Showing papers by "National Institute of Technology, Silchar published in 2019"
TL;DR: The state-of-the-art storage systems and their characteristics are thoroughly reviewed along with the cutting edge research prototypes and the potential application fields are identified.
Abstract: It is an exciting time for power systems as there are many ground-breaking changes happening simultaneously. There is a global concensus in increasing the share of renewable energy-based generation in the overall mix, transitioning to a more environmental-friendly transportation with electric vehicles as well as liberalizing the electricity markets, much to the distaste of traditional utility companies. All of these changes are against the status quo and introduce new paradigms in the way the power systems operate. The generation penetrates distribution networks, renewables introduce intermittency, and liberalized markets need more competitive operation with the existing assets. All of these challenges require using some sort of storage device to develop viable power system operation solutions. There are different types of storage systems with different costs, operation characteristics, and potential applications. Understanding these is vital for the future design of power systems whether it be for short-term transient operation or long-term generation planning. In this paper, the state-of-the-art storage systems and their characteristics are thoroughly reviewed along with the cutting edge research prototypes. Based on their architectures, capacities, and operation characteristics, the potential application fields are identified. Finally, the research fields that are related to energy storage systems are studied with their impacts on the future of power systems.
259 citations
TL;DR: IoT’s novel factors affecting traditional computer forensics are explored, including its strengths and weaknesses, and several indispensable open research challenges are identified as future research directions.
232 citations
TL;DR: The results show that both the considered metaheuristics are effective in finding the optimal design; however, water cycle algorithm has marginally better design solution than the other two algorithms.
164 citations
TL;DR: In this paper, the authors summarized the mixing enhancement approaches based on well-known cavity based injection scheme proposed in latest research works, and the influence of cavity on the performance of scramjet combustor is recapitulated from three aspects, namely variation of shape/geometry of cavity flame holder; location of fuel/air injection scheme; and recent progresses in dual/double cavity.
138 citations
TL;DR: A concrete and comprehensive plan should be adopted for zero tolerance against plastics waste and peoples participation is a must to achieve the full success as discussed by the authors The Government Agencies and Non-government organization of different nations have adopted many policies and laws to curb the harmful effects of plastics and microplastics.
Abstract: Plastics are synthetic polymer compound mostly made from petrochemical sources, such compound has high molecular mass and plasticity and certain chemicals are added to increase the performance and efficiency of the products. Plastics size less than 5 mm are categorized as Microplastics and it is one of the greatest potential threat to marine environment for the whole world. There are two types of micro-plastics i.e. primary micro-plastics and secondary micro-plastics. Primary microplastics are the by-products of particulate emissions released from industrial production, the release of plastics dust from plastics products. Secondary microplastics are larger plastic particulate material. These micro-plastics eventually end up in water bodies travelling all the way from rivers to seas or oceans. Microplastic can also act as a pollutant transport medium for other toxic elements such as DDT and hexachlorobenzene and eventually end up within the body of a living organism who consume it. The Government Agencies and Non-government organization of different nations have adopted many policies and laws to curb the harmful effects of plastics and microplastics. A concrete and comprehensive plan should be adopted for zero tolerance against plastics waste and peoples participation is a must to achieve the full success.
117 citations
TL;DR: In this article, the mixing and pressure drop characteristics for flow through a wavy micromixer of two geometrical configurations, namely raccoon and serpentine, were numerically analyzed.
Abstract: We numerically analyze the mixing and pressure drop characteristics for flow through wavy micromixer of two geometrical configurations, namely raccoon and serpentine for different values of amplitude of the waviness of the mixer (α), wavelength of the waviness (λ), Reynolds number(Re) and Schmidt number(Sc). Three different flow regimes are identified depending on the parameters influencing the mixing index. The mixing index for both the raccoon and serpentine mixer is very close to unity in the first regime (0.1
96 citations
TL;DR: In this paper, the authors analyzed magnetohydrodynamic natural convection heat transfer and entropy generation in rhombic enclosures filled with Cu-water nanofluids and found that at low Ra, the heat transfer rate remains invariant with the variation in Ha.
84 citations
TL;DR: The numerical application of the proposed approach demonstrates higher forecasting accuracy in comparison to traditional approach of integrating temperature into STLF without considering any seasonality effect, which is found essential for a precise STLF under diverse seasonal meteorological conditions.
