Research Topic: Development of Lean Six Sigma Model for Manufacturing Industries  

Research Area: Lean Manufacturing, Six Sigma

Abstract: Lean Manufacturing is widely regarded as a potential methodology to improve productivity and decrease costs in manufacturing organizations. The success of lean manufacturing demands consistent and conscious efforts from the organization, and has to overcome several hindrances. This research area also provides an important insight into manufacturers’ dilemma as to whether they can commit into Industry, considering the investment required and unperceived benefits.

Research Topic: Experiment Investigation on welding of nickel-based alloy by A-TIG Welding Process.

Research Area:  Manufacturing processes

Abstract: A novel variant of TIG welding process called the A-TIG welding process involves application of thin coating (10-15 μm thick) of activated flux on the joint area prior to welding and the process is found to produce dramatic increase in penetration of 300% in single pass welding. It can overcome the limitations of the conventional TIG welding process. Nickel –based alloy are commonly used due to its superior mechanical property and oxidation resistance at high temperature in aerospace, power, and nuclear industries.   A-TIG process will useful to improved productivity of welding joint. Here we experimentally investigate welding technology for Nickel-based alloy, it is necessary to select the appropriate flux, carrier solvent, and corresponding welding parameters. Consequently, PWHT cycles and final mechanical/metallurgical properties of the welded joints shall also be analyzed.

Topic
Repair, Strengthening and Performance Enhancement of Existing Reinforced Concrete Structures.

Abstract
Amongst the total infrastructure existing across the globe, nearly 70 % is Reinforced Concrete (RC) Structures, and of this 70 %, around 60 % again, are old structures with a varying degree of deterioration, and need major repairs. Again, awareness on environmental conservation emphasizes on reduction in use of concrete, use of waste material in concrete, and utilization of environmentally hazardous materials in concrete. With strengthening of existing structures, there are possibilities of attainment of dual advantage, one being the fact that concrete debris generation can be pushed back by few years, another is the reduced CO₂ emission of old strengthened structure as compared to the new one. Repair and Strengthening and Performance Enhancement of Existing RC Structures is gaining popularity in current market since its advantages outweigh the disadvantages. Strengthening of RC elements various mechanisms and materials is one of such prospective areas wherein no Indian Standard guidelines are available either for strengthening, or for ascertainment of performance of strengthened component. ISIS Canada, ACI 440-2R: 2017 and CNR-DT Guidelines are currently available in the area. Experimental investigations are to be undertaken in this area, with an aim to establish guidelines for strengthening of RC components, suitable for Indian climatic conditions. Analytical and Numerical analysis, supported by development of Empirical equations can also add up to an extent in current area of research.

Research Topic: Wild Animal Detection in Cluttered Forest Images using Machine Learning

Research Area: Image Processing & Machine Learning

Abstract: Monitoring and Detection of Wild Animals is the active research area from last decade. The detection is done from natural images captured from camera trapped networks. The collected images pose the challenge in detection as the information obtained is highly cluttered. Due to this the detection criteria generates large number of false discovery rates. The aim of the proposed work is to design a machine learning based system for wild animal detection in the cluttered images. The outcome of the project should demonstrate the robustness of machine learning algorithm in enhancing the detection performance of Wild animals and to increase the detection accuracy over all existing detection methodology.

Research Topic: Investigation of Security Issues in Internet of Things (IOT) Networks

Research Area: Networking Security and IOT.

Abstract: Internet of Things is growing technology which connects the lifeless things to life in the world. IOT is a vital research area and catching attention The present day IOT technology which is actually a wireless communication network are highly prone to security threats. Deployment of efficient security policies and protocols is extremely important in order to maintain confidentiality and integrity of network among others. The proposed work should be an extensive study of security issues in IOT Networks and design of an Intrusion detection framework that detect such vulnerable attacks in IOT and allow the devices to communicate effectively and smartly.

Research Topic: Speech Recognition with Audio-Video Modalities based Feature selection using 3D-Convolutional Neural Network

Research Area: Signal Processing and Deep Learning.

Abstract: Speech Recognition system fails when audio is corrupted. In such case, Audio-Visual Recognition system has been considered as the good solution. Audio –Visual Recognition is used for multi-speaker scenarios. These scenario is useful to leverage the information extracted in one modality to improve the recognition ability in other modality by providing complementary missing information. It can be looked as the fusion of two modalities of information to enhance the recognition accuracy. The proposed work includes design of framework that combines two different modality viz. audio and visual details. The idea is use Deep learning algorithms to extract visual details and demonstrate the effectiveness of joint learning of spatial and temporal information using 3D Convolutional Neural Networks.

