National Institute of Technology, Silchar

About: National Institute of Technology, Silchar is a education organization based out in Silchar, Assam, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1934 authors who have published 4219 publications receiving 41149 citations. The organization is also known as: NIT Silchar.

Characterisation of layer deposited by electric discharge coating process

Abstract: The present work focuses on characterisation of the deposited layer on aluminium substrate processed with electric discharge coating process. Different characterisation techniques such as scanning electron microscopy, energy dispersive X-ray and X-ray diffraction (XRD) have been employed to study the surface morphological changes, presence of materials and their phase transformations due to the formation and deposition of composite material layer on work surface. The grain size of the deposited particles has a significant effect on mechanical properties. Thus, an attempt has been made to calculate the grain size, dislocation density and microstrain of deposited material and its particles. The formation of tungsten carbides, namely, WC and W2C, is detected through XRD analysis. Clusters of globular particles in nanoscale are observed throughout the deposited layer.

Evaluation of Liquefaction Potential of Pond Ash

Abstract: India is facing a serious problem of effective disposal of huge quantity of fly ash generated from thermal power plants. Fly ash is highly susceptible to liquefaction and thus the rehabilitation of ash ponds requires a detailed study on evaluation of liquefaction potential so that suitable densification measures can be adopted. This paper contains various steps of evaluation of liquefaction potential of pond ash.

Role of Fly Ash in the Removal of Organic Pollutants from Wastewater

Abstract: Fly ash, a relatively abundant and inexpensive material, is currently being investigated as an adsorbent for the removal of various organic pollutants from wastewater. The wastewater contains various types of phenolic compounds, such as chloro, nitro, amino, and other substituted compounds. Various types of pesticides, such as lindane, malathion, carbofuran, etc., and dyes, such as, methylene blue, crystal violet, malachite green, etc., are also present in the wastewater. These contaminants pollute the water stream. These organic pollutants, such as phenolic compounds, pesticides, and dyes, etc., can be removed very effectively using fly ash as adsorbent. This article presents a detailed review on the role of fly ash in the removal of organic pollutants from wastewater. Adsorption of various pollutants using fly ash has been reviewed. The adsorption mechanism and other influencing factors, favorable conditions, and competitive ions, etc., on the adsorption process have also been discussed in this paper. I...

Resonant characteristics of aperture type FSS and its application in directivity improvement of microstrip antenna

Abstract: In this paper, we propose an aperture type frequency selective surface (FSS) by employing an array of 12 × 12 unit cell elements and its resonant characteristics is analyzed. A resonant cavity antenna is then formed by the ground plane substrate and the FSS superstrate. The high reflective behavior of the proposed FSS at an offset of the resonance is then utilized for improving the performance of this cavity antenna. The impedance bandwidth and directivity are improved up to 0.66 GHz and 8.95 dBi, simultaneously at an optimum gap of 17.6 mm between the antenna substrate and FSS superstrate. For validation purpose, prototypes of both patch antenna and FSS, are fabricated and characterized. A fairly good agreement is achieved between the measured and simulated results.

A Comparative Study on Prediction of Monthly Streamflow Using Hybrid ANFIS-PSO Approaches

Abstract: Monthly prediction of streamflow is a fundamental and complex hydrological phenomenon. Accurate streamflow prediction helps in water resources planning, design, and management, particularly for hydropower production, irrigation, protection of dams and flood risk management. Hence, in this paper, a hybrid robust model integrating adaptive neuro-fuzzy inference system (ANFIS) with particle swarm optimization (PSO) algorithm was developed for monthly streamflow prediction of Barak River basin, India. Multiple factors like Precipitation (Pt), temperature (Tt), humidity (Ht), Infiltration loss (It), are considered as the inputs for determining the streamflow. For validating the model performance, 70% of data (1980–2007) were used for training them and 30% of data (2008–2019) were used for testing them. A comparison is made between results of developed hybrid model with simple artificial neural network (ANN) and ANFIS models for assessing accuracy and efficiency of model performances. Obtained results of proposed models were evaluated based on four assessment indices including by Root Mean Square Error (RMSE), Mean Absolute Error (MAE), determination coefficient (R2) and Nash-Sutcliffe Coefficient (ENS). Based on comparison of results, it was concluded that robust ANFIS-PSO model with RMSE = 5.887, MAE = 4.978, R2 = 0.9668, and ENS = 0.961 demonstrated best performance with more reliability and accuracy in comparison to ANFIS and ANN models. Findings of this research proved that hybrid ANFIS with an evolutionary optimization algorithm is a reliable modelling approach for monthly streamflow prediction.