74 citations
TL;DR: A UAV-assisted emergency Wi-Fi network is proposed to expedite the rescue operations by guiding the survivors to the nearest rescue camp location and is capable of doing on-site surveillance and transmitting the data to the relief center for better rescue planning.
Abstract: Designing a reliable, resilient, and quickly deployable emergency communication network is a key challenge for post-disaster management. In this paper, a UAV-assisted emergency Wi-Fi network is proposed to expedite the rescue operations by guiding the survivors to the nearest rescue camp location. Here, the Raspberry PI (RPI) development board, mounted on UAV is considered to form a Wi-Fi chain network over the disaster region. During network set-up, the proposed solutions for the design challenges like UAV synchronization, avoid communication disruption and surveillance data management are the key contributions of this paper. The designed UAV network is capable of doing on-site surveillance and transmitting the data to the relief center for better rescue planning. One major challenge is to alert a survivor about the emergency network, which is addressed by designing a captive portal. Furthermore, to extend the Wi-Fi network, an Android-based application is developed by which each smartphone acts as a relay for its neighbor. Three types of field experiment are carried out to evaluate the performance of the designed prototype. It is found from the field results; the Wi-Fi access point mode and user datagram protocol are more suitable for network design as compared to Ad-Hoc mode and transmission control protocol, respectively. It is also observed from the experiment that the maximum hop distance for the prototype is 280 meters and 290 meters for a Wi-Fi configuration following IEEE 802.11n and IEEE 802.11ac protocol, respectively.
68 citations
TL;DR: An overview of additive manufacturing used in the manufacturing of fiber-reinforced polymeric composite materials is provided in this paper, where the authors delineate different additive manufacturing processes, formulations of different materials, drawbacks, and strengths associated with different additive Manufacturing processes.
68 citations
TL;DR: In this article, a generic multivariate adaptive regression splines-based approach for dynamics and stability analysis of sandwich plates with random system parameters is presented, where the propagation of uncert...
Abstract: This paper presents a generic multivariate adaptive regression splines-based approach for dynamics and stability analysis of sandwich plates with random system parameters. The propagation of uncert...
TL;DR: This paper presents condition monitoring aspects of induction motor, its present status with possible mitigation schemes and future maintenance challenges, and comprehensively analyze in the reported literature in a sequential manner.
Abstract: This paper presents condition monitoring aspects of induction motor, its present status with possible mitigation schemes and future maintenance challenges. The induction motors constitute the major portion of motors in domestic and industrial applications. These motors experience different types of failures and faults associated with insulation, bearing, stator, rotor, and eccentricity. As a matter of fact, these faults may subsequently enhance the probability of failures unless proper introspection is not accomplished. In order to reduce the failure time and operating cost, early detection is indispensable which necessitates condition-based approach on contrary to scheduled maintenance. The condition monitoring is a strong candidate to address the diagnosis of machinery failure problems and unreliability. In this context, a comprehensive analysis is reported in the literature with a focus on different methodologies being addressed for such objective. Utmost efforts are made to comprehensively analyze in the reported literature in a sequential manner citing the advantage and limitations in this paper. The authors hopefully described and illustrated the associated problems with possible mitigation in the context of condition monitoring which would be immensely helpful for future researchers working in these aspects and the future roadmap would be clearly reflected.
TL;DR: The simulation results indicate that the proposed HWPSO algorithm outperforms many state of the art algorithms by achieving a better optima with a very low standard deviation for most of the benchmark functions used.
Abstract: In this paper, a new population based hybrid meta-heuristic algorithm called the Hybrid Whale-Particle Swarm Optimization Algorithm (HWPSO) for solving complex optimization problems has been proposed. The proposed algorithm tries to overcome the limitations associated in a Particle Swarm Optimization (PSO) exploration phase i.e. Stagnation Effect, by hybridizing with a whale optimization algorithm (WOA) in a novel way as WOA has been reported to have very good exploration capability. During hybridization, two novel techniques have been employed, namely ‘Forced’ Whale and ‘Capping’ Phenomenon. The ‘Forced’ WOA is introduced in exploration phase and it enables the WOA to guide PSO for better local optima avoidance and concurrently a new ‘Capping’ phenomenon is employed which restricts the WOA search mechanism during exploitation phase, thereby converging the solution faster to a global optimum value. The performance of the proposed HWPSO has tested on 18 benchmark mathematical functions and 3 Electronics Design Optimization problems. The simulation results indicate that the proposed algorithm outperforms many state of the art algorithms by achieving a better optima with a very low standard deviation for most of the benchmark functions used. The effectiveness of the proposed HWPSO has been also validated by statistical as well as complexity analysis. The performance of HWPSO algorithm is also found to be satisfactory in all three cases of electronics design optimization problems, which have been further validated with standard design tools and found to be in close agreement with each other.