Research Topic: Investigation of Challenges in Free Space Optical Communication System in presence of Atmospheric Turbulence and its Mitigation Techniques.

Research Area: Free Space Optical Communication and

Abstract: Free Space Optical Communication is emerging area as the demand for higher data rate is rapidly increasing. FSO finds the application in the places where the installation of optical fibers is too costly or completely infeasible. FSO basically deploys the optical links in the atmospheric space without the use of optical fibers.
Ample bandwidth, High data rates are some of the promising advantages of FSO communication. However, the FSO communication faces security issues. Eavesdropping is one of the major information security threats in FSO network. Also, FSO technology uses atmospheric channel as a propagating medium whose properties are random function of space and time. It makes FSO communication a random phenomenon that is dependent on weather and geographical location. The environmental parameters like fog, snow, clouds, rain, haze, etc. causes strong attenuation. The proposed work should involves the investigation and effects on mentioned parameters on FSO link and techniques to mitigate the same.

Research Topic: Investigation and Design of Cyber Physical Systems of Systems

Research Area: Cyber Physical System of Systems

Abstract: A Cyber physical system of systems (CPSoS) is one of the emerging areas in the field of research. This is concatenation of two different concepts. The one is systems of systems (SoS) and other is the cyber physical systems(CPS). The SoS is characterized by mainly 5 components. They are operational independence of the components of the overall system, managerial independence of the components of the overall system, geographical distribution, emerging behavior, evolutionary development processes.
According to the leading researcher in CPSOS is defined as “A SoS is an integration of a finite number of constituent systems which are independent and operable, and which are networked together for a period of time to achieve a certain higher goal.” The concept of CPS is summarized as “The interaction of very large complex cyber physical systems for a large number of distributed computing devices to monitor , manage and control and exchange the information between them and human”. It requires the multidisciplinary approach. To design, and to operate cyber-physical systems of systems, knowledge and technologies from many domains are essential. Some of them are well described as Communication technologies and communication engineering. Standardized protocols, exploiting the Internet of Things, to provide new functionality/services, LiFi – light
communications, human-machine interface, dependable computing and communications,
security of distributed/cloud computing and of communication systems etc.
My interest areas are more lying in Communication technologies component of CPSoS This covers research in wireless communications, communication protocols , machine learning, etc. Following are the some of the emerging areas in CPSoS i.e, modeling and large-scale simulation of heterogeneous systems of systems, partially autonomous decision making and system-wide control and coordination, collaborative decision making by computer systems and humans, fault detection, resilience, reconfiguration, and integration of new components etc. Other than CPSoS , Block chain technologies also attract the attentions of researchers.

Following limitations have been identified for future research

Throughput: The potential throughput of issues in the Bitcoin network is currently maximized to 7 transactions per second. When the frequency of transactions in Blockchain increases to 2000 transactions per second, the throughput of the Blockchain network needs to be improved.

Latency: Now a days Bitcoin takes roughly 10 minutes for the completion of transaction. If upon addition of security features It may take little more time because it has to outweigh the cost of double spending attacks. Making a block and confirming the transaction should happen in seconds, while maintaining security. This Latency has to be decreased Size and bandwidth: The size of bitocoin is going to increased from 50000 MB to 250 PB in the network there will be a great challenge. Also Bitcoin community assumes that the size of one block is 1MB, and a block is created every ten minutes This is another challenge to solve the transactions size. Similarly, Security, Wasted Resources, smart contracts, applications of Blockchain etc creates the opportunity for research in Blockchain technologies. Similarly Sensor network routing protocols, vehicular adhoc network have limitations in energy efficient protocols, issues related to fairness, are few burning issues to solve CPSoS challenges.

Research Topic: Ionospheric model development for Indian region using IRNSS satellite data

Research Area: Data mining and artificial neural network

Abstract: Ionosphere plays vital role in the navigation positional accuracy determination, in robust satellite communication. Ionosphere consists of different layers depending on the altitude and its electron density in the layer. Literature cites different ionospheric models predicting the total electron density with spatial and temporal resolutions. These models are mostly using GPS satellite data. The need is felt that there is a requirement of developing ionospheric models for low latitudes of Indian region with different time duration. This research proposal is intended for developing a model to predict 3D tomography of total electron density for entire Indian region. This model is proposed to be developed using IRNSS satellite data collected from RNSS Range and Integrity Monitoring Stations (IRIMS) and various reference receivers spread over entire Indian main land and islands. This data is acquired daily for every second and sent to centralized place. The handling of this enormous data is proposed to use data mining algorithms, artificial neural network techniques for prediction.

