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Item Anharmonicities in the temperature-dependent bending rigidity of BC3 monolayer(2020) Mrudul M.S.; Thomas S.; Ajith K.M.The present work investigated the temperature-dependent thermodynamic and structural characteristics of graphene-like monolayer boron carbide (g-BC3) using classical molecular dynamics simulations. Herein, we mainly focused on the temperature dependence of mean square displacement of thermally stimulated ripples and bending rigidity of g-BC3. We observed that at high temperatures, the specific heat capacity at constant volume exhibits a significant increase beyond the limit of Dulong-Petit value due to the presence of anharmonicity in the g-BC3. Besides, the linear thermal expansion coefficient is found to be negative owing to the excitation of low-frequency bending vibrations in the out-of-plane orientation. Studies reveal that the out-of-plane of height fluctuations and bending rigidity are fully dependent on temperature and are described using the continuum theory of membranes. Moreover, the study on the height fluctuation and correlation shows variation from the estimation of the harmonic theory of membranes as a consequence of the anharmonic features of g-BC3. We believe that our study will provide a notable contribution to numerous applications of g-BC3 including nanoelectromechanical (NEMS) devices to become a reality. © 2020 Elsevier LtdItem Application of back propagation algorithms in neural network based identification responses of AISI 316 face milling cryogenic machining technique(2020) M C K.R.; Malghan R.L.; Shettigar A.K.; Rao S.S.; Herbert M.A.The paper explores the potential study of artificial neural network (ANN) for prediction of response surface roughness (Ra) in face milling operation with respect to cryogenic approach. The model of Ra was expressed as the main factor in face milling of spindle speed, feed rate, depth of cut and coolant type. The ANN is trained using four various back propagation algorithms (BPA). The emphasis of the paper is to investigate the performance and the accuracy of the attained results depicts the effectiveness of the trained ANN in identifying the predicted Ra. The incorporated various BPA in predicting the Ra. The performance comparative study is made among statistical (Response Surface Methodology (RSM)) and ANN (BPA–training algorithm) methods. The various incorporated BPA algorithms are Gradient Descent (GD), Scaled Conjugate Gradient Descent (SCGD), Levenberg Marquardt (LM) and Bayesian Neural Network (BNN). Afterwards the best suitable BPA is identified in predicting Ra for AISI 316 in face milling operation using liquid nitrogen (LN2) as cutting fluid. The outperformed BPA is identified based on the attained deviation percentage and time required for the training the network. © 2020, © 2020 Engineers Australia.Item Analysis of M-QAM Modulated Underwater Wireless Optical Communication System for Reconfigurable UOWSNs Employed in River Meets Ocean Scenario(2020) Uppalapati A.; Naik R.P.; Krishnan P.In this paper, the bit error rate (BER) performance of underwater wireless optical communication system employing with M-ary quadrature amplitude modulation is proposed for underwater optical wireless sensor networks (UOWSN) in river meets ocean scenario. The underwater channel degradation effects such as absorption, scattering and oceanic turbulence is taken into account. The oceanic turbulence is modelled by the Gamma-Gamma distribution. The first time, we proposed re-configurable UOWSN for the real time scenario of the river meets the ocean and derived the novel closed form analytical BER expressions of the proposed system over Gamma-Gamma turbulence with attenuation effects. The impact of oceanic turbulence parameters such as the variations of temperature, kinetic energy, viscosity, salinity, link range and the water type of system performance is investigated for river water, mixed water (river and ocean water) and ocean water. The proposed system and the related analysis will be highly useful in UOWSN and the Internet of underwater thing (IoUT) applications. © 1967-2012 IEEE.Item Analytical solution to transient inverse heat conduction problem using Green’s function(2020) Parida R.K.; Madav V.; Hindasageri V.A transient inverse heat conduction problem concerning jet impingement heat transfer has been solved analytically in this paper. Experimentally obtained transient temperature history at the non-impinging face, assumed to be the exposed surface in real practice, is the only input data. Aim of this study is to estimate two unknown thermo-physical parameters—overall heat transfer coefficient and adiabatic wall temperature—at the impinging face simultaneously. The approach of Green’s Function to accommodate both the transient