Session: Research Posters

Paper Number: 166626

Physics Based Gas Turbine Model for the Analysis of Low Carbon Fuels Aboard Ships 

There is a global shift trending toward low carbon fuels in transportation, with the International Maritime Organization mandating 50% emissions reduction by 2050. Aeroderivative gas turbines are highly valued aboard ships for their compact design, high energy density, and ability to rapidly adjust to the variable load characteristics of ship propellers at sea. Understanding the off-design performance of these turbines is essential for accurately assessing their operational efficiency and fuel flexibility in real-world conditions. However, widely used gas turbine modeling software, such as GasTurb14 and Numerical Propulsion System Simulation (NPSS), requires paid licenses and are primarily designed for aerospace and power generation applications, making them less accessible for marine propulsion studies.This study presents the development of a zero-dimensional system-level model built to analyze the impacts of alternative fuels on power output, fuel consumption, and emissions in an aero-derivative gas turbine engine aboard a naval ship. The model, developed in MATLAB and Python, incorporates publicly available characteristic maps for compressors and turbines, scaled to the GE LM2500 full load operating point using a genetic algorithm. Component efficiencies derived from these maps are used to predict the state points at each stage of the gas turbine, and turbine inlet temperatures are calculated using the open-source software Cantera to simulate the combustion process. The method previously used to predict off-design performance of a single turbine is validated with publicly available fuel speed relationship taken from an Arleigh Burke Class DDG. Performance and emissions of the engine are evaluated using standard F-76 marine diesel as a baseline and then compared to results obtained with methanol and hydrogen. With the appropriate hull resistance data, results of this model can accurately predict ship speed and fuel consumption across an operational range of 8–30 knots mode within 3.2% error. Error values increased under other modes of operation where less data was available for the power, RPM, and ship speed. The findings highlight the trade-offs between fuel energy density, efficiency, and emissions, offering insights into the feasibility of alternative fuels in naval applications. This model’s structure allows for further integration with chemical kinetic mechanisms and emissions modeling, providing a flexible platform for future alternative fuel assessments. The broader implications of this research extend beyond military applications, offering potential benefits for the marine transport sector—which accounts for 6% of global emissions—and other aeroderivative turbine applications in commercial cruise liners, offshore power generation, and mobile energy systems. By providing an open source, validated modeling framework, this work contributes to ongoing efforts in reducing emissions and optimizing fuel strategies in marine propulsion systems.

Presenting Author: Benedict Vergara George Washington University

Presenting Author Biography: Benedict Vergara received his B.S. and M.S. in Electrical Engineering at The George Washington University, both with Concentrations in Energy and Power Systems. Ben worked at the engineering consulting firm Strategic Analysis, Inc. as a staff engineer aiding the development of techno-economic analyses for clean energy technologies. Ben is currently a Ph.D. candidate in Electrical Engineering modeling energy systems to study the tradeoffs between cost, performance, and sustainability.​

Authors:

Tyler Wyka George Washington University
Indranil Brahma Bucknell University
Benedict Vergara George Washington University
Saniya Leblanc George Washington University