Research Topic: Weather cloud phase detection using remote sensing data

Research Area: Machine learning

Abstract: Weather cloud consist of a visible mass of tiny dew drops, ice covered crystals, or other particles suspended in the atmosphere. Clouds cover approximately 60% of the Earth’s surface and they strongly influence weather and climate. Clouds significantly impact radiative heating rates, latent heating rates, moisture transport and uncertainty in climate models and predictions of atmospheric effects on remote sensing measurements. The microphysical properties, spatial coverage, and location of clouds dictate the effect of clouds on the earth– atmosphere system. The literature survey shows that lots of work has been done in the field of cloud detection and cloud classification. But still there is need to explore more in the area of cloud phase detection. There are four phase categories: liquid water cloud top, with temperatures warmer than 273 K or colder than 273 K (i.e., super cooled), mixed-phase (liquid water and ice) clouds and glaciated (ice) clouds.  Appropriate phase detection is a critical step for remote sensing retrievals of cloud properties such as optical thickness (COT), effective particle radius (CER), and water path. Proposed study intend to develop hybrid method which can work on big data of satellite image. It is proposed to consider the physical understanding of the environment, atmospheric parameters and machine learning techniques to overcome constraints and drawbacks of existing algorithms.

Research Topic: Mangrove parameters estimation of selected region using remote sensing data

Research Area: Big data analysis and machine learning

Abstract: Preliminary literature study indicates that satellite remote sensing data is not yet applied to estimate Mangrove parameters of selected region. The proposed study aims to estimate mangrove features using multi-date, multi-polarization SAR (Synthetic Aperture Radar) data, multi band and hyperspectral band optical data. This data may be used for species discrimination, estimation of mangrove height, biomass, detection of mudflat type for mangrove plantation and carbon credit precise differentiation between mangrove and non-mangrove vegetation and canopy texture based assessment for mangrove health. Basically multiple images of SAR and multispectral, hyperspectral images along with ground truth will be used as input for model formation. After data preprocessing based on type of parameter and complexity of the relationship of parameter, correlation / multilinear regression /machine learning technique will be applied. Individual and combined models will be built and will be assessed for accuracy. Model will be more refined using multi-date data over study area.

Research Topic: Big data analysis for Gujarat state coastal ecosystem study

Research Area: Big data analysis and machine learning

Abstract: Large proportion of human population of the State is dependent on these coastal ecosystems for their livelihood. They are very important source of various non-timber forest products for coastal communities such as fire wood, honey, gum etc. Number of marine animals such as whale shark, and sea turtles are residents of the Gujarat coast. Therefore, conservation and protection of these ecosystems is very important for the sustainable growth and development of the State. Preliminary literature study indicates that there is huge scope of satellite remote sensing data application in the area of forest ecology. It is proposed to carry out Big data analysis on data such as multiple images of SAR (Synthetic Aperture Radar), multispectral, hyperspectral images for different applications like mangrove characterization, rainfall prediction, forest fire study. After data preprocessing based on type of parameter and complexity of the relationship of parameter, correlation / multilinear regression /machine learning technique will be applied. Individual and combined models will be built and will be assessed for accuracy. Model will be more refined using multi-date data over study area.

Research Topic: Efficient enhancement of Data Security in the Cloud Environment.

Research Area:  Big Data Security in Cloud Environment

Abstract: The digitization, atomization and significant growth in the IT Industry during the span of the last decade has enabled cloud computing to emerge as the most popular buzzword. Furthermore, the cutting edge technologies like the Internet of things, Machine learning also require cloud services to cater to the data storage and processing needs. As per the case study conducted by Cisco, more than 50,000 lakhs devices are going to get connected with the internet in the near future. The abundance of devices connected to the internet may significantly increase the cloud market as a much larger cloud task is going to deploy in the near future. Hence, it is expected that in India only the cloud market is going to reach the new horizons. Clearly, the optimized and secure usage of cloud service is going to be essential in the near future.

