The Collaboration Effect: Developing a New Generation of Gas Turbine & Rotating Detonation Engines

Author:
Elizabeth Favreau
Marketing Writing Team Lead

From the Argonne National Laboratory + Convergent Science Blog Series

Imagine this: You’re flying on a plane. Maybe you’re sitting in the window seat, eating airline pretzels, happily watching an in-flight movie. But then—the flame in one of the plane’s gas turbine engines blows out. Should you panic? Well, ideally you wouldn’t even notice as the engine automatically relights and you continue cruising safely to your destination. But why did the engine blow out? Can we prevent that from happening? And if it does blow out, how can we ensure the plane stays airborne?

These are among the critical questions that Argonne National Laboratory and Convergent Science investigate together. If you’ve been following this series, you’ll know their collaboration started off focused on piston engines for automotive applications. But combustion engines across the board, including airplane engines, feature similar physical processes, and the research goals are frequently the same: increase efficiency and reduce emissions. In addition, CONVERGE’s unique combination of autonomous meshing, fully coupled detailed chemistry, and high-fidelity physical models for spray, turbulence, and combustion make it a great tool to help engine designers reach those goals. 

Before industry can implement 3D simulation into their design process, however, they need appropriate, well-validated models. This is where Argonne and Convergent Science come in—the core objective of their collaboration is performing fundamental research and developing models that industry can use to advance technology. In pursuit of this objective, Argonne and Convergent Science expanded their research efforts to aviation engines and beyond.

Gas Turbines

Gas turbine engines today are the most commonly used propulsion system for airplanes, and they are also widely used for power generation. Two key areas of current gas turbine research are increasing efficiency and reducing pollutant emissions. There are several approaches to achieving these goals, including the use of alternative fuels, altering the combustion environment (e.g., increasing operating pressures and temperatures), or reducing the fuel flow rate and moving toward a leaner combustion regime.

This lean burn approach, while effective at reducing emissions, poses significant design challenges. If you run the gas turbine engine too lean, the primary zone of the combustor can get too cold and the flame can blow out. This phenomenon, called lean blow-off or lean blow-out (LBO), is the reason the plane engine went out during our imaginary flight. Clearly, LBO is undesirable, and predicting the conditions at which it occurs is a primary focus for Argonne and Convergent Science, as well as for the broader gas turbine community.

LBO limits vary from fuel to fuel, and understanding these differences is critical, especially as alternative fuels become increasingly widespread. “The flame stabilization characteristics depend on the physical as well as the chemical properties of a given fuel, so our aim is to develop computational models that can predictively capture this behavior and the difference in performance between conventional and alternative fuels,” said Dr. Prithwish Kundu, Research Scientist at Argonne National Laboratory.

Using CONVERGE, Argonne and Convergent Science engineers investigated the LBO limits for two fuels: A-2 (a conventional Jet-A fuel) and C-1 (an alternative fuel)¹. They conducted large eddy simulations (LES) of a realistic aviation gas turbine combustor from the U.S. National Jet Fuels Combustion Program (NJFCP). The combustor geometry preserved all flow passages and included the dome, liners, dilution jets, and effusion cooling holes. A Lagrangian approach was used to model the spray and atomization of the liquid fuels, and detailed chemistry was used to simulate combustion.

Gas turbine simulations tend to be computationally intensive because of the large computational domain, complicated geometry featuring a wide range of length scales (e.g., from millimeter-sized holes to a meter-long combustor), and complex physical processes. Argonne and Convergent Science engineers leveraged CONVERGE’s autonomous meshing to speed up the simulation setup and runtime. Automatic mesh generation saved weeks of time on the simulation setup, and Adaptive Mesh Refinement (AMR) helped shape the optimal mesh for desired spatial resolution to capture the complicated physical phenomena while keeping the overall cell count relatively low. 

With this method, Argonne and Convergent Science were able to accurately predict the difference in LBO limits for A-2 and C-1 fuels (Figure 1). Original equipment manufacturers (OEMs) have long desired a tool capable of predicting LBO, and demonstrating that CONVERGE is able to identify these limits in a reasonable amount of time is a significant achievement.

Having validated CONVERGE’s ability to predict LBO for conventional and alternative fuels, Argonne and Convergent Science engineers are turning to high altitude relight, which is the key to keeping our planes in the air should LBO occur. High altitude relight happens under challenging conditions, i.e., very low temperature and pressure. The NJFCP is currently developing an experimental database for high altitude relight, which Argonne and Convergent Science plan to use to validate their CONVERGE simulations. Overall, these studies pave the way for creating cleaner gas turbine engines, while also ensuring the safety of air travel.

