Search results for: Siva Chandrasekaran
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 49

Search results for: Siva Chandrasekaran

49 Heavy Metal Pollution in Soils of Yelagirihills,Tamilnadu by EDXRF Technique

Authors: Chandrasekaran, Ravisankar N. Harikrishnan, Rajalakshmi, K. K. Satapathy M. V. R. Prasad, K. V. Kanagasabapathy

Abstract:

Heavy metals were considered as highly toxic environmental pollutants to soil ecosystem and human health. In present study the 12 heavy metals (Mg, Al, K, Ca, Ti, Fe, V, Cr, Mn, Co,Ni and Zn.) are determined in soils of Yelagiri hills, Tamilnadu by energy dispersive X-ray fluorescence technique. Metal concentrations were used to quantify pollution contamination factors such as enrichment factor (EF), geo-accumulation index (Igeo) and contamination factor (CF) are calculated and reported.

Keywords: soil, heavy metals, EDXRF, pollution contamination factors

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48 Heavy Metal Contamination in Sediments of North East Coast of Tamilnadu by EDXRF Technique

Authors: R. Ravisankar, Tholkappian A. Chandrasekaran, Y. Raghu, K. K. Satapathy, M. V. R. Prasad, K. V. Kanagasabapathy

Abstract:

The coastal areas of Tamilnadu are assuming greater importance owing to increasing human population, urbanization and accelerated industrial activities. sIn the present study, sediment samples are collected along the east coast of Tamilnadu for assessment of heavy metal pollution. The concentration of 13 selected heavy metals such as Mg, Al, Si, K, Ca, Ti, Fe, V, Cr, Mn, Co, Ni and Zn determined by Energy dispersive X-ray fluorescence (EDXRF) technique. In order to describe the pollution status, Contamination factor and pollution load index are calculated and reported. This result suggests that sources of metal contamination were mainly attributed to natural inputs from surrounding environments.

Keywords: sediments, heavy metals, EDXRF, pollution contamination factors

Procedia PDF Downloads 302
47 Application of Analytical Method for Placement of DG Unit for Loss Reduction in Distribution Systems

Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

Abstract:

The main aim of the paper is to implement a technique using distributed generation in distribution systems to reduce the distribution system losses and to improve voltage profiles. The fuzzy logic technique is used to select the proper location of DG and an analytical method is proposed to calculate the size of DG unit at any power factor. The optimal sizes of DG units are compared with optimal sizes obtained using the genetic algorithm. The suggested method is programmed under Matlab software and is tested on IEEE 33 bus system and the results are presented.

Keywords: DG Units, sizing of DG units, analytical methods, optimum size

Procedia PDF Downloads 434
46 Machine Learning Approach for Automating Electronic Component Error Classification and Detection

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 96
45 Computational Chemical-Composition of Carbohydrates in the Context of Healthcare Informatics

Authors: S. Chandrasekaran, S. Nandita, M. Shivathmika, Srikrishnan Shivakumar

Abstract:

The objective of the research work is to analyze the computational chemical-composition of carbohydrates in the context of healthcare informatics. The computation involves the representation of complex chemical molecular structure of carbohydrate using graph theory and in a deployable Chemical Markup Language (CML). The parallel molecular structure of the chemical molecules with or without other adulterants for the sake of business profit can be analyzed in terms of robustness and derivatization measures. The rural healthcare program should create awareness in malnutrition to reduce ill-effect of decomposition and help the consumers to know the level of such energy storage mixtures in a quantitative way. The earlier works were based on the empirical and wet data which can vary from time to time but cannot be made to reuse the results of mining. The work is carried out on the quantitative computational chemistry on carbohydrates to provide a safe and secure right to food act and its regulations.

