Directory at CAVS
Biography
Joshua L. Bowman, Ph.D., is a Postdoctoral Associate at CAVS focused on OpenFOAM-based CFD (RANS/LES), machine-learned surrogate, and reduced-order modeling for rotating/propulsive flows, supported by scalable Slurm-based HPC workflows. He also supports DoD workflow efforts in naval propulsion (hull–propeller–rudder interaction) and hypersonic mesh/workflow support.
Research Interest
OpenFOAM Computational Fluid Dynamics (RANS/LES)
Unsteady vortex-dominated flows
Rotor & wake modeling
Machine-learned surrogate & reduced-order models (actuator-type)
HPC & Slurm workflow automation
Hull-propeller-rudder interaction
Hypersonic CFD meshing & workflows
Unsteady vortex-dominated flows
Rotor & wake modeling
Machine-learned surrogate & reduced-order models (actuator-type)
HPC & Slurm workflow automation
Hull-propeller-rudder interaction
Hypersonic CFD meshing & workflows
Selected PublicationsTotal Publications: 9
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. (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]
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]
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]
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]