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Fractional-order chaotic systems, its stabilization cum synchronisation and its circuit simulation
(Department of Electrical Engineering, NITS, 2018) Dutta, Maitreyee
Causative Fault Classification and Optimal Placement of Lightning Arrester for Minimizing the Risk of Failure in Transmission Systems
(Department of Electrical Engineering, NITS, 2019) Dey, Shiladitya
This project deals with classification and mitigation of faults arising in a transmission network. Response of operators to a fault depends upon the type of fault that has occurred itself. Response to a vegetative fault will be much different than that of lightning induced faults. Currently causative fault classification is only possible by physically visiting a place where the fault has occurred. However if the fault can be classified from the fault data itself, it would massively speed up system response and enhance smoother operation of transmission apparatus. Causative fault classification has been done in this project by utilizing Artificial Neural Network (ANN). With the help of ANN, fault classification with an exceedingly high accuracy (99.5% accuracy) has been achieved in this project. The project also describes an economical solution for transmission network protection against lightning surges and strokes by selective installation of arresters. To achieve this cherished goal, a probabilistic methodology based on IEEE Std. 1410 has been applied to the Northern Grid of West Bengal and an optimisation process based on Binary Bat Algorithm has been developed and applied to solve the stated problem. The proposed method considers technical, meteorological, geographical and economic criteria to achieve the best solution. Consequently, the costs of investment and the total annual costs including line investment, line maintenance and outage costs are being decreased taking into consideration the cost of protective devices. In the optimisation procedure, lightning occurrence and network characteristics as well as transmitted power are considered. The achieved outcomes confirm effectiveness of the suggested approach from technical, meteorological, geographical and economical point of view.
AGC of Multi-Microgrid System Using Modern Heuristically Optimized Controllers
(Department of Electrical Engineering, NITS, 2019) Sahoo, Manoj Kumar
Automatic Generation Control is a basic and important computer based real-time control in the interconnected power system. There are two basic control approaches in AGC one is primary control which is referred as governing control mechanism and another one is secondary control. Recent trend of use of distributed generation including renewable sources and energy storage devices, that gives rise to the development of microgrid. Because of quick change in burden there is a mismatch occurred in between source side and demand side. In this thesis AGC of two area multi-micro-Grid system and three area multi microgrids with higher degree of freedom controller i.e. 2-DOF-PID controllers are considered for study. The parameters of the controllers is optimized with modern me-ta heuristic algorithms like Firefly Algorithm (FA) and Mine Blast Algorithm (MBA) to find the better one as optimization technique. The investigation of the comparative results between FA and MBA algorithms reveals that the MBA is better than the other in terms of convergence rate and better quality of solutions in two area multi-micro-Grid system. Then, higher degree of freedom controller, 2-DOF-PID controller is considered for the same study system and the controller gains are tuned using MBA (better of FA and MBA) and the dynamic responses are obtained for comparison with PID controller. From the results it can be inferred that the proposed 2 DOF-PID controller is better than PID controller in terms of peak overshoot, settling time and number of oscillations. Then the sensitivity analysis of the proposed controller validates that the proposed controller optimized at nominal conditions is quite competent to give good reasonable performance at new operating conditions and need not be optimized again and again for every new conditions and hence quite robust. Further, the same 2 DOF-PID controller is used in three area multi-micro-Grid system and optimized with MBA algorithm. The results demonstrate the proposed MBA optimized controller performs better than PID controller in three area too and the sensitivity analysis confirms the robustness of the proposed controller in this study system too.
Day ahead Demand Side Management using Firefly Algorithm
(Department of Electrical Engineering, NITS, 2019) Debbarma, Sophia
With the increase in the number of electrical gadgets and appliances, the demand for electricity has also increased, it is now very important to emphasize in the concept of demand side management to meet the required demand of electricity. DSM assures efficient use of available energy resources. DSM along with smart grid allows the consumer to have details of power consumption information and allows the suppliers to lower the overall load demand during the peak period and modify the load curve. Necessary data of the energy consumption and price have been taken from different papers. In this research work, the primary aim is to mainly lower the overall load demand and thus the operational cost and utility bills. The work is done in different areas – residential, commercial and industrial. To get the optimized result, Meta-heuristic algorithm was developed to minimize the problem. Because of the flexibility, gradient free mechanisms and local optima avoidance of the algorithms, meta-heuristic techniques is gaining popular. Calculation of derivative of search space is not required in meta-heuristic technique making it highly flexible for solving a diverse range of problem. The evolutionary algorithms used to solve the demand side management problem is Particle Swarm Optimization, Firefly Algorithm and Salp Swarm Algorithm. The three algorithms is used to obtain the objective of the project work in three different area- residential, commercial and residential area. Firefly algorithm is found out to provide the best cost as compared to other two algorithm PSO and SSA. Firefly Algorithm is able to provide better accuracy.