Keywords: carbohydrates, chemical-composition, chemical markup, robustness, food safety

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44 Assessment of Treatment Methods to Remove Hazardous Dyes from Synthetic Wastewater

Authors: Abhiram Siva Prasad Pamula

Abstract:

Access to clean drinking water becomes scarce due to the increase in extreme weather events because of the rise in the average global temperatures and climate change. By 2030, approximately 47% of the world’s population will face water shortages due to uncertainty in seasonal rainfall. Over 10000 varieties of synthetic dyes are commercially available in the market and used by textile and paper industries, negatively impacting human health when ingested. Besides humans, textile dyes have a negative impact on aquatic ecosystems by increasing biological oxygen demand and chemical oxygen demand. This study assesses different treatment methods that remove dyes from textile wastewater while focusing on energy, economic, and engineering aspects of the treatment processes.

Keywords: textile wastewater, dye removal, treatment methods, hazardous pollutants

Procedia PDF Downloads 50
43 Fluorescence Sensing as a Tool to Estimate Palm Oil Quality and Yield

Authors: Norul Husna A. Kasim, Siva K. Balasundram

Abstract:

The gap between ‘actual yield’ and ‘potential yield’ has remained a problem in the Malaysian oil palm industry. Ineffective maturity assessment and untimely harvesting have compounded this problem. Typically, the traditional method of palm oil quality and yield assessment is destructive, costly and laborious. Fluorescence-sensing offers a new means of assessing palm oil quality and yield non-destructively. This work describes the estimation of palm oil quality and yield using a multi-parametric fluorescence sensor (Multiplex®) to quantify the concentration of secondary metabolites, such as anthocyanin and flavonoid, in fresh fruit bunches across three different palm ages (6, 9, and 12 years-old). Results show that fluorescence sensing is an effective means of assessing FFB maturity, in terms of palm oil quality and yield quantifications.

Keywords: anthocyanin, flavonoid fluorescence sensor, palm oil yield and quality

Procedia PDF Downloads 762
42 A Simplified, Fabrication-Friendly Acoustophoretic Model for Size Sensitive Particle Sorting

Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

Abstract:

In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS (Microelectromechanical Systems), microfluidics

Procedia PDF Downloads 132
41 Numerical Analysis on Triceratops Restraining System: Failure Conditions of Tethers

Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

Abstract:

Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

Procedia PDF Downloads 98
40 Rapid Green Synthesis and Characterization of Silver Nanoparticles Using Eclipta prostrata Leaf Extract

Authors: Siva Prasad Peddi

Abstract:

Silver nanoparticles were successfully synthesized from silver nitrate through a rapid green synthesis method using Eclipta prostrata leaf extract as a reducing cum stabilizing agent. The experimental procedure was readily conducted at room temperature and pressure, and could be easily scaled up. The silver nanoparticles thus obtained were characterized using UV-Visible Spectroscopy (UV-VIS) which yielded an absorption peak at 416 nm. The biomolecules responsible for capping of the bio-reduced silver nanoparticles synthesized using plant extract were successfully identified through FTIR analysis. It was evinced through Scanning Electron Microscope (SEM), and X-ray diffraction (XRD) analysis that the silver nanoparticles were crystalline in nature and spherical in shape. The average size of the particles obtained using Scherrer’s formula was 27.4 nm. The adopted technique for silver nanoparticle synthesis is suitable for large-scale production.

Keywords: silver nanoparticles, green synthesis, characterization, Eclipta prostrata

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39 Hybrid GNN Based Machine Learning Forecasting Model For Industrial IoT Applications

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 107
38 Electrospun Zinc Oxide Nanowires as Highly Sensitive Piezoelectric Transduction Elements for Nano-Scale Devices

Authors: K. Brince Paul, Nagendra Pratap Singh, Shiv Govind Singh, Siva Rama Krishna Vanjari

Abstract:

In this paper, we report optimized procedure for synthesizing highly oriented, horizontally aligned, Zinc oxide (ZnO) nanowires targeted towards developing highly sensitive piezoelectric transduction elements. The synthesis was carried out using Electrospinning technique, a facile, robust, low cost technique for producing nanowires. The as-synthesized ZnO nanowires were characterized by X-ray powder diffraction (XRD), Field Emission scanning electron microscopy (FESEM) and Energy-dispersive X-ray spectroscopy (EDX).The Piezoelectric behavior of these nanowires was characterized using Peizoelectric Force microscopy (PFM). A very high d33 coefficient of 23.1 pm/V obtained through the PFM measurements is an indicative of its potential application towards developing miniaturized piezoelectric transduction elements for nanoscale devices.