29 Mar 2019
TL;DR: This paper has given that software determination to robotically classify and categorize groundnut leaf diseases using KNN classifier algorithm to improve production of crops.
Abstract: One of the ultimate key factors besttow less yield is disease attack. The groundnut plant disease such as fungi, soil borne and viruses. In this paper, we are given that software determination to robotically classify and categorize groundnut leaf diseases. This method will improve production of crops. It comprises of number of steps viz. image acquisition, image pre-processing, segmentation, features extraction and classifier using K Nearest Neighbor (KNN). To increase performance of existing algorithm the SVM classifier is replaced with KNN classification. In this paper we categorized only 4 different disease using KNN classifier algorithm.
TL;DR: In this article, the stochastic buckling behavior of sandwich plates is analyzed considering uncertain system parameters (material and geometric uncertainty) using higher-order-zigzag theory (HOZT) and finite element model to evaluate the random first three buckling loads.
TL;DR: In this paper, the use of Musa acuminata (banana peel ash) as a heterogeneous catalyst for C-C bond formation via a Henry reaction under solvent-free conditions at ambient temperature was reported.
Abstract: Owing to the depletion of resources coupled with increasing waste generation, the conversion of waste biomass to value-added materials has gained interest. Here, we report for the first time the application of Musa acuminata (banana) peel ash (MAPA) as a heterogeneous catalyst for C–C bond formation via a Henry reaction under solvent-free conditions at ambient temperature. The catalyst was well characterized using different analytical techniques like FT-IR, SEM, TEM-EDS, XRD, XRF, XPS, BET and TGA, along with basicity determination by a Hammett indicator test and titration method. An excellent yield of nitroalcohol was obtained within 15–30 minutes. No dehydrated product was observed. The catalyst used in these studies has the advantage of being a waste material and is hence low-cost, easily prepared, recyclable and environmentally friendly. In addition, the use of a biogenic renewable catalyst, its atom economy, and room temperature and solvent-free reaction conditions and the avoidance of column chromatography make the protocol highly significant from green and sustainable chemistry perspectives.
TL;DR: In this paper, the authors analyzed the performance of laminar flow through a triangular corrugated channel and found that the rate of heat transfer is augmented with both Reynolds number and amplitude of wall waviness, together with increase in pressure drop.
Abstract: We analyse the thermo-hydraulic performance and entropy-generation characteristics for laminar flow through triangular corrugated channel. Results are presented in terms of heat transfer, pressure drop and entropy generation for different values of amplitude of waviness of the channel, wavelength and Reynolds number in the range of 5–500. It is found that the rate of heat transfer is augmented with both Reynolds number and amplitude of the wall waviness, together with increase in pressure drop. The enhancement in heat transfer and pressure drop as compared to equivalent straight channel are also assessed by performance factor combining the enhancement in heat transfer and corresponding increase in pressure drop. There is an intricate interplay between the geometrical parameters of the channel and the flow parameters in dictating the performance factor. Thermal entropy generation is dominant over the fluid friction for lower Reynolds number. The total entropy generation increases rapidly up to critical Reynolds number (Recri), after which it either remains almost constant or decreases gradually, and moreover Recri depends on the wavelength of the channel. The outcomes of the present work may be helpful to design the efficient and economic thermal devices and systems.
TL;DR: In this paper, the authors discussed the important aspects along with the promotion policies which are adopted by the Indian government for enlarging the country's own energy security by proper utilization of available renewable energy sources.
TL;DR: In this article, the effect of source-uncertainties on low-velocity impact of functionally graded material (FGM) plates following a coupled surrogate based finite element simulation approach is quantified.
