Reduced Kinetics Model Generation for Gas Turbine CFD
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Solution Overview
Problem
Current computational fluid dynamics (CFD) simulations face challenges in accurately modeling combustion processes in gas turbines due to the complexity of combustion kinetics and the computational inefficiency of detailed kinetics models, which are too large to implement effectively, especially in predicting transient phenomena like ignition and extinction under varying operating conditions.
Innovation Solution
Development of a software package, rkmGen, that generates compact reduced kinetics models through optimization against ignition delay time, laminar flame speed, and emissions data, using a lumped-parameterization based optimization scheme and Simulated Annealing algorithm, to improve computational efficiency and accuracy in CFD simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed kinetics models are used for combustion simulation, then prediction accuracy is improved, but computational efficiency deteriorates
Solution Approach 1:
The detailed kinetics model is segmented into two parts: a reduced kinetics model with a small number of species and reactions for computationally efficient simulation, and a detailed kinetics model used only for generating target data and validation. This segmentation allows the majority of simulations to use the efficient reduced model while still leveraging the accuracy of the detailed model for critical comparisons.
Solution Approach 2:
A reduced kinetics model (copy) is created that replicates the essential combustion behavior of the detailed kinetics model. The reduced model contains only the most important species and reactions, making it computationally efficient while maintaining sufficient accuracy for practical simulations. The copy is validated against the detailed model's predictions to ensure fidelity.
2Measurement precision
If detailed kinetics models are used for combustion simulation, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The essential combustion chemistry is extracted from the complex detailed kinetics model to create a simplified reduced kinetics model. Only the most critical species and reactions that govern combustion behavior are retained, while less important components are removed. This extraction process reduces model complexity while preserving the essential physics needed for accurate predictions.
Solution Approach 2:
The reduced kinetics model applies local quality by focusing computational resources on the most important chemical species and reactions that locally dominate the combustion process. Rather than uniformly treating all species and reactions with equal detail, the model concentrates on the critical few that have the greatest impact on combustion behavior, thereby reducing overall complexity while maintaining accuracy where it matters most.
Data Source
AI summary
A method for implementing a modeling tool that generates optimized reduced kinetic models for given operating conditions and a numerical scheme to speed-up kinetic evaluation of turbulent-chemistry coupling during CFD simulations. The tool is capable of predicting ignition and flameholding phenomenon for most propulsion systems, including gas turbine applications. A lumped-parameterization based optimization scheme may generate multi-step quasi-global kinetic models using laminar flame speed as the target data. This scheme may be further extended to include optimization of emission predictions such as CO and NOx.