​​​​

 Track 01 | Artificial Intelligence (AI) for Fluids Engineering 

• AI-assisted flow simulation and turbulence modeling

• Machine learning-based fluid flow prediction and surrogate modeling

• Physics-informed neural networks (PINNs) for fluid mechanics

• Data-driven reduced-order modeling (ROM)

• Deep learning for experimental fluid dynamics post-processing

• AI optimization for fluid engineering design

• Uncertainty quantification in AI/ML-based models
   

 Track 02 | Computational Fluid Dynamics (Methods and Applications) 

• CFD algorithm development and discretization methods

• Grid generation and mesh adaptation

• Turbulence modeling: DNS, LES, RANS, and hybrid approaches

• Fluid-structure interaction (FSI)

• Discrete element methods (LBM, Particle Method, Vortex Method)

• Multi-physics simulation

• High-performance computing for CFD

• Verification, validation, and uncertainty quantification
   

 Track 03 | Aerodynamics and Compressible Flows 

• Subsonic, transonic, and supersonic aerodynamics

• High-speed and hypersonic flows

• Shock wave dynamics and shock-boundary layer interactions

• Boundary layer transition and flow control

• Bluff body aerodynamics, wakes, and vortex shedding

• Aircraft, rotorcraft, and launch vehicle aerodynamics

• Wind energy and vehicle aerodynamics
   

 Track 04 | Bio-Inspired, Biomedical, and Biological Fluid Mechanics 

• Bio-inspired flow mechanisms (birds, fish, insects)

• Cardiovascular and respiratory fluid mechanics

• Hemodynamics and patient-specific blood flow modeling

• Drug delivery and aerosol transport in biological systems

• Microorganism locomotion and collective behavior

• Biomedical device fluid mechanics

• Bioreactor and tissue engineering flows
   

 Track 05 | Micro and Nano Fluid Mechanics 

• Micro/nano flow modeling and simulation

• Micro/nano thermodynamics and heat transfer

• Microfluidics and bio micro fluidics

• Applications of micro/nano fluidic systems

• Micro/nano measurement of fluid and heat

• Micro/nano fluidic-based energy storage

• Electrokinetic and surface-tension-driven flows
   

 Track 06 | Multiphase and Interfacial Flows 

• Bubble dynamics and droplet formation

• Gas-liquid and liquid-liquid two-phase flows

• Particle-laden flows (gas-solid, liquid-solid, slurry)

• Cavitation and erosion

• Interfacial instability and free-surface flows

• Boiling, condensation, and phase change

• Industrial multiphase applications (nuclear, petroleum, chemical)
   

 Track 07 | Complex Fluids 

• Non-Newtonian and viscoelastic fluid mechanics

• Polymer solutions and melts in flow

• Functional fluids (ER/MR fluids, ferrofluids, liquid crystals)

• Colloidal suspensions and emulsions

• Granular flows and dense suspensions

• Soft matter and active matter flows
   

 Track 08 | Computational Fluid Dynamics 

• Renewable energy systems (wind, tidal, solar thermal)

• Fuel cells and electrolyzers

• Thermal management and heat exchangers

• Combustion and reacting flow

• Energy storage fluid systems

• Carbon capture and sustainable process engineering
   

 Track 09 | Measurement, Instrumentation, and Industrial Applications 

• Advanced flow measurement (PIV, LDA, PTV, hot-wire anemometry)

• Optical diagnostics and laser spectroscopy

• Ultrasonic and non-invasive measurement methods

• Sensors, MEMS, and smart instrumentation

• Data processing, signal analysis, and machine learning for measurement

• Uncertainty quantification in flow measurements

• Industrial fluid mechanics and process engineering applications
   

 Track 10 | Fluid Mechanics: Fundamentals and Education 

• Turbulent flows and coherent structures

• Vortex dynamics and instability

• Jet, wake, and separated flows

• Flow control and manipulation

• Boundary layer flows and transition

• Fundamental studies in viscous and inviscid flows

• Fluids engineering education and pedagogy
   

 A1 | Flow Visualization Competition (ASME only) 

• Experimental and computational flow visualization entries

• Image/poster category (experimental or computational)

• Video category (experimental or computational)

• Judging criteria: visual appeal, originality, difficulty, physical insight

• Prizes awarded for top 3 entries in each category
   

 A2 | Who’s Who Competition (ASME only) 

• Competition to identify fluid mechanics personalities from photographs

• ASME Fluids Engineering Division community engagement activity

• Open to all AJKFED 2027 attendees​