Abstract: This paper quantifies the compound effect of source-uncertainties on low-velocity impact of functionally graded material (FGM) plates following a coupled surrogate based finite element simulation approach. The power law is employed to evaluate the material properties of FGM plate at different points, while the modified Hertzian contact law is implemented to determine the contact force and other parameters in a stochastic framework. The time dependent equations are solved by Newmark's time integration scheme. Insightful results are presented by investigating the effects of degree of stochasticity, oblique impact angle, thickness of plate, temperature, power law index, and initial velocity of impactor following both probabilistic and non-probabilistic approaches along with in-depth deterministic analyses. A detail probabilistic analysis leading to complete probabilistic characterization of the structural responses can be carried out when the statistical distribution of the stochastic input parameters are available. However, in many cases concerning FGM, these statistical distributions may remain unavailable due to the restriction of performing large number of experiments. In such situations, a fuzzy-based non-probabilistic approach could be appropriate to characterize the effect of uncertainty. A surrogate based approach based on artificial neural network coupled with the finite element model for low-velocity impact analysis of FGM plates is developed for achieving computational efficiency. The numerical results reveal that the low-velocity impact on FGM plates is significantly influenced by the effect of inevitable source-uncertainty associated with the stochastic system parameters, whereby the importance of adopting an inclusive design paradigm considering the effect of source-uncertainties in the impact analysis is established.
TL;DR: An integrated expert system comprising of Takagi–Sugeno–Kang fuzzy model with subtractive clustering with fuzzy logic has been developed for prediction surface roughness in green AWJM and the result shows that, predictions through TSK–FL model are comparable with experimental results.
Abstract: The aim of this paper is to process modelling of AWJM process on machining of green composites using fuzzy logic (FL). An integrated expert system comprising of Takagi–Sugeno–Kang (TSK) fuzzy model with subtractive clustering (SC) has been developed for prediction surface roughness in green AWJM. Initially, the data base is generated by performing the experiments on AWJM process using Taguchi $$(\hbox {L}_{27})$$ orthogonal array. Thereafter, SC is used to extracts the cluster information which are then utilized to construct the TSK model that best fit the data using minimum rules. The performance of TSK–FL model has been tested for its accuracy in prediction of surface roughness in AWJM process using artificially generated test cases. The result shows that, predictions through TSK–FL model are comparable with experimental results. The developed model can be used as systematic approach for prediction of surface roughness in green manufacturing processes.
TL;DR: In this paper, the effect of lime and discrete plastic fiber on the strength and stiffness behaviour of clayey soil was investigated using a series of unconfined compressive strength (UCS), split-tensile strength (S...
Abstract: This paper studies the effect of lime and discrete plastic fibre on the strength and stiffness behaviour of clayey soil. A series of unconfined compressive strength (UCS), split-tensile strength (S...
TL;DR: The proposed controller can deliver robust closed-loop response of BGC within a specified range of parametric uncertainty and meal disturbances owing to the appropriately tuned bound of LMI region parameters.
01 Dec 2019
TL;DR: Results from simulation, security and statistical analyses show that the proposed encryption algorithm can be used for multiple medical images encryption and quickens the encryption time.
Abstract: With the rise in medical imaging tools and telemedicine technology, the distance barriers in providing health care have been reduced by communicating patients data over the internet. To provide patients with privacy, the data are encrypted while transmitting over the insecure network. The paper proposes an encryption scheme for multiple medical images using a new finding in elliptic curve analogue ElGamal cryptosystem and Mersenne Twister pseudo-random number generator. The new finding quickens the encryption time as well as solve the problem of data expansion associated with ElGamal cryptosystem. Results from simulation, security and statistical analyses show that the proposed encryption algorithm can be used for multiple medical images encryption.
TL;DR: In this article, a comparative analysis of the trigate fin-shaped field effect transistor (FinFET) and quantum FinFET was carried out by using density gradient quantization models in the Synopsys three-dimensional (3D) technology computer-aided design (TCAD) platform.
Abstract: A comparative analysis of the trigate fin-shaped field-effect transistor (FinFET) and quantum FinFET (QFinFET) is carried out by using density gradient quantization models in the Synopsys three-dimensional (3-D) technology computer-aided design (TCAD) platform. The gate dielectric stack comprising 0.5 nm SiO2 (k = 3.9) and 2 nm HfO2 (k = 22) contributes to an effective oxide thickness of 0.86 nm and is kept constant throughout the study. The results demonstrate that the QFinFET can overcome the limitations of current FinFET devices when scaling down to the atomic level. An analytical model including quantum-mechanical effects for evaluation of the drain current of the FinFET is established and validated using the TCAD software. The degradation in the drive current with downscaling of the fin thickness for the trigate FinFET and the increase in the drive current for the QFinFET are presented. The results are improved by taking into account different channel lengths and body thicknesses to estimate the drain current–gate voltage and gate capacitance–gate voltage characteristics for both the trigate FinFET and QFinFET. The drain-induced barrier lowering and subthreshold swing are also analyzed for the trigate FinFET and QFinFET at different technology nodes, revealing excellent characteristics. It is clearly established that the QFinFET can overcome the limitations faced by current FinFET devices when scaling the silicon down to the atomic level and may represent the next generation of FinFET devices.