Research Topic: Optimization of Power System Operation

Research Area: Electrical Power System and Soft Computing

Abstract: With higher penetration of renewable generation and market liberalization, operating points of electric power systems become increasingly variable and less predictable. To ensure economically efficient and secure operation of such systems, fast and robust optimization algorithms are required. Despite considerable research efforts, the development of these algorithms remains a challenge due to the nonlinearity and high dimensionality of system models. This dissertation focuses on the optimal power flow (OPF) problem, which is at the heart of techniques used in power system operation and planning. As this problem is non-convex and highly nonlinear, modern solvers cannot always find its locally optimal or even feasible point. To address this issue, an approximation of the OPF problem is proposed that helps reduce its complexity without compromising the solution quality. Moreover, the obtained solution is guaranteed to be physically meaningful. Next, this work presents several computationally efficient techniques for strengthening convex relaxations of the OPF problem. A tighter relaxation helps provide a better estimate of a globally optimal solution of the original problem and recover a physically meaningful operating point. Lastly, this work presents several approaches to incorporating risk-based security indices in the OPF problem. To reduce the computational burden of solving the resulting problems, decomposition algorithms are employed. The proposed techniques were tested on grids of various sizes. The results demonstrate that these techniques can potentially help improve optimization tools used in power system operation.

Research Topic: Multi-Agent Optimized Control System for a Large-Scale Fossil-Fuel Electrical Power Unit

Research Area: Big data analysis and machine learning

Abstract Existing control systems for power plants are rigid and lack the capability to provide optimal operation with increasing amounts of requirements placed on the power plants, prompting the need for a more adaptive, robust control system. The object of this thesis aims to develop and present an optimized control system based on the concept of Multi-Agent Systems (MASs), MAS distributed control methodology will be applied to  a large-scale power plant optimized control system, improving the overall flexibility, autonomy, and robustness of the control system, which in turn will increases the efficiency and operation of the power plant.

Research Topic: Load Forecasting & Optimal Load dispatch using hybrid techniques

Research Area: Electrical Power System

Abstract:  The work carried out in this thesis comprises of two major parts. First part concentrates on short term forecasting of electric load, operating reserves and price in competitive electricity markets using the artificial intelligence techniques (Viz., artificial Neural Network (NN), Adaptive Wavelet Neural Network (AWNN), etc.). The AWNN is a new class of feed-forward NN having continuous wavelet function as activation functions of the hidden layer nodes. Therefore, it combines the time-frequency localization characteristic of wavelet and learning ability of feed forward NN into a single unit. Whereas second part involves the application of heuristic optimization algorithm for optimal generation allocation for Generation Companies (GenCos) in short-term and medium-term operations planning horizon in the competitive environment. The main contributions of this thesis include: Development of more accurate, efficient, and robust short-term forecasting method that can capture the volatility and non-stationarity in electric load, operating reserves and price time series.

Research Topic: Options Derivative Pricing and Electricity Hedging

Research Area: Electrical Power System and soft computing

Abstract: Despite the high volatility of electricity prices, there is still little demand for electricity power options, and the liquidity on the power exchanges of these power derivatives is quite low. One of the reasons is the uncertainty about how to evaluate these electricity options and about finding the right fair value of this product. Hedging of electricity is associated mainly with products such as futures and forwards. However, due to new trends in electricity trading and hedging, it is also useful to think more about options and the principles for working with them in hedging various portfolio positions and counter-parties. Quite often encounter a situation when it needs to have a perfect hedge for customer’s (end user consuming electricity) portfolio, or have to evaluate the volumetric risk (inability of a customer to predict consumption), which is very similar to selling options. Now comes the moment to compare the effects of using options or futures to hedge these open positions. From a practical viewpoint, the Black-Scholes prices appear to be the best available and the simplest method for evaluating option premiums, but there are some limitations which is to be consider.