Keywords: electrospinning, piezoelectric, technique, zinc oxide

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37 Detection of Adulterants in Milk Using IoT

Authors: Shaik Mohammad Samiullah Shariff, Siva Sreenath, Sai Haripriya, Prathyusha, M. Padma Lalitha

Abstract:

The Internet of Things (IoT) is the emerging technology that has been utilized to extend the possibilities for smart dairy farming (SDF). Milk consumption is continually increasing due to the world's growing population. As a result, some providers are prone to using dishonest measures to close the supply-demand imbalance, such as adding adulterants to milk. To identify the presence of adulterants in milk, traditional testing methods necessitate the use of particular chemicals and equipment. While efficient, this method has the disadvantage of yielding difficult and time-consuming qualitative results. Furthermore, same milk sample cannot be tested for other adulterants later. As a result, this study proposes an IoT-based approach for identifying adulterants in milk by measuring electrical conductivity (EC) or Total Dissolved Solids (TDS) and PH. In order to achieve this, an Arduino UNO microcontroller is used to assess the contaminants. When there is no adulteration, the pH and TDS values of milk range from 6.45 to 6.67 and 750 to 780ppm, respectively, according to this study. Finally, the data is uploaded to the cloud via an IoT device attached to the Ubidot web platform.

Keywords: internet of things (IoT), pH sensor, TDS sensor, EC sensor, industry 4.0

Procedia PDF Downloads 40
36 Channel Estimation/Equalization with Adaptive Modulation and Coding over Multipath Faded Channels for WiMAX

Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

WiMAX has adopted an Adaptive Modulation and Coding (AMC) in OFDM to endure higher data rates and error free transmission. AMC schemes employ the Channel State Information (CSI) to efficiently utilize the channel and maximize the throughput and for better spectral efficiency. This CSI has given to the transmitter by the channel estimators. In this paper, LSE (Least Square Error) and MMSE (Minimum Mean square Error) estimators are suggested and BER (Bit Error Rate) performance has been analyzed. Channel equalization is also integrated with with AMC-OFDM system and presented with Constant Modulus Algorithm (CMA) and Least Mean Square (LMS) algorithms with convergence rates analysis. Simulation results proved that increment in modulation scheme size causes to improvement in throughput along with BER value. There is a trade-off among modulation size, throughput, BER value and spectral efficiency. Results also reported the requirement of channel estimation and equalization in high data rate systems.

Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX

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35 BER Analysis of Energy Detection Spectrum Sensing in Cognitive Radio Using GNU Radio

Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

Cognitive Radio is a turning out technology that empowers viable usage of the spectrum. Energy Detector-based Sensing is the most broadly utilized spectrum sensing strategy. Besides, it is a lot of generic as receivers does not like any information on the primary user's signals, channel data, of even the sort of modulation. This paper puts forth the execution of energy detection sensing for AM (Amplitude Modulated) signal at 710 KHz, FM (Frequency Modulated) signal at 103.45 MHz (local station frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz. The OFDM/OFDMA based WiMAX physical layer with convolutional channel coding is actualized utilizing USRP N210 (Universal Software Radio Peripheral) and GNU Radio based Software Defined Radio (SDR). Test outcomes demonstrated the BER (Bit Error Rate) augmentation with channel noise and BER execution is dissected for different Eb/N0 (the energy per bit to noise power spectral density ratio) values.

