Showing papers by "Sir Padampat Singhania University published in 2019"

Non-edible vegetable oil-based feedstocks capable of bio-lubricant production for automotive sector applications-a review.

Abstract: Fossil fuel resource is on the draining stage which leads to an increment in the cost of the petroleum products. Nowadays, research is focused on the development of environment-friendly lubricants which are derivatives of renewable sources. Bio-lubricants based on non-edible oil sources are environmentally friendly because they are non-hazardous and biodegradable and no emission of toxic gases were detected when they are used. This study involves the characterizations and advantages, as well as utilization of inedible plant oil-driven bio-lubricants as an alternative for tribological applications. This report also presents the status of the global lubricant market as well as the potential outlook of the bio-lubricants for their future usage. Non-edible plant oil-driven bio-lubricants bear high viscosity, high lubricity, and high viscosity index which can enhance the equipment service life and deserve the ability to carry the high load and results in a minimum amount of metal traces during combustion while applied to engines. Beside their advantages, some of the disadvantages are also there which can be addressed by the employment of certain additives available according to the applications. The detailed study about the different additives utilized during their use in the internal combustion engine is also described in detail during this study. This study provides a detailed description of the possibilities associated with bio-lubricant based on non-edible oil feedstocks to the automotive sector applications.

Shape Memory Alloy (SMA) as a Potential Damper in Structural Vibration Control

Abstract: The utilization of smart structure technologies to mitigate the vibrations of structures have been the prime focus of numerous scientists involved in the area of structural vibration control. Smart materials serve multiple purposes like that of sensing, actuation and also exhibit the capability of modifying and adjusting the structural behavior when subjected to sudden external shock like earthquake or blast. Smart materials are basically defined as those materials possessing special features and can be applied in the design of structures to enhance the structural performance. Shape Memory Alloys (SMAs) are the most promising and prominent class of smart materials. When strained beyond 6–8%, SMAs possess the ability to regain its original shape. Reversible phase transformation is responsible for such sort of shape recovery. It can be either stress induced (pseudo-elasticity) or temperature induced (shape memory effect). This paper shows the potential of Nitinol (alloy of Ni and Ti) SMA damper to control structural vibrations when subjected to underground blast through a detailed computational study by considering a two-story steel frame as an example problem. Different bracing configurations of the damper are taken into account. A comparative study showing the effectiveness SMA braced damper over the conventional steel bracing is also carried out.

Experimental Investigation and Modeling of Surface Finish in Argon-Assisted Electrical Discharge Machining Using Dimensional Analysis

Abstract: This study investigates the use of argon gas-assisted electrical discharge machining (AGAEDM) of high carbon high chromium die steel. Compressed argon gas in die-sinking EDM under controlled conditions was used to evaluate the surface roughness (SR). The influence of process parameters, viz., discharge current, pulse-on time, duty cycle, tool rotation, and discharge gas pressure, on SR has been investigated as well. Analysis of variance was applied to determine the significant factors affecting SR. In the course of this investigation, a semi-empirical model has been developed to determine SR through dimensional analysis while applying the AGAEDM process. The experimental and predicted values, gathered through the semi-empirical model, have been found to be in accord with each other. The mean error between the predicted and the experimental values was less than 5%. A comparison was performed between the RSM and semi-empirical models. The semi-empirical model was found to predict responses most precisely as compared to RSM model. In this connection, surface morphology analysis has also been done by using a scanning electron microscope in the machined specimens. The energy-dispersive X-ray and X-ray diffraction examination were used to study the relocation of different elements and development of compounds on the surface of the machined specimen.

