(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

Worldwide, solid waste disposal is a serious problem rising day by day with the increase in population. Open dumping and incineration is a common practice for municipal solid waste disposal in India and other developing countries. This practice raises the acute pollution problem as well as a health risk. There is an urgent need for sustainable techniques to address this problem to generate a minimal impact on the environment. There are many sustainable methods for solid waste management, viz., sanitary landfilling, composting, vermicomposting, anaerobic digestions, and ethanol production. Among all the microbes and biological agents are playing a very important role. This chapter presents a detailed review of solid waste management and sustainable solution to this problem with the help of microbes and biological agent. © 2021 Scrivener Publishing LLC.

World University root node

Civil Engineering

Environmental and Agricultural Microbiology: Advances and Applications

Role of microbes and microbial consortium in solid waste management

A novel cutting strategy of machining microstructure surface with the multi-tip diamond tool based on the force modulation approach is proposed in this paper. The multi-tip diamond tool with periodic sinusoidal microstructures was prepared by focused ion beam technique. The influence of applied cutting forces on the depths of cut and material removal states was investigated experimentally. MD simulations revealed a significant phenomenon of no material side flow when using the multi-tip diamond tool cutting on single crystal copper substrate. The movement of stacking faults, Lomer-Cottrell locks and Hirth locks jointly governed the formation mechanism of machined surface. To demonstrate the feasibility and effectiveness of this proposed cutting strategy, the fabrication of periodic sinusoidal microstructures under constant forces was successfully realized on the microsphere surface. Furthermore, three-dimensional sin-shaped ripples required variable forces controlling were achieved with high-precision surface quality. The cross-sectional topography of obtained ripples matched the geometry of used MTD tool quite well. In particular, the processing parameters, including the time period of loading forces and cutting speeds, determine the expected wavelength of ripples and play a central role in the surface machining accuracy. © 2021 The Society of Manufacturing Engineers

Mechanical Engineering

Journal of Manufacturing Processes

Fabrication of three-dimensional sin-shaped ripples using a multi-tip diamond tool based on the force modulation approach

The current work talks about a stochastic approach to study the static response characteristics of natural fiber reinforced composites with random material and geometric properties. Stochasticity in macro scale is due to randomness in macro mechanical properties of bio composite which is inevitable owing to many uncontrollable parameters in manufacturing and fabrication processes of bio composites. Analysis is also done by taking ply orientation angles (meso scale) and other geometric properties like aspect ratio, thickness ratio as discrete random variables. Bio composite is made of sisal fiber(Natural fiber) and matrix based on Epoxidized Soybean-Oil(ESO). Macro-mechanical analysis of composite laminates is done using Finite element analysis and first order shear deformation theory (FSDT) is used for displacement formulation. Results are shown for different boundary conditions along with different stacking sequences and thickness ratios. Uncertainty quantification is done using Monte Carlo simulation technique by considering the mean and the standard deviation of input material properties of the bio composite to be known. Sensitivity analysis is done to show how each stochastic input parameter (Elastic modulii) influence thecomposite plate response characteristics. The validation of the modelis checked using the existing results which are in agreement with the results obtained. Results indicate that stochasticity in material or geometric properties of bio composite cannot be ignored. It is concluded that considering stochasticity of input parameters in design and analysis of structures is crucial to maintain structural integrity, safety and reliability. © 2021 Author(s).

AIP Conference Proceedings

Stochastic analysis of natural fiber-reinforced composites

The effect of microwave processing on the high temperature oxidation behavior of AlCrTiTaMo equimolar composition was investigated. The long term oxidation studies were carried out at 900 °C and 1100 °C for 100 h. Oxidation kinetics of the microwave-processed alloy yields a significant decrease in the oxidation rate and mass gain compared to the as-cast alloy. The physical nature and stability of thermally formed oxide on the as-cast and processed samples were probed using long-term electrochemical impedance spectroscopy (EIS) studies. The impedance of the oxide formed on the as-cast alloy decreased with the immersion time while it continuously increased for the microwave processed alloy suggesting its stable and defect free nature. The superior oxidation behavior of microwave-processed alloy was attributed to microstructural homogenization leading to the formation of protective oxide layer with favorable chemistry and structure. © 2021 Elsevier B.V.

Materials Chemistry and Physics

Effect of microwave processing on the oxidation behavior of refractory high entropy alloy

Recognizing human actions is an active research area, where pose of the performer is an important cue for recognition. However, applying the 3D landmark points of the performer in recognizing action, is relatively less explored area of research due to the challenge involved in the process of extracting 3D landmark points from single view of the performers. With the recent advancements in the area of 3D landmark point detection, exploiting the landmark points in recognizing human action, is a good idea. We propose a technique for Human Action Recognition by learning the 3D landmark points of human pose, obtained from single image. We apply an autoencoder architecture followed by a regression layer to estimate the pose parameters like shape, gesture and camera position, which are later mapped to the 3D landmark points by Skinned Multi Person Linear Model (SMPL model). The proposed method is a novel attempt to apply a CNN based 3D pose reconstruction model (autoencoder) for recognizing action. Further, instead of using the autoencoder as a classifier to classify to 3D poses, we replace the decoder part by a regressor to obtain the landmark points, which are then fed into a classifier. The 3D landmark points of the human performer(s) at each frame, are fed into a neural network classifier as features for recognizing action. © 2021, Springer Nature Singapore Pte Ltd.