Keywords: BER, Cognitive Radio, GNU Radio, OFDM, SDR, WiMAX

Procedia PDF Downloads 462
34 Functional Silos in a Cross-functional Scrum Team: A Study on How to Kill the Silo Mindset and Achieve a Fully Cross Functional Team for Excellence in Agile Project Delivery

Authors: Harihara Subramaniam Salem Chandrasekaran

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Scrum framework is built upon emphasises on self-management and cross-functionality around which the framework is built upon. However, in reality, many organisations that adapt scrum are having functional structures and hierarchy. In such cases, the scrum teams are built with a mixture of people from different functionalities to deliver specific products and projects. For instance, every scrum team would be having a designer, developer or tester, etc.; who will make their own contribution to an increment. This results in people centric dependencies for delivering an increment and thus creating bottlenecks at certain times. This paper presents in detail how functional silos are a challenge to the scrum teams and hinder the incremental deliver of value to customers. The study has been conducted with 14 individuals from the software industry from different functional departments, and the findings summarize that functional silos are naturally formed due to the organizational dynamics and hierarchy and the mindset of being confined within the silos is detrimental to the fundamental values of agile and scrum. The paper also sheds light on what the individuals propose to overcome the silo mindset within the scrum team and focus on continuous improvement in delivery excellence.

Keywords: agile, scrum, cross-functional, functional silos

Procedia PDF Downloads 95
33 Comparative Study on Different Type of Shear Connectors in Composite Slabs

Authors: S. Subrmanian, A. Siva, R. Raghul

Abstract:

In modern construction industry, usage of cold form composite slab has its scope widely due to its light weight, high structural properties and economic factor. To enhance the structural integrity, mechanical interlocking or frictional interlocking was introduced. The role of mechanical interlocking or frictional interlocking is to increase the longitudinal shear between the profiled sheet and concrete. This paper deals with the experimental evaluation of three types of mechanical interlocking devices namely normal stud shear connector, J-Type shear connector, U-Type shear connector. An attempt was made to evolve the shear connector which can be suitable for the composite slab as an interlocking device. Totally six number of composite slabs have been experimented with three types of shear connectors and comparison study is made. The outcome was compared with numerical model was created by ABAQUS software and analyzed for comparative purpose. The result was U-Type shear connector provided better performance and resistance.

Keywords: composite slabs, shear connector, end slip, longitudinal shear

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32 Thermalytix: An Advanced Artificial Intelligence Based Solution for Non-Contact Breast Screening

Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

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Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

Procedia PDF Downloads 233
31 Analysis and Design of Offshore Triceratops under Ultra-Deep Waters

Authors: Srinivasan Chandrasekaran, R. Nagavinothini

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Offshore platforms for ultra-deep waters are form-dominant by design; hybrid systems with large flexibility in horizontal plane and high rigidity in vertical plane are preferred due to functional complexities. Offshore triceratops is relatively a new-generation offshore platform, whose deck is partially isolated from the supporting buoyant legs by ball joints. They allow transfer of partial displacements of buoyant legs to the deck but restrain transfer of rotational response. Buoyant legs are in turn taut-moored to the sea bed using pre-tension tethers. Present study will discuss detailed dynamic analysis and preliminary design of the chosen geometric, which is necessary as a proof of validation for such design applications. A detailed numeric analysis of triceratops at 2400 m water depth under random waves is presented. Preliminary design confirms member-level design requirements under various modes of failure. Tether configuration, proposed in the study confirms no pull-out of tethers as stress variation is comparatively lesser than the yield value. Presented study shall aid offshore engineers and contractors to understand suitability of triceratops, in terms of design and dynamic response behaviour.