Smart Healthcare Remote Monitoring System Using Internet of Things
(Department of Computer Science & Engineering, NITS, 2019) Kumar, Rahul
In the present scenario, diagnosis and monitoring of health is a very important task in the healthcare industry. Due to busy schedule in day-to-day life, people are less concerned about health which might and possibly lead to a lot of health issues in one instant of time. Advances in technologies have led Internet of Thing (IoT) to be one of the most sought tools in the healthcare system. Thus, IoT in the medical field brings out the solution for effective patient monitoring at reduced cost and it also helps in preventing time relapses during a hospital, dispensary or clinic visit. Sitting is one of the most commonly adopted postures of a human being in daily life. People spend a long time sitting in an Office chair, room chair, lounge chair, and so on. The sitting behaviour analysis becomes an important research topic, especially in healthcare services. In this paper, we have designed a testing sheet for human posture identification using five light-weight pressure sensors. The pressure patterns of eight standardized sitting postures were acquired and transmitted to the computer for the automatic sit ting posture recognition with the application of different ML classifiers. Furthermore, we focused only on static postures. After receiving correct sitting posture result i.e. Sitting-upright, our next matter of concern in this paper is on the development and implementation of an effective healthcare monitoring system based on IoT. The prototype system we developed works on 3 phases: 1) Data acquisition using sensors including patients temperature, heart rate and body position (Accelerometer 2) Storage of health information to a database for local and remote data access. 3) GUI based web page design for showing health status
Automatic Generation Control of Multi-Area Multi-Source System Using Coyote Optimizer Algorithm based PD–TID Cascade Controller
(Department of Electrical Engineering, NITS, 2019) Kumar, Narisetty Varun
Automatic generation control (AGC) plays a crucial role in the operation and control of power systems. AGC is a supportive scheme that maintains the system frequency under permissible limits. This thesis presents Automatic Generation Control (AGC) of a three unequal area thermal system incorporating solar thermal power plant (STPP) in area-1 and geothermal power plant (GTPP) in area-2. The control areas are provided with single reheat turbine and generation rate constraints (GRC) of 3% / min. A maiden attempt has been made to apply a Proportional derivative–Tilt integral derivative (PD–TID) cascade controller in AGC. Controller gains are optimized using Coyote optimization algorithm (COA) which is population based metaheuristic. The system dynamic performances are studied with 1% step load perturbation in Area1. Performance of classical controllers such as Proportional Integral (PI), Proportional Integral Derivative (PID), Tilt Integral Derivative (TID) controllers are investigated and compared with PD–TID cascade controller. Investigations reveal that PI, PID and TID provide more or less same response where as PD–TID cascade controller provides much better response than the later. Dynamic analysis has also been carried out for the controllers in presence of random load pattern, which reveals the superior performance of the PD–TID cascade controller. Sensitivity analysis reveals that the COA optimized PD–TID Cascade controller parameters obtained at nominal condition of loading, size and position of disturbance and system parameter (Inertia constant, H) are robust and need not to be reset with wide changes in system loading, size, position of disturbance and system parameters.
Energy Management in a Microgrid Using Battery Electric Vehicle
(Department of Electrical Engineering, NITS, 2019) Chingakham, Rojita
This project considers an isolated Wind Power Plant based DC microgrid system supported with Battery Electric Vehicles (BEV). The maximum power from the wind energy is extracted using the control methodology of classical Perturbation and Observation (P&O) Algorithm. BEV is used for the purpose of transportation as well as for power transaction between the microgrid and its battery storage system. A comprehensive supervisor controller for connection and disconnection of EV based on the power difference between generation and load (P) and the status of State of Charge (SOC) of the battery of BEV is designed. As the BEV has bidirectional power transfer capability, it is used as a load when there is a large power surplus and as a source when the demand is more than a generation. The transportation activity performed by the EV is controlled by the intelligent based algorithm which is designed by using a fuzzy logic controller.