Computer Science and Engineering

Communications in Computer and Information Science

Human Action Recognition from 3D Landmark Points of the Performer

The dynamics and response a pitch–plunge airfoil with cubic hardening nonlinearity in the pitch degree of freedom are investigated numerically. The aerodynamics is assumed to be linear and modeled using the unsteady aero-dynamical formulation. The flow is fluctuating in both the longitudinal and vertical directions. The fluctuating flow is mathematically modeled as a long time-scale random process. The mean flow speed is used as the bifurcation parameter, and response analysis is carried out by systematically varying the bifurcation parameter. The route to flutter is presented, and the role of noisy flow fluctuations in the same is analyzed by examining the dependency on noise intensity. © 2021, Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

Investigating the Route to Flutter in a Pitch–Plunge Airfoil Subjected to Combined Flow Fluctuations

The success of deep learning-based techniques in solving various computer vision problems motivated the researchers to apply deep learning to predict the optical flow of a video in the next frame. However, the problem of predicting the motion of an object in the next few frames remains an unsolved and less explored problem. Given a sequence of frames, predicting the motion in the next few frames of the video becomes difficult in cases where the displacement of optical flow vector across frames is large. Traditional CNNs often fail to learn the dynamics of the objects across frames in case of large displacements of objects in consecutive frames. In this paper, we present an efficient CNN based on the concept of feature pyramid for extracting the spatial features from a few consecutive frames. The spatial features extracted from consecutive frames by a modified PWC-Net architecture are fed into a bidirectional LSTM for obtaining the temporal features. The proposed spatiotemporal feature pyramid is able to capture the abrupt motion of the moving objects in video, especially when displacement of the object is large across the consecutive frames. Further, the proposed spatiotemporal pyramidal feature can effectively predict the optical flow in next few frames, instead of predicting only the next frame. The proposed method of predicting optical flow outperforms the state of the art when applied on challenging datasets such as “MPI Sintel Final Pass,” “Monkaa” and “Flying Chairs” where abrupt and large displacement of the moving objects in consecutive frames is the main challenge. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Machine Vision and Applications

Learnable spatiotemporal feature pyramid for prediction of future optical flow in videos

The paper proposes optimal placement of dispatchable distributed generation units along with solar photovoltaic as distributed generator (DG) and subsequent optimal capacity operation of the dispatchable DG units in presence of solar photovoltaic (SPV) generation, i.e. when SPV generation is available. It is proposed here that these dispatchable DG units when operated at co-ordinated optimal capacity, in presence of SPV generation, result in further loss reduction without an additional DG unit installation The additional loss reduction so obtained results in more loss reduction and subsequent saving in loss cost. In this paper, a methodology is presented for optimal placement of solar photovoltaic distributed generation (SPVDG) in presence of other optimally placed dispatchable DG units with the assumption that the dispatchable DGs units were present in the distribution system before insertion of optimal SPVDG. An effective methodology is presented here for optimal operation of dispatchable DGs in presence of SPV generation. It is proposed and established that DG technologies (which are dispatchable in nature), must be operated at different optimal capacities than their respective installed optimal capacity, for further loss reduction when solar generation is available. This optimal operation defers the additional DG capacity addition for system loss reduction and at the same time provides a reduction in operational cost for certain dispatchable DG types. It is proposed that in presence of SPVDG, other distributed generators must be operated at somewhat reduced optimal capacity, but at their respective optimal location, for hours, when photovoltaic generation is available. This enables a reduction in their operational cost as well. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Electrical Engineering

Energy Systems

Co-ordinated optimal control of distributed generation in primary distribution system in presence of solar PV for loss reduction and voltage profile improvement

Interface modeling is one of the important components in the numerical modeling of soil–structure interaction problem. It is equally important as material and geometrical modeling. Inaccurate modeling of the interface between the soil and the structure may lead to unreliable results. However, in many cases, interface modeling is overlooked and the interface between the soil and the structure is generally modeled as a rigid connection. In the present paper, we have shown the influence of interface modeling in the analysis of laterally loaded deep foundations. A finite element model of laterally loaded foundation–soil system is developed wherein the foundation is modeled as a linear elastic system and the soil as nonlinear which is defined by the multi-yield surface plasticity model. The interface between the soil and the foundation is modeled using zero thickness contact element, which is defined, by constitutive relationships capable to define sliding and separation mechanisms at the interface. The results obtained from the proposed finite element model are then compared with the conventional approach of interface modeling. The present study indicates that the conventional approach overestimates the lateral load capacity of deep foundation as well as it is unable to explain the mechanisms of the deformation of laterally loaded foundation–soil system. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Civil Engineering

Significance of Interface Modeling in the Analysis of Laterally Loaded Deep Foundations

A rectangular patch antenna with π shaped slot is proposed as a miniaturized antenna element with a gain of 5.83 dB for WLAN (5.2 GHz) application. This compact π shaped slot antenna is used as a radiating element for the design of a 2 × 1 MIMO system for WLAN application. A near field passive parasitic element is used in the proposed MIMO antenna to improve the isolation. The MIMO system has a surface area of 0.29λ2 with a measured gain of 6 dBi and impedance bandwidth of 110 MHz. The diversity characteristics of MIMO are quantified with envelop correlation coefficient of 0.004, capacity loss of 0.35 bits/s/Hz, mean effective gain ratio (less than 1), mutual coupling around −20 dB, and TARC is −14.5 dB. The measured results are in good agreement with the simulation results and validate the proposed design. © 2021 IETE.