CAVS Publications

Search Publications

Publications for: Joshua L. Bowman
Peer-Reviewed Journals
Bowman, J. L., Bhushan, S., Burgreen, GW, & Dettwiller, I. (2025). Development and Validation of Machine-Learned Actuator Line Model for Hydrokinetic Turbine Rotor. Journal of Fluids Engineering. ASME. 147(8), 081501. DOI:10.1115/1.4067787. [Abstract] [Document Site]

Elfajri, O., Bowman, J. L., Bhushan, S., & O'Doherty, T. (2024). Detached Eddy Simulation of Hydrokinetic Turbine Wake in Shallow Water Depths. Ocean Engineering. 306, 118083. DOI:10.1016/j.oceaneng.2024.118083. [Abstract] [Document Site]

Elfajri, O., Bowman, J. L., Bhushan, S., Thompson, D., & O'Doherty, T. (2022). Numerical Study of the Effect of Tip-speed Ratio on Hydrokinetic Turbine Wake Recovery. Renewable Energy. 182, 725-750. DOI:10.1016/j.renene.2021.10.030. [Abstract] [Document Site]

Peer-Reviewed Conference Papers
Bowman, J. L., Bhushan, S., & Aram, S. (2025). Development, Verification and Validation of a Machine-Learned Actuator Line Propeller Model. Proceedings of the ASME 2025 Fluids Engineering Division Summer Meeting. Philadelphia, PA, USA. DOI:10.1115/FEDSM2025-158665. [Abstract] [Document Site]

Bowman, J. L., Bhushan, S., Burgreen, GW, & Dettwiller, I. (2024). A Machine-Learned Actuator Line Model for Hydrokinetic Turbines. Proceedings of the ASME 2024 Fluids Engineering Division Summer Meeting collocated with the ASME 2024 Heat Transfer Summer Conference and the ASME 2024 18th International Conference on Energy Sustainability. Anaheim, CA: ASME. DOI:10.1115/FEDSM2024-131429. [Abstract] [Document Site]

Bowman, J. L., Bhushan, S., Burgreen, GW, & Dettwiller, I. (2021). Hydrokinetic Turbine Performance and Wake Analysis Using a Data-Driven Actuator Line Model. Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition. Virtual Online: ASME. DOI:10.1115/IMECE2021-71957. [Abstract] [Document Site]

Bhushan, S., Burgreen, GW, Bowman, J. L., Dettwiller, I., & Brewer, W. (2020). Predictions of Steady and Unsteady Flows Using Machine-learned Surrogate Models. 2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) and Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S). GA, USA: IEEE. 80-87. DOI:10.1109/MLHPCAI4S51975.2020.00016. [Abstract] [Document Site]

Ellis, R., Bowman, J. L., O'Doherty, T., O'Doherty, D., Mason-Jones, A., Bhushan, S., & Thompson, D. (2019). A Comparison of Predictions by ANSYS CFX and OPENFOAM with Experimental Data of a Horizontal Axis Tidal Turbine. EWTEC 2019 – 13th European Wave and Tidal Energy Conference. Naples, Italy. [Abstract]

Bowman, J. L., Bhushan, S., Thompson, D., O'Doherty, D., O'Doherty, T., & Mason-Jones, A. (2018). A Physics-Based Actuator Disk Model for Hydrokinetic Turbines. 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-3227). Atlanta, GA: AIAA. DOI:10.2514/6.2018-3227. [Abstract] [Document Site]