3 publications
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Published Subscription Review Article
Digital Twin and Machine Learning Framework for Predictive Maintenance of Nuclear Power SystemsBy Shweta Zambare, Shivani Shendage, Pratiksha Surve, Nilophar Shaikh, Vaibhav Godase
Abstract: Nuclear power systems contain safety-critical components whose degradation can affect availability, reliability, and maintenance planning. Conventional maintenance strategies are largely based on scheduled inspection, threshold monitoring, and condition-based assessment, which may not fully exploit the large volume of continuously generated plant data. Digital Twin (DT) technology provides a mechanism for maintaining a synchronized virtual representation of a physical nuclear system, while machine learning (ML) can extract degradation patterns from multivariate …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article →
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Published Subscription Review Article
AI-Assisted Design of a Compact UWB Antenna with Tunable Band-Notch CharacteristicsBy Shweta Zambare, Shivani Shendage, Pratiksha Surve, Nilophar Shaikh, Vaibhav Godase
Abstract: Ultra-wideband antennas require wide impedance bandwidth while maintaining stable radiation characteristics and suppressing interference from coexisting narrowband wireless services. Conventional optimization of UWB antenna geometries generally requires repeated full-wave electromagnetic simulations, making parameter exploration computationally expensive. This paper proposes an artificial-intelligence-assisted methodology for designing a compact UWB monopole antenna with a tunable band-notch characteristic. The proposed antenna uses a microstrip-fed planar monopole printed on an FR-4 substrate, while a tunable …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article →
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Published Subscription Review Article
AI-Assisted Design of a Compact Bandpass Microwave Filter for 5G/6G ApplicationsBy Shweta Zambare, Shivani Shendage, Pratiksha Surve, Nilophar Shaikh, Vaibhav Godase
Abstract: The rapid development of fifth generation (5G) and emerging sixth generation (6G) wireless communication systems require compact, low-loss, highly selective and frequency-stable radio- frequency front-end components. Microwave bandpass filters play an important role in selecting desired communication channels while suppressing out-of-band interference. However, conventional filter design generally requires repeated electromagnetic simulation and manual optimization of geometrical parameters, resulting in considerable computational time. This paper presents an artificial intelligence (AI)-assisted methodology …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article →