Research Topic: Optimal Power system operation

Research Area: Electrical Power System and soft computing

Abstract: The Transmission system requires adequate and timely investment and also efficient and coordinated action to develop a robust and integrated system. The Indian Power System is growing steadily. Network expansion should be planned and implemented keeping in view the anticipated transmission needs. To match with the growing demand, transmission system is also expanding with an over lay of 765 kV AC lines on existing 400 kV System, high capacity long distance HVDC system, high capacity long distance HVAC system, adoption of FACTS devices, such as TCSC wherever feasible on 400 kV and 220 kV lines etc. With the formation of regional grid and interregional ties to form ultimately the National Grid, the Power System is becoming more and more complex. Side by side with this growth, requirement of high security and reliable operation of large generating plants with EHV and UHV transmission network assumes tremendous importance in maintaining Power System Stability for better grid management. The severe cascading blackouts that have been seen in many parts of the world highlight the vulnerability of large AC systems. Instances of grid failure due to: pollution flashover have come to notice on 400 kV single circuit lines during fog conditions, inadequate reactive power support, voltage instability, power swings etc. A firewall preventing the spread of such disturbances can be accomplished using measures to avoid voltage instability, relay coordination, design transmission line insulators suitable for varied environmental and pollution conditions, adopting FACTS controls, HVDC connections, which makes an important contribution in controlling power transmission, safe guarding stability and containing disturbances. Technologies such as FACTS and HVDC transmission have played a crucial role in alleviating transmission system constraints. To facilitate orderly growth and development of the power sector and also for reliable and secure operation of the grid, adequate margins in transmission system should be planned. While planning new generation capacities, requirement of associated transmission capacity would need to be examined to avoid mismatch between generation and transmission. A well planned and strong transmission system will ensure optimal utilization of transmission capacities, which would help in cost effective delivery of power. With steeply increasing costs of power 7 generation, it is more attractive to invest in system improvements that might reduce losses in T&D, than investing in additional capacity. Thus, it is required attempt on planning, operational and control problems of large scale systems, application of polymer insulators, design of compact transmission lines in EHV systems, development of new control strategies for FACTS devices etc.

Research Area/Domains

To carry out fundamental research on dynamic analysis of structure, beam, frames, shafts, turbines, gear boxes etc. with or without damages for fault diagnostics and health monitoring.

To optimum synthesis of mechanism to apply for the generalized applications.

To study and optimization of staking sequence of composite structures.

Research Area/Domain

To carry out fundamental research on alternate energy, energy conversion principles and to develop suitable, sustainable technologies for more efficient energy generation and utilization and thereby contributing towards India’s goal of energy self-sufficiency and sustainability.

Following are few areas of interest:

• Non-Conventional Energy; Alternate Energy (Solar Energy)

Increasing use of fossil fuels also causes serious environmental problems. Hence, there is a primary need to use renewable energy sources like solar, wind, tidal, biomass and energy from waste material. They are called non-conventional sources of energy.
The recent trend uses solar as the primary source for production of energy and its utilization in different ways. A lot of work is being required to carry out under this domain for improvement of energy conversion efficiency and its storage etc.

• Energy Management and Economics

Energy management is the means of controlling and reducing organization’s energy consumption and is important because it enables one to reduce costs, improves machine efficiency and effectiveness – this is becoming increasingly important as energy costs rise. In this Energy Audit concept is applied and goal of energy conservation is achieved. The economics aspect of any project is must for cost cutting and revenue generation model.

• Bio-Energy Technology (Biomass Gasification)

Gasification is a process that converts carbonaceous materials, such as coal, petroleum, petroleum coke, or biomass, into carbon monoxide and hydrogen. The gaseous products are further processed for use as an energy source or as a material for the production of a variety of chemicals and/or liquid fuels. Biomass gasification is one of the emerging areas where waste energy is used and gas is produced. Many technologies are used for this energy generation process.

• Thermal Turbo-machines and Wind Tunnel

Turbomachines refers to devices related to energy transfer between rotor and fluid, which includes turbines and compressors as well as pumps also. Such turbines are use to produce useful work from the energy and its conversion. Wind tunnels are large tubes with air moving inside. The tunnels are used to copy the actions of an object in flight. Researchers use wind tunnels to learn more about how an object kept inside is tested related to flow streams and its behavior. This prediction in behaviour of fluid pattern helps in solving problems related to fluid both static as well as dynamic. Wind tunnel takes various objects for measurement of parameters like static pressure, total pressure, wind velocity, drag force and lift force using aerofoil either single or cascade arrangement etc.

Research Area: Thermal system design-optimization

Abstract: Design-optimization of thermal systems requires an integrated understanding of thermodynamics, fluid dynamics and cost estimation. Generally, objectives involved in the design optimization of thermal systems are thermodynamic (i.e. maximum effectiveness/efficiency, maximum Co-efficient of Performance, minimum pressure drop etc.) and economic (i.e. minimum cost).  Ideally the optimization of thermal systems yields the proper worth if thermodynamics and economics objective considered simultaneously. So, it is necessary to evaluate thermo-economic optimization of various thermal systems (like, power cycle, refrigeration cycle, solar based system etc). The proposed area focused on the numerical as well as experimental investigation of the thermo-economic optimization of various thermal systems.

