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Result of Ph.D Entrance Exam : IURAT July 2021

Indus looks forward to having students who are passionate about research and aims to take the existing concepts in their chosen fields a step further, utilizing the resources available at the university.

PhD is an opportunity and a conscious choice to contribute to the nation with innovative development. It is a lengthy process wherein the scholar explores the research area in-depth for the next few coming years under the supervision of an experienced guide. Indus has a large number of faculty members eligible to lead research projects in diverse areas.

‘If you are ready to meet deadlines, write numerous drafts, build an educational circle, give presentations and most importantly, determined to explore the unexplored in your arena, Indus is waiting for you.’

Indus University has a systematic procedure for PhD aspirants to follow. From the minimum criteria required, the procedure for securing your admission in PhD to the areas we shall be offering PhD in, all the crucial details shall be put up on this very page soon.

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    How to arrive at a research topic?

    The term research means systematic study of a subject least explored until one knows massively more about it. One undertakes research either to solve an ongoing issue, answer a question pending since long or out of a desire to add one’s original thoughts to the existing ocean of knowledge. In short, research is re-searching on minimally searched topic to derive at a conclusion valuable to society.

    Once we know what research is about, we ought to ask an important question: How do we choose a research topic? After all, the success or failure of the research also depends on the selection of a topic. So, here are a few steps to guide you through the process of selecting a suitable topic.

    Stay curious:

    The first step includes asking appropriate questions to seek accurate answers. Ask yourself,

    • • Why do you wish to pursue a PhD?
    • • Would you be able to dedicate your attention to one topic for the next coming years?
    • • What could be that topic?
    • • From where can you collect the data?
    • • Who shall finance your PhD if not you?

    While you may receive answers to some of the questions instantly, a few others will take time to shape and manifest in front of you. The key is to remain realistic with oneself.

    Skimming the literature:

    The research asks for a lot of reading. Thus, to complete a PhD within the stipulated time it is essential to polish your reading skills. One of the best ways is to skim through the text relevant to your field. Skimming means quickly having a glance at a text, article, journal or any other material to get a general idea about the themes an author discusses in it. It allows you to take a peep at the ideas and opinions of the author on various topics, eventually giving you a foundation to build your structure on. At this stage, do not use a filter. Keep browsing as much content as you can.

    Scanning the resources:

    Once you have managed to gain a broad idea about the field you want to research on, you can take a step further. Begin by reading the books, which covers your area of interest, simultaneously jotting down important details and points. It shall help you, narrow down to a specific subject. Utilize nearby libraries, digital mediums or bookstores to get better clarity.

    Once done with the reading, make a map of significant keywords marked by you. Check their usage and demand in your field at present and the scenario after three to five years. You can mix and match the keywords to explore all the possible scenarios. It shall help you decide the topic you wish to research on. At this stage, you shall have a topic to contemplate on, though not so perfect.

    To assure that the topic you have chosen can be finalized; you shall have to do a few checks.

    1. Is there enough data written and available on the topic you are planning to research on?
    2. Would you be able to complete your PhD within time or the topic is too vast to finish?
    3. Is there a scope for you to contribute to your field using this topic?
    4. Is the topic recent? If yes, it is possible that the resources will not be available. Would you still like to go ahead?

    If you are confident of pulling off the topic decided by you, congratulations, you have your research topic.

    Do’s and don’ts while pursuing a PhD


    • Realistic goals

    • Skimming and scanning

    • Short-term targets

    • Note down your ideas in a diary

    • Reference manager to store the data

    • Stay in contact with research scholars

    • Attend conferences

    • Keep on writing drafts

    • Maintain a healthy lifestyle


    • Compare yourself or your work with others

    • Unnecessary stress

    • Procrastination

    • Strive for over-perfection

    • Plagiarize

    • Research for the sake of others, title or better job prospects

    • Have a biased point of view

    • Quit

    To learn more about research in detail

    Research Area Leading to Doctoral Degree

    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.

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

    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

    AbstractThe 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 desi