Avinash Upadhyay

Doctoral Student, Indian Institute of Technology Patna

Research

Boiling Performance Enhancement with Soluble Additives

Efficient thermal management is vital for modern energy and electronic systems, where boiling heat transfer serves as one of the most effective mechanisms for dissipating high heat fluxes. However, the performance of such systems is often constrained by early dryout and unstable bubble dynamics. This field of research explores the use of soluble molecular and ionic additives to enhance boiling performance by improving the critical heat flux (CHF) and heat transfer coefficient (HTC) through interfacial and physico-chemical modifications of the boiling surface. These additives actively influence surface wettability, bubble departure frequency, and microlayer dynamics, offering a tunable strategy for improving boiling efficiency without relying on permanent surface coatings. Our recent studies have demonstrated that incorporating ionic liquids as co-surfactants in aqueous surfactant solutions can simultaneously enhance CHF and HTC by promoting stable in-situ deposition and improved liquid replenishment at the heated surface.

Related Publications

[1] Upadhyay, A., Kumar, B., & Raj, R. (2024). “Ionic Liquid as a Cosurfactant for Critical Heat Flux Enhancement during Boiling with Aqueous Surfactant Solutions”, Applied Thermal Engineering, 122962. Link

[2] Upadhyay, A., Kumar, B., Kumar, N., & Raj, R. (2023). “Simultaneous Enhancement of Critical Heat Flux and Heat Transfer Coefficient via In-Situ Deposition of Ionic Liquids during Pool Boiling”, International Journal of Heat and Mass Transfer, 208, 124066. Link

Acoustic Emissions from Bubbles Departing an Underwater Nozzle

Bubble departure from an underwater nozzle produces discrete acoustic pulses that carry detailed information about interfacial dynamics. This research experimentally, numerically, and analytically investigates the origin and nature of these acoustic emissions, showing that a rapid liquid-jet inrush during the neck-fracture event excites the bubble oscillation and that air compressibility must be accounted for to match the acoustic response. A novel analytical model treats the departing bubble as a forced oscillator, extending the classical Marcel Minnaert resonance framework. These findings clarify previously ambiguous bubble-acoustic phenomena and enable more accurate interpretation of bubble signals in underwater multiphase flows and engineered thermal-fluid systems.

Related Publication

[1] Alam, M. Q., Upadhyay, A., Assam, A., & Raj, R. (2025). “On the origin and nature of acoustic emissions from bubbles departing an underwater nozzle”, Physics of Fluids, 37(4). Link

Adsorption Behavior of Surfactants and Ionic Liquids

The adsorption of amphiphilic molecules such as surfactants and ionic liquids at solid–liquid and liquid–vapor interfaces critically influences wetting, foaming, and heat-transfer characteristics in boiling systems. This research examines how molecular structure, counter-ion type, and concentration govern interfacial behavior and dynamic surface tension. Through a combination of boiling experiments, wettability measurements, and surface characterization, this work elucidates how ionic liquids—when used as co-surfactants—actively adsorb and form ultra-thin interfacial layers that modulate bubble nucleation and surface rewetting. Such controlled adsorption not only mitigates foam formation but also promotes stable liquid replenishment, leading to simultaneous enhancement in critical heat flux (CHF) and heat transfer coefficient (HTC). Insights from this research establish adsorption engineering as a powerful route to design next-generation, additive-driven boiling surfaces for high-performance thermal management applications.

Related Publications

Boiling Acoustic-Based Deep Learning Strategies for Regime Prediction

This research develops and validates a deep-learning framework that interprets acoustic signatures from boiling processes to accurately predict regime transitions and thermal performance states. Using high-sensitivity hydrophones and spectrogram-based preprocessing, the approach converts underwater boiling sound into machine-learning-ready data. A convolutional neural model (YAMNET), enhanced with explainable AI techniques (e.g., Grad-CAM), identifies key features and spectral bands associated with specific boiling regimes such as nucleate boiling, transition, or film boiling. By combining signal processing, transfer-learning of pre-trained audio models, and domain-specific feature extraction, the method achieves robust regime classification and opens pathways for early detection of boiling crisis in thermal-fluid systems.

Related Publications

[1] Suriyaprasaad, B., Upadhyay, A., Thakur, A., & Raj, R. (2025). “Explainable boiling acoustics analysis using Grad-CAM and YAMNet for robust pool boiling regime classification”, Applied Thermal Engineering, 127220. Link

Computational Fluid Dynamics (CFD) Simulations for Multiphase Applications

This research leverages advanced CFD methods to investigate multiphase phenomena such as bubble formation, departure, and oscillation in submerged nozzle flows. By coupling detailed numerical modeling of the liquid–gas interface with experimental validation of acoustic emissions, the work elucidates key mechanisms behind bubble dynamics, interfacial stress waves, and the resulting acoustic signals. The simulations incorporate compressibility of the gas phase, rapid neck‐fracture events, and transient liquid inrush to reproduce observed acoustic frequency peaks and waveform signatures. These CFD studies not only bridge the gap between physical measurements and mechanistic insight but also provide a predictive framework to guide the design of multiphase flow systems, thermal‐fluid devices, and noise‐mitigation solutions.

Related Publication

[1] Alam, M. Q., Upadhyay, A., Assam, A., & Raj, R. (2025). “On the origin and nature of acoustic emissions from bubbles departing an underwater nozzle”, Physics of Fluids, 37(4). Link

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