Effect of alumina nanoparticles as additive on the friction and wear behavior of polanga-based lubricant

Abstract: Many researchers have tried to improve the tribological characteristics of lubricants to decrease coefficients of friction and wear rates. Recently, nanoparticles have emerged as a new kind of additive because of their size, shape, and other properties. A nanolubricant is a new kind of engineering lubricant made by dispersing nanoparticles in a lubricant. Investigations related to the tribological characteristics of lubricants with addition of nanoparticles are reviewed herein. The paper focuses on the effects of the nanoparticle concentration on the tribological performance during oil lubrication. Specifically, measurements of physicochemical properties and tribological analysis were performed along with morphological study of the nanoparticles. The mechanisms of lubrication involving nanoparticles are discussed based on data collected from the experimental analysis and compared with work in literature. The effect of varying the concentration of alumina (Al2O3) nanoparticles in polanga oil on the coefficient of friction and wear was evaluated. The minimum coefficient of friction and wear were observed at 0.075% concentration, but increased at 0.1% concentration. A smooth surface of the pin was observed at 0.075% nanoparticle concentration in comparison with polanga-based oil. The maximum total acid number change was obtained for the 0.1% concentration. The wear scar obtained during the test was also minimum for the 0.075% concentration, and a better surface was observed for this concentration. In terms of future prospects, similar work based on nanoparticles with different shape and size could be carried out for other nonedible oils.

Comparative study of statistical and soft computing-based predictive models for material removal rate and surface roughness during helium-assisted EDM of D3 die steel

Abstract: This research work proposes mathematical models, based on artificial neural network (ANN) with back-propagation algorithm, adaptive neuro-fuzzy inference system (ANFIS) and response surface methodology (RSM), for prediction of material removal rate (MRR) and surface roughness (SR) of helium-assisted electrical discharge machining of D3 die steel. The helium gas-assisted die-sinking EDM with perforated electrode was carried out by an EDM machine. For the present experimental work, discharge current, pulse on time, duty cycle, electrode rotation and discharge gas pressure were selected as process factors, while MRR and SR were chosen as process responses. Analysis of variance (ANOVA) was done to examine the adequacy of the developed model. The fit summary confirmed that the quadratic model is statistically appropriate and the lack of fit is insignificant. Root mean square error and absolute standard deviation, obtained through RSM, were also used for developing the model and for its predicting abilities through ANN and ANFIS. The experimental and predicted values of MRR and SR during the process, obtained by RSM, ANN and ANFIS, were found to be in accord with each other. However, the ANFIS technique proved to be more fitting to the responses as compared to the ANN and the RSM. The optimum value of the MRR at 28.54 mg/min and the SR at 4.21 µm was obtained with optimal process parameters by optimization of developed statistical models using genetic algorithm.

Friction and wear characterization of modified jatropha oil (Jatropha Curcas) using pin on disc tribometer

Abstract: Based on the environmental concerns related to the pollution caused by the vehicles and the demand for an alternative to the conventional lubricant resulted in the studies to be conducted which are...

Status of biofuel in India with production and performance characteristics: a review

Abstract: With the growing rate of energy consumption around the world and increase in per capita consumption of the energy, both energy demand, and energy security are major concerns for all the economies a...

Effect of fuel injection pressure and timing on Polanga (Calophyllum Inophyllum) biodiesel blends for engine performance and emissions analysis

Abstract: To evaluate the performance and emissions of a diesel engine fuelled by biodiesel blends produced from polanga oil, the engine was run to investigate the effects of injection pressure and t...

Extensions of the classical theorems for very well-poised hypergeometric functions

Abstract: The well-known classical summation theorems due to Dougall and certain transformation formulas due to Whipple and Bailey for very well-poised hypergeometric functions are extended by introducing two additional pairs of numerator and denominator parameters with unit differences. These results have been derived with the help of well-known Bailey’s transform and a recently added extension of the Saalschutz theorem in the literature. The special cases of the results are shown to give some contiguous and parameters with integer differences type extensions of numerous hypergeometric summations. Applications of the results to a number of very interesting and general summations for Ramanujan type series involving $$\pi $$ and some other constants are also discussed.

Effect of sliding speed and temperature on the tribological behavior of pongamia oil-based blended lubricant

Abstract: The increase in industrialization has created the demand for petroleum-based lubricants throughout the world. The decrease in availability of mineral oils and their hazards related to the environme...

