(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 proposes an analytical model for predicting grinding-induced sub-surface damage depth in a silicon wafer. The model integrates the dislocation kinetics for crack initiation and fracture mechanics for crack propagation for the first time. Unlike other conventional models, the proposed model considers the effects of strain rate on damage depth and the dynamically changing metastable phase change properties. The model is verified by grinding experiments and a comparison of theoretical and experimental results shows a good quantitative agreement. It is found that increasing grinding speed and decreasing depth of cut cause a higher strain rate so as to enhance material brittleness, which is favorable to achieving low sub-surface damage. These findings will pave a way towards optimizing the grinding parameters and greatly improving the production efficiency of hard and brittle materials. © 2021 CIRP

World University root node

Mechanical Engineering

Fulltext

CIRP Journal of Manufacturing Science and Technology

An analytical model to predict the depth of sub-surface damage for grinding of brittle materials

The probabilistic seismic hazard analysis is conducted for the seismically active National Capital Region (NCR) of India, one of the most densely populated regions in the world, to quantify the peak ground acceleration (P GA) at bedrock level by considering seismogenic source characteristics, smoothened grid seismic zoning, magnitude recurrence model, uncertainties, and suites of suitable ground motion prediction equations. The spatial distribution of the resulting P GA value is presented using GIS for the entire NCR of India for 10% and 2% probability of exceedance in 50 years and 100 years. The estimated P GA values are found to vary in the range of 0.12 to 0.37 g and 0.15 to 0.40 g for a 2% probability of exceedance in 50 years and 100 years, respectively. And the P GA values range from 0.07 to 0.33 g and 0.08 to 0.35 g for the 10% probability of the exceedance in 50 years and 100 years, respectively. The results reveal that the eastern region of the study area falls under high seismicity due to its proximity to the Himalayan zone, a highly seismically active region. High P GA values are also observed for south-eastern regions of the NCR of India due to the vicinity of the Great-Boundary fault, Mathura fault, Moradabad fault. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Civil Engineering

Geomatics, Natural Hazards and Risk

Spatial distribution of bedrock level peak ground acceleration in the National Capital Region of India using geographic information system

Hydrogen production from food waste by biochemical and thermochemical methods is reviewed herein. Generally, fermentation, a biochemical method, is considered to be more suitable for hydrogen production from food waste, and the performance of fermentation units depends on many factors, e.g., substrate composition, type of pretreatment, reactor configuration, and operating parameters, e.g., organic loading rate, hydraulic retention time, pH, and temperature. Controlling so many factors is tedious, expensive, and results in a slow process. On the other hand, thermochemical methods involve fewer factors and steps, can be much faster and less costly, and can also be used for efficient hydrogen production from food waste. Steam gasification has produced good hydrogen yields from raw food waste. © 2021 Wiley-VCH GmbH

Chemical Engineering

Chemical Engineering and Technology

Biochemical and Thermochemical Routes of H2 Production from Food Waste: A Comparative Review

Action recognition in video sequences is an active research problem in Computer Vision. However, no significant efforts have been made for recognizing actions in hazy videos. This paper proposes a novel unified model for action recognition in hazy video using an efficient combination of a Convolutional Neural Network (CNN) for obtaining the dehazed video first, followed by extracting spatial features from each frame, and a deep bidirectional LSTM (DB-LSTM) network for extracting the temporal features during action. First, each frame of the hazy video is fed into the AOD-Net (All-in-One Dehazing Network) model to obtain the clear representation of frames. Next, spatial features are extracted from every sampled dehazed frame (produced by the AOD-Net model) by using a pre-trained VGG-16 architecture, which helps reduce the redundancy and complexity. Finally, the temporal information across the frames are learnt using a DB-LSTM network, where multiple LSTM layers are stacked together in both the forward and backward passes of the network. The proposed unified model is the first attempt to recognize human action in hazy videos. Experimental results on a synthetic hazy video dataset show state-of-the-art performances in recognizing actions. © 2021, Springer Nature Singapore Pte Ltd.