Keywords: offshore structures, triceratops, random waves, buoyant legs, preliminary design, dynamic analysis

Procedia PDF Downloads 167
30 Defect Induced Enhanced Photoresponse in Graphene

Authors: Prarthana Gowda, Tushar Sakorikar, Siva K. Reddy, Darim B. Ferry, Abha Misra

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Graphene, a two-dimensional carbon allotrope has demonstrated excellent electrical, mechanical and optical properties. A tunable band gap of grapheme demonstrated broad band absorption of light with a response time of picoseconds, however it suffers a fast recombination of the photo generated carriers. Many reports have explored to overcome this problem; in this presentation, we discuss defect induced enhanced photoresponse in a few layer graphene (FLG) due to exposure of infrared (IR) radiation. The two and four-fold enhancement in the photocurrent is achieved by addition of multiwalled carbon nano tubes (MWCNT) to an FLG surface and also creating the wrinkles in the FLG (WG) respectively. In our study, it is also inferred that the photo current generation is highly dependent on the morphological defects on the graphene. It is observed that the FLG (without defects) generates the photo current instantaneously, and after a prolonged exposure to the IR radiation decays the generation rate. Importantly, the presence of MWCNT on FLG enhances the stability and WG presented both stable as well as enhanced photo response.

Keywords: graphene, multiwalled carbon nano tubes, wrinkled graphene, photo detector, photo current

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29 Effect of Monsoon on Ground Water Quality and Contamination: A Case Study of Narsapur-Mogalthur Mandals, West Godavari District, Andhra Pradesh, India

Authors: M. S. V. K. V. Prasad, G. Siva Praveena, P. V. V. Prasada Rao

Abstract:

It is known that the groundwater quality is very important parameter because it is the main factor determining its suitability for drinking, agricultural and industrial purposes. Water Quality Index (WQI) has been calculated for ground water samples taken from Narsapur-Mogalthur mandals, West Godavari district, Andhra Pradesh, India, from 10 different locations in the pre-monsoon season as well as post monsoon. The water samples were analyzed for pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Total Hardness (TH), major cations like calcium, magnesium, sodium, potassium and anions like chloride, nitrate and sulphate in the laboratory using the standard methods given by the American Public Health Association (APHA). The overall quality of water in the study area is somewhat good for all constituents. Drinking water at almost all the locations was found to be slightly contaminated, except a few locations during the year 2014. It was found that some effective measures are urgently required for water quality management in this region.

Keywords: Water Quality Index, Physico-chemical parameters, Quality rating, monsoon

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28 Mathieu Stability of Offshore Buoyant Leg Storage and Regasification Platform

Authors: S. Chandrasekaran, P. A. Kiran

Abstract:

Increasing demand for large-sized Floating, Storage and Regasification Units (FSRUs) for oil and gas industries led to the development of novel geometric form of Buoyant Leg Storage and Regasification Platform (BLSRP). BLSRP consists of a circular deck supported by six buoyant legs placed symmetrically with respect to wave direction. Circular deck is connected to buoyant legs using hinged joints, which restrain transfer of rotational response from the legs to deck and vice-versa. Buoyant legs are connected to seabed using taut moored system with high initial pretension, enabling rigid body motion in vertical plane. Encountered environmental loads induce dynamic tether tension variations, which in turn affect stability of the platform. The present study investigates Mathieu stability of BLSRP under the postulated tether pullout cases by inducing additional tension in the tethers. From the numerical studies carried out, it is seen that postulated tether pullout on any one of the buoyant legs does not result in Mathieu type instability even under excessive tether tension. This is due to the presence of hinged joints, which are capable of dissipating the unbalanced loads to other legs. However, under tether pullout of consecutive buoyant legs, Mathieu-type instability is observed.

Keywords: offshore platforms, stability, postulated failure, dynamic tether tension

Procedia PDF Downloads 138
27 Improving Perceptual Reasoning in School Children through Chess Training

Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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26 Advantages of Electrifying Offshore Compression System

Authors: Siva Sankara Arudra, Kamaruzaman Baharuddin, Ir. Ahmed Fadzil Mustafa Kamal, Ir. Abdul Latif Mohamed

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The advancement of electrical and electronics technologies has rewarded the oil and gas industry with great opportunities to embed more environmentally solutions into design. Most offshore oil and gas producers have their engineering and production asset goals to promote greater use of environmentally friendly compression system technologies to eliminate hazardous emissions from conventional gas compressor drivers. Therefore, this paper comprehensively elaborates the parametric study conducted in integrating the latest electrical and electronics drives technology into the existing compression system. This study was conducted in aspects of layout, reliability & availability, maintainability, emission, and cost. An existing offshore facility that utilized gas turbines as the driver for gas compression was set as Conventional Case for this study. The Electrification Case will utilize electric motor drives as the driver for the compression system. Findings from this study indicate more advantages in driver electrification compared to conventional compression systems. The findings of this paper can be set as a benchmark for future offshore driver selection for gas compression systems of similar operating parameters and power range.

