Research

Several representative research areas pursued at CRFL are detailed in the following. Advancements coming out of these studies would improve the current understanding of reacting flows and the computational modeling of practical combustion systems.

Inter-scale turbulence chemistry dynamics with reduced basis representations

The longer term objective of this project is to explore the potential of employing new reduced basis representations within current state-of-the-art Large-Eddy Simulation (LES) frameworks to more accurately predict important resolved-scale dynamics associated with flame-turbulence interactions in premixed turbulent combustion. Our aim is not to develop a new simulation method with a complete set of new basis functions, but rather to develop new modeling elements embedded within current LES frameworks to capture dynamically dominant subgrid-resolved-scale interactions necessary for accurate prediction of resolved-scale premixed turbulent combustion dynamics. The analyses will derive from a series of numerical experiments designed to capture essential flame-turbulence dynamics in all premixed turbulent combustion regimes. The anticipated outcomes will include a library of reduced basis functions to incorporate as new modeling elements to capture potentially important dynamics currently missing in LES.

This research focuses on the dynamics surrounding flame front dynamics in fully turbulent high Reynolds number combustion, with general applicability to a wide range of technologies including aircraft combustors and gas turbines. This approach has the potential to initiate new directions in analysis and LES modeling strategies for broad application to non-equilibrium turbulent flow dynamics outside the classical cascade description.

Sponsored by the U.S. Air Force Office of Scientific Research

Development of yield-based sooting tendency modeling to enable advanced combustion fuel

The goal of this project is to accelerate the introduction of advanced combustion fuels and engines by developing fundamental knowledge that will enable them to be implemented while reducing soot particulate emissions. Given the importance of soot emissions from engines, projects focused on ameliorating them are underway at National Renewable Energy Laboratory (NREL), Sandia National Laboratories, Lawrence Livermore National Laboratory (LLNL), and other Department of Energy (DoE) facilities; this project seeks to complement those efforts through university-level research. Specifically, we will determine sooting tendencies for a large number of promising biomass-derived fuels through computations, then use the results to identify the fuel properties that maximize engine performance in terms of low emissions, select the biomass-derived fuels that have the best values of these properties, and improve Computational Fluid Dynamics (CFD) simulations so that the full value opportunity of advanced fuels in reducing particulate emissions can be realized.

Sponsored by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy

Development and evaluation of a novel fuel injector design method using hybrid-additive manufacturing

This work addresses the need for novel new design methodologies to address the critical operational issues in low-emissions, fuel-flexible, high-efficiency gas turbine combustors. These operational issues, including flame static stability and thermoacoustic oscillations, are first-order drivers of improved engine performance, particularly at higher operating temperatures. Design for these operational issues will be co-optimized with design for additive manufacturing, including the use of advanced post-processing techniques. The goal of this work is to use adjoint-based optimal design and additive manufacturing (AM) to radically re-imagine the design and manufacturing of fuel injection hardware for power generation gas turbines to improve key combustor operability challenges. We will use large-eddy simulation, hydrodynamic stability analysis, and constraints based on both flow/flame stability as well as AM limitations to optimize both the flow and the shape of the fuel injector simultaneously using a constrained optimization framework.

Sponsored by the U.S. Department of Energy

Multi-scale simulations of 2D material synthesis in metal-organic chemical vapor deposition

Transition Metal Dichalcogenides (TMD), such as WSe₂ and MoS₂, are a unique and highly versatile 2D nano-materials platform. The discovery of mono- and few-layer TMD has opened the path to explore new paradigms for electronic and photonic properties of next-generation sensors, catalysts, and meta-materials. Despite their potential as multi-functional material, TMD has only been successfully synthesized by Metal-Organic Chemical Vapor Decomposition (MOCVD) at laboratory-scale, but is currently not available in sufficient quality and quantity to support industrial- and commercial-scale uses. The unique potential of TMD-based materials is limited by the challenges inherent in the reproducible synthesis of high-quality materials over wafer-scale areas, and the exponentially more complex direct growth of multiple layers of TMD. The objective of this project is to formulate a multi-scale computational framework, which combines quantum mechanical calculations, reactive molecular dynamics, and computational fluid dynamics, to enable first-principle-based simulations of TMD synthesis at wafer scales, that can quantitatively predict TMD growth rates and quality. Such predictive capability will significantly improve the reproducibility of TMD growth and lead to simulation-based optimization of the synthesis reactor and process at commercial scales.
Sponsored by the U.S. National Science Foundation