TL;DR: It is demonstrated that the SnO2-CNTs can provide a one stop solution for water remediation as it effectively accomplished the major treatment tasks like adsorption, catalytic transformation/degradation and disinfection.
Abstract: Herein, we described a biogenic, additive fee, eco-friendly synthesized SnO2-CNT nanohybrid as an efficient, re-collectable and reusable material for onsite water remediation. We demonstrated that the SnO2-CNTs can provide a one stop solution for water remediation as it effectively accomplished the major treatment tasks like adsorption, catalytic transformation/degradation and disinfection. The structural, morphological, surface chemical compositions of the nanocomposite and the adsorption, catalytic and antimicrobial properties were investigated using common characterization and instrumental techniques. The results revealed the brilliant efficiency of SnO2-CNT nanoadsorbent towards As (III) and a maximum Langmuir adsorption capacity of 106.95 mg/g was observed at high arsenite concentration (C0 = 1 mg/L). The nanoadsorbent was also found to be equally efficient in low arsenite concentration ranges (C0 = 100 μg/L) as it could bring down the arsenic concentration below maximum permissible limit. Moreover, using model pollutants like p-nitrophenol, Alizarin red S, Metronidazole, bacterial strains (Bacillus subtilis, Escherichia coli, Streptococcus pneumonia etc.), and fungal strains (Aspergillus niger and Candida albicans), the multifunctional capability of SnO2-CNT towards water decontamination has been established. Our results suggested the promising potential of hierarchical nano-heterojunctions for engineering efficient water treatment processes.
TL;DR: In this paper, multi-parametric artificial intelligence (AI) based gene expression programming (GEP) models have been developed for mapping the input (engine load, Kerosene share and Ethanol share) and output (Bth, BSEC, NOX, UHC and CO) relationship under Diesosenol platforms.
14 Mar 2019
TL;DR: This article considers a lightweight and secure session-key establishment scheme for smart home networks and incorporates the Diffie–Hellman (DH) key exchange as an alternative method.
Abstract: The development of the applications of Internet of Things (IoT) technology continues to grow steadily-one of the top applications being smart home environments. A smart home comprises digital devices and systems that operate inside a home to bring efficiency to home life. Devices with low computational ability and devices with high computational ability work together in a smart home network, and therefore, communication between devices needs to be secure. This article considers a lightweight and secure session-key establishment scheme for smart home networks and incorporates the Diffie-Hellman (DH) key exchange as an alternative method. A trusted service provider provides the algorithm parameters to the devices so that a public key can be established between the home gateway and a smart device. The proposed scheme is formally analyzed using Security Protocol Animator for Automated Validation of Internet Security Protocol and Applications (AVISPA).
TL;DR: Full-color and white-color micro light-emitting diodes (μLEDs) using InGaN/AlGaN core-shell nanowire heterostructures, grown on silicon substrate by molecular beam epitaxy demonstrate strong and highly stable white-light emission with high color rendering index.
Abstract: We have demonstrated full-color and white-color micro light-emitting diodes (μLEDs) using InGaN/AlGaN core-shell nanowire heterostructures, grown on silicon substrate by molecular beam epitaxy. InGaN/AlGaN core-shell nanowire μLED arrays were fabricated with their wavelengths tunable from blue to red by controlling the indium composition in the device active regions. Moreover, our fabricated phosphor-free white-color μLEDs demonstrate strong and highly stable white-light emission with high color rendering index of ~ 94. The μLEDs are in circular shapes with the diameter varying from 30 to 100 μm. Such high-performance μLEDs are perfectly suitable for the next generation of high-resolution micro-display applications.
TL;DR: An in-depth analysis of the effects of class imbalance and class overlapping in conventional learning models has been presented and the proposed model evolves to eliminate borderline, redundant and overlapping cases with the account of Tomek-link pair and sparse neighbourhood.
Abstract: The class imbalance problem engraves the traditional learning models by degrading performance and yielding erroneous outcomes. It is the scenario where one of the class representation is over-shado...