{"id":313,"date":"2025-07-30T19:31:54","date_gmt":"2025-07-30T19:31:54","guid":{"rendered":"https:\/\/dev.www.purdue.edu\/research\/methodsmuri\/?page_id=313"},"modified":"2026-10-27T14:18:38","modified_gmt":"2026-10-27T14:18:38","slug":"products","status":"publish","type":"page","link":"https:\/\/www.purdue.edu\/research\/methodsmuri\/products\/","title":{"rendered":"METHODS MURI | Products"},"content":{"rendered":"\n
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Machine Learning Enabled Two-Phase Flow Metrologies, Models, and Optimized Designs<\/strong><\/p>\n<\/div>\n\n\n\n

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An Office of Naval Research (ONR) <\/strong>
Multidisciplinary University Research Initiative (MURI)<\/strong><\/p>\n<\/div>\n\n\n\n

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Journal Papers<\/strong>

S Khodakarami, PV Vydyula, A Bora, JA Weibel, GE Karniadakis. Physics-informed Kolmogorov\u2013Arnold networks (PIKANs) for noise-robust reconstruction of boiling heat flux from infrared measurements. Comput. Methods Appl. Mech. Eng. (2027). https:\/\/doi.org\/10.1016\/j.cma.2026.119459<\/a>.

FB Golezani, JK Narayanan, CR Kharangate. Impact of the Lee model coefficient on 3D CFD simulations of microgravity annular flow condensation with two-phase inlet conditions. Int. J. Heat Mass Transf. 2026. https:\/\/doi.org\/10.1016\/j.ijheatmasstransfer.2026.129082<\/a>

S Khodakarami, V Oommen, NA Daryakenari, M Beekenkamp, GE Karniadakis. Spectral bias in physics-informed and operator learning: Analysis and mitigation guidelines. Comput. Methods Appl. Mech. Eng. (2026). https:\/\/doi.org\/10.1016\/j.cma.2026.119156<\/a>.

F Naderi, X Ji, JK Narayanan, FB Golezani, C Zhang, L Pirnstill, F Zhu, CR Kharangate. Large-Scale Vision-Based Characterization of Flow Regimes and Interfacial Distributions for Heat Transfer Prediction in Terrestrial Horizontal Mini-Channel Flow Boiling. Appl. Therm. Eng. 2026. https:\/\/doi.org\/10.1016\/j.applthermaleng.2026.132079<\/a>.

AR Sakrikar, R Rajeev, S Kumar. Physics-informed Neural Networks to Predict Mass Transfer at Interfaces in Liquid-Vapor Phase Change Problems.\u00a0 Int. J. Heat Mass Transf. 2026. https:\/\/doi.org\/10.1016\/j.ijheatmasstransfer.2026.128392<\/a>.

V Oommen, S Khodakarami, A Bora, Z Wang, GE Karniadakis. Learning turbulent flows with generative models for super resolution and sparse flow reconstruction. Nature Communications, 2026. https:\/\/doi.org\/10.1038\/s41467-026-70145-4<\/a>.

S Khodakarami, V Oommen, A Bora, GE Karniadakis. Mitigating spectral bias in neural operators via high-frequency scaling for physical systems. Neural Networks. 2026. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0893608025009074<\/a>.<\/p>\n\n\n\n

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Conference Papers<\/strong>

AM Davis, Y Shen, X Ji, F Zhu. Denoising of Two-Phase Optically Sectioned Structured Illumination Reconstructions Using Encoder-Decoder Networks. IEEE ICIP 2026 Conference. https:\/\/doi.org\/10.1109\/ICIP61757.2026.11630429<\/a>.

S Govindaraj, FB Golezani, JK Narayanan, CR Kharangate. Physics-Informed Neural Networks for Control Volume Modeling of Flow Condensation. IEEE ITherm 2026 Conference.

S Govindaraj, PP Roy, JK Narayanan, CR Kharangate. Data-Driven Identification of Lee Coefficient Distributions in Horizondal Channel Flow Boiling Using Inverse PINNs. IEEE ITherm 2026 Conference.

F Naderi, CR Kharangate. Enhancing Thermal Management through YOLO-Based Analysis of Bubble Dynamics in Bottom-Wall Flow Boiling under Normal Gravity. IEEE ITherm 2026 Conference.

L Pirnstill, F Naderi, CR Kharangate. A Complete Framework for Model Discovery of Flow Boiling Interface Dynamics Utilizing Physics Informed Machine Learning. IEEE ITherm 2026 Conference.

F Naderi, FB Golezani, CR Kharangate. Enhancing Thermal Management through Deep Learning-Based Analysis of Bubble Dynamics in Flow Boiling. IEEE ITherm 2025 Conference. 10.1109\/ITherm55376.2025.11235809<\/a>.<\/p>\n\n\n\n

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Conference Oral Presentations<\/strong>

S Khodakarami, PV Vydyula, A Bora, JA Weibel, GE Karniadakis. Physics-informed Kolmogorov Arnold network solves unsteady three-dimensional heat conduction with experimentally measured boiling boundary conditions. WCCM ECCOMAS, July 19-24, 2026.