Profit Allocation Of Distribution System Considering Distributed Generation & Facts Devices
(Department of Electrical Engineering, NITS, 2019) Rashmi, Divya
This project is about to optimal sizing and siting of Distributed generator in Distribution side. The exponential increase in electricity demand has resulted in the continuous depletion of the traditional power generation sources. The traditional power generation sources are operated centrally and are not suited for environmental and cost issue in today’s liberalized electricity market. After decentralization, electricity provide to their customer in a reliable, decent and cost effective manner. DG proves to be the solution of these issue upto some extent. It is based on decentralization marketing strategy. The line losses are reduced, voltage profile improved and also maximize the economic benefits and share the social benefits amongst network partners when DG connected optimally.
Virtual Power Plant Supported Frequency Control Of Hybrid Microgrid Both In Isolated And Interconnected Mode
(Department of Electrical Engineering, NITS, 2019) Kumar, Praveen
The population growth and rapid industrialization rises power demand with depleting fossil fuels for conventional power generation day-by-day. It is also very tough to meet the varying electricity demand of consumers by conventional energy sources in current scenario, which leads to an increase in green house gases and CO2 emission. To address the above problem scientists and researchers looked into renewal energy resources like wind power, solar power, hydro power, tidal power, etc. which have sufficient potential to get better of these issues. One of the biggest reasons for the popularity of renewal energy resources is that it is cleanest form of energy available on earth. However, the main drawback with renewal sources is the dependency on the environment, so referred to as an intermittent generation. Therefore, we need some kind of enhanced concept in this field. So, for the better consistency and better facility of power supply, the small scale power generating technology such as wind, mini/micro- hydro, solar power etc. are gradually replacing conventional/traditional technology in various applications. These technologies are referred to as distributed energy recourses (DER) which represent a modular electric generation. However, there are various challenges associated with designing such power systems. In this regard, voltage and frequency are the most important aspects to be controlled. In addition, power quality is also taken into consideration for effective power dispatch to the consumers. Microgrid and virtual power plant (VPP), among many innovative paradigms in facilitating the integration of the DER, are two of the attractive conceptual solutions which provide coordination and aggregation for the DER. Coordinated control of VPP comprising of solar photovoltaic (SPV), wind turbine generator (WTG) and controllable load such as plugged-in hybrid electric vehicle (PHEV) and heat pump (HP) have been explored. The control concept includes the flexible adjustment of the aggregated power output of the VPP so as to address the frequency regulation. Investigation under simulation environment has been carried out to assess the effectiveness of the VPP to offer frequency support to both an isolated and interconnected microgrid mode. The parameters of the proportional–integral-differential (PID) controllers, employed with SPV, WTG, DIESEL, PHEV, and HP are optimized simultaneously using integral square error (ISE) criterion. The analyzed performance of ISE optimized PID controllers on the hybrid system model has been presented considering step change and random variations of SPV and critical load. Simulation results revealed that ISE optimized controllers for SPV, WTG, DIESEL, PHEV, and HP can provide the dynamic performance of the hybrid energy system. Present work considers VPP supported frequency control of hybrid microgrid in the isolated mode of operation. Since SPV generation is intermittent in nature, causing a variation power generation and also the load is variable. This results in a mismatch in generation and consumption of power. And this is the main reason system frequency deviates, which are never desirable. Therefore to minimize the effect and mismatch in power generation and consumption in the system tuned PID controllers are used. In conservative idea, the gain values of the PID controllers are chosen by trial and error method or by the traditional method as described in Ziegler and Nichols. The controller gains once tuned for a given operating point are only suitable for limited operating point changes. Therefore, the use of the conventionally tuned PID controller does not meet the requirements of healthy performance. Computational intelligence has opened paths to a new generation of advance process control. Present work considers PSO (Particle Swarm Optimization) algorithm and SSA (Salp Swarm Algorithm) optimization technique to optimize the gains of the controller employed with SPV, WTG, DIESEL, PHEV, and HP for automatic power control of the proposed hybrid system. Scope of the work includes the following major performance studies in time-domain simulation under different operating conditions of the proposed hybrid system in isolated and interconnected modes respectively. Isolated mode: (a) Performance of the system consisting of a PID controller for the step disturbance in critical load and SPV generation. (b) Performance of the system consisting of PID for the variable load. (c) Performance of the system consisting of PID for variable generation in SPV. (d) Performance of the system consisting of PID for variable generation in SPV as well as variable critical. In each of the above-mentioned cases controller parameters are tuned using SSA and PSO. Interconnected mode: (a) Performance of the interconnected system consisting of a PID controller for the step disturbance in critical load. (b) Performance of the interconnected system consisting of a PID controller for the variable power generation in SPV. (c) Performance of the interconnected system consisting of a PID controller for the variable power generation in SPV as well as variable critical load. In each of the above-mentioned cases controller parameters are tuned with SSA and PSO.