1. Artificial Intelligence in Materials Science

Science of materials is better understood in the current times. The complexity involved in the processing and subsequent influence on material properties calls for simplification of models that are used to understand materials behavior. Tailoring new materials for a purpose needs better understanding of the process and its effect on the properties. With advancement in data driven learning models like neural networks several fit-for-purpose materials can be tailored. Establishment of Process-structure-properties correlation is an important exercise. Doctoral candidates shall work on creating such models to predict and tailor novel materials fit-for-purpose.

2. Screening for efficient ionic liquid extraction solvent for rare earth elements

The purpose of the study is to select the most effective ionic liquid (IL) extraction solvents for rare earth elements (REEs) using a theoretical conductor-like screening model for real solvents (COSMO–RS) based on quantum chemistry and the statistical thermodynamics of predefined REE–IL systems. The thermodynamics of the extraction process is going to predict with the COSMO–RS method. Considering the calculated physicochemical properties of the IL containing these specific ions, the most effective IL extraction solvents for liquid–liquid extraction will be selected. The COSMO-RS approach can be applied before extensive experimental tests to quickly screen the affinity of any REEs for a large number of IL systems, if only the physical dissolution of the REEs is considered. The use of IL is a departure from the traditional strategies employed for extraction.

3. Recovery of copper from copper waste

Copper is one of the most important metal man has utilized. It is the major vein that powers nearly every home in the world, as its electric conducting properties allow homes to be lit up and electricity made available for use.

Solid waste from the copper smelting industry may be harmful if dispose of in the environment but have been highlighted as valuable secondary resources, if metal can be recovered. A number of studies have proposed recycling processes using pyrometallurgy and hydrometallurgy, which are the most promising techniques for the recovery of copper metal. The conventional pyrometallurgy route has some major drawbacks, such as materials re-handling is difficult, high energy requirements, difficult to control various operation and high air pollution etc. and in case of hydrometallurgy, it is time consuming.

From the viewpoint of effective use of resources and better industrial policy, the recovery of copper from copper waste is of great importance. Therefore, it is necessary to innovate a new technique to overcome the traditional process. The proposed new process i.e., electrolytic reduction of copper waste to recover copper will attract even much more attention.

4. Production of Fe–Ti alloy in liquid state using electrolysis process

As an attractive functional material, Fe–Ti alloy has been gaining increasing attention since it was first developed. It has excellent hydrogen-storage abilities and a low expansion rate. It therefore has potential for use as a solid hydrogen-storage material. 

High-purity Fe–Ti intermetallic alloy production in solid state, was investigated successfully in past. The alloys prepared with Fe–Ti intermetallic phases were porous or dense according to the variation of composition. It was observed that the dense structure of the Fe–Ti intermetallic alloy is of high purity and with small amounts of detected impurities. However, the current efficiencies of the processes to produce the solid Fe–Ti intermetallic alloy were very low. Therefore, it is important to develop technologies for the production of high-purity metals and alloys with high energy efficiency for industrial applications. With the aim of addressing the urgent problem of depletion of resources and the commercial challenges associated with the development of new technologies, we hope the production of eutectic Fe–Ti intermetallic alloy in liquid state by electrolysis process will be a more important research topic to overcome this problem.

5. Study the fire retardancy of Nano-ATH in polymer

Aluminum hydroxide is a common inorganic additive used in a wide range of industrial applications. One of its applications is its use as a fire retardant in place of halogen-based flame retardants which have some critical disadvantage like burning of these compounds will produce smoke and brominated dioxins, which may threaten human health. Metal hydroxides such as magnesium hydroxide (MH) and aluminium hydroxide (ATH) are the largest commercially manufactured flame retardants and have been widely used in wire and cable insulation products, synthetic marble, latex for carpet back-coatings, phenolic and epoxy (EP) resins, and unsaturated polyesters (UP). The endothermic decomposition process of MH and ATH decreases the temperature of the burning material and release water into the gas phase to dilute the flame. In addition, the presence of anhydrous alumina can help acid-catalyzed dehydration of some polymers and consequently enhance char formation. During burning of polymer, ATH releases water vapor, reduces the polymer surface temperature and frees non-flammable molecules to dilute the concentrated combustible gas. Since both anhydrous alumina (Al₂O₃) and magnesia (MgO) are white and highly refractory powders, they provide heat insulation by refracting heat when they accumulate on a surface. The main disadvantage of MH and ATH is their low flame retardant efficiency which requires high loadings combined with their inherent poor compatibility with hydrocarbon-based polymers. As a result addition of large amounts of either MH or ATH leads to severe deterioration of the mechanical properties of polymers.

