Mechanical Engineering

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Shiv Nadar University

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.

(SoE) School of Engineering

Lecture Notes in Mechanical Engineering

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

World University root node

Energy Conversion Systems: An Overview

Energy storage systems: A comprehensive review

In this paper, an outline of mean-field homogenization and fracture toughness of boron nitride nanotube-reinforced aluminium and epoxy composites have been presented. The meso-scale material modelling has been achieved using Mori-Tanaka and double inclusion homogenization schemes. To examine the effectiveness of Mori-Tanaka and double inclusion schemes, a comparison has been drawn with the rule of mixture. Meso-scale numerical results of boron nitride nanotube-reinforced aluminium and epoxy composites are presented for various design parameters such as aspect ratio and volume fraction of boron nitride nanotubes. The validation studies of the developed transversely isotropic composites model have been documented with the experiments performed and existing literature. Finally, macro-scale fracture toughness simulations incorporating the transversely isotropic properties have been performed using the domain integral method. It is observed that aluminium and epoxy with elastoplastic and viscoelastic nature, respectively, have shown a significant effect on the fracture properties of the composites. © IMechE 2020.

Fulltext

Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications

Meso–macro-scale computational analysis of boron nitride nanotube-reinforced aluminium and epoxy nanocomposites: A case study on crack propagation

Delamination type of failure is extremely common in laminated structures and is a primary reason for failure in many use cases especially in aircrafts. In this project, Machine Learning Techniques were employed to detect the crack size and location in a four-layered laminated structure. The dataset for this problem statement was not available so it had to be generated and to do so ANSYS 18.0 was used. One structural model without any cracks was modeled and a training set with 2000 samples was generated to output the natural frequencies with different crack locations and sizes. Two regressor machine learning architectures with three algorithms (Linear regressor, Random Forest regressor and XGB Regressor) were developed for the prediction task, one to predict the area of the delamination and the other was a multioutput regressor model, which had to predict the X and Y coordinates of the center of the crack. The Random Forest Regressor gave the best generalizability in predicting the area of the delamination although linear regressor was not far behind as it performed quite remarkably given its simplicity. While predicting the locations, linear regressor gave the best test performance although hyperparameter tuning of the random forest and XGB regressor achieved similar results as compared with the linear regressor. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Delamination Detection and Localization in Laminated Structures Using Machine Learning Techniques

Metamaterials, an artificial periodic two- or three-dimensional configuration, can change propagation characteristics of electromagnetic waves (i.e., reflection, transmission, absorption). The current challenges in the field of metamaterial coatings are their manufacturing in a large-scale and large-length scale. There is a clear need to enhance process technologies and scalability of these. Thermal spraying is a method used to deposit small- to large-scale coatings where the sprayed layer is typically formed by the successive impact of fully or partially molten particles of a material exposed to various process conditions. This work aims to investigate the feasibility to manufacture large scale metamaterial coatings using the thermal spray technique and examine their response to solar radiation. Two types of coatings namely, Cr2O3 and TiO2, were deposited onto various substrates (e.g., steel, aluminium, glass, indium tin oxide (ITO)–coated glass) with a fine wire mesh (143 µm and 1 mm aperture sizes) as the masking sheet to manipulate the surface pattern using suspension high-velocity oxy-fuel thermal spraying (S-HVOF) and atmospheric plasma-sprayed (APS) methods, respectively. Post deposition, their responses subjected to electromagnetic wave (between 250 and 2500 nm or ultraviolet (UV)-visible (Vis)-infrared (IR) region) were characterised. The additional microstructural characterisation was performed using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), three-dimensional profilometry, and optical spectroscopy. It is demonstrated that through novel application of thermal spray techniques, large-scale manufacturing of metamaterial coating is possible, and such material can affect electromagnetic wave propagation. Comparison between Cr2O3 and TiO2 coatings on aluminium substrates showed reduced three orders of reduced reflectance for Cr2O3 coatings (for 1-mm aperture size) throughout the spectrum. It was concluded that for a similar bandgap, Cr2O3 coatings on aluminium substrate will yield improved optical performance than TiO2 coating, and hence more useful to fabricate opto-electronic devices. Graphical abstract: [Figure not available: see fulltext.] © 2021, The Author(s).