Frequency control of isolated hybrid power system using FA optimized controller
(Department of Electrical Engineering, NITS, 2019) Sharma, Ajnish Kumar
India has a big populace and very constrained natural assets mainly for meeting its power necessities. If the wishes to hold its momentum of fast increase economy it is possible with a clear strategy for resource utilization, satisfactory use of power alternatives to be had. Power is crucial for development and which means that if India want to move faster than it need to ensure the reliable availability of energy. The existing electricity condition in India is not so pleasant and there is a huge scope of development. Maximum of the energy generation in India is generated by means of conventional power plant. Coal and mineral oil-primarily based energy flowers which contribute heavily to environmental degradation. Adding to this conventional power plant will cause for environmental degradation and inevitable import volatile oil and coal. We have to be judicious on utilization of considerable renewable energy sources available in the surrounding, which include biomass, sun, wind, geothermal and ocean electricity. Due to the inequality in accessing electricity across the region, renewable energy has the possibility of becoming the inspiration for us for energy requirements. Electricity has been universally identified as one of the most crucial inputs for economic growth and human progress. There’s a strong relationship between economic growth and consumption of energy. One hand, increase of a country GDP, hinges on the availability of economic and environmental friendly electricity generation, and on the other hand, the extent of economic improvement is proportional to the electricity demand. If India has to maintain its growth it has to boom its use of renewable resources and reduce its dependence on conventional energy sources. The frequency of small power system deviates for sudden adjustments in load or generation or the both. Automatic generation control of an autonomous hybrid generation system such as wind turbine (WT), solar photo voltaic (PV), diesel engine (DEG), battery energy storage system (BESS), have been taken into consideration for simulation research. The comparative performance of the controllers employed to alleviate this frequency deviation for isolated hybrid systems, is executed using time domain simulation. In general, controllers (PI or PID) are use which is tuned manually which is difficult and time tacking. The computational intelligence has opened paths to a brand new technology of superior method. Right here, Firefly algorithm(FA) is used for optimization of controllers ‘The advantage of the proposed hybrid structures with fractional order PID controller has been shown, the simulation outcomes reveal the effectiveness of the FF based fractional order PID controllers in reducing settling time, overshoot and oscillations. The results are as compared with FF optimized PID controller. Application of fractional order PID (FOPID) controller to an automated frequency control of isolated hybrid power system is studied. Fractional order PID controller's orders are fractional numbers rather than integers. Design stage of this controller includes figuring out five parameters. This paper employs Firefly algorithm for optimization. FA is an advanced search method that has proved to have very high efficiency. A unique fee feature is described to facilitate the manage approach over both the time domain and the frequency-area specifications. Comparisons are made with a PID controller and it's proven that the proposed FOPID controller can give quite good robustness domain simulation. In general, controllers (PI or PID) are use which is tuned manually which is difficult and time tacking. The computational intelligence has opened paths to a brand new technology of superior method. Right here, Firefly algorithm(FA) is used for optimization of controllers ‘The advantage of the proposed hybrid structures with fractional order PID controller has been shown, the simulation outcomes reveal the effectiveness of the FF based fractional order PID controllers in reducing settling time, overshoot and oscillations. The results are as compared with FF optimized PID controller. Application of fractional order PID (FOPID) controller to an automated frequency control of isolated hybrid power system is studied. Fractional order PID controller's orders are fractional numbers rather than integers. Design stage of this controller includes figuring out five parameters. This paper employs Firefly algorithm for optimization. FA is an advanced search method that has proved to have very high efficiency. A unique fee feature is described to facilitate the manage approach over both the time domain and the frequency-area specifications. Comparisons are made with a PID controller and it's proven that the proposed FOPID controller can give quite good robustness.