Computer Science and Engineering

Communications in Computer and Information Science

Action Recognition in Haze Using an Efficient Fusion of Spatial and Temporal Features

More than thirty-five years ago, the Bhopal disaster shook the whole world and investigators found out that many people survived just because they turned on the fans in their bedrooms. It was postulated that the forced ventilation played an important role in diluting the toxic gas and saved these people. In order to provide evidence to solve this old mystery, this research employed FLACS software to assess the hazardous degree of a toxic gas (hydrogen sulfide) leakage within a petrochemical process. Series of gas dispersion simulations were performed to actualize the hazardous characteristics and the corresponding risks of the release accident. The study shows that the hazardous level and the hazard range can be greatly influenced when parameters, such as the gas leakage circumstances (atmospheric conditions and wind speed) and the mitigation measures (direction of fans and their speed) are altered. By using explosion-proof fans in different positions and ventilation directions, combined with the natural wind in a certain direction, this research attempts to detect the best combination from various mitigation designs and to compare the influence of fan directions on hazard mitigation. It is also the first time of its kind to simulate the effect of forced ventilation on hazard mitigation within a process plant. The results show that the hazardous level of a toxic release can be effectively alleviated, when the direction of the mechanical ventilation is against the natural wind direction. With the help of the CFD simulation and the quantitative risk analysis technique, different loss prevention strategies can be tested via this method in order to establish a safer working environment. © 2020 Elsevier Ltd

Journal of Loss Prevention in the Process Industries

A preliminary explore to the forced ventilation on the toxic gas release/dispersion and the hazard mitigation within a petrochemical plant

Finding lightweight materials that are suitable for high-strength impact application is imperative. However, incorporating empirical methods for the same can be an exorbitant affair. This study aims to obviate these experimental methods and replace them with a numerical approach to the problem using the finite element method (FEM) in tandem with mean-field homogenization. CNT and BNNT nano-fillers were used in the polymer matrix for the sake of comparison of dynamical response. The preliminary step involves finding material properties of composite panels having different configurations and concentration of nanofillers both computationally and experimentally. Later, an explicit dynamic based finite element analysis was performed to simulate the low-velocity impact on each of the composite plate developed. Finally, temporal responses of the plate such as contact force, displacement, and velocity after the impact were illustrated and compared for both CNT and BNNT composite plates for different heterogeneities of fibre. © 2021 Elsevier Ltd

Materials Today Communications

Mean-field homogenization coupled low-velocity impact analysis of nano fibre reinforced composites

Voice disorders are common physiological challenges that arise largely due to vocal fatigue, i.e. fatigue of vocal folds and associated phonatory structures. Since the incurrence of fatigue in vocal folds directly depends on the qualitative and quantitative nature of the dynamical signature of vocal fold oscillations, the hitherto literature has resorted to estimating the time histories and stress histories of the vocal fold oscillations. Often, vocal fold dynamics are rid with different types of complexities. Therefore, the literature often resorts to the use of a mathematical model that closely resembles the human phonatory system. Modelling the mechanism of vocal folds as a two-mass model with 2DOF provides a reasonably accurate depiction of the same. In order to obtain the real-time histories of the vocal fold vibrations, a continuously changing parameter called phonation threshold pressure (PTP) is defined so as to describe the extent of accumulated fatigue. PTP can be determined numerically for a given set of physical and physiological parameters of the system. Since the vocal fold vibrations are of varying amplitude as time progresses, it is necessary to use a standard counting algorithm for fatigue analysis, like the Rainflow-Counting algorithm. Then, the incurred damage is computed with the help of a S-N curve and the Miner’s rule. With the time span of phonation as the control parameter and PTP as a continuously changing parameter, the responses of the system are systematically obtained. Later, comparisons on the fatigue damage are made. © 2021, Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