Effect of addition of copper nanoparticles on the tribological behavior of macadamia oil at different sliding speeds

Abstract: Environment degradation and non-biodegradability are the major problems associated with mineral oil-based lubricants. Non-edible vegetable oils are one of the suitable substitutes for the mineral o...

Analysis of the Behavior of High-Rise Structures with Viscoelastic Dampers Installed at Various Locations

Abstract: It is essential to analyze the behavior of each and every tall structure in the perspective of structural engineering when subjected to severe ground motion or earthquake. Vibratory forces are produced due to the result of such earthquakes at the base of the structure. Oscillations are created in buildings as a result of these vibrations. Such oscillations may cause severe damage to the structure. From the ground level, the vibrations get transmitted up to the top of the building and since the structural mass which creates lateral forces on the frame, the moment resisting capacity gets diminished for that of building components such as columns, beams, etc. This paper gives an idea of the different research works executed on a multi-storey building frame by taking various parameters into account. It explains the results of a study on the seismic behavior of a tall structure (G+15) installed with a damper. From a previously conducted experiment, it has been expressed that the stiffness and the strength of the structure enhances considerably with the use of such dampers. The current work aims to analyze the behavior of a multi-storeyed building for the most efficient location of viscoelastic damper in the structural system. A standard finite element software is used to carry out the analysis. Various parameters like lateral storey drift, base shear, time period, modal shapes, etc., are being analyzed and evaluated for the damper being placed at different locations.

Vibration Monitoring of Rotating Electrical Machines: Vibration Monitoring

Abstract: Vibration monitoring is applicable to all rotating machines for defect detection and diagnosis. Measurement and analysis of vibration have also been applied to rotating electrical machines with the objective of fault detection and predictive maintenance. The sources of vibration generation in electrical rotating machines, both electrical and mechanical, have been identified in this chapter. The vibratory characteristics associated with these defects have also been discussed in detail. Analyses of vibratory signatures in time domain, frequency domain, and time frequency domain have been dealt with, and different features and indicators associated with each domain have been described. The details of vibration measurement schemes such as transducers, different signal conditioning elements, as well as characteristics of recording and display devices and their applicability to electrical machines have also been included in the chapter.

Predictive analysis of surface roughness in argon-assisted EDM using semiempirical and ANN techniques

Abstract: This experimentation explores the utilization of argon-assisted electrical discharge machining (AAEDM) of high-carbon high-chromium die steel. High-pressure argon gas in conventional EDM was utilized to assess the surface roughness (SR). Analysis of variance was connected to decide the critical parameters influencing SR. In this study, a mathematical model has been instigated to get to know SR by using Buckingham pi-theorem while applying the AAEDM process. The fit summary confirmed that the quadratic model is statistically appropriate, and the lack-of-fit is insignificant. Root-mean-square error and absolute standard deviation, obtained through response surface method, were also used for developing the model and for its predicting abilities through ANN. The experiment and anticipated estimates of SR during the process, obtained by dimensional analysis and ANN, were found to be in accord with each other. However, the ANN technique proved to be more fitting to the response as compared to the dimensional analysis.

Low energy electron and positron impact differential cross sections for the ionization of water molecules in the coplanar and perpendicular kinematics.

Abstract: We report here triply differential cross sections (TDCSs) for 81 eV electron and positron-impact ionization of the combined (1b 1 + 3a 1 ) orbitals of the water molecule by using the second-order distorted wave Born approximation (DWBA2) for ejection electron and positron energies of 5 eV and 10 eV and different momentum transfer conditions. The electron-impact TDCS will be compared with the experimental data measured by Ren et al. [Phys. Rev. A 95, 022701 (2017)] and with the molecular 3-body distorted wave (M3DW) approximation results in the scattering plane as well as the perpendicular plane. The DWBA2 results are in better agreement with the experiment than the M3DW results for the scattering plane, and the M3DW results are somewhat better for the perpendicular plane. This observation is explained in terms of collision interactions. The electron and positron TDCSs are indistinguishable in the scattering plane. In the perpendicular plane, the positron results are similar in shape, but smaller in magnitude. However, the difference reduces with increasing projectile scattering angle and increasing ejected electron energy.

