Mechanical 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

Biofiber-based polymer composites have seen tremendous growth in the last decade and are expected to grow at a compound annual growth rate of 11.8% from 2016 to 2024. Biofiber composites are 25%-30% stronger than glass fiber of the same weight, which make them a potential player in the manufacturing industry. In this chapter, we present the advances and application of biofiber-based polymer composite in aerospace, automotive, military and defense, construction, and electronics followed by a recycling comparison study between synthetic, hybrid, and complete biofiber polymer composites. In the later part of the chapter, the advances in multiscale analysis, manufacturing methods, and pretreatment in biofiber and polymer composites are presented. At the end of the chapter, the future prospects of biofiber-based polymer composites are discussed. © 2022 Elsevier Ltd All rights reserved.

World University root node

(SoE) School of Engineering

Advances in Bio-Based Fiber: Moving Towards a Green Society

Advances and applications of biofiber-based polymer composites

This work is an extension part of the Assembly Line Worker Assignment Balancing Problem(ALWABP), aims to provide a dynamic solution for an assembly line fatigue worker job rotation by using machine learning based digital twin. This framework explains, fatigue worker identification and work rotation possibilities for a reconfigurable assembly line. The fatigue causing parameters are sensed from the workers and classified with a fatigue classifier then send the fatigue worker details to a worker job rotation search algorithm. The job rotation search algorithm provides a suggestion to the production supervisor for a best possible worker job rotation/reallocation solution dynamically. © 2021 The Author(s).

Procedia CIRP

A dynamic job rotation scheduling conceptual framework by a human representing digital twin

<p>Atmospheric degradation of the metallic components initiated by the accumulation of contaminants and humidity significantly limits the performance and sustainability of many engineering systems. Aluminium and its alloys are widely used in different industries such as food processing, marine, aerospace, automobiles and household appliances. The leaching of aluminium can cause significant environmental and health-related issues. In the present study, a facile and environment-friendly (hot water treatment) processing route was utilized to fabricate sustainable Al surfaces without the use of any chemical reagents and toxic solvents. The developed nanostructured Al surface showed immense mechanical, chemical and thermal durability restricting corrosion and leaching of aluminium. The processed Al composed of self-assembled 2D nanostructures showed extreme wettability ranging from superhydrophilic (θ &lt; 5°) to superhydrophobicity (SHS) (θ &gt; 160°), depending upon post-processing conditions. The developed SHS has showed high water (droplet impacts) and dust repellence under static and dynamic conditions. This is related with effective entrapment of air, prompted by the presence of nanostructured morphology, leading to stable Cassie state. Results showed that SHS possess better self-cleaning ability compared to the superhydrophilic counterpart. The SHS showed better sustainability in terms of high thermal stability in a temperature range of −80 °C to 350 °C and corrosion resistance under prolonged immersion for 48 h in salt media. Compared to unprocessed counterpart, SHS showed 40 times reduction in the corrosion rate, which is significantly high when compared with several other processing routes. The present study showed an eco-friendly and straightforward approach which can be effectively used for fabricating multifunctional metallic surfaces with widespread applications. © 2020 Elsevier Ltd</p>

Physics

(SoNS) School of Natural Sciences

Journal of Cleaner Production

Green manufacturing of nanostructured Al-Based sustainable self-cleaning metallic surfaces