S Khodakarami, PV Vydyula, A Bora, JA Weibel, GE Karniadakis. Physics-informed Kolmogorov Arnold network solves unsteady three-dimensional heat conduction with experimentally measured boiling boundary conditions. ICBCHT 12, June 14-17, 2026.

A Yee, M Yoda. “Quantitative visualizations of pool boiling for a dielectric fluid”. APS Division of Fluid Dynamics Annual Meeting, November 23-25, 2025.

D Olson, R Cruikshank, M Rutkowski, M Koochesfahani. “Application of Photobleaching Molecular Tagging Velocimetry to Flow Boiling Studies”. APS Division of Fluid Dynamics Annual Meeting, November 23-25, 2025.

S Khodakarami, V Oommen, A Bora, GE Karniadakis. “Mitigating spectral bias in neural operators with high-frequency scaling”. 18th USNCCM, July 20-24, 2025.

PV Vydyula, M Bongarala, JA Weibel. “Extrapolated Prediction of Pool Boiling Critical Heat Flux Through Modeling the Local Maximum in the Nucleate Boiling Curve”. ASME SHTC 2025, July 8-10, 2025.

JH West, A Ceperley, PV Vydyula, JA Weibel. “Synchronous Through-Substrate High-Speed Visual and Infrared Observation of Flow Boiling in a Rectangular Channel”. ASME SHTC 2025, July 8-10, 2025.

KNR Sinha, PV Vydyula, JA Weibel. “A deep learning approach for heat flux partitioning analysis of pool boiling using through-substrate infrared thermography”. ASME SHTC 2025, July 8-10, 2025.

A Sakrikar, R Rajeev, S Kumar. “Physics-informed Neural Network for bubble rise in two-phase flows”. Micro Flow and Interfacial Phenomena, June 16-18, 2025.<\/p>\n\n\n\n

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Conference Poster Presentations<\/strong>

AM Davis, Y Shen, X Ji, F Zhu. Denoising of Two-Phase Optically Sectioned Structured Illumination Reconstructions Using Encoder-Decoder Networks. IEEE ICIP 2026 Conference, September 13-17, 2026.

PV Vydyula, M Bongarala, JA Weibel. Development of Mechanism-Specific Correlations for Nucleate Pool Boiling via Bubble Footprint Tracking on the Heater Surface. ICBCHT 12, June 14-17, 2026.

JH West, PV Vydyula, AM Ceperley, JA Weibel. Synchronous surface temperature and phase distributions with side-view visualization across flow regimes in top-heated flow boiling. ICBCHT 12, June 14-17, 2026.

KNR Sinha, PV Vydyula, S Khodakarami, GE Karniadakis, JA Weibel. Learning Full-Channel Flow Boiling Temperature Maps from Limited Field-of-View IR Measurements and Side-View Flow Visualization via cGAN. ICBCHT 12, June 14-17, 2026.

F Naderi, CR Kharangate. Advancing Thermal Management: Comparative Analysis of State-of-the-Art Vision Models in Bubble Dynamics from High-Speed Imaging. IEEE ITherm 2026 Conference, May 26-29, 2026.

A Davis, M Spadaro, X Ji, Y Zhen, M Yoda, F Zhu. “Noise-free Structured-Illumination Reconstruction of Pool Boiling Images”. Purdue School of ECE graduate student research symposium, 16-Oct-2025.

PV Vydyula, M Bongarala, JA Weibel. “A Modeling Framework for Nucleate Pool Boiling Based on Heat Flux Partitioning”. ASME SHTC 2025, July 8-10, 2025.

F Naderi, TH Phan, L Pirnstill, and CR Kharangate. “Physics-Informed Neural Network Framework for Inverse Modeling of Two-Phase Boiling”. Micro Flow and Interfacial Phenomena, June 16-18, 2025.

A Davis, M Spadaro, X Ji, Y Zhen, M Yoda, F Zhu. “Noise-free Structured-Illumination Reconstruction of Pool Boiling Images”. CVPR 2025 CV4Science Workshop, June 11 – 15, 2025.

TH Phan, L Pirnstill, J Li, CR Kharangate. “Predicting Flow Boiling Heat Transfer Coefficient Utilizing Physics-Informed Machine Learning Model”. IEEE ITherm 2025, May 27-30, 2025.

F Naderi, FB Golezani, CR Kharangate. “Enhancing Thermal Management through Deep Learning-Based Analysis of Bubble Dynamics in Flow Boiling”. IEEE ITherm 2025 Conference, May 27-30, 2025.<\/p>\n\n\n\n

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