convective boundary conditions and transient radiation heat loss is used to derive the forward model, which is purely an analytical method. Levenberg–Marquardt algorithm, a basic approach to optimisation, is used as a solution procedure to the inverse problem. An in-house computer code using MATLAB (version R2014a) is used for analysis. The method is applied for a case of a methane–air flame impinging on one face of a flat 3-mm-thick stainless steel plate, keeping Reynolds number of the gas mixture 1000 and dimensionless burner tip to impinging plate distance equals to 4, while maintaining the equivalence ratio one. Inclusion of both radiation and convection losses in the Green’s function solution for the forward problem enhances the accuracy in the forward model, thereby increasing the possibility of estimating the parameters with better accuracy. The results are found to be in good agreement with the literature. This methodology is independent of flow and heating conditions, and can be applied even to high-temperature applications. © 2020, Akadémiai Kiadó, Budapest, Hungary.Item Analysis of impact behaviour of sisal-epoxy composites under low velocity regime(2021) Mahesh V.; Nilabh A.; Joladarashi S.; Kulkarni S.M.The present study concentrates on development of conceptual proof for sisal reinforced polymer matrix composite for structural applications subjected to low velocity impact using a finite element (FE) approach. The proposed sisal-epoxy composite of various thicknesses of 3.2 mm, 4 mm and 4.8 mm is subjected to different impact velocities of 1 m/s, 2 m/s and 3 m/s ranging in the low velocity impact regime to study the energy absorbed and damage mitigation behaviour of the proposed composite. The consequence of velocity of impact and thickness of laminate on the sisal epoxy composite's impact behaviour is assessed statistically using Taguchi's experimental design. Outcome of the present study discloses that the energy absorption increases with increased impact velocity and laminate thickness. However, the statistical study shows that impact velocity is predominant factor affecting the impact response of sisal epoxy composite laminate compared to laminate thickness. The role of matrix and fiber in damage initiation is studied using Hashin criteria and it is found that matrix failure is predominant over the fiber failure. © 2021 Lavoisier. All rights reserved.Item A comparative study on enhancer and inhibitor of glycine–nitrate combustion ZnO screen-printed sensor: detection of low concentration ammonia at room temperature(2020) Manjunath G.; Nagaraju P.; Mandal S.We report a comparative study on enhancing and inhibiting the sensing performance of Sr-doped ZnO (Sr0.01 Zn0.99O) and RuO2-activated Sr-doped ZnO heterostructured sensors towards the low concentration (≤ 50 ppm) of ammonia gas at ambient. Sub-microns sized with high specific surface area, high reactive, oxygen-deficient Sr-doped ZnO particles were synthesized at low temperature (196 °C) through facile glycine–nitrate solution combustion synthesis (SCS) method. Porous, adhered screen-printed film of Sr-doped ZnO with optical bandgap (3.22 eV) was dip-coated using 0.02 M RuCl3 aqueous solution to obtain RuO2 activation. Smaller crystallite size and lesser lattice distortion obtained with Sr-doping in ZnO enhance the gas response (S = 71) towards the 50 ppm of ammonia gas at room temperature. RuO2-activated Sr-doped ZnO sensor associated with lesser oxygen vacancies and a lower concentration of chemisorbed oxygen species due to passivation layer and no-spill-over activity of RuO2, which inhibits the gas response from 71 to 3. Sr-doped ZnO-based sensor shows high selectivity towards ammonia against 50 ppm of volatile organic compound (VOCs) vapor. Expeditious sensor kinetics (response time and recovery time) in the Sr-doped ZnO sensor was observed, in which smaller crystallite size offers a shorter distance for the diffusion of oxygen vacancies (Vo). Ultra-high-sensitive and selective sensors with ease and economical fabrication offer feasibility in industries and domestic applications where detection of the less concentration ammonia vapor is crucial. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.Item Analysis of ionic and nonionic surfactants blends used for the reverse micellar extraction of Lactoperoxidase from whey(2021) Karanth S.; Iyyaswami R.Bovine Lactoperoxidase (LP), a minor whey protein, is used as an antimicrobial in cosmetic, food, and pharmaceutical preparations. Industries are in pursuit of reliable, cheap, and scalable purification methods as the conventional techniques for LP purification like chromatography and membrane separation suffer from several drawbacks. The present work investigates the selective reverse micellar extraction of LP using the reverse micellar system formed by mixing food grade nonionic (Tween, Span, and Triton series) and ionic (AOT) surfactant blends. The analysis of LP extraction efficiency was performed by varying the concentration of nonionic surfactants with a constant AOT concentration of 100 mM and the initial pH of the system. Complete LP solubilization was achieved with reverse micelles formed by 100 mM AOT and 20 mM Tween 80 at pH 8. It was found that the extraction efficiency was dependent on the chain length or the number of ethylene oxide units in the Triton surfactant tail and the carbon–carbon double bond in Tween 80 tail, that is, on oleic acid. Span series however showed poor extraction in the organic phase substantiating the lesser water content. The forward extracted LP was successfully back-extracted into a fresh aqueous phase containing 1 M KCl at pH 10.5. The aqueous phase (whey) from the forward transfer can be further used to fractionate other whey proteins. © 2020 Curtin University and John Wiley & Sons, Ltd.Item An Online Method of Estimating State of Health of a Li-Ion Battery(2021) Goud J.S.; Kalpana R.; Singh B.Li-ion batteries are playing a crucial role in the fields of renewable energy systems and electric vehicles. The reliability of these systems depends on a battery management system (BMS) which monitors the state of charge (SoC) and state of health (SoH) effectively. Knowing the SoH of a battery in advance enhances the system reliability. This article proposes an accurate online estimation of SoH of a Li-ion battery integrated in solar photovoltaic system (SPV) applications. The proposed method uses the modified coulomb counting method to estimate the SoH of a battery. The proposed SoH estimation method is simulated in MATLAB/Simulink by considering the aging factors such as temperature, charge/discharge rates and depth of discharge. Moreover, the proposed method is validated using an experimental prototype and the results are found to be satisfactory. © 1986-2012 IEEE.Item Analysis and prediction of COVID-19 trajectory: A machine learning approach(2020) Majhi R.; Thangeda R.; Sugasi R.P.; Kumar N.The outbreak of Coronavirus 2019 (COVID-19) has impacted everyday lives globally. The number of positive cases is growing and India is now one of the most affected countries. This paper builds predictive models that can predict the number of positive cases with higher accuracy. Regression-based, Decision tree-based, and Random forest-based models have been built on the data from China and are validated on India's sample. The model is found to be effective and will be able to predict the positive number of cases in the future with minimal error. The developed machine learning model can work in real-time and can effectively predict the number of positive cases. Key measures and suggestions have been put forward considering the effect of lockdown. © 2020 John Wiley & Sons LtdItem An Investigation on the Influence of Thermal Damage on the Physical, Mechanical and Acoustic Behavior of Indian Gondwana Shale(2020) Srinivasan V.; Tripathy A.; Gupta T.; Singh T.N.In the present study, the effect of thermal treatment on the physical, mechanical and fracturing behavior of Gondwana shale samples from India was investigated. Acoustic Emission signals were used to identify the changes brought in by temperature variations on the crack damage zones and failure attributes in shale. The results suggested that mechanical parameters such as uniaxial compressive strength, tensile strength (σt), elastic modulus, mode-I fracture toughness (KIC), cohesion, and brittleness index (B1) exhibited a strong negative correlation with thermal damage (Dt). But, the internal angle of friction and brittleness index (B2) showed a reasonable positive relation with thermal treatment. The deformation of the shale was dominated by its clay mineral enrichment, the characteristics of which changed with heating. The intensity of fracturing as observed from acoustic signals was chiefly controlled by the orientation of bedding planes and the degree of thermal treatment. The initiation and propagation of macro-crack were found to be greatly influenced by the degree of thermal damage. Under compression, thermally damaged samples showed similar deformation pattern, while under Brazilian tensile load, the deformation path became inconsistent with increasing temperatures. It was observed that thermal damage in tested shale decreased the layer compaction, which eased the fracturing intensity, thereby reducing the overall strength of the samples. The present investigation concludes that even a slight change of the thermal conditions can substantially alter shale fracturing behavior and failure attributes posing serious safety concerns of deep geo-engineering structures. © 2020, Springer-Verlag GmbH Austria, part of Springer Nature.