High-entropy alloys (HEAs) with multiple principal elements represent a paradigm shift in structural alloy design and show excellent surface degradation resistance in corrosive environment. Here, the tribo-corrosion response of laser-engineered net-shaped CoCrFeMnNi HEA was evaluated in 3.5 wt% NaCl solution at room temperature. The additively manufactured (AM-ed) CoCrFeMnNi showed five times lower wear rate, regenerative passivation, and nobler corrosion potential during tribo-corrosion test compared to its arc-melted counterpart. A significant anisotropy was seen in the tribo-corrosion response with 45° to the build direction showing better performance compared to tests along the build direction and perpendicular to it. The open circuit potential curves were characterized by a sharp drop to more negative values as wear began, followed by continuous change for the active tribo-corrosion duration and finally a jump to nobler value at the end of the test indicating excellent surface re-passivation for the AM-ed alloy. The superior tribo-corrosion resistance of AM-ed CoCrFeMnNi was attributed to the refined microstructure and highly protective surface passivation layer promoted by the sub-grain cellular structure formed during additive manufacturing. These results highlight the potential of utilizing additive manufacturing of HEAs for use in extreme environments that require a combination of tribo-corrosion resistance, mechanical durability, extended service life, and net shaping with low dimensional tolerance. © 2021, The Author(s).

Fulltext

npj Materials Degradation

Tribo-corrosion response of additively manufactured high-entropy alloy

Amplitude death (AD) has been recently identified as a phenomenon that can be exploited to stop unwanted large amplitude oscillations arising from instabilities in engineering systems. These oscillations are a consequence of the occurrence of dynamic instability, for example, the flutter instability, which results in the manifestation of sustained limit cycle oscillations. Recent studies have demonstrated amplitude death in coupled aeroelastic systems with identical parameters using suitable reactive coupling. Deriving impetus from the same, the dynamical signatures of coupled non-identical aeroelastic systems under a variety of coupling characteristics are investigated in the present study. The coupling characteristics between the individual airfoils here are assumed to possess both reactive and dissipative terms and are represented via a linear torsional spring and a damper, respectively. Explicit parameter mismatch is introduced via the use of different structural parameters such as frequency ratio and air-mass ratio for the individual airfoils. We demonstrate that a nonlinear coupled aeroelastic system with parameter mismatch and combined coupling characteristics gives rise to broader regimes of AD in aeroelastic systems. Specifically, the possibility of encountering large amplitude oscillations, usually found with pure reactive coupling can be avoided by adding a dissipative coupling term. On introducing dissipative coupling, the regime of AD was found to increase substantially, for both identical and non-identical scenarios, which in turn aids in serving as an effective tool to be developed further toward the application of flutter instability suppression. © 2021 Author(s).

Chaos

Effect of parameter mismatch and dissipative coupling on amplitude death regime in a coupled nonlinear aeroelastic system

The deterioration of fluid machines due to slurry and cavitation erosion significantly impairs their serviceability. In the present work, we investigated the influence of deep cryogenic treatment (DCT) on the slurry and cavitation erosion resistance of WC-10Co-4Cr coatings developed using the detonation spraying technique. For comparison, hydroturbine steels and other conventional (Alumina and Stellite 6) coatings were also investigated. All thermal spray coatings showed typical lamellar structure along with the presence of pores and splat boundaries. Among all the coatings, the WC-10Co-4Cr showed the highest slurry (up to 15 times) and cavitation (2 times) erosion resistance owing to high hardness and fracture toughness. Post DCT, the WC-10Co-4Cr coating showed further improvement due to reduced porosity and improved hardness without decrement in fracture toughness. As a result, the DCT coating showed 1.5 to 4.2 times improved slurry erosion resistance than the as-sprayed counterpart, along with 1.6 times higher cavitation erosion resistance. The improved tribological performance of the coating after DCT is associated with enhanced hardness due to the presence of nano precipitates and densification as analyzed using electrochemical techniques. The topological analysis of the eroded surfaces indicated micro-cutting, micro-cracking, and delamination as the primary mechanism controlling the erosion behavior of the coatings. © 2021 Elsevier Ltd

Renewable Energy

Enhanced slurry and cavitation erosion resistance of deep cryogenically treated thermal spray coatings for hydroturbine applications