Keywords: turbomachinery, electrification, emission, compression system

Procedia PDF Downloads 103
25 Study of Indian and Southeast Asian Literature to Trace Evolution of Hanuman

Authors: Subramanian Chidambaran

Abstract:

Right from the Vedic period, we have instances of human heroes being deified and later even assimilated into other deities. Many scholars opine Indra to be one such Vedic deity who rose from a ‘human leader’ to the position of Devata. We also see the assimilation of the Vedic deity Rudra into Śiva in post-Vedic period. Thus the current deities and Gods we worship in the polytheistic Hindu system have been a result of many such deifications and assimilations. Hanumān is one such contemporary character in Indian culture that changed from a valiant hero of the Rāmāyaṇa to a prominent deity in present days. There are also many arguments on whether Hanumān was truly a monkey or a human as the term ‘vānara’ could be interpreted as ‘vā narah’ i.e. ‘or a human’. Despite the popularity of this deity, there is very little academic research done on the genesis and evolution of him. There are many questions that arise - Does Hanumān find any mention (in any form) in literature or archaeological evidence prior to Vālmῑki Rāmāyaṇa? What is the character of Hanumān in the Vālmῑki Rāmāyaṇa? How has this evolved in later Indian literature and where do we see the deification process beginning? What’s the character of Hanumān in literature beyond Indian shores such as Southeast Asian literature and how does it compare with those in Indian literature? This paper is an attempt to answer these questions and trace the evolution of the character Hanumān right from the Vālmῑki Rāmāyaṇa to other Indian literature as well as Southeast Asian literature.

Keywords: Hanumān, Indian, Rāmāyaṇa, Southeast Asia

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24 Biogenic Synthesis of ZnO Nanoparticles Using Annona muricata Plant Leaf Extract and Its Anti-Cancer Efficacy

Authors: Siva Chander Chabattula, Piyush Kumar Gupta, Debashis Chakraborty, Rama Shanker Verma

Abstract:

Green nanoparticles have gotten a lot of attention because of their potential applications in tissue regeneration, bioimaging, wound healing, and cancer therapy. The physical and chemical methods to synthesize metal oxide nanoparticles have an environmental impact, necessitating the development of an environmentally friendly green strategy for nanoparticle synthesis. In this study, we used Annona muricata plant leaf extract to synthesize Zinc Oxide nanoparticles (Am-ZnO NPs), which were evaluated using UV/Visible spectroscopy, FTIR spectroscopy, X-Ray Diffraction, DLS, and Zeta potential. Nanoparticles had an optical absorbance of 355 nm and a net negative surface charge of ~ - 2.59 mV. Transmission Electron Microscope characterizes the Shape and size of the nanoparticles. The obtained Am-ZnO NPs are biocompatible and hemocompatible in nature. These nanoparticles caused an anti-cancer therapeutic effect in MIA PaCa2 and MOLT4 cancer cells by inducing oxidative stress, and a change in mitochondrial membrane potential leads to programmed cell death. Further, we observed a reduction in the size of lung cancer spheroids (act as tumor micro-environment) with doxorubicin as a positive control.

