Indian Institute of Technology Bhubaneswar

About: Indian Institute of Technology Bhubaneswar is a education organization based out in Bhubaneswar, India. It is known for research contribution in the topics: Large Hadron Collider & Higgs boson. The organization has 1185 authors who have published 3132 publications receiving 48832 citations.

Biopolymer amendment for mitigating dispersive characteristics of red mud waste

Abstract: Previous studies revealed that the geotechnical properties of red mud waste (RMW) closely resemble that of conventional soils. Due to the predominant presence of exchangeable sodium, the RMW tends ...

Analysis of sound generation by flow past a circular cylinder performing rotary oscillations using direct simulation approach

Abstract: Generation of sound due to laminar flow past a circular cylinder performing rotary oscillations has been studied using a direct numerical simulation approach. Two-dimensional, unsteady, compressible Navier-Stokes equations are directly solved using high resolution, physical dispersion relation preserving schemes. In this work, modifications in the flow induced acoustic noise due to imposed rotary oscillations have been discussed in detail. Simulations have been performed for a Reynolds number Re = 150 and a Mach number M = 0.2 over a wide range of forcing frequencies and amplitudes of rotary oscillation, specifically in the synchronization region. Rotary oscillating motion of a cylinder modifies the vortex shedding patterns in the wake region as compared to the case of flow past a stationary cylinder. The frequency and strength of shed vortices determine the nature of aerodynamic forces acting on the cylinder as well as sound generation. Reduction in sound generation has been observed for some of the forced oscillation cases as compared to the flow past a stationary cylinder case. The Doak’s decomposition methodology has been used to segregate the acoustic and hydrodynamic modes from the momentum density field to understand changes in the radiated sound field for different forcing conditions. Furthermore, disturbance pressure fields have been decomposed into a number of modes based on their significance, using a proper orthogonal decomposition (POD) technique in order to identify and quantify the contribution of the lift and drag dipoles to the sound field. In addition, POD modes of disturbance vorticity fields as well as noise source structures based on approximate Lighthill’s stress tensor are also obtained and related to the generated sound fields. This analysis concludes that the frequency of rotary oscillation dictates the frequency content of the flow induced sound field. Low frequency rotary oscillations trigger sound waves with low frequencies and large wavelengths. As the forcing frequency increases, the corresponding sound field displays shorter wavelengths. Directivity of the sound field is affected by the amplitude of rotary oscillation. A case with higher forcing amplitude distributes sound energy more evenly in all directions as compared to a lower forcing amplitude case. Prescription of rotary oscillations to the circular cylinder significantly alters the frequency, amplitude, and directivity of the generated sound field.

Segmentation and recognition of text written in 3D using Leap motion interface

Abstract: In this paper, we present a word extraction and recognition methodology from online cursive handwritten text-lines recorded by Leap motion controller The online text, drawn by 3D gesture in air, is distinct from usual online pen-based strokes. The 3D gestures are recorded in air, hence they produce often non-uniform text style and jitter-effect while writing. Also, due to the constraint of writing in air, the pause of stroke-flow between words is missing. Instead all words and lines are connected by a continuous stroke. In this paper, we have used a simple but effective heuristic to segment words written in air. Here, we propose a segmentation methodology of continuous 3D strokes into text-lines and words. Separation of text lines is achieved by heuristically finding the large gap-information between end and start-positions of successive text lines. Word segmentation is characterized in our system as a two class problem. In the next phase, we have used Hidden Markov Model-based approach to recognize these segmented words. Our experimental validation with a large dataset consisting with 320 sentences reveals that the proposed heuristic based word segmentation algorithm performs with accuracy as high as 80.3%c and an accuracy of 77.6% has been recorded by HMM-based word recognition when these segmented words are fed to HMM. The results show that the framework is efficient even with cluttered gestures.

Silver(I)-diene complexes as versatile catalysts for the C-arylation of N-tosylaziridines: mechanistic insight from in situ diagnostics.

Abstract: Silver(I) complex [Ag(diene)2]+Y− (where diene = cyclooctadiene, norbornadiene, and 1,3-cyclohexadiene; Y− = PF6−, BF4−) efficiently catalyzes the arylation of N-tosylaziridines with arenes and heteroarenes under ambient condition to provide the corresponding β-aryl amine derivatives with excellent regioselectivity. To understand the nature of substrate activation, and initial bond breaking/making steps, the following studies were conducted with the help of in situ NMR (1H, 31P, 109Ag) and ESI-MS probe: (I) evaluation of Hammett reaction constant (ρ); (II) correlation of initial rate (k) versus cone angle (θ) of ligand L for reactions mediated by [Ag(COD)2]PF6/L (where L is a phosphine or a phosphite ligand); (III) identification of silver−arene intermediates in solution; and (IV) correlation of initial rate (k) with ΔHOMO−LUMO of [Ag(diene)2]PF6 obtained from preliminary DFT studies. Study I led to a ρ-value of −0.586, indicating that the extent of electrophilic perturbation is considerably less than a t...

Reduced graphene oxide based hybrid functionalized films for hydrogen detection: Theoretical and experimental studies

Abstract: In this work, hydrogen sensing characteristics of reduced graphene oxide (rGO) based functional nanomaterials are investigated with first principle calculations and experimental analysis. rGO doped with zinc oxide nanomaterial (i.e. rGO-ZnO), rGO-ZnO with silver nanoparticles (rGO-ZnO-Ag), rGO-ZnO with zirconium oxide (rGO-ZnO-ZrO2), rGO-ZnO doped with silver and palladium (rGO-ZnO-Ag-Pd) are investigated for their sensing capabilities. The influence of gas adsorption on the electronic features of the functional nanostructures are analyzed using the first principles density functional theory. The results of the computation reveal a considerable improvement of graphene oxide sensitivity in the hydrogen gas molecules following hybridization by ZnO, ZnO–Ag, ZnO–Ag–Pd and ZrO2. Fabrication and characterization of aforementioned functional materials and their hydrogen sensing performances are performed and essential sensing characteristics viz., sensitivity, response time, recovery time, reproducibility are also investigated. Out of the fabricated films, rGO-ZnO-Ag-Pd film is found to have the highest sensitivity towards hydrogen. It showed the sensitivity of ∼60% and highest performance factor (evaluated as the ratio of sensitivity to cycle time) among all films, including response time as 10 s and recovery time as 14 s. While performing sensing investigation, the distinct p-type behavior was observed for all the fabricated film. Obtained outcomes relate the promising future of rGO doped ZnO–Ag, ZnO–Ag–Pd and ZrO2 hybrid nano sensor in the advancement of sensitive gas sensors.