The mission of the Engine Combustion Research group is to develop the science-based understanding needed by industry to design the next generation of advanced internal-combustion engines that use both conventional and alternative fuels. We develop a detailed, pre-competitive understanding of the dominant in-cylinder processes, providing guidance to engine designers who can subsequently develop proprietary hardware designs and operating strategies that will support more efficient, cleaner engines.

Our work is motivated by the need to improve combustion engines during the nation’s transition to low-carbon options, thus ensuring the most effective use of both petroleum-derived fuels and renewable, low-carbon alternative fuels.

Advanced optical diagnostics and high-fidelity simulation supply data that accelerate  in-depth understanding of the complex physicochemical processes controlling combustion.

We have been working closely with U.S. engine manufacturers for more than 30 years to increase scientific understanding of internal combustion engine processes affecting efficiency and emissions. Our work focuses on several combustion strategies needed for improved engines, including

  • Ultra-low-emission, low-temperature combustion
  • Stratified-charge, spark-ignition combustion
  • Advanced diesel combustion approaches

We also study alternative fuels with properties that may enable higher engine efficiencies or speed the adoption of these advanced engine strategies.

Target vehicles include passenger cars, SUVs, light-to-medium duty trucks, and heavy-duty transport vehicles. We use experimental hardware appropriate to each of these market segments, and apply advanced, laser-based diagnostics to investigate the in-cylinder combustion processes under realistic engine geometries and operating conditions.

Additionally, we help industry to develop advanced engine design tools to enable numerical design and optimization. Advancing the accuracy of industry tools results in both better designs and reduced time to market—a crucial aspect of reducing CO2 emissions in support of U.S. climate goals. To this end, we work closely with both university modeling teams and commercial software suppliers.

Cleaner, more effcient engines


Our engine combustion research program is sponsored by the Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy (EERE), together with several industry partners. We conduct cooperative research with the U.S. automotive and heavy-duty diesel engine industries, energy companies, and other national laboratories under an Advanced Engine Combustion Memorandum of Understanding (MOU) led by Sandia. Leading engine research universities also participate closely in this collaboration. Sandia’s research and development efforts benefit from interactions with other CRF researchers sponsored by DOE’s Office of Science Basic Energy Sciences (BES) research program.


Research hardware includes several optically accessible, single-cylinder engines with production or prototypical engine heads and optically accessible combustion vessels capable of simulating an extremely wide range of engine thermodynamic conditions. Optical access in the engines is provided by quartz pistons, quartz cylinder liners, windowed spacers, and/or replacement of exhaust valves with periscope optical assemblies. Researchers also develop and adapt or improve existing optical diagnostic techniques to study the desired in-cylinder processes.

In addition, we use ultra-high-fidelity, computer simulation tools incorporating full physics and chemistry for near-first-principles simulation of engine combustion processes. Simulation results—in time and length scales too small to be measured accurately—provide both physical insight and numerical data with which we can improve the engineering CFD models used by engine designers. Performing these computations requires a range of resources from local, dedicated mid-scale high-performance computer clusters to Sandia’s corporate-supported high-performance computer clusters and DOE’s Leadership Class supercomputers.