arXiv subjects

Komal

Publications and source records attributed to Komal.

4 recordsLinked to original sources

arXiv2026

Effect of LH and ECR waves on plasma parameters in ADITYA Upgrade tokamak

The plasma discharges in ADITYA Upgrade Tokamak are produced by means of transformer action, in which Ohmically created plasma is driven by means of a secondary loop voltage. Due to reduction of plasma resistivity after a certain level of plasma temperature, Ohmic heating becomes poor and further achievement of temperature needs other heating techniques. ADITYA-U tokamak is facilitated with a 42 GHz-500 kW Electron Cyclotron Resonant Heating (ECRH) system. Also, there is a Lower Hybrid Current Drive (LHCD) system installed and operated at 3.7 GHz for driving non-inductive plasma current followed by the Ohmic current drive. Though an eventual impact in the rise of plasma temperature and plasma current due to the application of ECRH and LHCD respectively are very obvious, their energy coupling with the plasma results in several interesting outcomes in a number of experimentally measured plasma parameters. The present work addresses such impactful observations that are noticed and reported for the first time in ADITYA-U Tokamak.

physics.plasm-ph↗

arXiv2025

Favorable modifications of Scrape-Off Layer (SOL) heat flux width through pulsed fuelling in ADITYA-U Tokamak

Enhancement of the scrape-off layer (SOL) heat flux width has been observed in the ADITYA-U Tokamak following the injection of short fuel gas pulses. A notable reduction in parallel heat flux near the last closed flux surface (LCFS) is observed after each pulse. Comparative analysis indicates that pulsed fuelling is more effective in mitigating heat flux with improved core confinement than continuous gas feeding via real-time density control. Analytical and simulation works are also carried out for validation of experimental results. The analytical model shows that SOL width modification cannot be attributed solely to the decrease of temperature due to gas pulse injection; cross-field plasma diffusion also needs to increase. Simulations with the UEDGE code suggest that an increase in both the cross-field diffusion coefficient and inward pinch velocity is necessary to replicate the experimentally observed broadening of the heat flux SOL width. These findings provide insights into efficient SOL heat flux control strategies for future fusion devices.

physics.plasm-ph↗

arXiv2024

Advanced Mathematical Modelling for Energy-Efficient Data Transmission and Fusion in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are indispensable for data-intensive applications, necessitating efficient energy management and robust data fusion techniques. This paper proposes an integrated framework leveraging fuzzy logic and backpropagation neural networks (BPNN) to enhance energy efficiency and data accuracy in WSNs. The model focuses on optimizing Cluster Head (CH) selection using fuzzy logic, considering parameters such as energy levels, proximity to the base station, and local density centrality. A Minimum Spanning Tree (MST) algorithm is employed for energy-efficient data transmission from sensor nodes to CHs, minimizing energy consumption during data routing. BPNN-based data fusion at CHs reduces redundant data transmissions to the base station, thereby optimizing energy utilization and enhancing overall network performance. Simulation results demonstrate substantial improvements over conventional methods, including a 30% increase in network longevity, 25% improvement in data accuracy, and a 40% reduction in energy consumption. These gains are attributed to the intelligent CH selection strategy enabled by fuzzy logic, which ensures efficient resource allocation and minimizes energy wastage. The effectiveness of the proposed approach is validated through comprehensive simulations, showcasing its ability to prolong network lifetime, maintain data integrity, and improve energy efficiency. The integration of fuzzy logic and BPNN not only addresses the challenges of energy management and data fusion in WSNs but also provides a scalable and adaptable framework for future applications requiring reliable and sustainable sensor network operations. The source code is available at https://github.com/hikomal/BPNN_WSN.git

cs.NI↗

arXiv2022

Multi-Scale Features and Parallel Transformers Based Image Quality Assessment

With the increase in multimedia content, the type of distortions associated with multimedia is also increasing. This problem of image quality assessment is expanded well in the PIPAL dataset, which is still an open problem to solve for researchers. Although, recently proposed transformers networks have already been used in the literature for image quality assessment. At the same time, we notice that multi-scale feature extraction has proven to be a promising approach for image quality assessment. However, the way transformer networks are used for image quality assessment until now lacks these properties of multi-scale feature extraction. We utilized this fact in our approach and proposed a new architecture by integrating these two promising quality assessment techniques of images. Our experimentation on various datasets, including the PIPAL dataset, demonstrates that the proposed integration technique outperforms existing algorithms. The source code of the proposed algorithm is available online: https://github.com/KomalPal9610/IQA

cs.CV↗