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Mukesh Sharma

Publications and source records attributed to Mukesh Sharma.

8 recordsLinked to original sources
arXiv2026

The influence of body anisotropy on wake characteristics and enstrophy production for prolate ellipsoids at $ \mathrm{Re}_{D} = 10,000 $

The flow around prolate ellipsoids is investigated using Large Eddy Simulation (LES) at a Reynolds number of $ \mathrm{Re}_{D} = 10,000 $. Five different aspect ratios are considered, with $ \mathit{AR} = H/D $ varying from 5:1 to 1:1, where $D$ and $H$ represent the minor- and major- axes, respectively. The major axes of the ellipsoids are set perpendicular to the freestream, and the influence of body anisotropy on boundary layer separation, shear layer behaviour, enstrophy production, and local flow topology is examined. Higher body anisotropy leads to early separation of the boundary layer in the equatorial plane, resulting in a wider wake and a monotonic increase in pressure drag and total drag. Positive enstrophy production reaches a maximum approximately $2.5D$ downstream of the ellipsoids independently of body anisotropy. High body anisotropy leads to sustained negative enstrophy production in the near-wake, specifically near the poles of the 5:1 ellipsoid. Negative production occurs due to the distinct behaviour of streamlines near the high curvature pole, where they undergo strong anisotropic contraction in the cross-stream plane. Interactions between the vorticity vector and the intermediate eigenvector of the strain rate tensor are shown to be the primary source of enstrophy production close to the pole, and the intermediate eigenvalue exhibits negative values in this region. The negative production region is shown to be dominated by the unstable focus / compressing (UF/C) topology, which is consistent with findings from other studies that report negative enstrophy production in turbulent flows.

physics.flu-dyn↗
arXiv2023

Orbitally driven spin reorientation in Mn doped YBaCuFeO$_{5}$

Oxygen-deficient layered perovskite YBaCuFeO$_{5}$ (YBCFO) is one rare type-II multiferroic material where ferroelectricity, driven by incommensurate spiral magnetic order, is believed to be achievable up to temperatures higher than room temperature. A cycloidal spiral rather than helical spiral order is essential ingredient for the existence of ferroelectricity in this material. Motivated by a recent experimental work on Mn-doped YBCFO where the spiral plane is observed to cant more towards the crystallographic $c$ axis upon Mn doping at Fe sites compared to that in the parent compound, we performed a detailed theoretical investigation using the density functional theory calculations to understand the mechanism behind such spin reorientation. Our total energy calculations, within GGA+U+SO approximation, reveal that Fe/Cu spin moments indeed align more towards $c$ axis in the Mn-doped compounds than they were in parent compound YBCFO. Largest exchange interaction (Cu-Cu in the $ab$-plane) is observed to decrease systematically with Mn doping concentration reflecting the lowering of transition temperature seen in experiment. Further, the inter-bilayer Cu-Mn exchange interaction becomes ferromagnetic in the doped compound whereas the corresponding Cu-Fe exchange was antiferromagnetic in the parent compound giving rise to frustration in the commensurate magnetic order. Most importantly, our electronic structure calculations reveal that in the doped compounds because of hybridization with the d$_{z^2}$ orbital of Mn, the highest occupied Cu orbital becomes d$_{z^2}$ as opposed to the parent compound where the highest occupied Cu orbital is d$_{x^2-y^2}$. Therefore, we believe that the occupancy of out of plane oriented Cu d$_{z^2}$ orbital in place of planar d$_{x^2-y^2}$ orbital along with the frustrating exchange interaction drive the spins to align along $c$ in doped compound.

cond-mat.str-el↗
arXiv2022

Magnetic Transition in $\rm LaVO_{3} /LaTiO_{3}$ superlattice: A DFT+MC study

Magnetic phase transitions have been explored in a superlattice formed by stacking monolayers of $\rm LaTiO_{3}$ and $\rm LaVO_{3}$ alternately, using ab-initio density functional theory (DFT) and Monte-Carlo (MC) simulations. DFT derived intra-layer and inter-layer exchange interaction parameters were used for the MC simulations on a Ising spin model Hamiltonian. Two sharp peaks observed in specific heat without the interlayer exchange coupling indicate two independent magnetic ordering in $\rm LaTiO_{3}$ and $\rm LaVO_{3}$ layers at different temperatures. Inclusion of interlayer coupling leads to one sharp peak at higher temperature with a broad hump like feature at lower temperature in specific heat indicating a single magnetic phase transition to $C$-type antiferromagnetic phase in the superlattice.

