(SoE) School of Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

This paper deals with joint optimization of production scheduling and group maintenance planning in single machine system with multi units arranged in series. The objective is to achieve optimum production sequence, preventive maintenance (PM) intervals and grouping of units which minimize the total integrated cost per unit time of the system. Teaching-Learning Based Optimization (TLBO) algorithm is applied to optimize the objective function. The peculiarity of TLBO as against other algorithms is that it is independent of algorithm specific parameters. The largest order value rule is utilized to retrieve the permutation vector while grouping of units is performed under PM intervals. Computational results reveal the effectiveness of the proposed approach. © 2020 The Authors.

World University root node

Mechanical Engineering

Fulltext

Procedia CIRP

Integration of production scheduling and group maintenance planning in multi-unit system employing TLBO algorithm

Additive Manufacturing (AM) is one of several technological breakthroughs in the world, and Nanotechnology is the science of manipulating matter on an atomic, molecular, and supramolecular scale. Integration of both these domains can create wide variety of materials for new and innovative applications. In certain applications related to the fabrication of intricate structure and complex shapes, nanomaterials can help ease the manufacturing process and enhancement in the properties. This also leads to the development of some new and potential applications in biological sciences, space sciences, agriculture, and medicine. With the approach of using nanomaterials in additive manufacturing, we can make the new technology accessible to the inaccessible and more sustainable by easing the processing of the materials. In the past few years, there have been a lot of advancements in the integration of nanomaterials in AM for various applications. This review briefly comprehends these recent research and future of nanomaterial in AM. © 2020 Elsevier Ltd

Computer Science and Engineering

Current Opinion in Chemical Engineering

Recent developments of nanomaterial applications in additive manufacturing: a brief review

Herein, bimodal-reinforced AlCoCrFeNi complex concentrated alloy composite cladding on stainless steel 316L substrate using microwave hybrid processing is synthesized. Detailed microstructural analysis of the claddings shows the presence of cellular structure A2 (disordered BCC) with intermetallics (B2 (ordered BCC) and σ phases) at the intercellular regions. The presence of Cr23C6 is also observed for the reinforced claddings due to the dissociation of the SiC particles. The bimodal-reinforced cladding shows the highest hardness (in excess of 800 HV) and fracture toughness (≈12 MPa√m), followed by micro- and nanocomposite claddings. Under slurry erosion condition, the bimodal composite cladding exhibits 10 times better erosion resistance than stainless steel 316L and nonreinforced cladding (1.5–2 times), respectively, at oblique angle followed by nano- and microreinforced unimodal counterparts. The outstanding performance of the bimodal composite cladding under both test conditions is related to higher hardness, fracture toughness, and resistance to plastic deformation. The detailed analysis of the eroded samples shows microcutting and ploughing as a dominant mechanism at an oblique angle while platelets, cracks, and microindents being the contributing factors for erosion at the normal impact angle. © 2020 Wiley-VCH GmbH

Advanced Engineering Materials

Slurry Erosion–Corrosion of Bimodal Complex Concentrated Alloy Composite Cladding

In this work, we examined the impact of gate work-function and back-gate bias to enhance sensing metrics of a Dielectric Modulated (DM) p-type Tunnel Field Effect Transistor (p-TFET) based biosensor. The sensing metrics, namely Sensitivity (S) and Selectivity (ΔS) are considerably improved by using a lower value of gate work-function and positive back gate voltages. It is shown that by appropriate selection of gate work-function and back gate bias, Band-to-Band Tunneling (BTBT) of carriers is reduced and a significant change in electrical characteristics is observed in a device with an empty cavity. Therefore, the relative change in the drain current due to the presence of biomolecules in the nanogap cavity is maximized. Results indicate a Sensitivity of ∼109 for 3-aminopropyltriethoxysilane (APTES) biomolecule, and Selectivity of ∼102 for APTES concerning Biotin biomolecule in an optimally designed p-TFET biosensor. The impact of location, as well as the charge of biomolecules, are also analyzed in this work. Results showcase the additional degree of freedom through device optimization which facilitates the tunability of sensing metrics for improved biosensor performance. © 2020 IOP Publishing Ltd.

Electrical Engineering

Engineering Research Express

Investigation the impact of the gate work-function and biases on the sensing metrics of TFET based biosensors

Blind Image Quality Assessment (BIQA) has been an enticing research problem in image processing, during the last few decades. In spite of the introduction of several BIQA algorithms, quantifying image quality without the help of a reference image still remains an unsolved problem. We propose a method for BIQA, combining Natural Scene Statistics (NSS) feature and Probabilistic Quality representation by a CNN. A certain number of features are considered for each image. We also propose to increase the NSS feature set alongside with the same CNN architecture and compare its results accordingly. Support Vector Machine (SVM) regression is applied on these features to get a quality score for that particular image. The results obtained by applying the proposed quality score on benchmark datasets, show the effectiveness of the proposed quality metric compared to the state-of-the-art metrics. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Multimedia Tools and Applications

Blind image quality assessment using a combination of statistical features and CNN