Fatigue Analysis of Vocal-Folds Using Discretized Aeroelastic Model

In this research paper, vermicelli samples of 3 mm, 2 mm, and 1.25 mm diameters have been dried inside an even span greenhouse (1.2 × 0.8 m2 effective floor area) under forced convection mode in the climatic conditions of Rohtak, India (28°54′ N 76°34′E). The vermicelli samples were dried until safe moisture content was achieved. The present setup based on sustainable development due to thermal energy taken from sun, which has always an edge, compared to conventional drying in which high-grade energy (electric) is converted into low-grade energy (heat). The overall average values of thermal efficiency, energy efficiency, and exergy efficiency of greenhouse dryer for drying vermicelli were evaluated as 11.15\%, 34.83\% and 2.03\% respectively. Energy consumption and specific energy consumption of greenhouse dryer for drying vermicelli were found in the range of 0.279 to 0.539 kWh and 0.092 to 0.235 kJ/kg which was observed significantly lower than other drying methods. The drying kinetics of thin layer vermicelli has also been investigated. Lewis model was found to be most suitable to describe the thin layer drying behaviour of vermicelli drying under forced convection sustainable greenhouse drying mode. Practical applications. Traditionally, vermicelli is dried in open sun, but its colour and quality gets deteriorated due to exposure to ultraviolet rays, dust, animals, birds, rainfall etc. In industries, vermicelli is dried by electrical/hot air dryers, which consumes lot of energy and makes it costly. Therefore, a practical and advanced method of drying is essential to be developed. Greenhouse drying is an efficient, low cost and energy‐saving advanced technology, compared to the conventional hot air drying and open sun drying. This study proved to be feasible and efficient to work out an optimized drying condition for vermicelli drying under greenhouse, which could give a new path in vermicelli processing industry. The quality of dried vermicelli is good and can be stored for a long time. © 2021 Elsevier Ltd

Sustainable Energy Technologies and Assessments

Thermal performance and kinetic analysis of vermicelli drying inside a greenhouse for sustainable development

In the present article, the vibration response of geometrically imperfect functionally graded material (FGM) plates with geometric discontinuities and microstructural defects have been investigated. The structural kinematics used in the present study is based on logarithmic shear-strain function. A refined generalized porosity model has been developed to encompass even and uneven types of porosity models available in the literature. The geometric discontinuities have been assimilated in terms of a circular cutout of different sizes at the center of the plate. To incorporate the geometric imperfection, a generic function has been used. A C0 continuous iso-parametric finite element formulation has been used to attain the results whereas the accuracy of the present solution has been confirmed by comparing the results with the available literature. The analysis reveals that after a specific cutout radius, the FGM plates exhibit the nonlinear vibration characteristics. It has been observed that the influence of boundary conditions, cutout dimensions, geometric imperfections, and porosity inclusions on frequency parameters are significant. Most of the results presented in this paper are novel and may be treated as benchmark results for future reference. © 2021 Taylor & Francis Group, LLC.

Mechanics Based Design of Structures and Machines

Geometric/microstructural imperfection sensitivity in the vibration characteristics of geometrically non-uniform functionally graded plates with mixed boundary conditions

Many online comments on social media platforms are hateful, humorous, or sarcastic. The sarcastic nature of these comments (especially the short ones) alters their actual implied sentiments, which leads to misinterpretations by the existing sentiment analysis models. A lot of research has already been done to detect sarcasm in the text using user-based, topical, and conversational information but not much work has been done to use inter-sentence contextual information for detecting the same. This paper proposes a new deep learning architecture that uses a novel Bidirectional Inter-Sentence Contextual Attention mechanism (Bi-ISCA) to capture inter-sentence dependencies for detecting sarcasm in the user-generated short text using only the conversational context. The proposed deep learning model demonstrates the capability to capture explicit, implicit, and contextual incongruous words & phrases responsible for invoking sarcasm. Bi-ISCA generates results comparable to the state-of-the-art on two widely used benchmark datasets for the sarcasm detection task (Reddit and Twitter). To the best of our knowledge, none of the existing models use an inter-sentence contextual attention mechanism to detect sarcasm in the user-generated short text using only conversational context. © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).