Ammonia has many advantages as a zero-carbon energy storage solution, including robust infrastructure and high hydrogen density, but poor combustion properties make the direct use of ammonia in combustion applications such as internal combustion engines difficult. This project investigates the use of ammonia and hydrogen mixtures, with the hydrogen created by onboard catalytic cracking of the ammonia, for use in energy generation. The project investigates the performance as a sole fuel, as well as in blends with traditional hydrocarbon fuels as part of a carbon reduction strategy, and to increase energy resilience by relying on a locally generated fuel.
Advanced Dual Fuel Combustion of Zero-Carbon and Traditional Logistics Fuels
This project is investigating the performance and durability of low-pressure fuel burners in marine environments for on-board generation of thermal energy. Elements of the project include modeling of a new experimental burner within the Energy and Combustion Research Laboratory, the effects of salt on combustion and emissions, and predicting corrosion in the system.
Combustion Effects of Logistics Fuels and Salt-Air Environments
John Fernandez (M.S. Mechanical Engineering)
Hunter Apgar (B.S. Mechanical Engineering)
Jack Ryan (B.S. Mechanical Engineering)
Ethan Cahodas (B.S. Mechanical Engineering)
Stochastic Lagrangian-Eulerian (LE) methods are used in a variety of multiphase flow problems, such as fuel sprays or fluidized beds, where the number of dispersed phase bubbles/droplets/particles is too large to handle in a computationally efficient manner. Despite widespread use, there still remain questions about their numerical properties and convergence. Our lab is working to continue to develop the theory and numerical methods of LE approaches
Jairo Vanegas (M.S. Mechanical Engineering)
Chemical kinetics models of realistic fuels are very large (1,000+ chemical species) and computationally complex. It is not typically possible to directly incorporate these mechanisms into Computational Fluid Dynamics simulations without first reducing the mechanism in some manner. These reduced mechanisms are typically more limited in the conditions for which they can be used, and can themselves also still be very computationally expensive. Due to the high dimensionality of chemical kinetics systems, tabulation techniques, which can significantly reduce the computational expense of individual simulations by pre-computing the chemistry source terms, have not found much use outside of specific flamelet-type combustion models. We are developing new neural network-based approaches that are able to combine the accuracy and generalizability of large, reference chemical mechanisms with the computational efficiency of tabulation approaches while still be compatible with any turbulence-chemistry interaction closure.
Ahmed Almeldein (Ph.D. Mechanical Engineering)
Ephraim Simasiku (Visiting Fulbright Scholar)
“truth … is much too complicated to allow anything but approximations” — John von Neumann
Even the most sophisticated models involve some amount of assumptions, and must be solved imperfectly on computers. Most engineers understand this in general, but being able to quantify this statement, particularly when many different physics models are involved, is still difficult. Verification is the process of trying to quantify these numerical simulation errors. This is different from Validation, where simulation results are compared against experimental data, which gives a higher-level overview of the overall performance of a set of models and their settings. We are working to apply verification procedures to the flows relevant for engine simulations, including flow in complex, time-varying geometry, multiphase flows, and flames.
Angel Meza (B.S. Mechanical Engineering)
Garrett Perry (B.S. Mechanical Engineering)
Amjad Almaarafawi (B.S. Mechanical Engineering)
Transportation accounts 30% of the United States’ energy, and 70% of the country’s petroleum use. It also generates about 30% of the US’s greenhouse gas emissions. New engines and new fuels are required in order to reduce the environmental impact of internal combustion engines. Our lab is tackling the problem of non-predictive engine models, including spray models that are both accurate and applicable to full engine simulations.
Aman Kumar (Ph.D. Mechanical Engineering)
Justin Boussom (B.S. Mechanical Engineering)
John Chicoine (B.S. Mechanical Engineering)
Samuel Claflin (B.S. Mechanical Engineering)
Isabella Chan (B.S. Mechanical Engineering)
This project expanded current three-fluid models of water-steam flows to include field equations for homogeneous nucleation of liquid water droplets in expanding steam flows. This enables the multi-fluid approach to simulate a wider range of application conditions without resorting to ad hoc/empirical flow regime transitions.
Liquid fuels dominate the market for transportation and are also heavily involved in industrial applications and power generation. This is because of their high energy density, and ease of transportation. Unfortunately, most current liquid fuels are derived from petroleum and contribute to net greenhouse gas emissions when burned, along with the pollution caused by the extraction of petroleum in the first place. Biofuels are a possible solution that retains compatibility with most of today’s transportation and energy infrastructure, while significantly reducing the environmental impact. Generating cost-competitive biofuels will require significant development of biomass processing technologies, including optimizing the flow and transport.
The goal of this project is to develop CFD models for the various processes that occur in the the wet conversion of biomass in flow reactors. This is a collaborative project with Prof. Mike Timko at Worcester Polytechnic Institute on new CFD models to incorporate the effects of cellulose swelling during processing.
Gas turbines, whether for aerospace or power generation, field faces many of the same challenges as internal combustion engines. The push to reduce fuel consumption and pollutant emissions has prompted research into engines that operate closer to the limits of stability, or even radical new engine concepts like rotating detonation. Our lab is developing new models to accurately predict the performance of these new engines.