Keywords: Biomaterials, nanoparticle, anticancer activity, ZnO nanoparticles

Procedia PDF Downloads 155
23 Engineered Reactor Components for Durable Iron Flow Battery

Authors: Anna Ivanovskaya, Alexandra E. L. Overland, Swetha Chandrasekaran, Buddhinie S. Jayathilake

Abstract:

Iron-based redox flow batteries (IRFB) are promising for grid-scale storage because of their low-cost and environmental safety. Earth-abundant iron can enable affordable grid-storage to meet DOE’s target material cost <$20/kWh and levelized cost for storage $0.05/kWh. In conventional redox flow batteries, energy is stored in external electrolyte tanks and electrolytes are circulated through the cell units to achieve electrochemical energy conversions. However, IRFBs are hybrid battery systems where metallic iron deposition at the negative side of the battery controls the storage capacity. This adds complexity to the design of a porous structure of 3D-electrodes to achieve a desired high storage capacity. In addition, there is a need to control parasitic hydrogen evolution reaction which accompanies the metal deposition process, increases the pH, lowers the energy efficiency, and limits the durability. To achieve sustainable operation of IRFBs, electrolyte pH, which affects the solubility of reactants and the rate of parasitic reactions, needs to be dynamically readjusted. In the present study we explore the impact of complexing agents on maintaining solubility of the reactants and find the optimal electrolyte conditions and battery operating regime, which are specific for IRFBs with additives, and demonstrate the robust operation.

Keywords: flow battery, iron-based redox flow battery, IRFB, energy storage, electrochemistry

Procedia PDF Downloads 35
22 Structural Health Monitoring of Offshore Structures Using Wireless Sensor Networking under Operational and Environmental Variability

Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

Abstract:

The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network

Procedia PDF Downloads 237
21 Experimental Verification of Different Types of Shear Connectors on Composite Slab

Authors: A. Siva, R. Senthil, R. Banupriya, R. Saravanakumar

Abstract:

Cold-formed steel sheets are widely used as primary tension reinforcement in composite slabs. It also performs as formwork for concreting and better ceiling surface. The major type of failure occurring in composite slab is shear failure. When the composite slab is flexurally loaded, the longitudinal shear is generated and transferred to the steel sheet concrete interface. When the load increases, the interface slip occurs. The slip failure can be resisted by mechanical interface interlock by shear studs. In this paper, the slip failure has been resisted by shear connectors and geometry of the steel sheet alone. The geometry of the sheet is kept constant for all the specimens and the type of shear connectors has been varied. Totally, three types of shear connectors (viz., straight headed, U and J) are bolted to the trapezoidal profile sheet and the concrete is casted over it. After curing, the composite slab is subjected to flexure load and the test results are compared with the numerical results analysed by ABAQUS software. The test result shows that the U-shaped bolted stud has higher flexure strength than the other two types of shear connectors.

Keywords: cold formed steel sheet, headed studs, mechanical interlock, shear connectors, shear failure, slip failure

Procedia PDF Downloads 519
20 Channel Sounding and PAPR Reduction in OFDM for WiMAX Using Software Defined Radio

Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

WiMAX is a high speed broadband wireless access technology that adopted OFDM/OFDMA techniques to supply higher data rates with high spectral efficiency. However, OFDM suffers in view of high Peak to Average Power Ratio (PAPR) and high affect to synchronization errors. In this paper, the high PAPR problem is solved by using phase modulation to get Constant Envelop Orthogonal Frequency Division Multiplexing (CE-OFDM). The synchronization failures are brought down by employing a frequency lock loop, Poly phase clock synchronizer, Costas loop and blind equalizers such as Constant Modulus Algorithm (CMA) equalizer and Sign Kurtosis Maximization Adaptive Algorithm (SKMAA) equalizers. The WiMAX physical layer is executed on Software Defined Radio (SDR) prototype by utilizing USRP N210 as hardware and GNU Radio as software plat-forms. A SNR estimation is performed on the signal received through USRP N210. To empathize wireless propagation in specific environments, a sliding correlator wireless channel sounding system is designed by using SDR testbed.

Keywords: BER, CMA equalizer, Kurtosis equalizer, GNU Radio, OFDM/OFDMA, USRP N210

Procedia PDF Downloads 312