ERI: Fundamental Study of Multiscale Dynamics of Molecular Mixing and Chemical Reactions in Multiphase Systems

About This Grant

This project will examine how different substances mix and react in flowing mixtures of liquids and gases. When fluids mix and undergo chemical reactions, tiny random swirls of turbulence control how well molecules mix and react. Understanding these processes is very important because they affect the efficiently of energy production, how pollutants spread in the environment, and how chemicals, materials, and medicines are manufactured. However, predicting and controlling mixing and reactions in such chaotic flows is a big challenge because small changes at the microscopic level can lead to very different outcomes. To address this challenge, the project will develop new computer models that more accurately represent mixing and chemical reactions in complex flows at the molecular scale. Better simulation of these processes will help engineers design cleaner engines, more efficient chemical reactors, and processes to create materials with less waste and pollution. The project will also emphasize education and accessibility by training students in advanced simulation techniques, releasing new software tools as open source to the public, and engaging students through outreach activities. Through these efforts, the project will advance scientific knowledge while contributing to national prosperity, environmental protection, and public health. The research will develop a new bounded Langevin micromixing model to simulate molecular-scale mixing in turbulent multiphase flows. The stochastic model enforces physical bounds on scalar concentrations and provides improved predictions of how mixing fluctuations decay over time. Chemical reaction kinetics will be tightly coupled with the mixing process through Jacobian matrix analysis, allowing the model to adjust local mixing rates based on relevant reaction time scales. In addition, the model will adapt to local flow conditions using the Damköhler number, ensuring accurate treatment across regimes ranging from mixing-limited to reaction-limited behavior. The resulting models will be implemented within a computational framework and rigorously validated against high-fidelity data from direct numerical simulations and experimental measurements. The computational approach employs quadrature-based moment methods to efficiently represent the evolving distributions of scalars in mixing and reacting systems, capturing their inherent multiscale nature. The finalized model will be released as open-source software through the OpenQBMM library and integrated into OpenFOAM, enabling broad use and further development by the research and engineering communities. Finally, the project integrates research and education by actively involving graduate and undergraduate students in model development and validation, providing hands-on training in advanced simulation techniques and supporting workforce development in STEM fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.