A Novel Automatic Shot Boundary Detection Algorithm Robust to Illumination and Motion Effect
(Department of Computer Science & Engineering, NITS, 2019) Singh, Alok
Apparently, the summarizing, classifying and indexing valuable information from the massive amount of videos is very inefficient and time consuming through manual procedure. In order to make this process effective, it is necessary to segment a video into meaningful shots and locate the boundaries between the shots. Shot is a collection of continuous frames having similar content and visual feature and when the continuity in the similarity of the frames breaks it is termed as transition from one shot to another shot which creates a boundary between the shots. But, the performance of shot boundary detection approaches are yet to be addressed for the videos having sudden flash light and Object/Camera Motion efficiently. In this thesis, a novel approach for abrupt transition detection is proposed which can able to withstand under certain illumination and motion effect. The proposed algorithm can be roughly divided into two stages: firstly, the adaptive Wiener filter is applied to the lightness component of the frame to retain some important information on both frequencies and LBP-HF is extracted to reduce the illumination effect. From the experimentation, it is also confirmed that the motion effect is also reduced in the first stage. Secondly, Canny edge difference is used to further remove the illumination and motion effect which is not handled in the first stage. TRECVid 2001 and 2007 datasets are applied to analyze and validate our proposed algorithm. Experimental results manifest that the proposed system outperform the state-of-art shot boundary detection techniques.
Construction of Discrete Medial Axis using Digital Geometric Approach
(Department of Computer Science & Engineering, NITS, 2019) Dutta, Dona
Medial Axis is one of the classical problems in the field of computational geometry. The medial axis of an object is defined as the set of all points that has two or more than two closest points on the boundary of the object. It was first introduced by Blum as a tool for biological shape recognition. It is used for shape recognition, character recognition, pattern recognition, geographic information systems(GIS), mesh generation, detail suppression and model simplification for engineering analysis. But most of the existing algorithms for me dial axis construction is for the real domain. For applications in the discrete domain that require medial axis transformation, the medial axis is first constructed using real geometric techniques and then discretized to obtain the Discrete Medial Axis (DMA). Such DMA are often less accurate and can also be disconnected at places. The problems associated with such existing algorithms mainly includes distance error, hardware-precision error, complex algebraic and trignometric functions, resolution error, generation of debris pixels and spurious neighbors. To avoid such discripencies arising due to two-fold domain change error, we propose an algorithm to construct DMA using digital-geometric techniques only. Our proposed algorithm eliminates all the errors present in the existing algorithms. The proposed algorithm constructs DMA of given convex polygons, concave polygons and curved-shape objects by using Discrete Voronoi Diagram(DVD) for extended sites followed by edge detection and edge elimination wherever necessary. Experimental results show the efficacy of our proposed algorithm.
Profit Maximization of Wind-HESS based System by Minimizing the Negative Imbalance Cost
(Department of Electrical Engineering, NITS, 2019) Dhruvagupt
Recent decades the rapid development of wind power integration because of wind power generation reduces carbon emissions and extinction. Among all the renewable energy extraction technologies wind is most suitable and cheaper one. The main drawbacks of wind power integration are wind power predictability, optimal offering strategies for wind farms in a day ahead electricity markets. Due to this wind farms injects energy imbalance into the grid. We want to reduce the wind power intermittency nature by using hybrid energy storage system. Main advantages of hybrid energy storage system become more reliable and efficient. Here we proposed logic for coordination of hybrid energy storage system and wind farm in efficient manners to get maximum profit with minimum wind farms power imbalance. This thesis compared the profit before and after the integration of hybrid energy storage system with the wind-thermal integrated power system. Our results highlights that when HESS is supplying power to the wind-thermal based power system deviations are less, spot market compensation cost is less, LMP is also reduces and imbalance cost is also reduces.
