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Polarization Independent Ultra-wideband Meta-material Absorber Using Conductive Ink Resonator

Kumari Bharti, Kumar Abhinav, Kumar Prashant, Singh Mintu

Journal of Telecommunications and Information Technology

2024

nr 1

39--45

A wideband meta-material absorber with square and circular split rings that is based on a frequency selective surface of conductive ink is proposed. With over 90% absorptivity, the structure demonstrates broad absorption for the C, X, KU and K bands, as well as polarization independent characteristics for both TE and TM, at angles of up to 45°. Research has been performed to better understand the absorption phenomenon by looking into real and imaginary permittivity, permeability, normalized impedance, and surface current density. The meta-material absorber (MA) discussed in this study finds use in defense-related applications, such as radar surveillance, stealth technology, terrestrial and satellite communications.

Impact of convection and stability parameters on lightning activity over Andhra Pradesh, India

Umakanth N., Satyanarayana G. Ch., Simon B., Kumar Prashant, Rao M. C.

Acta Geophysica

2020

Vol. 68, no. 6

1845--1866

This paper brings out the interconnection of fash rate density (FRD) with convection and stability parameters over Andhra Pradesh (AP), India. The convection parameters include rainfall, relative humidity, specifc humidity, surface air temperature (SAT) and air temperature (at 850 mb). The stability parameters include convective available potential energy (CAPE), lifted index, K-index, total totals index (TTI), humidity index and total precipitable water. Both convective and stability parameters indicate good correlation with lightning activity. SAT and AT 850 mb have shown good correlations with lightning, which is a clear indication of interaction between warm air and dry air. CAPE and TTI have shown strong positive correlation with lightning activity. The correlation coefcient between FRD and CAPE is 0.81. We have also studied the infuence of convective and stability parameters during lightning and no lightning activity. Later, we also attempted the estimation of lightning activity by using artifcial neural network model. By using convection and stability parameters, six learning algorithms were used for training the artifcial neural network. Scaled conjugate gradient backpropagation training algorithm has given the better estimation, whereas resilient backpropagation training algorithm has shown the poor estimation of FRD.