Emergent Materials

Large-scale manufacturing route to metamaterial coatings using thermal spray techniques and their response to solar radiation

Progress made by materials scientists in recent years has greatly helped the field of ultra-precision manufacturing. Ranging from healthcare to electronics components, phenomena such as twinning, dislocation nucleation, and high-pressure phase transformation have helped to exploit plasticity across a wide range of metallic and semiconductor materials. One current problem at the forefront of the healthcare sector that can benefit from these advances is that of bacterial infections in implanted prosthetic devices. The treatment of implant infections is often complicated by the growth of bacterial biofilms on implant surfaces, which form a barrier that effectively protects the infecting organisms from host immune defenses and exogenous antibiotics. Further surgery is usually required to disrupt the biofilm, or to remove the implant altogether to permit antibiotics to clear the infection, incurring considerable cost and healthcare burdens. In this review, we focus on elucidating aspects of bactericidal surfaces inspired by the biological world to inform the design of implant surface treatments that will suppress bacterial colonization. Alongside manufacturing and materials related challenges, the review identifies the most promising natural bactericidal surfaces and provides representative models of their structure, highlighting the importance of the critical slope presented by these surfaces. The scalable production of these complex hierarchical structures on freeform metallic implant surfaces has remained a scientific challenge to date and, as identified by this review, is one of the many 21st-century puzzles to be addressed by the field of applied physics. © 2021 Author(s).

Applied Physics Reviews

Bactericidal surfaces: An emerging 21st-century ultra-precision manufacturing and materials puzzle

The high entropy alloys have become the most intensely researched materials in recent times. They offer the flexibility to choose a large array of metallic elements in the periodic table, a combination of which produces distinctive desirable properties that are not possible to be obtained by the pristine metals. Over the past decade, a myriad of publications has inundated the aspects of materials synthesis concerning HEA. Hitherto, the practice of HEA development has largely relied on a trial-and-error basis, and the hassles associate with this effort can be reduced by adopting a machine learning approach. This way, the “right first time” approach can be adopted to deterministically predict the right combination and composition of metallic elements to obtain the desired functional properties. This article reviews the latest advances in adopting machine learning approaches to predict and develop newer compositions of high entropy alloys. The review concludes by highlighting the newer applications areas that this accelerated development has enabled such that the HEA coatings can now potentially be used in several areas ranging from catalytic materials, electromagnetic shield protection and many other structural applications. © 2021, The Author(s).

Emergence of machine learning in the development of high entropy alloy and their prospects in advanced engineering applications

The term “nature-inspired” is associated with a sequence of efforts to understand, synthesize and imitate any natural object or phenomenon either in a tangible or intangible form, which allows us to obtain improved insights into nature. Such inspirations can come through materials, processes, or designs that we see around us. Materials, as opposed to processes and designs found in nature, are tangible and can readily be used without engineering efforts. One such example is that of an aquaporin that is used to filter water. The scope of this work in nature-inspired materials is to define, clarify, and consolidate our current understanding by reviewing examples from the laboratory to industrial scale to highlight emerging opportunities. A careful analysis of “nature-inspired materials” shows that they possess specific functionality that relies on our ability to harness particular electrical, mechanical, biological, chemical, sustainable, or combined gains. © 2021, The Author(s).

NPG Asia Materials

Nature-inspired materials: Emerging trends and prospects

<p>Hydro machinery components such as turbines, pipes, guide vanes, and pumps suffer from severe slurry erosion caused by the abrasive particles entrained in working fluid. In the current work, an array of systematic slurry erosion tests were executed to study the influence of impact angle on slurry erosion rates of Ni-SiC based composite claddings developed on SS 316&nbsp;L through microwave hybrid heating. Various microstructural and mechanical characterizations such as micro and nano-indentation, x-ray diffraction (XRD), and scanning electron microscopy (SEM) were performed on the developed claddings. The claddings contain 5&nbsp;wt.\% of SiC particles of different size fractions from nano to micro (unimodal) and combination of both in the matrix (bimodal). Slurry erosion studies were performed on the developed claddings at different impingement angles. The claddings exhibited good metallurgical bonding with the substrate without any pores throughout. The developed claddings exhibited high hardness and elastic modulus compared to the substrate material. A significant improvement in the erosion resistance of the claddings was observed with the addition of bimodal sized SiC secondary particles. The enhanced erosion resistance of the claddings could be attributed to the higher fracture toughness and hardness of the developed coating. Among the developed coatings, the bimodal sample with 5\% SiC claddings showed at least two times better erosion resistance than hydro-turbine steel at almost all the impact angles. SEM studies performed on the eroded samples showed micro-cutting and plowing as the main modes of material removal at lower impact angles. © 2021, Springer Nature B.V.</p>

Silicon

Slurry Erosion Resistance of Microwave Derived Ni-SiC Composite Claddings

In present article, we have fabricated micro/nano hierarchical structured aluminium surfaces with a vivid range of wettability and controllable adhesion using a facile and environment-friendly approach. The micropatterned surfaces show hydrophobicity with high adhesion due to impregnated wetting state, analogous to rose petal effect. Interestingly, the micro/nano hierarchical structured surfaces become superhydrophilic due to formation of aluminium oxide and hydroxide nanoflakes. After fluorination, these surfaces become superhydrophobic with a very low contact angle hysteresis. They also exhibit a very high chemical and thermal stability along with excellent self-cleaning capability. © 2021 Elsevier B.V.