Feature Selection Algorithm Using Effective Range and Overlapping Area for Classification of Gene Expression Data
(Department of Computer Science & Engineering, NITS, 2019) Verma, Manish Kumar
Feature selection is an important issue in the field of machine learning and data mining. Classifier’s accuracies and other generalization performance depend on the outcome of the feature selection. Feature selection can help in building a simple model with high accuracy to solve a complex real-world problem. Prediction and diagnosis of disease at an early stage can help many people to get rid of that disease. Classification of gene expression data can play a major role in the prediction of disease. Recently statistically defined feature selection algorithm named Effective Range based Gene Selection (ERGS) and Improved Feature Selection based on Effective Range (IFSER) is proposed. Where, ERGS considers only the overlapping area (OA) of the effective range of each class for every feature, on the other hand, IFSER also uses the other relationship (inclusion relation) of the effective range of each class. But both ERGS and IFSER fails to handle the one situation when the effective range of one class is completely included in the effective range of the other class. And the overlapping area and number of samples in the overlapping area and including area is incorrectly measures by both the algorithms. In this thesis, we are presenting a modified algorithm for feature selection which will overcome the limitation of ERGS and IFSER algorithms. To showcase the effectiveness of our proposed method several experiments on different gene expression datasets are performed and results are compared with other well-known feature selection algorithms. Experimental results manifest that the proposed modification in ERGS and IFSER improves the classification accuracies on gene expression dataset.
Optimal bidding strategy for wind-PSH based hybrid competitive power market
(Department of Electrical Engineering, NITS, 2019) Ravitheja, Rage
Recently, wind energy penetration is growing rapidly because of its advantages like clean fuel sources, no greenhouse gases during its operation, in fact now a days wind energy prices have become comparable with those of conventional prices. But the challenging task is intermittent nature of wind the output power and terminal voltage of wind farm is fluctuating and this effects the profit. This thesis presents a simple and efficient approach to maximize the profit by operating pumped storage hydro (PSH) power plant and demand response (DR) according to the instruction from the wind-thermal hybrid plant on by considering minimum and maximum limits of pumped storage hydro power plant. Wind speed is predicted for day ahead market. Here the error between predicted and actual (real time market) is fulfilled with the pumped storage hydro plant and demand response. Main aim of the demand response is that rebound period (higher demand) aligns itself with the higher wind generation output period and lower generation time demand should be curtailed and the incentives are provided based on the curtailment of the demand. So that minimized the curtailment of wind energy and revenue loss. The pumping and generation of pumped storage hydro power plant depends upon wind power plant. At positive error of wind speed the pumped storage will generate energy by releasing the water from higher head to lower head and at negative error of wind speed pumping water from lower head to upper head. The proposed methodology is implemented using MATLAB interior point solver (MIPS) to solve optimum power flow problem. The implementation has been done with modified IEEE 30 bus system.
Image Dehazing using Contrast Limited Adaptive Histogram Equalization and Guided Filter
(Department of Computer Science & Engineering, NITS, 2019) Biswas, Debalina
Due to the presence of haze in the atmosphere, the contrast as well as the true color of the real image taken in the outside, gets degraded. Therefore, it is much important to remove hazy effect from the real image to get clear or haze free image. So, here an image dehazing technique, based on combining Contrast Limited Adaptive Histogram Equalization (CLAHE) and Guided filter has been presented. Before applying the proposed algorithm, white balancing is applied to the input image, which helps in adjusting the actual color of the image with respect to white color, to make the output image look more natural. Experiments are carried out on different hazy images, collected from HazeRD dataset, having different haze levels like 50, 100, 200 etc. Results obtained shows that the proposed method can dehaze the hazy image quite effectively and can restore the contrast of the degraded image as well. Experiments are also performed for selecting the desired value of the clip limit for the proposed algorithm. Graphs have been plotted for the results obtained from the experiment, which shows why a particular clip limit is chosen in the proposed algorithm. The purpose of the presented work is to dehaze any hazy input image and get a clear image. Images affected by haze degrades the quality of the image which can create problem in many cases like vision-based physical security system, surveillance, in some medical cases etc. This can also lead to accidents in air, on sea and on the road. So, to avoid such problems and for improving the appearance of the degraded image, dehazing method should be adopted.