To overcome problem of high loading as well as deterioration, nano-ATH could be a solution. Nano-ATH has specific properties of high surface area and good dispersibility in solutions makes it suitable for applications. Non-hazardous, non- volatile and halogen free, hence it does not produce toxic fumes on decomposition. Addition of compatible nano-sized flame retardant fillers into polymer matrices seems to be the solution to most of the problems existing due to present day flame retardants used.

6. Development of intelligent biomaterial using additive manufacturing

The aim of this study is to demonstrate the ability of additive manufacturing (3D printing), to produce effective biomaterial to enhance the performance of biosensors and medical devices. The proposed research is going to help to develop novel nanostructured biomaterial with intelligent properties such as self-maintenance, self-repair, self-replication, self-diagnosis, recognition, learning, adaptively, information storage, etc, for biomedical devices. The focus of this study is to explore the embedded medication and sensors to be added in different additive manufacturing processes, which helps to automatically adjustable with strength and thickness in response to the applied forces as these have memorial ability to return to its original state on dissipation of the stresses. The project will focus on two key areas (i) design and development of intelligent nanostructured biomaterial and (ii) fabrication and characterization of the developed biomaterial.

7. Development of smart polymer nano-composites as shape memory materials

This project work covers smart polymer nano-composites with perspectives for application in energy harvesting, as self-healing or shape memory materials. It outlines their potential for applications, which would meet some of the most important challenges nowadays for harvesting energy, as materials with the capacity to self-heal or as materials memorizing a given shape. The purpose is to bring together these different applications in one single material.

Self-healing material are the next generation materials for high performance structures. To reduce the fatigue and subsequent probability of failure along with extended service life of polymer composite, proposed work is to introduce the self‐healing mechanism among different materials including insulators, electrical conductors, semiconductors, and ionic conductors. Later, the fabrication techniques and healing performances of the newly developed self‐healing, energy harvesting materials will be carried out.

Research Area: Special functions

Abstract: Special functions play an important role in the field of differential equations, as they arise as the solutions of linear differential equations. The field of special functions is rich with various polynomials and functions. These polynomials are studied for various properties they possess, like generating function relation, orthogonality, difference equation satisfied, inverse series relation, integral relations, summation formula etc. The study can be also taken to basic analogues which has applications in quantum theory. A new immerging area of Fractional Calculus can be considered in the study of various concepts of special function and/or polynomials. It has very good applications in image processing, wavelets, fast Fourier transforms (FFT), discrete-time fractional linear systems, fractional splines, robotics to name a few.

Research Area: Bio Mathematics (Computational Neuroscience)

Abstract: The study of neuroscience includes unrevealing the history and mystery behind the working of mammalian brain. It is of great importance because, although the research is carried out for years and years, one cannot find the actual cause or actual working behind every physiological processes going inside the brain. Thus, the research in this area is an upcoming one which can be studied experimentally, theoretically as well as computationally. Developing mathematical models such that it depicts the physiological process going inside the brain is obviously not an easy task. Calcium is known as the second messenger. Being a second messenger, calcium has its hand in many of the important processes like synaptogenesis, exitotoxicity, gene expression, cell differentiation, enzyme activation, etc. The mathematical modeling of physiological process of calcium diffusion is done by the researchers in past. Researchers have employed various analytical and numerical techniques which would depict the phenomena without changing the physiological conditions of the brain. The impact of different parameters of calcium toolkit like endoplasmic reticulum, mitochondria, voltage gated calcium channels, buffers, sodium calcium exchanger, etc. can be calculated mathematically with the help of these computational models. Looking back at the research which is already carried out, it is found that the study of calcium signaling and calcium homeostasis in view of neurodegenerative diseases is still computationally undone. The increase in calcium concentration directly affects the normal condition of the brain and results in neurodegenerativity and thus the neuronal disorders. The computational models can be constructed to study and analyze the diseased brain. These mathematical models would be helpful to biologists and the researchers working on in vitro studies. Hence the future of research in computational neuroscience area is bright as there are lots and lots of things which still need to be unrevealed.

