Numerical simulations of turbulent reacting flows with finite-rate chemistry and combustion-model adaptation
Abstract/Contents
- Abstract
- The utilization of finite-rate chemistry with realistic chemical kinetics in large-eddy simulations (LES) of turbulent reacting flows has attracted increasing interest in recent years. It enables further improvement in the prediction of emissions in the combustion process and helps eliminate the restriction often imposed by regime-specific combustion models. However, the cost of such approaches remains a great concern despite the continuing growth of computational capacity, as they are often orders-of-magnitude more expensive than the regime-specific flamelet-type models. In this study, the framework of Pareto-efficient combustion (PEC) modeling is developed, which allows the adaptive utilization of multiple combustion models under consideration of cost-fidelity characteristics for efficient simulations of complex turbulent flames. This adaptive approach provides a general combustion modeling capability with an adjustable level of fidelity and complexity. Based on the user-specific inputs on quantities of interest, desired simulation accuracy and computational cost, the PEC framework makes adaptive model assignments restricting the application of sub-models within their intended use. For complex problems, the proposed framework allows the usage of detailed description of the combustion chemistry in limited regions where it is necessary, while avoiding the concomitant overhead in regions where flamelet-type models are deemed sufficient. Efficient computational strategies are developed to accelerate large-scale parallel simulations with stiff finite-rate chemistry, including time stepping methods and load rebalancing techniques. The combined approach is applied to LES of turbulent flames, demonstrating its capability in improving the predictability and cost-effectiveness of turbulent combustion simulations.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Wu, Hao |
|---|---|
| Associated with | Stanford University, Department of Mechanical Engineering. |
| Primary advisor | Ihme, Matthias |
| Thesis advisor | Ihme, Matthias |
| Thesis advisor | Moin, Parviz |
| Thesis advisor | Wang, Hai, 1962- |
| Advisor | Moin, Parviz |
| Advisor | Wang, Hai, 1962- |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Hao Wu. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Hao Wu
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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