Rotating Detonation Engines

Improving traditional gas turbines is only one way to achieve high-efficiency, low-emissions engines for the aerospace and power generation industries.

“Emissions standards are regularly becoming more stringent, so gas turbines have to evolve accordingly,” said Dr. Gaurav Kumar, Principal Engineer at Convergent Science. “With stricter regulations, the technologies may need to be not just evolutionary, but revolutionary.”

Rotating detonation engines (RDEs) are one potentially revolutionary technology. RDE is an advanced engine concept that is both robust and scalable—you can run an RDE at a fairly wide range of fuel-air equivalence ratios, and you can produce both small and large engines from essentially the same design (Figure 2).

Compared to deflagrative combustion (which is typical in most gas turbine engines), detonative combustion offers a number of benefits, including a substantial increase in efficiency and decrease in emissions. Detonative combustion also provides greater thrust for the same amount of fuel, which is a significant advantage for propulsion applications, such as powering aircrafts and rockets. 

However, RDEs are still in the development phase, and there are certain challenges that have kept them from becoming widely adopted.

“First, maintaining a stable detonation wave is tricky, given that the mixing is highly complex and chaotic,” said Dr. Pinaki Pal, Research Scientist at Argonne. “Thermal management is another challenge, because RDEs have a high thermal load that is unequally distributed throughout the device due to the cyclic combustion wave. This behavior can fatigue the device and shorten its lifespan.”

In addition, an RDE is a difficult environment in which to take experimental measurements. Any instrument you use must be able to capture the high frequencies and large amplitude range of the RDE, while also surviving the harsh conditions inside the device. Moreover, many experimental tools provide averaged results, such as the average temperature or pressure at the device exit. These tools fail to capture the transient nature of an RDE as the detonation wave travels around the engine. Ultimately, new methods to analyze RDEs are needed.

CFD allows you to probe any point in time and space within your computational domain, so researchers can leverage simulations to better understand the chaotic, supersonic combustion in an RDE. To that end, Argonne and Convergent Science engineers simulated both hydrogen- and ethylene-fueled RDEs in CONVERGE using detailed chemistry, LES, and autonomous meshing^2,3.

Argonne and Convergent Science engineers quantified several key characteristics of the detonation wave, including wave height and frequency, for the hydrogen- and ethylene-fueled RDEs. The results are shown in Tables 1 and 2, respectively. For both cases, CONVERGE accurately captures the key RDE parameters compared with experimental data from the U.S. Air Force Research Laboratory.

“With CONVERGE, we’re able to get good quality combustion results with about 10–15 million cells, when other codes were using 90 million cells or more,” said Scott Drennan, Director of Gas Turbine and Aftertreatment Applications at Convergent Science. “And one of the key ways we’re able to do that is through Adaptive Mesh Refinement, which allows us to track the detonation wave by refining the mesh when and where it’s needed at every time step.”

Argonne and Convergent Science also employed a computational diagnostic tool called chemical explosive mode analysis (CEMA) to better understand the local combustion regime. This technique had previously been applied to diesel and scramjet engines, but this was the first time it was implemented for an RDE. Based on an eigenanalysis of the local chemical Jacobian, CEMA is able to identify local combustion modes, such as auto-ignition, deflagrative fronts, and local extinction.

“We demonstrated that CEMA is able to accurately capture the local combustion behavior within an RDE,” said Dr. Pal. “What we would like to do next is develop an on-the-fly dynamic adaptive modeling technique to prescribe regime-dependent combustion models based on the local combustion regime identified by CEMA, which would drastically reduce the computational cost and enhance the accuracy of a CFD simulation.”

In addition to further CEMA studies, there are several other areas of research that Argonne and Convergent Science plan to pursue. One project currently underway is extending the modeling approach used for the studies described above to rocket RDEs. Up to this point, Argonne and Convergent Science have simulated air-breathing RDEs. Now, they are investigating a methane-fueled rocket RDE that uses oxygen instead of air as the oxidizer. Another upcoming project is to simulate the combustor coupled with the turbine in order to evaluate the overall performance of the system. These predictive CFD models will enable engineers to gain more insight into the combustion phenomena in an RDE and to develop design strategies that can help propel the technology into the mainstream.

