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Pinaki Pal

Research Scientist


Dr. Pinaki Pal is a research scientist in Argonne’s Energy Systems division. His research interests broadly lie in the areas of computational fluid dynamics (CFD), turbulent combustion modeling, low temperature combustion, combustion dynamics, combustion rare events, machine learning, computational science, and high-performance computing, for a wide range of applications, such as propulsion (automotive and aerospace) and material synthesis.

At Argonne, he developed a turbulent combustion modeling framework to capture knocking combustion and extended the state-of-the-art models by incorporating fuel composition effects on turbulent flame propagation. Dr. Pal led a numerical study utilizing this combustion modeling approach to investigate the impact of fuel properties on knock-limited performance of spark-ignition engines, which won the ASME International Combustion Engine Division Best Paper Award 2020 (in Fuels category).  On the other hand, he also co-led the development of novel machine learning algorithms to accelerate turbulent combustion CFD simulations and engine design optimization. This research work has resulted in six software copyrights and one patent (pending). In addition, Dr. Pal initiated and led the computational research effort at Argonne pertaining to numerical modeling and design of rotating detonation engines (RDEs), which are promising candidates for power generation and hypersonic propulsion. He received the Impact Argonne (formerly Pacesetter) Award in 2019 for this R&D contribution.

Dr. Pal’s current research topics of interest include:

  1. CFD modeling and analysis of combustion dynamics in rotating detonation engines (RDEs)
  2. Deep learning techniques for accelerating turbulent combustion simulations
  3. Analysis of stochastic cycle-to-cycle combustion variability in spark-ignition engines using large-eddy simulations (LES) and machine learning
  4. Application of machine learning, CFD, and HPC, for rapid optimization in high-dimensional design spaces
  5. Physics-informed data-driven near-wall turbulence modeling
  6. Numerical investigation of fuel effects on gasoline compression ignition (GCI)
  7. Development of non-equilibrium wall models and combustion models in a high-order spectral element CFD code, Nek5000, for multi-mode engine simulations
  8. Computational modeling and analysis of nanoparticle synthesis in flame spray pyrolysis (FSP) reactors

Dr. Pal received his PhD from University of Michigan-Ann Arbor (2015) in Mechanical Engineering, with specialization in turbulent combustion modeling and CFD for low temperature combustion applications in both internal combustion engines and gas turbines. He also holds a Bachelor of Technology in Mechanical Engineering from the Indian Institute of Technology Kharagpur (India) (2011).