polymorphism Information Content) values ranged from 0.2322 (ETH152) to 0.8654 (ETH225). The percentage of polymorphic loci obtained was 100 as all the 19 microsatellite markers were found to be polymorphic. Except for ETH152, all the other loci had high PIC values, indicating that these markers are highly informative for characterization of Hallikar breed. The population was tested for Hardy-Weinberg equilibrium at 19 microsatellite loci, and at 74 per cent of the loci the population was found to be in disequilibrium.