Jet-in-Crossflow

As Argonne and Convergent Science work to achieve more predictive engine simulations, one area that holds significant potential for improvement is spray modeling. One of the simplest questions we can ask is, “Where does the fuel go?” The trajectory of the spray impacts all of the downstream processes in a combustor: fuel-air mixing, ignition, combustion, emissions, and thrust. But actually determining where the fuel goes is anything but simple.

“It’s a beautifully complex problem,” said Dr. Gina Magnotti, Research Scientist at Argonne National Laboratory. “The spray is sensitive to the local operating conditions, the injector geometry, the fuel properties—and we don’t necessarily have a full grasp on all of the salient physics that control the fuel spray atomization. What happens in the first few millimeters from the injector or atomizer exit has great consequences for the fuel-air mixing and the dispersion of the spray.”

Both gas turbines and RDEs feature jet-in-crossflow type mixing, so Dr. Magnotti and her colleagues conducted a CFD study to better understand this process⁴. They synthetically imposed realistic surface roughness inside the injector geometry. For their CONVERGE simulations, they coupled LES with a volume of fluid (VOF) approach to understand how the initial flow development impacts the spray formation process. The results were compared to experimental measurements taken at Argonne’s Advanced Photon Source (APS). Ultimately, they found that imposing realistic surface roughness affects crosswise stretching of the jet and distribution of liquid mass, as shown in Figure 3.

This study demonstrated that there is still much to learn about the fuel injection process, and Argonne and Convergent Science plan to continue research in this area. A better understanding of the link between internal injector flow and spray formation will provide more accurate boundary conditions for gas turbine and RDE simulations, which will improve their predictive capability. 

Fearless Engineering

The overarching goal of all these projects is to develop predictive computational models that industry can use to design revolutionary technology. The collaboration between Argonne and Convergent Science enables the fundamental research necessary to develop these models and provides a path for the models to get into the hands of industry. Working with Argonne also helps Convergent Science extend CONVERGE’s capabilities to new application areas and enables cutting-edge research in new, exciting fields. As Dr. Dan Lee, Co-Owner and Vice President of Convergent Science, puts it:

It’s a privilege to work with organizations like Argonne. One of the greatest ways to learn about new applications or expand your value proposition in new applications is to partner with people who already have experience in that area. When we partner with Argonne, we’re dealing with experts in a wide variety of applications. And what’s more is that any new area we want to go into, even if Argonne doesn’t currently have expertise in that particular area, they’re used to going into new research areas—they’re fearless. And that’s a great combination: talented, experienced, fearless.

Pushing fearlessly into these new research areas—aerospace, power generation, and more—allows for a greater impact on society, helping to bring about a cleaner and safer world.

In case you missed the other posts in this series, you can find them here:

• Part 1: The Collaboration Effect: A Decade of Innovation
• Part 2: The Collaboration Effect: Advancing Engines Through Simulation & Experimentation
• Part 4: The Collaboration Effect: Optimizing Drones for Future Missions

References

[1] Hasti, V.R., Kundu, P., Kumar, G., Drennan, S.A., Sibendu, S., Won, S.H., Dryer, F.L., and Gore, J.P., “Lean Blow-Out (LBO) Computations in a Gas Turbine Combustor,” 2018 AIAA/SAE/ASEE Joint Propulsion Conference, AIAA 2018-4958, Cincinnati, OH, United States, Jul 9–11, 2018. DOI: 10.2514/6.2018-4958

[2] Pal, P., Xu, C., Kumar, G., Drennan, S.A., Rankin, B.A., and Som, S., “Large-Eddy Simulation and Chemical Explosive Mode Analysis of Non-Ideal Combustion in a Non-Premixed Rotating Detonation Engine,” AIAA SciTech 2020 Forum, AIAA 2020-2161, Orlando, FL, United States, Jan 6–10, 2020. DOI: 10.2514/6.2020-2161

[3] Pal, P., Xu, C., Kumar, G., Drennan, S.A., Rankin, B.A., and Som, S., “Large-Eddy Simulations and Mode Analysis of Ethylene/Air Combustion in a Non-Premixed Rotating Detonation Engine,” AIAA Propulsion and Energy 2020 Forum, AIAA 2020-3876, Online, Aug 24–28, 2020. DOI: 10.2514/6.2020-3876

[4] Magnotti, G.M., Lin, K.-C., Carter, C.D., Kastengren, A., and Som, S., “A Computational Investigation of the Effect of Surface Roughness on the Development of a Liquid Jet in Subsonic Crossflow,” AIAA Propulsion and Energy 2020 Forum, AIAA 2020-3880, Online, Aug 24–28, 2020. DOI: 10.2514/6.2020-3880