Theoretical study of (e, 2e) triple-differential cross sections for DNA component ionization by electrons and positrons

Abstract: We report in this work a theoretical study of the electron- and positron-induced ionization of DNA components, namely, the thymine and the tetrahydrofuran (THF) molecules. Triply differential cross sections (TDCSs) are calculated in a coplanar geometry by using the second order distorted wave Born approximation (DWBA2). The current calculations exhibit a satisfactory agreement with the experimental measurements performed at a projectile energy E 0 = 250 eV for electron impact ionization of specific target orbitals of thymine and THF. Besides, significant differences were observed between electron and positron TDCSs.

Deep Learning Technique for Serving Visually Impaired Person

Abstract: The concepts like machine learning and artificial intelligence have been adopted in the real time applications due to their exceptional features and absolute algorithmic advantages. Deep learning is a one of research area in machine learning totally concerned with algorithmic techniques inspired by the structure and functions of the human neural system. It has created a niche for itself in learning processes involving multiple level of data representation and abstraction, thereby helping in making sense of data having several forms such as images, sound and text and finally revealing the feature level hierarchies. Deep learning techniques show higher level of accuracy and robustness in results and are independent of human crafted features. The Paper is divided into three main parts, first part identifies the need to develop the system for Visually Impaired person. Second part deals about various Deep learning techniques used for computer vision and object detection. And third part consist the proposed system for serving visually impaired person in doing daily chores.

Text Mining to Understand Major Keywords Explaining Sentiments of Travelers Using Travel Related Online Services in India

Abstract: This paper aims to explain and elaborate integration of two words netnography and mining. Netnography has been accepted and used as universal tool for performing online ethnography in various fields. This paper also focuses on the relevance of text mining in consumer research and how it is used to analyze consumer opinions on online travel related services using text mining tool named RapidMiner. The results obtained offers clear understanding of key terms and tokens which help us identify various words explaining satisfaction of travelers through the use of text based mining along with travel ratings collected via reviews and referral site, and social media platforms in India.

A Tree-Based Graph Coloring Algorithm Using Independent Set

Abstract: This paper introduces a tree data structure-based graph coloring algorithm. Algorithm explores vertices in the tree form to finds maximal independent set, than these independent sets are colored with minimum colors. Proposed algorithm is tested on various DIMACS standard of graph instances. Algorithm is design to solve graph coloring problem for high degree graphs, i.e. the proposed algorithm is highly efficient for those graphs which has number of edges to number of vertices ratio is very high. Worst and best case time complexity of proposed algorithm is also discussed in this paper.

Mapping of Disease Names to Standard Codes for Effective EHR System in India

Abstract: Ministry of health and family welfare (Govt of India) have recommended some guidelines for effective adoption of (Electronic Health Records (EHR) In these guidelines various health record standards are also recommended Electronic Health Record is need of the time in India Successful treatment methods are available in India The Health care is provided in different hierarchy and all service providers are involved at each hierarchy The hierarchy is distributed among rural, semi urban and urban sector Health care service is provided by Auxiliary Nurse Midwifery (ANM), Accredited Social Health Activist (ASHA), Primary Health centres, Govt Medical Officers and general practitioners and specialist in relevant area of treatment This paper speaks about providing the EHR Model with recording health information using standards recommended by National electronic Health record authority (NeHA)

Multiple Image Encryption with Fractional Hartley Transform and Robust Chaotic Mapping

Abstract: In this paper, we present a simple yet highly robust mechanism for multiple image encryption with optical transformation. A fractional order Hartley transform framework along with secret reversible integer transform (RIT) is used to decorrelate the images. The selection of fractional orders is based on a robust chaotic mapping. Optical transforms support fast and parallel processing but have limitation in digital implementation due to complex coefficients. We present a paradigm where complexity is completely eliminated at each security level to overcome the need of time consuming phase retrieval algorithms. The amalgamation of chaos further make it a highly sensitive and secure technique. This method gives optimum results with almost uniform histogram and lossless recovery of data which is otherwise limitation of optical transforms whose energy is concentrated at the center.