State feedback control & Sliding Mode Control of Rotary Inverted Pendulum
(Department of Electrical Engineering, NITS, 2019) Das, Kunal Kanti
Inverted pendulum system is a highly non-linear, unstable system as a result it is a challenging task for the control people to stabilize the system. The system is unstable without control, that is, the pendulum wills simply fall over if the pendulum arm isn’t rotate to balance it and naturally falls downward because of gravity. Thus, the inverted pendulum system is inherently unstable. Stabilization of Inverted Pendulum is defined as a very basic classical control problem in Control System. The Dynamics of Rotary Inverted Pendulum is related to many real life applications like missile launching system, balancing systems like human walking, Aircraft landing pad in sea etc. This is a highly unstable and non-linear system. This system is a under actuated system and also a non-minimum phase system so design a Controller for Inverted Pendulum System is very complex. This thesis includes system description of Inverted Pendulum System, Dynamics of the system, State space model, Derivation of Transfer Functions. In Past a lot of research work has already been done in Inverted Pendulum for development of Control Strategy. In this thesis the system is controlled by State feedback and sliding mode methods. By the help of state feedback method the rotary inverted pendulum is stabilize without any disturbance as the system is highly unstable state feedback method is not sufficient to stable the system even after giving any random disturbance. In the sliding mode method the system is try to stabilize by giving a random disturbance to the system. And there occurs a huge chattering which is very harmful for the system. To reduce the chattering super twisting method is used.
A Symmetric Cryptography Algorithm with 1024 bit Data Block and 512 bit Key with Enhanced Fiestel Cipher
(Department of Computer Science & Engineering, NITS, 2020) Maheshwari, Bharat
The growth of latest technology specially internet and its applications imposes a major concern in respect to information security in terms of protecting essential and confidential content against any possible and vital attacks. Cryptography has made the difference over the period of time by using developed encryption algorithms where some of them have successfully fulfil its designed goals, however others have failed due to specific requirements or encryption/decryption procedures have been recognized. Recent encryption algorithms employed aims mainly to escalate the security levels of sensitive information in order to deliver confidentiality, authentication, integrity, and non-repudiation. In this study, the proposed encryption algorithm has 1024 bit data block as input and combined the permutation and substitution methods for in-round encryption / decryption in-side the enhanced fiestel cipher along with pseudo randomly generated 512 bit key. Key generation and encryption / decryption performing using pseudo random number generation technique and enhanced fiestel cipher with 7 rounds methodology which removes of previous vulnerabilities. Analysis and experimental results have clearly proven solid randomness on key generation, encryption and decryption also enhanced performance and security in which it has met all desired objectives.
Numerical Investigation Of Spray And Combustion Of Gasoline And Diesel Engine Using Adaptive Mesh Refinement
(Department of Mechanical Engineering, NITS, 2020) Barbhuiya, Suleman Hussain
In recent years there has been growing requirement to develop more efficient engines and minimizing engine emissions in a shorter timescale. This is mainly due to increasing demand for fuel economy and tightening legislation for emissions. Computational Fluid Dynamics (CFD), as a rapid and cost effective tool, is being increasingly used in different stages of engine design and optimization. Internal-Combustion (IC) engine performance and emission characteristics are strongly determined by the complex interacting processes of in-cylinder flow, fuel spray injection and combustion. The combustion and spray process plays an important role in engine performance, emission and is therefore attracting great attention in CFD simulations. The complexity involved in IC engine combustion related to interaction of flow, turbulence and spray imposes a greater challenge in simulating combustion using CFD, whereas using CONVERGE software, these above issues can be tackled rapidly and accurately. CONVERGE utilizes the SAGE detailed chemistry solver for modeling the ignition and combustion processes. The present work considers the simulation of gasoline and diesel engine with the help of a CFD package, CONVERGE. Numerical simulation has been carried out to predict the spray breakup and combustion model using adaptive mess refinement (AMR).
