This collection contains a hierarchy of test problems for turbulent reacting flow simulations. It is meant to provide a testbed to build reduced model for relevant challenging reacting flow problems using different methods. In addition, this collection also serves to engage a broad community of experts in computational science and the field of engineering to address certain challenges in constructing reduced models for reacting flow simulations. All the datasets in this collection were generated under the Air Force Center of Excellence on Multi-Fidelity Modeling of Rocket Combustion Dynamics and the goal of the center is to advance the state-of-the-art in Reduced Order Models (ROMs) and enable efficient and accurate prediction of instabilities in liquid fueled rocket combustion systems.
A 2D planar representation of a generic laboratory-scale combustor is established to assess the capabilities of ROMs for representing realistic combustion flowfields. The purpose of this dataset is to provide a testbed to build reduced model for relevant challenging reacting flow problems using different methods. The dataset was generated under the Air Force Center of Excellence on Multi-Fidelity Modeling of Rocket Combustion Dynamics and the goal of the center is to advance the state-of-the-art in Reduced Order Models (ROMs) and enable efficient prediction of instabilities in liquid fueled rocket combustion systems., Detailed documentation of how the data is generated can be found in: https://afcoe.engin.umich.edu/benchmark-data. Instrument and/or Software specifications: - recommendation: Matlab and Tecplot. , 1. Data_150000to159999.tar: the unsteady flow field data from time step 150000 to 159999 (time increment, dt, between each time step is 1E-7 sec). 2. Data_160000to169999.tar: the unsteady flow field data from time step 160000 to 169999 (time increment, dt, between each time step is 1E-7 sec). , 3. Data_170000to179999.tar: the unsteady flow field data from time step 170000 to 179999 (time increment, dt, between each time step is 1E-7 sec). 4. Data_180000to189999.tar: the unsteady flow field data from time step 180000 to 189999 (time increment, dt, between each time step is 1E-7 sec)., 5. Data_190000to199999.tar: the unsteady flow field data from time step 190000 to 199999 (time increment, dt, between each time step is 1E-7 sec). 6. Data_200000to209999.tar: the unsteady flow field data from time step 200000 to 209999 (time increment, dt, between each time step is 1E-7 sec). , 7. Data_210000to219999.tar: the unsteady flow field data from time step 210000 to 219999 (time increment, dt, between each time step is 1E-7 sec). 8. Data_220000to229999.tar: the unsteady flow field data from time step 220000 to 229999 (time increment, dt, between each time step is 1E-7 sec). , and 9. grid.dat: the topology of the CFD mesh used to generate this data (can be directly loaded in Tecplot). 10. the file "sample_code.zip" contains the sample Matlab scripts to load and output the .dat files to help the researchers to get started. To run the script, the software Matlab is required and the researchers can simply run sampleIO.m script in Matlab to test the code.
Citation to related publication:
McQuarrie, S., Huang, C., and Willcox, K., Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process, Journal of the Royal Society of New Zealand, 2021. (code available: https://github.com/Willcox-Research-Group/ROM-OpInf-Combustion-2D)., McQuarrie, S. A., Huang, C., & Willcox, K. E. (2021). Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process. Journal of the Royal Society of New Zealand, 51(2), 194–211. https://doi.org/10.1080/03036758.2020.1863237 , Swischuk, R., Kramer, B., Huang, C., & Willcox, K. (2020). Learning Physics-Based Reduced-Order Models for a Single-Injector Combustion Process. AIAA Journal, 58(6), 2658–2672. https://doi.org/10.2514/1.J058943, Huang, C., Duraisamy, K., & Merkle, C. L. (2019). Investigations and Improvement of Robustness of Reduced-Order Models of Reacting Flow. AIAA Journal, 57(12), 5377–5389. https://doi.org/10.2514/1.J058392 , and Harvazinski, M. E., Huang, C., Sankaran, V., Feldman, T. W., Anderson, W. E., Merkle, C. L., & Talley, D. G. (2015). Coupling between hydrodynamics, acoustics, and heat release in a self-excited unstable combustor. Physics of Fluids, 27(4), 045102. https://doi.org/10.1063/1.4916673
A 2D planar representation of a generic laboratory-scale combustor is established to assess the capabilities of ROMs for representing realistic combustion flowfields. The purpose of this dataset is to provide a testbed to build reduced model for relevant challenging reacting flow problems using different methods. The dataset was generated under the Air Force Center of Excellence on Multi-Fidelity Modeling of Rocket Combustion Dynamics and the goal of the center is to advance the state-of-the-art in Reduced Order Models (ROMs) and enable efficient prediction of instabilities in liquid fueled rocket combustion systems., Instrument and/or Software specifications: - recommendation: Matlab and Tecplot, 1. Data_150000to159999.tar: the unsteady flow field data from time step 150000 to 159999 (time increment, dt, between each time step is 1E-7 sec). - Data_160000to169999.tar: the unsteady flow field data from time step 160000 to 169999 (time increment, dt, between each time step is 1E-7 sec).
2. Data_170000to179999.tar: the unsteady flow field data from time step 170000 to 179999 (time increment, dt, between each time step is 1E-7 sec).
3. grid.dat: the topology of the CFD mesh used to generate this data (can be directly loaded in Tecplot).
4. the file "sample_code.zip" contains the sample Matlab scripts to load and output the .dat files to help the researchers to get started. To run the script, the software Matlab is required and the researchers can simply run sampleIO.m script in Matlab to test the code.
, and Detailed documentation of how the data is generated can be found in: https://afcoe.engin.umich.edu/benchmark-data
Citation to related publication:
Huang, C., Duraisamy, K., and Merkle, C.L., Investigations and Improvement of Robustness of Reduced-Order Models of Reacting Flow, AIAA Journal, 2019., Swischuk, R., Kramer, B., Huang, C., and Willcox, K., Learning Physics-Based Reduced-Order Models for a Single-Injector Combustion Process , AIAA Journal, 2020., and Harvazinski, M.E., Huang, C., Sankaran, V., Feldman, T.W., Anderson, W.E., Merkle, C.L., and Talley, D.G., Coupling between hydrodynamics, acoustics, and heat release in a self-excited unstable combustor, Physics of Fluids, 2015.