Background: Automatic Machine Translation (AMT) Evaluation Metrics have become popular in the Machine Translation Community in recent times. This is because of the popularity of Machine Translation engines and Machine Translation as a field itself. Translator is a very important tool to break barriers between communities especially in countries like India, where people speak 22 different languages and their many variations. With the onset of Machine Translation engines, there is a need for a system that evaluates how well these are performing. This is where machine translation evaluation enters. Objective: This paper discusses the importance of Automatic Machine Translation Evaluation and compares various Machine Translation Evaluation metrics by performing Statistical Analysis on various metrics and human evaluations to find out which metric has the highest correlation with human scores. Methods: The correlation between the Automatic and Human Evaluation Scores and the correlation between the five Automatic evaluation scores are examined at the sentence level. Moreover, a hypothesis is set up and p-values are calculated to find out how significant these correlations are. Results: The results of the statistical analysis of the scores of various metrics and human scores are shown in the form of graphs to see the trend of the correlation between the scores of Automatic Machine Translation Evaluation metrics and human scores. Conclusion: Out of the five metrics considered for the study, METEOR shows the highest correlation with human scores as compared to the other metrics. © 2020 Bentham Science Publishers.

Recent Advances in Computer Science and Communications

Statistical analysis of machine translation evaluation systems for English-Hindi language pair

Chitosan is a linear natural polymer obtained by deacetylation of chitin using sodium hydroxide. Depending on the manufacturing process as well as its source, chitosan is commercially available in various types and grades with molecular weights (MW) ranging from 38 to 200 kDa and degree of deacetylation (DD) with a range between 60 to 100%. In this work, chitosan films of different degrees of deacetylation (DD) and molecular weights (MW) were prepared by the solution casting method at concentrations of 1%, 2%, and 3%. The influence of DD and MW were studied on the prepared films using various characterization techniques such as dressing pH, water absorption capacity, water vapour transmission rate (WVTR), porosity, and water contact angle (WCA). The water absorption capacity, water vapour transmission rate (WVTR), and porosity results showed that there were significant effects of DD, MW, and concentration on the above-mentioned films. © 2020 Scientific Publishers. All rights reserved.

Chemical Engineering

Journal of the Indian Chemical Society

Effect of degree of deacetylation and molecular weight on physicochemical properties of chitosan films

Background: In modern electrical power distribution systems, Power Quality has become an important concern due to the escalating use of automatic, microprocessor and microcontroller based end user applications. Methods: In this paper, power quality improvement has done using Photovoltaic based Distribution Static Compensator (PV-DSTATCOM). Complete simulation modelling and control of Photovoltaic based Distribution Static Compensator have been provided in the presented paper. In this configuration, DSTATCOM is fed by solar photovoltaic array and PV module is also helpful to maintain the DC link voltage. The switching of PV-STATCOM is controlled by Unit template based control theory. Results: The performance of PV-DSTATCOM has been evaluated for Unity Power Factor (UPF) and AC Voltage Control (ACVC) modes. Here, for studying the power quality issues three-phase distribution system is considered and results have been verified through simulation based on MATLAB software. Conclusion: Different power quality issues and their improvement are studied and presented here for harmonic reduction, DC voltage regulation and power factor correction. © 2020 Bentham Science Publishers.

Recent Advances in Electrical and Electronic Engineering

Unit template based control of PV-DSTATCOM

Vibrational study of the porous functionally graded plate with geometric discontinuities and partial supports has been presented in the present paper. The kinematics of functionally graded plate is based on the refined exponential shear deformation theory. The displacement field has been refined by dividing the in-plane and out of the plane displacements into bending and shear components. The theory accounts for the nonlinear transverse shear stress variation along with the thickness with only four unknowns. The closed-form solution (Navier’s solution), as well as FEM-based solution, have been used for the vibration analysis of functionally graded plate. The geometric discontinuities have been incorporated in terms of a circular cut-out of different sizes at the center of the plate. Modified rule of mixtures, modified sigmoid law, and trigonometric law have been used to compute the effective material properties of the functionally graded plate. A C0 continuous iso-parametric FEM formulation has been used to attain the results in the case of FEM solution, and the efficacy of the present solution is demonstrated by comparing the results with the available literature. The results reflect that the porosity inclusion, circular cut-out, and position of the boundary constraints have a notable influence on the fundamental frequency of the functionally graded plate. It is also concluded that after a specific radius of circular cut-out, the vibration response of functionally graded plate exhibits nonlinearity in nature. © IMechE 2020.

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Vibration of porous functionally graded plates with geometric discontinuities and partial supports

In present communication, a solar dryer having semi-transparent photovoltaic thermal (SPVT) roof has been used to dry bitter gourd. Experimentation has been done and results were validated with linear regression method through mathematical modelling as well as for non-linear Artificial Neural Network (ANN) modelling has been used. The experimental data namely, ambient air temperature, moisture evaporated, bitter gourd surface temperatures, solar intensity on different surfaces of dryer, room temperature and relative humidity have been recorded for the climatic condition of Varanasi, UP, India. The numerical value of convective heat transfer coefficients for bitter gourd found to be between 0.69–14.45 W/m2 K. The results for mass transfer (moisture evaporated) during drying of bitter gourd from theoretical model (linear regression method and ANN) and experiments showed good agreement. Further, net electrical energy, thermal energy and overall thermal energy were found to be 0.62, 3.77 and 5.41 kWh/m2/day respectively. The payback period at 10\% interest rate and 4\% inflation rate with ₹ 50 ($0.77) and ₹ 100 ($1.54) saving rate per kg were found to be 1.47 and 0.72 years respectively. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.