Assessing latent initiator based multiple healing in epoxy matrix GFRP laminated composites
(Department of Mechanical Engineering, NITS, 2020-07) Prasad, Tankeshwar
The matrix of any structural materials typically consists of brittle polymer, which is susceptible to crack initiation and growth. To resist this flaw, the concept of self-healing is introduced. Present research work demonstrates a latent initiator based healing agent is used externally into the damage region to restore its original mechanical properties after healing followed by a strong covalent bond at the interface. Also, healing can be possible in the multi-step. In comparison to another healing approach, the healing efficiency of healed samples was found higher compared to the virgin sample. In order to achieve this objective, latent initiator based healing agent grafted silica nanoparticles were synthesized using the one-pot/sol-gel method (IFSs) and multi-step process/post-synthesis grafting method (IGSs). Further, the performance and healing ability IFSs and IGSs reinforced epoxy composites have been investigated. After detail investigations, the results concluded that IFSs/IGSs has no healing capability for the resistance of crack in the epoxy nanocomposites. Looking opportunity towards maximum healing efficiency with unaltered mechanical properties, imidazole as a suitable latent initiator based healing agent for extrinsic healing capabilities of IFSs/epoxy composites using have been investigated. After a successful demonstration towards enhancing the toughening and healing performance of nanocomposites, multiple healing capabilities of GFRPs laminated composites using the same healing agent have been investigated further. Initially, the effect of varying content of imidazole on tensile, flexural and hardness properties of epoxy nanocomposites was demonstrated. Composites (IENC-110) added with 10 wt. % of imidazole and 1 wt. % IFS showed maximum enhancement in tensile strength by 61 % (66 MPa) compare to NE (41 MPa) respectively. However, the tensile modulus is remained unchanged as compared to NE. For flexural properties, the significant enhancement in flexural strength and flexural modulus by ~96 % (102 MPa), and 15 % (2.83 GPa), respectively for IENC-15 composites was found. Similarly, the maximum enhancement in hardness for IENC-110 composites by 19 % (24.57 HV) was found as compared to that of NE (20.71 HV). Further, multiple fracture test of SENB was performed to evaluate fracture toughness and healing performance of epoxy nanocomposites. The results showed the maximum recovery in fracture toughness for IENC-110 composites by 67 % (1.17 MPa.m0.5) as compared to the virgin sample (0.70 MPa.m0.5) was achieved over 3rd number of healing cycles. However, the maximum healing efficiency for IENC-110 composites of 140 % due to critical peak loads while 167 % due to fracture toughness at the 3rd number of healing cycles was achieved. Finally, the appearances of hackel marks in the fracture surface under fractography analysis also justify the significant enhancement in surface roughness. Further, multiple healing capabilities of GFRPs laminated composites using the same healing agent have been investigated. The effect of varying content of imidazole on tensile, flexural and hardness properties of GFRPs composites was demonstrated. The maximum enhancement in tensile strength, tensile modulus, strain and modulus of the toughness of GFI-10 composites of ~34 % (~464 MPa), ~13 % (~6.80 GPa), ~13 % (~8.16 %) and ~64 % (~22 MJ.m-3) respectively were found. This is mainly ascribed to the formation of strong interface between the fiber and the matrix due to the addition of imidazole. Further, the optical micrograph of the tensile fracture surface of the virgin sample showed poor through-thickness delamination where the fibers are failed like a broom. In contrast, the addition of imidazole in epoxy/GFRPs composites restricts the through-thickness delamination and reduced the blooming effect with partial fiber breakages. For flexural properties, the maximum enhancement in flexural strength, flexural modulus, flexural strain and work of flexural of GFI-10 composites of ~34 % (~389 MPa), ~22 % (~19.70 GPa), ~100 % (~0.04 mm/mm) and ~72 % (~16.76 MJ.m-2) respectively were found. This attributed the formation of strong bonding between glass fiber and matrix due to sustaining the more flexural stress. Similarly, for hardness properties, the maximum enhancement in the hardness of composite (IEGF-110) added with 10 wt. % of imidazole and 1 wt. % of IFS of 21 % (74.44 HV) was found. This may be attributed to the high packing density of the final network. Further, multiple fracture test of DCB was performed to evaluate fracture energy and healing performance of GFRPs composites. The results demonstrate a maximum recovery in fracture energy for GFI-10 composites by 83 % (1.87 kJ/m2) as compare to the virgin (0.37 kJ/m2) over 12th healing cycles. It suggests that healing with excess (10 wt. %) imidazole with respect to epoxy within the delamination surface increases the number of bonds that bounds the delaminated surfaces strongly during the repetitive healing. However, the maximum healing efficiency for GFI-10 composites of 154 % due to critical peak loads while 182 % due to fracture toughness at 12th number of healing cycles was achieved. Finally, the optical micrograph of the mid fracture surface of DCB samples showed the relatively rough fractures surface because of fiber bridging and fiber pull-out for GFI-10. Thus, the capability of imidazole to restrict the damage in FRPs composites is evident from the fractography investigation. This work successfully demonstrates the capability of imidazole introduce healing capability in GFRPs.

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