An Image Texture based approach in understanding and classifying Baby Sign Language

Abstract: A sign language is a mode of communication in which the intent of the message or the message itself is conveyed through body postures or the movement of the parts of the body like head, eyebrows and cheeks etc. Every expression is distinct and has distinguishable parts of language, its grammatical content fully displayed through gestures. There are more than three hundred sign languages used in the world. The baby sign language is a method of communication between the mothers and their toddlers by means of gestures, clearly expressing their emotions and desires. In the present research work study of the existing literature has been carried out and then prepared a data set of still jpeg images for 60 odd baby signs, performed GLCM(Gray Level Co-Occurrence Matrix) based feature extraction, then performed classification of gestures using KNN and Random Forest based machine learning algorithms. A classification accuracy of 73% has been achieved on the dataset prepared.

Flower Pollination Optimization and RoI for Node Deployment in Wireless Sensor Networks

Abstract: Wireless Sensor Network (WSN) most popular area of research where lots of work done are in this field. Energy efficiency is one of the most focusing areas because the lifetime of the network is the most common issue. Many algorithms work for cluster and these algorithms form cluster either distance or neighbor node. In our study, we focus on node deployment approach and after that, we focus on routing algorithm. In the Wireless Sensor Network, the node placement is the essential part for the proper communication between the sensor nodes and Base Station (BS). For better communication nodes should be aware of their own or neighbor node’s location. Better optimization of resources and performance improvement are the main concern for the Wireless Sensor Network. Optimal techniques should be utilized to place the nodes at the best possible locations for achieving the desired goal. For node placement, flower pollination optimization is used to generate the better result. Base Station is responsible for the communication of nodes with each other and it should be reachable to nodes. For this Region of Interest (RoI) is helpful to choose the best location. Placement of Base Station in the middle is the suitable place for the static nodes deployment and there should be another strategy for the dynamic environment. Nodes should be connected to each other for the transmission of data from the source to Base Station properly. From the MATLAB simulation, it has been shown that the proposed methodology improves the network performance in terms of dead nodes, energy and the various packets sent to Base Station.

A Framework Design for Human Authentication Based on Biometric Fusion Mechanism

Abstract: Biometrics has been a rising field of research in the present years and was concerned by using physical characteristics, for instance, those in light of iris or retinal looking at, stand up to affirmation, fingerprints, or voices of individuals to be recognized. Applying low assurance devices palm print is adequately got moreover it is specific, diverged from distinctive systems, for instance, one of a kind finger impression or iris palm print has favored and furthermore it fuses additional features, for instance, basic lines. In this paper a blend of Face , Fingerprint and Palm print is proposed in which the outcomes are computed in view of EER (Error Estimation Rate) and GAR (Genuine Acceptance Rate).

Performance Study of Gas-Assisted Electric Discharge Machining on Carbon–Chromium Die Steel

Abstract: The present study focuses on studying the effect of liquid cum gas as dielectric during Electric Discharge Machining (EDM) of carbon chromium die steel. In this work, a hybrid process of EDM employing both liquid (commercial kerosene oil) and gas (compressed helium gas) as dielectrics in die-sinking EDM has been explored. Experimentation has been done to the study effect of process factors like discharge current, pulse on time, duty cycle, tool rotation and discharge gas pressure on material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). Further, a comparative study of conventional EDM with liquid dielectric and hybrid EDM with liquid cum gaseous dielectric has been performed. It has been found that high MRR, low EWR and low SR are obtained when liquid cum gaseous dielectric was used as compared to conventional EDM with liquid dielectric. Analysis of surface morphology reveals that the formation of recast layer and surface cracks is less on specimen machined with liquid cum gaseous dielectric with respect to specimen machined with conventional liquid dielectric. The results show that the use of compressed helium gas has a positive impact on the machining performance. Superior surface finish and higher MRR reveal the possible implementation of the process in modern machining.