We discuss the implementation of a coupled Multi-phase particle in cell method (MPPIC) and Volume of Fluid (VOF) flow solver to simulate particles in a fluid flow field having a free surface. Using the solver developed using OpenFOAM 4.1 library, we study the flow of particles inside a highly anisotropic turbulent flow field of a hydrocyclone. The free surface from the air-core inside the hydrocyclone is resolved using the VOF method coupled with the LES turbulence model. We test multiple sub-grid scale model and find the dynamic k-equation model to have the best-predicting capability of the mean and turbulent flow field as well as the air-core shape. Using the established flow field, we study the particle flow properties and its effect on the fluid flow field using a four-way coupled description between MPPIC and VOF. Important flow properties such as the particle flow field velocity and turbulence modulation with varying particle concentration were studied. It was found that even with low solid concentration (0.3–1.5% by volume) there is a quite substantial increase in the fluctuating flow field (around 12%) and with a further increase (1.8%) we observe a decrease in the turbulent levels by approximately 6%. © 2020 Elsevier B.V.

Separation and Purification Technology

Effect of particle concentration on turbulent modulation inside hydrocyclone using coupled MPPIC-VOF method

This research deals with the design and fabrication of novel designs as a means to harness wind energy using ‘Savonius' Turbine. It is generally employed to harvest the low to extremely low wind speed potentials. They can be particularly of high use in the regions where the wind speeds are not high enough for installing conventional horizontal axis wind turbines. The paper introduces a novel concept of testing a Savonius wind turbine with dimple structures on its blades and investigating its effect on the turbine's efficiency. The study also deals with the experimental validation of the effect of using a converging ducted structure with a single stage and double stage configurations of Savonius wind turbine, apart from comparing the turbine's performance with and without endplates. The results of the study prove that power coefficient increases with the addition of dimple structures on the blades and it can be further augmented by using a ducted structure with the Savonius turbine. © 2020. All rights reserved.

International Journal of Renewable Energy Research

Numerical and Experimental Investigations on a Dimpled Savonius Vertical Axis Wind Turbine

Concentrated solar power tower (CSPT) technology coupled with molten salt thermal storage is a very promising approach to harness solar energy as it offers good efficiency along with cheap storage and it can thus meet the fluctuating demand for electricity in a grid. This helps to avoid additional investment in fossil fuel–powered plants used for base load and peaking demand. However, their large-scale adoption is constrained by their relatively high capital cost. One of the most important cost elements in a CSPT plant is the cost of heliostats themselves. Normally heliostats use square-shaped reflector, whereas it is reported that heliostats with reflectors of aspect ratio (width/height ratio) of approximately 2.0 are cheaper due to reduced wind loads on them. Further, simulation of heliostat fields populated with rectangular heliostats of an aspect ratio of 2.0 has shown that such heliostat fields are not only cheaper to build but also optically more efficient. This paper discusses the results of a small experimental setup created to validate the results of these simulations. © 2020, © 2020 Taylor & Francis Group, LLC.

Energy Sources, Part A: Recovery, Utilization and Environmental Effects

Effect of aspect ratio of heliostats on the optical efficiency of solar tower power plant–an experimental analysis

The Jaya algorithm is a novel, simple, and efficient meta-heuristic optimization technique and has received a successful application in the various fields of engineering and sciences. In the present paper, we apply the Jaya algorithm to permutation flow shop scheduling problem (PFSP) with the multi-objective of minimization of maximum completion time (makespan) and tardiness cost under due date constraints. PFSP is a well-known NP-hard and discrete combinatorial optimization problem. Firstly, to retrieve a job sequence, a random preference is allocated to each job in a permutation schedule. Secondly, a job preference vector is transformed into a job permutation vector by means of largest order value (LOV) rule. To deal with the multi-objective criteria, we apply a multi-attribute model (MAM) based on Apriori approach. The correctness of the Jaya algorithm is verified by comparing the results with the total enumeration method and simulated annealing (SA) algorithm. Computational results reveal that the proposed optimization technique is well efficient in solving multi-objective discrete combinatorial optimization problems such as the flow shop scheduling problem in the present study. © Springer Nature Singapore Pte Ltd. 2020.