Research Area: Financial Mathematics

Abstract: Financial Mathematics is also known as quantitative finance. This is a field of applied mathematics, concerned with financial market. This also includes statistics and economics in some or the other way. In financial mathematics, one will derive and extend the mathematical models by considering the observed market data as input. This types of financial models can determine present decisions with the consideration of the uncertainty of the future.  Using this an individual can also work as consultant who work independently and provide their expertise to the government or private sectors.

Research Area: Ocean modelling using satellite data

Abstract: Climate change is the major problem now a day, where Ocean play a major role due to large volume covered by the Ocean on Earth. Indian Ocean is the tropical region as it is covered by land area in northern, western and eastern parts. Mesoscale and submesoscale variabilities in Ocean can influence physical and biogeochemical cycles in the ocean through vertical and horizontal advection of nutrients and marine organism. The Oceanic phenomena consist physical and biological parameters like ocean surface waves, surface currents, ocean circulations, oceanic mixed layer, air-sea interactions, sea ice, fisheries, primary productivity of biological parameters i.e. Phytoplankton growth, Chlorophyll, Nutrients etc. and suspended particles.

Study covers:

• Theoretical Study of Physical and Biological parameters i.e. Sea Surface Temperature, Sea Surface Salinity, Ocean current, Sea level, Phytoplankton growth, Chlorophyll, Nutrients etc. using satellite and in situ data to understand the coastal and open ocean phenomena in Indian Ocean.
• Developing the mechanism for mesoscale and submesoscale length and its effect on biological parameters, will be investigated for Indian Ocean including Bay of Bengal, Arabian Sea and Southern Indian Ocean.
• Analyzing Coastal and Open Ocean phenomena of Indian Ocean are explored by utilizing the retrieval satellite and in-situ products.
• High resolution numerical ocean circulation model is used to analyze the submesoscale Ocean variability in Indian Ocean and validated with standard products of satellite, in-situ and merged.
• Implementation of data assimilation technique in Ocean Circulation Model with high resolution for the statistical analysis of the study and for better outputs.

Note: Currently, a research project is running with Space Applications, Center, ISRO under SCATSAT-1 Utilisation Program. The title of the project is mentioned below:

Project Title: ‘Role of Ekman pumping on biological ecosystem of Indian Ocean on mesoscale and submesoscale length scale’

Research Area (Chemistry)

• Nano-Chemical Sensor
• Analytical Method Development
• Drug delivery

Abstract: Currently we are working at the interface of traditional analytical chemistry and contemporary research on nanomaterials. In the research of analytical chemistry we design and develop new technique for detection and quantification for analyte. Currently we are focusing on “Hilic chromatography” a separation technique. This technique is significantly used for the separation of desire bio-molecules from the matrix of natural fluids.

Further, we are also working on design and development of Nano-chemical sensor based on fluorescence for the detection and determination of bio-molecules, ions and toxic elements. In this view we develop supramolecular based nanomaterial scaffolds by bottom-up nanofabrication process. Apart from detection, these Nano chemical sensors will be explored their application towards solving the problems of drug delivery, cancer therapy and other demanding areas.  

Research Area (English Literature)

• Indigenous Literary Studies
• Diaspora and Migration Literature and Studies
• Intertextuality and Adaptation Studies
• Gender Studies

Abstract: “Orality and Story-Telling in North American Writing with reference to novels of Leslie Marmon Silko and Thomas King.”

The dissertation makes a comparative analysis of select novels of Leslie Marmon Silko and Thomas king from the praxis of Orality and Storytelling and Native critical tradition. This research looks at the history of Native American verbal art from its earliest surviving representations to the works of contemporary authors from the Native American Renaissance. The focus is on several key aspects of how Native authors construct their novelistic re-creations of Native oral tradition and the world. How the evolution of issues such as repressive education, false portrayals of Native identity and abusive use of natural resources over a period of time, which is responsible for some of the discrepancies between Silko’s and King’s style. The methodology of this dissertation is a comparative study of select novels of King’s and Silko’s, using the insight given by Native critical tradition by Native authors particularly on Orality and Storytelling Literary Tradition. This study also focuses upon the application of postcolonial theories and exploring the possibilities of its application over Native Literary tradition. The idea is to preserve the sense of common experience that Native authors reveal in their writing.