| A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model | |
Huo ZJ(霍志杰); Cleary, Matthew J J; Wu K(吴坤); Masri, Assaad R R; Fan XJ(范学军)
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| Corresponding Author | Wu, Kun([email protected]) |
| Source Publication | COMBUSTION THEORY AND MODELLING
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| 2023-01-18 | |
| Pages | 29 |
| ISSN | 1364-7830 |
| Abstract | Due to the composition-dependent stiffness of chemistry, simulations of reactive turbulent flows may present computational load imbalance among parallel processes when spatial decomposition is used for parallelisation, causing high CPU idle time and waste of computational resources. To increase computational efficiency, a dynamic load balancing (DLB) model is proposed to redistribute computational load among computing cores. The DLB model exploits a decomposition in the mixture fraction space with two dynamic adjusting decomposition strategies to realise load redistribution. The DLB model is suitable for the integration of chemistry on stochastic particles in hybrid Eulerian/Lagrangian turbulent combustion models in which the Eulerian field is conventionally decomposed statically in physical space in a way that balances the computational load for the solution of the Navier-Stokes equation but which does not generally lead to balanced load for the computation of the composition fields. Here it is tested using an OpenFOAM-based platform, mmcFoam, which is a comprehensive object-orientated C++ library for stochastic turbulent combustion modelling. Apart from direct integration (DI) for chemistry, the DLB model is also coupled with dynamic adaptive chemistry (DAC) and in situ adaptive tabulation (ISAT), which allows for extra speedup. The performance of the coupled models is validated and assessed for two laboratory flame conditions that exhibit different levels of computational load imbalance. Overall, the DLB model effectively balances the computational load distribution and increases the effective usage of computing power, shortening the simulation wall time required. Moreover, a strong scaling test is carried out using up to 512 cores. Although all approaches have sub-ideal scalability, the scalability of each with DLB is significantly better than without DLB. While DLB-ISAT has relatively poor scalability compared to the DI- and DAC-based methods, DLB-ISAT still ranks the fastest among the algorithms in all scaling trials. |
| Keyword | dynamic load balancing DAC ISAT turbulent combustion MMC-LES |
| DOI | 10.1080/13647830.2023.2165967 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000913612900001 |
| WOS Keyword | LARGE-EDDY SIMULATION ; MMC-LES ; DENSITY-FUNCTION ; FLAMES ; NUCLEATION |
| WOS Research Area | Thermodynamics ; Energy & Fuels ; Engineering ; Mathematics |
| WOS Subject | Thermodynamics ; Energy & Fuels ; Engineering, Chemical ; Mathematics, Interdisciplinary Applications |
| Funding Project | National Key Project[GJXM92579] ; Australian Research Council[DP180104190] |
| Funding Organization | National Key Project ; Australian Research Council |
| Classification | Q3 |
| Ranking | 1 |
| Contributor | Wu, Kun |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/91585 |
| Collection | 高温气体动力学国家重点实验室 |
| Recommended Citation GB/T 7714 | Huo ZJ,Cleary, Matthew J J,Wu K,et al. A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model[J]. COMBUSTION THEORY AND MODELLING,2023:29.Rp_Au:Wu, Kun |
| APA | 霍志杰,Cleary, Matthew J J,吴坤,Masri, Assaad R R,&范学军.(2023).A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model.COMBUSTION THEORY AND MODELLING,29. |
| MLA | 霍志杰,et al."A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model".COMBUSTION THEORY AND MODELLING (2023):29. |
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| Jp2023Fa317.pdf（2253KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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