physics.comp-ph↗
arXiv2021

End-to-End Whisper to Natural Speech Conversion using Modified Transformer Network

Machine recognition of an atypical speech like whispered speech, is a challenging task. We introduce whisper-to-natural-speech conversion using sequence-to-sequence approach by proposing enhanced transformer architecture, which uses both parallel and non-parallel data. We investigate different features like Mel frequency cepstral coefficients and smoothed spectral features. The proposed networks are trained end-to-end using supervised approach for feature-to-feature transformation. Further, we also investigate the effectiveness of embedded auxillary decoder used after N encoder sub-layers, trained with the frame-level objective function for identifying source phoneme labels. We show results on opensource wTIMIT and CHAINS datasets by measuring word error rate using end-to-end ASR and also BLEU scores for the generated speech. Alternatively, we also propose a novel method to measure spectral shape of it by measuring formant distributions w.r.t. reference speech, as formant divergence metric. We have found whisper-to-natural converted speech formants probability distribution is similar to the groundtruth distribution. To the authors' best knowledge, this is the first time enhanced transformer has been proposed, both with and without auxiliary decoder for whisper-to-natural-speech conversion and vice versa.

eess.AS↗
arXiv2021

Controlling by Showing: i-Mimic: A Video-based Method to Control Robotic Arms

A novel concept of vision-based intelligent control of robotic arms is developed here in this work. This work enables the controlling of robotic arms motion only with visual inputs, that is, controlling by showing the videos of correct movements. This work can broadly be sub-divided into two segments. The first part of this work is to develop an unsupervised vision-based method to control robotic arm in 2-D plane, and the second one is with deep CNN in the same task in 3-D plane. The first method is unsupervised, where our aim is to perform mimicking of human arm motion in real-time by a manipulator. We developed a network, namely the vision-to-motion optical network (DON), where the input should be a video stream containing hand movements of human, the the output would be out the velocity and torque information of the hand movements shown in the videos. The output information of the DON is then fed to the robotic arm by enabling it to generate motion according to the real hand videos. The method has been tested with both live-stream video feed as well as on recorded video obtained from a monocular camera even by intelligently predicting the trajectory of human hand hand when it gets occluded. This is why the mimicry of the arm incorporates some intelligence to it and becomes intelligent mimic (i-mimic). Alongside the unsupervised method another method has also been developed deploying the deep neural network technique with CNN (Convolutional Neural Network) to perform the mimicking, where labelled datasets are used for training. The same dataset, as used in the unsupervised DON-based method, is used in the deep CNN method, after manual annotations. Both the proposed methods are validated with off-line as well as with on-line video datasets in real-time. The entire methodology is validated with real-time 1-link and simulated n-link manipulators alongwith suitable comparisons.

cs.CV↗
arXiv2019

Anisotropic thermoelectric properties of EuCd$_{2}$As$_{2}$ : An Ab-initio study

In search of better thermoelectric materials, we have systematically investigated the thermoelectric properties of a 122 Zintl phase compound EuCd$_{2}$As$_{2}$ using \textit{ab-initio} density functional theory and semi-classical Boltzmann transport theory within constant relaxation time approximation. Considering the ground state magnetic structure which is A-type antiferromagnetic (A-AFM) and non-magnetic (NM) structure, we evaluated various thermoelectric parameters such as Seebeck coefficient, electrical and thermal conductivity, power factor and figure of merit (ZT) as function temperature as well as chemical potential. Almost all thermoelectric parameters show anisotropy between $xx$ and $zz$ directions which is stronger in case of A-AFM than in NM. Both A-AFM and NM phase of the compound display better thermoelectric performance when hole doped. We observed high Seebeck coefficient and low electronic thermal conductivity in A-AFM phase along $zz$ direction. The remarkably high ZT of 1.79 at 500 K in A-AFM phase and ZT$\sim$1 in NM phase suggest that EuCd$_{2}$As$_{2}$ is a viable thermoelectric material when p-doped.

cond-mat.mtrl-sci↗
arXiv2014

Polytropic bulk viscous cosmological model with variable G and Λ

We consider a Bianchi type-I Polytropic bulk viscous fluid cosmological model with variable G and Λ. To get a deterministic model, we assume some conditions of A, B, C, and polytropic relation to find the results. physical significance of the cosmological models have also been discussed.

physics.gen-ph↗